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Sample records for based multi-scale image

  1. Automatic image enhancement based on multi-scale image decomposition

    NASA Astrophysics Data System (ADS)

    Feng, Lu; Wu, Zhuangzhi; Pei, Luo; Long, Xiong

    2014-01-01

    In image processing and computational photography, automatic image enhancement is one of the long-range objectives. Recently the automatic image enhancement methods not only take account of the globe semantics, like correct color hue and brightness imbalances, but also the local content of the image, such as human face and sky of landscape. In this paper we describe a new scheme for automatic image enhancement that considers both global semantics and local content of image. Our automatic image enhancement method employs the multi-scale edge-aware image decomposition approach to detect the underexposure regions and enhance the detail of the salient content. The experiment results demonstrate the effectiveness of our approach compared to existing automatic enhancement methods.

  2. Multi-Scale Patch-Based Image Restoration.

    PubMed

    Papyan, Vardan; Elad, Michael

    2016-01-01

    Many image restoration algorithms in recent years are based on patch processing. The core idea is to decompose the target image into fully overlapping patches, restore each of them separately, and then merge the results by a plain averaging. This concept has been demonstrated to be highly effective, leading often times to the state-of-the-art results in denoising, inpainting, deblurring, segmentation, and other applications. While the above is indeed effective, this approach has one major flaw: the prior is imposed on intermediate (patch) results, rather than on the final outcome, and this is typically manifested by visual artifacts. The expected patch log likelihood (EPLL) method by Zoran and Weiss was conceived for addressing this very problem. Their algorithm imposes the prior on the patches of the final image, which in turn leads to an iterative restoration of diminishing effect. In this paper, we propose to further extend and improve the EPLL by considering a multi-scale prior. Our algorithm imposes the very same prior on different scale patches extracted from the target image. While all the treated patches are of the same size, their footprint in the destination image varies due to subsampling. Our scheme comes to alleviate another shortcoming existing in patch-based restoration algorithms--the fact that a local (patch-based) prior is serving as a model for a global stochastic phenomenon. We motivate the use of the multi-scale EPLL by restricting ourselves to the simple Gaussian case, comparing the aforementioned algorithms and showing a clear advantage to the proposed method. We then demonstrate our algorithm in the context of image denoising, deblurring, and super-resolution, showing an improvement in performance both visually and quantitatively. PMID:26571527

  3. 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.

  4. 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.

  5. An improved fusion algorithm for infrared and visible images based on multi-scale transform

    NASA Astrophysics Data System (ADS)

    Li, He; Liu, Lei; Huang, Wei; Yue, Chao

    2016-01-01

    In this paper, an improved fusion algorithm for infrared and visible images based on multi-scale transform is proposed. First of all, Morphology-Hat transform is used for an infrared image and a visible image separately. Then two images were decomposed into high-frequency and low-frequency images by contourlet transform (CT). The fusion strategy of high-frequency images is based on mean gradient and the fusion strategy of low-frequency images is based on Principal Component Analysis (PCA). Finally, the final fused image is obtained by using the inverse contourlet transform (ICT). The experiments and results demonstrate that the proposed method can significantly improve image fusion performance, accomplish notable target information and high contrast and preserve rich details information at the same time.

  6. Multi-scale image fusion for x-ray grating-based mammography

    NASA Astrophysics Data System (ADS)

    Jiang, Xiaolei; Zhang, Li; Wang, Zhentian; Stampanoni, Marco

    2012-10-01

    X-ray phase contrast imaging (PCI) can provide high sensitivity of weakly absorbing low-Z objects in medical and biological fields, especially in mammography. Grating-based differential phase contrast (DPC) method is the most potential PCI method for clinic applications because it can works well with conventional X-ray tube and it can retrieve attenuation, DPC and dark-field information of the samples in a single scanning. Three kinds of information have different details and contrast which represent different physical characteristics of X-rays with matters. Hence, image fusion can show the most desirable characteristics of each image. In this paper, we proposed a multi-scale image fusion for X-ray grating-based DPC mammography. Firstly, non-local means method is adopted for denoising due to the strong noise, especially for DPC and dark-field images. Then, Laplacian pyