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Sample records for based multi-scale image

  1. Multi-scale classification based lesion segmentation for dermoscopic images.

    PubMed

    Abedini, Mani; Codella, Noel; Chakravorty, Rajib; Garnavi, Rahil; Gutman, David; Helba, Brian; Smith, John R

    2016-08-01

    This paper presents a robust segmentation method based on multi-scale classification to identify the lesion boundary in dermoscopic images. Our proposed method leverages a collection of classifiers which are trained at various resolutions to categorize each pixel as "lesion" or "surrounding skin". In detection phase, trained classifiers are applied on new images. The classifier outputs are fused at pixel level to build probability maps which represent lesion saliency maps. In the next step, Otsu thresholding is applied to convert the saliency maps to binary masks, which determine the border of the lesions. We compared our proposed method with existing lesion segmentation methods proposed in the literature using two dermoscopy data sets (International Skin Imaging Collaboration and Pedro Hispano Hospital) which demonstrates the superiority of our method with Dice Coefficient of 0.91 and accuracy of 94%.

  2. Proximity graphs based multi-scale image segmentation

    SciTech Connect

    Skurikhin, Alexei N

    2008-01-01

    We present a novel multi-scale image segmentation approach based on irregular triangular and polygonal tessellations produced by proximity graphs. Our approach consists of two separate stages: polygonal seeds generation followed by an iterative bottom-up polygon agglomeration into larger chunks. We employ constrained Delaunay triangulation combined with the principles known from the visual perception to extract an initial ,irregular polygonal tessellation of the image. These initial polygons are built upon a triangular mesh composed of irregular sized triangles and their shapes are ad'apted to the image content. We then represent the image as a graph with vertices corresponding to the polygons and edges reflecting polygon relations. The segmentation problem is then formulated as Minimum Spanning Tree extraction. We build a successive fine-to-coarse hierarchy of irregular polygonal grids by an iterative graph contraction constructing Minimum Spanning Tree. The contraction uses local information and merges the polygons bottom-up based on local region-and edge-based characteristics.

  3. Remote sensing image classification based on support vector machine with the multi-scale segmentation

    NASA Astrophysics Data System (ADS)

    Bao, Wenxing; Feng, Wei; Ma, Ruishi

    2015-12-01

    In this paper, we proposed a new classification method based on support vector machine (SVM) combined with multi-scale segmentation. The proposed method obtains satisfactory segmentation results which are based on both the spectral characteristics and the shape parameters of segments. SVM method is used to label all these regions after multiscale segmentation. It can effectively improve the classification results. Firstly, the homogeneity of the object spectra, texture and shape are calculated from the input image. Secondly, multi-scale segmentation method is applied to the RS image. Combining graph theory based optimization with the multi-scale image segmentations, the resulting segments are merged regarding the heterogeneity criteria. Finally, based on the segmentation result, the model of SVM combined with spectrum texture classification is constructed and applied. The results show that the proposed method can effectively improve the remote sensing image classification accuracy and classification efficiency.

  4. Medical image classification based on multi-scale non-negative sparse coding.

    PubMed

    Zhang, Ruijie; Shen, Jian; Wei, Fushan; Li, Xiong; Sangaiah, Arun Kumar

    2017-05-27

    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.

  5. Multi-scale retinex with color restoration image enhancement based on Gaussian filtering and guided filtering

    NASA Astrophysics Data System (ADS)

    Ma, Jinxiang; Fan, Xinnan; Ni, Jianjun; Zhu, Xifang; Xiong, Chao

    2017-07-01

    In order to restore image color and enhance contrast of remote sensing image without suffering from color cast and insufficient detail enhancement, a novel improved multi-scale retinex with color restoration (MSRCR) image enhancement algorithm based on Gaussian filtering and guided filtering was proposed in this paper. Firstly, multi-scale Gaussian filtering functions were used to deal with the original image to obtain the rough illumination components. Secondly, accurate illumination components were acquired by using the guided filtering functions. Then, combining with four-direction Sobel edge detector, a self-adaptive weight selection nonlinear image enhancement was carried out. Finally, a series of evaluate metrics such as mean, MSE, PSNR, contrast and information entropy were used to assess the enhancement algorithm. The results showed that the proposed algorithm can suppress effectively noise interference, enhance the image quality and restore image color effectively.

  6. Multi-scale learning based segmentation of glands in digital colonrectal pathology images

    NASA Astrophysics Data System (ADS)

    Gao, Yi; Liu, William; Arjun, Shipra; Zhu, Liangjia; Ratner, Vadim; Kurc, Tahsin; Saltz, Joel; Tannenbaum, Allen

    2016-03-01

    Digital histopathological images provide detailed spatial information of the tissue at micrometer resolution. Among the available contents in the pathology images, meso-scale information, such as the gland morphology, texture, and distribution, are useful diagnostic features. In this work, focusing on the colon-rectal cancer tissue samples, we propose a multi-scale learning based segmentation scheme for the glands in the colon-rectal digital pathology slides. The algorithm learns the gland and non-gland textures from a set of training images in various scales through a sparse dictionary representation. After the learning step, the dictionaries are used collectively to perform the classification and segmentation for the new image.

  7. A novel multi-scale Hessian based spot enhancement filter for two dimensional gel electrophoresis images.

    PubMed

    Shamekhi, Sina; Miran Baygi, Mohammad Hossein; Azarian, Bahareh; Gooya, Ali

    2015-11-01

    Two dimensional gel electrophoresis (2DGE) is a useful method for studying proteins in a wide variety of applications including identifying post-translation modification (PTM), biomarker discovery, and protein purification. Computerized segmentation and detection of the proteins are the two main processes that are carried out on the scanned image of the gel. Due to the complexities of 2DGE images and the presence of artifacts, the segmentation and detection of protein spots in these images are non-trivial, and involve supervised and time consuming processes. This paper introduces a new spot filter for enhancing, and separating the closely overlapping spots of protein in 2DGE images based on the multi-scale eigenvalue analysis of the image Hessian. Using a Gaussian spot model, we have derived closed form equations to compute the eigen components of the image Hessian of two overlapping spots in a multi-scale fashion. Based on this analysis, we have proposed a novel filter that suppresses the overlapping area and results in a better spot separation. The performance of the proposed filter has been evaluated on the synthetic and real 2DGE images. The comparison with three conventional techniques and a commercial software package reveals the superiority and effectiveness of the proposed filter.

  8. 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.

  9. Multi-scale learning based segmentation of glands in digital colonrectal pathology images

    PubMed Central

    Gao, Yi; Liu, William; Arjun, Shipra; Zhu, Liangjia; Ratner, Vadim; Kurc, Tahsin; Saltz, Joel; Tannenbaum, Allen

    2016-01-01

    Digital histopathological images provide detailed spatial information of the tissue at micrometer resolution. Among the available contents in the pathology images, meso-scale information, such as the gland morphology, texture, and distribution, are useful diagnostic features. In this work, focusing on the colon-rectal cancer tissue samples, we propose a multi-scale learning based segmentation scheme for the glands in the colon-rectal digital pathology slides. The algorithm learns the gland and non-gland textures from a set of training images in various scales through a sparse dictionary representation. After the learning step, the dictionaries are used collectively to perform the classification and segmentation for the new image. PMID:27818565

  10. An improved infrared image enhancement algorithm based on multi-scale decomposition

    NASA Astrophysics Data System (ADS)

    Zhang, Honghui; Luo, Haibo; Yu, Xin-rong; Ding, Qing-hai

    2014-11-01

    Due to the restriction of infrared imaging component and the radiation of atmosphere, infrared images are discontented with image contrast, blurry, large yawp. Aimed on these problems, a multi-scale image enhancement algorithm is proposed. The main principle is as follows: firstly, On the basis of the multi-scale image decomposition, We use an edge-preserving spatial filter that instead of the Gaussion filter proposed in the original version, adjust the scale-dependent factor With a weighted information. Secondly, contrast is equalized by applying nonlinear amplification. Thirdly, subband image is the weighted sum of sampled subband image and subsampled then upsampled subband image by a factor of two. Finally, Image reconstruction was applied. Experiment results show that the proposed method can enhance the original infrared image effectively and improve the contrast, moreover, it also can reserve the details and edges of the image well.

  11. Tone mapping infrared images using conditional filtering-based multi-scale retinex

    NASA Astrophysics Data System (ADS)

    Luo, Haibo; Xu, Lingyun; Hui, Bin; Chang, Zheng

    2015-10-01

    Tone mapping can be used to compress the dynamic range of the image data such that it can be fitted within the range of the reproduction media and human vision. The original infrared images that captured with infrared focal plane arrays (IFPA) are high dynamic images, so tone mapping infrared images is an important component in the infrared imaging systems, and it has become an active topic in recent years. In this paper, we present a tone mapping framework using multi-scale retinex. Firstly, a Conditional Gaussian Filter (CGF) was designed to suppress "halo" effect. Secondly, original infrared image is decomposed into a set of images that represent the mean of the image at different spatial resolutions by applying CGF of different scale. And then, a set of images that represent the multi-scale details of original image is produced by dividing the original image pointwise by the decomposed image. Thirdly, the final detail image is reconstructed by weighted sum of the multi-scale detail images together. Finally, histogram scaling and clipping is adopted to remove outliers and scale the detail image, 0.1% of the pixels are clipped at both extremities of the histogram. Experimental results show that the proposed algorithm efficiently increases the local contrast while preventing "halo" effect and provides a good rendition of visual effect.

  12. 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

  13. Multi-scale Gaussian representation and outline-learning based cell image segmentation

    PubMed Central

    2013-01-01

    Background High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. Methods We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. Results and conclusions We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks. PMID:24267488

  14. Image-based multi-scale simulation and experimental validation of thermal conductivity of lanthanum zirconate

    SciTech Connect

    Guo, Xingye; Hu, Bin; Wei, Changdong; Sun, Jiangang; Jung, Yeon-Gil; Li, Li; Knapp, James; Zhang, Jing

    2016-09-01

    Lanthanum zirconate (La2Zr2O7) is a promising candidate material for thermal barrier coating (TBC) applications due to its low thermal conductivity and high-temperature phase stability. In this work, a novel image-based multi-scale simulation framework combining molecular dynamics (MD) and finite element (FE) calculations is proposed to study the thermal conductivity of La2Zr2O7 coatings. Since there is no experimental data of single crystal La2Zr2O7 thermal conductivity, a reverse non-equilibrium molecular dynamics (reverse NEMD) approach is first employed to compute the temperature-dependent thermal conductivity of single crystal La2Zr2O7. The single crystal data is then passed to a FE model which takes into account of realistic thermal barrier coating microstructures. The predicted thermal conductivities from the FE model are in good agreement with experimental validations using both flash laser technique and pulsed thermal imaging-multilayer analysis. The framework proposed in this work provides a powerful tool for future design of advanced coating systems. (C) 2016 Elsevier Ltd. All rights reserved.

  15. a Detection Method of Artificial Area from High Resolution Remote Sensing Images Based on Multi Scale and Multi Feature Fusion

    NASA Astrophysics Data System (ADS)

    Li, P.; Hu, X.; Hu, Y.; Ding, Y.; Wang, L.; Li, L.

    2017-05-01

    In order to solve the problem of automatic detection of artificial objects in high resolution remote sensing images, a method for detection of artificial areas in high resolution remote sensing images based on multi-scale and multi feature fusion is proposed. Firstly, the geometric features such as corner, straight line and right angle are extracted from the original resolution, and the pseudo corner points, pseudo linear features and pseudo orthogonal angles are filtered out by the self-constraint and mutual restraint between them. Then the radiation intensity map of the image with high geometric characteristics is obtained by the linear inverse distance weighted method. Secondly, the original image is reduced to multiple scales and the visual saliency image of each scale is obtained by adaptive weighting of the orthogonal saliency, the local brightness and contrast which are calculated at the corresponding scale. Then the final visual saliency image is obtained by fusing all scales' visual saliency images. Thirdly, the visual saliency images of artificial areas based on multi scales and multi features are obtained by fusing the geometric feature energy intensity map and visual saliency image obtained in previous decision level. Finally, the artificial areas can be segmented based on the method called OTSU. Experiments show that the method in this paper not only can detect large artificial areas such as urban city, residential district, but also detect the single family house in the countryside correctly. The detection rate of artificial areas reached 92 %.

  16. Multi-scale Adaptive Computational Ghost Imaging

    PubMed Central

    Sun, Shuai; Liu, Wei-Tao; Lin, Hui-Zu; Zhang, Er-Feng; Liu, Ji-Ying; Li, Quan; Chen, Ping-Xing

    2016-01-01

    In some cases of imaging, wide spatial range and high spatial resolution are both required, which requests high performance of detection devices and huge resource consumption for data processing. We propose and demonstrate a multi-scale adaptive imaging method based on the idea of computational ghost imaging, which can obtain a rough outline of the whole scene with a wide range then accordingly find out the interested parts and achieve high-resolution details of those parts, by controlling the field of view and the transverse coherence width of the pseudo-thermal field illuminated on the scene with a spatial light modulator. Compared to typical ghost imaging, the resource consumption can be dramatically reduced using our scheme. PMID:27841339

  17. Multi-scale Adaptive Computational Ghost Imaging

    NASA Astrophysics Data System (ADS)

    Sun, Shuai; Liu, Wei-Tao; Lin, Hui-Zu; Zhang, Er-Feng; Liu, Ji-Ying; Li, Quan; Chen, Ping-Xing

    2016-11-01

    In some cases of imaging, wide spatial range and high spatial resolution are both required, which requests high performance of detection devices and huge resource consumption for data processing. We propose and demonstrate a multi-scale adaptive imaging method based on the idea of computational ghost imaging, which can obtain a rough outline of the whole scene with a wide range then accordingly find out the interested parts and achieve high-resolution details of those parts, by controlling the field of view and the transverse coherence width of the pseudo-thermal field illuminated on the scene with a spatial light modulator. Compared to typical ghost imaging, the resource consumption can be dramatically reduced using our scheme.

  18. Self-similarity Detection via Multi-scale Image Analysis

    NASA Astrophysics Data System (ADS)

    Kamejima, Kohji

    A dynamic scheme is presented for generating multi-scale images associated with self-similar patterns. By blurring with a small scale parameter, brightness distributions are extended to geometrically singular fractal patterns. Through weighted averaging with respect to scale factors, a multi-scale image is generated as a representation of the conditional probability for capturing unknown attractors. The local structure of the multi-scale image is analyzed to demonstrate the structural consistency of the capturing probability with respect to the imaging process associated with the attractor. By extracting stochastic features based on the capturing probability, a computational scheme is introduced for matching observed attractors with a preassigned dictionary of patterns. Proposed method was verified by simulation studies.

  19. Development of an Image-based Multi-Scale Finite Element Approach to Predict Fatigue Damage in Asphalt Mixtures

    NASA Astrophysics Data System (ADS)

    Arshadi, Amir

    Image-based simulation of complex materials is a very important tool for understanding their mechanical behavior and an effective tool for successful design of composite materials. In this thesis an image-based multi-scale finite element approach is developed to predict the mechanical properties of asphalt mixtures. In this approach the "up-scaling" and homogenization of each scale to the next is critically designed to improve accuracy. In addition to this multi-scale efficiency, this study introduces an approach for consideration of particle contacts at each of the scales in which mineral particles exist. One of the most important pavement distresses which seriously affects the pavement performance is fatigue cracking. As this cracking generally takes place in the binder phase of the asphalt mixture, the binder fatigue behavior is assumed to be one of the main factors influencing the overall pavement fatigue performance. It is also known that aggregate gradation, mixture volumetric properties, and filler type and concentration can affect damage initiation and progression in the asphalt mixtures. This study was conducted to develop a tool to characterize the damage properties of the asphalt mixtures at all scales. In the present study the Viscoelastic continuum damage model is implemented into the well-known finite element software ABAQUS via the user material subroutine (UMAT) in order to simulate the state of damage in the binder phase under the repeated uniaxial sinusoidal loading. The inputs are based on the experimentally derived measurements for the binder properties. For the scales of mastic and mortar, the artificially 2-Dimensional images of mastic and mortar scales were generated and used to characterize the properties of those scales. Finally, the 2D scanned images of asphalt mixtures are used to study the asphalt mixture fatigue behavior under loading. In order to validate the proposed model, the experimental test results and the simulation results were

  20. Multi-scale volumetric cell and tissue imaging based on optical projection tomography (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Ban, Sungbea; Cho, Nam Hyun; Ryu, Yongjae; Jung, Sunwoo; Vavilin, Andrey; Min, Eunjung; Jung, Woonggyu

    2016-04-01

    Optical projection tomography is a new optical imaging method for visualizing small biological specimens in three dimension. The most important advantage of OPT is to fill the gap between MRI and confocal microscope for the specimen having the range of 1-10 mm. Thus, it has been mainly used for whole-mount small animals and developmental study since this imaging modality was developed. The ability of OPT delivering anatomical and functional information of relatively large tissue in 3D has made it a promising platform in biomedical research. Recently, the potential of OPT spans its coverage to cellular scale. Even though there are increasing demand to obtain better understanding of cellular dynamics, only few studies to visualize cellular structure, shape, size and functional morphology over tissue has been investigated in existing OPT system due to its limited field of view. In this study, we develop a novel optical imaging system for 3D cellular imaging with OPT integrated with dynamic focusing technique. Our tomographic setup has great potential to be used for identifying cell characteristic in tissue because it can provide selective contrast on dynamic focal plane allowing for fluorescence as well as absorption. While the dominant contrast of optical imaging technique is to use the fluorescence for detecting certain target only, the newly developed OPT system will offer considerable advantages over currently available method when imaging cellar molecular dynamics by permitting contrast variation. By achieving multi-contrast, it is expected for this new imaging system to play an important role in delivering better cytological information to pathologist.

  1. Non-linear direct multi-scale image enhancement based on the luminance and contrast masking characteristics of the human visual system.

    PubMed

    Nercessian, Shahan C; Panetta, Karen A; Agaian, Sos S

    2013-09-01

    Image enhancement is a crucial pre-processing step for various image processing applications and vision systems. Many enhancement algorithms have been proposed based on different sets of criteria. However, a direct multi-scale image enhancement algorithm capable of independently and/or simultaneously providing adequate contrast enhancement, tonal rendition, dynamic range compression, and accurate edge preservation in a controlled manner has yet to be produced. In this paper, a multi-scale image enhancement algorithm based on a new parametric contrast measure is presented. The parametric contrast measure incorporates not only the luminance masking characteristic, but also the contrast masking characteristic of the human visual system. The formulation of the contrast measure can be adapted for any multi-resolution decomposition scheme in order to yield new human visual system-inspired multi-scale transforms. In this article, it is exemplified using the Laplacian pyramid, discrete wavelet transform, stationary wavelet transform, and dual-tree complex wavelet transform. Consequently, the proposed enhancement procedure is developed. The advantages of the proposed method include: 1) the integration of both the luminance and contrast masking phenomena; 2) the extension of non-linear mapping schemes to human visual system inspired multi-scale contrast coefficients; 3) the extension of human visual system-based image enhancement approaches to the stationary and dual-tree complex wavelet transforms, and a direct means of; 4) adjusting overall brightness; and 5) achieving dynamic range compression for image enhancement within a direct multi-scale enhancement framework. Experimental results demonstrate the ability of the proposed algorithm to achieve simultaneous local and global enhancements.

  2. Multi-Scale Optical Coherence Tomography Imaging

    NASA Astrophysics Data System (ADS)

    Oliveira, Michael Christopher

    An optical modality capable of quantitative, label-free, high-speed and high-resolution imaging across spatiotemporal scales coupled with sophisticated software for image reconstruction and quantitative analyses would be of great utility to scientists and engineers in the medical and life sciences fields. Currently, a combination of optical imaging techniques and software packages are needed to address the list of capabilities described previously. Optical coherence tomography is an optical imaging technique based on low coherence interferometry capable of measuring light backscattered from the sample at micrometer-level resolutions over millimeter-level penetration depths in biological tissue. Phase-sensitive extensions of OCT enable the functional assessment of biological tissue samples as well as the structural examination of samples down to the single-cell level. This dissertation describes the development and application of high-speed real-time multi-functional spectral-domain OCT (MF-SD-OCT) for structural and functional examination of biological samples across spatiotemporal scales. A discussion of the development of a GPU-accelerated high-speed MF-SD-OCT imaging system accompanied by demonstrations of the performance enhancements due to the GPU are presented initially. Next, the development of MF-SD-OCT-based quantitative methods for the structural and functional assessment and characterization and classification of biological tissue samples is discussed. The utility of these methods is demonstrated through structural, functional and optical characterization and classification of peripheral nerve and muscle tissue. The dissertation concludes with a discussion of the improvements made to spectral-domain optical coherence phase microscopy (SD-OCPM) to enable dynamic live cell imaging and the application of dynamic live cell SD-OCPM for morphological visualization of cheek epithelial cells and examination of functionally stimulated morphological changes in

  3. Image-based multi-scale modelling and validation of radio-frequency ablation in liver tumours.

    PubMed

    Payne, Stephen; Flanagan, Ronan; Pollari, Mika; Alhonnoro, Tuomas; Bost, Claire; O'Neill, David; Peng, Tingying; Stiegler, Philipp

    2011-11-13

    The treatment of cancerous tumours in the liver remains clinically challenging, despite the wide range of treatment possibilities, including radio-frequency ablation (RFA), high-intensity focused ultrasound and resection, which are currently available. Each has its own advantages and disadvantages. For non- or minimally invasive modalities, such as RFA, considered here, it is difficult to monitor the treatment in vivo. This is particularly problematic in the liver, where large blood vessels act as heat sinks, dissipating delivered heat and shrinking the size of the lesion (the volume damaged by the heat treatment) locally; considerable experience is needed on the part of the clinician to optimize the heat treatment to prevent recurrence. In this paper, we outline our work towards developing a simulation tool kit that could be used both to optimize treatment protocols in advance and to train the less-experienced clinicians for RFA treatment of liver tumours. This tool is based on a comprehensive mathematical model of bio-heat transfer and cell death. We show how simulations of ablations in two pigs, based on individualized imaging data, compare directly with experimentally measured lesion sizes and discuss the likely sources of error and routes towards clinical implementation. This is the first time that such a 'loop' of mathematical modelling and experimental validation in vivo has been performed in this context, and such validation enables us to make quantitative estimates of error.

  4. Dehazing method through polarimetric imaging and multi-scale analysis

    NASA Astrophysics Data System (ADS)

    Cao, Lei; Shao, Xiaopeng; Liu, Fei; Wang, Lin

    2015-05-01

    An approach for haze removal utilizing polarimetric imaging and multi-scale analysis has been developed to solve one problem that haze weather weakens the interpretation of remote sensing because of the poor visibility and short detection distance of haze images. On the one hand, the polarization effects of the airlight and the object radiance in the imaging procedure has been considered. On the other hand, one fact that objects and haze possess different frequency distribution properties has been emphasized. So multi-scale analysis through wavelet transform has been employed to make it possible for low frequency components that haze presents and high frequency coefficients that image details or edges occupy are processed separately. According to the measure of the polarization feather by Stokes parameters, three linear polarized images (0°, 45°, and 90°) have been taken on haze weather, then the best polarized image min I and the worst one max I can be synthesized. Afterwards, those two polarized images contaminated by haze have been decomposed into different spatial layers with wavelet analysis, and the low frequency images have been processed via a polarization dehazing algorithm while high frequency components manipulated with a nonlinear transform. Then the ultimate haze-free image can be reconstructed by inverse wavelet reconstruction. Experimental results verify that the dehazing method proposed in this study can strongly promote image visibility and increase detection distance through haze for imaging warning and remote sensing systems.

  5. Multi-scale imaging and elastic simulation of carbonates

    NASA Astrophysics Data System (ADS)

    Faisal, Titly Farhana; Awedalkarim, Ahmed; Jouini, Mohamed Soufiane; Jouiad, Mustapha; Chevalier, Sylvie; Sassi, Mohamed

    2016-05-01

    for this current unresolved phase is important. In this work we take a multi-scale imaging approach by first extracting a smaller 0.5" core and scanning at approx 13 µm, then further extracting a 5mm diameter core scanned at 5 μm. From this last scale, region of interests (containing unresolved areas) are identified for scanning at higher resolutions using Focalised Ion Beam (FIB/SEM) scanning technique reaching 50 nm resolution. Numerical simulation is run on such a small unresolved section to obtain a better estimate of the effective moduli which is then used as input for simulations performed using CT-images. Results are compared with expeirmental acoustic test moduli obtained also at two scales: 1.5" and 0.5" diameter cores.

  6. Human visual system-based multi-scale tools with biomedical and security applications

    NASA Astrophysics Data System (ADS)

    Nercessian, Shahan

    Multi-scale transforms have been shown to be invaluable tools for image processing. The effectiveness of consequently formulated multi-scale algorithms have practically made them de facto standards for realizing solutions for a broad range of image processing problems. Multi-scale formulations of transforms and algorithms are motivated by the ability of the human visual system (HVS) to extract edge structures at their different scales. Image processing algorithms, consequently, have been developed which alter multi-transform coefficients of images for various means. However, the multi-scale contrasts as defined by these schemes generally not consistent with many other relevant HVS phenomena. Upon reviewing relevant HVS characteristics, new tools which are consistent with these features are presented. Accordingly, new image enhancement, image de-noising, and image fusion algorithms which make use of HVS-inspired multi-scale tools are presented as contributions to each of these fields. In this context, the aim of the presented algorithms is two-fold: The intention is to both consider new multi-scale solutions, as well as to formulate them using perceptually-driven mathematical constructs based on HVS characteristics. In the context of image enhancement, a new set of multi-scale image enhancement algorithms are presented which are able to simultaneously provide both local and global enhancements within a direct enhancement framework. For the purpose of image de-noising, a multi-scale formulation of the non-local-means de-noising algorithm is developed which is shown to both visually and quantitatively outperform existing de-noising approaches. Many algorithms to achieve image fusion based on the presented transforms are presented. One set of algorithms is based on a Parameterized Logarithmic Image Processing model, while another is based on an adaptive similarity-based weighting scheme. The interdependence between the different algorithms considered in this

  7. Fusion of infrared and visual images through region extraction by using multi scale center-surround top-hat transform.

    PubMed

    Bai, Xiangzhi; Zhou, Fugen; Xue, Bindang

    2011-04-25

    Fusion of infrared and visual images is an important research area in image analysis. The purpose of infrared and visual image fusion is to combine the image information of the original images into the final fusion result. So, it is crucial to effectively extract the image information of the original images and reasonably combine them into the final fusion image. To achieve this purpose, an algorithm by using multi scale center-surround top-hat transform through region extraction is proposed in this paper. Firstly, multi scale center-surround top-hat transform is discussed and used to extract the multi scale bright and dim image regions of the original images. Secondly, the final extracted image regions for image fusion are constructed from the extracted multi scale bright and dim image regions. Finally, after a base image is calculated from the original images, the final extracted image regions are combined into the base image through a power strategy to form the final fusion result. Because the image information of the original images are well extracted and combined, the proposed algorithm is very effective for image fusion. Comparison experiments have been performed on different image sets, and the results verified the effectiveness of the proposed algorithm.

  8. A real-time multi-scale 2D Gaussian filter based on FPGA

    NASA Astrophysics Data System (ADS)

    Luo, Haibo; Gai, Xingqin; Chang, Zheng; Hui, Bin

    2014-11-01

    Multi-scale 2-D Gaussian filter has been widely used in feature extraction (e.g. SIFT, edge etc.), image segmentation, image enhancement, image noise removing, multi-scale shape description etc. However, their computational complexity remains an issue for real-time image processing systems. Aimed at this problem, we propose a framework of multi-scale 2-D Gaussian filter based on FPGA in this paper. Firstly, a full-hardware architecture based on parallel pipeline was designed to achieve high throughput rate. Secondly, in order to save some multiplier, the 2-D convolution is separated into two 1-D convolutions. Thirdly, a dedicate first in first out memory named as CAFIFO (Column Addressing FIFO) was designed to avoid the error propagating induced by spark on clock. Finally, a shared memory framework was designed to reduce memory costs. As a demonstration, we realized a 3 scales 2-D Gaussian filter on a single ALTERA Cyclone III FPGA chip. Experimental results show that, the proposed framework can computing a Multi-scales 2-D Gaussian filtering within one pixel clock period, is further suitable for real-time image processing. Moreover, the main principle can be popularized to the other operators based on convolution, such as Gabor filter, Sobel operator and so on.

  9. 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.

  10. Imaging multi-scale dynamics in vivo with spiral volumetric optoacoustic tomography

    NASA Astrophysics Data System (ADS)

    Deán-Ben, X. Luís.; Fehm, Thomas F.; Ford, Steven J.; Gottschalk, Sven; Razansky, Daniel

    2017-03-01

    Imaging dynamics in living organisms is essential for the understanding of biological complexity. While multiple imaging modalities are often required to cover both microscopic and macroscopic spatial scales, dynamic phenomena may also extend over different temporal scales, necessitating the use of different imaging technologies based on the trade-off between temporal resolution and effective field of view. Optoacoustic (photoacoustic) imaging has been shown to offer the exclusive capability to link multiple spatial scales ranging from organelles to entire organs of small animals. Yet, efficient visualization of multi-scale dynamics remained difficult with state-of-the-art systems due to inefficient trade-offs between image acquisition and effective field of view. Herein, we introduce a spiral volumetric optoacoustic tomography (SVOT) technique that provides spectrally-enriched high-resolution optical absorption contrast across multiple spatio-temporal scales. We demonstrate that SVOT can be used to monitor various in vivo dynamics, from video-rate volumetric visualization of cardiac-associated motion in whole organs to high-resolution imaging of pharmacokinetics in larger regions. The multi-scale dynamic imaging capability thus emerges as a powerful and unique feature of the optoacoustic technology that adds to the multiple advantages of this technology for structural, functional and molecular imaging.

  11. Object-Oriented Change Detection Based on Multi-Scale Approach

    NASA Astrophysics Data System (ADS)

    Jia, Yonghong; Zhou, Mingting; Jinshan, Ye

    2016-06-01

    The change detection of remote sensing images means analysing the change information quantitatively and recognizing the change types of the surface coverage data in different time phases. With the appearance of high resolution remote sensing image, object-oriented change detection method arises at this historic moment. In this paper, we research multi-scale approach for high resolution images, which includes multi-scale segmentation, multi-scale feature selection and multi-scale classification. Experimental results show that this method has a stronger advantage than the traditional single-scale method of high resolution remote sensing image change detection.

  12. [Segmentation-based multi-scale urban green space landscape].

    PubMed

    Sun, Xiaofang; Lu, Jian; Sun, Yibin

    2006-09-01

    In this study, three scales urban green space landscapes were generated by multi-resolution segmentation. With 50 and 300 pixels as the object segmentation thresholds, the small- and large-scale landscape object image layers were produced, and the two object image layers were obtained by the nearest neighbor classification method. The result of small-scale landscape classification image was segmented into middle-scale landscape image, and then classified. Green space information was extracted through vector form of object image layers of three scales landscape classification. The landscape indexes diversity, dominance, evenness, fractal dimension, fragmentation, and interior to edge ration were calculated, with the largest values of the former four indexes being 2.2, 0.681, 0.948, and 0.326, and the smallest values being 1.641, 0. 122, 0.707, and 0.113, respectively, indicating that the diversity, evenness and fragmentation decreased, while the dominance increased with increasing landscape scale. The method of multi-resolution segmentation to generate multi-scale landscape could meet the needs of urban green space landscape research.

  13. Multi-scale visual words for hierarchical medical image categorisation

    NASA Astrophysics Data System (ADS)

    Markonis, Dimitrios; Seco de Herrera, Alba G.; Eggel, Ivan; Müller, Henning

    2012-02-01

    The biomedical literature published regularly has increased strongly in past years and keeping updated even in narrow domains is difficult. Images represent essential information of their articles and can help to quicker browse through large volumes of articles in connection with keyword search. Content-based image retrieval is helping the retrieval of visual content. To facilitate retrieval of visual information, image categorisation can be an important first step. To represent scientific articles visually, medical images need to be separated from general images such as flowcharts or graphs to facilitate browsing, as graphs contain little information. Medical modality classification is a second step to focus search. The techniques described in this article first classify images into broad categories. In a second step the images are further classified into the exact medical modalities. The system combines the Scale-Invariant Feature Transform (SIFT) and density-based clustering (DENCLUE). Visual words are first created globally to differentiate broad categories and then within each category a new visual vocabulary is created for modality classification. The results show the difficulties to differentiate between some modalities by visual means alone. On the other hand the improvement of the accuracy of the two-step approach shows the usefulness of the method. The system is currently being integrated into the Goldminer image search engine of the ARRS (American Roentgen Ray Society) as a web service, allowing concentrating image search onto clinically relevant images automatically.

  14. Fusion of infrared-visible images using improved multi-scale top-hat transform and suitable fusion rules

    NASA Astrophysics Data System (ADS)

    Zhu, Pan; Ma, Xiaoqing; Huang, Zhanhua

    2017-03-01

    Integration of infrared and visible images is an active and important topic in image understanding and interpretation. In this paper, a new fusion method is proposed based on the improved multi-scale center-surround top-hat transform, which can effectively extract the feature information and detail information of source images. Firstly, the multi-scale bright (dark) feature regions of infrared and visible images are respectively extracted at different scale levels by the improved multi-scale center-surround top-hat transform. Secondly, the feature regions at the same scale in both images are combined by multi-judgment contrast fusion rule, and the final feature images are obtained by simply adding all scales of feature images together. Then, a base image is calculated by performing Gaussian fuzzy logic combination rule on two smoothed source images. Finally, the fusion image is obtained by importing the extracted bright and dark feature images into the base image with a suitable strategy. Both objective assessment and subjective vision of the experimental results indicate that the proposed method is superior to current popular MST-based methods and morphology-based methods in the field of infrared-visible images fusion.

  15. 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.

  16. Multi-channel and multi-scale mid-level image representation for scene classification

    NASA Astrophysics Data System (ADS)

    Yang, Jinfu; Yang, Fei; Wang, Guanghui; Li, Mingai

    2017-03-01

    Convolutional neural network (CNN)-based approaches have received state-of-the-art results in scene classification. Features from the output of fully connected (FC) layers express one-dimensional semantic information but lose the detailed information of objects and the spatial information of scene categories. On the contrary, deep convolutional features have been proved to be more suitable for describing an object itself and the spatial relations among objects in an image. In addition, the feature map from each layer is max-pooled within local neighborhoods, which weakens the invariance of global consistency and is unfavorable to scenes with highly complicated variation. To cope with the above issues, an orderless multi-channel mid-level image representation on pre-trained CNN features is proposed to improve the classification performance. The mid-level image representation of two channels from the FC layer and the deep convolutional layer are integrated at multi-scale levels. A sum pooling approach is also employed to aggregate multi-scale mid-level image representation to highlight the importance of the descriptors beneficial for scene classification. Extensive experiments on SUN397 and MIT 67 indoor datasets demonstrate that the proposed method achieves promising classification performance.

  17. Optical correlation recognition of infrared target based on wavelet multi-scale product

    NASA Astrophysics Data System (ADS)

    Chen, Fang-han; Wang, Wen-sheng

    2011-06-01

    As one of the most successful optical correlation recognizers, hybrid optoelectronic joint transform correlator (HOJTC) has received more and more attraction than the purely electronic way in the field of target detection and recognition. It primarily because that HOJTC has the advantages of optics as well as those of electronics. This kind of combination determines that the performance of HOJTC is closely related to optical configuration of system and digital image processing technology. For the stability of optical part, a lot of efforts concerning image processing methods have been made in recent years for improving the power of recognition of HOJTC. Edge contours play a decisive role in target detection. In order to obtain adequate contour feature of target, the solution of edge extraction based on wavelet multi-scale product is proposed. Normalized maximum and argument of each point could be defined utilizing wavelet coefficient of image. Both of them contain the relation of coefficient product between each scale. Edge points synthesized the information of multi-scale are extracted by searching local maxima along the direction of gradient. The way adopted fully exploited the character of multi-resolution of wavelet. Simulation experiments and optical experiments indicate that the energy of correlation peaks is obviously enhanced after the original image is processed by wavelet multi-scale product, and it successfully realizes detection and recognition of infrared target.

  18. Multi-Scale Fusion for Improved Localization of Malicious Tampering in Digital Images.

    PubMed

    Korus, Paweł; Huang, Jiwu

    2016-03-01

    A sliding window-based analysis is a prevailing mechanism for tampering localization in passive image authentication. It uses existing forensic detectors, originally designed for a full-frame analysis, to obtain the detection scores for individual image regions. One of the main problems with a window-based analysis is its impractically low localization resolution stemming from the need to use relatively large analysis windows. While decreasing the window size can improve the localization resolution, the classification results tend to become unreliable due to insufficient statistics about the relevant forensic features. In this paper, we investigate a multi-scale analysis approach that fuses multiple candidate tampering maps, resulting from the analysis with different windows, to obtain a single, more reliable tampering map with better localization resolution. We propose three different techniques for multi-scale fusion, and verify their feasibility against various reference strategies. We consider a popular tampering scenario with mode-based first digit features to distinguish between singly and doubly compressed regions. Our results clearly indicate that the proposed fusion strategies can successfully combine the benefits of small-scale and large-scale analyses and improve the tampering localization performance.

  19. MREG V1.1 : a multi-scale image registration algorithm for SAR applications.

    SciTech Connect

    Eichel, Paul H.

    2013-08-01

    MREG V1.1 is the sixth generation SAR image registration algorithm developed by the Signal Processing&Technology Department for Synthetic Aperture Radar applications. Like its predecessor algorithm REGI, it employs a powerful iterative multi-scale paradigm to achieve the competing goals of sub-pixel registration accuracy and the ability to handle large initial offsets. Since it is not model based, it allows for high fidelity tracking of spatially varying terrain-induced misregistration. Since it does not rely on image domain phase, it is equally adept at coherent and noncoherent image registration. This document provides a brief history of the registration processors developed by Dept. 5962 leading up to MREG V1.1, a full description of the signal processing steps involved in the algorithm, and a user's manual with application specific recommendations for CCD, TwoColor MultiView, and SAR stereoscopy.

  20. Vessel Segmentation in Retinal Images Using Multi-scale Line Operator and K-Means Clustering.

    PubMed

    Saffarzadeh, Vahid Mohammadi; Osareh, Alireza; Shadgar, Bita

    2014-04-01

    Detecting blood vessels is a vital task in retinal image analysis. The task is more challenging with the presence of bright and dark lesions in retinal images. Here, a method is proposed to detect vessels in both normal and abnormal retinal fundus images based on their linear features. First, the negative impact of bright lesions is reduced by using K-means segmentation in a perceptive space. Then, a multi-scale line operator is utilized to detect vessels while ignoring some of the dark lesions, which have intensity structures different from the line-shaped vessels in the retina. The proposed algorithm is tested on two publicly available STARE and DRIVE databases. The performance of the method is measured by calculating the area under the receiver operating characteristic curve and the segmentation accuracy. The proposed method achieves 0.9483 and 0.9387 localization accuracy against STARE and DRIVE respectively.

  1. Agile multi-scale decompositions for automatic image registration

    NASA Astrophysics Data System (ADS)

    Murphy, James M.; Leija, Omar Navarro; Le Moigne, Jacqueline

    2016-05-01

    In recent works, the first and third authors developed an automatic image registration algorithm based on a multiscale hybrid image decomposition with anisotropic shearlets and isotropic wavelets. This prototype showed strong performance, improving robustness over registration with wavelets alone. However, this method imposed a strict hierarchy on the order in which shearlet and wavelet features were used in the registration process, and also involved an unintegrated mixture of MATLAB and C code. In this paper, we introduce a more agile model for generating features, in which a flexible and user-guided mix of shearlet and wavelet features are computed. Compared to the previous prototype, this method introduces a flexibility to the order in which shearlet and wavelet features are used in the registration process. Moreover, the present algorithm is now fully coded in C, making it more efficient and portable than the mixed MATLAB and C prototype. We demonstrate the versatility and computational efficiency of this approach by performing registration experiments with the fully-integrated C algorithm. In particular, meaningful timing studies can now be performed, to give a concrete analysis of the computational costs of the flexible feature extraction. Examples of synthetically warped and real multi-modal images are analyzed.

  2. Multi-Scale Gaussian Normalization for Solar Image Processing.

    PubMed

    Morgan, Huw; Druckmüller, Miloslav

    Extreme ultra-violet images of the corona contain information over a wide range of spatial scales, and different structures such as active regions, quiet Sun, and filament channels contain information at very different brightness regimes. Processing of these images is important to reveal information, often hidden within the data, without introducing artefacts or bias. It is also important that any process be computationally efficient, particularly given the fine spatial and temporal resolution of Atmospheric Imaging Assembly on the Solar Dynamics Observatory (AIA/SDO), and consideration of future higher resolution observations. A very efficient process is described here, which is based on localised normalising of the data at many different spatial scales. The method reveals information at the finest scales whilst maintaining enough of the larger-scale information to provide context. It also intrinsically flattens noisy regions and can reveal structure in off-limb regions out to the edge of the field of view. We also applied the method successfully to a white-light coronagraph observation.

  3. 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

  4. Multi-scale measures of rugosity, slope and aspect from benthic stereo image reconstructions.

    PubMed

    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 [Formula: see text]. 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

  5. Multi-Scale Fractal Analysis of Image Texture and Pattern

    NASA Technical Reports Server (NTRS)

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

    1999-01-01

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

  6. Multi-Scale Fractal Analysis of Image Texture and Pattern

    NASA Technical Reports Server (NTRS)

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

    1999-01-01

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

  7. Multi-Scale Fractal Analysis of Image Texture and Pattern

    NASA Technical Reports Server (NTRS)

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

    1999-01-01

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

  8. Multi scale detail-preserving denoising method of infrared image via relative total variation

    NASA Astrophysics Data System (ADS)

    Cui, Guang-mang; Feng, Hua-jun; Xu, Zhi-hai; Li, Qi; Chen, Yue-ting

    2013-09-01

    How to remove the noise in infrared image effectively with detail preserving is a significant but difficult problem in infrared image processing. Various methods have been proposed to obtain good results. However, these algorithms usually cannot distinguish noise and detail efficiently, which leads to smoothing some details in infrared images. Recently a novel local measure called relative total variation (RTV) is proposed to accomplish effective texture removal. RTV measure is combined with a general windowed total variation measure and a novel inherent variation measure to smooth the image texture effectively while preserving the main structure. In this paper, using detail preserving smoothing method via RTV, a multi scale denoising algorithm for infrared image is proposed. Firstly, the infrared image is decomposed into several scales by non-subsampled Contourlet transform (NSCT). NSCT decomposition does not do any down sampling or up sampling, thus the results are not band limited. Secondly,the algorithm applies RTV based detail preserving denoising method for each decomposed layers. Different smoothing parameters are respectively used to adjust the denoising levels in different scales. Finally, various synthetic weights are utilized to different layers to reconstruct the final infrared denosing results. Compared with other infrared denoising approaches, the quantitative comparisons demonstrate that the proposed method could well suppress the noise of infrared image while preserving the edge details effectively. Both visual quality and objective measure results show that this method is efficient and has a good application in infrared image denoising.

  9. Multi-Scale Fractal Analysis of Image Texture and Pattern

    NASA Technical Reports Server (NTRS)

    Emerson, Charles W.; Quattrochi, Dale A.; Luvall, Jeffrey C.

    1997-01-01

    Fractals embody important ideas of self-similarity, in which the spatial behavior or appearance of a system is largely scale-independent. Self-similarity is a property of curves or surfaces where each part is indistinguishable from the whole. The fractal dimension D of remote sensing data yields quantitative insight on the spatial complexity and information content contained within these data. Analyses of Normalized Difference Vegetation Index (NDVI) images of homogeneous land covers near Huntsville, Alabama revealed that the fractal dimension of an image of an agricultural land cover indicates greater complexity as pixel size increases, a forested land cover gradually grows smoother, and an urban image remains roughly self-similar over the range of pixel sizes analyzed(l0 to 80 meters). The forested scene behaves as one would expect-larger pixel sizes decrease the complexity of the image as individual clumps of trees are averaged into larger blocks. The increased complexity of the agricultural image with increasing pixel size results from the loss of homogeneous groups of pixels in the large fields to mixed pixels composed of varying combinations of NDVI values that correspond to roads and vegetation. The same process occur's in the urban image to some extent, but the lack of large, homogeneous areas in the high resolution NDVI image means the initially high D value is maintained as pixel size increases. The slope of the fractal dimension-resolution relationship provides indications of how image classification or feature identification will be affected by changes in sensor resolution.

  10. Bayesian multi-scale smoothing of photon-limited images with applications to astronomy and medicine

    NASA Astrophysics Data System (ADS)

    White, John

    Multi-scale models for smoothing Poisson signals or images have gained much attention over the past decade. A new Bayesian model is developed using the concept of the Chinese restaurant process to find structures in two-dimensional images when performing image reconstruction or smoothing. This new model performs very well when compared to other leading methodologies for the same problem. It is developed and evaluated theoretically and empirically throughout Chapter 2. The newly developed Bayesian model is extended to three-dimensional images in Chapter 3. The third dimension has numerous different applications, such as different energy spectra, another spatial index, or possibly a temporal dimension. Empirically, this method shows promise in reducing error with the use of simulation studies. A further development removes background noise in the image. This removal can further reduce the error and is done using a modeling adjustment and post-processing techniques. These details are given in Chapter 4. Applications to real world problems are given throughout. Photon-based images are common in astronomical imaging due to the collection of different types of energy such as X-Rays. Applications to real astronomical images are given, and these consist of X-ray images from the Chandra X-ray observatory satellite. Diagnostic medicine uses many types of imaging such as magnetic resonance imaging and computed tomography that can also benefit from smoothing techniques such as the one developed here. Reducing the amount of radiation a patient takes will make images more noisy, but this can be mitigated through the use of image smoothing techniques. Both types of images represent the potential real world use for these methods.

  11. Multi-Scale Fractal Analysis of Image Texture and Pattern

    NASA Technical Reports Server (NTRS)

    Emerson, Charles W.

    1998-01-01

    Fractals embody important ideas of self-similarity, in which the spatial behavior or appearance of a system is largely independent of scale. Self-similarity is defined as a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. An ideal fractal (or monofractal) curve or surface has a constant dimension over all scales, although it may not be an integer value. This is in contrast to Euclidean or topological dimensions, where discrete one, two, and three dimensions describe curves, planes, and volumes. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution. However, most geographical phenomena are not strictly self-similar at all scales, but they can often be modeled by a stochastic fractal in which the scaling and self-similarity properties of the fractal have inexact patterns that can be described by statistics. Stochastic fractal sets relax the monofractal self-similarity assumption and measure many scales and resolutions in order to represent the varying form of a phenomenon as a function of local variables across space. In image interpretation, pattern is defined as the overall spatial form of related features, and the repetition of certain forms is a characteristic pattern found in many cultural objects and some natural features. Texture is the visual impression of coarseness or smoothness caused by the variability or uniformity of image tone or color. A potential use of fractals concerns the analysis of image texture. In these situations it is commonly observed that the degree of roughness or inexactness in an image or surface is a function of scale and not of experimental technique. The fractal dimension of remote sensing data could yield quantitative insight on the spatial complexity and

  12. Multi-scale Imaging of Cellular and Sub-cellular Structures using Scanning Probe Recognition Microscopy.

    NASA Astrophysics Data System (ADS)

    Chen, Q.; Rice, A. F.

    2005-03-01

    Scanning Probe Recognition Microscopy is a new scanning probe capability under development within our group to reliably return to and directly interact with a specific nanobiological feature of interest. In previous work, we have successfully recognized and classified tubular versus globular biological objects from experimental atomic force microscope images using a method based on normalized central moments [ref. 1]. In this paper we extend this work to include recognition schemes appropriate for cellular and sub-cellular structures. Globular cells containing tubular actin filaments are under investigation. Thus there are differences in external/internal shapes and scales. Continuous Wavelet Transform with a differential Gaussian mother wavelet is employed for multi- scale analysis. [ref. 1] Q. Chen, V. Ayres and L. Udpa, ``Biological Investigation Using Scanning Probe Recognition Microscopy,'' Proceedings 3rd IEEE Conference on Nanotechnology, vol. 2, p 863-865 (2003).

  13. Multi-scale probabilistic seismic imaging with the USArray

    NASA Astrophysics Data System (ADS)

    Olugboji, T. M.; Lekic, V.; Burdick, S.; Gao, C.

    2016-12-01

    Seismological imaging of the structure of Earth's interior is essential to our understanding of the dynamics and evolution of our planet. Although some fundamental challenges in this imaging problem exist, e.g. lack of stations in the oceans and uneven earthquake distribution, other challenges can now be addressed by the emergence of high performance computing capabilities. These include the assumptions made a-priori about the parameterization and explicit regularization - damping and smoothing - of the Earth model, the inadequate accounting for observational and modeling uncertainty, and the subjectivity often imposed when deciding on the manner in which to combine seismic data with varying sensitivity to different properties in the earth model. In this talk, we present extensions of traditional seismic imaging techniques to crustal and upper mantle structure using a probabilistic (Bayesian) approach. We illustrate various benefits to this approach by analyzing Love and Rayleigh phase velocity and P-wave travel time measurements made using the USArray. We show that the probabilistic approach can: (1) Aid geophysical inference by assessing parameter uncertainty and trade-offs in seismic images (tomograms); (2) Recover multiple scales of heterogeneity by avoiding explicit regularization, even when data coverage is uniform; (3) Yield multi-modal distributions on velocities in regions of rapid velocity variations; and, (4) Quantify improvements in seismic images attributable to new data or new acquisition methods and techniques. We emphasize the central role of high performance computing and the philosophy of open software development and exchange to the success of these techniques, which explore large parameter space and generate large ensembles solutions. Finally, we describe novel approaches to exploring, presenting and understanding the large quantity of information that is contained in the ensemble solutions.

  14. Multi-scale approaches for high-speed imaging and analysis of large neural populations

    PubMed Central

    Ahrens, Misha B.; Yuste, Rafael; Peterka, Darcy S.; Paninski, Liam

    2017-01-01

    Progress in modern neuroscience critically depends on our ability to observe the activity of large neuronal populations with cellular spatial and high temporal resolution. However, two bottlenecks constrain efforts towards fast imaging of large populations. First, the resulting large video data is challenging to analyze. Second, there is an explicit tradeoff between imaging speed, signal-to-noise, and field of view: with current recording technology we cannot image very large neuronal populations with simultaneously high spatial and temporal resolution. Here we describe multi-scale approaches for alleviating both of these bottlenecks. First, we show that spatial and temporal decimation techniques based on simple local averaging provide order-of-magnitude speedups in spatiotemporally demixing calcium video data into estimates of single-cell neural activity. Second, once the shapes of individual neurons have been identified at fine scale (e.g., after an initial phase of conventional imaging with standard temporal and spatial resolution), we find that the spatial/temporal resolution tradeoff shifts dramatically: after demixing we can accurately recover denoised fluorescence traces and deconvolved neural activity of each individual neuron from coarse scale data that has been spatially decimated by an order of magnitude. This offers a cheap method for compressing this large video data, and also implies that it is possible to either speed up imaging significantly, or to “zoom out” by a corresponding factor to image order-of-magnitude larger neuronal populations with minimal loss in accuracy or temporal resolution. PMID:28771570

  15. Multi-scale saliency search in image analysis.

    SciTech Connect

    Slepoy, Alexander; Campisi, Anthony; Backer, Alejandro

    2005-10-01

    Saliency detection in images is an important outstanding problem both in machine vision design and the understanding of human vision mechanisms. Recently, seminal work by Itti and Koch resulted in an effective saliency-detection algorithm. We reproduce the original algorithm in a software application Vision and explore its limitations. We propose extensions to the algorithm that promise to improve performance in the case of difficult-to-detect objects.

  16. 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.

  17. 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

  18. A multi-scale segmentation approach to filling gaps in Landsat ETM+ SLC-off images

    USGS Publications Warehouse

    Maxwell, S.K.; Schmidt, G.L.; Storey, J.C.

    2007-01-01

    On 31 May 2003, the Landsat Enhanced Thematic Plus (ETM+) Scan Line Corrector (SLC) failed, causing the scanning pattern to exhibit wedge-shaped scan-to-scan gaps. We developed a method that uses coincident spectral data to fill the image gaps. This method uses a multi-scale segment model, derived from a previous Landsat SLC-on image (image acquired prior to the SLC failure), to guide the spectral interpolation across the gaps in SLC-off images (images acquired after the SLC failure). This paper describes the process used to generate the segment model, provides details of the gap-fill algorithm used in deriving the segment-based gap-fill product, and presents the results of the gap-fill process applied to grassland, cropland, and forest landscapes. Our results indicate this product will be useful for a wide variety of applications, including regional-scale studies, general land cover mapping (e.g. forest, urban, and grass), crop-specific mapping and monitoring, and visual assessments. Applications that need to be cautious when using pixels in the gap areas include any applications that require per-pixel accuracy, such as urban characterization or impervious surface mapping, applications that use texture to characterize landscape features, and applications that require accurate measurements of small or narrow landscape features such as roads, farmsteads, and riparian areas.

  19. A multi-scale tensor voting approach for small retinal vessel segmentation in high resolution fundus images.

    PubMed

    Christodoulidis, Argyrios; Hurtut, Thomas; Tahar, Houssem Ben; Cheriet, Farida

    2016-09-01

    Segmenting the retinal vessels from fundus images is a prerequisite for many CAD systems for the automatic detection of diabetic retinopathy lesions. So far, research efforts have concentrated mainly on the accurate localization of the large to medium diameter vessels. However, failure to detect the smallest vessels at the segmentation step can lead to false positive lesion detection counts in a subsequent lesion analysis stage. In this study, a new hybrid method for the segmentation of the smallest vessels is proposed. Line detection and perceptual organization techniques are combined in a multi-scale scheme. Small vessels are reconstructed from the perceptual-based approach via tracking and pixel painting. The segmentation was validated in a high resolution fundus image database including healthy and diabetic subjects using pixel-based as well as perceptual-based measures. The proposed method achieves 85.06% sensitivity rate, while the original multi-scale line detection method achieves 81.06% sensitivity rate for the corresponding images (p<0.05). The improvement in the sensitivity rate for the database is 6.47% when only the smallest vessels are considered (p<0.05). For the perceptual-based measure, the proposed method improves the detection of the vasculature by 7.8% against the original multi-scale line detection method (p<0.05).

  20. A Multi-Scale Algorithm for Graffito Advertisement Detection from Images of Real Estate

    NASA Astrophysics Data System (ADS)

    Yang, Jun; Zhu, Shi-Jiao

    There is a significant need to detect and extract the graffito advertisement embedded in the housing images automatically. However, it is a hard job to separate the advertisement region well since housing images generally have complex background. In this paper, a detecting algorithm which uses multi-scale Gabor filters to identify graffito regions is proposed. Firstly, multi-scale Gabor filters with different directions are applied to housing images, then the approach uses these frequency data to find likely graffito regions using the relationship of different channels, it exploits the ability of different filters technique to solve the detection problem with low computational efforts. Lastly, the method is tested on several real estate images which are embedded graffito advertisement to verify its robustness and efficiency. The experiments demonstrate graffito regions can be detected quite well.

  1. Multi-Scale Segmentation of High Resolution Remote Sensing Images by Integrating Multiple Features

    NASA Astrophysics Data System (ADS)

    Di, Y.; Jiang, G.; Yan, L.; Liu, H.; Zheng, S.

    2017-05-01

    Most of multi-scale segmentation algorithms are not aiming at high resolution remote sensing images and have difficulty to communicate and use layers' information. In view of them, we proposes a method of multi-scale segmentation of high resolution remote sensing images by integrating multiple features. First, Canny operator is used to extract edge information, and then band weighted distance function is built to obtain the edge weight. According to the criterion, the initial segmentation objects of color images can be gained by Kruskal minimum spanning tree algorithm. Finally segmentation images are got by the adaptive rule of Mumford-Shah region merging combination with spectral and texture information. The proposed method is evaluated precisely using analog images and ZY-3 satellite images through quantitative and qualitative analysis. The experimental results show that the multi-scale segmentation of high resolution remote sensing images by integrating multiple features outperformed the software eCognition fractal network evolution algorithm (highest-resolution network evolution that FNEA) on the accuracy and slightly inferior to FNEA on the efficiency.

  2. [Breeding habitat characteristics of red-crowned crane at Zhalong of Northeast China: a multi-scale approach based on TM and ASAR image data].

    PubMed

    Liu, Chun-Yue; Jiang, Hong-Xing; Zhang, Shu-Qing; Hou, Yun-Qiu; Lu, Jun

    2012-02-01

    Based on the Landsat TM and Envisat ASAR HH/HV imagery data and by using the GPS data of red-crowned crane nesting sites (n = 28) at Zhalong National Nature Reserve of Northeast China, the models of the breeding habitat selection of red-crowned crane at the Reserve were established by binary Logistic regression to identify the key variables for the habitat selection at eight spatial scales (30-240 m). The relative performance of the two models based on the Landsat TM and Envisat ASAR HH/HV databases was compared, and the prediction capacity of the models across the eight scales was approached. The overall precisions of the two models were satisfactory (> or = 69.0%). At scale 30 m, only variable TCA_2 entered with negative value into the model based on Landsat TM database, which indicated that the crane at this scale avoided selecting higher density reed marshes. At scales 60-120 m, the variable PCA_2 entered with positive value into the two models, indicating that the crane at these scales had higher demand of high density reed marshes to improve its concealment. At scale 90 m, the variable HV backward scatting coefficient also entered into the combined model, which indicated that water condition was the important factor for the habitat selection of the crane at this scale. At scales > 120 m, the texture information of the two satellite sensors started to be involved into the two models, indicating that at larger scales, the crane had decreasing demand on the vegetation features for its breeding habitat selection but increasing sensitivity to the anthropogenic disturbance factors. The introduction of ASAR variables into the models increased the prediction accuracy of the models markedly at all scales.

  3. Robust Face Recognition via Multi-Scale Patch-Based Matrix Regression.

    PubMed

    Gao, Guangwei; Yang, Jian; Jing, Xiaoyuan; Huang, Pu; Hua, Juliang; Yue, Dong

    2016-01-01

    In many real-world applications such as smart card solutions, law enforcement, surveillance and access control, the limited training sample size is the most fundamental problem. By making use of the low-rank structural information of the reconstructed error image, the so-called nuclear norm-based matrix regression has been demonstrated to be effective for robust face recognition with continuous occlusions. However, the recognition performance of nuclear norm-based matrix regression degrades greatly in the face of the small sample size problem. An alternative solution to tackle this problem is performing matrix regression on each patch and then integrating the outputs from all patches. However, it is difficult to set an optimal patch size across different databases. To fully utilize the complementary information from different patch scales for the final decision, we propose a multi-scale patch-based matrix regression scheme based on which the ensemble of multi-scale outputs can be achieved optimally. Extensive experiments on benchmark face databases validate the effectiveness and robustness of our method, which outperforms several state-of-the-art patch-based face recognition algorithms.

  4. Robust Face Recognition via Multi-Scale Patch-Based Matrix Regression

    PubMed Central

    Gao, Guangwei; Yang, Jian; Jing, Xiaoyuan; Huang, Pu; Hua, Juliang; Yue, Dong

    2016-01-01

    In many real-world applications such as smart card solutions, law enforcement, surveillance and access control, the limited training sample size is the most fundamental problem. By making use of the low-rank structural information of the reconstructed error image, the so-called nuclear norm-based matrix regression has been demonstrated to be effective for robust face recognition with continuous occlusions. However, the recognition performance of nuclear norm-based matrix regression degrades greatly in the face of the small sample size problem. An alternative solution to tackle this problem is performing matrix regression on each patch and then integrating the outputs from all patches. However, it is difficult to set an optimal patch size across different databases. To fully utilize the complementary information from different patch scales for the final decision, we propose a multi-scale patch-based matrix regression scheme based on which the ensemble of multi-scale outputs can be achieved optimally. Extensive experiments on benchmark face databases validate the effectiveness and robustness of our method, which outperforms several state-of-the-art patch-based face recognition algorithms. PMID:27525734

  5. Solving the problem of imaging resolution: stochastic multi-scale image fusion

    NASA Astrophysics Data System (ADS)

    Karsanina, Marina; Mallants, Dirk; Gilyazetdinova, Dina; Gerke, Kiril

    2016-04-01

    Structural features of porous materials define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, gas exchange between biologically active soil root zone and atmosphere, etc.) and solute transport. To characterize soil and rock microstructure X-ray microtomography is extremely useful. However, as any other imaging technique, this one also has a significant drawback - a trade-off between sample size and resolution. The latter is a significant problem for multi-scale complex structures, especially such as soils and carbonates. Other imaging techniques, for example, SEM/FIB-SEM or X-ray macrotomography can be helpful in obtaining higher resolution or wider field of view. The ultimate goal is to create a single dataset containing information from all scales or to characterize such multi-scale structure. In this contribution we demonstrate a general solution for merging multiscale categorical spatial data into a single dataset using stochastic reconstructions with rescaled correlation functions. The versatility of the method is demonstrated by merging three images representing macro, micro and nanoscale spatial information on porous media structure. Images obtained by X-ray microtomography and scanning electron microscopy were fused into a single image with predefined resolution. The methodology is sufficiently generic for implementation of other stochastic reconstruction techniques, any number of scales, any number of material phases, and any number of images for a given scale. The methodology can be further used to assess effective properties of fused porous media images or to compress voluminous spatial datasets for efficient data storage. Potential practical applications of this method are abundant in soil science, hydrology and petroleum engineering, as well as other geosciences. This work was partially supported by RSF grant 14-17-00658 (X-ray microtomography study of shale

  6. Multi-scale contrast enhancement of oriented features in 2D images using directional morphology

    NASA Astrophysics Data System (ADS)

    Das, Debashis; Mukhopadhyay, Susanta; Praveen, S. R. Sai

    2017-01-01

    This paper presents a multi-scale contrast enhancement scheme for improving the visual quality of directional features present in 2D gray scale images. Directional morphological filters are employed to locate and extract the scale-specific image features with different orientations which are subsequently stored in a set of feature images. The final enhanced image is constructed by weighted combination of these feature images with the original image. While construction, the feature images corresponding to progressively smaller scales are made to have higher proportion of contribution through the use of progressively larger weights. The proposed method has been formulated, implemented and executed on a set of real 2D gray scale images with oriented features. The experimental results visually establish the efficacy of the method. The proposed method has been compared with other similar methods both on subjective and objective basis and the overall performance is found to be satisfactory.

  7. Multi-scale X-ray Microtomography Imaging of Immiscible Fluids After Imbibition

    NASA Astrophysics Data System (ADS)

    Garing, C.; de Chalendar, J.; Voltolini, M.; Ajo Franklin, J. B.; Benson, S. M.

    2015-12-01

    A major issue for CO2 storage security is the efficiency and long-term reliability of the trapping mechanisms occurring in the reservoir where CO2 is injected. Residual trapping is one of the key processes for storage security beyond the primary stratigraphic seal. Although classical conceptual models of residual fluid trapping assume that disconnected ganglia are permanently immobilized, multiple mechanisms exist which could allow the remobilization of residually trapped CO2. The aim of this study is to quantify fluid phases saturation, connectivity and morphology after imbibition using x-ray microtomography in order to evaluate potential changes in droplets organization due to differences in capillary pressure between disconnected ganglia. Particular emphasis is placed on the effect of image resolution. Synchrotron-based x-ray microtomographic datasets of air-water spontaneous imbibition were acquired in sintered glass beads and sandstone samples with voxel sizes varying from 0.64 to 4.44 μm. The results show that for both sandstones the residual air phase is homogeneously distributed within the entire pore space and consists of disconnected clusters of multiple sizes and morphologies. The multi-scale analysis of subsamples of few pores and throats imaged at the same location of the sample reveals significant variations in the estimation of connectivity, size and shape of the fluid phases. This is particularly noticeable when comparing the results from the images with voxel sizes above 1 μm with the results from the images acquired with voxel sizes below 1 μm.

  8. Development and Characterization of Embedded Sensory Particles Using Multi-Scale 3D Digital Image Correlation

    NASA Technical Reports Server (NTRS)

    Cornell, Stephen R.; Leser, William P.; Hochhalter, Jacob D.; Newman, John A.; Hartl, Darren J.

    2014-01-01

    A method for detecting fatigue cracks has been explored at NASA Langley Research Center. Microscopic NiTi shape memory alloy (sensory) particles were embedded in a 7050 aluminum alloy matrix to detect the presence of fatigue cracks. Cracks exhibit an elevated stress field near their tip inducing a martensitic phase transformation in nearby sensory particles. Detectable levels of acoustic energy are emitted upon particle phase transformation such that the existence and location of fatigue cracks can be detected. To test this concept, a fatigue crack was grown in a mode-I single-edge notch fatigue crack growth specimen containing sensory particles. As the crack approached the sensory particles, measurements of particle strain, matrix-particle debonding, and phase transformation behavior of the sensory particles were performed. Full-field deformation measurements were performed using a novel multi-scale optical 3D digital image correlation (DIC) system. This information will be used in a finite element-based study to determine optimal sensory material behavior and density.

  9. A multi-scale multi-frequency deconvolution algorithm for synthesis imaging in radio interferometry

    NASA Astrophysics Data System (ADS)

    Rau, U.; Cornwell, T. J.

    2011-08-01

    Aims: We describe MS-MFS, a multi-scale multi-frequency deconvolution algorithm for wide-band synthesis-imaging, and present imaging results that illustrate the capabilities of the algorithm and the conditions under which it is feasible and gives accurate results. Methods: The MS-MFS algorithm models the wide-band sky-brightness distribution as a linear combination of spatial and spectral basis functions, and performs image-reconstruction by combining a linear-least-squares approach with iterative χ2 minimization. This method extends and combines the ideas used in the MS-CLEAN and MF-CLEAN algorithms for multi-scale and multi-frequency deconvolution respectively, and can be used in conjunction with existing wide-field imaging algorithms. We also discuss a simpler hybrid of spectral-line and continuum imaging methods and point out situations where it may suffice. Results: We show via simulations and application to multi-frequency VLA data and wideband EVLA data, that it is possible to reconstruct both spatial and spectral structure of compact and extended emission at the continuum sensitivity level and at the angular resolution allowed by the highest sampled frequency.

  10. An Investigation of Wavelet Bases for Grid-Based Multi-Scale Simulations Final Report

    SciTech Connect

    Baty, R.S.; Burns, S.P.; Christon, M.A.; Roach, D.W.; Trucano, T.G.; Voth, T.E.; Weatherby, J.R.; Womble, D.E.

    1998-11-01

    The research summarized in this report is the result of a two-year effort that has focused on evaluating the viability of wavelet bases for the solution of partial differential equations. The primary objective for this work has been to establish a foundation for hierarchical/wavelet simulation methods based upon numerical performance, computational efficiency, and the ability to exploit the hierarchical adaptive nature of wavelets. This work has demonstrated that hierarchical bases can be effective for problems with a dominant elliptic character. However, the strict enforcement of orthogonality was found to be less desirable than weaker semi-orthogonality or bi-orthogonality for solving partial differential equations. This conclusion has led to the development of a multi-scale linear finite element based on a hierarchical change of basis. The reproducing kernel particle method has been found to yield extremely accurate phase characteristics for hyperbolic problems while providing a convenient framework for multi-scale analyses.

  11. A multi-scale registration of urban aerial image with airborne lidar data

    NASA Astrophysics Data System (ADS)

    Huang, Shuo; Chen, Siying; Zhang, Yinchao; Guo, Pan; Chen, He

    2015-11-01

    This paper presented a multi-scale progressive registration method of airborne LiDAR data with aerial image. The cores of the proposed method lie in the coarse registration with road networks and the fine registration method using regularized building corners. During the two-stage registration, the exterior orientation parameters (EOP) are continually refined. By validation of the actual flight data of Dunhuang, the experimental result shows that the proposed method can obtain accurate results with low-precision initial EOP, also improve the automatic degree of registration.

  12. A multi-scale micromechanical investigation on thermal conductivity of cement-based composites

    NASA Astrophysics Data System (ADS)

    Liu, Jiahan; Xu, Shilang; Zeng, Qiang

    2017-01-01

    Cement-based composites (CBCs) are one of the most widely used materials in construction. An appealing characterization of thermal conductivity of CBCs plays an essential role to evaluate the energy consumption in buildings and to facilitate the development of novel thermal insulation materials. Based on Eshelby equivalent inclusion principle and multi-scale methodology, this paper attempted to present a generalized multi-scale micromechanical model in terms of thermal performance of the CBCs, which covers some classic models for thermal conductivity estimation. A Mori-Tanaka homogenization method was applied to investigate the thermal conductivity of the CBCs of different compounds, water-to-cement ratios and curing ages. In addition, saturation degree factor was considered. The results of this model are in good agreement with the experimental value, showing that the multi-scale model developed in this paper is able to evaluate the thermal conductivity of the CBCs in different conditions.

  13. Hi-fidelity multi-scale local processing for visually optimized far-infrared Herschel images

    NASA Astrophysics Data System (ADS)

    Li Causi, G.; Schisano, E.; Liu, S. J.; Molinari, S.; Di Giorgio, A.

    2016-07-01

    In the context of the "Hi-Gal" multi-band full-plane mapping program for the Galactic Plane, as imaged by the Herschel far-infrared satellite, we have developed a semi-automatic tool which produces high definition, high quality color maps optimized for visual perception of extended features, like bubbles and filaments, against the high background variations. We project the map tiles of three selected bands onto a 3-channel panorama, which spans the central 130 degrees of galactic longitude times 2.8 degrees of galactic latitude, at the pixel scale of 3.2", in cartesian galactic coordinates. Then we process this image piecewise, applying a custom multi-scale local stretching algorithm, enforced by a local multi-scale color balance. Finally, we apply an edge-preserving contrast enhancement to perform an artifact-free details sharpening. Thanks to this tool, we have thus produced a stunning giga-pixel color image of the far-infrared Galactic Plane that we made publicly available with the recent release of the Hi-Gal mosaics and compact source catalog.

  14. Multi-scale electromagnetic imaging of the Monte Aquila Fault (Agri Valley, Southern Italy)

    NASA Astrophysics Data System (ADS)

    Giocoli, Alessandro; Piscitelli, Sabatino; Romano, Gerardo; Balasco, Marianna; Lapenna, Vincenzo; Siniscalchi, Agata

    2010-05-01

    The Agri Valley is a NW-SE trending intermontane basin formed during the Quaternary times along the axial zone of the Southern Apennines thrust belt chain. This basin is about 30 Km long and 12 Km wide and is filled by Quaternary continental deposits, which cover down-thrown pre-Quaternary rocks of the Apennines chain. The Agri Valley was hit by the M 7.0, 1857 Basilicata earthquake (Branno et al., 1985), whose macroseismic field covered a wide sector of the Southern Apennines chain. The latest indications of Late Quaternary faulting processes in Agri Valley were reported in Maschio et al., (2005), which documented a unknown NE-dipping normal fault thanks to the finding of small-scale morphological features of recent tectonic activity. The identified structure was termed Monte Aquila Fault (MAF) and corresponds to the southern strand of the NW-SE trending Monti della Maddalena Fault System (Maschio et al., 2005; Burrato and Valensise, 2007). The NE-dipping MAF consists of a main northern segment, about 10 Km long, and two smaller segments with cumulate length of ~10 Km, thus bringing the total length to ~20 Km. The three segments are arranged in a right-stepping en-echelon pattern and are characterized by subtle geomorphic features. In order to provide more detailed and accurate information about the MAF, a strategy based on the application of complementary investigation tools was employed. In particular, multi-scale electromagnetic investigation, including Electrical Resistivity Tomography (ERT), Ground Penetrating Radar (GPR) and Magnetotelluric (MT) methods, was used to image the MAF from near-surface to several hundred metres depth. Large-scale MT investigation proved to be useful in detecting the MAF location down to several hundred meters depth, but it didn't show any shallow evidence about MAF. Conversely, ERT and GPR surveys evidenced signatures of normal-faulting activity at shallow depth (e.g., back-tilting of the bedrock, colluvial wedges, etc.). In

  15. Object-based class modelling for multi-scale riparian forest habitat mapping

    NASA Astrophysics Data System (ADS)

    Strasser, Thomas; Lang, Stefan

    2015-05-01

    Object-based class modelling allows for mapping complex, hierarchical habitat systems. The riparian zone, including forests, represents such a complex ecosystem. Forests within riparian zones are biologically high productive and characterized by a rich biodiversity; thus considered of high community interest with an imperative to be protected and regularly monitored. Satellite earth observation (EO) provides tools for capturing the current state of forest habitats such as forest composition including intermixture of non-native tree species. Here we present a semi-automated object based image analysis (OBIA) approach for the mapping of riparian forests by applying class modelling of habitats based on the European Nature Information System (EUNIS) habitat classifications and the European Habitats Directive (HabDir) Annex 1. A very high resolution (VHR) WorldView-2 satellite image provided the required spatial and spectral details for a multi-scale image segmentation and rule-base composition to generate a six-level hierarchical representation of riparian forest habitats. Thereby habitats were hierarchically represented within an image object hierarchy as forest stands, stands of homogenous tree species and single trees represented by sunlit tree crowns. 522 EUNIS level 3 (EUNIS-3) habitat patches with a mean patch size (MPS) of 12,349.64 m2 were modelled from 938 forest stand patches (MPS = 6868.20 m2) and 43,742 tree stand patches (MPS = 140.79 m2). The delineation quality of the modelled EUNIS-3 habitats (focal level) was quantitatively assessed to an expert-based visual interpretation showing a mean deviation of 11.71%.

  16. Transferring Multi-Scale Approaches from 3d City Modeling to Ifc-Based Tunnel Modeling

    NASA Astrophysics Data System (ADS)

    Borrmann, A.; Kolbe, T. H.; Donaubauer, A.; Steuer, H.; Jubierre, J. R.

    2013-09-01

    A multi-scale representation of the built environment is required to provide information with the adequate level of detail (LoD) for different use cases and objectives. This applies not only to the visualization of city and building models, but in particular to their use in the context of planning and analysis tasks. While in the field of Geographic Information Systems, the handling of multi-scale representations is well established and understood, no formal approaches for incorporating multi-scale methods exist in the field of Building Information Modeling (BIM) so far. However, these concepts are much needed to better support highly dynamic planning processes that make use of very rough information about the facility under design in the early stages and provide increasingly detailed and fine-grained information in later stages. To meet these demands, this paper presents a comprehensive concept for incorporating multi-scale representations with infrastructural building information models, with a particular focus on the representation of shield tunnels. Based on a detailed analysis of the data modeling methods used in CityGML for capturing multiscale representations and the requirements present in the context of infrastructure planning projects, we discuss potential extensions to the BIM data model Industry Foundation Classes (IFC). Particular emphasis is put on providing means for preserving the consistency of the representation across the different Levels-of-Detail (LoD). To this end we make use of a procedural geometry description which makes it possible to define explicit dependencies between geometric entities on different LoDs. The modification of an object on a coarse level consequently results in an automated update of all dependent objects on the finer levels. Finally we discuss the transformation of the IFC-based multi-scale tunnel model into a CityGML compliant tunnel representation.

  17. Robust segmentation of trabecular bone for in vivo CT imaging using anisotropic diffusion and multi-scale morphological reconstruction

    NASA Astrophysics Data System (ADS)

    Chen, Cheng; Jin, Dakai; Zhang, Xiaoliu; Levy, Steven M.; Saha, Punam K.

    2017-03-01

    Osteoporosis is associated with an increased risk of low-trauma fractures. Segmentation of trabecular bone (TB) is essential to assess TB microstructure, which is a key determinant of bone strength and fracture risk. Here, we present a new method for TB segmentation for in vivo CT imaging. The method uses Hessian matrix-guided anisotropic diffusion to improve local separability of trabecular structures, followed by a new multi-scale morphological reconstruction algorithm for TB segmentation. High sensitivity (0.93), specificity (0.93), and accuracy (0.92) were observed for the new method based on regional manual thresholding on in vivo CT images. Mechanical tests have shown that TB segmentation using the new method improved the ability of derived TB spacing measure for predicting actual bone strength (R2=0.83).

  18. Multi-scale feature extraction for learning-based classification of coronary artery stenosis

    NASA Astrophysics Data System (ADS)

    Tessmann, Matthias; Vega-Higuera, Fernando; Fritz, Dominik; Scheuering, Michael; Greiner, Günther

    2009-02-01

    Assessment of computed tomography coronary angiograms for diagnostic purposes is a mostly manual, timeconsuming task demanding a high degree of clinical experience. In order to support diagnosis, a method for reliable automatic detection of stenotic lesions in computed tomography angiograms is presented. Thereby, lesions are detected by boosting-based classification. Hence, a strong classifier is trained using the AdaBoost algorithm on annotated data. Subsequently, the resulting strong classification function is used in order to detect different types of coronary lesions in previously unseen data. As pattern recognition algorithms require a description of the objects to be classified, a novel approach for feature extraction in computed tomography angiograms is introduced. By generation of cylinder segments that approximate the vessel shape at multiple scales, feature values can be extracted that adequately describe the properties of stenotic lesions. As a result of the multi-scale approach, the algorithm is capable of dealing with the variability of stenotic lesion configuration. Evaluation of the algorithm was performed on a large database containing unseen segmented centerlines from cardiac computed tomography images. Results showed that the method was able to detect stenotic cardiovascular diseases with high sensitivity and specificity. Moreover, lesion based evaluation revealed that the majority of stenosis can be reliable identified in terms of position, type and extent.

  19. Multi-scale spectrally resolved quantitative fluorescence imaging system: towards neurosurgical guidance in glioma resection

    NASA Astrophysics Data System (ADS)

    Xie, Yijing; Thom, Maria; Miserocchi, Anna; McEvoy, Andrew W.; Desjardins, Adrien; Ourselin, Sebastien; Vercauteren, Tom

    2017-02-01

    In glioma resection surgery, the detection of tumour is often guided by using intraoperative fluorescence imaging notably with 5-ALA-PpIX, providing fluorescent contrast between normal brain tissue and the gliomas tissue to achieve improved tumour delineation and prolonged patient survival compared with the conventional white-light guided resection. However, the commercially available fluorescence imaging system relies on surgeon's eyes to visualise and distinguish the fluorescence signals, which unfortunately makes the resection subjective. In this study, we developed a novel multi-scale spectrally-resolved fluorescence imaging system and a computational model for quantification of PpIX concentration. The system consisted of a wide-field spectrally-resolved quantitative imaging device and a fluorescence endomicroscopic imaging system enabling optical biopsy. Ex vivo animal tissue experiments as well as human tumour sample studies demonstrated that the system was capable of specifically detecting the PpIX fluorescent signal and estimate the true concentration of PpIX in brain specimen.

  20. Improved convergence of gradient-based reconstruction using multi-scale models

    SciTech Connect

    Cunningham, G.S.; Hanson, K.M.; Koyfman, I.

    1996-05-01

    Geometric models have received increasing attention in medical imaging for tasks such as segmentation, reconstruction, restoration, and registration. In order to determine the best configuration of the geometric model in the context of any of these tasks, one needs to perform a difficult global optimization of an energy function that may have many local minima. Explicit models of geometry, also called deformable models, snakes, or active contours, have been used extensively to solve image segmentation problems in a non-Bayesian framework. Researchers have seen empirically that multi-scale analysis is useful for convergence to a configuration that is near the global minimum. In this type of analysis, the image data are convolved with blur functions of increasing resolution, and an optimal configuration of the snake is found for each blurred image. The configuration obtained using the highest resolution blur is used as the solution to the global optimization problem. In this article, the authors use explicit models of geometry for a variety of Bayesian estimation problems, including image segmentation, reconstruction and restoration. The authors introduce a multi-scale approach that blurs the geometric model, rather than the image data, and show that this approach turns a global, highly nonquadratic optimization into a sequence of local, approximately quadratic problems that converge to the global minimum. The result is a deterministic, robust, and efficient optimization strategy applicable to a wide variety of Bayesian estimation problems in which geometric models of images are an important component.

  1. A Multi-Scale Based Model for Composite Materials with Embedded PZT Filaments for Energy Harvesting

    NASA Astrophysics Data System (ADS)

    El-Etriby, Ahmed E.; Abdel-Meguid, Mohamed E.; Shalan, Khalid M.; Hatem, Tarek M.; Bahei-El-Din, Yehia A.

    Ambient vibrations are major source of wasted energy, exploiting properly such vibration can be converted to valuable energy and harvested to power up devices, i.e. electronic devices. Accordingly, energy harvesting using smart structures with active piezoelectric ceramics has gained wide interest over the past few years as a method for converting such wasted energy. This paper provides numerical and experimental analysis of piezoelectric fiber based composites for energy harvesting applications proposing a multi-scale modeling approach coupled with experimental verification.

  2. Physics-Based Multi-Scale Modeling of Shear Initiated Reactions in Energetic and Reactive Materials

    DTIC Science & Technology

    2010-04-01

    Physics-based Multi-scale Modeling of Shear Initiated Reactions in Energetic and Reactive Materials by John K. Brennan, Müge Fermen -Coker...Energetic and Reactive Materials John K. Brennan and Müge Fermen -Coker Weapons and Materials Research Directorate, ARL and Linhbao Tran Shock...Materials 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) John K. Brennan, Müge Fermen -Coker, and Linhbao Tran 5d

  3. Directional Multi-scale Modeling of High-Resolution Computed Tomography (HRCT) Lung Images for Diffuse Lung Disease Classification

    NASA Astrophysics Data System (ADS)

    Vo, Kiet T.; Sowmya, Arcot

    A directional multi-scale modeling scheme based on wavelet and contourlet transforms is employed to describe HRCT lung image textures for classifying four diffuse lung disease patterns: normal, emphysema, ground glass opacity (GGO) and honey-combing. Generalized Gaussian density parameters are used to represent the detail sub-band features obtained by wavelet and contourlet transforms. In addition, support vector machines (SVMs) with excellent performance in a variety of pattern classification problems are used as classifier. The method is tested on a collection of 89 slices from 38 patients, each slice of size 512x512, 16 bits/pixel in DICOM format. The dataset contains 70,000 ROIs of those slices marked by experienced radiologists. We employ this technique at different wavelet and contourlet transform scales for diffuse lung disease classification. The technique presented here has best overall sensitivity 93.40% and specificity 98.40%.

  4. Automated parameterisation for multi-scale image segmentation on multiple layers

    PubMed Central

    Drăguţ, L.; Csillik, O.; Eisank, C.; Tiede, D.

    2014-01-01

    We introduce a new automated approach to parameterising multi-scale image segmentation of multiple layers, and we implemented it as a generic tool for the eCognition® software. This approach relies on the potential of the local variance (LV) to detect scale transitions in geospatial data. The tool detects the number of layers added to a project and segments them iteratively with a multiresolution segmentation algorithm in a bottom-up approach, where the scale factor in the segmentation, namely, the scale parameter (SP), increases with a constant increment. The average LV value of the objects in all of the layers is computed and serves as a condition for stopping the iterations: when a scale level records an LV value that is equal to or lower than the previous value, the iteration ends, and the objects segmented in the previous level are retained. Three orders of magnitude of SP lags produce a corresponding number of scale levels. Tests on very high resolution imagery provided satisfactory results for generic applicability. The tool has a significant potential for enabling objectivity and automation of GEOBIA analysis. PMID:24748723

  5. Multi-Scale Optical Imaging of the Delayed Type Hypersensitivity Reaction Attenuated by Rapamycin

    PubMed Central

    Luo, Meijie; Zhang, Zhihong; Li, Hui; Qiao, Sha; Liu, Zheng; Fu, Ling; Shen, Guanxin; Luo, Qingming

    2014-01-01

    Neutrophils and monocytes/macrophages (MMs) play important roles in the development of cell-mediated delayed type hypersensitivity (DTH). However, the dynamics of neutrophils and MMs during the DTH reaction and how the immunosuppressant rapamycin modulates their behavior in vivo are rarely reported. Here, we take advantage of multi-scale optical imaging techniques and a footpad DTH reaction model to non-invasively investigate the dynamic behavior and properties of immune cells from the whole field of the footpad to the cellular level. During the classic elicitation phase of the DTH reaction, both neutrophils and MMs obviously accumulated at inflammatory foci at 24 h post-challenge. Rapamycin treatment resulted in advanced neutrophil recruitment and vascular hyperpermeability at an early stage (4 h), the reduced accumulation of neutrophils (> 50% inhibition ratio) at 48 h, and the delayed involvement of MMs in inflammatory foci. The motility parameters of immune cells in the rapamycin-treated reaction at 4 h post-challenge displayed similar mean velocities, arrest durations, mean displacements, and confinements as the classic DTH reaction at 24 h. These results indicate that rapamycin treatment shortened the initial preparation stage of the DTH reaction and attenuated its intensity, which may be due to the involvement of T helper type 2 cells or regulatory T cells. PMID:24465276

  6. Diagnosis of Plus Disease in Retinopathy of Prematurity Using Retinal Image multiScale Analysis

    PubMed Central

    Gelman, Rony; Martinez-Perez, M. Elena; Vanderveen, Deborah K.; Moskowitz, Anne; Fulton, Anne B.

    2005-01-01

    PURPOSE. To evaluate a semiautomated image analysis software package, Retinal Image multiScale Analysis (RISA), for the diagnosis of plus disease in preterm infants with retinopathy of prematurity (ROP). METHODS. Digital images of the posterior pole showing both disc and macula in preterm infants with ROP were analyzed with an enhanced version of RISA. Venules (N = 106) and arterioles (N = 44) were identified, and integrated curvature, diameter, and tortuosity of the vessels were calculated. After the RISA calculations were completed, the origins of the vessels were determined to be 32 eyes in 16 infants (12 eyes with plus disease, 20 with no plus disease, as diagnosed by ophthalmic examination). Vessels were sorted into two groups—plus disease and no plus disease—and each RISA parameter was compared using the Mann-Whitney test. For each parameter, sensitivity and specificity were plotted as a function of cutoff criterion, receiver operating characteristic (ROC) curves were constructed, and the areas under the curve (AUC) were calculated. RESULTS. For both arterioles and venules, each of the three parameters was significantly larger for the plus disease group. For instance, the median estimated arteriolar and venular diameters were approximately 12 μm greater in plus disease. Sensitivity and specificity plots indicated good accuracy of each parameter for the diagnosis of plus disease. The AUC showed that curvature had the highest diagnostic accuracy (0.911 for arterioles, 0.824 for venules). CONCLUSIONS. The strong performance of RISA parameters in this sample suggests that RISA may be useful for diagnosing plus disease in preterm infants with ROP. PMID:16303973

  7. Diagnosis of plus disease in retinopathy of prematurity using Retinal Image multiScale Analysis.

    PubMed

    Gelman, Rony; Martinez-Perez, M Elena; Vanderveen, Deborah K; Moskowitz, Anne; Fulton, Anne B

    2005-12-01

    To evaluate a semiautomated image analysis software package, Retinal Image multiScale Analysis (RISA), for the diagnosis of plus disease in preterm infants with retinopathy of prematurity (ROP). Digital images of the posterior pole showing both disc and macula in preterm infants with ROP were analyzed with an enhanced version of RISA. Venules (N = 106) and arterioles (N = 44) were identified, and integrated curvature, diameter, and tortuosity of the vessels were calculated. After the RISA calculations were completed, the origins of the vessels were determined to be 32 eyes in 16 infants (12 eyes with plus disease, 20 with no plus disease, as diagnosed by ophthalmic examination). Vessels were sorted into two groups-plus disease and no plus disease-and each RISA parameter was compared using the Mann-Whitney test. For each parameter, sensitivity and specificity were plotted as a function of cutoff criterion, receiver operating characteristic (ROC) curves were constructed, and the areas under the curve (AUC) were calculated. For both arterioles and venules, each of the three parameters was significantly larger for the plus disease group. For instance, the median estimated arteriolar and venular diameters were approximately 12 mum greater in plus disease. Sensitivity and specificity plots indicated good accuracy of each parameter for the diagnosis of plus disease. The AUC showed that curvature had the highest diagnostic accuracy (0.911 for arterioles, 0.824 for venules). The strong performance of RISA parameters in this sample suggests that RISA may be useful for diagnosing plus disease in preterm infants with ROP.

  8. Meanie3D - a mean-shift based, multivariate, multi-scale clustering and tracking algorithm

    NASA Astrophysics Data System (ADS)

    Simon, Jürgen-Lorenz; Malte, Diederich; Silke, Troemel

    2014-05-01

    Project OASE is the one of 5 work groups at the HErZ (Hans Ertel Centre for Weather Research), an ongoing effort by the German weather service (DWD) to further research at Universities concerning weather prediction. The goal of project OASE is to gain an object-based perspective on convective events by identifying them early in the onset of convective initiation and follow then through the entire lifecycle. The ability to follow objects in this fashion requires new ways of object definition and tracking, which incorporate all the available data sets of interest, such as Satellite imagery, weather Radar or lightning counts. The Meanie3D algorithm provides the necessary tool for this purpose. Core features of this new approach to clustering (object identification) and tracking are the ability to identify objects using the mean-shift algorithm applied to a multitude of variables (multivariate), as well as the ability to detect objects on various scales (multi-scale) using elements of Scale-Space theory. The algorithm works in 2D as well as 3D without modifications. It is an extension of a method well known from the field of computer vision and image processing, which has been tailored to serve the needs of the meteorological community. In spite of the special application to be demonstrated here (like convective initiation), the algorithm is easily tailored to provide clustering and tracking for a wide class of data sets and problems. In this talk, the demonstration is carried out on two of the OASE group's own composite sets. One is a 2D nationwide composite of Germany including C-Band Radar (2D) and Satellite information, the other a 3D local composite of the Bonn/Jülich area containing a high-resolution 3D X-Band Radar composite.

  9. Automated macular pathology diagnosis in retinal OCT images using multi-scale spatial pyramid with local binary patterns.

    PubMed

    Liu, Yu-Ying; Chen, Mei; Ishikawa, Hiroshi; Wollstein, Gadi; Schuman, Joel S; Rehg, James M

    2010-01-01

    We address a novel problem domain in the analysis of optical coherence tomography (OCT) images: the diagnosis of multiple macular pathologies in retinal OCT images. The goal is to identify the presence of normal macula and each of three types of macular pathologies, namely, macular hole, macular edema, and age-related macular degeneration, in the OCT slice centered at the fovea. We use a machine learning approach based on global image descriptors formed from a multi-scale spatial pyramid. Our local descriptors are dimension-reduced Local Binary Pattern histograms, which are capable of encoding texture information from OCT images of the retina. Our representation operates at multiple spatial scales and granularities, leading to robust performance. We use 2-class Support Vector Machine classifiers to identify the presence of normal macula and each of the three pathologies. We conducted extensive experiments on a large dataset consisting of 326 OCT scans from 136 patients. The results show that the proposed method is very effective.

  10. Multi-scale sustainability assessments for biomass-based and coal-based fuels in China.

    PubMed

    Man, Yi; Xiao, Honghua; Cai, Wei; Yang, Siyu

    2017-12-01

    Transportation liquid fuels production is heavily depend on oil. In recent years, developing biomass based and coal based fuels are regarded as promising alternatives for non-petroleum based fuels in China. With the rapid growth of constructing and planning b biomass based and coal based fuels production projects, sustainability assessments are needed to simultaneously consider the resource, the economic, and the environmental factors. This paper performs multi-scale analyses on the biomass based and coal based fuels in China. The production cost, life cycle cost, and ecological life cycle cost (ELCC) of these synfuels are investigated to compare their pros to cons and reveal the sustainability. The results show that BTL fuels has high production cost. It lacks of economic attractiveness. However, insignificant resource cost and environmental cost lead to a substantially lower ELCC, which may indicate better ecological sustainability. CTL fuels, on the contrary, is lower in production cost and reliable for economic benefit. But its coal consumption and pollutant emissions are both serious, leading to overwhelming resource cost and environmental cost. A shifting from petroleum to CTL fuels could double the ELCC, posing great threat to the sustainability of the entire fuels industry. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Classification of Urban Feature from Unmanned Aerial Vehicle Images Using Gasvm Integration and Multi-Scale Segmentation

    NASA Astrophysics Data System (ADS)

    Modiri, M.; Salehabadi, A.; Mohebbi, M.; Hashemi, A. M.; Masumi, M.

    2015-12-01

    The use of UAV in the application of photogrammetry to obtain cover images and achieve the main objectives of the photogrammetric mapping has been a boom in the region. The images taken from REGGIOLO region in the province of, Italy Reggio -Emilia by UAV with non-metric camera Canon Ixus and with an average height of 139.42 meters were used to classify urban feature. Using the software provided SURE and cover images of the study area, to produce dense point cloud, DSM and Artvqvtv spatial resolution of 10 cm was prepared. DTM area using Adaptive TIN filtering algorithm was developed. NDSM area was prepared with using the difference between DSM and DTM and a separate features in the image stack. In order to extract features, using simultaneous occurrence matrix features mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation for each of the RGB band image was used Orthophoto area. Classes used to classify urban problems, including buildings, trees and tall vegetation, grass and vegetation short, paved road and is impervious surfaces. Class consists of impervious surfaces such as pavement conditions, the cement, the car, the roof is stored. In order to pixel-based classification and selection of optimal features of classification was GASVM pixel basis. In order to achieve the classification results with higher accuracy and spectral composition informations, texture, and shape conceptual image featureOrthophoto area was fencing. The segmentation of multi-scale segmentation method was used.it belonged class. Search results using the proposed classification of urban feature, suggests the suitability of this method of classification complications UAV is a city using images. The overall accuracy and kappa coefficient method proposed in this study, respectively, 47/93% and 84/91% was.

  12. Multi-scale brain networks.

    PubMed

    Betzel, Richard F; Bassett, Danielle S

    2016-11-11

    The network architecture of the human brain has become a feature of increasing interest to the neuroscientific community, largely because of its potential to illuminate human cognition, its variation over development and aging, and its alteration in disease or injury. Traditional tools and approaches to study this architecture have largely focused on single scales-of topology, time, and space. Expanding beyond this narrow view, we focus this review on pertinent questions and novel methodological advances for the multi-scale brain. We separate our exposition into content related to multi-scale topological structure, multi-scale temporal structure, and multi-scale spatial structure. In each case, we recount empirical evidence for such structures, survey network-based methodological approaches to reveal these structures, and outline current frontiers and open questions. Although predominantly peppered with examples from human neuroimaging, we hope that this account will offer an accessible guide to any neuroscientist aiming to measure, characterize, and understand the full richness of the brain's multiscale network structure-irrespective of species, imaging modality, or spatial resolution.

  13. Multi-scale structural changes of starch-based material during microwave and conventional heating.

    PubMed

    Zhu, Jie; Li, Lin; Zhang, Shuyan; Li, Xiaoxi; Zhang, Binjia

    2016-11-01

    This work revealed the influence of thermal processing on the microstructural, mesoscopic and molecular scale structures and thus the plasticizer migration of the starch ester films. Thermal processing promoted the permeation of water molecules to hinder the shrink of the amorphous macromolecules. That is, the swelling of the amorphous macromolecules diminished the ordered regions to a certain degree, resulting in the enlarged amorphous regions. Along with slight degradation of the macromolecules, the crystallites were partially disorganized, as indicated by a reduced relative crystallinity. These multi-scale structural changes of the films and the thermally enhanced mobility of plasticizer molecules synergistically enhanced the plasticizer migration. This study not only enables a well understanding of how thermal treatment alters the plasticizer migration of starch-based films from a multi-scale structural view, but also hints to our future work that rationally modulating the structural features of starch-based film may effectively control the migration of chemicals. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. Label-free, multi-scale imaging of ex-vivo mouse brain using spatial light interference microscopy

    NASA Astrophysics Data System (ADS)

    Min, Eunjung; Kandel, Mikhail E.; Ko, Chemyong J.; Popescu, Gabriel; Jung, Woonggyu; Best-Popescu, Catherine

    2016-12-01

    Brain connectivity spans over broad spatial scales, from nanometers to centimeters. In order to understand the brain at multi-scale, the neural network in wide-field has been visualized in detail by taking advantage of light microscopy. However, the process of staining or addition of fluorescent tags is commonly required, and the image contrast is insufficient for delineation of cytoarchitecture. To overcome this barrier, we use spatial light interference microscopy to investigate brain structure with high-resolution, sub-nanometer pathlength sensitivity without the use of exogenous contrast agents. Combining wide-field imaging and a mosaic algorithm developed in-house, we show the detailed architecture of cells and myelin, within coronal olfactory bulb and cortical sections, and from sagittal sections of the hippocampus and cerebellum. Our technique is well suited to identify laminar characteristics of fiber tract orientation within white matter, e.g. the corpus callosum. To further improve the macro-scale contrast of anatomical structures, and to better differentiate axons and dendrites from cell bodies, we mapped the tissue in terms of its scattering property. Based on our results, we anticipate that spatial light interference microscopy can potentially provide multiscale and multicontrast perspectives of gross and microscopic brain anatomy.

  15. Label-free, multi-scale imaging of ex-vivo mouse brain using spatial light interference microscopy

    PubMed Central

    Min, Eunjung; Kandel, Mikhail E.; Ko, CheMyong J; Popescu, Gabriel; Jung, Woonggyu; Best-Popescu, Catherine

    2016-01-01

    Brain connectivity spans over broad spatial scales, from nanometers to centimeters. In order to understand the brain at multi-scale, the neural network in wide-field has been visualized in detail by taking advantage of light microscopy. However, the process of staining or addition of fluorescent tags is commonly required, and the image contrast is insufficient for delineation of cytoarchitecture. To overcome this barrier, we use spatial light interference microscopy to investigate brain structure with high-resolution, sub-nanometer pathlength sensitivity without the use of exogenous contrast agents. Combining wide-field imaging and a mosaic algorithm developed in-house, we show the detailed architecture of cells and myelin, within coronal olfactory bulb and cortical sections, and from sagittal sections of the hippocampus and cerebellum. Our technique is well suited to identify laminar characteristics of fiber tract orientation within white matter, e.g. the corpus callosum. To further improve the macro-scale contrast of anatomical structures, and to better differentiate axons and dendrites from cell bodies, we mapped the tissue in terms of its scattering property. Based on our results, we anticipate that spatial light interference microscopy can potentially provide multiscale and multicontrast perspectives of gross and microscopic brain anatomy. PMID:28009019

  16. Label-free, multi-scale imaging of ex-vivo mouse brain using spatial light interference microscopy.

    PubMed

    Min, Eunjung; Kandel, Mikhail E; Ko, CheMyong J; Popescu, Gabriel; Jung, Woonggyu; Best-Popescu, Catherine

    2016-12-23

    Brain connectivity spans over broad spatial scales, from nanometers to centimeters. In order to understand the brain at multi-scale, the neural network in wide-field has been visualized in detail by taking advantage of light microscopy. However, the process of staining or addition of fluorescent tags is commonly required, and the image contrast is insufficient for delineation of cytoarchitecture. To overcome this barrier, we use spatial light interference microscopy to investigate brain structure with high-resolution, sub-nanometer pathlength sensitivity without the use of exogenous contrast agents. Combining wide-field imaging and a mosaic algorithm developed in-house, we show the detailed architecture of cells and myelin, within coronal olfactory bulb and cortical sections, and from sagittal sections of the hippocampus and cerebellum. Our technique is well suited to identify laminar characteristics of fiber tract orientation within white matter, e.g. the corpus callosum. To further improve the macro-scale contrast of anatomical structures, and to better differentiate axons and dendrites from cell bodies, we mapped the tissue in terms of its scattering property. Based on our results, we anticipate that spatial light interference microscopy can potentially provide multiscale and multicontrast perspectives of gross and microscopic brain anatomy.

  17. Multi scale Disaster Risk Reduction Systems Space and Community based Experiences over HKH Region

    NASA Astrophysics Data System (ADS)

    Gurung, D. R.; Shrestha, M.; Shrestha, N.; Debnath, B.; Jishi, G.; Bajracharya, R.; Dhonju, H. K.; Pradhan, S.

    2014-11-01

    An increasing trend in the recurrence of natural disasters and associated impacts due to Floods, Glacier Lake out bursts, landslides and forest fire is reported over Hindu Kush Himalyan (HKH) region. Climate change and anthropogenic coupled factors are identified as primary factors for such increased vulnerability. The large degree of poverty, lack of infrastructure, poor accessibility and uncertainties involved in understanding high altitude land surface and climate dynamics poses serious challenges in reducing disaster vulnerability and mitigating disaster impacts. In this context effective development of Disaster Risk Reduction (DRR) protocols and mechanisms have been realized as an urgent need. The paper presents the adoption and experiences of multi scale DRR systems across different Himalayan member countries ranging from community based indigenous early warning to space based emergency response and decision support systems. The Establishment of a Regional Flood Information System (HKH-HYCOS) over Ganges-Brahmaputra-Meghna (GBM) and Indus river basins promoted the timely exchange of flood data and information for the reduction of flood vulnerability within and among the participating countries. Satellite based forest fire alert systems evoked significant response among diverse stakeholders to optimize fire incidence and control. Satellite rainfall estimation products, satellite altimetry based flood early warning systems, flood inundation modelling and products, model derived hydrology flow products from different global data-sharing networks constitutes diverse information to support multi scale DRR systems. Community-based Flood Early Warning System (FEWS) enabled by wireless technology established over the Singara and Jiadhal rivers in Assam also stands as one of the promising examples of minimizing flood risk. Disaster database and information system and decision support tools in Nepal serves as potential tool to support diverse stakeholders.

  18. A Physiologically Based, Multi-Scale Model of Skeletal Muscle Structure and Function

    PubMed Central

    Röhrle, O.; Davidson, J. B.; Pullan, A. J.

    2012-01-01

    Models of skeletal muscle can be classified as phenomenological or biophysical. Phenomenological models predict the muscle’s response to a specified input based on experimental measurements. Prominent phenomenological models are the Hill-type muscle models, which have been incorporated into rigid-body modeling frameworks, and three-dimensional continuum-mechanical models. Biophysically based models attempt to predict the muscle’s response as emerging from the underlying physiology of the system. In this contribution, the conventional biophysically based modeling methodology is extended to include several structural and functional characteristics of skeletal muscle. The result is a physiologically based, multi-scale skeletal muscle finite element model that is capable of representing detailed, geometrical descriptions of skeletal muscle fibers and their grouping. Together with a well-established model of motor-unit recruitment, the electro-physiological behavior of single muscle fibers within motor units is computed and linked to a continuum-mechanical constitutive law. The bridging between the cellular level and the organ level has been achieved via a multi-scale constitutive law and homogenization. The effect of homogenization has been investigated by varying the number of embedded skeletal muscle fibers and/or motor units and computing the resulting exerted muscle forces while applying the same excitatory input. All simulations were conducted using an anatomically realistic finite element model of the tibialis anterior muscle. Given the fact that the underlying electro-physiological cellular muscle model is capable of modeling metabolic fatigue effects such as potassium accumulation in the T-tubular space and inorganic phosphate build-up, the proposed framework provides a novel simulation-based way to investigate muscle behavior ranging from motor-unit recruitment to force generation and fatigue. PMID:22993509

  19. A Combined In Vitro Imaging and Multi-Scale Modeling System for Studying the Role of Cell Matrix Interactions in Cutaneous Wound Healing.

    PubMed

    De Jesus, Aribet M; Aghvami, Maziar; Sander, Edward A

    2016-01-01

    Many cell types remodel the extracellular matrix of the tissues they inhabit in response to a wide range of environmental stimuli, including mechanical cues. Such is the case in dermal wound healing, where fibroblast migrate into and remodel the provisional fibrin matrix in a complex manner that depends in part on the local mechanical environment and the evolving multi-scale mechanical interactions of the system. In this study, we report on the development of an image-based multi-scale mechanical model that predicts the short-term (24 hours), structural reorganization of a fibrin gel by fibroblasts. These predictive models are based on an in vitro experimental system where clusters of fibroblasts (i.e., explants) were spatially arranged into a triangular geometry onto the surface of fibrin gels that were subjected to either Fixed or Free in-plane mechanical constraints. Experimentally, regional differences in short-term structural remodeling and cell migration were observed for the two gel boundary conditions. A pilot experiment indicated that these small differences in the short-term remodeling of the fibrin gel translate into substantial differences in long-term (4 weeks) remodeling, particularly in terms of collagen production. The multi-scale models were able to predict some regional differences in remodeling and qualitatively similar reorganization patterns for the two boundary conditions. However, other aspects of the model, such as the magnitudes and rates of deformation of gel, did not match the experiments. These discrepancies between model and experiment provide fertile ground for challenging model assumptions and devising new experiments to enhance our understanding of how this multi-scale system functions. These efforts will ultimately improve the predictions of the remodeling process, particularly as it relates to dermal wound healing and the reduction of patient scarring. Such models could be used to recommend patient-specific mechanical-based

  20. A Combined In Vitro Imaging and Multi-Scale Modeling System for Studying the Role of Cell Matrix Interactions in Cutaneous Wound Healing

    PubMed Central

    2016-01-01

    Many cell types remodel the extracellular matrix of the tissues they inhabit in response to a wide range of environmental stimuli, including mechanical cues. Such is the case in dermal wound healing, where fibroblast migrate into and remodel the provisional fibrin matrix in a complex manner that depends in part on the local mechanical environment and the evolving multi-scale mechanical interactions of the system. In this study, we report on the development of an image-based multi-scale mechanical model that predicts the short-term (24 hours), structural reorganization of a fibrin gel by fibroblasts. These predictive models are based on an in vitro experimental system where clusters of fibroblasts (i.e., explants) were spatially arranged into a triangular geometry onto the surface of fibrin gels that were subjected to either Fixed or Free in-plane mechanical constraints. Experimentally, regional differences in short-term structural remodeling and cell migration were observed for the two gel boundary conditions. A pilot experiment indicated that these small differences in the short-term remodeling of the fibrin gel translate into substantial differences in long-term (4 weeks) remodeling, particularly in terms of collagen production. The multi-scale models were able to predict some regional differences in remodeling and qualitatively similar reorganization patterns for the two boundary conditions. However, other aspects of the model, such as the magnitudes and rates of deformation of gel, did not match the experiments. These discrepancies between model and experiment provide fertile ground for challenging model assumptions and devising new experiments to enhance our understanding of how this multi-scale system functions. These efforts will ultimately improve the predictions of the remodeling process, particularly as it relates to dermal wound healing and the reduction of patient scarring. Such models could be used to recommend patient-specific mechanical-based

  1. Multi-scaled license plate detection based on the label-moveable maximal MSER clique

    NASA Astrophysics Data System (ADS)

    Gu, Qin; Yang, Jianyu; Kong, Lingjiang; Cui, Guolong

    2015-08-01

    In this paper, we consider a robust vehicle license plate detection problem for intelligent transportation systems in the presence of various illumination situations. We propose a robust and fast multi-scaled license plate detection and location algorithm, which exploits a Label-Moveable Maximal MSER clique. Specifically, first, we extract the candidate character regions using the Maximally Stable Extremal Region (MSER) features. Second, we divide each candidate character region into four types and extract the suspected initial node (the top-left character) based on its neighbor MSER distribution characteristic. Third, we label each candidate character region to accomplish license detection and location based on the detected suspected initial node and the corresponding label-moveable maximal MSER clique. The robust of license plate detection, the accuracy of character labeling for license location, and the improvement of calculation efficiency are evaluated via the real data.

  2. Dorsal hand vein recognition based on Gabor multi-orientation fusion and multi-scale HOG features

    NASA Astrophysics Data System (ADS)

    Han, Tuo; Wang, Zhiyong; Yang, Xiaoping

    2016-10-01

    Kinds of factors such as illumination and hand gestures would reduce the accuracy of dorsal hand vein recognition. Aiming at single hand vein image with low contrast and simple structure, an algorithm combining Gabor multi-orientation features fusion with Multi-scale Histogram of Oriented Gradient (MS-HOG) is proposed in this paper. With this method, more features will be extracted to improve the recognition accuracy. Firstly, diagrams of multi-scale and multi-orientation are acquired using Gabor transformation, then the Gabor features of the same scale and multi-orientation will be fused, and the features of the correspondent fusion diagrams will be extracted with a HOG operator of a certain scale. Finally the multi-scale cascaded histograms will be obtained for hand vein recognition. The experimental results show that our method not only improve the recognition accuracy but has good robustness in dorsal hand vein recognition.

  3. Enhancement tuning and control for high dynamic range images in multi-scale locally adaptive contrast enhancement algorithms

    NASA Astrophysics Data System (ADS)

    Cvetkovic, Sascha D.; Schirris, Johan; de With, Peter H. N.

    2009-01-01

    For real-time imaging in surveillance applications, visibility of details is of primary importance to ensure customer confidence. If we display High Dynamic-Range (HDR) scenes whose contrast spans four or more orders of magnitude on a conventional monitor without additional processing, results are unacceptable. Compression of the dynamic range is therefore a compulsory part of any high-end video processing chain because standard monitors are inherently Low- Dynamic Range (LDR) devices with maximally two orders of display dynamic range. In real-time camera processing, many complex scenes are improved with local contrast enhancements, bringing details to the best possible visibility. In this paper, we show how a multi-scale high-frequency enhancement scheme, in which gain is a non-linear function of the detail energy, can be used for the dynamic range compression of HDR real-time video camera signals. We also show the connection of our enhancement scheme to the processing way of the Human Visual System (HVS). Our algorithm simultaneously controls perceived sharpness, ringing ("halo") artifacts (contrast) and noise, resulting in a good balance between visibility of details and non-disturbance of artifacts. The overall quality enhancement, suitable for both HDR and LDR scenes, is based on a careful selection of the filter types for the multi-band decomposition and a detailed analysis of the signal per frequency band.

  4. Structural and multi-scale rheophysical investigation of diphasic magneto-sensitive materials based on biopolymers.

    PubMed

    Roger, Stéphane; Sang, Yan Yip Cheung; Bee, Agnès; Perzynski, Régine; Di Meglio, Jean Marc; Ponton, Alain

    2015-08-01

    We present a structural and a multi-scale rheophysical investigation of magneto-sensitive materials based on biopolymers, namely aqueous solutions of sodium alginate incorporating magnetic maghemite nanoparticles, functionalized with adsorbed negative citrate ions. The large alginate ionic strength impacts the structure and the rheology of these nanocomposites in zero magnetic field. In given physico-chemical conditions, the system is fluid and homogeneous on macroscopic scales while it is diphasic on microscopic ones, containing micro-droplets coming from the demixion of the system. These micro-droplets are liquid and deformable under magnetic field. Their under-field elongation and their zero-field relaxation are directly observed by optical microscopy to determine their interfacial tension, their magnetic susceptibility and their internal viscosity. A structural analysis of the solutions of alginate chains and of the phase-separated mixtures of alginate and nanoparticles by Small Angle Scattering completes the local description of the system.

  5. Fault diagnosis of wind bearing based on multi-scale wavelet kernel extreme learning machine

    NASA Astrophysics Data System (ADS)

    Zhu, Siwen; Jiao, Bin

    2017-08-01

    The principle of kernel Extreme Learning Machine (ELM) is demonstrated. On this basis, a multi - scale wavelet kernel extreme learning machine is proposed. The multi-scale wavelet kernel is used as the kernel function of the extreme learning machine. The test shows that it is an achievable extreme learning machine. Experiments show that, using the multi-scale wavelet kernel extreme learning machine in the wind turbine bearing fault diagnosis has higher classification accuracy and speed than the support vector machine classification algorithm, and has excellent application value.

  6. A dissipation-based control method for the multi-scale modelling of quasi-brittle materials

    NASA Astrophysics Data System (ADS)

    Massart, Thierry J.; Peerlings, Ron H. J.; Geers, Marc G. D.

    2005-07-01

    Multi-scale models based on computational homogenisation are nowadays developed for the simulation of complex material behaviour. The use of homogenisation techniques on finite-sized representative volume elements in the presence of quasi-brittle damage may lead to the presence of snap-backs in the macroscopic material response. A methodology to simulate this type of response in the multi-scale technique is proposed, based on the control of the dissipation at the mesoscopic scale. To cite this article: T.J. Massart et al., C. R. Mecanique 333 (2005).

  7. SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.

    PubMed

    Solovyev, Alexey; Mikheev, Maxim; Zhou, Leming; Dutta-Moscato, Joyeeta; Ziraldo, Cordelia; An, Gary; Vodovotz, Yoram; Mi, Qi

    2010-01-01

    Multi-scale modeling of complex biological systems remains a central challenge in the systems biology community. A method of dynamic knowledge representation known as agent-based modeling enables the study of higher level behavior emerging from discrete events performed by individual components. With the advancement of computer technology, agent-based modeling has emerged as an innovative technique to model the complexities of systems biology. In this work, the authors describe SPARK (Simple Platform for Agent-based Representation of Knowledge), a framework for agent-based modeling specifically designed for systems-level biomedical model development. SPARK is a stand-alone application written in Java. It provides a user-friendly interface, and a simple programming language for developing Agent-Based Models (ABMs). SPARK has the following features specialized for modeling biomedical systems: 1) continuous space that can simulate real physical space; 2) flexible agent size and shape that can represent the relative proportions of various cell types; 3) multiple spaces that can concurrently simulate and visualize multiple scales in biomedical models; 4) a convenient graphical user interface. Existing ABMs of diabetic foot ulcers and acute inflammation were implemented in SPARK. Models of identical complexity were run in both NetLogo and SPARK; the SPARK-based models ran two to three times faster.

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

    PubMed Central

    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.

    2016-01-01

    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. PMID:26935567

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

    PubMed

    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

    2016-03-03

    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.

  10. 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.

  11. Asymmetric cold/warm rolling simulation by crystal plasticity multi-scale finite element analysis based on crystallographic homogenization

    SciTech Connect

    Onishi, Koshiro; Sakamoto, Hidetoshi; Kuramae, Hiroyuki; Morimoto, Hideo; Nakamachi, Eiji

    2010-06-15

    The purpose of this study is forming a high formability aluminum alloy sheet metal by controlling the microcrystal structure and the texture. So asymmetric rolling is applied to the material process. Analysis method is crystal plasticity multi-scale finite element analysis based on crystallographic homogenization.

  12. A simple multi-scale Gaussian smoothing-based strategy for automatic chromatographic peak extraction.

    PubMed

    Fu, Hai-Yan; Guo, Jun-Wei; Yu, Yong-Jie; Li, He-Dong; Cui, Hua-Peng; Liu, Ping-Ping; Wang, Bing; Wang, Sheng; Lu, Peng

    2016-06-24

    Peak detection is a critical step in chromatographic data analysis. In the present work, we developed a multi-scale Gaussian smoothing-based strategy for accurate peak extraction. The strategy consisted of three stages: background drift correction, peak detection, and peak filtration. Background drift correction was implemented using a moving window strategy. The new peak detection method is a variant of the system used by the well-known MassSpecWavelet, i.e., chromatographic peaks are found at local maximum values under various smoothing window scales. Therefore, peaks can be detected through the ridge lines of maximum values under these window scales, and signals that are monotonously increased/decreased around the peak position could be treated as part of the peak. Instrumental noise was estimated after peak elimination, and a peak filtration strategy was performed to remove peaks with signal-to-noise ratios smaller than 3. The performance of our method was evaluated using two complex datasets. These datasets include essential oil samples for quality control obtained from gas chromatography and tobacco plant samples for metabolic profiling analysis obtained from gas chromatography coupled with mass spectrometry. Results confirmed the reasonability of the developed method. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Wavelet based multi-scale shape features on arbitrary surfaces for cortical thickness discrimination

    PubMed Central

    Kim, Won Hwa; Pachauri, Deepti; Hatt, Charles; Chung, Moo K.; Johnson, Sterling C.; Singh, Vikas

    2012-01-01

    Hypothesis testing on signals defined on surfaces (such as the cortical surface) is a fundamental component of a variety of studies in Neuroscience. The goal here is to identify regions that exhibit changes as a function of the clinical condition under study. As the clinical questions of interest move towards identifying very early signs of diseases, the corresponding statistical differences at the group level invariably become weaker and increasingly hard to identify. Indeed, after a multiple comparisons correction is adopted (to account for correlated statistical tests over all surface points), very few regions may survive. In contrast to hypothesis tests on point-wise measurements, in this paper, we make the case for performing statistical analysis on multi-scale shape descriptors that characterize the local topological context of the signal around each surface vertex. Our descriptors are based on recent results from harmonic analysis, that show how wavelet theory extends to non-Euclidean settings (i.e., irregular weighted graphs). We provide strong evidence that these descriptors successfully pick up group-wise differences, where traditional methods either fail or yield unsatisfactory results. Other than this primary application, we show how the framework allows performing cortical surface smoothing in the native space without mappint to a unit sphere. PMID:25284968

  14. A wireless video multicasting scheme based on multi-scale compressed sensing

    NASA Astrophysics Data System (ADS)

    Wang, Anhong; Wu, Qingdian; Ma, Xiaoli; Zeng, Bing

    2015-12-01

    Video multicast is becoming more and more popular in wireless multimedia applications, in which one major challenge is to offer heterogeneous users with a graceful degradation against varying packet loss ratios and channel noise. In this paper, we propose a multi-scale compressed sensing-based wireless video multicast scheme, abbreviated as MCS-cast. The encoder of MCS-cast decomposes each video frame through a discrete wavelet transform (DWT) and explores an optimized compressed sensing (CS) rate to sample/measure each DWT level. The CS measurements are then packed in such a way that all packets are made as equally important as possible, while each packet includes different percentages of different DWT levels. Finally, the packets are transmitted via an analog-like modulator with mapping of the measurements into a very dense constellation. We demonstrate that because of larger percentages of more important DWT levels in each packet, packet loss leads to a much reduced influence on the reconstruction quality. Experimental results show that our MCS-cast preserves the property of graceful degradation for heterogeneous users and can outperform the state-of-the-art SoftCast by up to 3 dB in PSNR at high packet loss ratios (over the same noisy channel).

  15. Multi-scale marine biodiversity patterns inferred efficiently from habitat image processing.

    PubMed

    Mellin, Camille; Parrott, Lael; Andréfouët, Serge; Bradshaw, Corey J A; MacNeil, M Aaron; Caley, M Julian

    2012-04-01

    Cost-effective proxies of biodiversity and species abundance, applicable across a range of spatial scales, are needed for setting conservation priorities and planning action. We outline a rapid, efficient, and low-cost measure of spectral signal from digital habitat images that, being an effective proxy for habitat complexity, correlates with species diversity and requires little image processing or interpretation. We validated this method for coral reefs of the Great Barrier Reef (GBR), Australia, across a range of spatial scales (1 m to 10 km), using digital photographs of benthic communities at the transect scale and high-resolution Landsat satellite images at the reef scale. We calculated an index of image-derived spatial heterogeneity, the mean information gain (MIG), for each scale and related it to univariate (species richness and total abundance summed across species) and multivariate (species abundance matrix) measures of fish community structure, using two techniques that account for the hierarchical structure of the data: hierarchical (mixed-effect) linear models and distance-based partial redundancy analysis. Over the length and breadth of the GBR, MIG alone explained up to 29% of deviance in fish species richness, 33% in total fish abundance, and 25% in fish community structure at multiple scales, thus demonstrating the possibility of easily and rapidly exploiting spatial information contained in digital images to complement existing methods for inferring diversity and abundance patterns among fish communities. Thus, the spectral signal of unprocessed remotely sensed images provides an efficient and low-cost way to optimize the design of surveys used in conservation planning. In data-sparse situations, this simple approach also offers a viable method for rapid assessment of potential local biodiversity, particularly where there is little local capacity in terms of skills or resources for mounting in-depth biodiversity surveys.

  16. Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems

    PubMed Central

    Cilfone, Nicholas A.; Kirschner, Denise E.; Linderman, Jennifer J.

    2015-01-01

    Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228

  17. Multi-scale mechanism based life prediction of polymer matrix composites for high temperature airframe applications

    NASA Astrophysics Data System (ADS)

    Upadhyaya, Priyank

    A multi-scale mechanism-based life prediction model is developed for high-temperature polymer matrix composites (HTPMC) for high temperature airframe applications. In the first part of this dissertation the effect of Cloisite 20A (C20A) nano-clay compounding on the thermo-oxidative weight loss and the residual stresses due to thermal oxidation for a thermoset polymer bismaleimide (BMI) are investigated. A three-dimensional (3-D) micro-mechanics based finite element analysis (FEA) was conducted to investigate the residual stresses due to thermal oxidation using an in-house FEA code (NOVA-3D). In the second part of this dissertation, a novel numerical-experimental methodology is outlined to determine cohesive stress and damage evolution parameters for pristine as well as isothermally aged (in air) polymer matrix composites. A rate-dependent viscoelastic cohesive layer model was implemented in an in-house FEA code to simulate the delamination initiation and propagation in unidirectional polymer composites before and after aging. Double cantilever beam (DCB) experiments were conducted (at UT-Dallas) on both pristine and isothermally aged IM-7/BMI composite specimens to determine the model parameters. The J-Integral based approach was adapted to extract cohesive stresses near the crack tip. Once the damage parameters had been characterized, the test-bed FEA code employed a micromechanics based viscoelastic cohesive layer model to numerically simulate the DCB experiment. FEA simulation accurately captures the macro-scale behavior (load-displacement history) simultaneously with the micro-scale behavior (crack-growth history).

  18. Potential habitat of Javan Hawk-Eagle based on multi-scale approach and its implication for conservation

    NASA Astrophysics Data System (ADS)

    Nurfatimah, C.; Syartinilia; Mulyani, Y. A.

    2017-01-01

    In Indonesia the Javan Hawk-Eagle has been designated as one of the 25 top priority protected species to be increased by 10% of current population number. Lack of suitable habitat is most likely the reason for the decline of the species in landscapes subject to major human modification. Central part of Java Island has suffered the most severe forest damage and fragmentation compared to the western part and eastern part of the island. This study presents the number of predicted suitable habitats for Javan Hawk-Eagle in the central part of Java Island based on habitat probability model. Multi-scale approach was being used to determine the accuracy level of patches reading between different image resolutions. 38 patches were detected at 30 m2, 28 patches at 90 m2, and 19 patches were detected at 250 m2 images resolutions. Higher reading implied more landscape structures within different regions should be considered during management of habitat conservation. Therefore, larger scale of conservation management application should be conducted as well.

  19. Constructal multi-scale structure of PCM-based heat sinks

    NASA Astrophysics Data System (ADS)

    Salimpour, Mohammad Reza; Kalbasi, Rasool; Lorenzini, Giulio

    2017-03-01

    This paper inquires the effectiveness of a PCM-based heat sink as a reliable solution to portable electronic devices. This sink is composed of a PCM with low thermal conductivity and fins to boost its conductivity. The optimization is subjected to fixed heat sink volume filled with PCM between vertical equidistant fins. New fins are installed in the unheated space existing in each enclosure which is not involved in thermal distribution from vertical fins to the PCM. Based on the same principle, new fins generations are augmented stepwise to the multi-scale structure. The steps of adding fins will continue up to the point that the objective function reaches its maximal value, i.e., maximizing the longest safe operation time without allowing the electronics to reach the critical temperature. The results indicate that in each length of the enclosure, the optimum volume fraction and the best fins distance values exist in which the heat sink performance becomes maximum, and adding more fins lowers the performance of the heat sink. Increasing the enclosure's length by 2n does not change them. For an enclosure with constant length, the optimal number of steps for adding fins within the enclosure is a function of the fin thickness. The results indicate that increasing the thickness changes the optimal number of adding fins inside the enclosure (normally a decrease). As the fin thickness is lowered, there will be a higher effect by adding vertical fins in the enclosure. Numerical simulations cover the Rayleigh number range 2× 105≤ RaH ≤ 2.7× 108, where H is the heat sink height.

  20. Constructal multi-scale structure of PCM-based heat sinks

    NASA Astrophysics Data System (ADS)

    Salimpour, Mohammad Reza; Kalbasi, Rasool; Lorenzini, Giulio

    2016-11-01

    This paper inquires the effectiveness of a PCM-based heat sink as a reliable solution to portable electronic devices. This sink is composed of a PCM with low thermal conductivity and fins to boost its conductivity. The optimization is subjected to fixed heat sink volume filled with PCM between vertical equidistant fins. New fins are installed in the unheated space existing in each enclosure which is not involved in thermal distribution from vertical fins to the PCM. Based on the same principle, new fins generations are augmented stepwise to the multi-scale structure. The steps of adding fins will continue up to the point that the objective function reaches its maximal value, i.e., maximizing the longest safe operation time without allowing the electronics to reach the critical temperature. The results indicate that in each length of the enclosure, the optimum volume fraction and the best fins distance values exist in which the heat sink performance becomes maximum, and adding more fins lowers the performance of the heat sink. Increasing the enclosure's length by 2n does not change them. For an enclosure with constant length, the optimal number of steps for adding fins within the enclosure is a function of the fin thickness. The results indicate that increasing the thickness changes the optimal number of adding fins inside the enclosure (normally a decrease). As the fin thickness is lowered, there will be a higher effect by adding vertical fins in the enclosure. Numerical simulations cover the Rayleigh number range 2× 105≤ RaH ≤ 2.7× 108 , where H is the heat sink height.

  1. Multi-scale textural feature extraction and particle swarm optimization based model selection for false positive reduction in mammography.

    PubMed

    Zyout, Imad; Czajkowska, Joanna; Grzegorzek, Marcin

    2015-12-01

    The high number of false positives and the resulting number of avoidable breast biopsies are the major problems faced by current mammography Computer Aided Detection (CAD) systems. False positive reduction is not only a requirement for mass but also for calcification CAD systems which are currently deployed for clinical use. This paper tackles two problems related to reducing the number of false positives in the detection of all lesions and masses, respectively. Firstly, textural patterns of breast tissue have been analyzed using several multi-scale textural descriptors based on wavelet and gray level co-occurrence matrix. The second problem addressed in this paper is the parameter selection and performance optimization. For this, we adopt a model selection procedure based on Particle Swarm Optimization (PSO) for selecting the most discriminative textural features and for strengthening the generalization capacity of the supervised learning stage based on a Support Vector Machine (SVM) classifier. For evaluating the proposed methods, two sets of suspicious mammogram regions have been used. The first one, obtained from Digital Database for Screening Mammography (DDSM), contains 1494 regions (1000 normal and 494 abnormal samples). The second set of suspicious regions was obtained from database of Mammographic Image Analysis Society (mini-MIAS) and contains 315 (207 normal and 108 abnormal) samples. Results from both datasets demonstrate the efficiency of using PSO based model selection for optimizing both classifier hyper-parameters and parameters, respectively. Furthermore, the obtained results indicate the promising performance of the proposed textural features and more specifically, those based on co-occurrence matrix of wavelet image representation technique.

  2. Hierarchical Multi-Scale Approach To Validation and Uncertainty Quantification of Hyper-Spectral Image Modeling

    SciTech Connect

    Engel, David W.; Reichardt, Thomas A.; Kulp, Thomas J.; Graff, David; Thompson, Sandra E.

    2016-09-17

    Validating predictive models and quantifying uncertainties inherent in the modeling process is a critical component of the HARD Solids Venture program [1]. Our current research focuses on validating physics-based models predicting the optical properties of solid materials for arbitrary surface morphologies and characterizing the uncertainties in these models. We employ a systematic and hierarchical approach by designing physical experiments and comparing the experimental results with the outputs of computational predictive models. We illustrate this approach through an example comparing a micro-scale forward model to an idealized solid-material system and then propagating the results through a system model to the sensor level. Our efforts should enhance detection reliability of the hyper-spectral imaging technique and the confidence in model utilization and model outputs by users and stakeholders.

  3. Hierarchical multi-scale approach to validation and uncertainty quantification of hyper-spectral image modeling

    NASA Astrophysics Data System (ADS)

    Engel, Dave W.; Reichardt, Thomas A.; Kulp, Thomas J.; Graff, David L.; Thompson, Sandra E.

    2016-05-01

    Validating predictive models and quantifying uncertainties inherent in the modeling process is a critical component of the HARD Solids Venture program [1]. Our current research focuses on validating physics-based models predicting the optical properties of solid materials for arbitrary surface morphologies and characterizing the uncertainties in these models. We employ a systematic and hierarchical approach by designing physical experiments and comparing the experimental results with the outputs of computational predictive models. We illustrate this approach through an example comparing a micro-scale forward model to an idealized solid-material system and then propagating the results through a system model to the sensor level. Our efforts should enhance detection reliability of the hyper-spectral imaging technique and the confidence in model utilization and model outputs by users and stakeholders.

  4. On the combined use of radar systems for multi-scale imaging of transport infrastructures

    NASA Astrophysics Data System (ADS)

    Catapano, I.; Bavusi, M.; Loperte, A.; Crocco, L.; Soldovieri, F.

    2012-04-01

    Ground Penetrating Radar (GPR) systems are worth to be considered as in situ non invasive diagnostic tools capable of assessing stability and integrity of transport infrastructures. As a matter of fact, by exploiting the interactions among probing electromagnetic waves and hidden objects, they provide images of the inner status of the spatial region under test from which infer risk factors, such as deformations and oxidization of the reinforcement bars as well as water infiltrations, crack and air gaps. With respect to the assessment of concrete infrastructures integrity, the reconstruction capabilities of GPR systems have been widely investigated [1,2]. However, the demand for diagnostic tools capable of providing detailed and real time information motivates the design and the performance evaluation of novel technologies and data processing methodologies aimed not only to effectively detect hidden anomalies but also to estimate their geometrical features. In this framework, this communication aims at investigating the advantages offered by the joint use of two GPR systems both of them equipped with a specific tomographic imaging approach. The first considered system is a time domain GPR equipped with a 1.5GHz shielded antenna, which is suitable for quick and good resolution surveys of the shallower layers of the structure. As second system, the holographic radar Rascan-4/4000 [3,4] is taken into account, due to its capability of providing holograms of hidden targets from the amplitude of the interference signal arising between the backscattered field and a reference signal. The imaging capabilities of both the GPR tools are enhanced by means of model based data processing approaches, which afford the imaging as a linear inverse scattering problem. Mathematical details on the inversion strategies will be provided at the conference. The combined use of the above GPR systems allows to perform multi-resolution surveys of the region under test, whose aim is, first of

  5. Good match exploration for thermal infrared face recognition based on YWF-SIFT with multi-scale fusion

    NASA Astrophysics Data System (ADS)

    Bai, Junfeng; Ma, Yong; Li, Jing; Li, Hao; Fang, Yu; Wang, Rui; Wang, Hongyuan

    2014-11-01

    Stable local feature detection is a critical prerequisite in the problem of infrared (IR) face recognition. Recently, Scale Invariant Feature Transform (SIFT) is introduced for feature detection in an infrared face frame, which is achieved by applying a simple and effective averaging window with SIFT termed as Y-styled Window Filter (YWF). However, the thermal IR face frame has an intrinsic characteristic such as lack of feature points (keypoints); therefore, the performance of the YWF-SIFT method will be inevitably influenced when it was used for IR face recognition. In this paper, we propose a novel method combining multi-scale fusion with YWF-SIFT to explore more good feature matches. The multi-scale fusion is performed on a thermal IR frame and a corresponding auxiliary visual frame generated from an off-the-shelf low-cost visual camera. The fused image is more informative, and typically contains much more stable features. Besides, the use of YWF-SIFT method enables us to establish feature correspondences more accurately. Quantitative experimental results demonstrate that our algorithm is able to significantly improve the quantity of feature points by approximately 38%. As a result, the performance of YWF-SIFT with multi-scale fusion is enhanced about 12% in infrared human face recognition.

  6. Vision-based multi-scaled vehicle detection and distance relevant mix tracking for driver assistance system

    NASA Astrophysics Data System (ADS)

    Gu, Qin; Yang, Jianyu; Zhai, Yuqiang; Kong, Lingjiang

    2015-04-01

    This paper aims to improve the robustness of vision-based multi-scaled vehicle detection and tracking for an actual driver assistance system. Considering the problem of discontinuity of detection and tracking for multi-scaled vehicles especially in an ultra-close area, we propose a novel detection framework which concludes short-range local feature (license plate) detection and long-range skeleton detection. Specially, the rear license plate can be located accurately by introducing a multi-scaled morphological operator and analyzing the color information. Then, vehicles in a long supervising range can be detected with a Look-up Table-based AdaBoost classifier synchronically. Finally, an inverse perspective mapping-based tracking strategy is proposed to unite the location results in the framework. It is proved to make up the leak vehicle detection in the near supervising area and improve the robustness of tracking. The accuracy of license-based detection and the robust mix tracking have both been testified in several groups of experiments.

  7. Multi-scale modeling of fiber and fabric reinforced cement based composites

    NASA Astrophysics Data System (ADS)

    Soranakom, Chote

    With an increased use of fiber reinforced concrete in structural applications, proper characterization techniques and development of design guides are needed. This dissertation presents a multi-scale modeling approach for fiber and fabric reinforced cement-based composites. A micromechanics-based model of the yarn pullout mechanism due to the failure of the interfacial zone is presented. The effect of mechanical anchorage of transverse yarns is simulated using nonlinear spring elements. The yarn pullout mechanism was used in a meso-scale modeling approach to simulate the yarn bridging force in the crack evolution process. The tensile stress-strain response of a tension specimen that experiences distributed cracking can be simulated using a generalized finite difference approach. The stiffness degradation, tension stiffening, crack spacing evolution, and crack width characteristics of cement composites can be derived using matrix, interface and fiber properties. The theoretical models developed for fabric reinforced cement composites were then extended to cover other types of fiber reinforced concrete such as shotcrete, glass fiber reinforced concrete (GFRC), steel fiber reinforced concrete (SFRC), ferrocement and other conventional composite systems. The uniaxial tensile stress-strain response was used to formulate a generalized parametric closed-form solution for predicting flexural behavior of various composites at the macro-structural level. The flexural behaviors of these composites were modeled in a unified manner by means of a moment-curvature relationship based on the uniaxial material models. A variety of theoretical models were developed to address the various mechanisms including: an analytical yarn pullout model; a nonlinear finite difference fabric pullout model; a nonlinear finite difference tension model; closed-form solutions for strain-softening materials; closed-form solutions for strain-softening/hardening materials; and closed-form solutions for

  8. Physics-Based Multi-Scale Modeling of Shear Initiated Reactions in Energetic and Reactive Materials

    DTIC Science & Technology

    2009-03-01

    Phys. 1972, 5, 1921. 7. McQuarrie , D. A., Statistical Mechanics , Harper: New York, 1976. 8. Chase, M. W.; Davies, C. A.; Downey, J. R.; Frurip, D. J...munitions due to fragment impact. Present computational capabilities in continuum mechanics codes used by Army designers do not possess the capability to...into the continuum mechanics code CTH, and perform simulations for HEs and RMs. 2 Figure 1. Schematic of multi-scale shear initiation model. As

  9. Selective ensemble modeling load parameters of ball mill based on multi-scale frequency spectral features and sphere criterion

    NASA Astrophysics Data System (ADS)

    Tang, Jian; Yu, Wen; Chai, Tianyou; Liu, Zhuo; Zhou, Xiaojie

    2016-01-01

    It is difficult to model multi-frequency signal, such as mechanical vibration and acoustic signals of wet ball mill in the mineral grinding process. In this paper, these signals are decomposed into multi-scale intrinsic mode functions (IMFs) by the empirical mode decomposition (EMD) technique. A new adaptive multi-scale spectral features selection approach based on sphere criterion (SC) is applied to these IMFs frequency spectra. The candidate sub-models are constructed by the partial least squares (PLS) with the selected features. Finally, the branch and bound based selective ensemble (BBSEN) algorithm is applied to select and combine these ensemble sub-models. This method can be easily extended to regression and classification problems with multi-time scale signal. We successfully apply this approach to a laboratory-scale ball mill. The shell vibration and acoustic signals are used to model mill load parameters. The experimental results demonstrate that this novel approach is more effective than the other modeling methods based on multi-scale frequency spectral features.

  10. A multi-scale biomechanical model based on the physiological structure and lignocellulose components of wheat straw.

    PubMed

    Chen, Longjian; Li, Aiwei; He, Xueqin; Han, Lujia

    2015-11-20

    Biomechanical behavior is a fundamental property for the efficient utilization of wheat straw in such applications as fuel and renewable materials. Tensile experiments and lignocellulose analyses were performed on three types of wheat straw. A multi-scale finite element model composed of the microscopic model of the microfibril equivalent volume element and the macroscopic model of straw tissue was proposed based on the physiological structure and lignocellulose components of wheat straw. The tensile properties of wheat straw were simulated by ANSYS software. The predicted stress-strain data were compared with the observed data, and good correspondence was achieved for all three types of wheat straw. The validated multi-scale finite-element (FE) model was then used to investigate the effect of the lignocellulose components on the biomechanical properties of wheat straw. More than 80% of stress is carried by the cellulose fiber, whereas the strain is mainly carried by the amorphous cellulose.

  11. Analysis of Decadal Vegetation Dynamics Using Multi-Scale Satellite Images

    NASA Astrophysics Data System (ADS)

    Chiang, Y.; Chen, K.

    2013-12-01

    This study aims at quantifying vegetation fractional cover (VFC) by incorporating multi-resolution satellite images, including Formosat-2(RSI), SPOT(HRV/HRG), Landsat (MSS/TM) and Terra/Aqua(MODIS), to investigate long-term and seasonal vegetation dynamics in Taiwan. We used 40-year NDVI records for derivation of VFC, with field campaigns routinely conducted to calibrate the critical NDVI threshold. Given different sensor capabilities in terms of their spatial and spectral properties, translation and infusion of NDVIs was used to assure NDVI coherence and to determine the fraction of vegetation cover at different spatio-temporal scales. Based on the proposed method, a bimodal sequence of intra-annual VFC which corresponds to the dual-cropping agriculture pattern was observed. Compared to seasonal VFC variation (78~90%), decadal VFC reveals moderate oscillations (81~86%), which were strongly linked with landuse changes and several major disturbances. This time-series mapping of VFC can be used to examine vegetation dynamics and its response associated with short-term and long-term anthropogenic/natural events.

  12. A multi-scale superpixel classification approach to the detection of regions of interest in whole slide histopathology images

    NASA Astrophysics Data System (ADS)

    Bejnordi, Babak E.; Litjens, Geert; Hermsen, Meyke; Karssemeijer, Nico; van der Laak, Jeroen A. W. M.

    2015-03-01

    This paper presents a new algorithm for automatic detection of regions of interest in whole slide histopathological images. The proposed algorithm generates and classifies superpixels at multiple resolutions to detect regions of interest. The algorithm emulates the way the pathologist examines the whole slide histopathology image by processing the image at low magnifications and performing more sophisticated analysis only on areas requiring more detailed information. However, instead of the traditional usage of fixed sized rectangular patches for the identification of relevant areas, we use superpixels as the visual primitives to detect regions of interest. Rectangular patches can span multiple distinct structures, thus degrade the classification performance. The proposed multi-scale superpixel classification approach yields superior performance for the identification of the regions of interest. For the evaluation, a set of 10 whole slide histopathology images of breast tissue were used. Empirical evaluation of the performance of our proposed algorithm relative to expert manual annotations shows that the algorithm achieves an area under the Receiver operating characteristic (ROC) curve of 0.958, demonstrating its efficacy for the detection of regions of interest.

  13. Sparse signal decomposition method based on multi-scale chirplet and its application to the fault diagnosis of gearboxes

    NASA Astrophysics Data System (ADS)

    Peng, Fuqiang; Yu, Dejie; Luo, Jiesi

    2011-02-01

    Based on the chirplet path pursuit and the sparse signal decomposition method, a new sparse signal decomposition method based on multi-scale chirplet is proposed and applied to the decomposition of vibration signals from gearboxes in fault diagnosis. An over-complete dictionary with multi-scale chirplets as its atoms is constructed using the method. Because of the multi-scale character, this method is superior to the traditional sparse signal decomposition method wherein only a single scale is adopted, and is more applicable to the decomposition of non-stationary signals with multi-components whose frequencies are time-varying. When there are faults in a gearbox, the vibration signals collected are usually AM-FM signals with multiple components whose frequencies vary with the rotational speed of the shaft. The meshing frequency and modulating frequency, which vary with time, can be derived by the proposed method and can be used in gearbox fault diagnosis under time-varying shaft-rotation speed conditions, where the traditional signal processing methods are always blocked. Both simulations and experiments validate the effectiveness of the proposed method.

  14. Automatic event detection in low SNR microseismic signals based on multi-scale permutation entropy and a support vector machine

    NASA Astrophysics Data System (ADS)

    Jia, Rui-Sheng; Sun, Hong-Mei; Peng, Yan-Jun; Liang, Yong-Quan; Lu, Xin-Ming

    2016-12-01

    Microseismic monitoring is an effective means for providing early warning of rock or coal dynamical disasters, and its first step is microseismic event detection, although low SNR microseismic signals often cannot effectively be detected by routine methods. To solve this problem, this paper presents permutation entropy and a support vector machine to detect low SNR microseismic events. First, an extraction method of signal features based on multi-scale permutation entropy is proposed by studying the influence of the scale factor on the signal permutation entropy. Second, the detection model of low SNR microseismic events based on the least squares support vector machine is built by performing a multi-scale permutation entropy calculation for the collected vibration signals, constructing a feature vector set of signals. Finally, a comparative analysis of the microseismic events and noise signals in the experiment proves that the different characteristics of the two can be fully expressed by using multi-scale permutation entropy. The detection model of microseismic events combined with the support vector machine, which has the features of high classification accuracy and fast real-time algorithms, can meet the requirements of online, real-time extractions of microseismic events.

  15. Automatic event detection in low SNR microseismic signals based on multi-scale permutation entropy and a support vector machine

    NASA Astrophysics Data System (ADS)

    Jia, Rui-Sheng; Sun, Hong-Mei; Peng, Yan-Jun; Liang, Yong-Quan; Lu, Xin-Ming

    2017-07-01

    Microseismic monitoring is an effective means for providing early warning of rock or coal dynamical disasters, and its first step is microseismic event detection, although low SNR microseismic signals often cannot effectively be detected by routine methods. To solve this problem, this paper presents permutation entropy and a support vector machine to detect low SNR microseismic events. First, an extraction method of signal features based on multi-scale permutation entropy is proposed by studying the influence of the scale factor on the signal permutation entropy. Second, the detection model of low SNR microseismic events based on the least squares support vector machine is built by performing a multi-scale permutation entropy calculation for the collected vibration signals, constructing a feature vector set of signals. Finally, a comparative analysis of the microseismic events and noise signals in the experiment proves that the different characteristics of the two can be fully expressed by using multi-scale permutation entropy. The detection model of microseismic events combined with the support vector machine, which has the features of high classification accuracy and fast real-time algorithms, can meet the requirements of online, real-time extractions of microseismic events.

  16. Seeing is believing - multi-scale spatio-temporal imaging towards in vivo cell biology.

    PubMed

    Follain, Gautier; Mercier, Luc; Osmani, Naël; Harlepp, Sébastien; Goetz, Jacky G

    2017-01-01

    Life is driven by a set of biological events that are naturally dynamic and tightly orchestrated from the single molecule to entire organisms. Although biochemistry and molecular biology have been essential in deciphering signaling at a cellular and organismal level, biological imaging has been instrumental for unraveling life processes across multiple scales. Imaging methods have considerably improved over the past decades and now allow to grasp the inner workings of proteins, organelles, cells, organs and whole organisms. Not only do they allow us to visualize these events in their most-relevant context but also to accurately quantify underlying biomechanical features and, so, provide essential information for their understanding. In this Commentary, we review a palette of imaging (and biophysical) methods that are available to the scientific community for elucidating a wide array of biological events. We cover the most-recent developments in intravital imaging, light-sheet microscopy, super-resolution imaging, and correlative light and electron microscopy. In addition, we illustrate how these technologies have led to important insights in cell biology, from the molecular to the whole-organism resolution. Altogether, this review offers a snapshot of the current and state-of-the-art imaging methods that will contribute to the understanding of life and disease. © 2017. Published by The Company of Biologists Ltd.

  17. A feasibility study on the measurement of tree trunks in forests using multi-scale vertical images

    NASA Astrophysics Data System (ADS)

    Berveglieri, A.; Oliveira, R. O.; Tommaselli, A. M. G.

    2014-06-01

    The determination of the Diameter at Breast Height (DBH) is an important variable that contributes to several studies on forest, e.g., environmental monitoring, tree growth, volume of wood, and biomass estimation. This paper presents a preliminary technique for the measurement of tree trunks using terrestrial images collected with a panoramic camera in nadir view. A multi-scale model is generated with these images. Homologue points on the trunk surface are measured over the images and their ground coordinates are determined by intersection of rays. The resulting XY coordinates of each trunk, defining an arc shape, can be used as observations in a circle fitting by least squares. Then, the DBH of each trunk is calculated using an estimated radius. Experiments were performed in two urban forest areas to assess the approach. In comparison with direct measurements on the trunks taken with a measuring tape, the discrepancies presented a Root Mean Square Error (RMSE) of 1.8 cm with a standard deviation of 0.7 cm. These results demonstrate compatibility with manual measurements and confirm the feasibility of the proposed technique.

  18. Fusion of Multi-Scale Dems from Descent and Navcm Images of CHANG'E-3 Using Compressed Sensing Method

    NASA Astrophysics Data System (ADS)

    Peng, M.; Wan, W.; Liu, Z.; Di, K.

    2017-07-01

    The multi-source DEMs generated using the images acquired in the descent and landing phase and after landing contain supplementary information, and this makes it possible and beneficial to produce a higher-quality DEM through fusing the multi-scale DEMs. The proposed fusion method consists of three steps. First, source DEMs are split into small DEM patches, then the DEM patches are classified into a few groups by local density peaks clustering. Next, the grouped DEM patches are used for sub-dictionary learning by stochastic coordinate coding. The trained sub-dictionaries are combined into a dictionary for sparse representation. Finally, the simultaneous orthogonal matching pursuit (SOMP) algorithm is used to achieve sparse representation. We use the real DEMs generated from Chang'e-3 descent images and navigation camera (Navcam) stereo images to validate the proposed method. Through the experiments, we have reconstructed a seamless DEM with the highest resolution and the largest spatial coverage among the input data. The experimental results demonstrated the feasibility of the proposed method.

  19. Multi-scale Morphological Image Enhancement of Chest Radiographs by a Hybrid Scheme.

    PubMed

    Alavijeh, Fatemeh Shahsavari; Mahdavi-Nasab, Homayoun

    2015-01-01

    Chest radiography is a common diagnostic imaging test, which contains an enormous amount of information about a patient. However, its interpretation is highly challenging. The accuracy of the diagnostic process is greatly influenced by image processing algorithms; hence enhancement of the images is indispensable in order to improve visibility of the details. This paper aims at improving radiograph parameters such as contrast, sharpness, noise level, and brightness to enhance chest radiographs, making use of a triangulation method. Here, contrast limited adaptive histogram equalization technique and noise suppression are simultaneously performed in wavelet domain in a new scheme, followed by morphological top-hat and bottom-hat filtering. A unique implementation of morphological filters allows for adjustment of the image brightness and significant enhancement of the contrast. The proposed method is tested on chest radiographs from Japanese Society of Radiological Technology database. The results are compared with conventional enhancement techniques such as histogram equalization, contrast limited adaptive histogram equalization, Retinex, and some recently proposed methods to show its strengths. The experimental results reveal that the proposed method can remarkably improve the image contrast while keeping the sensitive chest tissue information so that radiologists might have a more precise interpretation.

  20. Multi-scale Morphological Image Enhancement of Chest Radiographs by a Hybrid Scheme

    PubMed Central

    Alavijeh, Fatemeh Shahsavari; Mahdavi-Nasab, Homayoun

    2015-01-01

    Chest radiography is a common diagnostic imaging test, which contains an enormous amount of information about a patient. However, its interpretation is highly challenging. The accuracy of the diagnostic process is greatly influenced by image processing algorithms; hence enhancement of the images is indispensable in order to improve visibility of the details. This paper aims at improving radiograph parameters such as contrast, sharpness, noise level, and brightness to enhance chest radiographs, making use of a triangulation method. Here, contrast limited adaptive histogram equalization technique and noise suppression are simultaneously performed in wavelet domain in a new scheme, followed by morphological top-hat and bottom-hat filtering. A unique implementation of morphological filters allows for adjustment of the image brightness and significant enhancement of the contrast. The proposed method is tested on chest radiographs from Japanese Society of Radiological Technology database. The results are compared with conventional enhancement techniques such as histogram equalization, contrast limited adaptive histogram equalization, Retinex, and some recently proposed methods to show its strengths. The experimental results reveal that the proposed method can remarkably improve the image contrast while keeping the sensitive chest tissue information so that radiologists might have a more precise interpretation. PMID:25709942

  1. Diesel engine air tightness feature recognition based on multi-scale analysis

    NASA Astrophysics Data System (ADS)

    Song, Xiaojie; Liu, Wei; Tan, Boxue

    2013-03-01

    Cylinder air tightness is an important indicator to the comprehensive performance of internal combustion engine. It can be got the low-frequency and high-frequency signals of the starting voltage waveform using multi-scale analysis method and by binary discrete wavelet transform with the Mallat algorithm. The experiment results show that the working conditions of diesel engine starting process can be shown from the low-frequency signals, and the main frequency distribution can be recognised from the high frequency partial. This algorithm can effectively identify signal characteristics, and provide a reliable basis for signal feature recognition.

  2. Micro/nano-computed tomography technology for quantitative dynamic, multi-scale imaging of morphogenesis.

    PubMed

    Gregg, Chelsea L; Recknagel, Andrew K; Butcher, Jonathan T

    2015-01-01

    Tissue morphogenesis and embryonic development are dynamic events challenging to quantify, especially considering the intricate events that happen simultaneously in different locations and time. Micro- and more recently nano-computed tomography (micro/nanoCT) has been used for the past 15 years to characterize large 3D fields of tortuous geometries at high spatial resolution. We and others have advanced micro/nanoCT imaging strategies for quantifying tissue- and organ-level fate changes throughout morphogenesis. Exogenous soft tissue contrast media enables visualization of vascular lumens and tissues via extravasation. Furthermore, the emergence of antigen-specific tissue contrast enables direct quantitative visualization of protein and mRNA expression. Micro-CT X-ray doses appear to be non-embryotoxic, enabling longitudinal imaging studies in live embryos. In this chapter we present established soft tissue contrast protocols for obtaining high-quality micro/nanoCT images and the image processing techniques useful for quantifying anatomical and physiological information from the data sets.

  3. Micro/Nano-Computed Tomography Technology for Quantitative Dynamic, Multi-scale Imaging of Morphogenesis

    PubMed Central

    Gregg, Chelsea L.; Recknagel, Andrew K.; Butcher, Jonathan T.

    2015-01-01

    Tissue morphogenesis and embryonic development are dynamic events challenging to quantify, especially considering the intricate events that happen simultaneously in different locations and time. Micro-, and more recently nano-computed tomography (micro/nanoCT), has been used for the past 15 years to characterize large 3D fields of tortuous geometries at high spatial resolution. We and others have advanced micro/nanoCT imaging strategies for quantifying tissue and organ level fate changes throughout morphogenesis. Exogenous soft tissue contrast media enables visualization of vascular lumens and tissues via extravasation. Furthermore, the emergence of antigen specific tissue contrast enables direct quantitative visualization of protein and mRNA expression. Micro-CT X-ray doses appear to be non-embryotoxic, enabling longitudinal imaging studies in live embryos. In this paper we present established soft tissue contrast protocols for obtaining high quality micro/nanoCT images and the image processing techniques useful for quantifying anatomical and physiological information from the datasets. PMID:25245686

  4. Towards a physically-based multi-scale ecohydrological simulator for semi-arid regions

    NASA Astrophysics Data System (ADS)

    Caviedes-Voullième, Daniel; Josefik, Zoltan; Hinz, Christoph

    2017-04-01

    The use of numerical models as tools for describing and understanding complex ecohydrological systems has enabled to test hypothesis and propose fundamental, process-based explanations of the system system behaviour as a whole as well as its internal dynamics. Reaction-diffusion equations have been used to describe and generate organized pattern such as bands, spots, and labyrinths using simple feedback mechanisms and boundary conditions. Alternatively, pattern-matching cellular automaton models have been used to generate vegetation self-organization in arid and semi-arid regions also using simple description of surface hydrological processes. A key question is: How much physical realism is needed in order to adequately capture the pattern formation processes in semi-arid regions while reliably representing the water balance dynamics at the relevant time scales? In fact, redistribution of water by surface runoff at the hillslope scale occurs at temporal resolution of minutes while the vegetation development requires much lower temporal resolution and longer times spans. This generates a fundamental spatio-temporal multi-scale problem to be solved, for which high resolution rainfall and surface topography are required. Accordingly, the objective of this contribution is to provide proof-of-concept that governing processes can be described numerically at those multiple scales. The requirements for a simulating ecohydrological processes and pattern formation with increased physical realism are, amongst others: i. high resolution rainfall that adequately captures the triggers of growth as vegetation dynamics of arid regions respond as pulsed systems. ii. complex, natural topography in order to accurately model drainage patterns, as surface water redistribution is highly sensitive to topographic features. iii. microtopography and hydraulic roughness, as small scale variations do impact on large scale hillslope behaviour iv. moisture dependent infiltration as temporal

  5. Three-dimensional imaging of sediment cores: a multi-scale approach

    NASA Astrophysics Data System (ADS)

    Deprez, Maxim; Van Daele, Maarten; Boone, Marijn; Anselmetti, Flavio; Cnudde, Veerle

    2017-04-01

    Downscaling is a method used in building-material research, where several imaging methods are applied to obtain information on the petrological and petrophysical properties of materials from a centimetre to a sub-micrometre scale (De Boever et al., 2015). However, to reach better resolutions, the sample size is necessarily adjusted as well. If, for instance, X-ray micro computed tomography (µCT) is applied on the material, the resolution can increase as the sample size decreases. In sedimentological research, X-ray computed tomography (CT) is a commonly used technique (Cnudde & Boone, 2013). The ability to visualise materials with different X-ray attenuations reveals structures in sediment cores that cannot be seen with the bare eye. This results in discoveries of sedimentary structures that can lead to a reconstruction of parts of the depositional history in a sedimentary basin (Van Daele et al., 2014). Up to now, most of the CT data used for this kind of research are acquired with a medical CT scanner, of which the highest obtainable resolution is about 250 µm (Cnudde et al., 2006). As the size of most sediment grains is smaller than 250 µm, a lot of information, concerning sediment fabric, grain-size and shape, is not obtained when using medical CT. Therefore, downscaling could be a useful method in sedimentological research. After identifying a region of interest within the sediment core with medical CT, a subsample of several millimetres diameter can be taken and imaged with µCT, allowing images with a resolution of a few micrometres. The subsampling process, however, needs to be considered thoroughly. As the goal is to image the structure and fabric of the sediments, deformation of the sediments during subsampling should be avoided as much as possible. After acquiring the CT data, image processing and analysis are performed in order to retrieve shape and orientation parameters of single grains, mud clasts and organic material. This single-grain data can

  6. A New Paradigm of Interactive Artery/Vein Separation in Non-Contrast Pulmonary CT Imaging using Multi-Scale Topo-Morphologic Opening

    PubMed Central

    Gao, Zhiyun; Grout, Randall W.; Holtze, Colin; Hoffman, Eric A.

    2014-01-01

    Distinguishing pulmonary arterial and venous (A/V) trees via in vivo imaging is a critical first step in the quantification of vascular geometry for the purpose of diagnosing several pulmonary diseases and to develop new image-based phenotypes. A multi-scale topo-morphologic opening (MSTMO) algorithm has recently been developed in our laboratory for separating A/V trees via non-contrast pulmonary human CT imaging. The method starts with two sets of seeds – one for each of A/V trees and combines fuzzy distance transform and fuzzy connectivity in conjunction with several morphological operations leading to locally-adaptive iterative multi-scale opening of two mutually conjoined structures. In the current paper, we introduce the methods for handling “local update” and “separators” into our previous theoretical formulation and incorporate the algorithm into an effective graphical user interface (GUI). Results of a comprehensive evaluative study assessing both accuracy and reproducibility of the method under the new setup are presented and also, the effectiveness of the GUI-based system towards improving A/V separation results is examined. Accuracy of the method has been evaluated using mathematical phantoms, CT images of contrast-separated pulmonary A/V casting of a pig’s lung and non-contrast pulmonary human CT imaging. The method has achieved 99% true A/V labeling in the cast phantom and, almost, 92% to 94% true labeling in human lung data. Reproducibility of the method has been evaluated using multiuser A/V separation in human CT data along with contrast-enhanced CT images of a pig’s lung at different positive end-expiratory pressures (PEEPs). The method has achieved, almost, 92% to 98% agreements in multi-user A/V labeling with ICC for A/V measures being over 0.96 to 0.99. Effectiveness of the GUI based method has been evaluated on human data in terms of improvements of accuracy of A/V separation results and results have shown 8% to 22% improvements

  7. Stress distribution retrieval in granular materials: A multi-scale model and digital image correlation measurements

    NASA Astrophysics Data System (ADS)

    Bruno, Luigi; Decuzzi, Paolo; Gentile, Francesco

    2016-01-01

    The promise of nanotechnology lies in the possibility of engineering matter on the nanoscale and creating technological interfaces that, because of their small scales, may directly interact with biological objects, creating new strategies for the treatment of pathologies that are otherwise beyond the reach of conventional medicine. Nanotechnology is inherently a multiscale, multiphenomena challenge. Fundamental understanding and highly accurate predictive methods are critical to successful manufacturing of nanostructured materials, bio/mechanical devices and systems. In biomedical engineering, and in the mechanical analysis of biological tissues, classical continuum approaches are routinely utilized, even if these disregard the discrete nature of tissues, that are an interpenetrating network of a matrix (the extra cellular matrix, ECM) and a generally large but finite number of cells with a size falling in the micrometer range. Here, we introduce a nano-mechanical theory that accounts for the-non continuum nature of bio systems and other discrete systems. This discrete field theory, doublet mechanics (DM), is a technique to model the mechanical behavior of materials over multiple scales, ranging from some millimeters down to few nanometers. In the paper, we use this theory to predict the response of a granular material to an external applied load. Such a representation is extremely attractive in modeling biological tissues which may be considered as a spatial set of a large number of particulate (cells) dispersed in an extracellular matrix. Possibly more important of this, using digital image correlation (DIC) optical methods, we provide an experimental verification of the model.

  8. The use of digital image correlation for non-destructive and multi-scale damage quantification

    NASA Astrophysics Data System (ADS)

    Schwartz, Eric; Saralaya, Raghavendra; Cuadra, Jefferson; Hazeli, Kavan; Vanniamparambil, Prashanth A.; Carmi, Rami; Bartoli, Ivan; Kontsos, Antonios

    2013-04-01

    This research demonstrates the use of Digital Image Correlation (DIC) as a non-contact, non-destructive testing and evaluation (NDT and E) technique by presenting experimental results pertinent to damage monitoring and quantification in several material systems at different length scales of interest. At the microstructural level compact tension aluminum alloy specimens were tested under Mode I loading conditions using an appropriate field of view to track grain scale crack initiation and growth. The results permitted the quantification of the strain accumulation near the tip of the fatigue pre-crack, as well as the computation of the relevant crack opening displacement as a function of crack length. At the mesoscale level, damage quantification in fiber reinforced composites subject to both tensile and fatigue loading conditions was achieved by using the DIC as part of a novel integrated NDT approach combining both acoustic and thermal methods. DIC in these experiments provided spatially resolved and high accuracy strain measurements capable to track the formation of damage "hot spots" that corresponded to the sites of the ultimately visible fracture pattern, while it further allowed the correlation of mechanical parameters to thermal and acoustic features. Finally, at the macrostructural level DIC measurements were also performed and compared to traditional displacement gauges mounted on a steel deck model subject to both static and dynamic loads, as well as on masonry structures including hollow and grouted concrete walls.

  9. Multi-scale modeling of soft fibrous tissues based on proteoglycan mechanics.

    PubMed

    Linka, Kevin; Khiêm, Vu Ngoc; Itskov, Mikhail

    2016-08-16

    Collagen in the form of fibers or fibrils is an essential source of strength and structural integrity in most organs of the human body. Recently, with the help of complex experimental setups, a paradigm change concerning the mechanical contribution of proteoglycans (PGs) took place. Accordingly, PG connections protect the surrounding collagen fibrils from over-stretching rather than transmitting load between them. In this paper, we describe the reported PG mechanics and incorporate it into a multi-scale model of soft fibrous tissues. To this end, a nano-to-micro model of a single collagen fiber is developed by taking the entropic-energetic transition on the collagen molecule level into account. The microscopic damage occurring inside the collagen fiber is elucidated by sliding of PGs as well as by over-stretched collagen molecules. Predictions of this two-constituent-damage model are compared to experimental data available in the literature.

  10. Fluid ascent and magma storage beneath Gunung Merapi revealed by multi-scale seismic imaging

    NASA Astrophysics Data System (ADS)

    Luehr, Birger-G.; Koulakov, Ivan; Rabbel, Wolfgang; Zschau, Jochen; Ratdomopurbo, Antonius; Brotopuspito, Kirbani Sri; Fauzi, Pak; Sahara, David P.

    2013-07-01

    Magma is fed to a volcano through a complex “plumbing” system that involves not only shallow structures beneath the volcano edifice, but also deep structures and processes within the underlying crust and upper mantle. This paper summarizes seismic experiments carried out over many years at Gunung Merapi in Central Java. These have resolved the 3D seismic velocity structure of the Merapi edifice, and provided a 3D structural image of the lithosphere and subduction zone beneath Central Java. Earthquake locations reveal that with distance from the trench, the dip of the subducting slab steepens from nearly horizontal (0-150 km), through 45° (150-250 km), to 70° (> 250 km). The slab appears as a 30 km thick double layer of seismicity in a depth range of 80 km to 150 km, and it can be identified seismically to a depth of more than 600 km. The active volcanoes of Merapi, Sumbing, and Lawu are located at the edge of a large low velocity body that extends from the upper crust to the upper mantle beneath Central Java. Shear wave signals recorded above this anomaly are strongly attenuated compared to neighboring areas. The anomalous body has a detected volume of > 50,000 km3 and a decrease in P and S velocities relative to adjacent regions of up to 30%. The resulting Vp/Vs ratio of up to 1.9 is unusually high for lower crust. Additionally, the anomaly extends along a 45 degree-slope downward from beneath the volcanic arc and meets the slab at 100 km depth. We interpret this sloping anomaly as a pathway for fluids and partial melts. Increased seismicity is observed at depths of ~ 100 km, possibly as a result of dehydration of the subducting slab with related fluid releases causing partial melting of overlying mantle material. The large velocity reduction and high Vp/Vs ratio in the region are consistent with an increase in temperature, a reduction of shear strength, and the presence of fluids or melts of 13 to 25 vol.%. The detected strong anomaly beneath Central Java

  11. Multi-scale modeling of microstructure dependent intergranular brittle fracture using a quantitative phase-field based method

    SciTech Connect

    Chakraborty, Pritam; Zhang, Yongfeng; Tonks, Michael R.

    2015-12-07

    In this study, the fracture behavior of brittle materials is strongly influenced by their underlying microstructure that needs explicit consideration for accurate prediction of fracture properties and the associated scatter. In this work, a hierarchical multi-scale approach is pursued to model microstructure sensitive brittle fracture. A quantitative phase-field based fracture model is utilized to capture the complex crack growth behavior in the microstructure and the related parameters are calibrated from lower length scale atomistic simulations instead of engineering scale experimental data. The workability of this approach is demonstrated by performing porosity dependent intergranular fracture simulations in UO2 and comparing the predictions with experiments.

  12. Automated Macular Pathology Diagnosis in Retinal OCT Images Using Multi-Scale Spatial Pyramid and Local Binary Patterns in Texture and Shape Encoding

    PubMed Central

    Liu, Yu-Ying; Chen, Mei; Ishikawa, Hiroshi; Wollstein, Gadi; Schuman, Joel S.; Rehg, James M.

    2011-01-01

    We address a novel problem domain in the analysis of optical coherence tomography (OCT) images: the diagnosis of multiple macular pathologies in retinal OCT images. The goal is to identify the presence of normal macula and each of three types of macular pathologies, namely, macular edema, macular hole, and age-related macular degeneration, in the OCT slice centered at the fovea. We use a machine learning approach based on global image descriptors formed from a multi-scale spatial pyramid. Our local features are dimension-reduced Local Binary Pattern histograms, which are capable of encoding texture and shape information in retinal OCT images and their edge maps, respectively. Our representation operates at multiple spatial scales and granularities, leading to robust performance. We use 2-class Support Vector Machine classifiers to identify the presence of normal macula and each of the three pathologies. To further discriminate sub-types within a pathology, we also build a classifier to differentiate full-thickness holes from pseudo-holes within the macular hole category. We conduct extensive experiments on a large dataset of 326 OCT scans from 136 subjects. The results show that the proposed method is very effective (all AUC > 0.93). PMID:21737338

  13. Automated macular pathology diagnosis in retinal OCT images using multi-scale spatial pyramid and local binary patterns in texture and shape encoding.

    PubMed

    Liu, Yu-Ying; Chen, Mei; Ishikawa, Hiroshi; Wollstein, Gadi; Schuman, Joel S; Rehg, James M

    2011-10-01

    We address a novel problem domain in the analysis of optical coherence tomography (OCT) images: the diagnosis of multiple macular pathologies in retinal OCT images. The goal is to identify the presence of normal macula and each of three types of macular pathologies, namely, macular edema, macular hole, and age-related macular degeneration, in the OCT slice centered at the fovea. We use a machine learning approach based on global image descriptors formed from a multi-scale spatial pyramid. Our local features are dimension-reduced local binary pattern histograms, which are capable of encoding texture and shape information in retinal OCT images and their edge maps, respectively. Our representation operates at multiple spatial scales and granularities, leading to robust performance. We use 2-class support vector machine classifiers to identify the presence of normal macula and each of the three pathologies. To further discriminate sub-types within a pathology, we also build a classifier to differentiate full-thickness holes from pseudo-holes within the macular hole category. We conduct extensive experiments on a large dataset of 326 OCT scans from 136 subjects. The results show that the proposed method is very effective (all AUC>0.93).

  14. Multi-scale Properties and Processes in Hierarchically-Structured Organic-Inorganic Solids and Surface-Based Microfluidic Systems

    NASA Astrophysics Data System (ADS)

    Messinger, Robert James

    Hierarchically-structured materials and surface-based microfluidic systems exhibit diverse properties that are inherently multi-scale in origin. In particular, different molecular, mesoscopic, and micron-scale properties and processes are often correlated and collectively account for many properties of interest, such as bulk catalytic activities or electrokinetic flow rates. However, such properties and processes often exhibit complex relationships over the different length scales that are not well understood, and consequently, difficult to control. Establishing correlations between them has been challenging, in part due to the difficulty of rigorously characterizing complex, heterogeneous materials and surface-based microfluidic experiments over multiple length scales, particularly at the molecular and mesoscopic levels. Herein, new multi-scale understanding and correlations have been established for different hierarchically-structured organic-inorganic solids or surface-based microfluidic systems, enabling control of material or device properties over discrete length scales. The molecular-level compositions, structures, interactions, and dynamics have been measured in diverse hierarchically-structured materials, such as mesostructured zeolites, mesostructured organosilicas, and organosiloxane foams, and subsequently correlated with their meso- and macroscopic material structures and properties. The results reveal new insights on the molecular-level interactions that govern their syntheses, the resulting local compositions and material structures, and the relationships among material properties over multiple characteristic length scales. Multi-dimensional solid-state nuclear magnetic resonance (NMR) spectroscopy is a cornerstone of these investigations, which enables correlative measurements in multiple frequency dimensions of the through-space or through-bond interactions between the constituent nuclei within the different materials. Other multi-scale

  15. [A method for obtaining redshifts of quasars based on wavelet multi-scaling feature matching].

    PubMed

    Liu, Zhong-Tian; Li, Xiang-Ru; Wu, Fu-Chao; Zhao, Yong-Heng

    2006-09-01

    The LAMOST project, the world's largest sky survey project being implemented in China, is expected to obtain 10(5) quasar spectra. The main objective of the present article is to explore methods that can be used to estimate the redshifts of quasar spectra from LAMOST. Firstly, the features of the broad emission lines are extracted from the quasar spectra to overcome the disadvantage of low signal-to-noise ratio. Then the redshifts of quasar spectra can be estimated by using the multi-scaling feature matching. The experiment with the 15, 715 quasars from the SDSS DR2 shows that the correct rate of redshift estimated by the method is 95.13% within an error range of 0. 02. This method was designed to obtain the redshifts of quasar spectra with relative flux and a low signal-to-noise ratio, which is applicable to the LAMOST data and helps to study quasars and the large-scale structure of the universe etc.

  16. 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.

  17. Multi-scale hippocampal parcellation improves atlas-based segmentation accuracy

    NASA Astrophysics Data System (ADS)

    Plassard, Andrew J.; McHugo, Maureen; Heckers, Stephan; Landman, Bennett A.

    2017-02-01

    Known for its distinct role in memory, the hippocampus is one of the most studied regions of the brain. Recent advances in magnetic resonance imaging have allowed for high-contrast, reproducible imaging of the hippocampus. Typically, a trained rater takes 45 minutes to manually trace the hippocampus and delineate the anterior from the posterior segment at millimeter resolution. As a result, there has been a significant desire for automated and robust segmentation of the hippocampus. In this work we use a population of 195 atlases based on T1-weighted MR images with the left and right hippocampus delineated into the head and body. We initialize the multi-atlas segmentation to a region directly around each lateralized hippocampus to both speed up and improve the accuracy of registration. This initialization allows for incorporation of nearly 200 atlases, an accomplishment which would typically involve hundreds of hours of computation per target image. The proposed segmentation results in a Dice similiarity coefficient over 0.9 for the full hippocampus. This result outperforms a multi-atlas segmentation using the BrainCOLOR atlases (Dice 0.85) and FreeSurfer (Dice 0.75). Furthermore, the head and body delineation resulted in a Dice coefficient over 0.87 for both structures. The head and body volume measurements also show high reproducibility on the Kirby 21 reproducibility population (R2 greater than 0.95, p < 0.05 for all structures). This work signifies the first result in an ongoing work to develop a robust tool for measurement of the hippocampus and other temporal lobe structures.

  18. Pattern-based, multi-scale segmentation and regionalization of EOSD land cover

    NASA Astrophysics Data System (ADS)

    Niesterowicz, Jacek; Stepinski, Tomasz F.

    2017-10-01

    The Earth Observation for Sustainable Development of Forests (EOSD) map is a 25 m resolution thematic map of Canadian forests. Because of its large spatial extent and relatively high resolution the EOSD is difficult to analyze using standard GIS methods. In this paper we propose multi-scale segmentation and regionalization of EOSD as new methods for analyzing EOSD on large spatial scales. Segments, which we refer to as forest land units (FLUs), are delineated as tracts of forest characterized by cohesive patterns of EOSD categories; we delineated from 727 to 91,885 FLUs within the spatial extent of EOSD depending on the selected scale of a pattern. Pattern of EOSD's categories within each FLU is described by 1037 landscape metrics. A shapefile containing boundaries of all FLUs together with an attribute table listing landscape metrics make up an SQL-searchable spatial database providing detailed information on composition and pattern of land cover types in Canadian forest. Shapefile format and extensive attribute table pertaining to the entire legend of EOSD are designed to facilitate broad range of investigations in which assessment of composition and pattern of forest over large areas is needed. We calculated four such databases using different spatial scales of pattern. We illustrate the use of FLU database for producing forest regionalization maps of two Canadian provinces, Quebec and Ontario. Such maps capture the broad scale variability of forest at the spatial scale of the entire province. We also demonstrate how FLU database can be used to map variability of landscape metrics, and thus the character of landscape, over the entire Canada.

  19. SU-E-I-100: Heterogeneity Studying for Primary and Lymphoma Tumors by Using Multi-Scale Image Texture Analysis with PET-CT Images

    SciTech Connect

    Li, Dengwang; Wang, Qinfen; Li, H; Chen, J

    2014-06-01

    Purpose: The purpose of this research is studying tumor heterogeneity of the primary and lymphoma by using multi-scale texture analysis with PET-CT images, where the tumor heterogeneity is expressed by texture features. Methods: Datasets were collected from 12 lung cancer patients, and both of primary and lymphoma tumors were detected with all these patients. All patients underwent whole-body 18F-FDG PET/CT scan before treatment.The regions of interest (ROI) of primary and lymphoma tumor were contoured by experienced clinical doctors. Then the ROI of primary and lymphoma tumor is extracted automatically by using Matlab software. According to the geometry size of contour structure, the images of tumor are decomposed by multi-scale method.Wavelet transform was performed on ROI structures within images by L layers sampling, and then wavelet sub-bands which have the same size of the original image are obtained. The number of sub-bands is 3L+1.The gray level co-occurrence matrix (GLCM) is calculated within different sub-bands, thenenergy, inertia, correlation and gray in-homogeneity were extracted from GLCM.Finally, heterogeneity statistical analysis was studied for primary and lymphoma tumor using the texture features. Results: Energy, inertia, correlation and gray in-homogeneity are calculated with our experiments for heterogeneity statistical analysis.Energy for primary and lymphomatumor is equal with the same patient, while gray in-homogeneity and inertia of primaryare 2.59595±0.00855, 0.6439±0.0007 respectively. Gray in-homogeneity and inertia of lymphoma are 2.60115±0.00635, 0.64435±0.00055 respectively. The experiments showed that the volume of lymphoma is smaller than primary tumor, but thegray in-homogeneity and inertia were higher than primary tumor with the same patient, and the correlation with lymphoma tumors is zero, while the correlation with primary tumor isslightly strong. Conclusion: This studying showed that there were effective heterogeneity

  20. 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

  1. An evaluation of noise reduction algorithms for particle-based fluid simulations in multi-scale applications

    NASA Astrophysics Data System (ADS)

    Zimoń, M. J.; Prosser, R.; Emerson, D. R.; Borg, M. K.; Bray, D. J.; Grinberg, L.; Reese, J. M.

    2016-11-01

    Filtering of particle-based simulation data can lead to reduced computational costs and enable more efficient information transfer in multi-scale modelling. This paper compares the effectiveness of various signal processing methods to reduce numerical noise and capture the structures of nano-flow systems. In addition, a novel combination of these algorithms is introduced, showing the potential of hybrid strategies to improve further the de-noising performance for time-dependent measurements. The methods were tested on velocity and density fields, obtained from simulations performed with molecular dynamics and dissipative particle dynamics. Comparisons between the algorithms are given in terms of performance, quality of the results and sensitivity to the choice of input parameters. The results provide useful insights on strategies for the analysis of particle-based data and the reduction of computational costs in obtaining ensemble solutions.

  2. Imaging ATUM ultrathin section libraries with WaferMapper: a multi-scale approach to EM reconstruction of neural circuits

    PubMed Central

    Hayworth, Kenneth J.; Morgan, Josh L.; Schalek, Richard; Berger, Daniel R.; Hildebrand, David G. C.; Lichtman, Jeff W.

    2014-01-01

    The automated tape-collecting ultramicrotome (ATUM) makes it possible to collect large numbers of ultrathin sections quickly—the equivalent of a petabyte of high resolution images each day. However, even high throughput image acquisition strategies generate images far more slowly (at present ~1 terabyte per day). We therefore developed WaferMapper, a software package that takes a multi-resolution approach to mapping and imaging select regions within a library of ultrathin sections. This automated method selects and directs imaging of corresponding regions within each section of an ultrathin section library (UTSL) that may contain many thousands of sections. Using WaferMapper, it is possible to map thousands of tissue sections at low resolution and target multiple points of interest for high resolution imaging based on anatomical landmarks. The program can also be used to expand previously imaged regions, acquire data under different imaging conditions, or re-image after additional tissue treatments. PMID:25018701

  3. Multi-scale modeling of microstructure dependent intergranular brittle fracture using a quantitative phase-field based method

    DOE PAGES

    Chakraborty, Pritam; Zhang, Yongfeng; Tonks, Michael R.

    2015-12-07

    In this study, the fracture behavior of brittle materials is strongly influenced by their underlying microstructure that needs explicit consideration for accurate prediction of fracture properties and the associated scatter. In this work, a hierarchical multi-scale approach is pursued to model microstructure sensitive brittle fracture. A quantitative phase-field based fracture model is utilized to capture the complex crack growth behavior in the microstructure and the related parameters are calibrated from lower length scale atomistic simulations instead of engineering scale experimental data. The workability of this approach is demonstrated by performing porosity dependent intergranular fracture simulations in UO2 and comparing themore » predictions with experiments.« less

  4. Monitoring plant cover on the Tibetan Plateau: A multi-scale remote sensing based approach

    NASA Astrophysics Data System (ADS)

    Lehnert, Lukas; Meyer, Hanna; Thies, Boris; Reudenbach, Christoph; Bendix, Jörg

    2014-05-01

    The degradation of the grasslands on the Tibetan Plateau (TP) is seen as ongoing process. This general assumption is based on small scale studies which are not comparable because field methods and indicators differ among the investigations. Thus, especially for remote areas, a remotely sensed monitoring system is critically needed to monitor degradation. Additionally, a single and comparable product for the entire TP is of urgent concern to evaluate the ecological consequences of the assumed ongoing degradation on ecosystem services provided by the grasslands on the TP. As indicator for degradation plant cover was used in this study because a close link between degradation and plant cover has been identified by several previous studies on the TP. Thus, we implemented a four-scale remote sensing approach to derive plant cover. As reference and validation data, field records were taken between 2011 and 2013 at 15 locations spanning the entire TP and covering all grazed grassland vegetation types. Plant cover was measured in situ at up to 210 plots per location using standardized taken digital photos. To classify green vegetated parts in the digital photos, simple threshold classifications were applied to the ratio of red and green color values. The geographical position of all plots was recorded using a differential GPS. Plant cover was derived from satellite data at three scales using spectral angle mapper (SAM), normalized difference band indices and linear spectral unmixing. The result of the first two approaches was transferred to plant cover using multiple linear regression techniques. Reference spectra and endmember spectra for SAM and linear spectral unmixing were recorded using a field spectrometer. The hyperspectral information was resampled to satellite bands using the spectral response functions of the sensors. To derive plant cover at local scale, we classified 35 high resolution WorldView-2, Quickbird and RapidEye satellite images using the in situ

  5. The Multi-Scale Veto Model: A Two-Stage Analog Network for Edge Detection and Image Reconstruction

    DTIC Science & Technology

    1992-03-01

    1992 This report describes reseatch done at the Artiicial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the...AD-A259 600EWli~ Mliii MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LAjORATORY AI. Memo No. 1320 March, 1992 The Multi-Scale Veto...laboratory’s artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under Office of

  6. Penetration into Granular Earth Materials (Topic H): A Multi-scale Physics-Based Approach Towards Developing a Greater Understanding of Dynamically Loaded Heterogeneous Systems

    DTIC Science & Technology

    2016-08-01

    Multi-scale Physics -Based Approach Towards Developing a Greater Understanding of Dynamically Loaded Heterogeneous Systems Distribution Statement A...MATERIALS (TOPIC H): HDTRA 1-09-1-0045 A MULTI-SCALE PHYSICS -BASED APPROACH TOWARDS DEVELOPING A GREATER UNDERSTANDING OF DYNAMICALLY Sb. GRANT NUMBER...4.535 924 × 10 –1 kilogram (kg) unified atomic mass unit (amu) 1.660 539 × 10 –27 kilogram (kg) pound-mass per cubic foot (lb ft –3 ) 1.601 846

  7. Defining the limits and reliability of rigid-body fitting in cryo-EM maps using multi-scale image pyramids.

    PubMed

    van Zundert, G C P; Bonvin, A M J J

    2016-08-01

    Cryo-electron microscopy provides fascinating structural insight into large macromolecular machines at increasing detail. Despite significant advances in the field, the resolution of the resulting three-dimensional images is still typically insufficient for de novo model building. To bridge the resolution gap and give an atomic interpretation to the data, high-resolution models are typically placed into the density as rigid bodies. Unfortunately, this is often done manually using graphics software, a subjective method that can lead to over-interpretation of the data. A more objective approach is to perform an exhaustive cross-correlation-based search to fit subunits into the density. Here we show, using five experimental ribosome maps ranging in resolution from 5.5 to 6.9Å, that cross-correlation-based fitting is capable of successfully fitting subunits correctly in the density for over 90% of the cases. Importantly, we provide indicators for the reliability and ambiguity of a fit, using the Fisher z-transformation and its associated confidence intervals, giving a formal approach to identify over-interpreted regions in the density. In addition, we quantify the resolution requirement for a successful fit as a function of the subunit size. For larger subunits the resolution of the data can be down-filtered to 20Å while still retaining an unambiguous fit. We leverage this information through the use of multi-scale image pyramids to accelerate the search up to 30-fold on CPUs and 40-fold on GPUs at a negligible loss in success rate. We implemented this approach in our rigid-body fitting software PowerFit, which can be freely downloaded from https://github.com/haddocking/powerfit.

  8. A multi-scale continuum model of skeletal muscle mechanics predicting force enhancement based on actin-titin interaction.

    PubMed

    Heidlauf, Thomas; Klotz, Thomas; Rode, Christian; Altan, Ekin; Bleiler, Christian; Siebert, Tobias; Röhrle, Oliver

    2016-12-01

    Although recent research emphasises the possible role of titin in skeletal muscle force enhancement, this property is commonly ignored in current computational models. This work presents the first biophysically based continuum-mechanical model of skeletal muscle that considers, in addition to actin-myosin interactions, force enhancement based on actin-titin interactions. During activation, titin attaches to actin filaments, which results in a significant reduction in titin's free molecular spring length and therefore results in increased titin forces during a subsequent stretch. The mechanical behaviour of titin is included on the microscopic half-sarcomere level of a multi-scale chemo-electro-mechanical muscle model, which is based on the classic sliding-filament and cross-bridge theories. In addition to titin stress contributions in the muscle fibre direction, the continuum-mechanical constitutive relation accounts for geometrically motivated, titin-induced stresses acting in the muscle's cross-fibre directions. Representative simulations of active stretches under maximal and submaximal activation levels predict realistic magnitudes of force enhancement in fibre direction. For example, stretching the model by 20 % from optimal length increased the isometric force at the target length by about 30 %. Predicted titin-induced stresses in the muscle's cross-fibre directions are rather insignificant. Including the presented development in future continuum-mechanical models of muscle function in dynamic situations will lead to more accurate model predictions during and after lengthening contractions.

  9. VisANT 3.5: multi-scale network visualization, analysis and inference based on the gene ontology

    PubMed Central

    Hu, Zhenjun; Hung, Jui-Hung; Wang, Yan; Chang, Yi-Chien; Huang, Chia-Ling; Huyck, Matt; DeLisi, Charles

    2009-01-01

    Despite its wide usage in biological databases and applications, the role of the gene ontology (GO) in network analysis is usually limited to functional annotation of genes or gene sets with auxiliary information on correlations ignored. Here, we report on new capabilities of VisANT—an integrative software platform for the visualization, mining, analysis and modeling of the biological networks—which extend the application of GO in network visualization, analysis and inference. The new VisANT functions can be classified into three categories. (i) Visualization: a new tree-based browser allows visualization of GO hierarchies. GO terms can be easily dropped into the network to group genes annotated under the term, thereby integrating the hierarchical ontology with the network. This facilitates multi-scale visualization and analysis. (ii) Flexible annotation schema: in addition to conventional methods for annotating network nodes with the most specific functional descriptions available, VisANT also provides functions to annotate genes at any customized level of abstraction. (iii) Finding over-represented GO terms and expression-enriched GO modules: two new algorithms have been implemented as VisANT plugins. One detects over-represented GO annotations in any given sub-network and the other finds the GO categories that are enriched in a specified phenotype or perturbed dataset. Both algorithms take account of network topology (i.e. correlations between genes based on various sources of evidence). VisANT is freely available at http://visant.bu.edu. PMID:19465394

  10. Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation

    PubMed Central

    An, Gary

    2008-01-01

    . The ABMs all utilize cell-level agents that encapsulate specific mechanistic knowledge extracted from in vitro experiments. The execution of the ABMs results in a dynamic representation of the multi-scale conceptual models derived from those experiments. These models represent a qualitative means of integrating basic scientific information on acute inflammation in a multi-scale, modular architecture as a means of conceptual model verification that can potentially be used to concatenate, communicate and advance community-wide knowledge. PMID:18505587

  11. Multi-scale thermal stability of a hard thermoplastic protein-based material.

    PubMed

    Latza, Victoria; Guerette, Paul A; Ding, Dawei; Amini, Shahrouz; Kumar, Akshita; Schmidt, Ingo; Keating, Steven; Oxman, Neri; Weaver, James C; Fratzl, Peter; Miserez, Ali; Masic, Admir

    2015-09-21

    Although thermoplastic materials are mostly derived from petro-chemicals, it would be highly desirable, from a sustainability perspective, to produce them instead from renewable biopolymers. Unfortunately, biopolymers exhibiting thermoplastic behaviour and which preserve their mechanical properties post processing are essentially non-existent. The robust sucker ring teeth (SRT) from squid and cuttlefish are one notable exception of thermoplastic biopolymers. Here we describe thermoplastic processing of squid SRT via hot extrusion of fibres, demonstrating the potential suitability of these materials for large-scale thermal forming. Using high-resolution in situ X-ray diffraction and vibrational spectroscopy, we elucidate the molecular and nanoscale features responsible for this behaviour and show that SRT consist of semi-crystalline polymers, whereby heat-resistant, nanocrystalline β-sheets embedded within an amorphous matrix are organized into a hexagonally packed nanofibrillar lattice. This study provides key insights for the molecular design of biomimetic protein- and peptide-based thermoplastic structural biopolymers with potential biomedical and 3D printing applications.

  12. Multi-scale thermal stability of a hard thermoplastic protein-based material

    PubMed Central

    Latza, Victoria; Guerette, Paul A.; Ding, Dawei; Amini, Shahrouz; Kumar, Akshita; Schmidt, Ingo; Keating, Steven; Oxman, Neri; Weaver, James C.; Fratzl, Peter; Miserez, Ali; Masic, Admir

    2015-01-01

    Although thermoplastic materials are mostly derived from petro-chemicals, it would be highly desirable, from a sustainability perspective, to produce them instead from renewable biopolymers. Unfortunately, biopolymers exhibiting thermoplastic behaviour and which preserve their mechanical properties post processing are essentially non-existent. The robust sucker ring teeth (SRT) from squid and cuttlefish are one notable exception of thermoplastic biopolymers. Here we describe thermoplastic processing of squid SRT via hot extrusion of fibres, demonstrating the potential suitability of these materials for large-scale thermal forming. Using high-resolution in situ X-ray diffraction and vibrational spectroscopy, we elucidate the molecular and nanoscale features responsible for this behaviour and show that SRT consist of semi-crystalline polymers, whereby heat-resistant, nanocrystalline β-sheets embedded within an amorphous matrix are organized into a hexagonally packed nanofibrillar lattice. This study provides key insights for the molecular design of biomimetic protein- and peptide-based thermoplastic structural biopolymers with potential biomedical and 3D printing applications. PMID:26387704

  13. Multi-scale thermal stability of a hard thermoplastic protein-based material

    NASA Astrophysics Data System (ADS)

    Latza, Victoria; Guerette, Paul A.; Ding, Dawei; Amini, Shahrouz; Kumar, Akshita; Schmidt, Ingo; Keating, Steven; Oxman, Neri; Weaver, James C.; Fratzl, Peter; Miserez, Ali; Masic, Admir

    2015-09-01

    Although thermoplastic materials are mostly derived from petro-chemicals, it would be highly desirable, from a sustainability perspective, to produce them instead from renewable biopolymers. Unfortunately, biopolymers exhibiting thermoplastic behaviour and which preserve their mechanical properties post processing are essentially non-existent. The robust sucker ring teeth (SRT) from squid and cuttlefish are one notable exception of thermoplastic biopolymers. Here we describe thermoplastic processing of squid SRT via hot extrusion of fibres, demonstrating the potential suitability of these materials for large-scale thermal forming. Using high-resolution in situ X-ray diffraction and vibrational spectroscopy, we elucidate the molecular and nanoscale features responsible for this behaviour and show that SRT consist of semi-crystalline polymers, whereby heat-resistant, nanocrystalline β-sheets embedded within an amorphous matrix are organized into a hexagonally packed nanofibrillar lattice. This study provides key insights for the molecular design of biomimetic protein- and peptide-based thermoplastic structural biopolymers with potential biomedical and 3D printing applications.

  14. Identifying vegetation's influence on multi-scale fluvial processes based on plant trait adaptations

    NASA Astrophysics Data System (ADS)

    Manners, R.; Merritt, D. M.; Wilcox, A. C.; Scott, M.

    2015-12-01

    Riparian vegetation-geomorphic interactions are critical to the physical and biological function of riparian ecosystems, yet we lack a mechanistic understanding of these interactions and predictive ability at the reach to watershed scale. Plant functional groups, or groupings of species that have similar traits, either in terms of a plant's life history strategy (e.g., drought tolerance) or morphology (e.g., growth form), may provide an expression of vegetation-geomorphic interactions. We are developing an approach that 1) identifies where along a river corridor plant functional groups exist and 2) links the traits that define functional groups and their impact on fluvial processes. The Green and Yampa Rivers in Dinosaur National Monument have wide variations in hydrology, hydraulics, and channel morphology, as well as a large dataset of species presence. For these rivers, we build a predictive model of the probable presence of plant functional groups based on site-specific aspects of the flow regime (e.g., inundation probability and duration), hydraulic characteristics (e.g., velocity), and substrate size. Functional group traits are collected from the literature and measured in the field. We found that life-history traits more strongly predicted functional group presence than did morphological traits. However, some life-history traits, important for determining the likelihood of a plant existing along an environmental gradient, are directly related to the morphological properties of the plant, important for the plant's impact on fluvial processes. For example, stem density (i.e., dry mass divided by volume of stem) is positively correlated to drought tolerance and is also related to the modulus of elasticity. Growth form, which is related to the plant's susceptibility to biomass-removing fluvial disturbances, is also related to frontal area. Using this approach, we can identify how plant community composition and distribution shifts with a change to the flow

  15. Multi-scale Modelling of bcc-Fe Based Alloys for Nuclear Applications

    SciTech Connect

    Malerba, Lorenzo

    2008-07-01

    , advanced techniques to fit interatomic potentials consistent with thermodynamics are proposed and the results of their application to the mentioned alloys are presented. Next, the development of advanced methods, based on the use of artificial intelligence, to improve both the physical reliability and the computational efficiency of kinetic Monte Carlo codes for the study of point-defect clustering and phase changes beyond the scale of MD, is reported. These recent progresses bear the promise of being able, in the near future, of producing reliable tools for the description of the microstructure evolution of realistic model alloys under irradiation. (author)

  16. Gearbox fault diagnosis using adaptive zero phase time-varying filter based on multi-scale chirplet sparse signal decomposition

    NASA Astrophysics Data System (ADS)

    Wu, Chunyan; Liu, Jian; Peng, Fuqiang; Yu, Dejie; Li, Rong

    2013-07-01

    When used for separating multi-component non-stationary signals, the adaptive time-varying filter(ATF) based on multi-scale chirplet sparse signal decomposition(MCSSD) generates phase shift and signal distortion. To overcome this drawback, the zero phase filter is introduced to the mentioned filter, and a fault diagnosis method for speed-changing gearbox is proposed. Firstly, the gear meshing frequency of each gearbox is estimated by chirplet path pursuit. Then, according to the estimated gear meshing frequencies, an adaptive zero phase time-varying filter(AZPTF) is designed to filter the original signal. Finally, the basis for fault diagnosis is acquired by the envelope order analysis to the filtered signal. The signal consisting of two time-varying amplitude modulation and frequency modulation(AM-FM) signals is respectively analyzed by ATF and AZPTF based on MCSSD. The simulation results show the variances between the original signals and the filtered signals yielded by AZPTF based on MCSSD are 13.67 and 41.14, which are far less than variances (323.45 and 482.86) between the original signals and the filtered signals obtained by ATF based on MCSSD. The experiment results on the vibration signals of gearboxes indicate that the vibration signals of the two speed-changing gearboxes installed on one foundation bed can be separated by AZPTF effectively. Based on the demodulation information of the vibration signal of each gearbox, the fault diagnosis can be implemented. Both simulation and experiment examples prove that the proposed filter can extract a mono-component time-varying AM-FM signal from the multi-component time-varying AM-FM signal without distortion.

  17. Multi-scale exploration of the technical, economic, and environmental dimensions of bio-based chemical production.

    PubMed

    Zhuang, Kai H; Herrgård, Markus J

    2015-09-01

    In recent years, bio-based chemicals have gained traction as a sustainable alternative to petrochemicals. However, despite rapid advances in metabolic engineering and synthetic biology, there remain significant economic and environmental challenges. In order to maximize the impact of research investment in a new bio-based chemical industry, there is a need for assessing the technological, economic, and environmental potentials of combinations of biomass feedstocks, biochemical products, bioprocess technologies, and metabolic engineering approaches in the early phase of development of cell factories. To address this issue, we have developed a comprehensive Multi-scale framework for modeling Sustainable Industrial Chemicals production (MuSIC), which integrates modeling approaches for cellular metabolism, bioreactor design, upstream/downstream processes and economic impact assessment. We demonstrate the use of the MuSIC framework in a case study where two major polymer precursors (1,3-propanediol and 3-hydroxypropionic acid) are produced from two biomass feedstocks (corn-based glucose and soy-based glycerol) through 66 proposed biosynthetic pathways in two host organisms (Escherichia coli and Saccharomyces cerevisiae). The MuSIC framework allows exploration of tradeoffs and interactions between economy-scale objectives (e.g. profit maximization, emission minimization), constraints (e.g. land-use constraints) and process- and cell-scale technology choices (e.g. strain design or oxygenation conditions). We demonstrate that economy-scale assessment can be used to guide specific strain design decisions in metabolic engineering, and that these design decisions can be affected by non-intuitive dependencies across multiple scales.

  18. Focal plane generation of multi-resolution and multi-scale image representation for low-power vision applications

    NASA Astrophysics Data System (ADS)

    Fernández-Berni, J.; Carmona-Galán, R.; Carranza-González, L.; Zarándy, A.; Rodríguez-Vázquez, Á.

    2011-06-01

    Early vision stages represent a considerably heavy computational load. A huge amount of data needs to be processed under strict timing and power requirements. Conventional architectures usually fail to adhere to the specifications in many application fields, especially when autonomous vision-enabled devices are to be implemented, like in lightweight UAVs, robotics or wireless sensor networks. A bioinspired architectural approach can be employed consisting of a hierarchical division of the processing chain, conveying the highest computational demand to the focal plane. There, distributed processing elements, concurrent with the photosensitive devices, influence the image capture and generate a pre-processed representation of the scene where only the information of interest for subsequent stages remains. These focal-plane operators are implemented by analog building blocks, which may individually be a little imprecise, but as a whole render the appropriate image processing very efficiently. As a proof of concept, we have developed a 176x144-pixel smart CMOS imager that delivers lighter but enriched representations of the scene. Each pixel of the array contains a photosensor and some switches and weighted paths allowing reconfigurable resolution and spatial filtering. An energy-based image representation is also supported. These functionalities greatly simplify the operation of the subsequent digital processor implementing the high level logic of the vision algorithm. The resulting figures, 5.6mW@30fps, permit the integration of the smart image sensor with a wireless interface module (Imote2 from Memsic Corp.) for the development of vision-enabled WSN applications.

  19. Multi-scale cellulose based new bio-aerogel composites with thermal super-insulating and tunable mechanical properties.

    PubMed

    Seantier, Bastien; Bendahou, Dounia; Bendahou, Abdelkader; Grohens, Yves; Kaddami, Hamid

    2016-03-15

    Bio-composite aerogels based on bleached cellulose fibers (BCF) and cellulose nanoparticles having various morphological and physico-chemical characteristics are prepared by a freeze-drying technique and characterized. The various composite aerogels obtained were compared to a BCF aerogel used as the reference. Severe changes in the material morphology were observed by SEM and AFM due to a variation of the cellulose nanoparticle properties such as the aspect ratio, the crystalline index and the surface charge density. BCF fibers form a 3D network and they are surrounded by the cellulose nanoparticle thin films inducing a significant reduction of the size of the pores in comparison with a neat BCF based aerogel. BET analyses confirm the appearance of a new organization structure with pores of nanometric sizes. As a consequence, a decrease of the thermal conductivities is observed from 28mWm(-1)K(-1) (BCF aerogel) to 23mWm(-1)K(-1) (bio-composite aerogel), which is below the air conductivity (25mWm(-1)K(-1)). This improvement of the insulation properties for composite materials is more pronounced for aerogels based on cellulose nanoparticles having a low crystalline index and high surface charge (NFC-2h). The significant improvement of their insulation properties allows the bio-composite aerogels to enter the super-insulating materials family. The characteristics of cellulose nanoparticles also influence the mechanical properties of the bio-composite aerogels. A significant improvement of the mechanical properties under compression is obtained by self-organization, yielding a multi-scale architecture of the cellulose nanoparticles in the bio-composite aerogels. In this case, the mechanical property is more dependent on the morphology of the composite aerogel rather than the intrinsic characteristics of the cellulose nanoparticles.

  20. Multi-Scale Studies of Transport and Adsorption Phenomena of Cement-based Materials in Aqueous and Saline Environment

    NASA Astrophysics Data System (ADS)

    Yoon, Se Yoon

    The transport and adsorption phenomena in cement-based materials are the most important processes in the durability of concrete structures or nuclear waste containers, as they are precursors to a number of deterioration processes such as chloride-induced corrosion, sulfate attack, carbonation, etc. Despite this importance, our understanding of these processes remains limited because the pore structure and composition of concrete are complex. In addition, the range of the pore sizes, from nanometers to millimeters, requires the multi-scale modeling of the transport and adsorption processes. Among the various environments that cement-based materials are exposed to, aqueous and saline environments represent the most common types. Therefore, this dissertation investigates the adsorption and transport phenomena of cement-based materials exposed to an aqueous and saline environment from atomic to macro-scales using different arrays of novel spectroscopic techniques and simulation methods, such as scanning transmission X-ray microscopy (STXM), X-ray absorption near edge structure (XANES), molecular dynamics (MD), and finite element method (FEM). The structure and transport of water molecules through interlayer spacing of tobermorite was investigated using MD simulations because the interlayer water of calcium silicate hydrate (C-S-H) gel influences various material properties of concrete. The adsorption processes of cementitious phases interacting with sodium and chloride ions at the nano-scale were identified using STXM and XANES measurements. A mathematical model and FEM procedure were developed to identify the effect of surface treatments at macro-scale on ionic transport phenomena of surface-treated concrete. Finally, this dissertation introduced a new material, calcined layered double hydroxide (CLDH), to prevent chloride-induced deterioration.

  1. Fast vessel segmentation in retinal images using multi-scale enhancement and second-order local entropy

    NASA Astrophysics Data System (ADS)

    Yu, H.; Barriga, S.; Agurto, C.; Zamora, G.; Bauman, W.; Soliz, P.

    2012-03-01

    Retinal vasculature is one of the most important anatomical structures in digital retinal photographs. Accurate segmentation of retinal blood vessels is an essential task in automated analysis of retinopathy. This paper presents a new and effective vessel segmentation algorithm that features computational simplicity and fast implementation. This method uses morphological pre-processing to decrease the disturbance of bright structures and lesions before vessel extraction. Next, a vessel probability map is generated by computing the eigenvalues of the second derivatives of Gaussian filtered image at multiple scales. Then, the second order local entropy thresholding is applied to segment the vessel map. Lastly, a rule-based decision step, which measures the geometric shape difference between vessels and lesions is applied to reduce false positives. The algorithm is evaluated on the low-resolution DRIVE and STARE databases and the publicly available high-resolution image database from Friedrich-Alexander University Erlangen-Nuremberg, Germany). The proposed method achieved comparable performance to state of the art unsupervised vessel segmentation methods with a competitive faster speed on the DRIVE and STARE databases. For the high resolution fundus image database, the proposed algorithm outperforms an existing approach both on performance and speed. The efficiency and robustness make the blood vessel segmentation method described here suitable for broad application in automated analysis of retinal images.

  2. Tri-modal microscopy with multiphoton and optical coherence microscopy/tomography for multi-scale and multi-contrast imaging

    PubMed Central

    Chong, Shau Poh; Lai, Tom; Zhou, Yifeng; Tang, Shuo

    2013-01-01

    Multi-scale multimodal microscopy is a very useful technique by providing multiple imaging contrasts with adjustable field of views and spatial resolutions. Here, we present a tri-modal microscope combining multiphoton microscopy (MPM), optical coherence microscopy (OCM) and optical coherence tomography (OCT) for subsurface visualization of biological tissues. The advantages of the tri-modal system are demonstrated on various biological samples. It enables the visualization of multiple intrinsic contrasts including scattering, two-photon excitation fluorescence (TPEF), and second harmonic generation (SHG). It also enables a rapid scanning over a large tissue area and a high resolution zoom-in for cellular-level structures on regions of interest. The tri-modal microscope can be important for label-free imaging to obtain a sufficient set of parameters for reliable sample analysis. PMID:24049679

  3. 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.

  4. 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.

  5. Cloud detection in all-sky images via multi-scale neighborhood features and multiple supervised learning techniques

    NASA Astrophysics Data System (ADS)

    Cheng, Hsu-Yung; Lin, Chih-Lung

    2017-01-01

    Cloud detection is important for providing necessary information such as cloud cover in many applications. Existing cloud detection methods include red-to-blue ratio thresholding and other classification-based techniques. In this paper, we propose to perform cloud detection using supervised learning techniques with multi-resolution features. One of the major contributions of this work is that the features are extracted from local image patches with different sizes to include local structure and multi-resolution information. The cloud models are learned through the training process. We consider classifiers including random forest, support vector machine, and Bayesian classifier. To take advantage of the clues provided by multiple classifiers and various levels of patch sizes, we employ a voting scheme to combine the results to further increase the detection accuracy. In the experiments, we have shown that the proposed method can distinguish cloud and non-cloud pixels more accurately compared with existing works.

  6. Multi-scale lidar-based approaches to characterizing stream networks, surface roughness and landforms of forest watersheds

    NASA Astrophysics Data System (ADS)

    Brubaker, Kristen M.

    The overall objective of this study is to utilize high resolution lidar-derived digital elevation models (DEMs) to improve classification and understanding of forested watersheds. Since geographic information systems technology became broadly used in natural resource fields in the 1980s, scientists have used digital elevation models to study aspects of forested ecosystems including the delineation of drainage networks, geomorphic modeling, and ecological classification for forest management and ecosystem management. With recently available lidar elevation data, we have improved our ability to "see" features on the landscape by orders of magnitude. Existing methodologies for assessing geomorphometry and hydrologic network delineation across the landscape may not suffice for all tasks. By taking a multi-scale, multidisciplinary approach, we can improve our understanding of headwater ecosystems and how to assess and predict the relationship between terrain and vegetation. This research was performed in the Leading Ridge experimental watersheds, the site of a long-term study analyzing the impact of forest management practices on stream water quality. The Leading Ridge experimental watersheds are also located within the Susquehanna/Shale Hills Critical Zone Observatory. In order to assess the ability of lidar-derived DEM to improve stream network modeling, the stream network for Leading Ridge watershed number one was recorded using a GPS unit during base flow conditions. The stream network was then modeled using lidar-derived 1 m, 3 m, and 10 m resolution DEMs as well as photogrammetrically-derived NED (National Elevation Dataset) DEM. All of the lidar-derived DEMs resulted in a relatively accurate stream network model, with the 3 m DEM providing the most accurate model. There was no significant difference between any of the lidar-derived modeled stream networks, but they were all significantly different from the NED DEM-derived stream network, which was much less

  7. Development of a multi-scale and multi-modality imaging system to characterize tumours and their microenvironment in vivo

    NASA Astrophysics Data System (ADS)

    Rouffiac, Valérie; Ser-Leroux, Karine; Dugon, Emilie; Leguerney, Ingrid; Polrot, Mélanie; Robin, Sandra; Salomé-Desnoulez, Sophie; Ginefri, Jean-Christophe; Sebrié, Catherine; Laplace-Builhé, Corinne

    2015-03-01

    In vivo high-resolution imaging of tumor development is possible through dorsal skinfold chamber implantable on mice model. However, current intravital imaging systems are weakly tolerated along time by mice and do not allow multimodality imaging. Our project aims to develop a new chamber for: 1- long-term micro/macroscopic visualization of tumor (vascular and cellular compartments) and tissue microenvironment; and 2- multimodality imaging (photonic, MRI and sonography). Our new experimental device was patented in March 2014 and was primarily assessed on 75 mouse engrafted with 4T1-Luc tumor cell line, and validated in confocal and multiphoton imaging after staining the mice vasculature using Dextran 155KDa-TRITC or Dextran 2000kDa-FITC. Simultaneously, a universal stage was designed for optimal removal of respiratory and cardiac artifacts during microscopy assays. Experimental results from optical, ultrasound (Bmode and pulse subtraction mode) and MRI imaging (anatomic sequences) showed that our patented design, unlike commercial devices, improves longitudinal monitoring over several weeks (35 days on average against 12 for the commercial chamber) and allows for a better characterization of the early and late tissue alterations due to tumour development. We also demonstrated the compatibility for multimodality imaging and the increase of mice survival was by a factor of 2.9, with our new skinfold chamber. Current developments include: 1- defining new procedures for multi-labelling of cells and tissue (screening of fluorescent molecules and imaging protocols); 2- developing ultrasound and MRI imaging procedures with specific probes; 3- correlating optical/ultrasound/MRI data for a complete mapping of tumour development and microenvironment.

  8. Correlative multi-scale 3D imaging of shales: An example from the Haynesville-Bossier Shale, southeast USA

    NASA Astrophysics Data System (ADS)

    Ma, Lin; Dowey, Patrick; Fauchille, Anne-Laure; Taylor, Kevin; Lee, Peter

    2017-04-01

    Shale and shale reservoirs have attracted the attention of both industry and scholars. However, the strong heterogeneity at different scales and the extremely fine-grained nature of shales makes macroscopic and microscopic characterisation highly challenging. Recent advances in imaging techniques have provided many novel characterisation opportunities of shale components and microstructures at multiple scales. Correlative 3D imaging, where multiple techniques are combined, is playing an increasingly important role in the imaging and quantification of shale microstructures. In this study, combined utilization of X-ray computed tomography (XCT) and 3D electron microscopy (3D-EM) characterized the heterogeneity of shale microstructures over a large range of scales, from macro-scale to nano-scale ( 100 - 10-9 m). Specifically, core-scale XCT provides bedding/lamination/fractures information at macroscale; Micro-CT quantifies granular minerals and large piece of organic matter at meso-scale; Nano-CT gives fine-grain minerals and small pieces of organic matter at micro-scale; FIB-SEM and TEM tomography provide nano-scale images, and clay mineral and nano-pores can be resolved at this scale. Other chemical and physical measurements correlated to imaging techniques can provide complementary information for minerals, organic matter and pores. The application of these techniques can be used more widely for imaging particular features in different shales and further lead to a greater understanding of properties in the heterogeneous and low-permeability systems.

  9. Multi-scale 3D X-ray Imaging Capabilities at the Advanced Photon Source - Current status and future direction (Invited)

    NASA Astrophysics Data System (ADS)

    DeCarlo, F.; Xiao, X.; Khan, F.; Glowacki, A.; Schwarz, N.; Jacobsen, C.

    2011-12-01

    In x-ray computed μ-tomography (μ-XCT), a thin scintillator screen is coupled to a visible light lens and camera system to obtain micrometer-scale transmission imaging of specimens as large as a few millimeters. Recent advances in detector technology allow collecting these images at unprecedented frame rates. For a high x-ray flux density synchrotron facility like the Advanced Photon Source (APS), the detector exposure time ranges from hundreds of milliseconds to hundreds of picoseconds, making possible to acquire a full 3D micrometer-resolution dataset in less than one second. The micron resolution limitation of parallel x-ray beam projection systems can be overcame by Transmission X-ray Microscopes (TXM) where part of the image magnification is done in x-ray regime using x-ray optics like capillary condensers and Fresnel zone plates. These systems, when installed on a synchrotron x-ray source, can generate 2D images with up to 20 nm resolution with second exposure time and collect a full 3D nano-resolution dataset in few minutes. μ-XCT and TXM systems available at the x-ray imaging beamlines of the APS are routinely used in material science and geoscience applications where high-resolution and fast 3D imaging are instrumental in extracting in situ four-dimensional dynamic information. In this presentation we describe the computational challenges associated with μ-XCT and TXM systems and present the framework and infrastructure developed at the APS to allow for routine multi-scale data integration between the two systems.

  10. Multi-scale 3D X-ray Imaging Capabilities at the Advanced Photon Source - Current status and future direction (Invited)

    NASA Astrophysics Data System (ADS)

    DeCarlo, F.; Xiao, X.; Khan, F.; Glowacki, A.; Schwarz, N.; Jacobsen, C.

    2013-12-01

    In x-ray computed μ-tomography (μ-XCT), a thin scintillator screen is coupled to a visible light lens and camera system to obtain micrometer-scale transmission imaging of specimens as large as a few millimeters. Recent advances in detector technology allow collecting these images at unprecedented frame rates. For a high x-ray flux density synchrotron facility like the Advanced Photon Source (APS), the detector exposure time ranges from hundreds of milliseconds to hundreds of picoseconds, making possible to acquire a full 3D micrometer-resolution dataset in less than one second. The micron resolution limitation of parallel x-ray beam projection systems can be overcame by Transmission X-ray Microscopes (TXM) where part of the image magnification is done in x-ray regime using x-ray optics like capillary condensers and Fresnel zone plates. These systems, when installed on a synchrotron x-ray source, can generate 2D images with up to 20 nm resolution with second exposure time and collect a full 3D nano-resolution dataset in few minutes. μ-XCT and TXM systems available at the x-ray imaging beamlines of the APS are routinely used in material science and geoscience applications where high-resolution and fast 3D imaging are instrumental in extracting in situ four-dimensional dynamic information. In this presentation we describe the computational challenges associated with μ-XCT and TXM systems and present the framework and infrastructure developed at the APS to allow for routine multi-scale data integration between the two systems.

  11. Multi-scale model of resistive-type superconducting fault current limiters based on 2G HTS coated conductors

    NASA Astrophysics Data System (ADS)

    Bonnard, Charles-Henri; Sirois, Frédéric; Lacroix, Christian; Didier, Gaëtan

    2017-01-01

    In order to plan the integration of superconducting fault current limiters (SFCLs) in power systems, accurate models of SFCLs must be made available in commercial power system transient simulators. In this context, we developed such a model for the EMTP-RV software package, a power system transient simulator widely used by power utilities. The model can be used with any resistive-type SFCL (rSFCL) made of high temperature superconductor (HTS) tapes, which are discretized in ‘electro-thermal elements’. Those elements consist solely of electric circuit components, and are used to represent portions of tape of various sizes and dimensions (a ‘multi-scale’ approach). Both the electrical and thermal behaviors of the tape are modeled, including interfacial effects, nonlinear properties of materials and heat transfer to the surrounding environment. Such a multi-scale model can simulate accurately both the local quench dynamics of HTS tapes (microscopic scale) and the global impact of the rSFCL on the power system (macroscopic/system scale). In this paper, the model is used to compute phenomena such as propagation velocity of a hot spot and heat diffusion through the thickness of the tape. Results were verified by comparing EMTP-RV results with finite element simulations. In addition to the development of the multi-scale model itself, which is the major contribution of this paper, the use of the model allowed us to determine the conditions of validity of the commonly used ‘homogenization’ of the thermal properties across the tape thickness. Indeed, when the current flowing into the rSFCL is slightly above its critical current I c (and up to 2{I}{{c}}), very important errors in the power waveforms arise, leading to potentially wrong decisions of protection systems. Homogenized thermal models should thus be used with great care in practice.

  12. Sensor-based auto-focusing system using multi-scale feature extraction and phase correlation matching.

    PubMed

    Jang, Jinbeum; Yoo, Yoonjong; Kim, Jongheon; Paik, Joonki

    2015-03-10

    This paper presents a novel auto-focusing system based on a CMOS sensor containing pixels with different phases. Robust extraction of features in a severely defocused image is the fundamental problem of a phase-difference auto-focusing system. In order to solve this problem, a multi-resolution feature extraction algorithm is proposed. Given the extracted features, the proposed auto-focusing system can provide the ideal focusing position using phase correlation matching. The proposed auto-focusing (AF) algorithm consists of four steps: (i) acquisition of left and right images using AF points in the region-of-interest; (ii) feature extraction in the left image under low illumination and out-of-focus blur; (iii) the generation of two feature images using the phase difference between the left and right images; and (iv) estimation of the phase shifting vector using phase correlation matching. Since the proposed system accurately estimates the phase difference in the out-of-focus blurred image under low illumination, it can provide faster, more robust auto focusing than existing systems.

  13. Sensor-Based Auto-Focusing System Using Multi-Scale Feature Extraction and Phase Correlation Matching

    PubMed Central

    Jang, Jinbeum; Yoo, Yoonjong; Kim, Jongheon; Paik, Joonki

    2015-01-01

    This paper presents a novel auto-focusing system based on a CMOS sensor containing pixels with different phases. Robust extraction of features in a severely defocused image is the fundamental problem of a phase-difference auto-focusing system. In order to solve this problem, a multi-resolution feature extraction algorithm is proposed. Given the extracted features, the proposed auto-focusing system can provide the ideal focusing position using phase correlation matching. The proposed auto-focusing (AF) algorithm consists of four steps: (i) acquisition of left and right images using AF points in the region-of-interest; (ii) feature extraction in the left image under low illumination and out-of-focus blur; (iii) the generation of two feature images using the phase difference between the left and right images; and (iv) estimation of the phase shifting vector using phase correlation matching. Since the proposed system accurately estimates the phase difference in the out-of-focus blurred image under low illumination, it can provide faster, more robust auto focusing than existing systems. PMID:25763645

  14. Modeling Hierarchical Non-Precious Metal Catalyst Cathodes for PEFCs Using Multi-Scale X-ray CT Imaging

    DOE PAGES

    Komini Babu, S.; Chung, H. T.; Wu, G.; ...

    2014-08-18

    This paper reports the development of a model for simulating polymer electrolyte fuel cells (PEFCs) with non-precious metal catalyst (NPMC) cathodes. NPMCs present an opportunity to dramatically reduce the cost of PEFC electrodes by removing the costly Pt catalyst. To address the significant transport losses in thick NPMC cathodes (ca. >60 µm), we developed a hierarchical electrode model that resolves the unique structure of the NPMCs we studied. A unique feature of the approach is the integration of the model with morphology data extracted from nano-scale resolution X-ray computed tomography (nano-CT) imaging of the electrodes. A notable finding is themore » impact of the liquid water accumulation in the electrode and the significant performance improvement possible if electrode flooding is mitigated.« less

  15. Modeling Hierarchical Non-Precious Metal Catalyst Cathodes for PEFCs Using Multi-Scale X-ray CT Imaging

    SciTech Connect

    Komini Babu, S.; Chung, H. T.; Wu, G.; Zelenay, P.; Litster, S.

    2014-08-18

    This paper reports the development of a model for simulating polymer electrolyte fuel cells (PEFCs) with non-precious metal catalyst (NPMC) cathodes. NPMCs present an opportunity to dramatically reduce the cost of PEFC electrodes by removing the costly Pt catalyst. To address the significant transport losses in thick NPMC cathodes (ca. >60 µm), we developed a hierarchical electrode model that resolves the unique structure of the NPMCs we studied. A unique feature of the approach is the integration of the model with morphology data extracted from nano-scale resolution X-ray computed tomography (nano-CT) imaging of the electrodes. A notable finding is the impact of the liquid water accumulation in the electrode and the significant performance improvement possible if electrode flooding is mitigated.

  16. Multi-Scale Imaging of Earth's Deep Interior: New Constraints on Structure and Thermo- chemical Evolution of Earth's Mantle

    NASA Astrophysics Data System (ADS)

    van der Hilst, R. D.; de Hoop, M. V.; Wang, P.; Cao, Q.; Shang, X.

    2008-12-01

    Since seismic tomography began its revolution of global geophysics some 30 years ago we have made tremendous progress in our ability to image and understand structures and processes in Earth's deep interior. The long wavelength (global) structures discovered in pioneering studies in the early 198ies (e.g., Dziewonski and Woodhouse, 1984) have largely survived the test of time, and later studies have pushed the tomographic models to more-and-more detail. As a result, consensus has emerged on the large scale variations in mantle P and S wavespeed, the presence of compositional heterogeneity, and an intermediate style convection that is neither strictly layered nor unobstructed whole-mantle flow. Tomography constrains smooth variations in material properties. To understand better the radial structure of Earth's interior, along with (mass, heat) fluxes across interfaces and boundary layers, we also need constraints on rapid transitions in material properties. Seminal discoveries have been made through analysis of data associated with reflection, refraction, and phase conversion at interfaces. This trend continues, but the explosion in availability of waveforms from broadband seismograph networks all over the world, combined with advances in inverse scattering theory and high-performance computing, has begun to make global "exploration seismics" of deep Earth interfaces possible. We report new results of large-scale, high resolution imaging of the core-mantle boundary region (D") with inverse scattering of ScS and SKKS wavefields (either separately or jointly) and of the upper mantle transition zone with the wavefield that contains SS precursors due to underside reflection at mantle discontinuities. In the future, inverse scattering with wavefields recorded at global networks may enable the systematic scanning of Earth's mantle and CMB region, which in tandem with parallel advances in mineralogy and phase chemistry research may reveal that the mantle that we often think

  17. Multi-Scale Environment For Simulation And Materials Characterization In Stress Management For 3D IC TSV-Based Technologies—Effect Of Stress On The Device Characteristics

    NASA Astrophysics Data System (ADS)

    Sukharev, Valeriy; Zschech, Ehrenfried

    2011-09-01

    The paper addresses the growing need in a simulation-based design verification flow capable to analyze any design of 3D IC stacks and to determine across-die out-of-spec variations in device electrical characteristics caused by layout and through-silicon-via (TSV)/package-induced mechanical stress. The limited test and characterization capabilities of 3D IC stacks and a strict "good die" requirement make this type of analysis really critical for the achievement of an acceptable level of functional and parametric yield and reliability. The paper focuses on the development of a design-for-manufacturability (DFM) type of methodology for managing mechanical stresses during a sequence of designs of 3D TSV-based dies, stacks and packages. A set of physics-based compact models for a multi-scale simulation, to assess the mechanical stress across the device layers in silicon dies stacked and packaged with the 3D TSV technology, is proposed. A strategy for a materials data generation to feed simulation and a respective materials characterization approach are proposed, with the goal to establish a database for multi-scale materials parameters of wafer-level and package-level structures. A proposal for model validation based and a calibration approach based on fitting the simulation results to measured local stress components and to electrical characteristics of the test-chip devices are discussed.

  18. Multiplexed multi-scale imaging: novel roles for the scaffold protein IQGAP1 in epithelial cell development (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Schweikhard, Volker

    2016-02-01

    The precise sub-cellular spatial localization of multi-protein complexes is increasingly recognized as a key mechanism governing the organization of mammalian cells. Consequently, there is a need for novel microscopy techniques capable of investigating such sub-cellular architectures in comprehensive detail. Here, we applied a novel multiplexed STORM super-resolution microscopy technique, in combination with high-throughput immunofluorescence microscopy and live-cell imaging, to investigate the roles of the scaffold protein IQGAP1 in epithelial cells. IQGAP1 is known to orchestrate a wide range of biological processes, including intracellular signaling, cytoskeletal regulation, cell-cell adhesion, and protein trafficking, by forming distinct complexes with a number of known interaction partners, and recruiting these complexes to specific subcellular locations. Our results demonstrate that, in addition to supporting epithelial adherens junctions by associating with specialized cortical actin structures, IQGAP1 plays a second role in which it controls the confinement of a unique, previously undocumented class of membranous compartments to the basal actin cortex. These largely immotile yet highly dynamic structures appear transiently as cells merge into clusters and establish of apical-basolateral (epithelial) polarity, and are identified as an intermediate compartment in the endocytic recycling pathways for cell junction complexes and cell surface receptors. Although these two functions of IQGAP1 occur in parallel and largely independently of each other, they both support the maturation and maintenance of polarized epithelial cell architectures.

  19. Multi-scale reasonable attenuation tomography analysis (MuRAT): An imaging algorithm designed for volcanic regions

    NASA Astrophysics Data System (ADS)

    De Siena, L.; Thomas, C.; Aster, R.

    2014-05-01

    The attenuation of body-wave amplitudes with propagation distance can be used to provide detailed tomographic images of seismic interfaces, fluid reservoirs, and melt batches in the crust. The high sensitivity of body-wave energies to high-scattering structures becomes an obstacle when we try to apply attenuation tomography to small-scale volcanic media, where we must take into account the complexities induced by strong heterogeneous scattering, topography, and uncertain source modeling in the recorded wave-fields. The MuRAT code uses a source- and site-independent coda-normalization method to obtain frequency-dependent measurements of P-to-coda and S-to-coda energy ratios. The code inverts these data for both the geometrical spreading factor and the spatially-dependent quality factors (Q), providing additional attenuation information in the regions where velocity tomography is available. The high sensitivity of coda-waves to highly heterogeneous structures highlights zones of anomalous scattering, which may corrupt amplitude-dependent attenuation measurements, and where basal assumptions of linear optics may go unfulfilled. A multi-step tomographic inversion increases the stability of the results obtained in regions of high heterogeneity (e.g., the volcanic edifice) by the inclusion of data corresponding to either sources or stations located in regions of lower heterogeneity. On the other hand, a mere increase in the number of rays entirely contained in the heterogeneous structures affects both the stability and the effective resolution of the results. We apply the code to two small waveform datasets recorded at an active (Mount St. Helens) and at a quiescent (Mount Vesuvius) volcano. The results show that the seismicity located inside or under the volcanic edifice produces an increase of the low-frequency energy ratios with travel time in both areas. In our interpretation, the anomalous concentration of energy which affects any waveform recorded on the cone

  20. 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

  1. 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

  2. A multi-scale Monte Carlo method for electrolytes

    NASA Astrophysics Data System (ADS)

    Liang, Yihao; Xu, Zhenli; Xing, Xiangjun

    2015-08-01

    Artifacts arise in the simulations of electrolytes using periodic boundary conditions (PBCs). We show the origin of these artifacts are the periodic image charges and the constraint of charge neutrality inside the simulation box, both of which are unphysical from the view point of real systems. To cure these problems, we introduce a multi-scale Monte Carlo (MC) method, where ions inside a spherical cavity are simulated explicitly, while ions outside are treated implicitly using a continuum theory. Using the method of Debye charging, we explicitly derive the effective interactions between ions inside the cavity, arising due to the fluctuations of ions outside. We find that these effective interactions consist of two types: (1) a constant cavity potential due to the asymmetry of the electrolyte, and (2) a reaction potential that depends on the positions of all ions inside. Combining the grand canonical Monte Carlo (GCMC) with a recently developed fast algorithm based on image charge method, we perform a multi-scale MC simulation of symmetric electrolytes, and compare it with other simulation methods, including PBC + GCMC method, as well as large scale MC simulation. We demonstrate that our multi-scale MC method is capable of capturing the correct physics of a large system using a small scale simulation.

  3. An improved multi-scale autoconvolution transform

    NASA Astrophysics Data System (ADS)

    Shao, Chunyan; Ding, Qinghai; Luo, Haibo

    2014-11-01

    Affine invariant feature computing method is an important part of statistical pattern recognition due to the robustness, repeatability, distinguishability and wildly applicability of affine invariant feature. Multi-Scale Autoconvolution (MSA) is a transformation proposed by Esa Rathu which can get complete affine invariant feature. Rathu proved that the linear relationship of any four non-colinear points is affine invariant. The transform is based on a probabilistic interpretation of the image function. The performance of MSA transform is better on image occlusion and noise, but it is sensitive to illumination variation. Aim at this problem, an improved MSA transform is proposed in this paper by computing the map of included angle between N-domain vectors. The proposed method is based on the probabilistic interpretation of N-domain vectors included angle map. N-domain vectors included angle map is built through computing the vectors included angle where the vectors are composed of the image point and its N-domain image points. This is due to that the linear relationship of included angles between vectors composed of any four non-colinear points is an affine invariance. This paper proves the method can be derived in mathematical aspect. The transform values can be used as descriptors for affine invariant pattern classification. The main contribution of this paper is applying the N-domain vectors included angle map while taking the N-domain vector included angle as the probability of the pixel. This computing method adapts the illumination variation better than taking the gray value of the pixel as the probability. We illustrate the performance of improved MSA transform in various object classification tasks. As shown by a comparison with the original MSA transform based descriptors and affine invariant moments, the proposed method appears to be better to cope with illumination variation, image occlusion and image noise.

  4. Hands-on, online, and workshop-based K-12 weather and climate education resources from the Center for Multi-scale Modeling of Atmospheric Processes

    NASA Astrophysics Data System (ADS)

    Foster, S. Q.; Johnson, R. M.; Randall, D. A.; Denning, A.; Burt, M. A.; Gardiner, L.; Genyuk, J.; Hatheway, B.; Jones, B.; La Grave, M. L.; Russell, R. M.

    2009-12-01

    The need for improving the representation of cloud processes in climate models has been one of the most important limitations of the reliability of climate-change simulations. Now in its fourth year, the National Science Foundation-funded Center for Multi-scale Modeling of Atmospheric Processes (CMMAP) at Colorado State University (CSU) is addressing this problem through a revolutionary new approach to representing cloud processes on their native scales, including the cloud-scale interaction processes that are active in cloud systems. CMMAP has set ambitious education and human-resource goals to share basic information about the atmosphere, clouds, weather, climate, and modeling with diverse K-12 and public audiences. This is accomplished through collaborations in resource development and dissemination between CMMAP scientists, CSU’s Little Shop of Physics (LSOP) program, and the Windows to the Universe (W2U) program at University Corporation for Atmospheric Research (UCAR). Little Shop of Physics develops new hands on science activities demonstrating basic science concepts fundamental to understanding atmospheric characteristics, weather, and climate. Videos capture demonstrations of children completing these activities which are broadcast to school districts and public television programs. CMMAP and LSOP educators and scientists partner in teaching a summer professional development workshops for teachers at CSU with a semester's worth of college-level content on the basic physics of the atmosphere, weather, climate, climate modeling, and climate change, as well as dozens of LSOP inquiry-based activities suitable for use in classrooms. The W2U project complements these efforts by developing and broadly disseminating new CMMAP-related online content pages, animations, interactives, image galleries, scientists’ biographies, and LSOP videos to K-12 and public audiences. Reaching nearly 20 million users annually, W2U is highly valued as a curriculum enhancement

  5. Multi-scale Drivers of Variations in Atmospheric Evaporative Demand Based on Observations and Physically-based Modeling

    NASA Astrophysics Data System (ADS)

    Peng, L.; Sheffield, J.; Li, D.

    2015-12-01

    Evapotranspiration (ET) is a key link between the availability of water resources and climate change and climate variability. Variability of ET has important environmental and socioeconomic implications for managing hydrological hazards, food and energy production. Although there have been many observational and modeling studies of ET, how ET has varied and the drivers of the variations at different temporal scales remain elusive. Much of the uncertainty comes from the atmospheric evaporative demand (AED), which is the combined effect of radiative and aerodynamic controls. The inconsistencies among modeled AED estimates and the limited observational data may originate from multiple sources including the limited time span and uncertainties in the data. To fully investigate and untangle the intertwined drivers of AED, we present a spectrum analysis to identify key controls of AED across multiple temporal scales. We use long-term records of observed pan evaporation for 1961-2006 from 317 weather stations across China and physically-based model estimates of potential evapotranspiration (PET). The model estimates are based on surface meteorology and radiation derived from reanalysis, satellite retrievals and station data. Our analyses show that temperature plays a dominant role in regulating variability of AED at the inter-annual scale. At the monthly and seasonal scales, the primary control of AED shifts from radiation in humid regions to humidity in dry regions. Unlike many studies focusing on the spatial pattern of ET drivers based on a traditional supply and demand framework, this study underlines the importance of temporal scales when discussing controls of ET variations.

  6. Knickzone Extraction Tool (KET) - A new ArcGIS toolset for automatic extraction of knickzones from a DEM based on multi-scale stream gradients

    NASA Astrophysics Data System (ADS)

    Zahra, Tuba; Paudel, Uttam; Hayakawa, Yuichi S.; Oguchi, Takashi

    2017-04-01

    Extraction of knickpoints or knickzones from a Digital Elevation Model (DEM) has gained immense significance owing to the increasing implications of knickzones on landform development. However, existing methods for knickzone extraction tend to be subjective or require time-intensive data processing. This paper describes the proposed Knickzone Extraction Tool (KET), a new raster-based Python script deployed in the form of an ArcGIS toolset that automates the process of knickzone extraction and is both fast and more user-friendly. The KET is based on multi-scale analysis of slope gradients along a river course, where any locally steep segment (knickzone) can be extracted as an anomalously high local gradient. We also conducted a comparative analysis of the KET and other contemporary knickzone identification techniques. The relationship between knickzone distribution and its morphometric characteristics are also examined through a case study of a mountainous watershed in Japan.

  7. Building and Refining Protein Models within Cryo-electron Microscopy Density Maps Based on Homology Modeling and Multi-scale Structure Refinement

    PubMed Central

    Zhu, Jiang; Cheng, Lingpeng; Fang, Qin; Hong Zhou, Z.; Honig, Barry

    2010-01-01

    Summary Automatic modeling methods using cryo-electron microscopy (cryoEM) density maps as constrains are promising approaches to building atomic models of individual proteins or protein domains. However, their application to large macromolecular assemblies has not been possible largely due to computational limitations inherent to such unsupervised methods. Here we describe a new method, EM-IMO, for building, modifying and refining local structures of protein models using cryoEM maps as a constraint. As a supervised refinement method, EM-IMO allows users to specify parameters derived from inspections, so as to guide, and as a consequence, significantly speed up the refinement. An EM-IMO-based refinement protocol is first benchmarked on a data set of 50 homology models using simulated density maps. A multi-scale refinement strategy that combines EM-IMO-based and molecular dynamics (MD)-based refinement is then applied to build backbone models for the seven conformers of the five capsid proteins in our near-atomic resolution cryoEM map of the grass carp reovirus (GCRV) virion, a member of the aquareovirus genus of the Reoviridae family. The refined models allow us to reconstruct a backbone model of the entire GCRV capsid and provide valuable functional insights that are described in the accompanying publication. Our study demonstrates that the integrated use of homology modeling and a multi-scale refinement protocol that combines supervised and automated structure refinement offers a practical strategy for building atomic models based on medium- to high-resolution cryoEM density maps. PMID:20109465

  8. Multi-scale non-local denoising method in neuroimaging.

    PubMed

    Chen, Yiping; Wang, Cheng; Wang, Liansheng

    2016-03-17

    Non-local means algorithm can remove image noise in a unique way that is contrary to traditional techniques. This is because it not only smooths the image but it also preserves the information details of the image. However, this method suffers from high computational complexity. We propose a multi-scale non-local means method in which adaptive multi-scale technique is implemented. In practice, based on each selected scale, the input image is divided into small blocks. Then, we remove the noise in the given pixel by using only one block. This can overcome the low efficiency problem caused by the original non-local means method. Our proposed method also benefits from the local average gradient orientation. In order to perform evaluation, we compared the processed images based on our technique with the ones by the original and the improved non-local means denoising method. Extensive experiments are conducted and results shows that our method is faster than the original and the improved non-local means method. It is also proven that our implemented method is robust enough to remove noise in the application of neuroimaging.

  9. Drought impacts on vegetation dynamics in the Mediterranean based on remote sensing and multi-scale drought indices

    NASA Astrophysics Data System (ADS)

    Trigo, Ricardo; Gouveia, Celia M.; Beguería, Santiago; Vicente-Serrano, Sergio

    2015-04-01

    A number of recent studies have identified a significant increase in the frequency of drought events in the Mediterranean basin (e.g. Trigo et al., 2013, Vicente-Serrano et al., 2014). In the Mediterranean region, large drought episodes are responsible for the most negative impacts on the vegetation including significant losses of crop yield, increasing risk of forest fires (e.g. Gouveia et al., 2012) and even forest decline. The aim of the present work is to analyze in detail the impacts of drought episodes on vegetation in the Mediterranean basin behavior using NDVI data from (from GIMMS) for entire Mediterranean basin (1982-2006) and the multi-scale drought index (the Standardised Precipitation-Evapotranspiration Index (SPEI). Correlation maps between fields of monthly NDVI and SPEI for at different time scales (1-24 months) were computed in order to identify the regions and seasons most affected by droughts. Affected vegetation presents high spatial and seasonal variability, with a maximum in summer and a minimum in winter. During February 50% of the affected pixels corresponded to a time scale of 6 months, while in November the most frequent time scale corresponded to 3 months, representing more than 40% of the affected region. Around 20% of grid points corresponded to the longer time scales (18 and 24 months), persisting fairly constant along the year. In all seasons the wetter clusters present higher NDVI values which indicates that aridity holds a key role to explain the spatial differences in the NDVI values along the year. Despite the localization of these clusters in areas with higher values of monthly water balance, the strongest control of drought on vegetation activity are observed for the drier classes located over regions with smaller absolute values of water balance. Gouveia C.M., Bastos A., Trigo R.M., DaCamara C.C. (2012) "Drought impacts on vegetation in the pre and post-fire events over Iberian Peninsula". Natural Hazards and Earth System

  10. Targeting the Biophysical Properties of the Myeloma Initiating Cell Niches: A Pharmaceutical Synergism Analysis Using Multi-Scale Agent-Based Modeling

    PubMed Central

    Su, Jing; Zhang, Le; Zhang, Wen; Choi, Dong Song; Wen, Jianguo; Jiang, Beini; Chang, Chung-Che; Zhou, Xiaobo

    2014-01-01

    Multiple myeloma, the second most common hematological cancer, is currently incurable due to refractory disease relapse and development of multiple drug resistance. We and others recently established the biophysical model that myeloma initiating (stem) cells (MICs) trigger the stiffening of their niches via SDF-1/CXCR4 paracrine; The stiffened niches then promote the colonogenesis of MICs and protect them from drug treatment. In this work we examined in silico the pharmaceutical potential of targeting MIC niche stiffness to facilitate cytotoxic chemotherapies. We first established a multi-scale agent-based model using the Markov Chain Monte Carlo approach to recapitulate the niche stiffness centric, pro-oncogenetic positive feedback loop between MICs and myeloma-associated bone marrow stromal cells (MBMSCs), and investigated the effects of such intercellular chemo-physical communications on myeloma development. Then we used AMD3100 (to interrupt the interactions between MICs and their stroma) and Bortezomib (a recently developed novel therapeutic agent) as representative drugs to examine if the biophysical properties of myeloma niches are drugable. Results showed that our model recaptured the key experimental observation that the MBMSCs were more sensitive to SDF-1 secreted by MICs, and provided stiffer niches for these initiating cells and promoted their proliferation and drug resistance. Drug synergism analysis suggested that AMD3100 treatment undermined the capability of MICs to modulate the bone marrow microenvironment, and thus re-sensitized myeloma to Bortezomib treatments. This work is also the first attempt to virtually visualize in 3D the dynamics of the bone marrow stiffness during myeloma development. In summary, we established a multi-scale model to facilitate the translation of the niche-stiffness centric myeloma model as well as experimental observations to possible clinical applications. We concluded that targeting the biophysical properties of stem

  11. Targeting the biophysical properties of the myeloma initiating cell niches: a pharmaceutical synergism analysis using multi-scale agent-based modeling.

    PubMed

    Su, Jing; Zhang, Le; Zhang, Wen; Choi, Dong Song; Wen, Jianguo; Jiang, Beini; Chang, Chung-Che; Zhou, Xiaobo

    2014-01-01

    Multiple myeloma, the second most common hematological cancer, is currently incurable due to refractory disease relapse and development of multiple drug resistance. We and others recently established the biophysical model that myeloma initiating (stem) cells (MICs) trigger the stiffening of their niches via SDF-1/CXCR4 paracrine; The stiffened niches then promote the colonogenesis of MICs and protect them from drug treatment. In this work we examined in silico the pharmaceutical potential of targeting MIC niche stiffness to facilitate cytotoxic chemotherapies. We first established a multi-scale agent-based model using the Markov Chain Monte Carlo approach to recapitulate the niche stiffness centric, pro-oncogenetic positive feedback loop between MICs and myeloma-associated bone marrow stromal cells (MBMSCs), and investigated the effects of such intercellular chemo-physical communications on myeloma development. Then we used AMD3100 (to interrupt the interactions between MICs and their stroma) and Bortezomib (a recently developed novel therapeutic agent) as representative drugs to examine if the biophysical properties of myeloma niches are drugable. Results showed that our model recaptured the key experimental observation that the MBMSCs were more sensitive to SDF-1 secreted by MICs, and provided stiffer niches for these initiating cells and promoted their proliferation and drug resistance. Drug synergism analysis suggested that AMD3100 treatment undermined the capability of MICs to modulate the bone marrow microenvironment, and thus re-sensitized myeloma to Bortezomib treatments. This work is also the first attempt to virtually visualize in 3D the dynamics of the bone marrow stiffness during myeloma development. In summary, we established a multi-scale model to facilitate the translation of the niche-stiffness centric myeloma model as well as experimental observations to possible clinical applications. We concluded that targeting the biophysical properties of stem

  12. 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.

  13. 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...

  14. 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...

  15. Local variance for multi-scale analysis in geomorphometry

    PubMed Central

    Drăguţ, Lucian; Eisank, Clemens; Strasser, Thomas

    2011-01-01

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

  16. Local variance for multi-scale analysis in geomorphometry

    NASA Astrophysics Data System (ADS)

    Drăguţ, Lucian; Eisank, Clemens; Strasser, Thomas

    2011-07-01

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

  17. 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

  18. Dual multi-scale filter with SSS and GW for infrared small target detection

    NASA Astrophysics Data System (ADS)

    Xin, Yun-hong; Zhou, Jiao; Chen, Yi-shuan

    2017-03-01

    Multi-scale analysis is a powerful tool in the field of signal processing. In this paper, we propose an efficient small target detection algorithm that is mainly based on the dual multi-scale filters which work sequentially. The algorithm consists of two stages: at the first stage, Spectrum Scale-Space (SSS) is used as the pre-process procedure to obtain the multi-scale saliency maps, which can suppress the low frequency background noise and make the target region prominently at different scale levels. As a result, the more detail information and feature information can be exhibited in the different decomposition image level. After then, the least information entropy is used as the criterion to select the optimal salient map out; At the second stage, the Gabor wavelets (GW) algorithm is utilized to suppress the high frequency noise remained in the optimal salient map and match the feature of size and direction of small target at different scales and angles, and next, to ensure the robustness of the target detection, Non-negative Matrix Factorization (NMF) is applied to fuse all the GW multi-scale images into one optimal target image, which is the final output of the presented method. Experimental results show that, compared with the contrast method, the proposed algorithm has high SCRG and high correct target detection rate, and works well in different types of complex backgrounds.

  19. A multi-scale permafrost investigation along the Alaska Highway Corridor based on airborne electromagnetic and auxiliary geophysical data

    NASA Astrophysics Data System (ADS)

    Minsley, B. J.; Kass, M. A.; Bloss, B.; Pastick, N.; Panda, S. K.; Smith, B. D.; Abraham, J. D.; Burns, L. E.

    2012-12-01

    More than 8000 square kilometers of airborne electromagnetic (AEM) data were acquired along the Alaska Highway Corridor in 2005-2006 by the Alaska Department of Natural Resources Division of Geological and Geophysical Surveys. Because this large AEM dataset covers diverse geologic and permafrost settings, it is an excellent testbed for studying the electrical geophysical response from a wide range of subsurface conditions. These data have been used in several recent investigations of geology, permafrost, and infrastructure along the highway corridor. In this study, we build on existing interpretations of permafrost features by re-inverting the AEM data using traditional least squares inversion techniques as well as recently developed stochastic methods aimed at quantifying uncertainty in geophysical data. Ground-based geophysical measurements, including time-domain electromagnetic soundings, surface nuclear magnetic resonance soundings, and shallow frequency-domain electromagnetic profiles, have also been acquired to help validate and extend the AEM interpretations. Here, we focus on the integration of different types of data to yield an improved characterization of permafrost, including: methods to discriminate between geologic and thermal controls on resistivity; identifying relationships between shallow resistivity and active layer thickness by incorporating auxiliary remote sensing data and ground-based measurements; quantifying apparent slope-aspect-resistivity relationships, where south-facing slopes appear less resistive than north-facing slopes within similar geologic settings; and investigating an observed decrease in resistivity beneath several areas associated with recent fires.

  20. Experimentally- and Dislocation-Based Multi-scale Modeling of Metal Plasticity Including Temperature and Rate Effects

    NASA Astrophysics Data System (ADS)

    Nemat-Nasser, Sia

    2005-08-01

    Excluding high-temperature creep, the plastic deformation of metals occurs by the motion of dislocations that produce slip on various slip planes in various slip directions. It is thus natural to seek to develop constitutive relations for metal plasticity, based on the concept of dislocations and their kinematics and kinetics. Such an approach has been successfully used by a number of investigators over the past several decades. More recently, however, the development of the recovery Hopkinson techniques by this writer and his coworkers at UCSD's CEAM, has provided important experimental tools to obtain reliable data on stress-strain response of variety of metals over broad ranges of strain rates and temperatures. A wealth of information has become available to guide and verify constitutive models that are proposed to describe metal plasticity. Using such data, I have been able to create a class of dislocation-based models that involve a few material constants, and seem to accurately characterize the response of a large number of metals over 10-4 to 105/s strain rates, and 77 to 1,300K temperatures.

  1. Multi-scale characterization of graphenic materials synthesized by a solvothermal-based process: Influence of the thermal treatment

    NASA Astrophysics Data System (ADS)

    Speyer, Lucie; Fontana, Sébastien; Cahen, Sébastien; Ghanbaja, Jaafar; Medjahdi, Ghouti; Hérold, Claire

    2015-12-01

    Owing to its exceptional properties and a large range of possible applications, graphene gives rise to a great interest. Several major methods, as mechanical cleavage, liquid phase exfoliation of graphite and supported growth, have been developed these last years. However, it remains difficult to yield industrial quantities of graphene-based materials. Besides the research for the improvement of these major ways of synthesis, we focused on a much less common method: solvothermal synthesis. Graphenic powders can be obtained by a solvothermal reaction between ethanol and sodium followed by a thermal treatment step. We performed the solvothermal reaction and pyrolyzed the as-obtained sodium ethoxide with different temperature and time conditions, in order to study the influence of these two parameters on the final carbon-based sample. Various characterization techniques revealed the obtaining of graphenic materials with large aspect ratio, containing multi-layer graphene (MLG) regions. This study shows the strong influence of temperature and time of pyrolysis on purity, crystallinity and thickness of the samples, and goes toward an optimization of the thermal treatment step.

  2. Multi-Scale Particle Size Distributions of Mars, Moon and Itokawa based on a time-maturation dependent fragmentation model

    NASA Astrophysics Data System (ADS)

    Charalambous, C. A.; Pike, W. T.

    2013-12-01

    We present the development of a soil evolution framework and multiscale modelling of the surface of Mars, Moon and Itokawa thus providing an atlas of extra-terrestrial Particle Size Distributions (PSD). These PSDs are profoundly based on a tailoring method which interconnects several datasets from different sites captured by the various missions. The final integrated product is then fully justified through a soil evolution analysis model mathematically constructed via fundamental physical principles (Charalambous, 2013). The construction of the PSD takes into account the macroscale fresh primary impacts and their products, the mesoscale distributions obtained by the in-situ data of surface missions (Golombek et al., 1997, 2012) and finally the microscopic scale distributions provided by Curiosity and Phoenix Lander (Pike, 2011). The distribution naturally extends at the magnitudinal scales at which current data does not exist due to the lack of scientific instruments capturing the populations at these data absent scales. The extension is based on the model distribution (Charalambous, 2013) which takes as parameters known values of material specific probabilities of fragmentation and grinding limits. Additionally, the establishment of a closed-form statistical distribution provides a quantitative description of the soil's structure. Consequently, reverse engineering of the model distribution allows the synthesis of soil that faithfully represents the particle population at the studied sites (Charalambous, 2011). Such representation essentially delivers a virtual soil environment to work with for numerous applications. A specific application demonstrated here will be the information that can directly be extracted for the successful drilling probability as a function of distance in an effort to aid the HP3 instrument of the 2016 Insight Mission to Mars. Pike, W. T., et al. "Quantification of the dry history of the Martian soil inferred from in situ microscopy

  3. Multi-scale, micro-computed tomography-based pore network models to simulate drainage in heterogeneous rocks

    NASA Astrophysics Data System (ADS)

    Bultreys, Tom; Van Hoorebeke, Luc; Cnudde, Veerle

    2015-04-01

    The multi-phase flow behavior of complex rocks with broad pore size distributions often digresses from classical relations. Pore-scale simulation methods can be a great tool to improve the understanding of this behavior. However, the broad range of pore sizes present makes it difficult to gather the experimental input data needed for these simulations and poses great computational challenges. We developed a novel micro-computed-tomography (micro-CT) based dual pore network model (DPNM), which takes microporosity into account in an upscaled fashion using symbolic network elements called micro-links, while treating the macroporosity as a traditional pore network model. The connectivity and conductivity of the microporosity is derived from local information measured on micro-CT scans. Microporous connectivity is allowed both in parallel and in series to the macropore network. We allow macropores to be drained as a consequence of their connection with microporosity, permitting simulations where the macropore network alone does not percolate. The validity of the method is shown by treating an artificial network and a network extracted from a micro-CT scan of Estaillades limestone.

  4. Multi-Scale Agent-Based Multiple Myeloma Cancer Modeling and the Related Study of the Balance between Osteoclasts and Osteoblasts

    PubMed Central

    Qiao, Minna; Wu, Dan; Carey, Michelle; Zhou, Xiaobo; Zhang, Le

    2015-01-01

    Research Background Currently, multiple myeloma is the second most common hematological malignancy in the U.S., constituting 1% of all cancers. With conventional treatment, the median survival time is typically 3–4 years, although it can be extended to 5–7 years or longer with advanced treatments. Recent research indicated that an increase in osteoclast (OC) activity is often associated withmultiple myeloma (MM) and that a decrease inosteoblast (OB) activity contributesto the osteolytic lesions in MM. Normally, the populations of OCs and OBs are inequilibrium, and an imbalance in this statecontributes to the development of lesions. Research procedures A multi-scale agent-based multiple myeloma model was developed to simulate the proliferation, migration and death of OBs and OCs. Subsequently, this model was employed to investigate the efficacy of thethree most commonly used drugs for MM treatment under the following two premises: the reduction in the progression of MM and the re-establishment of the equilibrium between OCs and OBs. Research purposes The simulated results not only demonstrated the capacity of the model to choose optimal combinations of the drugs but also showed that the optimal use of the three drugs can restore the balance between OCs and OBs as well as kill MMs. Furthermore, the drug synergism analysis function of the model revealed that restoring the balance between OBs and OCs can significantly increase the efficacy of drugs against tumor cells. PMID:26659358

  5. Mechanical integrity of a carbon nanotube/copper-based through-silicon via for 3D integrated circuits: a multi-scale modeling approach

    NASA Astrophysics Data System (ADS)

    Awad, Ibrahim; Ladani, Leila

    2015-12-01

    Carbon nanotube (CNT)/copper (Cu) composite material is proposed to replace Cu-based through-silicon vias (TSVs) in micro-electronic packages. The proposed material is believed to offer extraordinary mechanical and electrical properties and the presence of CNTs in Cu is believed to overcome issues associated with miniaturization of Cu interconnects, such as electromigration. This study introduces a multi-scale modeling of the proposed TSV in order to evaluate its mechanical integrity under mechanical and thermo-mechanical loading conditions. Molecular dynamics (MD) simulation was used to determine CNT/Cu interface adhesion properties. A cohesive zone model (CZM) was found to be most appropriate to model the interface adhesion, and CZM parameters at the nanoscale were determined using MD simulation. CZM parameters were then used in the finite element analysis in order to understand the mechanical and thermo-mechanical behavior of composite TSV at micro-scale. From the results, CNT/Cu separation does not take place prior to plastic deformation of Cu in bending, and separation does not take place when standard thermal cycling is applied. Further investigation is recommended in order to alleviate the increased plastic deformation in Cu at the CNT/Cu interface in both loading conditions.

  6. Mechanical integrity of a carbon nanotube/copper-based through-silicon via for 3D integrated circuits: a multi-scale modeling approach.

    PubMed

    Awad, Ibrahim; Ladani, Leila

    2015-12-04

    Carbon nanotube (CNT)/copper (Cu) composite material is proposed to replace Cu-based through-silicon vias (TSVs) in micro-electronic packages. The proposed material is believed to offer extraordinary mechanical and electrical properties and the presence of CNTs in Cu is believed to overcome issues associated with miniaturization of Cu interconnects, such as electromigration. This study introduces a multi-scale modeling of the proposed TSV in order to evaluate its mechanical integrity under mechanical and thermo-mechanical loading conditions. Molecular dynamics (MD) simulation was used to determine CNT/Cu interface adhesion properties. A cohesive zone model (CZM) was found to be most appropriate to model the interface adhesion, and CZM parameters at the nanoscale were determined using MD simulation. CZM parameters were then used in the finite element analysis in order to understand the mechanical and thermo-mechanical behavior of composite TSV at micro-scale. From the results, CNT/Cu separation does not take place prior to plastic deformation of Cu in bending, and separation does not take place when standard thermal cycling is applied. Further investigation is recommended in order to alleviate the increased plastic deformation in Cu at the CNT/Cu interface in both loading conditions.

  7. Multi-Scale Autoregressive Processes

    DTIC Science & Technology

    1989-06-01

    rationnelles et leurs langages," Mas- son 1984, Collection "Etudes et Recherches en Informatique". [12] J.L. DUNAU, "Etude d’une classe de marches...June 1989 LIDS-P-1880 Multi-Scale Autoregressive Processes Michele Basseville’ Albert Benveniste’ Institut de Recherche en Informatique et Systemes...Centre National de la Recherche Scientifique (CNRS) and A.B. is also with Institut National de Recherche en Informatique et en Automatique (INRIA). The

  8. Non-local and nonlinear background suppression method controlled by multi-scale clutter metric

    NASA Astrophysics Data System (ADS)

    Gong, Jinnan; Hou, Qingyu; Zhang, Wei; Zhi, Xiyang

    2015-07-01

    To improve the detection performance for non-morphological multi-scale target in IR image containing complex cloud clutter, on basis of cloud scenario self-similarity feature, a non-local and nonlinear background suppression algorithm controlled by multi-scale clutter metric is presented. According to the classical achievements on cloud structure, self-similarity and relativity of cloud clutter on image for target detection is deeply analyzed by classical indicators firstly. Then we establish multi-scale clutter metric method based on LoG operator to describe scenes feature for controlled suppression method. After that, non-local means based on optimal strength similarity metric as non-local processing, and multi-scale median filter and on minimum gradient direction as local processing are set up. Finally linear fusing principle adopting clutter metric for local and non-local processing is put forward. Experimental results by two kinds of infrared imageries show that compared with classical and similar methods, the proposed method solves the existing problems of targets energy attenuation and suppression degradation in strongly evolving regions in previous methods. By evaluating indicators, the proposed method has a superior background suppression performance by increasing the BSF and ISCR 2 times at least.

  9. Multi-Scale Change Detection Research of Remotely Sensed Big Data in CyberGIS

    NASA Astrophysics Data System (ADS)

    Xing, J.; Sieber, R.

    2015-12-01

    Big remotely sensed data, the heterogeneity of satellite platforms and file formats along with increasing volumes and velocities, offers new types of analyses. This makes big remotely sensed data a good candidate for CyberGIS, the aim of which is to enable knowledge discovery of big data in the cloud. We apply CyberGIS to feature-based multi-scale land use/cover change (LUCC) detection. There have been attempts to do multi-scale LUCC. However, studies were done with small data and could not consider the mismatch between multi-scale analysis and computational scale. They have yet to consider the possibilities for scalar research across numerous temporal and spatial scales afforded by big data, especially if we want to advance beyond pixel-based analysis and also reduce preprocessing requirements. We create a geospatial cyberinfrastructure (GCI) to handle multi-spatio-temporal scale change detection. We first clarify different meanings of scale in CyberGIS and LUCC to derive a feature scope layer in the GCI based on Stommel modelling. Our analysis layer contains a multi-scale segmentation-based method based on normalized cut image segmentation and wavelet-based image scaling algorithms. Our computer resource utilization layer uses Wang and Armstrong's (2009) method for mainly for memory, I/O and CPU time. Our case is urban-rural change detection in the Greater Montreal Area (5 time periods, 2006-2012, 100 virtual machines), 36,000km2 and varying from 0.6m to 38m resolution. We present a ground truthed accuracy assessment of a change matrix that is composed of 6 feature classes at 12 different spatio-temporal scales, and the performance of the change detection GCI for multi-scale LUCC study. The GCI allows us to extract and coordinate different types of changes by varying spatio-temporal scales from the big imagery datasets.

  10. Multi-scale drivers of spatial variation in old-growth forest carbon density disentangled with Lidar and an individual-based landscape model

    Treesearch

    Rupert Seidl; Thomas A. Spies; Werner Rammer; E. Ashley Steel; Robert J. Pabst; Keith. Olsen

    2012-01-01

    Forest ecosystems are the most important terrestrial carbon (C) storage globally, and presently mitigate anthropogenic climate change by acting as a large and persistent sink for atmospheric CO2. Yet, forest C density varies greatly in space, both globally and at stand and landscape levels. Understanding the multi-scale drivers of this variation...

  11. A MultiScale Particle Filter Framework for Contour Detection.

    PubMed

    Widynski, Nicolas; Mignotte, Max

    2014-10-01

    We investigate the contour detection task in complex natural images. We propose a novel contour detection algorithm which jointly tracks at two scales small pieces of edges called edgelets. This multiscale edgelet structure naturally embeds semi-local information and is the basic element of the proposed recursive Bayesian modeling. Prior and transition distributions are learned offline using a shape database. Likelihood functions are learned online, thus are adaptive to an image, and integrate color and gradient information via local, textural, oriented, and profile gradient-based features. The underlying model is estimated using a sequential Monte Carlo approach, and the final soft contour detection map is retrieved from the approximated trajectory distribution. We also propose to extend the model to the interactive cut-out task. Experiments conducted on the Berkeley Segmentation data sets show that the proposed MultiScale Particle Filter Contour Detector method performs well compared to competing state-of-the-art methods.

  12. Evaluation of multi-scale hyperspectral reflectance and emittance image data for remote mineral mapping in northeastern Death Valley National Park, California and Oasis Valley, Nevada

    NASA Astrophysics Data System (ADS)

    Aslett, Zan

    This dissertation focuses upon the analyses of hyperspectral reflectance and thermal emission image data to remotely detect and map surficial mineralogy in an arid environment in southern Nevada and southeastern California. It includes four manuscripts prepared for submission to peer-reviewed journals, which are presented as single chapters. The research involves the use of longwave-infrared (LWIR) hyper- and multi-spectral measurements made from ground, aerial, and spaceborne perspectives of sedimentary and meta-sedimentary geologic units in northeastern Death Valley National Park, California and both shortwave-infrared (SWIR) and LWIR hyperspectral measurements in an area of diverse Paleozoic and Tertiary geology in Oasis Valley, Nevada. In Chapter 1, a brief overview of the dissertation is provided, including background on reflected and thermal-infrared mineral spectroscopy; remote sensing; the impacts of spatial and spectral resolution upon the ability to detect, identify, and map minerals using remote sensing image data; and the use of combined reflectance and emittance image data to better map minerals. In Chapter 2, ground-based SEBASS LWIR hyperspectral image data is analyzed in order to determine the utility of very high resolution remotely-sensed emittance measurements to delineate late-Proterozoic and Paleozoic sedimentary lithologies of an outcrop at Hell's Gate, Death Valley. In Chapter 3, airborne SEBASS image data over Boundary Canyon are analyzed in conjunction with moderate-scale geologic maps and laboratory measurements to map minerals associated with sedimentary and meta-sedimentary rocks and important in recognizing a detachment fault structure, as well as metamorphic facies. In Chapter 4, ground-based and aerial SEBASS, aerial MASTER, and spaceborne ASTER emittance measurements are compared over two study sites to determine what repercussions viewing perspective and spatial, spectral, and radiometric resolutions have upon remote identification

  13. Strong, Multi-Scale Heterogeneity in Earth's Lowermost Mantle.

    PubMed

    Tkalčić, Hrvoje; Young, Mallory; Muir, Jack B; Davies, D Rhodri; Mattesini, Maurizio

    2015-12-17

    The core mantle boundary (CMB) separates Earth's liquid iron outer core from the solid but slowly convecting mantle. The detailed structure and dynamics of the mantle within ~300 km of this interface remain enigmatic: it is a complex region, which exhibits thermal, compositional and phase-related heterogeneity, isolated pockets of partial melt and strong variations in seismic velocity and anisotropy. Nonetheless, characterising the structure of this region is crucial to a better understanding of the mantle's thermo-chemical evolution and the nature of core-mantle interactions. In this study, we examine the heterogeneity spectrum from a recent P-wave tomographic model, which is based upon trans-dimensional and hierarchical Bayesian imaging. Our tomographic technique avoids explicit model parameterization, smoothing and damping. Spectral analyses reveal a multi-scale wavelength content and a power of heterogeneity that is three times larger than previous estimates. Inter alia, the resulting heterogeneity spectrum gives a more complete picture of the lowermost mantle and provides a bridge between the long-wavelength features obtained in global S-wave models and the short-scale dimensions of seismic scatterers. The evidence that we present for strong, multi-scale lowermost mantle heterogeneity has important implications for the nature of lower mantle dynamics and prescribes complex boundary conditions for Earth's geodynamo.

  14. A multi-scale approach to mass segmentation using active contour models

    NASA Astrophysics Data System (ADS)

    Yu, Hongwei; Li, Lihua; Xu, Weidong; Liu, Wei

    2010-03-01

    As an important step of mass classification, mass segmentation plays an important role in computer-aided diagnosis (CAD). In this paper, we propose a novel scheme for breast mass segmentation in mammograms, which is based on level set method and multi-scale analysis. Mammogram is firstly decomposed by Gaussian pyramid into a sequence of images from fine to coarse, the C-V model is then applied at the coarse scale, and the obtained rough contour is used as the initial contour for segmentation at the fine scale. A local active contour (LAC) model based on image local information is utilized to refine the rough contour locally at the fine scale. In addition, the feature of area and gray level extracted from coarse segmentation is used to set the parameters of LAC model automatically to improve the adaptivity of our method. The results show the higher accuracy and robustness of the proposed multi-scale segmentation method than the conventional ones.

  15. A multi-scale Lattice Boltzmann model for simulating solute transport in 3D X-ray micro-tomography images of aggregated porous materials

    NASA Astrophysics Data System (ADS)

    Zhang, Xiaoxian; Crawford, John W.; Flavel, Richard J.; Young, Iain M.

    2016-10-01

    The Lattice Boltzmann (LB) model and X-ray computed tomography (CT) have been increasingly used in combination over the past decade to simulate water flow and chemical transport at pore scale in porous materials. Because of its limitation in resolution and the hierarchical structure of most natural soils, the X-ray CT tomography can only identify pores that are greater than its resolution and treats other pores as solid. As a result, the so-called solid phase in X-ray images may in reality be a grey phase, containing substantial connected pores capable of conducing fluids and solute. Although modified LB models have been developed to simulate fluid flow in such media, models for solute transport are relatively limited. In this paper, we propose a LB model for simulating solute transport in binary soil images containing permeable solid phase. The model is based on the single-relaxation time approach and uses a modified partial bounce-back method to describe the resistance caused by the permeable solid phase to chemical transport. We derive the relationship between the diffusion coefficient and the parameter introduced in the partial bounce-back method, and test the model against analytical solution for movement of a pulse of tracer. We also validate it against classical finite volume method for solute diffusion in a simple 2D image, and then apply the model to a soil image acquired using X-ray tomography at resolution of 30 μm in attempts to analyse how the ability of the solid phase to diffuse solute at micron-scale affects the behaviour of the solute at macro-scale after a volumetric average. Based on the simulated results, we discuss briefly the danger in interpreting experimental results using the continuum model without fully understanding the pore-scale processes, as well as the potential of using pore-scale modelling and tomography to help improve the continuum models.

  16. Multi-scale structural and chemical analysis of sugarcane bagasse in the process of sequential acid–base pretreatment and ethanol production by Scheffersomyces shehatae and Saccharomyces cerevisiae

    PubMed Central

    2014-01-01

    Background Heavy usage of gasoline, burgeoning fuel prices, and environmental issues have paved the way for the exploration of cellulosic ethanol. Cellulosic ethanol production technologies are emerging and require continued technological advancements. One of the most challenging issues is the pretreatment of lignocellulosic biomass for the desired sugars yields after enzymatic hydrolysis. We hypothesized that consecutive dilute sulfuric acid-dilute sodium hydroxide pretreatment would overcome the native recalcitrance of sugarcane bagasse (SB) by enhancing cellulase accessibility of the embedded cellulosic microfibrils. Results SB hemicellulosic hydrolysate after concentration by vacuum evaporation and detoxification showed 30.89 g/l xylose along with other products (0.32 g/l glucose, 2.31 g/l arabinose, and 1.26 g/l acetic acid). The recovered cellulignin was subsequently delignified by sodium hydroxide mediated pretreatment. The acid–base pretreated material released 48.50 g/l total reducing sugars (0.91 g sugars/g cellulose amount in SB) after enzymatic hydrolysis. Ultra-structural mapping of acid–base pretreated and enzyme hydrolyzed SB by microscopic analysis (scanning electron microcopy (SEM), transmitted light microscopy (TLM), and spectroscopic analysis (X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, Fourier transform near-infrared (FT-NIR) spectroscopy, and nuclear magnetic resonance (NMR) spectroscopy) elucidated the molecular changes in hemicellulose, cellulose, and lignin components of bagasse. The detoxified hemicellulosic hydrolysate was fermented by Scheffersomyces shehatae (syn. Candida shehatae UFMG HM 52.2) and resulted in 9.11 g/l ethanol production (yield 0.38 g/g) after 48 hours of fermentation. Enzymatic hydrolysate when fermented by Saccharomyces cerevisiae 174 revealed 8.13 g/l ethanol (yield 0.22 g/g) after 72 hours of fermentation. Conclusions Multi-scale structural studies of SB after sequential acid–base

  17. 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

  18. Multi-scale feature learning on pixels and super-pixels for seminal vesicles MRI segmentation

    NASA Astrophysics Data System (ADS)

    Gao, Qinquan; Asthana, Akshay; Tong, Tong; Rueckert, Daniel; Edwards, Philip "Eddie"

    2014-03-01

    We propose a learning-based approach to segment the seminal vesicles (SV) via random forest classifiers. The proposed discriminative approach relies on the decision forest using high-dimensional multi-scale context-aware spatial, textual and descriptor-based features at both pixel and super-pixel level. After affine transformation to a template space, the relevant high-dimensional multi-scale features are extracted and random forest classifiers are learned based on the masked region of the seminal vesicles from the most similar atlases. Using these classifiers, an intermediate probabilistic segmentation is obtained for the test images. Then, a graph-cut based refinement is applied to this intermediate probabilistic representation of each voxel to get the final segmentation. We apply this approach to segment the seminal vesicles from 30 MRI T2 training images of the prostate, which presents a particularly challenging segmentation task. The results show that the multi-scale approach and the augmentation of the pixel based features with the super-pixel based features enhances the discriminative power of the learnt classifier which leads to a better quality segmentation in some very difficult cases. The results are compared to the radiologist labeled ground truth using leave-one-out cross-validation. Overall, the Dice metric of 0:7249 and Hausdorff surface distance of 7:0803 mm are achieved for this difficult task.

  19. New Method for Accurate Calibration of Micro-Channel Plate based Detection Systems and its use in the Fast Plasma Investigation of NASA's Magnetospheric MultiScale Mission

    NASA Astrophysics Data System (ADS)

    Gliese, U.; Avanov, L. A.; Barrie, A.; Kujawski, J. T.; Mariano, A. J.; Tucker, C. J.; Chornay, D. J.; Cao, N. T.; Zeuch, M.; Pollock, C. J.; Jacques, A. D.

    2013-12-01

    The Fast Plasma Investigation (FPI) of the NASA Magnetospheric MultiScale (MMS) mission employs 16 Dual Electron Spectrometers (DESs) and 16 Dual Ion Spectrometers (DISs) with 4 of each type on each of 4 spacecraft to enable fast (30ms for electrons; 150ms for ions) and spatially differentiated measurements of full the 3D particle velocity distributions. This approach presents a new and challenging aspect to the calibration and operation of these instruments on ground and in flight. The response uniformity and reliability of their calibration and the approach to handling any temporal evolution of these calibrated characteristics all assume enhanced importance in this application, where we attempt to understand the meaning of particle distributions within the ion and electron diffusion regions. Traditionally, the micro-channel plate (MCP) based detection systems for electrostatic particle spectrometers have been calibrated by setting a fixed detection threshold and, subsequently, measuring a detection system count rate plateau curve to determine the MCP voltage that ensures the count rate has reached a constant value independent of further variation in the MCP voltage. This is achieved when most of the MCP pulse height distribution (PHD) is located at higher values (larger pulses) than the detection amplifier threshold. This method is adequate in single-channel detection systems and in multi-channel detection systems with very low crosstalk between channels. However, in dense multi-channel systems, it can be inadequate. Furthermore, it fails to fully and individually characterize each of the fundamental parameters of the detection system. We present a new detection system calibration method that enables accurate and repeatable measurement and calibration of MCP gain, MCP efficiency, signal loss due to variation in gain and efficiency, crosstalk from effects both above and below the MCP, noise margin, and stability margin in one single measurement. The fundamental

  20. 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.

  1. Local current transport and surface potential of photovoltaic Cu(In,Ga)Se2 thin films probed by multi-scale imaging methods

    NASA Astrophysics Data System (ADS)

    Jeong, A. R.; Kim, G. Y.; Jo, W.; Nam, D. H.; Cheong, H.; Jo, H. J.; Kim, D.-H.; Sung, S. J.; Kang, J. K.; Lee, D. H.

    2013-03-01

    Microstructural alteration induces non-uniform device characteristics in polycrystalline thin films. In thin-film solar cells based on Cu(In,Ga)Se2 (CIGS), local electrical properties are investigated by Raman scattering spectroscopic imaging and scanning probe microscopic tools. Localized and uneven intensity of phonon modes, which represent different orientation and phases, elucidate the nature of non-uniformity of crystallinity, composition and defects in the films. Surface potential mapping at nanoscale is performed by Kelvin probe force microscopy, showing ˜40 mV of band-bending at the grain boundaries. Externally biased-current mapping, which is obtained by conductive atomic force microscopy, shows preferred current path in the films. Invited talk at the 6th International Workshop on Advanced Materials Science and Nanotechnology IWAMSN2012, 30 October-2 November 2012, Ha Long, Vietnam.

  2. Image thresholding based on Adjusted Rand Index

    NASA Astrophysics Data System (ADS)

    Fang, Lulu; Zou, Yaobin; Dong, Fangmin; Lei, Bangjun; Sun, Shuifa

    2015-07-01

    This paper proposes a new image thresholding method by integrating Multi-scale Gradient Multiplication (MGM) transformation and Adjusted Rand Index (ARI). The proposed method evaluates the optimal threshold by computing the accumulation similarity between two image collections from the perspective of global spatial attributes of images. One of the image collections are obtained by binarizing the original gray level image with each possible gray level. The others are the reference images, produced by binarizing MGM image. The MGM image is the result of applying MGM transformation to the original image. ARI is a similarity measurement in statistics, particularly in data clustering, which can be readily computed based on two image matrices. To be more accurate, the optimal threshold is determined by maximizing the accumulation similarity of ARI. Comparisons with three well established thresholding methods are depicted for numbers of real-world images. Experiment results demonstrate the effectiveness and robustness of the proposed method.

  3. A Collaborative Informatics Infrastructure for Multi-scale Science

    SciTech Connect

    Myers, J D; Allison, T C; Bittner, S; Didier, B; Frenklach, M; Green, Jr., W H; Ho, Y; Hewson, J; Koegler, W; Lansing, C; Leahy, D; Lee, M; McCoy, R; Minkoff, M; Nijsure, S; von Laszewski, G; Montoya, D; Pancerella, C; Pinzon, R; Pitz, W J; Rahn, L A; Ruscis, B; Schuchardt, K; Stephan, E; Wagner, A; Windus, T; Yang, C

    2005-05-11

    The Collaboratory for Multi-scale Chemical Science (CMCS) is developing a powerful informatics-based approach to synthesizing multi-scale information to support a systems-based research approach and is applying it in support of combustion research. An open source multi-scale informatics toolkit is being developed that addresses a number of issues core to the emerging concept of knowledge grids including provenance tracking and lightweight federation of data and application resources into cross-scale information flows. The CMCS portal is currently in use by a number of high-profile pilot groups and is playing a significant role in enabling their efforts to improve and extend community maintained chemical reference information.

  4. A Collaborative Informatics Infrastructure for Multi-scale Science

    SciTech Connect

    Myers, James D.; Allison, Thomas C.; Bittner, Sandra; Didier, Brett T.; Frenklach, Michael; Green, William H.; Ho, Yen-Ling; Hewson, John; Koegler, Wendy S.; Lansing, Carina S.; Leahy, David; Lee, Michael; McCoy, Renata; Minkoff, Michael; Nijsure, Sandeep; von Laszewski, Gregor; Montoya, David W.; Pancerella, Carmen M.; Pinzon, Reinhardt; Pitz, William; Rahn, Larry; Ruscic, Branko; Schuchardt, Karen L.; Stephan, Eric G.; Wagner, Albert F.; Windus, Theresa L.; Yang, Christine

    2004-03-28

    The Collaboratory for Multi-scale Chemical Science (CMCS) is developing a powerful informatics-based approach to synthesizing multi-scale information to support a systems-based research approach and is applying it in support of combustion research. An open source multi-scale informatics toolkit is being developed that addresses a number of issues core to the emerging concept of knowledge grids including provenance tracking and lightweight federation of data and application resources into cross-scale information flows. The CMCS portal is currently in use by a number of high-profile pilot groups and is playing a significant role in enabling their efforts to improve and extend community maintained chemical reference information.

  5. A Collaborative Informatics Infrastructure for Multi-scale Science

    SciTech Connect

    Myers, James D.; Allison, Thomas C.; Bittner, Sandra J.; Didier, Brett T.; Frenklach, Michael; Green, William H.; Ho, Yen-Ling; Hewson, John; Koegler, Wendy S.; Lansing, Carina S.; Leahy, David; Lee, Michael; McCoy, Renata; Minkoff, Michael; Nijsure, Sandeep; von Laszewski, Gregor; Montoya, David; Oluwole, Luwi; Pancerella, Carmen M.; Pinzon, Reinhardt; Pitz, William; Rahn, Larry A.; Ruscic, Branko; Schuchardt, Karen L.; Stephan, Eric G.; Wagner, Al; Windus, Theresa L.; Yang, Christine

    2005-10-01

    The Collaboratory for Multi-scale Chemical Science (CMCS) is developing a powerful informatics-based approach to synthesizing multi-scale information to support a systems-based research approach and is applying it in support of combustion research. An open source multi-scale informatics toolkit is being developed that addresses a number of issues core to the emerging concept of knowledge grids including provenance tracking and lightweight federation of data and application resources into cross-scale information flows. The CMCS portal is currently in use by a number of high-profile pilot groups and is playing a significant role in enabling their efforts to improve and extend community maintained chemical reference information.

  6. The Adaptive Multi-scale Simulation Infrastructure

    SciTech Connect

    Tobin, William R.

    2015-09-01

    The Adaptive Multi-scale Simulation Infrastructure (AMSI) is a set of libraries and tools developed to support the development, implementation, and execution of general multimodel simulations. Using a minimal set of simulation meta-data AMSI allows for minimally intrusive work to adapt existent single-scale simulations for use in multi-scale simulations. Support for dynamic runtime operations such as single- and multi-scale adaptive properties is a key focus of AMSI. Particular focus has been spent on the development on scale-sensitive load balancing operations to allow single-scale simulations incorporated into a multi-scale simulation using AMSI to use standard load-balancing operations without affecting the integrity of the overall multi-scale simulation.

  7. Change detection in high resolution SAR images based on multiscale texture features

    NASA Astrophysics Data System (ADS)

    Wen, Caihuan; Gao, Ziqiang

    2011-12-01

    This paper studied on change detection algorithm of high resolution (HR) Synthetic Aperture Radar (SAR) images based on multi-scale texture features. Firstly, preprocessed multi-temporal Terra-SAR images were decomposed by 2-D dual tree complex wavelet transform (DT-CWT), and multi-scale texture features were extracted from those images. Then, log-ratio operation was utilized to get difference images, and the Bayes minimum error theory was used to extract change information from difference images. Lastly, precision assessment was done. Meanwhile, we compared with the result of method based on texture features extracted from gray-level cooccurrence matrix (GLCM). We had a conclusion that, change detection algorithm based on multi-scale texture features has a great more improvement, which proves an effective method to change detect of high spatial resolution SAR images.

  8. Multi-scaling modelling in financial markets

    NASA Astrophysics Data System (ADS)

    Liu, Ruipeng; Aste, Tomaso; Di Matteo, T.

    2007-12-01

    In the recent years, a new wave of interest spurred the involvement of complexity in finance which might provide a guideline to understand the mechanism of financial markets, and researchers with different backgrounds have made increasing contributions introducing new techniques and methodologies. In this paper, Markov-switching multifractal models (MSM) are briefly reviewed and the multi-scaling properties of different financial data are analyzed by computing the scaling exponents by means of the generalized Hurst exponent H(q). In particular we have considered H(q) for price data, absolute returns and squared returns of different empirical financial time series. We have computed H(q) for the simulated data based on the MSM models with Binomial and Lognormal distributions of the volatility components. The results demonstrate the capacity of the multifractal (MF) models to capture the stylized facts in finance, and the ability of the generalized Hurst exponents approach to detect the scaling feature of financial time series.

  9. Modification of a Colliculo-thalamocortical Mouse Brain Slice, Incorporating 3-D printing of Chamber Components and Multi-scale Optical Imaging.

    PubMed

    Slater, Bernard J; Fan, Anthony Y; Stebbings, Kevin A; Saif, M Taher A; Llano, Daniel A

    2015-09-18

    The ability of the brain to process sensory information relies on both ascending and descending sets of projections. Until recently, the only way to study these two systems and how they interact has been with the use of in vivo preparations. Major advances have been made with acute brain slices containing the thalamocortical and cortico-thalamic pathways in the somatosensory, visual, and auditory systems. With key refinements to our recent modification of the auditory thalamocortical slice(1), we are able to more reliably capture the projections between most of the major auditory midbrain and forebrain structures: the inferior colliculus (IC), medial geniculate body (MGB), thalamic reticular nucleus (TRN), and the auditory cortex (AC). With portions of all these connections retained, we are able to answer detailed questions that complement the questions that can be answered with in vivo preparations. The use of flavoprotein autofluorescence imaging enables us to rapidly assess connectivity in any given slice and guide the ensuing experiment. Using this slice in conjunction with recording and imaging techniques, we are now better equipped to understand how information processing occurs at each point in the auditory forebrain as information ascends to the cortex, and the impact of descending cortical modulation. 3-D printing to build slice chamber components permits double-sided perfusion and broad access to networks within the slice and maintains the widespread connections key to fully utilizing this preparation.

  10. A framework for multi-scale modelling

    PubMed Central

    Chopard, B.; Borgdorff, Joris; Hoekstra, A. G.

    2014-01-01

    We review a methodology to design, implement and execute multi-scale and multi-science numerical simulations. We identify important ingredients of multi-scale modelling and give a precise definition of them. Our framework assumes that a multi-scale model can be formulated in terms of a collection of coupled single-scale submodels. With concepts such as the scale separation map, the generic submodel execution loop (SEL) and the coupling templates, one can define a multi-scale modelling language which is a bridge between the application design and the computer implementation. Our approach has been successfully applied to an increasing number of applications from different fields of science and technology. PMID:24982249

  11. Four-stage dissolved oxygen strategy based on multi-scale analysis for improving spinosad yield by Saccharopolyspora spinosa ATCC49460.

    PubMed

    Bai, Yun; Zhou, Peng-Peng; Fan, Pei; Zhu, Yuan-Min; Tong, Yao; Wang, Hong-Bo; Yu, Long-Jiang

    2015-05-01

    Dissolved oxygen (DO) is an important influencing factor in the process of aerobic microbial fermentation. Spinosad is an aerobic microbial-derived secondary metabolite. In our study, spinosad was used as an example to establish a DO strategy by multi-scale analysis, which included a reactor, cell and gene scales. We changed DO conditions that are related to the characteristics of cell metabolism (glucose consumption rate, biomass accumulation and spinosad production). Consequently, cell growth was promoted by maintaining DO at 40% in the first 24 h and subsequently increasing DO to 50% in 24 h to 96 h. In an in-depth analysis of the key enzyme genes (gtt, spn A, spn K and spn O), expression of spinosad and specific Adenosine Triphosphate (ATP), the spinosad yield was increased by regulating DO to 30% within 96 h to 192 h and then changing it to 25% in 192 h to 240 h. Under the four-phase DO strategy, spinosad yield increased by 652.1%, 326.1%, 546.8%, and 781.4% compared with the yield obtained under constant DO control at 50%, 40%, 30%, and 20% respectively. The proposed method provides a novel way to develop a precise DO strategy for fermentation.

  12. Incipient loose detection of hoops for pipeline based on ensemble empirical mode decomposition and multi-scale entropy and extreme learning machine

    NASA Astrophysics Data System (ADS)

    Li, Xiaowei; Wei, Qin; Qu, Yongzhi; Cai, Lin

    2017-06-01

    Hoops are very important fittings in hydraulic pipeline, incipient loose detection of hoops will help to prevent hydraulic piping system from breaking down. Since the vibration signals of fluid pipe are non-stationary and of great complexity, multi-scale entropy(MSE), a method characterized by evaluating complexity and irregularity of time series on multiple scales, is used for extracting feature vectors from the vibration signals. In order to obtain components related to system characteristics, ensemble empirical mode decomposition(EEMD) is applied to reconstruct the original signals before the procedure of MSE. Extreme learning machine(ELM) is a new machine learning algorithm characterized by high accuracy and efficiency. In this paper, ELM is introduced as a classifier to identify the different conditions of hoops according to feature vectors extracted by EEMD and MSE algorithms. Thus a novel loose detection method combining with EEMD-MSE and ELM is put forward. The analysis and experimental results demonstrate that the proposed loose detection and feature extraction method for hydraulic pipeline is effective with high performance.

  13. Flow around new wind fence with multi-scale fractal structure in an atmospheric boundary layer

    NASA Astrophysics Data System (ADS)

    McClure, Sarah; Lee, Sang-Joon; Zhang, Wei

    2015-11-01

    Understanding and controlling atmospheric boundary-layer flows with engineered structures, such as porous wind fences or windbreaks, has been of great interest to the fluid mechanics and wind engineering community. Previous studies found that the regular mono-scale grid fence of 50% porosity and a bottom gap of 10% of the fence height are considered to be optimal over a flat surface. Significant differences in turbulent flow structure have recently been noted behind multi-scale fractal wind fences, even with the same porosity. In this study, wind-tunnel tests on the turbulent flow and the turbulence kinetic energy transport of 1D and 2D multi-scale fractal fences under atmospheric boundary-layer were conducted. Velocity fields around the fractal fences were systematically measured using Particle Image Velocimetry to uncover effects of key parameters on turbulent flows around the fences at a Reynolds number of approximately 3.6x104 based on the free-stream speed and fence height. The turbulent flow structures induced by specific 1D/2D multi-scale fractal wind fences were compared to those of a conventional grid fence. The present results would contribute to the design of new-generation wind fences to reduce snow/sand deposition on critical infrastructure such as roads and bridges.

  14. Follicular lymphoma grading using cell-graphs and multi-scale feature analysis

    NASA Astrophysics Data System (ADS)

    Oztan, Basak; Kong, Hui; Gürcan, Metin N.; Yener, Bülent

    2012-03-01

    We present a method for the computer-aided histopathological grading of follicular lymphoma (FL) images based on a multi-scale feature analysis. We analyze FL images using cell-graphs to characterize the structural organization of the cells in tissues. Cell-graphs represent histopathological images with undirected and unweighted graphs wherein the cytological components constitute the graph nodes and the approximate adjacencies of the components are represented with edges. Using the features extracted from nuclei- and cytoplasm-based cell-graphs, a classifier defines the grading of the follicular lymphoma images. The performance of this system is comparable to that of our recently developed system that characterizes higher-level semantic description of tissues using model-based intermediate representation (MBIR) and color-textural analysis. When tested with three different classifiers, the combination of cell-graph based features with the MBIR and color-textural features followed by a multi-scale feature selection is shown to achieve considerably higher classification accuracies than any set of these feature sets can achieve separately.

  15. A White Beam Far-field Neutron Interferometer for Multi-scale Resolution of Porosity

    NASA Astrophysics Data System (ADS)

    Hussey, D. S.; Miao, H.; Anovitz, L. M.; Jacobson, D. L.; LaManna, J.; Wen, H.

    2016-12-01

    The pore structure of geological formations spans many decades of length scales, from the Angstrom to the kilometer. There are few probes which can assess characterize these structures simultaneously. We will present a demonstration of a new neutron phase imaging method that can provide quantitative, multi-scale images, addressing length scales from the nanometer to the centimeter. The phase imaging method is based on a far field interferometer that produces phase gradient and small-angle scattering images using a polychromatic neutron beam. The interferometer is based on the Moiré pattern of two phase modulating gratings which was previously realized in hard x-ray and visible light experiments. An important aspect of the method is the ability to tune the auto-correlation length of the interferometer by changing the separation of the two gratings, and thereby provides a measure of the real-space pair-correlation function, G(z), of the sample. As has been shown for other scattering methods, measures of G(z) can incorporate multiple scattering permitting the study of thick samples. As well, the method has the potential to enable tomographic reconstruction so that a fully 3D distribution of the microstructure can be measured. Multi-scale data from several core specimens will be presented showing the quantitative ability of the method.

  16. Magnetospheric MultiScale (MMS) System Manager

    NASA Technical Reports Server (NTRS)

    Schiff, Conrad; Maher, Francis Alfred; Henely, Sean Philip; Rand, David

    2014-01-01

    The Magnetospheric MultiScale (MMS) mission is an ambitious NASA space science mission in which 4 spacecraft are flown in tight formation about a highly elliptical orbit. Each spacecraft has multiple instruments that measure particle and field compositions in the Earths magnetosphere. By controlling the members relative motion, MMS can distinguish temporal and spatial fluctuations in a way that a single spacecraft cannot.To achieve this control, 2 sets of four maneuvers, distributed evenly across the spacecraft must be performed approximately every 14 days. Performing a single maneuver on an individual spacecraft is usually labor intensive and the complexity becomes clearly increases with four. As a result, the MMS flight dynamics team turned to the System Manager to put the routine or error-prone under machine control freeing the analysts for activities that require human judgment.The System Manager is an expert system that is capable of handling operations activities associated with performing MMS maneuvers. As an expert system, it can work off a known schedule, launching jobs based on a one-time occurrence or on a set reoccurring schedule. It is also able to detect situational changes and use event-driven programming to change schedules, adapt activities, or call for help.

  17. Comparison of Pixel-Based and Object-Based Classification Using Parameters and Non-Parameters Approach for the Pattern Consistency of Multi Scale Landcover

    NASA Astrophysics Data System (ADS)

    Juniati, E.; Arrofiqoh, E. N.

    2017-09-01

    Information extraction from remote sensing data especially land cover can be obtained by digital classification. In practical some people are more comfortable using visual interpretation to retrieve land cover information. However, it is highly influenced by subjectivity and knowledge of interpreter, also takes time in the process. Digital classification can be done in several ways, depend on the defined mapping approach and assumptions on data distribution. The study compared several classifiers method for some data type at the same location. The data used Landsat 8 satellite imagery, SPOT 6 and Orthophotos. In practical, the data used to produce land cover map in 1:50,000 map scale for Landsat, 1:25,000 map scale for SPOT and 1:5,000 map scale for Orthophotos, but using visual interpretation to retrieve information. Maximum likelihood Classifiers (MLC) which use pixel-based and parameters approach applied to such data, and also Artificial Neural Network classifiers which use pixel-based and non-parameters approach applied too. Moreover, this study applied object-based classifiers to the data. The classification system implemented is land cover classification on Indonesia topographic map. The classification applied to data source, which is expected to recognize the pattern and to assess consistency of the land cover map produced by each data. Furthermore, the study analyse benefits and limitations the use of methods.

  18. Impact of Moderate Resolution Imaging Spectroradiometer Aerosol Optical Depth and AirNow PM2.5 assimilation on Community Multi-scale Air Quality aerosol predictions over the contiguous United States

    NASA Astrophysics Data System (ADS)

    Chai, Tianfeng; Kim, Hyun-Cheol; Pan, Li; Lee, Pius; Tong, Daniel

    2017-05-01

    In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) and AirNow PM2.5 measurements are assimilated into the Community Multi-scale Air Quality (CMAQ) model using an optimal interpolation (OI) method. Over a 30 day test period in July 2011, three assimilation configurations were used in which MODIS AOD and AirNow PM2.5 measurements were first assimilated separately before being assimilated simultaneously. The background error covariance is estimated using both the National Meteorological Center approach and the Hollingsworth-Lönnberg method. The AOD observations from Terra are assimilated at 17Z and the Aqua AOD observations are assimilated at 20Z each day. AirNow PM2.5 measurements are assimilated 4 times a day at 00Z, 06Z, 12Z, and 18Z. Model performances are measured by the daily averaged and domain-averaged biases and the root-mean-square errors (RMSEs) obtained by comparing the predictions with the AirNow PM2.5 observations that were not assimilated. Either assimilating the MODIS AOD or assimilating the AirNow PM2.5 alone helps PM2.5 predictions over the entire 30 days. The case that assimilates the observations from both sources has the best performance. While the CMAQ PM2.5 results exhibit exaggerated diurnal variations compared to the AirNow measurements, this is not as severe at rural sites as at urban or suburban sites. It was also found that assimilating the total AOD observations is more beneficial for correcting the PM2.5 underestimations than directly assimilating the AirNow PM2.5 measurements every 6 h. While the simple approach of applying the AOD scaling factors uniformly throughout the vertical columns proved effective, it is liable to produce substantial errors. This is demonstrated by a high-AOD event.

  19. Multi-scale patch and multi-modality atlases for whole heart segmentation of MRI.

    PubMed

    Zhuang, Xiahai; Shen, Juan

    2016-07-01

    A whole heart segmentation (WHS) method is presented for cardiac MRI. This segmentation method employs multi-modality atlases from MRI and CT and adopts a new label fusion algorithm which is based on the proposed multi-scale patch (MSP) strategy and a new global atlas ranking scheme. MSP, developed from the scale-space theory, uses the information of multi-scale images and provides different levels of the structural information of images for multi-level local atlas ranking. Both the local and global atlas ranking steps use the information theoretic measures to compute the similarity between the target image and the atlases from multiple modalities. The proposed segmentation scheme was evaluated on a set of data involving 20 cardiac MRI and 20 CT images. Our proposed algorithm demonstrated a promising performance, yielding a mean WHS Dice score of 0.899 ± 0.0340, Jaccard index of 0.818 ± 0.0549, and surface distance error of 1.09 ± 1.11 mm for the 20 MRI data. The average runtime for the proposed label fusion was 12.58 min.

  20. Computer-aided detection of human cone photoreceptor inner segments using multi-scale circular voting

    NASA Astrophysics Data System (ADS)

    Liu, Jianfei; Dubra, Alfredo; Tam, Johnny

    2016-03-01

    Cone photoreceptors are highly specialized cells responsible for the origin of vision in the human eye. Their inner segments can be noninvasively visualized using adaptive optics scanning light ophthalmoscopes (AOSLOs) with nonconfocal split detection capabilities. Monitoring the number of cones can lead to more precise metrics for real-time diagnosis and assessment of disease progression. Cell identification in split detection AOSLO images is hindered by cell regions with heterogeneous intensity arising from shadowing effects and low contrast boundaries due to overlying blood vessels. Here, we present a multi-scale circular voting approach to overcome these challenges through the novel combination of: 1) iterative circular voting to identify candidate cells based on their circular structures, 2) a multi-scale strategy to identify the optimal circular voting response, and 3) clustering to improve robustness while removing false positives. We acquired images from three healthy subjects at various locations on the retina and manually labeled cell locations to create ground-truth for evaluating the detection accuracy. The images span a large range of cell densities. The overall recall, precision, and F1 score were 91±4%, 84±10%, and 87±7% (Mean±SD). Results showed that our method for the identification of cone photoreceptor inner segments performs well even with low contrast cell boundaries and vessel obscuration. These encouraging results demonstrate that the proposed approach can robustly and accurately identify cells in split detection AOSLO images.

  1. Multi-Scale Dynamics, Control, and Simulation of Granular Spacecraft

    NASA Technical Reports Server (NTRS)

    Quadrelli, Marco B.; Basinger, Scott; Swartzlander, Grover

    2013-01-01

    In this paper, we present some ideas regarding the modeling, dynamics and control aspects of granular spacecraft. Granular spacecraft are complex multibody systems composed of a spatially disordered distribution of a large number of elements, for instance a cloud of grains in orbit. An example of application is a spaceborne observatory for exoplanet imaging, where the primary aperture is a cloud instead of a monolithic aperture. A model is proposed of a multi-scale dynamics of the grains and cloud in orbit, as well as a control approach for cloud shape maintenance and alignment, and preliminary simulation studies are carried out for the representative imaging system.

  2. Multi-Scale Dynamics, Control, and Simulation of Granular Spacecraft

    NASA Technical Reports Server (NTRS)

    Quadrelli, Marco B.; Basinger, Scott; Swartzlander, Grover

    2013-01-01

    In this paper, we present some ideas regarding the modeling, dynamics and control aspects of granular spacecraft. Granular spacecraft are complex multibody systems composed of a spatially disordered distribution of a large number of elements, for instance a cloud of grains in orbit. An example of application is a spaceborne observatory for exoplanet imaging, where the primary aperture is a cloud instead of a monolithic aperture. A model is proposed of a multi-scale dynamics of the grains and cloud in orbit, as well as a control approach for cloud shape maintenance and alignment, and preliminary simulation studies are carried out for the representative imaging system.

  3. Multi-scale interactions in Dictyostelium discoideum aggregation

    NASA Astrophysics Data System (ADS)

    Dixon, James A.; Kelty-Stephen, Damian G.

    2012-12-01

    Cellular aggregation is essential for a wide range of phenomena in developmental biology, and a crucial event in the life-cycle of Dictyostelium discoideum. The current manuscript presents an analysis of multi-scale interactions involved in D. discoideum aggregation and non-aggregation events. The multi-scale fractal dimensions of a sequence of microscope images were used to estimate changing structure at different spatial scales. Three regions showing aggregation and three showing non-aggregation were considered. The results showed that both aggregation and non-aggregation regions were strongly multi-fractal. Analyses of the over-time relationships among nine scales of the generalized dimension, D(q), were conducted using vector autoregression and vector error-correction models. Both types of regions showed evidence that across-scale interactions serve to maintain the equilibrium of the system. Aggregation and non-aggregation regions also showed different patterns of effects of individual scales on other scales. Specifically, aggregation regions showed greater effects of both the smallest and largest scales on the smaller scale structures. The results suggest that multi-scale interactions are responsible for maintaining and altering the cellular structures during aggregation.

  4. Compressed sensing MRI using higher order multi-scale FREBAS for sparsifying transform function

    NASA Astrophysics Data System (ADS)

    Ito, S.; Ito, K.; Shibuya, M.; Yamada, Y.

    2015-03-01

    In recent years, compressed sensing (CS) has attracted considerable attention in areas such as rapid magnetic resonance (MR) imaging. Signal sparsity is an essential condition for compressed sensing. In this work, a multi-scale sparsifying transform based on the Fresnel transform (FREBAS) is adopted in order to improve the quality of CS images. The experimental results demonstrate that by increasing the sparsity of the image in the FREBAS transform domain, curved features in MR images can be more faithfully reconstructed than is possible using the traditional wavelet transform or curvelet transform particularly for low sampling rates in k-space. In addition, proposed method is robust to the selection of sampling trajectory of NMR signal.

  5. Multi-modality registration via multi-scale textural and spectral embedding representations

    NASA Astrophysics Data System (ADS)

    Li, Lin; Rusu, Mirabela; Viswanath, Satish; Penzias, Gregory; Pahwa, Shivani; Gollamudi, Jay; Madabhushi, Anant

    2016-03-01

    Intensity-based similarity measures assume that the original signal intensity of different modality images can provide statistically consistent information regarding the two modalities to be co-registered. In multi-modal registration problems, however, intensity-based similarity measures are often inadequate to identify an optimal transformation. Texture features can improve the performance of the multi-modal co-registration by providing more similar appearance representations of the two images to be co-registered, compared to the signal intensity representations. Furthermore, texture features extracted at different length scales (neighborhood sizes) can reveal similar underlying structural attributes between the images to be co-registered similarities that may not be discernible on the signal intensity representation alone. However one limitation of using texture features is that a number of them may be redundant and dependent and hence there is a need to identify non-redundant representations. Additionally it is not clear which features at which specific scales reveal similar attributes across the images to be co-registered. To address this problem, we introduced a novel approach for multimodal co-registration that employs new multi-scale image representations. Our approach comprises 4 distinct steps: (1) texure feature extraction at each length scale within both the target and template images, (2) independent component analysis (ICA) at each texture feature length scale, and (3) spectrally embedding (SE) the ICA components (ICs) obtained for the texture features at each length scale, and finally (4) identifying and combining the optimal length scales at which to perform the co-registration. To combine and co-register across different length scales, -mutual information (-MI) was applied in the high dimensional space of spectral embedding vectors to facilitate co-registration. To validate our multi-scale co-registration approach, we aligned 45 pairs of prostate

  6. 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

  7. Nanostructured particles from multi scale building blocks

    NASA Astrophysics Data System (ADS)

    Hampsey, J. Eric

    Nanotechnology has emerged as one of the most exciting new and developing fields in science today. New nanoscale materials and devices such as nanoparticles, nanocomposites, nanowires, and nanosensors could revolutionize the 21st century in the same way that the transistor and Internet led to the information age. One key component in developing these new technologies is to assemble individual atomic and molecular building blocks into larger structures with fundamentally new properties and functions. Nature is very efficient at assembling multi scale building blocks such as proteins, lipids, and minerals into nanostructured materials such as bone, teeth, diatoms, eggshells, seashells, cell membranes, and DNA. Surfactant and colloidal building block can also be assembled into different nanoscale materials and devices by utilizing hydrophobic/hydrophilic and other surface interactions. Using these concepts, this dissertation focuses on the syntheses and applications of nanostructured particles assembled from multi scale building blocks. Important factors in the synthesis of the particles include particle size, particle morphology, pore size and pore structure. Five different types of nanostructured particles assembled from different multi scale building blocks are demonstrated in this work: (1) Spherical metal/silica mesoporous particles with high surface areas and controllable pore sizes, pore structures, and metal content are synthesized from surfactant, silicate, and metal building blocks for catalytic applications; (2) Mesoporous hollow spheres with controllable pore sizes and pore structures are synthesized from surfactant, silica, and polystyrene building blocks; (3) Spherical mesoporous carbon particles with controllable pore sizes and pore structures are templated from silica particles assembled from silica and surfactant building blocks; (4) Spherical mesoporous, microporous, and bimodal carbon particles are synthesized from sucrose and silica building blocks

  8. The Monitoring, Detection, Isolation and Assessment of Information Warfare Attacks Through Multi-Level, Multi-Scale System Modeling and Model Based Technology

    DTIC Science & Technology

    2004-01-01

    window size of 10. Figure 5-7 shows the ROC curve of the “EWMA vector” classifier for the λ value of 0.04 based on the CHAID algorithm in comparison ...k(i), from the training data using the event intensity method ...11 Figure 1-2. The observations of the event intensity, k(i), from the testing data using the event intensity method

  9. Surface Roughness from Point Clouds - A Multi-Scale Analysis

    NASA Astrophysics Data System (ADS)

    Milenković, Milutin; Ressl, Camillo; Hollaus, Markus; Pfeifer, Norbert

    2013-04-01

    Roughness is a physical parameter of surfaces which should include the surface complexity in geophysical models. In hydrodynamic modeling, e.g., roughness should estimate the resistance caused by the surface on the flow, or in remote sensing, how the signal is scattered. Roughness needs to be estimated as a parameter of the model. This has been identified as main source of the uncertainties in model prediction, mainly due to the errors that follow a traditional roughness estimation, e.g. from surface profiles, or by a visual interpretation and manual delineation from aerial photos. Currently, roughness estimation is shifting towards point clouds of surfaces, which primarily come from laser scanning and image matching techniques. However, those data sets are also not free of errors and may affect roughness estimation. Our study focusses on the estimation of roughness indices from different point clouds, and the uncertainties that follow such a procedure. The analysis is performed on a graveled surface of a river bed in Eastern Austria, using point clouds acquired by a triangulating laser scanner (Minolta Vivid 910), photogrammetry (DSLR camera), and terrestrial laser scanner (Riegl FWF scanner). To enable their comparison, all the point clouds are transformed to a superior coordinate system. Then, different roughness indices are calculated and compared at different scales, including stochastic and features-based indices like RMS of elevation, std.dev., Peak to Valley height, openness. The analysis is additionally supported with the spectral signatures (frequency domain) of the different point clouds. The selected techniques provide point clouds of different resolution (0.1-10cm) and coverage (0.3-10m), which also justifies the multi-scale roughness analysis. By doing this, it becomes possible to differentiate between the measurement errors and the roughness of the object at the resolutions of the point clouds. Parts of this study have been funded by the project

  10. Integrating multi-scale data on homologous recombination into a new recognition mechanism based on simulations of the RecA-ssDNA/dsDNA structure

    PubMed Central

    Yang, Darren; Boyer, Benjamin; Prévost, Chantal; Danilowicz, Claudia; Prentiss, Mara

    2015-01-01

    RecA protein is the prototypical recombinase. Members of the recombinase family can accurately repair double strand breaks in DNA. They also provide crucial links between pairs of sister chromatids in eukaryotic meiosis. A very broad outline of how these proteins align homologous sequences and promote DNA strand exchange has long been known, as are the crystal structures of the RecA-DNA pre- and postsynaptic complexes; however, little is known about the homology searching conformations and the details of how DNA in bacterial genomes is rapidly searched until homologous alignment is achieved. By integrating a physical model of recognition to new modeling work based on docking exploration and molecular dynamics simulation, we present a detailed structure/function model of homology recognition that reconciles extremely quick searching with the efficient and stringent formation of stable strand exchange products and which is consistent with a vast body of previously unexplained experimental results. PMID:26384422

  11. Hydro-climatic trends and water resource management implications based on multi-scale data for the Lake Victoria region, Kenya

    NASA Astrophysics Data System (ADS)

    Koutsouris, A. J.; Destouni, G.; Jarsjö, J.; Lyon, S. W.

    2010-07-01

    Unreliable rainfall may be a main cause of poverty in rural areas, such as the Kisumu district by Lake Victoria in Kenya. Climate change may further increase the negative effects of rainfall uncertainty. These effects could be mitigated to some extent through improved and adaptive water resource management and planning, which relies on our interpretations and projections of the coupled hydro-climatic system behaviour and its development trends. In order to identify and quantify the main differences and consistencies among such hydro-climatic assessments, this study investigates trends and exemplifies their use for important water management decisions for the Lake Victoria drainage basin (LVDB), based on local scale data for the Orongo village in the Kisumu district, and regional scale data for the whole LVDB. Results show low correlation between locally and regionally observed hydro-climatic trends, and large differences, which in turn affects assessments of important water resource management parameters. However, both data scales converge in indicating that observed local and regional hydrological discharge trends are primarily driven by local and regional water use and land use changes.

  12. The evolution of spillover effects between oil and stock markets across multi-scales using a wavelet-based GARCH-BEKK model

    NASA Astrophysics Data System (ADS)

    Liu, Xueyong; An, Haizhong; Huang, Shupei; Wen, Shaobo

    2017-01-01

    Aiming to investigate the evolution of mean and volatility spillovers between oil and stock markets in the time and frequency dimensions, we employed WTI crude oil prices, the S&P 500 (USA) index and the MICEX index (Russia) for the period Jan. 2003-Dec. 2014 as sample data. We first applied a wavelet-based GARCH-BEKK method to examine the spillover features in frequency dimension. To consider the evolution of spillover effects in time dimension at multiple-scales, we then divided the full sample period into three sub-periods, pre-crisis period, crisis period, and post-crisis period. The results indicate that spillover effects vary across wavelet scales in terms of strength and direction. By analysis the time-varying linkage, we found the different evolution features of spillover effects between the Oil-US stock market and Oil-Russia stock market. The spillover relationship between oil and US stock market is shifting to short-term while the spillover relationship between oil and Russia stock market is changing to all time scales. That result implies that the linkage between oil and US stock market is weakening in the long-term, and the linkage between oil and Russia stock market is getting close in all time scales. This may explain the phenomenon that the US stock index and the Russia stock index showed the opposite trend with the falling of oil price in the post-crisis period.

  13. Investigation of mechanism of bone regeneration in a porous biodegradable calcium phosphate (CaP) scaffold by a combination of a multi-scale agent-based model and experimental optimization/validation.

    PubMed

    Zhang, Le; Qiao, Minna; Gao, Hongjie; Hu, Bin; Tan, Hua; Zhou, Xiaobo; Li, Chang Ming

    2016-08-21

    Herein, we have developed a novel approach to investigate the mechanism of bone regeneration in a porous biodegradable calcium phosphate (CaP) scaffold by a combination of a multi-scale agent-based model, experimental optimization of key parameters and experimental data validation of the predictive power of the model. The advantages of this study are that the impact of mechanical stimulation on bone regeneration in a porous biodegradable CaP scaffold is considered, experimental design is used to investigate the optimal combination of growth factors loaded on the porous biodegradable CaP scaffold to promote bone regeneration and the training, testing and analysis of the model are carried out by using experimental data, a data-mining algorithm and related sensitivity analysis. The results reveal that mechanical stimulation has a great impact on bone regeneration in a porous biodegradable CaP scaffold and the optimal combination of growth factors that are encapsulated in nanospheres and loaded into porous biodegradable CaP scaffolds layer-by-layer can effectively promote bone regeneration. Furthermore, the model is robust and able to predict the development of bone regeneration under specified conditions.

  14. Investigation of mechanism of bone regeneration in a porous biodegradable calcium phosphate (CaP) scaffold by a combination of a multi-scale agent-based model and experimental optimization/validation

    NASA Astrophysics Data System (ADS)

    Zhang, Le; Qiao, Minna; Gao, Hongjie; Hu, Bin; Tan, Hua; Zhou, Xiaobo; Li, Chang Ming

    2016-08-01

    Herein, we have developed a novel approach to investigate the mechanism of bone regeneration in a porous biodegradable calcium phosphate (CaP) scaffold by a combination of a multi-scale agent-based model, experimental optimization of key parameters and experimental data validation of the predictive power of the model. The advantages of this study are that the impact of mechanical stimulation on bone regeneration in a porous biodegradable CaP scaffold is considered, experimental design is used to investigate the optimal combination of growth factors loaded on the porous biodegradable CaP scaffold to promote bone regeneration and the training, testing and analysis of the model are carried out by using experimental data, a data-mining algorithm and related sensitivity analysis. The results reveal that mechanical stimulation has a great impact on bone regeneration in a porous biodegradable CaP scaffold and the optimal combination of growth factors that are encapsulated in nanospheres and loaded into porous biodegradable CaP scaffolds layer-by-layer can effectively promote bone regeneration. Furthermore, the model is robust and able to predict the development of bone regeneration under specified conditions.

  15. Parsing the Sources of Gross Gains in Stream Flow Based on Mass Recovery of Concurrent Instantaneous and Constant-Rate Tracer Releases Over Multi-Scaled Reaches

    NASA Astrophysics Data System (ADS)

    Gooseff, M. N.; Payn, R. A.; McGlynn, B. L.

    2014-12-01

    Reach-scale solute transport studies are often used to characterize transient storage of solutes or groundwater-stream exchanges, yet the results are limited by window of detection issues (the limit of temporal and spatial scales over which one can infer processes from observed breakthrough curves). To determine the influence of exchanges into and out of reaches of different spatial scales, we conducted two simultaneous tracer injection types in a headwater stream in the Tenderfoot Creek Experimental Forest in central Montana, USA - one constant rate Rhodamine WT (RWT) injection (8 days) over 2.8 km of stream, and synoptic chloride releases in 28 100-m and 14 200-m subreaches when the RWT concentrations were at quasi-steady state. From the synoptic releases, we examined the spatial distribution of stream flow exchanges. Stream discharge increased from 0.8 L s-1 (at the head) to 27 L s-1 (at the base) along the 2.8-km study reach. Although the stream gains water at the scale of the 2.8-km study reach, stream water balances in the 100-m and 200-m subreaches demonstrate gross gains and losses. When comparing the summed gains and losses of the two 100-m subreach exchanges to that of the encompassing 200-m reach, the combined 100 m reaches always exhibit greater gain and loss. We interpret this as an indication that the 200-m reach includes return flows that appear to be losses from the 100-m subreaches. When we evaluate the change in RWT load at 100-m and 200-m subreach scales, we find typically less mass loss of RWT than is computed from the chloride slug releases, indicating the gain of RWT from long hyporheic flowpaths that originate upstream of the subreach of interest (even when RWT is likely to be a less conservative tracer than chloride). We can further parse gains of stream water at the 100-m and 200-m scales into estimates of hyporheic water (i.e., streamwater labelled with RWT returning to the channel) and lateral water (not labelled with RWT), and we find

  16. Multi-scale harmonic model for solar and climate cyclical variation throughout the Holocene based on Jupiter-Saturn tidal frequencies plus the 11-year solar dynamo cycle

    NASA Astrophysics Data System (ADS)

    Scafetta, Nicola

    2012-05-01

    The Schwabe frequency band of the Zurich sunspot record since 1749 is found to be made of three major cycles with periods of about 9.98, 10.9 and 11.86 years. The side frequencies appear to be closely related to the spring tidal period of Jupiter and Saturn (range between 9.5 and 10.5 years, and median 9.93 years) and to the tidal sidereal period of Jupiter (about 11.86 years). The central cycle may be associated to a quasi-11-year solar dynamo cycle that appears to be approximately synchronized to the average of the two planetary frequencies. A simplified harmonic constituent model based on the above two planetary tidal frequencies and on the exact dates of Jupiter and Saturn planetary tidal phases, plus a theoretically deduced 10.87-year central cycle reveals complex quasi-periodic interference/beat patterns. The major beat periods occur at about 115, 61 and 130 years, plus a quasi-millennial large beat cycle around 983 years. We show that equivalent synchronized cycles are found in cosmogenic records used to reconstruct solar activity and in proxy climate records throughout the Holocene (last 12,000 years) up to now. The quasi-secular beat oscillations hindcast reasonably well the known prolonged periods of low solar activity during the last millennium such as the Oort, Wolf, Spörer, Maunder and Dalton minima, as well as the 17 115-year long oscillations found in a detailed temperature reconstruction of the Northern Hemisphere covering the last 2000 years. The millennial three-frequency beat cycle hindcasts equivalent solar and climate cycles for 12,000 years. Finally, the harmonic model herein proposed reconstructs the prolonged solar minima that occurred during 1900-1920 and 1960-1980 and the secular solar maxima around 1870-1890, 1940-1950 and 1995-2005 and a secular upward trending during the 20th century: this modulated trending agrees well with some solar proxy model, with the ACRIM TSI satellite composite and with the global surface temperature

  17. Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features

    NASA Astrophysics Data System (ADS)

    Wang, Min; Cui, Qi; Wang, Jie; Ming, Dongping; Lv, Guonian

    2017-01-01

    In this paper, we first propose several novel concepts for object-based image analysis, which include line-based shape regularity, line density, and scale-based best feature value (SBV), based on the region-line primitive association framework (RLPAF). We then propose a raft cultivation area (RCA) extraction method for high spatial resolution (HSR) remote sensing imagery based on multi-scale feature fusion and spatial rule induction. The proposed method includes the following steps: (1) Multi-scale region primitives (segments) are obtained by image segmentation method HBC-SEG, and line primitives (straight lines) are obtained by phase-based line detection method. (2) Association relationships between regions and lines are built based on RLPAF, and then multi-scale RLPAF features are extracted and SBVs are selected. (3) Several spatial rules are designed to extract RCAs within sea waters after land and water separation. Experiments show that the proposed method can successfully extract different-shaped RCAs from HR images with good performance.

  18. Quantitative assessment of laser-dazzling effects through wavelet-weighted multi-scale SSIM measurements

    NASA Astrophysics Data System (ADS)

    Qian, Fang; Guo, Jin; Sun, Tao; Wang, Tingfeng

    2015-04-01

    Laser active imaging systems are widespread tools used in region surveillance and threat identification. However, the photoelectric imaging detector in the imaging systems is easy to be disturbed and this leads to errors of the recognition and even the missing of the target. In this paper, a novel wavelet-weighted multi-scale structural similarity (WWMS-SSIM) algorithm is proposed. 2-D four-level wavelet decomposition is performed for the original and disturbed images. Each image can be partitioned into one low-frequency subband (LL) and a series of octave high-frequency subbands (HL, LH and HH). Luminance, contrast and structure comparison are computed in different subbands with different weighting factors. Based on the results of the above, we can construct a modified WWMS-SSIM. Cross-distorted image quality assessment experiments show that the WWMS-SSIM algorithm is more suitable for the subjective visual feeling comparing with NMSE and SSIM. In the laser-dazzling image quality assessment experiments, the WWMS-SSIM gives more reasonable evaluations to the images with different power and laser spot positions, which can be useful to give the guidance of the laser active imaging system defense and application.

  19. Strong, Multi-Scale Heterogeneity in Earth’s Lowermost Mantle

    PubMed Central

    Tkalčić, Hrvoje; Young, Mallory; Muir, Jack B.; Davies, D. Rhodri; Mattesini, Maurizio

    2015-01-01

    The core mantle boundary (CMB) separates Earth’s liquid iron outer core from the solid but slowly convecting mantle. The detailed structure and dynamics of the mantle within ~300 km of this interface remain enigmatic: it is a complex region, which exhibits thermal, compositional and phase-related heterogeneity, isolated pockets of partial melt and strong variations in seismic velocity and anisotropy. Nonetheless, characterising the structure of this region is crucial to a better understanding of the mantle’s thermo-chemical evolution and the nature of core-mantle interactions. In this study, we examine the heterogeneity spectrum from a recent P-wave tomographic model, which is based upon trans-dimensional and hierarchical Bayesian imaging. Our tomographic technique avoids explicit model parameterization, smoothing and damping. Spectral analyses reveal a multi-scale wavelength content and a power of heterogeneity that is three times larger than previous estimates. Inter alia, the resulting heterogeneity spectrum gives a more complete picture of the lowermost mantle and provides a bridge between the long-wavelength features obtained in global S-wave models and the short-scale dimensions of seismic scatterers. The evidence that we present for strong, multi-scale lowermost mantle heterogeneity has important implications for the nature of lower mantle dynamics and prescribes complex boundary conditions for Earth’s geodynamo. PMID:26674394

  20. Multi-scale gravity and cosmology

    SciTech Connect

    Calcagni, Gianluca

    2013-12-01

    The gravitational dynamics and cosmological implications of three classes of recently introduced multi-scale spacetimes (with, respectively, ordinary, weighted and q-derivatives) are discussed. These spacetimes are non-Riemannian: the metric structure is accompanied by an independent measure-differential structure with the characteristics of a multi-fractal, namely, different dimensionality at different scales and, at ultra-short distances, a discrete symmetry known as discrete scale invariance. Under this minimal paradigm, five general features arise: (a) the big-bang singularity can be replaced by a finite bounce, (b) the cosmological constant problem is reinterpreted, since accelerating phases can be mimicked by the change of geometry with the time scale, without invoking a slowly rolling scalar field, (c) the discreteness of geometry at Planckian scales can leave an observable imprint of logarithmic oscillations in cosmological spectra and (d) give rise to an alternative mechanism to inflation or (e) to a fully analytic model of cyclic mild inflation, where near scale invariance of the perturbation spectrum can be produced without strong acceleration. Various properties of the models and exact dynamical solutions are discussed. In particular, the multi-scale geometry with weighted derivatives is shown to be a Weyl integrable spacetime.

  1. Tuneable resolution as a systems biology approach for multi-scale, multi-compartment computational models.

    PubMed

    Kirschner, Denise E; Hunt, C Anthony; Marino, Simeone; Fallahi-Sichani, Mohammad; Linderman, Jennifer J

    2014-01-01

    The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work.

  2. 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…

  3. 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…

  4. 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.

  5. 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

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

    PubMed

    Ong, Frank; Lustig, Michael

    2016-06-01

    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.

  7. 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.; Kumar, S.; Lapenta, W.; Li, X.; Matsui, T.; Rienecker, M.; Shen, B.W.; Shi, J.J.; Simpson, J.; Zeng, X.

    2008-01-01

    Numerical cloud resolving models (CRMs), which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that CRMs agree with observations in simulating various types of clouds and cloud systems from different geographic locations. 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 Numerical Weather Prediction (NWP) and regional scale model can be run in grid size similar to cloud resolving model through nesting technique. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a szrper-parameterization or multi-scale modeling -framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign can provide initial conditions as well as validation through utilizing the Earth Satellite simulators. At Goddard, we have developed a multi-scale modeling system with unified physics. The modeling system consists a coupled GCM-CRM (or MMF); a state-of-the-art weather research forecast model (WRF) and a cloud-resolving model (Goddard Cumulus Ensemble model). In these models, the same microphysical schemes (2ICE, several 3ICE), radiation (including explicitly calculated cloud optical properties), and surface models are applied. In addition, a comprehensive unified Earth Satellite

  8. 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.

  9. Multi-scaling and mesoscopic structures

    PubMed Central

    Salje, E. K. H.

    2010-01-01

    Multi-scaling and the systematic investigation of mesoscopic structures represent a field of fruitful cooperation in physics, chemistry, mineralogy and life sciences. The increasing miniaturization of devices as well as the emphasis of recent research on microstructures with length scales of a few nanometres lead to paradigm changes that may impact not only on our scientific understanding of fine-grained structures but also on the way we will develop device materials in the future. Here the role of interfaces becomes more important, and developments in areas such as ‘domain boundary engineering’ are evidence of this scientific evolution. In addition, nano-porous materials are particularly important in geology and in the development of artificial bones and ultra-light metals. Some of these developments are reviewed in this paper. PMID:20123752

  10. Nonlinear helicons bearing multi-scale structures

    NASA Astrophysics Data System (ADS)

    Abdelhamid, Hamdi M.; Yoshida, Zensho

    2017-02-01

    The helicon waves exhibit varying characters depending on plasma parameters, geometry, and wave numbers. Here, we elucidate an intrinsic multi-scale property embodied by the combination of the dispersive effect and nonlinearity. The extended magnetohydrodynamics model (exMHD) is capable of describing a wide range of parameter space. By using the underlying Hamiltonian structure of exMHD, we construct an exact nonlinear solution, which turns out to be a combination of two distinct modes, the helicon and Trivelpiece-Gould (TG) waves. In the regime of relatively low frequency or high density, however, the combination is made of the TG mode and an ion cyclotron wave (slow wave). The energy partition between these modes is determined by the helicities carried by the wave fields.

  11. Multi-Scale 7DOF View Adjustment.

    PubMed

    Cho, Isaac; Li, Jialei; Wartell, Zachary

    2017-02-13

    Multi-scale virtual environments contain geometric details ranging over several orders of magnitude and typically employ out-of-core rendering techniques. When displayed in virtual reality systems this entails using a 7 degree-of-freedom (DOF) view model where view scale is a separate 7th DOF in addition to 6DOF view pose. Dynamic adjustment of this and other view parameters become very important to usability. In this paper, we evaluate how two adjustment techniques interact with uni- and bi-manual 7 degree-of-freedom navigation in DesktopVR and a CAVE. The travel task has two stages, an initial targeted zoom and a detailed geometric inspection. The results show benefits of the auto-adjustments on completion time and stereo fusion issues, but only in certain circumstances. Peculiar view configuration examples show the difficulty of creating robust adjustment rules.

  12. Metadata in the Collaboratory for Multi-Scale Chemical Science

    SciTech Connect

    Pancerella, Carmen M.; Hewson, John; Koegler, Wendy S.; Leahy, David; Lee, Michael; Rahn, Larry; Yang, Christine; Myers, James D.; Didier, Brett T.; McCoy, Renata; Schuchardt, Karen L.; Stephan, Eric G.; Windus, Theresa L.; Amin, Kaizer; Bittner, Sandra; Lansing, Carina S.; Minkoff, Michael; Nijsure, Sandeep; von Laszewski, Gregor; Pinzon, Reinhardt; Ruscic, Branko; Wagner, Albert F.; Wang, Baoshan; Pitz, William; Ho, Yen-Ling; Montoya, David W.; Xu, Lili; Allison, Thomas C.; Green, William H.; Frenklach, Michael

    2003-10-02

    The goal of the Collaboratory for the Multi-scale Chemical Sciences (CMCS) [1] is to develop an informatics-based approach to synthesizing multi-scale chemistry information to create knowledge in the chemical sciences. CMCS is using a portal and metadata-aware content store as a base for building a system to support inter-domain knowledge exchange in chemical science. Key aspects of the system include configurable metadata extraction and translation, a core schema for scientific pedigree, and a suite of tools for managing data and metadata and visualizing pedigree relationships between data entries. CMCS metadata is represented using Dublin Core with metadata extensions that are useful to both the chemical science community and the science community in general. CMCS is working with several chemistry groups who are using the system to collaboratively assemble and analyze existing data to derive new chemical knowledge. In this paper we discuss the project’s metadata-related requirements, the relevant software infrastructure, core metadata schema, and tools that use the metadata to enhance science

  13. Multi-scale indicators in CropWatch

    NASA Astrophysics Data System (ADS)

    Wu, B.; Gommes, R.; Zhang, M.; Zeng, H.; Yan, N.; Zhang, N.; Zou, W.; Chang, S.; Liu, G.

    2013-12-01

    separately. For China, a special indicator (crop type proportion, CTP) will be used to estimate planting area by crop type. Based on the multi-scale remote sensing based indicators, CropWatch can identify recent and noteworthy changes affecting wheat, maize, rice and soybean, and focus on trends that are likely to continue.

  14. Wake characteristics of a porous square cylinder formed by a multi-scale array of obstacles

    NASA Astrophysics Data System (ADS)

    Wise, Daniel J.; Avoustin, Pauline; Cassadour, Martin; Brevis, Wernher

    2015-11-01

    The characteristics of the flow developed behind arrays of square cylinders are investigated through Particle Image Velocimetry (PIV) and Acoustic Doppler Velocimetry (ADV) measurements in an open-channel water flume. Four arrangements of cylinders are examined: three are multi-scale arrays of cylinders based on the Sierpinski carpet fractal, and the fourth is a regular aligned array of single length-scale cylinders. The porosity, frontal area and external length scale is the same for each cylinder array, while the internal geometry is changed. The relative effect on the dynamics of the wake of the fractal parameters defining the array geometry, such as lacunarity and succolarity is quantified. Special focus is given to the effect of these parameters on the extension and properties of the separated shear layers and on the low-velocity zone developed downstream the cylinders.

  15. An augmented Lagrangian multi-scale dictionary learning algorithm

    NASA Astrophysics Data System (ADS)

    Liu, Qiegen; Luo, Jianhua; Wang, Shanshan; Xiao, Moyan; Ye, Meng

    2011-12-01

    Learning overcomplete dictionaries for sparse signal representation has become a hot topic fascinated by many researchers in the recent years, while most of the existing approaches have a serious problem that they always lead to local minima. In this article, we present a novel augmented Lagrangian multi-scale dictionary learning algorithm (ALM-DL), which is achieved by first recasting the constrained dictionary learning problem into an AL scheme, and then updating the dictionary after each inner iteration of the scheme during which majorization-minimization technique is employed for solving the inner subproblem. Refining the dictionary from low scale to high makes the proposed method less dependent on the initial dictionary hence avoiding local optima. Numerical tests for synthetic data and denoising applications on real images demonstrate the superior performance of the proposed approach.

  16. Multi-scale structural community organisation of the human genome.

    PubMed

    Boulos, Rasha E; Tremblay, Nicolas; Arneodo, Alain; Borgnat, Pierre; Audit, Benjamin

    2017-04-11

    Structural interaction frequency matrices between all genome loci are now experimentally achievable thanks to high-throughput chromosome conformation capture technologies. This ensues a new methodological challenge for computational biology which consists in objectively extracting from these data the structural motifs characteristic of genome organisation. We deployed the fast multi-scale community mining algorithm based on spectral graph wavelets to characterise the networks of intra-chromosomal interactions in human cell lines. We observed that there exist structural domains of all sizes up to chromosome length and demonstrated that the set of structural communities forms a hierarchy of chromosome segments. Hence, at all scales, chromosome folding predominantly involves interactions between neighbouring sites rather than the formation of links between distant loci. Multi-scale structural decomposition of human chromosomes provides an original framework to question structural organisation and its relationship to functional regulation across the scales. By construction the proposed methodology is independent of the precise assembly of the reference genome and is thus directly applicable to genomes whose assembly is not fully determined.

  17. Reconfigurable multi-scale colloidal assembly on excluded volume patterns

    PubMed Central

    Edwards, Tara D.; Yang, Yuguang; Everett, W. Neil; Bevan, Michael A.

    2015-01-01

    The ability to create multi-scale, periodic colloidal assemblies with unique properties is important to emerging applications. Dynamically manipulating colloidal structures via tunable kT-scale attraction can provide the opportunity to create particle-based nano- and microstructured materials that are reconfigurable. Here, we report a novel tactic to obtain reconfigurable, multi-scale, periodic colloidal assemblies by combining thermoresponsive depletant particles and patterned topographical features that, together, reversibly mediate local kT-scale depletion interactions. This method is demonstrated in optical microscopy experiments to produce colloidal microstructures that reconfigure between well-defined ordered structures and disordered fluid states as a function of temperature and pattern feature depth. These results are well described by Monte Carlo simulations using theoretical depletion potentials that include patterned excluded volume. Ultimately, the approach reported here can be extended to control the size, shape, orientation, and microstructure of colloidal assemblies on multiple lengths scales and on arbitrary pre-defined pattern templates. PMID:26330058

  18. An iteratively adaptive multi-scale finite element method for elliptic PDEs with rough coefficients

    NASA Astrophysics Data System (ADS)

    Hou, Thomas Y.; Hwang, Feng-Nan; Liu, Pengfei; Yao, Chien-Chou

    2017-05-01

    We propose an iteratively adaptive Multi-scale Finite Element Method (MsFEM) for elliptic PDEs with rough coefficients. The choice of the local boundary conditions for the multi-sale basis functions determines the accuracy of the MsFEM numerical solution, and one needs to incorporate the global information of the elliptic equation into the local boundary conditions of the multi-scale basis functions to recover the underlying fine-mesh solution of the equation. In our proposed iteratively adaptive method, we achieve this global-to-local information transfer through the combination of coarse-mesh solving using adaptive multi-scale basis functions and fine-mesh smoothing operations. In each iteration step, we first update the multi-scale basis functions based on the approximate numerical solutions of the previous iteration steps, and obtain the coarse-mesh approximate solution using a Galerkin projection. Then we apply several steps of smoothing operations to the coarse-mesh approximate solution on the underlying fine mesh to get the updated approximate numerical solution. The proposed algorithm can be viewed as a nonlinear two-level multi-grid method with the restriction and prolongation operators adapted to the approximate numerical solutions of the previous iteration steps. Convergence analysis of the proposed algorithm is carried out under the framework of two-level multi-grid method, and the harmonic coordinates are employed to establish the approximation property of the adaptive multi-scale basis functions. We demonstrate the efficiency of our proposed multi-scale methods through several numerical examples including a multi-scale coefficient problem, a high-contrast interface problem, and a convection-dominated diffusion problem.

  19. Multi-scale study of soil structure from different genetic horizons: from meter to nanometer

    NASA Astrophysics Data System (ADS)

    Karsanina, Marina; Skvortsova, Elena; Abrosimov, Konstantin; Sizonenko, Timofey; Romanenko, Konstantin; Belokhin, Vasily; Yudina, Anna; Gilyazetdinova, Dina; Korost, Dmitry; Gerke, Kirill

    2016-04-01

    Soil structure is extremely diverse, has numerous relevant scales, e.g., important pore hierarchical levels, such as intra and inter aggregate porosity, cracks and others. None of the existing imaging techniques is capable of catching all scales within one single image due to sample size/resolution limitations. The only way to experimentally obtain soil structural information from all important scales is to utilize multi-scale scanning using different imaging approaches. In this study we use macro X-ray tomography (with resolution of 100 um), micro X-ray tomography (with resolution range of 3-16 um) and SEM with nanoscale resolutions to obtain a vast multi-scale structural data from meter to nanometer. Two one meter long undisturbed soil columns extracted from soddy-podzolic and grey forest soils were used as objects of our multi-scale study. At first macrotomography was used to make the coarsest 3D image of the whole column. Afterwards, the column was carefully sliced to obtain smaller undisturbed samples for microtomography scanning. Some undisturbed soil pieces were also imaged using SEM to obtain sub-micron images of the soil structure. All resulting 2/3D images were segmented using up-to-date image processing and segmentation techniques to obtain solid material and pore space binary phases. Directional correlation functions were utilized to characterize multi-scale soil structures and compare/differentiate them from each other. We extensively show how such powerful structural descriptors as correlation functions can results in better soil structure characterization and classification. Combined with multi-scale image fusion and/or pore-scale modelling techniques 3D multi-scale images can used to assess scale dependant flow and transport properties. This work was partially supported by RFBR grant 15-34-20989 (field studies, X-ray tomography and SEM imaging) and RSF grant 14-17-00658 (directional correlation functions). References: 1. Karsanina, M.V., Gerke, K

  20. Multi-scale models for cell adhesion

    NASA Astrophysics Data System (ADS)

    Wu, Yinghao; Chen, Jiawen; Xie, Zhong-Ru

    2014-03-01

    The interactions of membrane receptors during cell adhesion play pivotal roles in tissue morphogenesis during development. Our lab focuses on developing multi-scale models to decompose the mechanical and chemical complexity in cell adhesion. Recent experimental evidences show that clustering is a generic process for cell adhesive receptors. However, the physical basis of such receptor clustering is not understood. We introduced the effect of molecular flexibility to evaluate the dynamics of receptors. By delivering new theory to quantify the changes of binding free energy in different cellular environments, we revealed that restriction of molecular flexibility upon binding of membrane receptors from apposing cell surfaces (trans) causes large entropy loss, which dramatically increases their lateral interactions (cis). This provides a new molecular mechanism to initialize receptor clustering on the cell-cell interface. By using the subcellular simulations, we further found that clustering is a cooperative process requiring both trans and cis interactions. The detailed binding constants during these processes are calculated and compared with experimental data from our collaborator's lab.

  1. A Novel Spectral Approach to Multi-Scale Modeling

    NASA Astrophysics Data System (ADS)

    Landi, Giacomo

    2011-12-01

    In this work, we present a novel approach for predicting the elastic, thermo-elastic and plastic fields in three-dimensional (3-D) voxel-based microstructure datasets subjected to uniform periodic boundary conditions. Such localization relationships (linkages) lie at the core of all multi-scale modeling frameworks and can be efficiently formulated in a Discrete Fourier Transforms (DFT) -based knowledge system. This new formalism has its theoretical roots in the statistical continuum theories developed originally by Kroner [1]. However, in the approach described by Kroner, the terms in the series were established by selecting a reference medium and numerically evaluating a complex series of nested convolution integrals. This approach is largely hampered by the principal value problem, and exhibits high sensitivity to the properties of the selected reference medium. In the present work, the same series expressions have been recast into much more computationally efficient representations using DFTs. The spectral analysis transforms the complex integral relations into relatively simple algebraic expressions involving polynomials of structure parameters and morphology-independent influence coefficients. These coefficients need to be established only once for a given material system. The main advantage of the new DFT-based framework is that it allows easy calibration of Kroner's expansions to results from finite element methods, thereby overcoming all of the main obstacles associated with the principal value problem and the need to select a reference medium. This approach can be seen as an efficient procedure for data-mining the results from computationally expensive numerical models and establishing the underlying knowledge systems at a selected length scale in multi-scale modeling problems. The set of influence coefficients described above constitutes the underlying knowledge for a given deformation and can be easily stored and recalled as and when needed in a multi-scale

  2. Multi-Level and Multi-Scale Feature Aggregation Using Pretrained Convolutional Neural Networks for Music Auto-Tagging

    NASA Astrophysics Data System (ADS)

    Lee, Jongpil; Nam, Juhan

    2017-08-01

    Music auto-tagging is often handled in a similar manner to image classification by regarding the 2D audio spectrogram as image data. However, music auto-tagging is distinguished from image classification in that the tags are highly diverse and have different levels of abstractions. Considering this issue, we propose a convolutional neural networks (CNN)-based architecture that embraces multi-level and multi-scaled features. The architecture is trained in three steps. First, we conduct supervised feature learning to capture local audio features using a set of CNNs with different input sizes. Second, we extract audio features from each layer of the pre-trained convolutional networks separately and aggregate them altogether given a long audio clip. Finally, we put them into fully-connected networks and make final predictions of the tags. Our experiments show that using the combination of multi-level and multi-scale features is highly effective in music auto-tagging and the proposed method outperforms previous state-of-the-arts on the MagnaTagATune dataset and the Million Song Dataset. We further show that the proposed architecture is useful in transfer learning.

  3. Patient-specific modeling and multi-scale blood simulation for computational hemodynamic study on the human cerebrovascular system.

    PubMed

    Oshima, Marie; Torii, Ryo; Tokuda, Shigefumi; Yamada, Shigeki; Koizumi, Akio

    2012-09-01

    To develop a targeted drug delivery system for cerebrovascular disorders such as stroke, it is important to obtain detailed information on flow rates and hemodynamics of the human cerebrovascular system for individual patients. A patient-specific integrated numerical simulation system has been developed by the authors such that vascular geometry is constructed from medical images such as magnetic resonance imaging (MRI) or computed tomography (CT) data, and computational conditions are modeled mathematically to represent the realistic in vivo environments. In general, the three-dimensional numerical simulation using a patient-specific model is conducted only for a localized diseased region with atherosclerosis or an aneurysm. Although the analysis region is only a part of the circulatory system, the simulation should include the effects from the entire circulatory system. Since the peripheral network determines the flow distributions in the cerebrovascular system, the paper reviews the recent simulation methods to take into account the network by coupling the image-based three-dimensional simulation with a one- and zero-dimensional simulations as an outflow boundary condition The paper shows the mathematical modeling of the multi-scale outflow boundary condition and its applications to patient- specific models of the arterial circle of Willis. The results are compared to those using the conventional, free-stream boundary condition. As a result, the multi-scale outflow boundary condition shows a significant difference in flow rate of each artery and in flow distribution in the arterial circle of Willis.

  4. 17.1%-Efficient Multi-Scale-Textured Black Silicon Solar Cells without Dielectric Antireflection Coating

    SciTech Connect

    Toor, F.; Page, M. R.; Branz, H. M.; Yuan, H. C.

    2011-01-01

    In this work we present 17.1%-efficient p-type single crystal Si solar cells with a multi-scale-textured surface and no dielectric antireflection coating. Multi-scale texturing is achieved by a gold-nanoparticle-assisted nanoporous etch after conventional micron scale KOH-based pyramid texturing (pyramid black etching). By incorporating geometric enhancement of antireflection, this multi-scale texturing reduces the nanoporosity depth required to make silicon `black' compared to nanoporous planar surfaces. As a result, it improves short-wavelength spectral response (blue response), previously one of the major limiting factors in `black-Si' solar cells. With multi-scale texturing, the spectrum-weighted average reflectance from 350- to 1000-nm wavelength is below 2% with a 100-nm deep nanoporous layer. In comparison, roughly 250-nm deep nanopores are needed to achieve similar reflectance on planar surface. Here, we characterize surface morphology, reflectivity and solar cell performance of the multi-scale textured solar cells.

  5. SAR image registration based on SIFT and MSA

    NASA Astrophysics Data System (ADS)

    Yi, Zhaoxiang; Zhang, Xiongmei; Mu, Xiaodong; Wang, Kui; Song, Jianshe

    2014-02-01

    Referring to the problem of SAR image registration, an image registration method based on Scale Invariant Feature Transform (SIFT) and Multi-Scale Autoconvolution (MSA) is proposed. Based on the extraction of SIFT descriptors and the MSA affine invariant moments of the region around the keypoints, the feature fusion method based on canonical correlation analysis (CCA) is employed to fuse them together to be a new descriptor. After the control points are rough matched, the distance and gray correlation around the rough matched points are combined to build the similarity matrix and the singular value decomposition (SVD) method is employed to realize precise image registration. Finally, the affine transformation parameters are obtained and the images are registered. Experimental results show that the proposed method outperforms the SIFT method and achieves high accuracy in sub-pixel level.

  6. Predictive rendering of composite materials: a multi-scale approach

    NASA Astrophysics Data System (ADS)

    Muller, T.; Callet, P.; da Graça, F.; Paljic, A.; Porral, P.; Hoarau, R.

    2015-03-01

    Predictive rendering of material appearance means going deep into the understanding of the physical interaction between light and matter and how these interactions are perceived by the human brain. In this paper we describe our approach to predict the appearance of composite materials by relying on the multi-scale nature of the involved phenomena. Using recent works on physical modeling of complex materials, we show how to predict the aspect of a composite material based on its composition and its morphology. Specifically, we focus on the materials whose morphological structures are defined at several embedded scales. We rely on the assumption that when the inclusions in a composite material are smaller than the considered wavelength, the optical constants of the corresponding effective media can be computed by a homogenization process (or analytically for special cases) to be used into the Fresnel formulas.

  7. Multi-scale evaporator architectures for geothermal binary power plants

    SciTech Connect

    Sabau, Adrian S; Nejad, Ali; Klett, James William; Bejan, Adrian

    2016-01-01

    In this paper, novel geometries of heat exchanger architectures are proposed for evaporators that are used in Organic Rankine Cycles. A multi-scale heat exchanger concept was developed by employing successive plenums at several length-scale levels. Flow passages contain features at both macro-scale and micro-scale, which are designed from Constructal Theory principles. Aside from pumping power and overall thermal resistance, several factors were considered in order to fully assess the performance of the new heat exchangers, such as weight of metal structures, surface area per unit volume, and total footprint. Component simulations based on laminar flow correlations for supercritical R134a were used to obtain performance indicators.

  8. A discriminant multi-scale histopathology descriptor using dictionary learning

    NASA Astrophysics Data System (ADS)

    Romo, David; García-Arteaga, Juan D.; Arbeláez, Pablo; Romero, Eduardo

    2014-03-01

    When examining a histological sample, an expert must not only identify structures at different scale and conceptual levels, i.e. cellular, tissular and organic, but also recognize and integrate the visual cues of specific pathologies and histological concepts such as "gland", "carcinoma" or "collagen". It is necessary then to code the texture and color so that the relevant information present at different scales is emphasized and preserved. In this article we propose a novel multi-scale image descriptor using dictionaries that learn and code discriminant visual elements associated with specific histological concepts. The dictionaries are built separately for each concept using sparse coding algorithms. The descriptor's discrimination capacity is evaluated using a naive strategy that assigns a particular image to the class best represented by a particular dictionary. Results show how, even using this very simple approach, average recall and precision measures of 0.81 and 0.86 were obtained for the challenging problem of classifying epidermis, eccrine glands, hair follicle and nodular carcinoma in basal skin carcinoma images.

  9. Multi-scale structured, superhydrophobic and wide-angle, antireflective coating in the near-infrared region.

    PubMed

    Camargo, Kelly C; Michels, Alexandre F; Rodembusch, Fabiano S; Horowitz, Flavio

    2012-05-21

    Superhydrophobic self-cleaning surfaces were produced with simultaneous wide-angle optical transmittance in the near-infrared region and antireflection properties from combination of multi-scale surface topology based on silica nanoparticles, index grading and interference.

  10. 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

  11. 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

  12. Fractional-order elastic models of cartilage: A multi-scale approach

    NASA Astrophysics Data System (ADS)

    Magin, Richard L.; Royston, Thomas J.

    2010-03-01

    The objective of this research is to develop new quantitative methods to describe the elastic properties (e.g., shear modulus, viscosity) of biological tissues such as cartilage. Cartilage is a connective tissue that provides the lining for most of the joints in the body. Tissue histology of cartilage reveals a multi-scale architecture that spans a wide range from individual collagen and proteoglycan molecules to families of twisted macromolecular fibers and fibrils, and finally to a network of cells and extracellular matrix that form layers in the connective tissue. The principal cells in cartilage are chondrocytes that function at the microscopic scale by creating nano-scale networks of proteins whose biomechanical properties are ultimately expressed at the macroscopic scale in the tissue's viscoelasticity. The challenge for the bioengineer is to develop multi-scale modeling tools that predict the three-dimensional macro-scale mechanical performance of cartilage from micro-scale models. Magnetic resonance imaging (MRI) and MR elastography (MRE) provide a basis for developing such models based on the nondestructive biomechanical assessment of cartilage in vitro and in vivo. This approach, for example, uses MRI to visualize developing proto-cartilage structure, MRE to characterize the shear modulus of such structures, and fractional calculus to describe the dynamic behavior. Such models can be extended using hysteresis modeling to account for the non-linear nature of the tissue. These techniques extend the existing computational methods to predict stiffness and strength, to assess short versus long term load response, and to measure static versus dynamic response to mechanical loads over a wide range of frequencies (50-1500 Hz). In the future, such methods can perhaps be used to help identify early changes in regenerative connective tissue at the microscopic scale and to enable more effective diagnostic monitoring of the onset of disease.

  13. 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.

  14. CitSci.org: Multi-Scale Citizen Science Support

    NASA Astrophysics Data System (ADS)

    Newman, G. J.; Crall, A.; Graham, J.; Laituri, M.

    2011-12-01

    Citizen science and community-based monitoring programs are increasing in number and breadth, generating volumes of scientific data. Many programs are ill-equipped to effectively manage these data. We examined the art and science of multi-scale citizen science support, focusing on issues of integration and flexibility that arise when programs span multiple spatial, temporal, and social scales across many domains. Our objectives were to: (1) review existing citizen science approaches and data management needs; (2) develop a cyber-infrastructure to support citizen science program needs; and (3) describe lessons learned. We find that approaches differ in scope, scale, and activities and that citizen science programs need best practices for data collection, standardization, integration and analysis. We built a multi-scale cyber-infrastructure support system for citizen science programs (www.citsci.org) and show that carefully designed systems can support individual program requirements while promoting interoperability necessary for cross-program meta-analyses. The system allows users with different levels of permission to themselves easily customize features and attributes they wish to collect, while adhering to a growing user-contributed, yet vetted, set of attributes necessary for cross-discipline comparisons and meta-analyses. Program evaluation integrated into the cyber-infrastructure will improve our ability to track effectiveness. We discuss the importance of standards for interoperability and the challenges associated with system maintenance and long-term support and conclude by offering a vision of the future of citizen science data management and cyber-infrastructure support.

  15. Multi-scale structures of turbulent magnetic reconnection

    SciTech Connect

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

    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 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.

  16. A multi-scale and ungridded representation of data products

    NASA Astrophysics Data System (ADS)

    Chin, T. M.; Armstrong, E. M.; Vazquez, J.

    2016-02-01

    Remote sensing data have irregular sampling patterns primarily due to sensor tracks. These data are typically interpolated to a regular grid for further use. "Gridding" is usually performed by relocating each data sample to its nearest grid-point or grid-box, often followed by an averaging procedure. A fundamental problem with such a practice is that the geolocation information is truncated, often distorting subgrid-scale features. Another issue is that a single grid resolution is often chosen to interpolate over some sparsely sampled regions at the expense of the information available over densely sampled regions. To address these issues, we introduce the multi-resolution variational analysis (MRVA) method, developed by modifying the multiresolution analysis (a loss-less signal decomposition based on orthonormal wavelets) for the irregularly sampled data. MRVA represents the interpolated fields using the wavelet coefficients at multiple scales. The multi-scale representation allows the interpolation scheme to be adaptable to spatially heterogeneous sampling patterns, since, unlike the Fourier basis, a wavelet basis possesses spatial specificity. Because the wavelet basis is a continuous function, an MRVA field can be sampled anywhere (gridless), facilitating validation of the interpolated field against another irregularly sampled data set. It also allows packaging of the interpolated field at any specified set of locations, enabling server-side subsetting that optimizes file size for efficient delivery. Due to losslessness, the wavelet coefficients also allow efficient storage, independent from the resolution of the output grid; the storage size depends only on the physical feature scale. The MRVA method has been applied to sea surface wind, temperature, and salinity data sets so far and is used for production of the Multi-scale Ultra-high Resolution (MUR) sea surface temperature data.

  17. Improved Detection System Description and New Method for Accurate Calibration of Micro-Channel Plate Based Instruments and Its Use in the Fast Plasma Investigation on NASA's Magnetospheric MultiScale Mission

    NASA Technical Reports Server (NTRS)

    Gliese, U.; Avanov, L. A.; Barrie, A. C.; Kujawski, J. T.; Mariano, A. J.; Tucker, C. J.; Chornay, D. J.; Cao, N. T.; Gershman, D. J.; Dorelli, J. C.; Zeuch, M. A.; Pollock, C. J.; Jacques, A. D.

    2015-01-01

    The Fast Plasma Investigation (FPI) on NASAs Magnetospheric MultiScale (MMS) mission employs 16 Dual Electron Spectrometers (DESs) and 16 Dual Ion Spectrometers (DISs) with 4 of each type on each of 4 spacecraft to enable fast (30 ms for electrons; 150 ms for ions) and spatially differentiated measurements of the full 3D particle velocity distributions. This approach presents a new and challenging aspect to the calibration and operation of these instruments on ground and in flight. The response uniformity, the reliability of their calibration and the approach to handling any temporal evolution of these calibrated characteristics all assume enhanced importance in this application, where we attempt to understand the meaning of particle distributions within the ion and electron diffusion regions of magnetically reconnecting plasmas. Traditionally, the micro-channel plate (MCP) based detection systems for electrostatic particle spectrometers have been calibrated using the plateau curve technique. In this, a fixed detection threshold is set. The detection system count rate is then measured as a function of MCP voltage to determine the MCP voltage that ensures the count rate has reached a constant value independent of further variation in the MCP voltage. This is achieved when most of the MCP pulse height distribution (PHD) is located at higher values (larger pulses) than the detection system discrimination threshold. This method is adequate in single-channel detection systems and in multi-channel detection systems with very low crosstalk between channels. However, in dense multi-channel systems, it can be inadequate. Furthermore, it fails to fully describe the behavior of the detection system and individually characterize each of its fundamental parameters. To improve this situation, we have developed a detailed phenomenological description of the detection system, its behavior and its signal, crosstalk and noise sources. Based on this, we have devised a new detection

  18. Hierarchical multi-atlas label fusion with multi-scale feature representation and label-specific patch partition.

    PubMed

    Wu, Guorong; Kim, Minjeong; Sanroma, Gerard; Wang, Qian; Munsell, Brent C; Shen, Dinggang

    2015-02-01

    Multi-atlas patch-based label fusion methods have been successfully used to improve segmentation accuracy in many important medical image analysis applications. In general, to achieve label fusion a single target image is first registered to several atlas images. After registration a label is assigned to each target point in the target image by determining the similarity between the underlying target image patch (centered at the target point) and the aligned image patch in each atlas image. To achieve the highest level of accuracy during the label fusion process it's critical for the chosen patch similarity measurement to accurately capture the tissue/shape appearance of the anatomical structure. One major limitation of existing state-of-the-art label fusion methods is that they often apply a fixed size image patch throughout the entire label fusion procedure. Doing so may severely affect the fidelity of the patch similarity measurement, which in turn may not adequately capture complex tissue appearance patterns expressed by the anatomical structure. To address this limitation, we advance state-of-the-art by adding three new label fusion contributions: First, each image patch is now characterized by a multi-scale feature representation that encodes both local and semi-local image information. Doing so will increase the accuracy of the patch-based similarity measurement. Second, to limit the possibility of the patch-based similarity measurement being wrongly guided by the presence of multiple anatomical structures in the same image patch, each atlas image patch is further partitioned into a set of label-specific partial image patches according to the existing labels. Since image information has now been semantically divided into different patterns, these new label-specific atlas patches make the label fusion process more specific and flexible. Lastly, in order to correct target points that are mislabeled during label fusion, a hierarchical approach is used to

  19. Hierarchical Multi-atlas Label Fusion with Multi-scale Feature Representation and Label-specific Patch Partition

    PubMed Central

    Wu, Guorong; Kim, Minjeong; Sanroma, Gerard; Wang, Qian; Munsell, Brent C.; Shen, Dinggang

    2014-01-01

    Multi-atlas patch-based label fusion methods have been successfully used to improve segmentation accuracy in many important medical image analysis applications. In general, to achieve label fusion a single target image is first registered to several atlas images, after registration a label is assigned to each target point in the target image by determining the similarity between the underlying target image patch (centered at the target point) and the aligned image patch in each atlas image. To achieve the highest level of accuracy during the label fusion process it’s critical the chosen patch similarity measurement accurately captures the tissue/shape appearance of the anatomical structure. One major limitation of existing state-of-the-art label fusion methods is that they often apply a fixed size image patch throughout the entire label fusion procedure. Doing so may severely affect the fidelity of the patch similarity measurement, which in turn may not adequately capture complex tissue appearance patterns expressed by the anatomical structure. To address this limitation, we advance state-of-the-art by adding three new label fusion contributions: First, each image patch now characterized by a multi-scale feature representation that encodes both local and semi-local image information. Doing so will increase the accuracy of the patch-based similarity measurement. Second, to limit the possibility of the patch-based similarity measurement being wrongly guided by the presence of multiple anatomical structures in the same image patch, each atlas image patch is further partitioned into a set of label-specific partial image patches according to the existing labels. Since image information has now been semantically divided into different patterns, these new label-specific atlas patches make the label fusion process more specific and flexible. Lastly, in order to correct target points that are mislabeled during label fusion, a hierarchically approach is used to improve the

  20. Tuneable resolution as a systems biology approach for multi-scale, multi-compartment computational models

    PubMed Central

    Kirschner, Denise E; Hunt, C Anthony; Marino, Simeone; Fallahi-Sichani, Mohammad; Linderman, Jennifer J

    2014-01-01

    The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work. WIREs Syst Biol Med 2014, 6:225–245. doi:10.1002/wsbm.1270 How to cite this article: WIREs Syst Biol Med 2014, 6:289–309. doi:10.1002/wsbm.1270 PMID:24810243

  1. Multi-scale photoacoustic remote sensing (PARS) (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Haji Reza, Parsin; Bell, Kevan; Shi, W.; Zemp, Roger J.

    2016-03-01

    We introduce a novel multi-scale photoacoustic remote sensing (PARS) imaging system. Our system can provide optical resolution details for superficial structures as well as acoustic resolution for deep-tissue imaging down to 5 cm, in a non-contact setting. PARS system does not require any contact with the sample or ultrasound coupling medium. The optical resolution PARS (OR-OARS) system uses optically focused pulsed excitation with optical detection of photoacoustic signatures using a long-coherence interrogation beam co-focused and co-scanned with the excitation spot. In the OR-PARS initial pressures are sampled right at their subsurface origin where acoustic pressures are largest. The Acoustic resolution PARS (AR-PARS) picks up the surface oscillation of the tissue caused by generated photoacoustic signal using a modified version of Michelson interferometry. By taking advantage of 4-meters polarization maintaining single-mode fiber and a green fiber laser we have generated a multi-wavelength source using stimulated Raman scattering. Remote functional imaging using this multi-wavelength excitation source and PARS detection mechanism has been demonstrated. The oxygen saturation estimations are shown for both phantom and in vivo studies. Images of blood vessel structures for an In vivo chicken embryo model is demonstrated. The Phantom studies indicates ~3µm and ~300µm lateral resolution for OR-PARS and AR-PARS respectively. To the best of our knowledge this is the first dual modality non-contact optical and acoustic resolution system used for in vivo imaging.

  2. A multi-scale sensing and diagnosis system combining accelerometers and gyroscopes for bridge health monitoring

    NASA Astrophysics Data System (ADS)

    Sung, S. H.; Park, J. W.; Nagayama, T.; Jung, H. J.

    2014-01-01

    This paper presents a multi-scale sensing and diagnosis system combining accelerometers and gyroscopes for bridge health monitoring. Since the damage metric estimated from acceleration measurement is insensitive to damage near the hinged support of a bridge, the damage diagnosis performance is limited near the support region. However, the performance can be improved by using two or more complementary data measured from multi-scale sensing. To more effectively diagnose the integrity of an overall bridge structure, angular velocity is complementary to acceleration, because of its high sensitivity to damage near the hinged support. This study proposes a multi-scale sensing and diagnosis system for bridge health monitoring based on a two-step approach. First, the damage diagnosis based on acceleration measurement is performed on the whole structure by using deflection estimated by modal flexibility. Next, the angular-velocity-based damage diagnosis is additionally carried out to localize missed damage by the acceleration-based approach near the hinged support. For validating the feasibility of the proposed system, a series of numerical and experimental studies on a simply supported beam model was performed. It was found that the multiple damages (one is near the center and another is near the support) can be successfully localized by the proposed multi-scale sensing and diagnosis system, while the damage near the support was missed by a conventional damage metric estimated from acceleration measurements.

  3. 3D Gabor wavelet based vessel filtering of photoacoustic images.

    PubMed

    Haq, Israr Ul; Nagoaka, Ryo; Makino, Takahiro; Tabata, Takuya; Saijo, Yoshifumi

    2016-08-01

    Filtering and segmentation of vasculature is an important issue in medical imaging. The visualization of vasculature is crucial for the early diagnosis and therapy in numerous medical applications. This paper investigates the use of Gabor wavelet to enhance the effect of vasculature while eliminating the noise due to size, sensitivity and aperture of the detector in 3D Optical Resolution Photoacoustic Microscopy (OR-PAM). A detailed multi-scale analysis of wavelet filtering and Hessian based method is analyzed for extracting vessels of different sizes since the blood vessels usually vary with in a range of radii. The proposed algorithm first enhances the vasculature in the image and then tubular structures are classified by eigenvalue decomposition of the local Hessian matrix at each voxel in the image. The algorithm is tested on non-invasive experiments, which shows appreciable results to enhance vasculature in photo-acoustic images.

  4. Strong, Multi-Scale Heterogeneity in Earth's Lowermost Mantle

    NASA Astrophysics Data System (ADS)

    Tkalčić, Hrvoje; Young, Mallory

    2014-05-01

    The ~300 km thick layer above the Earth's core mantle boundary remains largely an enigma and has proven to be far more than a simple dividing line; rather it is a complex region with a range of proposed phenomena such as thermal and compositional heterogeneity, partial melting and anisotropy. Characterizing the heterogeneity in the lowermost mantle will prove crucial to accurately understanding key geodynamical processes within our planet. Here we obtain compressional wave (P-wave) velocity images and uncertainty estimates for the lowermost mantle using old and newly collected travel time data sensitive to the lowermost mantle and core and collected by waveform cross-correlation. The images obtained by the inversion technique are void of explicit model parameterization and smoothing. To attest to the impressive capabilities of the transdimensional and hierarchical Bayesian inversion scheme, we design a comprehensive, all-embracing synthetic resolution test demonstrating the retrieval of velocity discontinuities, smooth velocity transitions, structures of varying scales and strengths. Subsequent spectral analyses reveal a power of heterogeneity three times larger than previous estimates and a multi-scale wavelength content in the P-wave velocity field of the lowermost mantle. The newly obtained P-wave tomographic images of the lowermost mantle are not dominated by harmonic degree 2 structure as is the case for tomographic images derived from S-wave data. Instead, the heterogeneity size is more uniformly distributed between about 500 and 6000 km. Inter alia, the resulting heterogeneity spectrum provides a bridge between the long-wavelength features of previous global models and the very short-scale dimensions of scatterers mapped in independent studies. Because the long scale features are less dominant in our model than in S-wave velocity maps, we cannot reasonably determine a correlation between them and the position of detected ultra-low velocity zones.

  5. Advanced computational workflow for the multi-scale modeling of the bone metabolic processes.

    PubMed

    Dao, Tien Tuan

    2016-09-16

    Multi-scale modeling of the musculoskeletal system plays an essential role in the deep understanding of complex mechanisms underlying the biological phenomena and processes such as bone metabolic processes. Current multi-scale models suffer from the isolation of sub-models at each anatomical scale. The objective of this present work was to develop a new fully integrated computational workflow for simulating bone metabolic processes at multi-scale levels. Organ-level model employs multi-body dynamics to estimate body boundary and loading conditions from body kinematics. Tissue-level model uses finite element method to estimate the tissue deformation and mechanical loading under body loading conditions. Finally, cell-level model includes bone remodeling mechanism through an agent-based simulation under tissue loading. A case study on the bone remodeling process located on the human jaw was performed and presented. The developed multi-scale model of the human jaw was validated using the literature-based data at each anatomical level. Simulation outcomes fall within the literature-based ranges of values for estimated muscle force, tissue loading and cell dynamics during bone remodeling process. This study opens perspectives for accurately simulating bone metabolic processes using a fully integrated computational workflow leading to a better understanding of the musculoskeletal system function from multiple length scales as well as to provide new informative data for clinical decision support and industrial applications.

  6. A novel visible and infrared image fusion algorithm based on detail enhancement

    NASA Astrophysics Data System (ADS)

    Wang, Bo

    2016-11-01

    In order to improve the characteristic information of the fused images, we propose a novel infrared and visible image fusion algorithm based on image detail enhancement in this paper, the bilateral filter and dynamic range partitioning (BF & DRP) are used to improve the original infrared image, and the multi-scale retinex transform (MRT) also is used to deal with image fusion. Firstly a method of bilateral filter and dynamic range partitioning (BF & DRP) was used to improve the details of the low SNR and low contrast original infrared image, by which the edges of targets were strengthened, the noises were suppressed, and the constrast of infrared image was enhanced. Secondly, and finally, the multi-scale retinex transform was used to improve the fusion of visible and infrared image, by combining the multi-scale transform and regional fusion where the adaptive low frequency and high frequency coefficient were considered, which effectively suppressed the noises and enhanced the details.. Experimental results proved the effectiveness of the proposed image fusion method. The salient color and texture feature of visible image was well preserved, the important details of infrared and visible image were highlighted. The results show that this algorithm is better than traditional image fusion method, such as wavelet transform, non-sampled contourlet transform, in in standard deviation, information entropy and Average gradient etc.. the algorithm of this paper is able to preserve the details of image, increase the amount of importance characteristic information, is advantageous to the visual performance and distinguishability of fused image for human observation.

  7. Multi-scale investigation of shrub encroachment in southern Africa

    NASA Astrophysics Data System (ADS)

    Aplin, Paul; Marston, Christopher; Wilkinson, David; Field, Richard; O'Regan, Hannah

    2016-04-01

    There is growing speculation that savannah environments throughout Africa have been subject to shrub encroachment in recent years, whereby grassland is lost to woody vegetation cover. Changes in the relative proportions of grassland and woodland are important in the context of conservation of savannah systems, with implications for faunal distributions, environmental management and tourism. Here, we focus on southern Kruger National Park, South Africa, and investigate whether or not shrub encroachment has occurred over the last decade and a half. We use a multi-scale approach, examining the complementarity of medium (e.g. Landsat TM and OLI) and fine (e.g. QuickBird and WorldView-2) spatial resolution satellite sensor imagery, supported by intensive field survey in 2002 and 2014. We employ semi-automated land cover classification, involving a hybrid unsupervised clustering approach with manual class grouping and checking, followed by change detection post-classification comparison analysis. The results show that shrub encroachment is indeed occurring, a finding evidenced through three fine resolution replicate images plus medium resolution imagery. The results also demonstrate the complementarity of medium and fine resolution imagery, though some thematic information must be sacrificed to maintain high medium resolution classification accuracy. Finally, the findings have broader implications for issues such as vegetation seasonality, spatial transferability and management practices.

  8. Multi-Scale Low-Entropy Method for Optimizing the Processing Parameters during Automated Fiber Placement.

    PubMed

    Han, Zhenyu; Sun, Shouzheng; Fu, Hongya; Fu, Yunzhong

    2017-09-03

    Automated fiber placement (AFP) process includes a variety of energy forms and multi-scale effects. This contribution proposes a novel multi-scale low-entropy method aiming at optimizing processing parameters in an AFP process, where multi-scale effect, energy consumption, energy utilization efficiency and mechanical properties of micro-system could be taken into account synthetically. Taking a carbon fiber/epoxy prepreg as an example, mechanical properties of macro-meso-scale are obtained by Finite Element Method (FEM). A multi-scale energy transfer model is then established to input the macroscopic results into the microscopic system as its boundary condition, which can communicate with different scales. Furthermore, microscopic characteristics, mainly micro-scale adsorption energy, diffusion coefficient entropy-enthalpy values, are calculated under different processing parameters based on molecular dynamics method. Low-entropy region is then obtained in terms of the interrelation among entropy-enthalpy values, microscopic mechanical properties (interface adsorbability and matrix fluidity) and processing parameters to guarantee better fluidity, stronger adsorption, lower energy consumption and higher energy quality collaboratively. Finally, nine groups of experiments are carried out to verify the validity of the simulation results. The results show that the low-entropy optimization method can reduce void content effectively, and further improve the mechanical properties of laminates.

  9. A novel analytical solution for gas diffusion in multi-scale fuel cell porous media

    NASA Astrophysics Data System (ADS)

    Xu, Peng; Qiu, Shuxia; Cai, Jianchao; Li, Cuihong; Liu, Haicheng

    2017-09-01

    Gas diffusion in multi-scale fuel cell porous media such as gas diffusion layer, microporous layer and catalyst layer affects the power performance of proton exchange membrane fuel cells. The effective gas diffusivity is one of the key parameters for gas diffusion in multi-scale fuel cell porous media, which has attracted broad interests from science and engineering. A new analytical model is presented and solved for gas diffusion in fuel cell porous media based on fractal geometry. Due to its multi-scale characteristics and existence of microscale and nanoscale pores in most fuel cell porous media, both molecular and Knudsen diffusion mechanisms are taken into account. An expression for the effective gas diffusivity of multi-scale porous media is derived, expressed in terms of bulk diffusion, pore structure as well as the Knudsen number. The proposed fractal model is validated by comparison with available experimental data and empirical correlations. The model shows that the effective gas diffusivity increases with increase of porosity and pore fractal dimension, while it decreases with increased tortuosity fractal dimension. It is believed that the current work may shed light on the gas diffusion mechanism in fuel cell porous media.

  10. Multi-scale forest landscape pattern characterization

    NASA Astrophysics Data System (ADS)

    Wang, Jialing

    The purpose of this dissertation is to examine several important issues in landscape pattern analysis, including the identification of important landscape metrics, the impact of the modifiable areal unit problem (MAUP) in landscape pattern analysis, the linkage between pattern and process, and the application of landscape pattern analysis. A theoretical framework of hierarchical patch dynamics paradigm and a technical framework of GIS and remote sensing integration are employed to address these questions. The Red Hills region of southwestern Georgia and northern Florida is chosen as the study area. Land use/cover (LULC) and longleaf pine distribution maps were generated through satellite image classification. Sub-watersheds were used as the main analysis units. Principal component analysis (PCA) was conducted on 43 sub-watersheds at three hierarchical LULC levels to identify important landscape metrics. At both landscape- and class-levels, the measurement of fragmentation was identified as the most important landscape dimension. Other dimensions and important metrics varied with different scales. Hexagons were used as an alternative zoning system to examine the MAUP impact in landscape pattern analysis. The results indicated that landscape pattern analyses at class level and at broader scales were more sensitive to MAUP than at landscape level and at finer scales. Local-scale pattern analysis based on moving window analysis greatly reduced the impact of MAUP at class level, but had little effects at landscape level. An examination of the relationship between landscape pattern variables and biophysical/socio-economic variables was undertaken by using statistical analysis. The biophysical variables of soil drainage and mean slope and the socio-economic variables of road density, population density, distance to Tallahassee, Florida, and plantation amount were found to be closely correlated to the landscape patterns in this region. However, a large amount of variation

  11. 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.

  12. Mineral image enhancement based on sequential combination of toggle and top-hat based contrast operator.

    PubMed

    Bai, Xiangzhi

    2013-01-01

    Enhancing mineral image especially making mineral image details clear is very useful for mineral analysis. To effectively enhance mineral image, an algorithm based on the toggle contrast operator and top-hat based contrast operator is proposed in this paper. Sequentially combining the toggle contrast operator and top-hat based contrast operator could be used to identify image features especially the image details. So, appropriately exacting the identified image features by the sequentially combined toggle and top-hat based contrast operator is important for mineral image enhancement, which is analyzed firstly in this paper. After that, the multi-scale extension of feature extraction is given and used to construct the final features for mineral image enhancement. By importing the final extracted image features into the original mineral image through contrast enlargement, the original mineral image is well enhanced and the mineral image details are very clear. Experimental results on different types of mineral images verified the effective performance of the proposed algorithm. Copyright © 2012 Elsevier Ltd. All rights reserved.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. Physics of Multi-scale Convection In The Earth's Mantle

    NASA Astrophysics Data System (ADS)

    Korenaga, J.; Jordan, T. H.

    We investigate the physics of multi-scale convection in the Earth's mantle, character- ized by the coexistence of large-scale mantle circulation associated plate tectonics and small-scale sublithospheric convection. Several basic scaling laws are derived, using a series of 2-D numerical modeling and 3-D linear stability analyses, for the following three distinct phases of sublithospheric convection: (1) onset of convection, (2) lay- ered convection in the upper mantle, and (3) breakdown of layered convection. First, the onset of convection with temperature-dependent viscosity is studied with 2-D con- vection models. A robust scaling law for onset time is derived by a nonlinear scaling analysis based on the concept of the differential Rayleigh number. Next, the planform of sublithospheric convection is studied by a 3-D linear stability analysis of longitu- dinal rolls in the presence of vertical shear. Finally, the temporal and spatial evolu- tion of sublithospheric convection is studied by 2-D whole-mantle convection models with temperature- and depth-dependent viscosity and an endothermic phase transition. Scaling laws for the breakdown of layered convection as well as the strength of con- vection are derived as a function of viscosity layering, the phase buoyancy parameter, and the thermal Rayleigh number. All of these scaling laws are combined to delineate possible dynamic regimes beneath evolving lithosphere.

  20. Multi-Scale Effects in the Strength of Ceramics.

    PubMed

    Cook, Robert F

    2015-10-01

    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.

  1. Spontaneous Neural Dynamics and Multi-scale Network Organization

    PubMed Central

    Foster, Brett L.; He, Biyu J.; Honey, Christopher J.; Jerbi, Karim; Maier, Alexander; Saalmann, Yuri B.

    2016-01-01

    Spontaneous neural activity has historically been viewed as task-irrelevant noise that should be controlled for via experimental design, and removed through data analysis. However, electrophysiology and functional MRI studies of spontaneous activity patterns, which have greatly increased in number over the past decade, have revealed a close correspondence between these intrinsic patterns and the structural network architecture of functional brain circuits. In particular, by analyzing the large-scale covariation of spontaneous hemodynamics, researchers are able to reliably identify functional networks in the human brain. Subsequent work has sought to identify the corresponding neural signatures via electrophysiological measurements, as this would elucidate the neural origin of spontaneous hemodynamics and would reveal the temporal dynamics of these processes across slower and faster timescales. Here we survey common approaches to quantifying spontaneous neural activity, reviewing their empirical success, and their correspondence with the findings of neuroimaging. We emphasize invasive electrophysiological measurements, which are amenable to amplitude- and phase-based analyses, and which can report variations in connectivity with high spatiotemporal precision. After summarizing key findings from the human brain, we survey work in animal models that display similar multi-scale properties. We highlight that, across many spatiotemporal scales, the covariance structure of spontaneous neural activity reflects structural properties of neural networks and dynamically tracks their functional repertoire. PMID:26903823

  2. Multi-Scale Modeling of Wave Attenuation by Vegetation

    NASA Astrophysics Data System (ADS)

    Chen, Q. J.; Zhu, L.; Chakrabarti, A.

    2016-02-01

    In the past decade, interest in wave attenuation by vegetation has increased considerably as coastal scientists and engineers search for sustainable solutions to mitigate the impacts of climate change and natural hazards. It is well known that vegetation in wetlands can effectively reduce the flow speed, modify turbulence structure, attenuate wave energy, and affect sediment dynamics. Restoring coastal wetlands and reducing flood risks require improved understanding and better predictive capability of wave and surge attenuation over inundated coastal landscapes with vegetation. The interactions of surface weaves and natural vegetation span over a large range of scales, from turbulence and eddies at the vegetation stem scale to wave generation in vast inundated wetlands of hundreds of square miles under hurricane conditions. The study is focused on a phase-averaged energy-based model and phase-resolving Euler and Navier-Stokes (N-S) solvers with different representations of submerged vegetation. We will present recent advances in multi-scale modeling of wave attenuation by wetland vegetation. Numerical modeling results ranging from vegetation-resolved large eddy simulation under idealized conditions to incorporating vegetation-induced drag forces into conservation laws of momentum and energy for engineering applications will be shown. Effects of vegetation flexibility, turbulence closure, and various wave theories on the prediction of wave attenuation and the choice of vegetation drag coefficients will be discussed.

  3. An Optimized PatchMatch for multi-scale and multi-feature label fusion.

    PubMed

    Giraud, Rémi; Ta, Vinh-Thong; Papadakis, Nicolas; Manjón, José V; Collins, D Louis; Coupé, Pierrick

    2016-01-01

    Automatic segmentation methods are important tools for quantitative analysis of Magnetic Resonance Images (MRI). Recently, patch-based label fusion approaches have demonstrated state-of-the-art segmentation accuracy. In this paper, we introduce a new patch-based label fusion framework to perform segmentation of anatomical structures. The proposed approach uses an Optimized PAtchMatch Label fusion (OPAL) strategy that drastically reduces the computation time required for the search of similar patches. The reduced computation time of OPAL opens the way for new strategies and facilitates processing on large databases. In this paper, we investigate new perspectives offered by OPAL, by introducing a new multi-scale and multi-feature framework. During our validation on hippocampus segmentation we use two datasets: young adults in the ICBM cohort and elderly adults in the EADC-ADNI dataset. For both, OPAL is compared to state-of-the-art methods. Results show that OPAL obtained the highest median Dice coefficient (89.9% for ICBM and 90.1% for EADC-ADNI). Moreover, in both cases, OPAL produced a segmentation accuracy similar to inter-expert variability. On the EADC-ADNI dataset, we compare the hippocampal volumes obtained by manual and automatic segmentation. The volumes appear to be highly correlated that enables to perform more accurate separation of pathological populations.

  4. Fusion of Multi-View and Multi-Scale Aerial Imagery for Real-Time Situation Awareness Applications

    NASA Astrophysics Data System (ADS)

    Zhuo, X.; Kurz, F.; Reinartz, P.

    2015-08-01

    Manned aircraft has long been used for capturing large-scale aerial images, yet the high costs and weather dependence restrict its availability in emergency situations. In recent years, MAV (Micro Aerial Vehicle) emerged as a novel modality for aerial image acquisition. Its maneuverability and flexibility enable a rapid awareness of the scene of interest. Since these two platforms deliver scene information from different scale and different view, it makes sense to fuse these two types of complimentary imagery to achieve a quick, accurate and detailed description of the scene, which is the main concern of real-time situation awareness. This paper proposes a method to fuse multi-view and multi-scale aerial imagery by establishing a common reference frame. In particular, common features among MAV images and geo-referenced airplane images can be extracted by a scale invariant feature detector like SIFT. From the tie point of geo-referenced images we derive the coordinate of corresponding ground points, which are then utilized as ground control points in global bundle adjustment of MAV images. In this way, the MAV block is aligned to the reference frame. Experiment results show that this method can achieve fully automatic geo-referencing of MAV images even if GPS/IMU acquisition has dropouts, and the orientation accuracy is improved compared to the GPS/IMU based georeferencing. The concept for a subsequent 3D classification method is also described in this paper.

  5. Note: design and construction of a multi-scale, high-resolution, tube-generated x-ray computed-tomography system for three-dimensional (3D) imaging.

    PubMed

    Mertens, J C E; Williams, J J; Chawla, Nikhilesh

    2014-01-01

    The design and construction of a high resolution modular x-ray computed tomography (XCT) system is described. The approach for meeting a specified set of performance goals tailored toward experimental versatility is highlighted. The instrument is unique in its detector and x-ray source configuration, both of which enable elevated optimization of spatial and temporal resolution. The process for component selection is provided. The selected components are specified, the custom component design discussed, and the integration of both into a fully functional XCT instrument is outlined. The novelty of this design is a new lab-scale detector and imaging optimization through x-ray source and detector modularity.

  6. Note: Design and construction of a multi-scale, high-resolution, tube-generated X-Ray computed-tomography system for three-dimensional (3D) imaging

    SciTech Connect

    Mertens, J. C. E.; Williams, J. J.; Chawla, Nikhilesh

    2014-01-15

    The design and construction of a high resolution modular x-ray computed tomography (XCT) system is described. The approach for meeting a specified set of performance goals tailored toward experimental versatility is highlighted. The instrument is unique in its detector and x-ray source configuration, both of which enable elevated optimization of spatial and temporal resolution. The process for component selection is provided. The selected components are specified, the custom component design discussed, and the integration of both into a fully functional XCT instrument is outlined. The novelty of this design is a new lab-scale detector and imaging optimization through x-ray source and detector modularity.

  7. Bio-inspired homogeneous multi-scale place recognition.

    PubMed

    Chen, Zetao; Lowry, Stephanie; Jacobson, Adam; Hasselmo, Michael E; Milford, Michael

    2015-12-01

    Robotic mapping and localization systems typically operate at either one fixed spatial scale, or over two, combining a local metric map and a global topological map. In contrast, recent high profile discoveries in neuroscience have indicated that animals such as rodents navigate the world using multiple parallel maps, with each map encoding the world at a specific spatial scale. While a number of theoretical-only investigations have hypothesized several possible benefits of such a multi-scale mapping system, no one has comprehensively investigated the potential mapping and place recognition performance benefits for navigating robots in large real world environments, especially using more than two homogeneous map scales. In this paper we present a biologically-inspired multi-scale mapping system mimicking the rodent multi-scale map. Unlike hybrid metric-topological multi-scale robot mapping systems, this new system is homogeneous, distinguishable only by scale, like rodent neural maps. We present methods for training each network to learn and recognize places at a specific spatial scale, and techniques for combining the output from each of these parallel networks. This approach differs from traditional probabilistic robotic methods, where place recognition spatial specificity is passively driven by models of sensor uncertainty. Instead we intentionally create parallel learning systems that learn associations between sensory input and the environment at different spatial scales. We also conduct a systematic series of experiments and parameter studies that determine the effect on performance of using different neural map scaling ratios and different numbers of discrete map scales. The results demonstrate that a multi-scale approach universally improves place recognition performance and is capable of producing better than state of the art performance compared to existing robotic navigation algorithms. We analyze the results and discuss the implications with respect to

  8. Region of interest extraction based on saliency detection and contrast analysis for remote sensing images

    NASA Astrophysics Data System (ADS)

    Lv, Jing; Zhang, Libao; Wang, Shuang

    2016-10-01

    Region of Interest (ROI) extraction is an important component in remote sensing images processing, which is useful for further practical applications such as image compression, image fusion, image segmentation and image registration. Traditional ROI extraction methods are usually prior knowledge-based and depend on a global searching solution which are time consuming and computational complex. Saliency detection which is widely used for ROI extraction from natural scene images in these years can effectively solve the problem of high computation complexity in ROI extraction for remote sensing images as well as retain accuracy. In this paper, a new computational model is proposed to improve the accuracy of ROI extraction in remote sensing images. Considering the characteristics of remote sensing images, we first use lifting wavelet transform based on adaptive direction evaluation (ADE) to obtain multi-scale orientation contrast feature map (MF). Secondly, the features of color are exploited using the information content analysis to provide a color information map (CIM). Thirdly, feature fusion is used to integrate multi-scale orientation contrast features and color information for generating a saliency map. Finally, an adaptive threshold segmentation algorithm is employed to obtain the ROI. Compared with existing models, our method can not only effectively extract detail of the ROIs, but also effectively remove mistaken detection of the inner parts of the ROIs.

  9. Flexible fabrication of multi-scale integrated 3D periodic nanostructures with phase mask

    NASA Astrophysics Data System (ADS)

    Yuan, Liang Leon

    Top-down fabrication of artificial nanostructures, especially three-dimensional (3D) periodic nanostructures, that forms uniform and defect-free structures over large area with the advantages of high throughput and rapid processing and in a manner that can further monolithically integrate into multi-scale and multi-functional devices is long-desired but remains a considerable challenge. This thesis study advances diffractive optical element (DOE) based 3D laser holographic nanofabrication of 3D periodic nanostructures and develops new kinds of DOEs for advanced diffracted-beam control during the fabrication. Phase masks, as one particular kind of DOE, are a promising direction for simple and rapid fabrication of 3D periodic nanostructures by means of Fresnel diffraction interference lithography. When incident with a coherent beam of light, a suitable phase mask (e.g. with 2D nano-grating) can create multiple diffraction orders that are inherently phase-locked and overlap to form a 3D light interference pattern in the proximity of the DOE. This light pattern is typically recorded in photosensitive materials including photoresist to develop into 3D photonic crystal nanostructure templates. Two kinds of advanced phase masks were developed that enable delicate phase control of multiple diffraction beams. The first exploits femtosecond laser direct writing inside fused silica to assemble multiple (up to nine) orthogonally crossed (2D) grating layers, spaced on Talbot planes to overcome the inherent weak diffraction efficiency otherwise found in low-contrast volume gratings. A systematic offsetting of orthogonal grating layers to establish phase offsets over 0 to pi/2 range provided precise means for controlling the 3D photonic crystal structure symmetry between body centered tetragonal (BCT) and woodpile-like tetragonal (wTTR). The second phase mask consisted of two-layered nanogratings with small sub-wavelength grating periods and phase offset control. That was

  10. Pore-scale capillary pressure analysis using multi-scale X-ray micromotography

    NASA Astrophysics Data System (ADS)

    Garing, Charlotte; de Chalendar, Jacques A.; Voltolini, Marco; Ajo-Franklin, Jonathan B.; Benson, Sally M.

    2017-06-01

    A multi-scale synchrotron-based X-ray microtomographic dataset of residually trapped air after gravity-driven brine imbibition was acquired for three samples with differing pore topologies and morphologies; image volumes were reconstructed with voxel sizes from 4.44 μm down to 0.64 μm. Capillary pressure distributions among the population of trapped ganglia were investigated by calculating interfacial curvature in order to assess the potential for remobilization of residually-trapped non-wetting ganglia due to differences in capillary pressure presented by neighbor ganglia. For each sample, sintered glass beads, Boise sandstone and Fontainebleau sandstone, sub-volumes with different voxel sizes were analyzed to quantify air/brine interfaces and interfacial curvatures and investigate the effect of image resolution on both fluid phase identification and curvature estimates. Results show that the method developed for interfacial curvature estimation leads to reliable capillary pressure estimates for gas ganglia. Higher resolution images increase confidence in curvature calculations, especially for the sandstone samples that display smaller gas-brine interfaces which are then represented by a higher number of voxels when imaged with a micron or sub-micron voxels size. The analysis of sub-volumes from the Boise and Fontainebleau dataset highlights the presence of a residually-trapped gas phase consisting of ganglia located in one or few pores and presenting significantly different capillary pressures, especially in the case of Fontainebleau sandstone. As a result, Ostwald ripening could occur, leading to gas transfer from ganglia with higher capillary pressure to surrounding ganglia with lower capillary pressures. More generally, at the pore-scale, most gas ganglia do present similar capillary pressures and Ostwald ripening would then not represent a major mechanism for residually-trapped gas transfer and remobilization.

  11. Multi-scale Modeling of Plasticity in Tantalum.

    SciTech Connect

    Lim, Hojun; Battaile, Corbett Chandler.; Carroll, Jay; Buchheit, Thomas E.; Boyce, Brad; Weinberger, Christopher

    2015-12-01

    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 describing 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, direct

  12. Multi-scale modeling of chemotactic interactions

    NASA Astrophysics Data System (ADS)

    Grima, Ramon

    Biological complexity emerges from the synthesis of biochemical, chemical and physical phenomena. In recent years there has been an intense effort in modeling various cellular systems of interest to understand how the observed complexity emerges from the underlying mechanisms. Most modeling approaches are based on a population description of the cells: these methods, though usually amenable to calculation, are only valid in the limit of large numbers of interacting cells. Many systems of interest involve the interaction of a relatively small number of cells; even biological systems composed of thousands of cells have spatially extended regions over which the number density of cells is small. For the latter cases, population descriptions are not valid and individual based models become a necessity. Such models, usually cellular automaton models, have been numerically studied in recent years; however, these models are not usually amenable to analytic calculation. The work presented in this thesis seeks to fulfill a gap in modeling approaches to the understanding of biocomplexity by constructing an individual based model on which analysis is possible, through the methods of statistical physics and the theory of stochastic processes. This model will be used to study the differences between individual based and population based models and the range of applicability of the latter. For the sake of comparison of the two, new efficient computational algorithms are devised for the simulation of both types of models. We finally complete our multiscale study of modeling by investigating the robustness of individual based models; this meaning a comparison of the results of different microscopic descriptions modeling the same underlying phenomena.

  13. Multi-scale and Multi-modal Analysis of Metamorphic Rocks Coupling Fluorescence and TXM Techniques

    NASA Astrophysics Data System (ADS)

    De Andrade, V. J. D.; Gursoy, D.; Wojcik, M.; DeCarlo, F.; Ganne, J.; Dubacq, B.

    2014-12-01

    Rocks are commonly polycrystalline systems presenting multi-scale chemical and structural heterogeneities inherited from crystallization processes or successive metamorphic events. Through different applications on metamorphic rocks involving fluorescence microprobes and full-field spectroscopy, one will illustrate how spatially resolved analytical techniques allow rock compositional variations to be related to large-scale geodynamic processes. Those examples also stress the importance of multi-modality instruments with zoom-in capability to study samples from mm to several μm large fields of view, with micrometer down to sub-100 nanometer spatial resolutions. In this perspective, imaging capabilities offered by the new ultra-bright diffraction limited synchrotron sources will be described based on experimental data. At last, the new hard X-ray Transmission X-ray Microscope (TXM) at Sector 32 of the APS at Argonne National Laboratory, performing nano computed tomography with in situ capabilities will be presented. The instrument benefit from several R&D key activities like the fabrication of new zone plates in the framework of the Multi-Bend Achromat Lattice (MBA) upgrade at APS, or the development of powerful tomography reconstruction algorithms able to operate with a limited number of projections.

  14. Three dimensional data-driven multi scale atomic representation of optical coherence tomography.

    PubMed

    Kafieh, Raheleh; Rabbani, Hossein; Selesnick, Ivan

    2015-05-01

    In this paper, we discuss about applications of different methods for decomposing a signal over elementary waveforms chosen in a family called a dictionary (atomic representations) in optical coherence tomography (OCT). If the representation is learned from the data, a nonparametric dictionary is defined with three fundamental properties of being data-driven, applicability on 3D, and working in multi-scale, which make it appropriate for processing of OCT images. We discuss about application of such representations including complex wavelet based K-SVD, and diffusion wavelets on OCT data. We introduce complex wavelet based K-SVD to take advantage of adaptability in dictionary learning methods to improve the performance of simple dual tree complex wavelets in speckle reduction of OCT datasets in 2D and 3D. The algorithm is evaluated on 144 randomly selected slices from twelve 3D OCTs taken by Topcon 3D OCT-1000 and Cirrus Zeiss Meditec. Improvement of contrast to noise ratio (CNR) (from 0.9 to 11.91 and from 3.09 to 88.9, respectively) is achieved. Furthermore, two approaches are proposed for image segmentation using diffusion. The first method is designing a competition between extended basis functions at each level and the second approach is defining a new distance for each level and clustering based on such distances. A combined algorithm, based on these two methods is then proposed for segmentation of retinal OCTs, which is able to localize 12 boundaries with unsigned border positioning error of 9.22 ±3.05 μm, on a test set of 20 slices selected from 13 3D OCTs.

  15. Scattering from Multi-Scale Surface.

    DTIC Science & Technology

    1984-02-01

    based on type II surfaces are gross oversimplifications. Following the work of Mandelbrot [14] one class of such scatterers have become known as...392 (1975) [12] Ohtsubo, J., Asakura, T., Opt. Comm. 25, 315 (1978) [131 Chandley, P. J., Escamilla, H. M., Opt. Comm. 29, 151 (1979) [14] Mandelbrot

  16. Automatic Craniomaxillofacial Landmark Digitization via Segmentation-guided Partially-joint Regression Forest Model and Multi-scale Statistical Features

    PubMed Central

    Zhang, Jun; Gao, Yaozong; Wang, Li; Tang, Zhen; Xia, James J.; Shen, Dinggang

    2016-01-01

    Objective The goal of this paper is to automatically digitize craniomaxillofacial (CMF) landmarks efficiently and accurately from cone-beam computed tomography (CBCT) images, by addressing the challenge caused by large morphological variations across patients and image artifacts of CBCT images. Methods We propose a Segmentation-guided Partially-joint Regression Forest (S-PRF) model to automatically digitize CMF landmarks. In this model, a regression voting strategy is first adopted to localize each landmark by aggregating evidences from context locations, thus potentially relieving the problem caused by image artifacts near the landmark. Second, CBCT image segmentation is utilized to remove uninformative voxels caused by morphological variations across patients. Third, a partially-joint model is further proposed to separately localize landmarks based on the coherence of landmark positions to improve the digitization reliability. In addition, we propose a fast vector quantization (VQ) method to extract high-level multi-scale statistical features to describe a voxel's appearance, which has low dimensionality, high efficiency, and is also invariant to the local inhomogeneity caused by artifacts. Results Mean digitization errors for 15 landmarks, in comparison to the ground truth, are all less than 2mm. Conclusion Our model has addressed challenges of both inter-patient morphological variations and imaging artifacts. Experiments on a CBCT dataset show that our approach achieves clinically acceptable accuracy for landmark digitalization. Significance Our automatic landmark digitization method can be used clinically to reduce the labor cost and also improve digitalization consistency. PMID:26625402

  17. Multi-Scale Initial Conditions For Cosmological Simulations

    SciTech Connect

    Hahn, Oliver; Abel, Tom; /KIPAC, Menlo Park /ZAH, Heidelberg /HITS, Heidelberg

    2011-11-04

    We discuss a new algorithm to generate multi-scale initial conditions with multiple levels of refinements for cosmological 'zoom-in' simulations. The method 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). The new algorithm achieves rms relative errors of the order of 10{sup -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. An optional hybrid multi-grid and Fast Fourier Transform (FFT) based scheme is introduced which has identical Fourier-space behaviour as traditional approaches. Using a suite of re-simulations of a galaxy cluster halo our real-space-based approach is found to reproduce correlation functions, density profiles, key halo properties and subhalo abundances with per cent level accuracy. Finally, we generalize our approach for two-component baryon and dark-matter simulations and demonstrate that the power spectrum evolution is in excellent agreement with linear perturbation theory. For initial baryon density fields, it is suggested to use the local Lagrangian approximation in order to generate a density field for mesh-based codes that is consistent with the Lagrangian perturbation theory instead of the current practice of using the Eulerian linearly scaled densities.

  18. Multi-scale initial conditions for cosmological simulations

    NASA Astrophysics Data System (ADS)

    Hahn, Oliver; Abel, Tom

    2011-08-01

    We discuss a new algorithm to generate multi-scale initial conditions with multiple levels of refinements for cosmological 'zoom-in' simulations. The method 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). The new algorithm 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. An optional hybrid multi-grid and Fast Fourier Transform (FFT) based scheme is introduced which has identical Fourier-space behaviour as traditional approaches. Using a suite of re-simulations of a galaxy cluster halo our real-space-based approach is found to reproduce correlation functions, density profiles, key halo properties and subhalo abundances with per cent level accuracy. Finally, we generalize our approach for two-component baryon and dark-matter simulations and demonstrate that the power spectrum evolution is in excellent agreement with linear perturbation theory. For initial baryon density fields, it is suggested to use the local Lagrangian approximation in order to generate a density field for mesh-based codes that is consistent with the Lagrangian perturbation theory instead of the current practice of using the Eulerian linearly scaled densities.

  19. Multi-Scale Rotation-Invariant Convolutional Neural Networks for Lung Texture Classification.

    PubMed

    Wang, Qiangchang; Zheng, Yuanjie; Yang, Gongping; Jin, Weidong; Chen, Xinjian; Yin, Yilong

    2017-03-21

    We propose a new Multi-scale Rotation-invariant Convolutional Neural Network (MRCNN) model for classifying various lung tissue types on high-resolution computed tomography (HRCT). MRCNN employs Gabor-local binary pattern (Gabor-LBP) which introduces a good property in image analysis - invariance to image scales and rotations. In addition, we offer an approach to deal with the problems caused by imbalanced number of samples between different classes in most of the existing works, accomplished by changing the overlapping size between the adjacent patches. Experimental results on a public Interstitial Lung Disease (ILD) database show a superior performance of the proposed method to state-of-the-art.

  20. Wavelet-based zerotree coding of aerospace images

    NASA Astrophysics Data System (ADS)

    Franques, Victoria T.; Jain, Vijay K.

    1996-06-01

    This paper presents a wavelet based image coding method achieving high levels of compression. A multi-resolution subband decomposition system is constructed using Quadrature Mirror Filters. Symmetric extension and windowing of the multi-scaled subbands are incorporated to minimize the boundary effects. Next, the Embedded Zerotree Wavelet coding algorithm is used for data compression method. Elimination of the isolated zero symbol, for certain subbands, leads to an improved EZW algorithm. Further compression is obtained with an adaptive arithmetic coder. We achieve a PSNR of 26.91 dB at a bit rate of 0.018, 35.59 dB at a bit rate of 0.149, and 43.05 dB at 0.892 bits/pixel for the aerospace image, Refuel.

  1. Exploring with simulations the transport properties of multi-scale porous materials

    NASA Astrophysics Data System (ADS)

    Hyväluoma, Jari; Mattila, Keijo; Puurtinen, Tuomas; Timonen, Jussi

    2015-04-01

    The internal structure of many natural porous materials such as soils and carbonate rocks involves multiple length scales. This severely hinders the research relating structure and transport properties: typically laboratory experiments cannot distinguish contributions from individual scales while computer simulations cannot capture multiple scales due to limited computational resources. 3D imaging and image-based fluid flow simulations are increasingly used for studying the pore-scale transport processes. Combining imaging with pore-scale flow simulation techniques, e.g. the lattice Boltzmann method, provides direct means to quantify pore-scale transport processes. However, pore-scale computer simulations have not really been able to capture multiple scales due to the limited size of the simulation system. We show here that the current computational resources and software techniques already allow transport simulations in domains beyond the realms of current imaging techniques, and, more importantly, enable numerical experiments in multi-scale porous materials. We were able to simulate single-phase fluid flow with the lattice Boltzmann method in a synthetic x-ray-tomography image taken from the set of world's largest 3D images of a porous material [1]. The used image has 163843 image voxels and porosity of 0.134 (i.e., 5.9 - 1011 pore voxels) and it represents the microstructure of Fontainebleau sandstone. While the modelled sandstone image is rather homogeneous and therefore does not really represent a multiscale porous material, from a computational point of view it serves the purpose of demonstrating the power of contemporary software and hardware techniques. The simulation was executed at the Edinburgh Parallel Computing Centre on the ARCHER supercomputer ranked number 25 among all supercomputers. ARCHER has 3008 computing nodes each of which has two 12-core Ivy Bridge 2.7 GHz CPUs and 64 GB of memory providing 1.67 Petaflops of theoretical peak performance. The

  2. Infrared and visible image fusion based on visual saliency map and weighted least square optimization

    NASA Astrophysics Data System (ADS)

    Ma, Jinlei; Zhou, Zhiqiang; Wang, Bo; Zong, Hua

    2017-05-01

    The goal of infrared (IR) and visible image fusion is to produce a more informative image for human observation or some other computer vision tasks. In this paper, we propose a novel multi-scale fusion method based on visual saliency map (VSM) and weighted least square (WLS) optimization, aiming to overcome some common deficiencies of conventional methods. Firstly, we introduce a multi-scale decomposition (MSD) using the rolling guidance filter (RGF) and Gaussian filter to decompose input images into base and detail layers. Compared with conventional MSDs, this MSD can achieve the unique property of preserving the information of specific scales and reducing halos near edges. Secondly, we argue that the base layers obtained by most MSDs would contain a certain amount of residual low-frequency information, which is important for controlling the contrast and overall visual appearance of the fused image, and the conventional ;averaging; fusion scheme is unable to achieve desired effects. To address this problem, an improved VSM-based technique is proposed to fuse the base layers. Lastly, a novel WLS optimization scheme is proposed to fuse the detail layers. This optimization aims to transfer more visual details and less irrelevant IR details or noise into the fused image. As a result, the fused image details would appear more naturally and be suitable for human visual perception. Experimental results demonstrate that our method can achieve a superior performance compared with other fusion methods in both subjective and objective assessments.

  3. Improved Image Fusion Method Based on NSCT and Accelerated NMF

    PubMed Central

    Wang, Juan; Lai, Siyu; Li, Mingdong

    2012-01-01

    In order to improve algorithm efficiency and performance, a technique for image fusion based on the Non-subsampled Contourlet Transform (NSCT) domain and an Accelerated Non-negative Matrix Factorization (ANMF)-based algorithm is proposed in this paper. Firstly, the registered source images are decomposed in multi-scale and multi-direction using the NSCT method. Then, the ANMF algorithm is executed on low-frequency sub-images to get the low-pass coefficients. The low frequency fused image can be generated faster in that the update rules for W and H are optimized and less iterations are needed. In addition, the Neighborhood Homogeneous Measurement (NHM) rule is performed on the high-frequency part to achieve the band-pass coefficients. Finally, the ultimate fused image is obtained by integrating all sub-images with the inverse NSCT. The simulated experiments prove that our method indeed promotes performance when compared to PCA, NSCT-based, NMF-based and weighted NMF-based algorithms. PMID:22778618

  4. Improved image fusion method based on NSCT and accelerated NMF.

    PubMed

    Wang, Juan; Lai, Siyu; Li, Mingdong

    2012-01-01

    In order to improve algorithm efficiency and performance, a technique for image fusion based on the Non-subsampled Contourlet Transform (NSCT) domain and an Accelerated Non-negative Matrix Factorization (ANMF)-based algorithm is proposed in this paper. Firstly, the registered source images are decomposed in multi-scale and multi-direction using the NSCT method. Then, the ANMF algorithm is executed on low-frequency sub-images to get the low-pass coefficients. The low frequency fused image can be generated faster in that the update rules for W and H are optimized and less iterations are needed. In addition, the Neighborhood Homogeneous Measurement (NHM) rule is performed on the high-frequency part to achieve the band-pass coefficients. Finally, the ultimate fused image is obtained by integrating all sub-images with the inverse NSCT. The simulated experiments prove that our method indeed promotes performance when compared to PCA, NSCT-based, NMF-based and weighted NMF-based algorithms.

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

    SciTech Connect

    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 blood 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.

  6. 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.

  7. On unified modeling, theory, and method for solving multi-scale global optimization problems

    NASA Astrophysics Data System (ADS)

    Gao, David Yang

    2016-10-01

    A unified model is proposed for general optimization problems in multi-scale complex systems. Based on this model and necessary assumptions in physics, the canonical duality theory is presented in a precise way to include traditional duality theories and popular methods as special applications. Two conjectures on NP-hardness are proposed, which should play important roles for correctly understanding and efficiently solving challenging real-world problems. Applications are illustrated for both nonconvex continuous optimization and mixed integer nonlinear programming.

  8. Blood Flow: Multi-scale Modeling and Visualization

    SciTech Connect

    2010-01-01

    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 developing methods for multi-scale computations, techniques for multi-scale visualizations must be designed. This animation presents early results of joint efforts of teams from Brown University and Argonne National Laboratory to develop a multi-scale visualization methodology. It illustrates a flow of healthy (red) and diseased (blue) blood cells with a Dissipative Particle Dynamics (DPD) method. Each blood cell is represented by a mesh made of 500 DPD-particles, and small spheres show a sub-set of the DPD particles representing the blood plasma, while instantaneous streamlines and slices represent the ensemble average velocity. Credits: Science: Leopold Grinberg and George Karniadakis, Brown University Visualization: Joseph A. Insley and Michael E. Papka, Argonne National Laboratory This research used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under contract DE-AC02-06CH11357. This research was supported in part by the National Science Foundation through the PetaApps program and used TeraGrid resources provided by National Institute for Computational Sciences.

  9. Efficient, Multi-Scale Designs Take Flight

    NASA Technical Reports Server (NTRS)

    2003-01-01

    Engineers can solve aerospace design problems faster and more efficiently with a versatile software product that performs automated structural analysis and sizing optimization. Collier Research Corporation's HyperSizer Structural Sizing Software is a design, analysis, and documentation tool that increases productivity and standardization for a design team. Based on established aerospace structural methods for strength, stability, and stiffness, HyperSizer can be used all the way from the conceptual design to in service support. The software originated from NASA s efforts to automate its capability to perform aircraft strength analyses, structural sizing, and weight prediction and reduction. With a strategy to combine finite element analysis with an automated design procedure, NASA s Langley Research Center led the development of a software code known as ST-SIZE from 1988 to 1995. Collier Research employees were principal developers of the code along with Langley researchers. The code evolved into one that could analyze the strength and stability of stiffened panels constructed of any material, including light-weight, fiber-reinforced composites.

  10. Multi-scale Quantitative Precipitation Forecasting Using ...

    EPA Pesticide Factsheets

    Global sea surface temperature (SST) anomalies can affect terrestrial precipitation via ocean-atmosphere interaction known as climate teleconnection. Non-stationary and non-linear characteristics of the ocean-atmosphere system make the identification of the teleconnection signals difficult to be detected at a local scale as it could cause large uncertainties when using linear correlation analysis only. This paper explores the relationship between global SST and terrestrial precipitation with respect to long-term non-stationary teleconnection signals during 1981-2010 over three regions in North America and one in Central America. Empirical mode decomposition as well as wavelet analysis is utilized to extract the intrinsic trend and the dominant oscillation of the SST and precipitation time series in sequence. After finding possible associations between the dominant oscillation of seasonal precipitation and global SST through lagged correlation analysis, the statistically significant SST regions are extracted based on the correlation coefficient. With these characterized associations, individual contribution of these SST forcing regions linked to the related precipitation responses are further quantified through nonlinear modeling with the aid of extreme learning machine. Results indicate that the non-leading SST regions also contribute a salient portion to the terrestrial precipitation variability compared to some known leading SST regions. In some cases, these

  11. 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.

  12. Imaging-based observational databases for clinical problem solving: the role of informatics

    PubMed Central

    Bui, Alex A T; Hsu, William; Arnold, Corey; El-Saden, Suzie; Aberle, Denise R; Taira, Ricky K

    2013-01-01

    Imaging has become a prevalent tool in the diagnosis and treatment of many diseases, providing a unique in vivo, multi-scale view of anatomic and physiologic processes. With the increased use of imaging and its progressive technical advances, the role of imaging informatics is now evolving—from one of managing images, to one of integrating the full scope of clinical information needed to contextualize and link observations across phenotypic and genotypic scales. Several challenges exist for imaging informatics, including the need for methods to transform clinical imaging studies and associated data into structured information that can be organized and analyzed. We examine some of these challenges in establishing imaging-based observational databases that can support the creation of comprehensive disease models. The development of these databases and ensuing models can aid in medical decision making and knowledge discovery and ultimately, transform the use of imaging to support individually-tailored patient care. PMID:23775172

  13. Modeling of Multi-Scale Channeling Phenomena in Porous Flow

    NASA Astrophysics Data System (ADS)

    Räss, Ludovic; Omlin, Samuel; Yarushina, Viktoriya; Simon, Nina; Podladchikov, Yuri

    2015-04-01

    Predictive modeling of fluid percolation through tight porous rocks is critical to evaluate environmental risks associated with waste storage and reservoir operations. To understand the evolution of two-phase mixtures of fluid and solid it is insufficient to only combine single-phase fluid flow methods and solid mechanics. A proper coupling of these two different multi-scales physical processes is required to describe the complex evolution of permeability and porosity in space and in time. We conduct numerical modeling experiments in geometrically simple but physically complex systems of stressed rocks containing self-focusing porous flow. Our model is physically and thermodynamically consistent and describes the formation and evolution of fluid pathways. The model consists of a system of coupled equations describing poro-elasto-viscous deformation and flow. Nonlinearity of the solid rheology is also taken into account. We have developed a numerical application based on an iterative finite difference scheme that runs on mutli-GPUs cluster in parallel. In order to validate these models, we consider the largest CO2 sequestration project in operation at the Sleipner field in the Norwegian North Sea. Attempts to match the observations at Sleipner using conventional reservoir simulations fail to capture first order observations, such as the seemingly effortless vertical flow of CO2 through low permeability shale layers and the formation of focused flow channels or chimneys. Conducted high-resolution three-dimensional numerical simulations predict the formation of dynamically evolving high porosity and permeability pathways as a natural outcome of porous flow nonlinearly coupled with rock deformation, which may trigger leakage through low permeability barriers.

  14. A multi-scale modeling framework for instabilities of film/substrate systems

    NASA Astrophysics Data System (ADS)

    Xu, Fan; Potier-Ferry, Michel

    2016-01-01

    Spatial pattern formation in stiff thin films on soft substrates is investigated from a multi-scale point of view based on a technique of slowly varying Fourier coefficients. A general macroscopic modeling framework is developed and then a simplified macroscopic model is derived. The model incorporates Asymptotic Numerical Method (ANM) as a robust path-following technique to trace the post-buckling evolution path and to predict secondary bifurcations. The proposed multi-scale finite element framework allows sinusoidal and square checkerboard patterns as well as their bifurcation portraits to be described from a quantitative standpoint. Moreover, it provides an efficient way to compute large-scale instability problems with a significant reduction of computational cost compared to full models.

  15. Signal feature extraction by multi-scale PCA and its application to respiratory sound classification.

    PubMed

    Xie, Shengkun; Jin, Feng; Krishnan, Sridhar; Sattar, Farook

    2012-07-01

    Respiratory sound (RS) signals carry significant information about the underlying functioning of the pulmonary system by the presence of adventitious sounds. Although many studies have addressed the problem of pathological RS classification, only a limited number of scientific works have focused in multi-scale analysis. This paper proposes a new signal classification scheme for various types of RS based on multi-scale principal component analysis as a signal enhancement and feature extraction method to capture major variability of Fourier power spectra of the signal. Since we classify RS signals in a high dimensional feature subspace, a new classification method, called empirical classification, is developed for further signal dimension reduction in the classification step and has been shown to be more robust and outperform other simple classifiers. An overall accuracy of 98.34% for the classification of 689 real RS recording segments shows the promising performance of the presented method.

  16. On incremental non-linearity in granular media: phenomenological and multi-scale views

    NASA Astrophysics Data System (ADS)

    Darve, Félix; Nicot, François

    2005-12-01

    On the basis of fundamental constitutive laws such as elasticity, perfect plasticity, and pure viscosity, many elasto-viscoplastic constitutive relations have been developed since the 1970s through phenomenological approaches. In addition, a few more recent micro-mechanical models based on multi-scale approaches are now able to describe the main macroscopic features of the mechanical behaviour of granular media. The purpose of this paper is to compare a phenomenological constitutive relation and a micro-mechanical model with respect to a basic issue regularly raised about granular assemblies: the incrementally non-linear character of their behaviour. It is shown that both phenomenological and micro-mechanical models exhibit an incremental non-linearity. In addition, the multi-scale approach reveals that the macroscopic incremental non-linearity could stem from the change in the regime of local contacts between particles (from plastic regime to elastic regime) in terms of the incremental macroscopic loading direction. Copyright

  17. FEM × DEM: a new efficient multi-scale approach for geotechnical problems with strain localization

    NASA Astrophysics Data System (ADS)

    Nguyen, Trung Kien; Claramunt, Albert Argilaga; Caillerie, Denis; Combe, Gaël; Dal Pont, Stefano; Desrues, Jacques; Richefeu, Vincent

    2017-06-01

    The paper presents a multi-scale modeling of Boundary Value Problem (BVP) approach involving cohesive-frictional granular materials in the FEM × DEM multi-scale framework. On the DEM side, a 3D model is defined based on the interactions of spherical particles. This DEM model is built through a numerical homogenization process applied to a Volume Element (VE). It is then paired with a Finite Element code. Using this numerical tool that combines two scales within the same framework, we conducted simulations of biaxial and pressuremeter tests on a cohesive-frictional granular medium. In these cases, it is known that strain localization does occur at the macroscopic level, but since FEMs suffer from severe mesh dependency as soon as shear band starts to develop, the second gradient regularization technique has been used. As a consequence, the objectivity of the computation with respect to mesh dependency is restored.

  18. Multi-scale seismic tomography of the Merapi-Merbabu volcanic complex, Indonesia

    NASA Astrophysics Data System (ADS)

    Mujid Abdullah, Nur; Valette, Bernard; Potin, Bertrand; Ramdhan, Mohamad

    2017-04-01

    Merapi-Merbabu volcanic complex is the most active volcano located on Java Island, Indonesia, where the Indian plate subducts beneath Eurasian plate. We present a preliminary study of a multi-scale seismic tomography of the substructures of the volcanic complex. The main objective of our study is to image the feeding paths of the volcanic complex at an intermediate scale by using the data from the dense network (about 5 km spacing) constituted by 53 stations of the French-Indonesian DOMERAPI experiment complemented by the data of the German-Indonesian MERAMEX project (134 stations) and of the Indonesia Tsunami Early Warning System (InaTEWS) located in the vicinity of the complex. The inversion was performed using the INSIGHT algorithm, which follows a non-linear least squares approach based on a stochastic description of data and model. In total, 1883 events and 41846 phases (26647 P and 15199 S) have been processed, and a two-scale approach was adopted. The model obtained at regional scale is consistent with the previous studies. We selected the most reliable regional model as a prior model for the local tomography performed with a variant of the INSIGHT code. The algorithm of this code is based on the fact that inverting differences of data when transporting the errors in probability is equivalent to inverting initial data while introducing specific correlation terms in the data covariance matrix. The local tomography provides images of the substructure of the volcanic complex with a sufficiently good resolution to allow identification of a probable magma chamber at about 20 km.

  19. Multi-scale characterization of nanostructured sodium aluminum hydride

    NASA Astrophysics Data System (ADS)

    NaraseGowda, Shathabish

    instruments were utilized for this work and their data collection and analysis are reported. Quasielastic neutron scattering experiments were conducted at NIST Center for Neutron Research to characterize atomic hydrogen diffusion in bulk and nano-confined NaAlH4. It was observed that upon confinement of NaAlH4, a significantly higher fraction of hydrogen atoms were involved in diffusive motion on the pico-second to nano-second timescales. However, the confinement had no impact on the lattice diffusivities (jump/hopping rates) of atomic hydrogen, indicating that the improved hydrogen release rates were not due to any kinetic destabilization effects. Instead, the investigation strongly suggested thermodynamic destabilization as the major effect of nano-confinement. The local interaction of the metal sites in metal organic frameworks with the infiltrated hydride was studied using extended x-ray absorption spectroscopy technique. The experiments were conducted at Center for Advanced Microstructures and Devices at Louisiana State University. The metal sites were found to be chemically un-altered, hence ruling out any catalytic role in the dehydrogenation at room temperatures. The fractal morphology of NaAlH4 was characterized by ultra-small angle x-ray scattering experiments performed at Argonne National Lab. The studies quantitatively estimated the extent of densification in the course of one desorption cycle. The particle sizes were found to increase two-fold during heat treatment. Also, the nano-confinement procedure was shown to produce dense mass fractals as opposed to pristine NaAlH4, exhibiting a surface fractal morphology. Based on this finding, a new method to identify confined material from un-confined material in nano-composites was developed and is presented. Preliminary results of modeling and correlating multi-scale phenomena using a phase-field approach are also presented as the foundation for future work.

  20. 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

    2017-01-01

    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.

  1. Integration of regional to outcrop digital data: 3D visualisation of multi-scale geological models

    NASA Astrophysics Data System (ADS)

    Jones, R. R.; McCaffrey, K. J. W.; Clegg, P.; Wilson, R. W.; Holliman, N. S.; Holdsworth, R. E.; Imber, J.; Waggott, S.

    2009-01-01

    Multi-scale geological models contain three-dimensional, spatially referenced data, typically spanning at least six orders of magnitude from outcrop to regional scale. A large number of different geological and geophysical data sources can be combined into a single model. Established 3D visualisation methods that are widely used in hydrocarbon exploration and production for sub-surface data have been adapted for onshore surface geology through a combination of methods for digital data acquisition, 3D visualisation, and geospatial analysis. The integration of georeferenced data across a wider than normal range in scale helps to address several of the existing limitations that are inherent in traditional methods of map production and publishing. The primary advantage of a multi-scale approach is that spatial precision and dimensionality (which are generally degraded when data are displayed in 2D at a single scale) can be preserved at all scales. Real-time, immersive, interactive software, based on a "3D geospatial" graphical user interface (GUI), allows complex geological architectures to be depicted, and is more inherently intuitive than software based on a standard "desktop" GUI metaphor. The continuing convergence of different kinds of geo-modelling, GIS, and visualisation software, as well as industry acceptance of standardised middleware, has helped to make multi-scale geological models a practical reality. This is illustrated with two case studies from NE England and NW Scotland.

  2. 17.1%-Efficient Multi-Scale-Textured Black Silicon Solar Cells without Dielectric Antireflection Coating: Preprint

    SciTech Connect

    Toor, F.; Page, M. R.; Branz, H. M.; Yuan, H. C.

    2011-07-01

    In this work we present 17.1%-efficient p-type single crystal Si solar cells with a multi-scale-textured surface and no dielectric antireflection coating. Multi-scale texturing is achieved by a gold-nanoparticle-assisted nanoporous etch after conventional micron scale KOH-based pyramid texturing (pyramid black etching). By incorporating geometric enhancement of antireflection, this multi-scale texturing reduces the nanoporosity depth required to make silicon 'black' compared to nanoporous planar surfaces. As a result, it improves short-wavelength spectral response (blue response), previously one of the major limiting factors in 'black-Si' solar cells. With multi-scale texturing, the spectrum-weighted average reflectance from 350- to 1000-nm wavelength is below 2% with a 100-nm deep nanoporous layer. In comparison, roughly 250-nm deep nanopores are needed to achieve similar reflectance on planar surface. Here, we characterize surface morphology, reflectivity and solar cell performance of the multi-scale textured solar cells.

  3. The Brera Multi-scale Wavelet ROSAT HRI source catalogue

    NASA Astrophysics Data System (ADS)

    Panzera, M. R.; Campana, S.; Covino, S.; Lazzati, D.; Mignani, R. P.; Moretti, A.; Tagliaferri, G.

    2003-02-01

    We present the Brera Multi-scale Wavelet ROSAT HRI source catalogue (BMW-HRI) derived from all ROSAT HRI pointed observations with exposure times longer than 100 s available in the ROSAT public archives. The data were analyzed automatically using a wavelet detection algorithm suited to the detection and characterization of both point-like and extended sources. This algorithm is able to detect and disentangle sources in very crowded fields and/or in the presence of extended or bright sources. Images have been also visually inspected after the analysis to ensure verification. The final catalogue, derived from 4303 observations, consists of 29 089 sources detected with a detection probability of >=4.2 sigma . For each source, the primary catalogue entries provide name, position, count rate, flux and extension along with the relative errors. In addition, results of cross-correlations with existing catalogues at different wavelengths (FIRST, IRAS, 2MASS and GSC2) are also reported. Some information is available on the web via the DIANA Interface. As an external check, we compared our catalogue with the previously available ROSHRICAT catalogue (both in its short and long versions) and we were able to recover, for the short version, ~ 90% of the entries. We computed the sky coverage of the entire HRI data set by means of simulations. The complete BMW-HRI catalogue provides a sky coverage of 732 deg2 down to a limiting flux of ~ 10-12 erg s-1 cm-2 and of 10 deg2 down to ~ 10-14 erg s-1 cm-2. We were able to compute the cosmological log(N)-log(S) distribution down to a flux of =~ 1.2 x 10-14 erg s-1 cm-2. The catalogue is only available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsweb.u-strasbg.fr/cgi-bin/qcat?J/A+A/399/351

  4. Multi-Scale Modeling the Mechanical Properties of Biaxial Weft Knitted Fabrics for Composite Applications

    NASA Astrophysics Data System (ADS)

    Abghary, Mohammad Javad; Nedoushan, Reza Jafari; Hasani, Hossein

    2017-08-01

    In this paper a multi-scale numerical model for simulating the mechanical behavior of biaxial weft knitted fabrics produced based on 1×1 rib structure is presented. Fabrics were produced on a modern flat knitting machine using polyester as stitch yarns and nylon as straight yarns. A macro constitutive equation was presented to model the fabric mechanical behavior as a continuum material. User defined material subroutines were provided to implement the constitutive behavior in Abaqus software. The constitutive equation needs remarkable tensile tests on the fabric as the inputs. To solve this drawbacks meso scale modeling of the fabric was used to predict stress-strain curves of the fabric in three different directions (course, wale and 45°). In these simulations only the yarn properties are needed. To evaluate the accuracy of the proposed macro and meso models, fabric tensile behavior in 22.5 and 67.5° directions were simulated by the calibrated macro model and compared with experimental results. Spherical deformation was also simulated by the multi scale model and compared with experimental results. The results showed that the multi-scale modeling can successfully predict the tensile and spherical deformation of the biaxial weft knitted fabric with least required experiments. This model will be useful for composite applications.

  5. Multi-Scale Modeling the Mechanical Properties of Biaxial Weft Knitted Fabrics for Composite Applications

    NASA Astrophysics Data System (ADS)

    Abghary, Mohammad Javad; Nedoushan, Reza Jafari; Hasani, Hossein

    2016-11-01

    In this paper a multi-scale numerical model for simulating the mechanical behavior of biaxial weft knitted fabrics produced based on 1×1 rib structure is presented. Fabrics were produced on a modern flat knitting machine using polyester as stitch yarns and nylon as straight yarns. A macro constitutive equation was presented to model the fabric mechanical behavior as a continuum material. User defined material subroutines were provided to implement the constitutive behavior in Abaqus software. The constitutive equation needs remarkable tensile tests on the fabric as the inputs. To solve this drawbacks meso scale modeling of the fabric was used to predict stress-strain curves of the fabric in three different directions (course, wale and 45°). In these simulations only the yarn properties are needed. To evaluate the accuracy of the proposed macro and meso models, fabric tensile behavior in 22.5 and 67.5° directions were simulated by the calibrated macro model and compared with experimental results. Spherical deformation was also simulated by the multi scale model and compared with experimental results. The results showed that the multi-scale modeling can successfully predict the tensile and spherical deformation of the biaxial weft knitted fabric with least required experiments. This model will be useful for composite applications.

  6. Multi-scale characterization of surface blistering morphology of helium irradiated W thin films

    NASA Astrophysics Data System (ADS)

    Yang, J. J.; Zhu, H. L.; Wan, Q.; Peng, M. J.; Ran, G.; Tang, J.; Yang, Y. Y.; Liao, J. L.; Liu, N.

    2015-09-01

    Surface blistering morphologies of W thin films irradiated by 30 keV He ion beam were studied quantitatively. It was found that the blistering morphology strongly depends on He fluence. For lower He fluence, the accumulation and growth of He bubbles induce the intrinsic surface blisters with mono-modal size distribution feature. When the He fluence is higher, the film surface morphology exhibits a multi-scale property, including two kinds of surface blisters with different characteristic sizes. In addition to the intrinsic He blisters, film/substrate interface delamination also induces large-sized surface blisters. A strategy based on wavelet transform approach was proposed to distinguish and extract the multi-scale surface blistering morphologies. Then the density, the lateral size and the height of these different blisters were estimated quantitatively, and the effect of He fluence on these geometrical parameters was investigated. Our method could provide a potential tool to describe the irradiation induced surface damage morphology with a multi-scale property.

  7. Multi-scale model of food drying: Current status and challenges.

    PubMed

    Rahman, M M; Joardder, Mohammad U H; Khan, M I H; Pham, Nghia Duc; Karim, M A

    2016-09-19

    For a long time, food engineers have been trying to describe the physical phenomena that occur during food processing especially drying. Physics-based theoretical modeling is an important tool for the food engineers to reduce the hurdles of experimentation. Drying of food is a multi-physics phenomenon such as coupled heat and mass transfer. Moreover, food structure is multi-scale in nature, and the microstructural features play a great role in the food processing specially in drying. Previously simple macroscopic model was used to describe the drying phenomena which can give a little description about the smaller scale. The multiscale modeling technique can handle all the phenomena that occur during drying. In this special kind of modeling approach, the single scale models from bigger to smaller scales are interconnected. With the help of multiscale modeling framework, the transport process associated with drying can be studied on a smaller scale and the resulting information can be transferred to the bigger scale. This article is devoted to discussing the state of the art multi-scale modeling, its prospect and challenges in the field of drying technology. This article has also given some directions to how to overcome the challenges for successful implementation of multi-scale modeling.

  8. 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.

  9. Multi-scale methodology: a key to deciphering systems biology.

    PubMed

    Ye, Xinhao; Chu, Ju; Zhuang, Yinping; Zhang, Siliang

    2005-01-01

    Presently, it is widely accepted complex systems couldn't be comprehended by studying parts in isolation without examining integrative and emergent properties, and system-level understanding thus has become the focus in biological science. However, it should also be noted that common systematic analysis was restricted to large-scale analysis at a certain level, while the facts that the nature of complex systems is their multi-scale structures was usually neglected or ignored. Therefore, this paper described a multi-scale methodology to investigate the nature of biological complexity and prospected this methodology could lead to a promising revolution in current system-level understanding and the integration of molecular biology databases.

  10. 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.

  11. Complexity of carbon market from multi-scale entropy analysis

    NASA Astrophysics Data System (ADS)

    Fan, Xinghua; Li, Shasha; Tian, Lixin

    2016-06-01

    Complexity of carbon market is the consequence of economic dynamics and extreme social political events in global carbon markets. The multi-scale entropy can measure the long-term structures in the daily price return time series. By using multi-scale entropy analysis, we explore the complexity of carbon market and mean reversion trend of daily price return. The logarithmic difference of data Dec16 from August 6, 2010 to May 22, 2015 is selected as the sample. The entropy is higher in small time scale, while lower in large. The dependence of the entropy on the time scale reveals the mean reversion of carbon prices return in the long run. A relatively great fluctuation over some short time period indicates that the complexity of carbon market evolves consistently with economic development track and the events of international climate conferences.

  12. Multi-Scale Complexity in Linear Dispersive Pulse Propagation Phenomena

    DTIC Science & Technology

    2011-02-01

    matter of course, one then takes the limit as D∆ → 0 after the analysis has been completed. Equation (7) is an integro - differential equation for the...Eqs. (7)–(8). These integro - differential equations are somewhat simplified in the tem- poral frequency domain obtained by taking the temporal Fourier...and, as such, they present an important example of multi-scale com- plexity. 2.1 Integral Equation Representation of Electromagnetic Pulse

  13. 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.

  14. Multi-Scale SSA or Data-Adaptive Wavelets

    NASA Astrophysics Data System (ADS)

    Yiou, P.; Sornette, D.; Sornette, D.; Sornette, D.; Ghil, M.; Ghil, M.

    2001-05-01

    Using multi-scale ideas from wavelet analysis, the singular-spectrum analysis (SSA) is extended to the study of nonstationary time series, including the case where their variance diverges. The wavelet transform is similar to a local Fourier transform within a finite moving window whose width W, proportional to the major period of interest, is varied to explore a broad range of such periods. SSA, on the other hand, relies on the construction of the lag-correlation matrix C on M lagged copies of the time series over a fixed window width W proportional to M to detect the regular part of the variability in that window in terms of the minimal number of oscillatory components. The proposed multi-scale SSA is a local SSA analysis within a moving window of width M<= W <= N, where N is the length of the time series. Multi-scale SSA varies W, while keeping a fixed W/M ratio, and uses the eigenvectors of the corresponding lag-correlation matrix C(M) as data-adaptive wavelets; successive eigenvectors of C(M) correspond approximately to successive derivatives of the first mother wavelet in standard wavelet analysis. Multi-scale SSA thus solves objectively the delicate problem of optimizing the analyzing wavelet in the time-frequency domain, by a suitable localization of the signal's correlation matrix. We present several examples of application to synthetic signals with fractal or power-law behavior which mimic selected features of certain climatic or geophysical time series. The method is applied to the monthly values of the Southern Oscillation index (SOI) which captures major features of the El Niño/Southern Oscillation in the Tropical Pacific. Our methodology highlights an abrupt periodicity shift in the SOI near 1960. This abrupt shift between 5 and 3 years supports the Devil's staircase scenario for the El Niño/Southern Oscillation phenomenon.

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

    PubMed

    Hayashibe, Mitsuhiro; Guiraud, David

    2013-09-04

    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. 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. 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 contractions schemes. We introduced a

  16. Moist multi-scale models for the hurricane embryo

    SciTech Connect

    Majda, Andrew J.; Xing, Yulong; Mohammadian, Majid

    2010-01-01

    Determining the finite-amplitude preconditioned states in the hurricane embryo, which lead to tropical cyclogenesis, is a central issue in contemporary meteorology. In the embryo there is competition between different preconditioning mechanisms involving hydrodynamics and moist thermodynamics, which can lead to cyclogenesis. Here systematic asymptotic methods from applied mathematics are utilized to develop new simplified moist multi-scale models starting from the moist anelastic equations. Three interesting multi-scale models emerge in the analysis. The balanced mesoscale vortex (BMV) dynamics and the microscale balanced hot tower (BHT) dynamics involve simplified balanced equations without gravity waves for vertical vorticity amplification due to moist heat sources and incorporate nonlinear advective fluxes across scales. The BMV model is the central one for tropical cyclogenesis in the embryo. The moist mesoscale wave (MMW) dynamics involves simplified equations for mesoscale moisture fluctuations, as well as linear hydrostatic waves driven by heat sources from moisture and eddy flux divergences. A simplified cloud physics model for deep convection is introduced here and used to study moist axisymmetric plumes in the BHT model. A simple application in periodic geometry involving the effects of mesoscale vertical shear and moist microscale hot towers on vortex amplification is developed here to illustrate features of the coupled multi-scale models. These results illustrate the use of these models in isolating key mechanisms in the embryo in a simplified content.

  17. 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.

  18. Quasi-3D Algorithm in Multi-scale Modeling Framework

    NASA Astrophysics Data System (ADS)

    Jung, J.; Arakawa, A.

    2008-12-01

    As discussed in the companion paper by Arakawa and Jung, the Quasi-3D (Q3D) Multi-scale Modeling Framework (MMF) is a 4D estimation/prediction framework that combines a GCM with a 3D anelastic vector vorticity equation model (VVM) applied to a Q3D network of horizontal grid points. This paper presents an outline of the recently revised Q3D algorithm and a highlight of the results obtained by application of the algorithm to an idealized model setting. The Q3D network of grid points consists of two sets of grid-point arrays perpendicular to each other. For a scalar variable, for example, each set consists of three parallel rows of grid points. Principal and supplementary predictions are made on the central and the two adjacent rows, respectively. The supplementary prediction is to allow the principal prediction be three-dimensional at least to the second-order accuracy. To accommodate a higher-order accuracy and to make the supplementary predictions formally three-dimensional, a few rows of ghost points are added at each side of the array. Values at these ghost points are diagnostically determined by a combination of statistical estimation and extrapolation. The basic structure of the estimation algorithm is determined in view of the global stability of Q3D advection. The algorithm is calibrated using the statistics of past data at and near the intersections of the two sets of grid- point arrays. Since the CRM in the Q3D MMF extends beyond individual GCM boxes, the CRM can be a GCM by itself. However, it is better to couple the CRM with the GCM because (1) the CRM is a Q3D CRM based on a highly anisotropic network of grid points and (2) coupling with a GCM makes it more straightforward to inherit our experience with the conventional GCMs. In the coupled system we have selected, prediction of thermdynamic variables is almost entirely done by the Q3D CRM with no direct forcing by the GCM. The coupling of the dynamics between the two components is through mutual

  19. Multi-scales region segmentation for ROI separation in digital mammograms

    NASA Astrophysics Data System (ADS)

    Zhang, Dapeng; Zhang, Di; Li, Yue; Wang, Wei

    2017-02-01

    Mammography is currently the most effective imaging modality used by radiologists for the screening of breast cancer. Segmentation is one of the key steps in the process of developing anatomical models for calculation of safe medical dose of radiation. This paper explores the potential of the statistical region merging segmentation technique for Breast segmentation in digital mammograms. First, the mammograms are pre-processing for regions enhancement, then the enhanced images are segmented using SRM with multi scales, finally these segmentations are combined for region of interest (ROI) separation and edge detection. The proposed algorithm uses multi-scales region segmentation in order to: separate breast region from background region, region edge detection and ROIs separation. The experiments are performed using a data set of mammograms from different patients, demonstrating the validity of the proposed criterion. Results show that, the statistical region merging segmentation algorithm actually can work on the segmentation of medical image and more accurate than another methods. And the outcome shows that the technique has a great potential to become a method of choice for segmentation of mammograms.

  20. A multi-scale computational model of the effects of TMS on motor cortex

    PubMed Central

    Seo, Hyeon; Schaworonkow, Natalie; Jun, Sung Chan; Triesch, Jochen

    2017-01-01

    The detailed biophysical mechanisms through which transcranial magnetic stimulation (TMS) activates cortical circuits are still not fully understood. Here we present a multi-scale computational model to describe and explain the activation of different pyramidal cell types in motor cortex due to TMS. Our model determines precise electric fields based on an individual head model derived from magnetic resonance imaging and calculates how these electric fields activate morphologically detailed models of different neuron types. We predict neural activation patterns for different coil orientations consistent with experimental findings. Beyond this, our model allows us to calculate activation thresholds for individual neurons and precise initiation sites of individual action potentials on the neurons’ complex morphologies. Specifically, our model predicts that cortical layer 3 pyramidal neurons are generally easier to stimulate than layer 5 pyramidal neurons, thereby explaining the lower stimulation thresholds observed for I-waves compared to D-waves. It also shows differences in the regions of activated cortical layer 5 and layer 3 pyramidal cells depending on coil orientation. Finally, it predicts that under standard stimulation conditions, action potentials are mostly generated at the axon initial segment of cortical pyramidal cells, with a much less important activation site being the part of a layer 5 pyramidal cell axon where it crosses the boundary between grey matter and white matter. In conclusion, our computational model offers a detailed account of the mechanisms through which TMS activates different cortical pyramidal cell types, paving the way for more targeted application of TMS based on individual brain morphology in clinical and basic research settings. PMID:28408973

  1. Bush Encroachment Mapping for Africa - Multi-Scale Analysis with Remote Sensing and GIS

    NASA Astrophysics Data System (ADS)

    Graw, V. A. M.; Oldenburg, C.; Dubovyk, O.

    2015-12-01

    Bush encroachment describes a global problem which is especially facing the savanna ecosystem in Africa. Livestock is directly affected by decreasing grasslands and inedible invasive species which defines the process of bush encroachment. For many small scale farmers in developing countries livestock represents a type of insurance in times of crop failure or drought. Among that bush encroachment is also a problem for crop production. Studies on the mapping of bush encroachment so far focus on small scales using high-resolution data and rarely provide information beyond the national level. Therefore a process chain was developed using a multi-scale approach to detect bush encroachment for whole Africa. The bush encroachment map is calibrated with ground truth data provided by experts in Southern, Eastern and Western Africa. By up-scaling location specific information on different levels of remote sensing imagery - 30m with Landsat images and 250m with MODIS data - a map is created showing potential and actual areas of bush encroachment on the African continent and thereby provides an innovative approach to map bush encroachment on the regional scale. A classification approach links location data based on GPS information from experts to the respective pixel in the remote sensing imagery. Supervised classification is used while actual bush encroachment information represents the training samples for the up-scaling. The classification technique is based on Random Forests and regression trees, a machine learning classification approach. Working on multiple scales and with the help of field data an innovative approach can be presented showing areas affected by bush encroachment on the African continent. This information can help to prevent further grassland decrease and identify those regions where land management strategies are of high importance to sustain livestock keeping and thereby also secure livelihoods in rural areas.

  2. 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

  3. On combining image-based and ontological semantic dissimilarities for medical image retrieval applications

    PubMed Central

    Kurtz, Camille; Depeursinge, Adrien; Napel, Sandy; Beaulieu, Christopher F.; Rubin, Daniel L.

    2014-01-01

    Computer-assisted image retrieval applications can assist radiologists by identifying similar images in archives as a means to providing decision support. In the classical case, images are described using low-level features extracted from their contents, and an appropriate distance is used to find the best matches in the feature space. However, using low-level image features to fully capture the visual appearance of diseases is challenging and the semantic gap between these features and the high-level visual concepts in radiology may impair the system performance. To deal with this issue, the use of semantic terms to provide high-level descriptions of radiological image contents has recently been advocated. Nevertheless, most of the existing semantic image retrieval strategies are limited by two factors: they require manual annotation of the images using semantic terms and they ignore the intrinsic visual and semantic relationships between these annotations during the comparison of the images. Based on these considerations, we propose an image retrieval framework based on semantic features that relies on two main strategies: (1) automatic “soft” prediction of ontological terms that describe the image contents from multi-scale Riesz wavelets and (2) retrieval of similar images by evaluating the similarity between their annotations using a new term dissimilarity measure, which takes into account both image-based and ontological term relations. The combination of these strategies provides a means of accurately retrieving similar images in databases based on image annotations and can be considered as a potential solution to the semantic gap problem. We validated this approach in the context of the retrieval of liver lesions from computed tomographic (CT) images and annotated with semantic terms of the RadLex ontology. The relevance of the retrieval results was assessed using two protocols: evaluation relative to a dissimilarity reference standard defined for pairs

  4. On combining image-based and ontological semantic dissimilarities for medical image retrieval applications.

    PubMed

    Kurtz, Camille; Depeursinge, Adrien; Napel, Sandy; Beaulieu, Christopher F; Rubin, Daniel L

    2014-10-01

    Computer-assisted image retrieval applications can assist radiologists by identifying similar images in archives as a means to providing decision support. In the classical case, images are described using low-level features extracted from their contents, and an appropriate distance is used to find the best matches in the feature space. However, using low-level image features to fully capture the visual appearance of diseases is challenging and the semantic gap between these features and the high-level visual concepts in radiology may impair the system performance. To deal with this issue, the use of semantic terms to provide high-level descriptions of radiological image contents has recently been advocated. Nevertheless, most of the existing semantic image retrieval strategies are limited by two factors: they require manual annotation of the images using semantic terms and they ignore the intrinsic visual and semantic relationships between these annotations during the comparison of the images. Based on these considerations, we propose an image retrieval framework based on semantic features that relies on two main strategies: (1) automatic "soft" prediction of ontological terms that describe the image contents from multi-scale Riesz wavelets and (2) retrieval of similar images by evaluating the similarity between their annotations using a new term dissimilarity measure, which takes into account both image-based and ontological term relations. The combination of these strategies provides a means of accurately retrieving similar images in databases based on image annotations and can be considered as a potential solution to the semantic gap problem. We validated this approach in the context of the retrieval of liver lesions from computed tomographic (CT) images and annotated with semantic terms of the RadLex ontology. The relevance of the retrieval results was assessed using two protocols: evaluation relative to a dissimilarity reference standard defined for pairs of

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

    SciTech Connect

    Stander, Nielen; Basudhar, Anirban; Basu, Ushnish; Gandikota, Imtiaz; Savic, Vesna; Sun, Xin; Choi, Kyoo Sil; Hu, Xiaohua; Pourboghrat, F.; Park, Taejoon; Mapar, Aboozar; Kumar, Shavan; Ghassemi-Armaki, Hassan; Abu-Farha, Fadi

    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 to 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 Comprehensive

  6. Research iris serial images quality assessment method based on HVS

    NASA Astrophysics Data System (ADS)

    Li, Zhi-hui; Zhang, Chang-hai; Ming, Xing; Zhao, Yong-hua

    2006-01-01

    Iris recognition can be widely used in security and customs, and it provides superiority security than other human feature recognition such as fingerprint, face and so on. The iris image quality is crucial to recognition effect. Accordingly reliable image quality assessments are necessary for evaluating iris image quality. However, there haven't uniformly criterion to Image quality assessment. Image quality assessment have Objective and Subjective Evaluation methods, In practice, However Subjective Evaluation method is fussy and doesn't effective on iris recognition. Objective Evaluation method should be used in iris recognition. According to human visual system model (HVS) Multi-scale and selectivity characteristic, it presents a new iris Image quality assessment method. In the paper, ROI is found and wavelet transform zero-crossing is used to find Multi-scale edge, and Multi-scale fusion measure is used to assess iris image quality. In experiment, Objective and Subjective Evaluation methods are used to assess iris images. From the results, the method is effectively to iris image quality assessment.

  7. A Hierarchical Theory and Patch Dynamics Paradigm for Multi-scale Ground Water Modeling

    NASA Astrophysics Data System (ADS)

    Phanikumar, M. S.; Li, S.

    2002-12-01

    Concepts involving scale, extent, and dimensionality are central to a number of hydrological processes. Traditional modeling approaches fail to describe the interactions between a continuous cascade of scales present in a natural hydrological system. Hierarchical theory can provide a conceptual framework to describe processes at different spatiotemporal scales using multiple nested levels of organization and could bridge the gap between stochastic and deterministic points of view. In the present paper, we propose a systematic approach based on the hierarchical patch dynamics paradigm (HPDP) and demonstrate its application to problems with multi-scale interactions. We use a sequence of successively refined computational meshes centered around regions of interest (patches) and allow interactions between different scales using two-way coupling (e.g., regional to local and vice versa). We illustrate our approach using problems that involve fragmented and isolated patches (e.g., as a result of anthropogenic effects such as house building or agriculture) and a multiplicity of scale making patch dynamics and interactions across different levels an important aspect. Although concepts of hierarchical theory are not new, efforts to bridge the gaps between concepts, theory and practical implementations are relatively new and limited in the context of groundwater hydrology. Using several test cases, we demonstrate that the new approach can be used to analyze scale interactions in a multi-scale system and that it provides a computational framework that is much more robust than based on traditional approaches. We define metrics to describe the performance of the proposed approach and compare predictions based on the HPDP with those based on traditional modeling and demonstrate that significant savings in computer time result from the new approach. The HPDP becomes particularly attractive when applied to multi-scale reactive transport problems.

  8. A multi-scale approach to designing therapeutics for tuberculosis.

    PubMed

    Linderman, Jennifer J; Cilfone, Nicholas A; Pienaar, Elsje; Gong, Chang; Kirschner, Denise E

    2015-05-01

    Approximately one third of the world's population is infected with Mycobacterium tuberculosis. Limited information about how the immune system fights M. tuberculosis and what constitutes protection from the bacteria impact our ability to develop effective therapies for tuberculosis. We present an in vivo systems biology approach that integrates data from multiple model systems and over multiple length and time scales into a comprehensive multi-scale and multi-compartment view of the in vivo immune response to M. tuberculosis. We describe computational models that can be used to study (a) immunomodulation with the cytokines tumor necrosis factor and interleukin 10, (b) oral and inhaled antibiotics, and (c) the effect of vaccination.

  9. 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

  10. 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.

  11. A multi-scale, multi-wavelength source extraction method: getsources

    NASA Astrophysics Data System (ADS)

    Men'shchikov, A.; André, Ph.; Didelon, P.; Motte, F.; Hennemann, M.; Schneider, N.

    2012-06-01

    We present a multi-scale, multi-wavelength source extraction algorithm called getsources. Although it has been designed primarily for use in the far-infrared surveys of Galactic star-forming regions with Herschel, the method can be applied to many other astronomical images. Instead of the traditional approach of extracting sources in the observed images, the new method analyzes fine spatial decompositions of original images across a wide range of scales and across all wavebands. It cleans those single-scale images of noise and background, and constructs wavelength-independent single-scale detection images that preserve information in both spatial and wavelength dimensions. Sources are detected in the combined detection images by following the evolution of their segmentation masks across all spatial scales. Measurements of the source properties are done in the original background-subtracted images at each wavelength; the background is estimated by interpolation under the source footprints and overlapping sources are deblended in an iterative procedure. In addition to the main catalog of sources, various catalogs and images are produced that aid scientific exploitation of the extraction results. We illustrate the performance of getsources on Herschel images by extracting sources in sub-fields of the Aquila and Rosette star-forming regions. The source extraction code and validation images with a reference extraction catalog are freely available.

  12. 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.

  13. Multi-Scale Structure and Earthquake Properties in the San Jacinto Fault Zone Area

    NASA Astrophysics Data System (ADS)

    Ben-Zion, Y.

    2014-12-01

    I review multi-scale multi-signal seismological results on structure and earthquake properties within and around the San Jacinto Fault Zone (SJFZ) in southern California. The results are based on data of the southern California and ANZA networks covering scales from a few km to over 100 km, additional near-fault seismometers and linear arrays with instrument spacing 25-50 m that cross the SJFZ at several locations, and a dense rectangular array with >1100 vertical-component nodes separated by 10-30 m centered on the fault. The structural studies utilize earthquake data to image the seismogenic sections and ambient noise to image the shallower structures. The earthquake studies use waveform inversions and additional time domain and spectral methods. We observe pronounced damage regions with low seismic velocities and anomalous Vp/Vs ratios around the fault, and clear velocity contrasts across various sections. The damage zones and velocity contrasts produce fault zone trapped and head waves at various locations, along with time delays, anisotropy and other signals. The damage zones follow a flower-shape with depth; in places with velocity contrast they are offset to the stiffer side at depth as expected for bimaterial ruptures with persistent propagation direction. Analysis of PGV and PGA indicates clear persistent directivity at given fault sections and overall motion amplification within several km around the fault. Clear temporal changes of velocities, probably involving primarily the shallow material, are observed in response to seasonal, earthquake and other loadings. Full source tensor properties of M>4 earthquakes in the complex trifurcation area include statistically-robust small isotropic component, likely reflecting dynamic generation of rock damage in the source volumes. The dense fault zone instruments record seismic "noise" at frequencies >200 Hz that can be used for imaging and monitoring the shallow material with high space and time details, and

  14. Multi-scale modeling for sustainable chemical production.

    PubMed

    Zhuang, Kai; Bakshi, Bhavik R; Herrgård, Markus J

    2013-09-01

    With recent advances in metabolic engineering, it is now technically possible to produce a wide portfolio of existing petrochemical products from biomass feedstock. In recent years, a number of modeling approaches have been developed to support the engineering and decision-making processes associated with the development and implementation of a sustainable biochemical industry. The temporal and spatial scales of modeling approaches for sustainable chemical production vary greatly, ranging from metabolic models that aid the design of fermentative microbial strains to material and monetary flow models that explore the ecological impacts of all economic activities. Research efforts that attempt to connect the models at different scales have been limited. Here, we review a number of existing modeling approaches and their applications at the scales of metabolism, bioreactor, overall process, chemical industry, economy, and ecosystem. In addition, we propose a multi-scale approach for integrating the existing models into a cohesive framework. The major benefit of this proposed framework is that the design and decision-making at each scale can be informed, guided, and constrained by simulations and predictions at every other scale. In addition, the development of this multi-scale framework would promote cohesive collaborations across multiple traditionally disconnected modeling disciplines to achieve sustainable chemical production.

  15. Multi-scale curvature tensor analysis of machined surfaces

    NASA Astrophysics Data System (ADS)

    Bartkowiak, Tomasz; Brown, Christopher

    2016-12-01

    This paper demonstrates the use of multi-scale curvature analysis, an areal new surface characterization technique for better understanding topographies, for analyzing surfaces created by conventional machining and grinding. Curvature, like slope and area, changes with scale of observation, or calculation, on irregular surfaces, therefore it can be used for multi-scale geometric analysis. Curvatures on a surface should be indicative of topographically dependent behavior of a surface and curvatures are, in turn, influenced by the processing and use of the surface. Curvatures have not been well characterized previously. Curvature has been used for calculations in contact mechanics and for the evaluation of cutting edges. In the current work two parts were machined and then one of them was ground. The surface topographies were measured with a scanning laser confocal microscope. Plots of curvatures as a function of position and scale are presented, and the means and standard deviations of principal curvatures are plotted as a function of scale. Statistical analyses show the relations between curvature and these two manufacturing processes at multiple scales.

  16. Multi-scale radiomic analysis of sub-cortical regions in MRI related to autism, gender and age

    PubMed Central

    Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

    2017-01-01

    We propose using multi-scale image textures to investigate links between neuroanatomical regions and clinical variables in MRI. Texture features are derived at multiple scales of resolution based on the Laplacian-of-Gaussian (LoG) filter. Three quantifier functions (Average, Standard Deviation and Entropy) are used to summarize texture statistics within standard, automatically segmented neuroanatomical regions. Significance tests are performed to identify regional texture differences between ASD vs. TDC and male vs. female groups, as well as correlations with age (corrected p < 0.05). The open-access brain imaging data exchange (ABIDE) brain MRI dataset is used to evaluate texture features derived from 31 brain regions from 1112 subjects including 573 typically developing control (TDC, 99 females, 474 males) and 539 Autism spectrum disorder (ASD, 65 female and 474 male) subjects. Statistically significant texture differences between ASD vs. TDC groups are identified asymmetrically in the right hippocampus, left choroid-plexus and corpus callosum (CC), and symmetrically in the cerebellar white matter. Sex-related texture differences in TDC subjects are found in primarily in the left amygdala, left cerebellar white matter, and brain stem. Correlations between age and texture in TDC subjects are found in the thalamus-proper, caudate and pallidum, most exhibiting bilateral symmetry. PMID:28361913

  17. 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

  18. Multi-scale radiomic analysis of sub-cortical regions in MRI related to autism, gender and age

    NASA Astrophysics Data System (ADS)

    Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

    2017-03-01

    We propose using multi-scale image textures to investigate links between neuroanatomical regions and clinical variables in MRI. Texture features are derived at multiple scales of resolution based on the Laplacian-of-Gaussian (LoG) filter. Three quantifier functions (Average, Standard Deviation and Entropy) are used to summarize texture statistics within standard, automatically segmented neuroanatomical regions. Significance tests are performed to identify regional texture differences between ASD vs. TDC and male vs. female groups, as well as correlations with age (corrected p < 0.05). The open-access brain imaging data exchange (ABIDE) brain MRI dataset is used to evaluate texture features derived from 31 brain regions from 1112 subjects including 573 typically developing control (TDC, 99 females, 474 males) and 539 Autism spectrum disorder (ASD, 65 female and 474 male) subjects. Statistically significant texture differences between ASD vs. TDC groups are identified asymmetrically in the right hippocampus, left choroid-plexus and corpus callosum (CC), and symmetrically in the cerebellar white matter. Sex-related texture differences in TDC subjects are found in primarily in the left amygdala, left cerebellar white matter, and brain stem. Correlations between age and texture in TDC subjects are found in the thalamus-proper, caudate and pallidum, most exhibiting bilateral symmetry.

  19. Space-scale unfolding mechanism in canonical multi-scale flows

    NASA Astrophysics Data System (ADS)

    Baj, Pawel; Bruce, Paul J. K.; Buxton, Oliver R. H.

    2015-11-01

    Some recent studies on fractal generated turbulence revealed a highly increased transverse turbulent scalar flux downstream of fractal grids compared to regular grids. The complexity of these flows makes it impossible to track the origins of this phenomenon, often referred to as the space-scale unfolding mechanism (SSU). Thus research on flows past canonical examples of single and multi-scale obstacles, which are arrays of bars of the same and different thicknesses, was undertaken in order to investigate the SSU's roots. The velocity field and the scalar concentration field were measured simultaneously downstream of the obstacles by means of particle image velocimetry and laser induced fluorescence techniques. It is observed that the concentration field behind the multi-scale obstacle undergoes intense quasi-periodic transverse scalar bursts, which are believed to be the manifestation of the SSU, whereas such events are either weak or absent in the single scale configuration. Investigation of the velocity field reveals a phase locking between wakes of different scale objects in terms of the phase-conditioned transverse integral length scale. Both phenomena are observed to be triggered at the downstream position corresponding to the wakes' intersection point. The authors acknowledge support form the EU through the FP7 Marie Curie MULTISOLVE project (grant agreement No. 317269).

  20. Multi-scale Modeling of the Cardiovascular System: Disease Development, Progression, and Clinical Intervention.

    PubMed

    Zhang, Yanhang; Barocas, Victor H; Berceli, Scott A; Clancy, Colleen E; Eckmann, David M; Garbey, Marc; Kassab, Ghassan S; Lochner, Donna R; McCulloch, Andrew D; Tran-Son-Tay, Roger; Trayanova, Natalia A

    2016-09-01

    Cardiovascular diseases (CVDs) are the leading cause of death in the western world. With the current development of clinical diagnostics to more accurately measure the extent and specifics of CVDs, a laudable goal is a better understanding of the structure-function relation in the cardiovascular system. Much of this fundamental understanding comes from the development and study of models that integrate biology, medicine, imaging, and biomechanics. Information from these models provides guidance for developing diagnostics, and implementation of these diagnostics to the clinical setting, in turn, provides data for refining the models. In this review, we introduce multi-scale and multi-physical models for understanding disease development, progression, and designing clinical interventions. We begin with multi-scale models of cardiac electrophysiology and mechanics for diagnosis, clinical decision support, personalized and precision medicine in cardiology with examples in arrhythmia and heart failure. We then introduce computational models of vasculature mechanics and associated mechanical forces for understanding vascular disease progression, designing clinical interventions, and elucidating mechanisms that underlie diverse vascular conditions. We conclude with a discussion of barriers that must be overcome to provide enhanced insights, predictions, and decisions in pre-clinical and clinical applications.

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

    NASA Astrophysics Data System (ADS)

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

    2017-06-01

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

  2. Exploring multi-scale forest above ground biomass estimation with optical remote sensing imageries

    NASA Astrophysics Data System (ADS)

    Koju, U.; Zhang, J.; Gilani, H.

    2017-02-01

    Forest shares 80% of total exchange of carbon between the atmosphere and the terrestrial ecosystem. Due to this monitoring of forest above ground biomass (as carbon can be calculated as 0.47 part of total biomass) has become very important. Forest above ground biomass as being the major portion of total forest biomass should be given a very careful consideration in its estimation. It is hoped to be useful in addressing the ongoing problems of deforestation and degradation and to gain carbon mitigation benefits through mechanisms like Reducing Emissions from Deforestation and Forest Degradation (REDD+). Many methods of above ground biomass estimation are in used ranging from use of optical remote sensing imageries of very high to very low resolution to SAR data and LIDAR. This paper describes a multi-scale approach for assessing forest above ground biomass, and ultimately carbon stocks, using very high imageries, open source medium resolution and medium resolution satellite datasets with a very limited number of field plots. We found this method is one of the most promising method for forest above ground biomass estimation with higher accuracy and low cost budget. Pilot study was conducted in Chitwan district of Nepal on the estimation of biomass using this technique. The GeoEye-1 (0.5m), Landsat (30m) and Google Earth (GE) images were used remote sensing imageries. Object-based image analysis (OBIA) classification technique was done on Geo-eye imagery for the tree crown delineation at the watershed level. After then, crown projection area (CPA) vs. biomass model was developed and validated at the watershed level. Open source GE imageries were used to calculate the CPA and biomass from virtual plots at district level. Using data mining technique, different parameters from Landsat imageries along with the virtual sample biomass were used for upscaling biomass estimation at district level. We found, this approach can considerably reduce field data requirements for

  3. 3D multi-scale modelling of mechanical behaviour of sound and leached mortar

    SciTech Connect

    Bernard, F.; Kamali-Bernard, S. Prince, W.

    2008-04-15

    A 3D multi-scale modelling of mechanical properties of cement-based materials approach is presented. The proposed approach provides a quantitative means to estimate and predict the mechanical properties of cement-based materials taking into account the eventual changes in the micro-structure. Two numerical tools are combined. First, the NIST's 3D model (CEMHYD3D) is used to generate a realistic 3D Representative Volume Element of cement-based materials at different scales. Then, multi-scale simulations are performed by using the FE software Abaqus for the calculation of the mechanical behaviour. The approach is then successfully applied to a specific mortar in order to determine firstly its mechanical behaviour under tensile and compression loadings and secondly the evolution of its Young's modulus under the leaching phenomenon. This evolution is a key parameter since the leaching may be critical for the mechanical integrity of concrete structures such as radioactive waste storage systems in which cement-based materials may be largely used. The numerical results of the modelling are consistent with the experimental ones.

  4. A multi-scale strategy for discovery of novel endogenous neuropeptides in the crustacean nervous system.

    PubMed

    Jia, Chenxi; Lietz, Christopher B; Ye, Hui; Hui, Limei; Yu, Qing; Yoo, Sujin; Li, Lingjun

    2013-10-08

    The conventional mass spectrometry (MS)-based strategy is often inadequate for the comprehensive characterization of various size neuropeptides without the assistance of genomic information. This study evaluated sequence coverage of different size neuropeptides in two crustacean species, blue crab Callinectes sapidus and Jonah crab Cancer borealis using conventional MS methodologies and revealed limitations to mid- and large-size peptide analysis. Herein we attempt to establish a multi-scale strategy for simultaneous and confident sequence elucidation of various sizes of peptides in the crustacean nervous system. Nine novel neuropeptides spanning a wide range of molecular weights (0.9-8.2kDa) were fully sequenced from a major neuroendocrine organ, the sinus gland of the spiny lobster Panulirus interruptus. These novel neuropeptides included seven allatostatin (A- and B-type) peptides, one crustacean hyperglycemic hormone precursor-related peptide, and one crustacean hyperglycemic hormone. Highly accurate multi-scale characterization of a collection of varied size neuropeptides was achieved by integrating traditional data-dependent tandem MS, improved bottom-up sequencing, multiple fragmentation technique-enabled top-down sequencing, chemical derivatization, and in silico homology search. Collectively, the ability to characterize a neuropeptidome with vastly differing molecule sizes from a neural tissue extract could find great utility in unraveling complex signaling peptide mixtures employed by other biological systems. Mass spectrometry (MS)-based neuropeptidomics aims to completely characterize the neuropeptides in a target organism as an important first step toward a better understanding of the structure and function of these complex signaling molecules. Although liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) with data-dependent acquisition is a powerful tool in peptidomic research, it often lacks the capability for de novo sequencing of

  5. Using CellML with OpenCMISS to Simulate Multi-Scale Physiology

    PubMed Central

    Nickerson, David P.; Ladd, David; Hussan, Jagir R.; Safaei, Soroush; Suresh, Vinod; Hunter, Peter J.; Bradley, Christopher P.

    2014-01-01

    OpenCMISS is an open-source modeling environment aimed, in particular, at the solution of bioengineering problems. OpenCMISS consists of two main parts: a computational library (OpenCMISS-Iron) and a field manipulation and visualization library (OpenCMISS-Zinc). OpenCMISS is designed for the solution of coupled multi-scale, multi-physics problems in a general-purpose parallel environment. CellML is an XML format designed to encode biophysically based systems of ordinary differential equations and both linear and non-linear algebraic equations. A primary design goal of CellML is to allow mathematical models to be encoded in a modular and reusable format to aid reproducibility and interoperability of modeling studies. In OpenCMISS, we make use of CellML models to enable users to configure various aspects of their multi-scale physiological models. This avoids the need for users to be familiar with the OpenCMISS internal code in order to perform customized computational experiments. Examples of this are: cellular electrophysiology models embedded in tissue electrical propagation models; material constitutive relationships for mechanical growth and deformation simulations; time-varying boundary conditions for various problem domains; and fluid constitutive relationships and lumped-parameter models. In this paper, we provide implementation details describing how CellML models are integrated into multi-scale physiological models in OpenCMISS. The external interface OpenCMISS presents to users is also described, including specific examples exemplifying the extensibility and usability these tools provide the physiological modeling and simulation community. We conclude with some thoughts on future extension of OpenCMISS to make use of other community developed information standards, such as FieldML, SED-ML, and BioSignalML. Plans for the integration of accelerator code (graphical processing unit and field programmable gate array) generated from CellML models is also

  6. Using CellML with OpenCMISS to Simulate Multi-Scale Physiology.

    PubMed

    Nickerson, David P; Ladd, David; Hussan, Jagir R; Safaei, Soroush; Suresh, Vinod; Hunter, Peter J; Bradley, Christopher P

    2014-01-01

    OpenCMISS is an open-source modeling environment aimed, in particular, at the solution of bioengineering problems. OpenCMISS consists of two main parts: a computational library (OpenCMISS-Iron) and a field manipulation and visualization library (OpenCMISS-Zinc). OpenCMISS is designed for the solution of coupled multi-scale, multi-physics problems in a general-purpose parallel environment. CellML is an XML format designed to encode biophysically based systems of ordinary differential equations and both linear and non-linear algebraic equations. A primary design goal of CellML is to allow mathematical models to be encoded in a modular and reusable format to aid reproducibility and interoperability of modeling studies. In OpenCMISS, we make use of CellML models to enable users to configure various aspects of their multi-scale physiological models. This avoids the need for users to be familiar with the OpenCMISS internal code in order to perform customized computational experiments. Examples of this are: cellular electrophysiology models embedded in tissue electrical propagation models; material constitutive relationships for mechanical growth and deformation simulations; time-varying boundary conditions for various problem domains; and fluid constitutive relationships and lumped-parameter models. In this paper, we provide implementation details describing how CellML models are integrated into multi-scale physiological models in OpenCMISS. The external interface OpenCMISS presents to users is also described, including specific examples exemplifying the extensibility and usability these tools provide the physiological modeling and simulation community. We conclude with some thoughts on future extension of OpenCMISS to make use of other community developed information standards, such as FieldML, SED-ML, and BioSignalML. Plans for the integration of accelerator code (graphical processing unit and field programmable gate array) generated from CellML models is also

  7. Multi-scale, tailor-made heart simulation can predict the effect of cardiac resynchronization therapy.

    PubMed

    Okada, Jun-Ichi; Washio, Takumi; Nakagawa, Machiko; Watanabe, Masahiro; Kadooka, Yoshimasa; Kariya, Taro; Yamashita, Hiroshi; Yamada, Yoko; Momomura, Shin-Ichi; Nagai, Ryozo; Hisada, Toshiaki; Sugiura, Seiryo

    2017-07-01

    The currently proposed criteria for identifying patients who would benefit from cardiac resynchronization therapy (CRT) still need to be optimized. A multi-scale heart simulation capable of reproducing the electrophysiology and mechanics of a beating heart may help resolve this problem. The objective of this retrospective study was to test the capability of patient-specific simulation models to reproduce the response to CRT by applying the latest multi-scale heart simulation technology. We created patient-specific heart models with realistic three-dimensional morphology based on the clinical data recorded before treatment in nine patients with heart failure and conduction block treated by biventricular pacing. Each model was tailored to reproduce the surface electrocardiogram and hemodynamics of each patient in formats similar to those used in clinical practice, including electrocardiography (ECG), echocardiography, and hemodynamic measurements. We then performed CRT simulation on each heart model according to the actual pacing protocol and compared the results with the clinical data. CRT simulation improved the ECG index and diminished wall motion dyssynchrony in each patient. These results, however, did not correlate with the actual response. The best correlation was obtained between the maximum value of the time derivative of ventricular pressure (dP/dtmax) and the clinically observed improvement in the ejection fraction (EF) (r=0.94, p<0.01). By integrating the complex pathophysiology of the heart, patient-specific, multi-scale heart simulation could successfully reproduce the response to CRT. With further verification, this technique could be a useful tool in clinical decision making. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  8. Calculating distribution coefficients based on multi-scale free energy simulations: an evaluation of MM and QM/MM explicit solvent simulations of water-cyclohexane transfer in the SAMPL5 challenge

    NASA Astrophysics Data System (ADS)

    König, Gerhard; Pickard, Frank C.; Huang, Jing; Simmonett, Andrew C.; Tofoleanu, Florentina; Lee, Juyong; Dral, Pavlo O.; Prasad, Samarjeet; Jones, Michael; Shao, Yihan; Thiel, Walter; Brooks, Bernard R.

    2016-11-01

    One of the central aspects of biomolecular recognition is the hydrophobic effect, which is experimentally evaluated by measuring the distribution coefficients of compounds between polar and apolar phases. We use our predictions of the distribution coefficients between water and cyclohexane from the SAMPL5 challenge to estimate the hydrophobicity of different explicit solvent simulation techniques. Based on molecular dynamics trajectories with the CHARMM General Force Field, we compare pure molecular mechanics (MM) with quantum-mechanical (QM) calculations based on QM/MM schemes that treat the solvent at the MM level. We perform QM/MM with both density functional theory (BLYP) and semi-empirical methods (OM1, OM2, OM3, PM3). The calculations also serve to test the sensitivity of partition coefficients to solute polarizability as well as the interplay of the quantum-mechanical region with the fixed-charge molecular mechanics environment. Our results indicate that QM/MM with both BLYP and OM2 outperforms pure MM. However, this observation is limited to a subset of cases where convergence of the free energy can be achieved.

  9. Mixing in 3D Sparse Multi-Scale Grid Generated Turbulence

    NASA Astrophysics Data System (ADS)

    Usama, Syed; Kopec, Jacek; Tellez, Jackson; Kwiatkowski, Kamil; Redondo, Jose; Malik, Nadeem

    2017-04-01

    Flat 2D fractal grids are known to alter turbulence characteristics downstream of the grid as compared to the regular grids with the same blockage ratio and the same mass inflow rates [1]. This has excited interest in the turbulence community for possible exploitation for enhanced mixing and related applications. Recently, a new 3D multi-scale grid design has been proposed [2] such that each generation of length scale of turbulence grid elements is held in its own frame, the overall effect is a 3D co-planar arrangement of grid elements. This produces a 'sparse' grid system whereby each generation of grid elements produces a turbulent wake pattern that interacts with the other wake patterns downstream. A critical motivation here is that the effective blockage ratio in the 3D Sparse Grid Turbulence (3DSGT) design is significantly lower than in the flat 2D counterpart - typically the blockage ratio could be reduced from say 20% in 2D down to 4% in the 3DSGT. If this idea can be realized in practice, it could potentially greatly enhance the efficiency of turbulent mixing and transfer processes clearly having many possible applications. Work has begun on the 3DSGT experimentally using Surface Flow Image Velocimetry (SFIV) [3] at the European facility in the Max Planck Institute for Dynamics and Self-Organization located in Gottingen, Germany and also at the Technical University of Catalonia (UPC) in Spain, and numerically using Direct Numerical Simulation (DNS) at King Fahd University of Petroleum & Minerals (KFUPM) in Saudi Arabia and in University of Warsaw in Poland. DNS is the most useful method to compare the experimental results with, and we are studying different types of codes such as Imcompact3d, and OpenFoam. Many variables will eventually be investigated for optimal mixing conditions. For example, the number of scale generations, the spacing between frames, the size ratio of grid elements, inflow conditions, etc. We will report upon the first set of findings

  10. The Parameterization of Top-Hat Particle Sensors with Microchannel-Plate-Based Detection Systems and its Application to the Fast Plasma Investigation on NASA's Magnetospheric MultiScale Mission

    NASA Technical Reports Server (NTRS)

    Gershman, Daniel J.; Gliese, Ulrik; Dorelli, John C.; Avanov, Levon A.; Barrie, Alexander C.; Chornay, Dennis J.; MacDonald, Elizabeth A.; Holland, Matthew P.; Pollock, Craig J.

    2015-01-01

    The most common instrument for low energy plasmas consists of a top-hat electrostatic analyzer geometry coupled with a microchannel-plate (MCP)-based detection system. While the electrostatic optics for such sensors are readily simulated and parameterized during the laboratory calibration process, the detection system is often less well characterized. Furthermore, due to finite resources, for large sensor suites such as the Fast Plasma Investigation (FPI) on NASA's Magnetospheric Multiscale (MMS) mission, calibration data are increasingly sparse. Measurements must be interpolated and extrapolated to understand instrument behavior for untestable operating modes and yet sensor inter-calibration is critical to mission success. To characterize instruments from a minimal set of parameters we have developed the first comprehensive mathematical description of both sensor electrostatic optics and particle detection systems. We include effects of MCP efficiency, gain, scattering, capacitive crosstalk, and charge cloud spreading at the detector output. Our parameterization enables the interpolation and extrapolation of instrument response to all relevant particle energies, detector high voltage settings, and polar angles from a small set of calibration data. We apply this model to the 32 sensor heads in the Dual Electron Sensor (DES) and 32 sensor heads in the Dual Ion Sensor (DIS) instruments on the 4 MMS observatories and use least squares fitting of calibration data to extract all key instrument parameters. Parameters that will evolve in flight, namely MCP gain, will be determined daily through application of this model to specifically tailored in-flight calibration activities, providing a robust characterization of sensor suite performance throughout mission lifetime. Beyond FPI, our model provides a valuable framework for the simulation and evaluation of future detection system designs and can be used to maximize instrument understanding with minimal calibration

  11. Dual-wavelength retinal image registration based on vessel segmentation and optic disc detection

    NASA Astrophysics Data System (ADS)

    Xian, Yong-li; Dai, Yun; Gao, Chun-ming; Du, Rui

    2016-09-01

    The dual-wavelength retinal image registration is one of the critical steps in the spectrophotometric measurements of oxygen saturation in the retinal vasculature. The dual-wavelength images (570 nm and 600 nm) are simultaneously captured by dual-wavelength retinal oximeter based on commercial fundus camera. The retinal oxygen saturation is finally measured after vessel segmentation, image registration and calculation of optical density ratio of the two images. Because the dual-wavelength images are acquired from different optical path, it is necessary to go through image registration before they are used to analyze the oxygen saturation. This paper presents a new approach to dual-wavelength retinal image registration based on vessel segmentation and optic disc detection. Firstly, the multi-scale segmentation algorithm based on the Hessian matrix is used to realize vessel segmentation. Secondly, after optic disc is detected by convergence index filter and the center of the optic disc is obtained by centriod algorithm, the translational difference between the images can be determined. The center of the optic disc is used as the center of rotation, and the registration based on mutual information can be achieved using contour and gray information of vessels through segmented image. So the rotational difference between the images can be determined too. The result shows that the algorithm can provide an accurate registration for the dual-wavelength retinal image.

  12. Multi-Scale Modeling of Hypersonic Gas Flow

    NASA Astrophysics Data System (ADS)

    Boyd, Iain D.

    On March 27, 2004, NASA successfully flew the X-43A hypersonic test flight vehicle at a velocity of 5000 mph to break the aeronautics speed record that had stood for over 35 years. The final flight of the X-43A on November 16, 2004 further increased the speed record to 6,600 mph which is almost ten times the speed of sound. The very high speed attainable by hypersonic airplanes could revolutionize air travel by dramatically reducing inter-continental flight times. For example, a hypersonic flight from New York to Sydney, Australia, a distance of 10,000 miles, would take less than 2 h. Reusable hypersonic vehicles are also being researched to significantly reduce the cost of access to space. Computer modeling of the gas flows around hypersonic vehicles will play a critical part in their development. This article discusses the conditions that can prevail in certain hypersonic gas flows that require a multi-scale modeling approach.

  13. A multi-scale approach to designing therapeutics for tuberculosis

    SciTech Connect

    Linderman, Jennifer J.; Cilfone, Nicholas A.; Pienaar, Elsje; Gong, Chang; Kirschner, Denise E.

    2015-04-20

    Approximately one third of the world’s population is infected with Mycobacterium tuberculosis. Limited information about how the immune system fights M. tuberculosis and what constitutes protection from the bacteria impact our ability to develop effective therapies for tuberculosis. We present an in vivo systems biology approach that integrates data from multiple model systems and over multiple length and time scales into a comprehensive multi-scale and multi-compartment view of the in vivo immune response to M. tuberculosis. Lastly, we describe computational models that can be used to study (a) immunomodulation with the cytokines tumor necrosis factor and interleukin 10, (b) oral and inhaled antibiotics, and (c) the effect of vaccination.

  14. A multi-scale approach to designing therapeutics for tuberculosis

    DOE PAGES

    Linderman, Jennifer J.; Cilfone, Nicholas A.; Pienaar, Elsje; ...

    2015-04-20

    Approximately one third of the world’s population is infected with Mycobacterium tuberculosis. Limited information about how the immune system fights M. tuberculosis and what constitutes protection from the bacteria impact our ability to develop effective therapies for tuberculosis. We present an in vivo systems biology approach that integrates data from multiple model systems and over multiple length and time scales into a comprehensive multi-scale and multi-compartment view of the in vivo immune response to M. tuberculosis. Lastly, we describe computational models that can be used to study (a) immunomodulation with the cytokines tumor necrosis factor and interleukin 10, (b) oralmore » and inhaled antibiotics, and (c) the effect of vaccination.« less

  15. A Goddard Multi-Scale Modeling System with Unified Physics

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo

    2008-01-01

    A multi-scale modeling system with unified physics has been developed at NASA Goddard Space Flight Center (GSFC). The system consists of an MMF, the coupled NASA Goddard finite-volume GCM (fvGCM) and Goddard Cumulus Ensemble model (GCE, a CRM); the state-of-the-art Weather Research and Forecasting model (WRF) and the stand alone GCE. These models can share the same microphysical schemes, radiation (including explicitly calculated cloud optical properties), and surface models that have been developed, improved and tested for different environments. The following is presented in this report: (1) a brief review of the GCE model and its applications on the impact of aerosols on deep precipitation processes, (2) the Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) a discussion on the Goddard WRF version (its developments and applications).

  16. Spatially Extended Networks with Singular Multi-scale Connectivity Patterns

    NASA Astrophysics Data System (ADS)

    Touboul, Jonathan

    2014-08-01

    The cortex is a very large network characterized by a complex connectivity including at least two scales: a microscopic scale at which the interconnections are non-specific and very dense, while macroscopic connectivity patterns connecting different regions of the brain at larger scale are extremely sparse. This motivates to analyze the behavior of networks with multiscale coupling, in which a neuron is connected to its nearest-neighbors where , and in which the probability of macroscopic connection between two neurons vanishes. These are called singular multi-scale connectivity patterns. We introduce a class of such networks and derive their continuum limit. We show convergence in law and propagation of chaos in the thermodynamic limit. The limit equation obtained is an intricate non-local McKean-Vlasov equation with delays which is universal with respect to the type of micro-circuits and macro-circuits involved.

  17. A Multi-scale Approach to Designing Therapeutics for Tuberculosis

    PubMed Central

    Linderman, Jennifer J.; Cilfone, Nicholas A.; Pienaar, Elsje; Gong, Chang; Kirschner, Denise E.

    2015-01-01

    Approximately one third of the world’s population is infected with Mycobacterium tuberculosis. Limited information about how the immune system fights M. tuberculosis and what constitutes protection from the bacteria impact our ability to develop effective therapies for tuberculosis. We present an in vivo systems biology approach that integrates data from multiple model systems and over multiple length and time scales into a comprehensive multi-scale and multi-compartment view of the in vivo immune response to M. tuberculosis. We describe computational models that can be used to study (a) immunomodulation with the cytokines tumor necrosis factor and interleukin 10, (b) oral and inhaled antibiotics, and (c) the effect of vaccination. PMID:25924949

  18. Multi-Scale Jacobi Method for Anderson Localization

    NASA Astrophysics Data System (ADS)

    Imbrie, John Z.

    2015-11-01

    A new KAM-style proof of Anderson localization is obtained. A sequence of local rotations is defined, such that off-diagonal matrix elements of the Hamiltonian are driven rapidly to zero. This leads to the first proof via multi-scale analysis of exponential decay of the eigenfunction correlator (this implies strong dynamical localization). The method has been used in recent work on many-body localization (Imbrie in On many-body localization for quantum spin chains, arXiv:1403.7837 , 2014).

  19. Multi-Scale Coupling in Ocean and Climate Modeling

    SciTech Connect

    Zhengyu Liu, Leslie Smith

    2009-08-14

    We have made significant progress on several projects aimed at understanding multi-scale dynamics in geophysical flows. Large-scale flows in the atmosphere and ocean are influenced by stable density stratification and rotation. The presence of stratification and rotation has important consequences through (i) the conservation of potential vorticity q = {omega} {center_dot} {del} {rho}, where {omega} is the total vorticity and {rho} is the density, and (ii) the existence of waves that affect the redistribution of energy from a given disturbance to the flow. Our research is centered on quantifying the effects of potential vorticity conservation and of wave interactions for the coupling of disparate time and space scales in the oceans and the atmosphere. Ultimately we expect the work to help improve predictive capabilities of atmosphere, ocean and climate modelers. The main findings of our research projects are described.

  20. Multi-scale traffic safety and operational performance study of large trucks on mountainous interstate highway.

    PubMed

    Chen, Suren; Chen, Feng; Wu, Jun

    2011-01-01

    In addition to multi-vehicle accidents, large trucks are also prone to single-vehicle accidents on the mountainous interstate highways due to the complex terrain and fast-changing weather. By integrating both historical data analysis and simulations, a multi-scale approach is developed to evaluate the traffic safety and operational performance of large trucks on mountainous interstate highways in both scales of individual vehicle as well as traffic on the whole highway. A typical mountainous highway in Colorado is studied for demonstration purposes. Firstly, the ten-year historical accident records are analyzed to identify the accident-vulnerable-locations (AVLs) and site-specific critical adverse driving conditions. Secondly, simulation-based single-vehicle assessment is performed for different driving conditions at those AVLs along the whole corridor. Finally, the cellular-automaton (CA)-based simulation is carried out to evaluate the multi-vehicle traffic safety as well as the operational performance of the traffic by considering the actual speed limits, including the differential speed limits (DSL) at some locations. It is found that the multi-scale approach can provide insightful and comprehensive observations of the highway performance, which is especially important for mountainous highways.

  1. A theoretical foundation for multi-scale regular vegetation patterns.

    PubMed

    Tarnita, Corina E; Bonachela, Juan A; Sheffer, Efrat; Guyton, Jennifer A; Coverdale, Tyler C; Long, Ryan A; Pringle, Robert M

    2017-01-18

    Self-organized regular vegetation patterns are widespread and thought to mediate ecosystem functions such as productivity and robustness, but the mechanisms underlying their origin and maintenance remain disputed. Particularly controversial are landscapes of overdispersed (evenly spaced) elements, such as North American Mima mounds, Brazilian murundus, South African heuweltjies, and, famously, Namibian fairy circles. Two competing hypotheses are currently debated. On the one hand, models of scale-dependent feedbacks, whereby plants facilitate neighbours while competing with distant individuals, can reproduce various regular patterns identified in satellite imagery. Owing to deep theoretical roots and apparent generality, scale-dependent feedbacks are widely viewed as a unifying and near-universal principle of regular-pattern formation despite scant empirical evidence. On the other hand, many overdispersed vegetation patterns worldwide have been attributed to subterranean ecosystem engineers such as termites, ants, and rodents. Although potentially consistent with territorial competition, this interpretation has been challenged theoretically and empirically and (unlike scale-dependent feedbacks) lacks a unifying dynamical theory, fuelling scepticism about its plausibility and generality. Here we provide a general theoretical foundation for self-organization of social-insect colonies, validated using data from four continents, which demonstrates that intraspecific competition between territorial animals can generate the large-scale hexagonal regularity of these patterns. However, this mechanism is not mutually exclusive with scale-dependent feedbacks. Using Namib Desert fairy circles as a case study, we present field data showing that these landscapes exhibit multi-scale patterning-previously undocumented in this system-that cannot be explained by either mechanism in isolation. These multi-scale patterns and other emergent properties, such as enhanced resistance to

  2. The information extraction of Gannan citrus orchard based on the GF-1 remote sensing image

    NASA Astrophysics Data System (ADS)

    Wang, S.; Chen, Y. L.

    2017-02-01

    The production of Gannan oranges is the largest in China, which occupied an important part in the world. The extraction of citrus orchard quickly and effectively has important significance for fruit pathogen defense, fruit production and industrial planning. The traditional spectra extraction method of citrus orchard based on pixel has a lower classification accuracy, difficult to avoid the “pepper phenomenon”. In the influence of noise, the phenomenon that different spectrums of objects have the same spectrum is graveness. Taking Xunwu County citrus fruit planting area of Ganzhou as the research object, aiming at the disadvantage of the lower accuracy of the traditional method based on image element classification method, a decision tree classification method based on object-oriented rule set is proposed. Firstly, multi-scale segmentation is performed on the GF-1 remote sensing image data of the study area. Subsequently the sample objects are selected for statistical analysis of spectral features and geometric features. Finally, combined with the concept of decision tree classification, a variety of empirical values of single band threshold, NDVI, band combination and object geometry characteristics are used hierarchically to execute the information extraction of the research area, and multi-scale segmentation and hierarchical decision tree classification is implemented. The classification results are verified with the confusion matrix, and the overall Kappa index is 87.91%.

  3. The registration of dual-modality ship target images based on edge extraction

    NASA Astrophysics Data System (ADS)

    Zhang, Weimin; Wang, Risheng; Zhou, Fugen

    2014-11-01

    In this paper, we study the problem of visible and IR(infrared) ship target image registration with scale changes. We mainly focus on the infrared and visible image feature extraction and matching method. A method based on Force Field Transformation is used to determine the ship target contour area. Canny edge detection method is applied to obtain the edge features. During the process of image registration, we take the cross-correlation as the similarity measure and propose an improved Powell algorithm based on multi-scale searching to optimize the registration parameters. Through the edge fusion results, we can see the corresponding edges are almost overlapped, indicating that the method could achieve satisfying results. Also the average error distance of match is less than one pixel.

  4. Fusion of infrared and visible images based on BEMD and NSDFB

    NASA Astrophysics Data System (ADS)

    Zhu, Pan; Huang, Zhanhua; Lei, Hai

    2016-07-01

    This paper presents a new fusion method based on the adaptive multi-scale decomposition of bidimensional empirical mode decomposition (BEMD) and the flexible directional expansion of nonsubsampled directional filter banks (NSDFB) for visible-infrared images. Compared with conventional multi-scale fusion methods, BEMD is non-parametric and completely data-driven, which is relatively more suitable for non-linear signals decomposition and fusion. NSDFB can provide direction filtering on the decomposition levels to capture more geometrical structure of the source images effectively. In our fusion framework, the entropies of the two patterns of source images are firstly calculated and the residue of the image whose entropy is larger is extracted to make it highly relevant with the other source image. Then, the residue and the other source image are decomposed into low-frequency sub-bands and a sequence of high-frequency directional sub-bands in different scales by using BEMD and NSDFB. In this fusion scheme, two relevant fusion rules are used in low-frequency sub-bands and high-frequency directional sub-bands, respectively. Finally, the fused image is obtained by applying corresponding inverse transform. Experimental results indicate that the proposed fusion algorithm can obtain state-of-the-art performance for visible-infrared images fusion in both aspects of objective assessment and subjective visual quality even for the source images obtained in different conditions. Furthermore, the fused results have high contrast, remarkable target information and rich details information that are more suitable for human visual characteristics or machine perception.

  5. Multi-scale optimal interpolation: application to DINEOF analysis spiced with a local optimal interpolation

    NASA Astrophysics Data System (ADS)

    Beckers, J.-M.; Barth, A.; Tomazic, I.; Alvera-Azcárate, A.

    2014-03-01

    We present a method in which the optimal interpolation of multi-scale processes can be untangled into a succession of simpler interpolations. First, we prove how the optimal analysis of a superposition of two processes can be obtained by different mathematical formulations involving iterations and analysis focusing on a single process. From the different mathematical equivalent formulations we then select the most efficient ones by analyzing the behavior of the different possibilities in a simple and well controlled test case. The clear guidelines deduced from this experiment are then applied in a real situation in which we combine large-scale analysis of hourly SEVIRI satellite images using DINEOF with a local optimal interpolation using a Gaussian covariance. It is shown that the optimal combination indeed provides the best reconstruction and can therefore be exploited to extract the maximum amount of useful information from the original data.

  6. Multi-scale engineering of plant cell cultures for promotion of specialized metabolism.

    PubMed

    Wilson, Sarah A; Cummings, Elizabeth M; Roberts, Susan C

    2014-10-01

    To establish plant culture systems for product synthesis, a multi-scale engineering approach is necessary. At the intracellular level, the influx of 'omics' data has necessitated development of new methods to properly annotate and establish useful metabolic models that can be applied to elucidate unknown steps in specialized metabolite biosynthesis, define effective metabolic engineering strategies and increase enzyme diversity available for synthetic biology platforms. On an intercellular level, the presence of aggregates in culture leads to distinct metabolic sub-populations. Recent advances in flow cytometric analyses and mass spectrometry imaging allow for resolution of metabolites on the single cell level, providing an increased understanding of culture heterogeneity. Finally, extracellular engineering can be used to enhance culture performance through media manipulation, co-culture with bacteria, the use of exogenous elicitors or modulation of shear stress. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. LinkRbrain: multi-scale data integrator of the brain.

    PubMed

    Mesmoudi, Salma; Rodic, Mathieu; Cioli, Claudia; Cointet, Jean-Philippe; Yarkoni, Tal; Burnod, Yves

    2015-02-15

    LinkRbrain is an open-access web platform for multi-scale data integration and visualization of human brain data. This platform integrates anatomical, functional, and genetic knowledge produced by the scientific community. The linkRbrain platform has two major components: (1) a data aggregation component that integrates multiple open databases into a single platform with a unified representation; and (2) a website that provides fast multi-scale integration and visualization of these data and makes the results immediately available. LinkRbrain allows users to visualize functional networks or/and genetic expression over a standard brain template (MNI152). Interrelationships between these components based on topographical overlap are displayed using relational graphs. Moreover, linkRbrain enables comparison of new experimental results with previous published works. Previous tools and studies illustrate the opportunities of data mining across multiple tiers of neuroscience and genetic information. However, a global systematic approach is still missing to gather cognitive, topographical, and genetic knowledge in a common framework in order to facilitate their visualization, comparison, and integration. LinkRbrain is an efficient open-access tool that affords an integrative understanding of human brain function. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. Predicting the roughness length of turbulent flows over landscapes with multi-scale microtopography

    NASA Astrophysics Data System (ADS)

    Pelletier, Jon D.; Field, Jason P.

    2016-05-01

    The fully rough form of the law of the wall is commonly used to quantify velocity profiles and associated bed shear stresses in fluvial, aeolian, and coastal environments. A key parameter in this law is the roughness length, z0. Here we propose a predictive formula for z0 that uses the amplitude and slope of each wavelength of microtopography within a discrete-Fourier-transform-based approach. Computational fluid dynamics (CFD) modeling is used to quantify the effective z0 value of sinusoidal microtopography as a function of the amplitude and slope. The effective z0 value of landscapes with multi-scale roughness is then given by the sum of contributions from each Fourier mode of the microtopography. Predictions of the equation are tested against z0 values measured in ˜ 105 wind-velocity profiles from southwestern US playa surfaces. Our equation is capable of predicting z0 values to 50 % accuracy, on average, across a 4 order of magnitude range. We also use our results to provide an alternative formula that, while somewhat less accurate than the one obtained from a full multi-scale analysis, has an advantage of being simpler and easier to apply.

  9. A hybrid multi-scale computational scheme for advection-diffusion-reaction equation

    NASA Astrophysics Data System (ADS)

    Karimi, S.; Nakshatrala, K. B.

    2016-12-01

    Simulation of transport and reaction processes in porous media and subsurface science has become more vital than ever. Over the past few decades, a variety of mathematical models and numerical methodologies for porous media simulations have been developed. As the demand for higher accuracy and validity of the models grows, the issue of disparate temporal and spatial scales becomes more problematic. The variety of reaction processes and complexity of pore geometry poses a huge computational burden in a real-world or reservoir scale simulation. Meanwhile, methods based on averaging or up- scaling techniques do not provide reliable estimates to pore-scale processes. To overcome this problem, development of hybrid and multi-scale computational techniques is considered a promising approach. In these methods, pore-scale and continuum-scale models are combined, hence, a more reliable estimate to pore-scale processes is obtained without having to deal with the tremendous computational overhead of pore-scale methods. In this presentation, we propose a computational framework that allows coupling of lattice Boltzmann method (for pore-scale simulation) and finite element method (for continuum-scale simulation) for advection-diffusion-reaction equations. To capture disparate in time and length events, non-matching grid and time-steps are allowed. Apart from application of this method to benchmark problems, multi-scale simulation of chemical reactions in porous media is also showcased.

  10. Development of Multi-Scale Finite Element Analysis Codes for High Formability Sheet Metal Generation

    SciTech Connect

    Nnakamachi, Eiji; Kuramae, Hiroyuki; Ngoc Tam, Nguyen; Nakamura, Yasunori; Sakamoto, Hidetoshi; Morimoto, Hideo

    2007-05-17

    In this study, the dynamic- and static-explicit multi-scale finite element (F.E.) codes are developed by employing the homogenization method, the crystalplasticity constitutive equation and SEM-EBSD measurement based polycrystal model. These can predict the crystal morphological change and the hardening evolution at the micro level, and the macroscopic plastic anisotropy evolution. These codes are applied to analyze the asymmetrical rolling process, which is introduced to control the crystal texture of the sheet metal for generating a high formability sheet metal. These codes can predict the yield surface and the sheet formability by analyzing the strain path dependent yield, the simple sheet forming process, such as the limit dome height test and the cylindrical deep drawing problems. It shows that the shear dominant rolling process, such as the asymmetric rolling, generates ''high formability'' textures and eventually the high formability sheet. The texture evolution and the high formability of the newly generated sheet metal experimentally were confirmed by the SEM-EBSD measurement and LDH test. It is concluded that these explicit type crystallographic homogenized multi-scale F.E. code could be a comprehensive tool to predict the plastic induced texture evolution, anisotropy and formability by the rolling process and the limit dome height test analyses.

  11. Accelerating electrostatic surface potential calculation with multi-scale approximation on graphics processing units.

    PubMed

    Anandakrishnan, Ramu; Scogland, Tom R W; Fenley, Andrew T; Gordon, John C; Feng, Wu-chun; Onufriev, Alexey V

    2010-06-01

    Tools that compute and visualize biomolecular electrostatic surface potential have been used extensively for studying biomolecular function. However, determining the surface potential for large biomolecules on a typical desktop computer can take days or longer using currently available tools and methods. Two commonly used techniques to speed-up these types of electrostatic computations are approximations based on multi-scale coarse-graining and parallelization across multiple processors. This paper demonstrates that for the computation of electrostatic surface potential, these two techniques can be combined to deliver significantly greater speed-up than either one separately, something that is in general not always possible. Specifically, the electrostatic potential computation, using an analytical linearized Poisson-Boltzmann (ALPB) method, is approximated using the hierarchical charge partitioning (HCP) multi-scale method, and parallelized on an ATI Radeon 4870 graphical processing unit (GPU). The implementation delivers a combined 934-fold speed-up for a 476,040 atom viral capsid, compared to an equivalent non-parallel implementation on an Intel E6550 CPU without the approximation. This speed-up is significantly greater than the 42-fold speed-up for the HCP approximation alone or the 182-fold speed-up for the GPU alone.

  12. 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.

  13. No-reference multiscale blur detection tool for content based image retrieval

    NASA Astrophysics Data System (ADS)

    Ezekiel, Soundararajan; Stocker, Russell; Harrity, Kyle; Alford, Mark; Ferris, David; Blasch, Erik; Gorniak, Mark

    2014-06-01

    In recent years, digital cameras have been widely used for image capturing. These devices are equipped in cell phones, laptops, tablets, webcams, etc. Image quality is an important component of digital image analysis. To assess image quality for these mobile products, a standard image is required as a reference image. In this case, Root Mean Square Error and Peak Signal to Noise Ratio can be used to measure the quality of the images. However, these methods are not possible if there is no reference image. In our approach, a discrete-wavelet transformation is applied to the blurred image, which decomposes into the approximate image and three detail sub-images, namely horizontal, vertical, and diagonal images. We then focus on noise-measuring the detail images and blur-measuring the approximate image to assess the image quality. We then compute noise mean and noise ratio from the detail images, and blur mean and blur ratio from the approximate image. The Multi-scale Blur Detection (MBD) metric provides both an assessment of the noise and blur content. These values are weighted based on a linear regression against full-reference y values. From these statistics, we can compare to normal useful image statistics for image quality without needing a reference image. We then test the validity of our obtained weights by R2 analysis as well as using them to estimate image quality of an image with a known quality measure. The result shows that our method provides acceptable results for images containing low to mid noise levels and blur content.

  14. Bio-stimuli-responsive multi-scale hyaluronic acid nanoparticles for deepened tumor penetration and enhanced therapy.

    PubMed

    Huo, Mengmeng; Li, Wenyan; Chaudhuri, Arka Sen; Fan, Yuchao; Han, Xiu; Yang, Chen; Wu, Zhenghong; Qi, Xiaole

    2017-09-01

    In this study, we developed bio-stimuli-responsive multi-scale hyaluronic acid (HA) nanoparticles encapsulated with polyamidoamine (PAMAM) dendrimers as the subunits. These HA/PAMAM nanoparticles of large scale (197.10±3.00nm) were stable during systematic circulation then enriched at the tumor sites; however, they were prone to be degraded by the high expressed hyaluronidase (HAase) to release inner PAMAM dendrimers and regained a small scale (5.77±0.25nm) with positive charge. After employing tumor spheroids penetration assay on A549 3D tumor spheroids for 8h, the fluorescein isothiocyanate (FITC) labeled multi-scale HA/PAMAM-FITC nanoparticles could penetrate deeply into these tumor spheroids with the degradation of HAase. Moreover, small animal imaging technology in male nude mice bearing H22 tumor showed HA/PAMAM-FITC nanoparticles possess higher prolonged systematic circulation compared with both PAMAM-FITC nanoparticles and free FITC. In addition, after intravenous administration in mice bearing H22 tumors, methotrexate (MTX) loaded multi-scale HA/PAMAM-MTX nanoparticles exhibited a 2.68-fold greater antitumor activity. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Simultaneous multi-scale registration using large deformation diffeomorphic metric mapping.

    PubMed

    Risser, Laurent; Vialard, François-Xavier; Wolz, Robin; Murgasova, Maria; Holm, Darryl D; Rueckert, Daniel

    2011-10-01

    In the framework of large deformation diffeomorphic metric mapping (LDDMM), we present a practical methodology to integrate prior knowledge about the registered shapes in the regularizing metric. Our goal is to perform rich anatomical shape comparisons from volumetric images with the mathematical properties offered by the LDDMM framework. We first present the notion of characteristic scale at which image features are deformed. We then propose a methodology to compare anatomical shape variations in a multi-scale fashion, i.e., at several characteristic scales simultaneously. In this context, we propose a strategy to quantitatively measure the feature differences observed at each characteristic scale separately. After describing our methodology, we illustrate the performance of the method on phantom data. We then compare the ability of our method to segregate a group of subjects having Alzheimer's disease and a group of controls with a classical coarse to fine approach, on standard 3D MR longitudinal brain images. We finally apply the approach to quantify the anatomical development of the human brain from 3D MR longitudinal images of pre-term babies. Results show that our method registers accurately volumetric images containing feature differences at several scales simultaneously with smooth deformations. © 2011 British Crown Copyright

  16. Analysis of Atmospheric Flow in Mountainous Terrain Using Multi-Scale Observations and Dimension-Reduction Techniques

    NASA Astrophysics Data System (ADS)

    Zeeman, M. J.; Banerjee, T.; Belusic, D.; Brugger, P.; Mauder, M.; Vercauteren, N.

    2016-12-01

    Observations that link multi-scale Boundary layer processes to land-atmosphere exchange of matter and energy are needed for the calibration and verification earth-system models. The intermittent, mixed and spatially heterogeneous nature of some (sub-)mesoscale processes in the surface boundary layer makes their identification and characterization very challenging. The challenges lie in the current experimental state-of-the-art as well as the tools to analyze spatially explicit time series. Of particular interest are methodologies that complement the widely adopted eddy covariance (EC) technique in separating turbulent and non-turbulent motion from high-frequency time series, especially in stable conditions. We tested novel methodologies for the detection and quantification of mode-shifts and events in flow on novel spatially explicit observations of the velocity field and temperature structures at the ICOS/TERENO observatory Fendt in mountainous terrain in southern Germany. The multi-scale observations include wind field observations from a triple Doppler-lidar network (0.01 to 1km3) in tandem with high-resolution fibre-optic and thermal image temperature velocimetry (.2 to 220m). The analyses rely on signal decomposition and statistical clustering to characterize (non-)turbulent motions and their feedback on turbulent mixing, without prior knowledge of the multi-scale nature of the process that generated such events. The achieved dimension reduction facilitates the application of such diverse, multi-scale experimental data and the study of turbulent mixing processes. We discuss how such novel observations and analysis tools can help improve our understanding of boundary-layer processes and the interaction near the surface in real-life, non-idealized situations.

  17. Modelling strategies to predict the multi-scale effects of rural land management change

    NASA Astrophysics Data System (ADS)

    Bulygina, N.; Ballard, C. E.; Jackson, B. M.; McIntyre, N.; Marshall, M.; Reynolds, B.; Wheater, H. S.

    2011-12-01

    Changes to the rural landscape due to agricultural land management are ubiquitous, yet predicting the multi-scale effects of land management change on hydrological response remains an important scientific challenge. Much empirical research has been of little generic value due to inadequate design and funding of monitoring programmes, while the modelling issues challenge the capability of data-based, conceptual and physics-based modelling approaches. In this paper we report on a major UK research programme, motivated by a national need to quantify effects of agricultural intensification on flood risk. Working with a consortium of farmers in upland Wales, a multi-scale experimental programme (from experimental plots to 2nd order catchments) was developed to address issues of upland agricultural intensification. This provided data support for a multi-scale modelling programme, in which highly detailed physics-based models were conditioned on the experimental data and used to explore effects of potential field-scale interventions. A meta-modelling strategy was developed to represent detailed modelling in a computationally-efficient manner for catchment-scale simulation; this allowed catchment-scale quantification of potential management options. For more general application to data-sparse areas, alternative approaches were needed. Physics-based models were developed for a range of upland management problems, including the restoration of drained peatlands, afforestation, and changing grazing practices. Their performance was explored using literature and surrogate data; although subject to high levels of uncertainty, important insights were obtained, of practical relevance to management decisions. In parallel, regionalised conceptual modelling was used to explore the potential of indices of catchment response, conditioned on readily-available catchment characteristics, to represent ungauged catchments subject to land management change. Although based in part on

  18. Software Integration in Multi-scale Simulations: the PUPIL System

    NASA Astrophysics Data System (ADS)

    Torras, J.; Deumens, E.; Trickey, S. B.

    2006-10-01

    The state of the art for computational tools in both computational chemistry and computational materials physics includes many algorithms and functionalities which are implemented again and again. Several projects aim to reduce, eliminate, or avoid this problem. Most such efforts seem to be focused within a particular specialty, either quantum chemistry or materials physics. Multi-scale simulations, by their very nature however, cannot respect that specialization. In simulation of fracture, for example, the energy gradients that drive the molecular dynamics (MD) come from a quantum mechanical treatment that most often derives from quantum chemistry. That “QM” region is linked to a surrounding “CM” region in which potentials yield the forces. The approach therefore requires the integration or at least inter-operation of quantum chemistry and materials physics algorithms. The same problem occurs in “QM/MM” simulations in computational biology. The challenge grows if pattern recognition or other analysis codes of some kind must be used as well. The most common mode of inter-operation is user intervention: codes are modified as needed and data files are managed “by hand” by the user (interactively and via shell scripts). User intervention is however inefficient by nature, difficult to transfer to the community, and prone to error. Some progress (e.g Sethna’s work at Cornell [C.R. Myers et al., Mat. Res. Soc. Symp. Proc., 538(1999) 509, C.-S. Chen et al., Poster presented at the Material Research Society Meeting (2000)]) has been made on using Python scripts to achieve a more efficient level of interoper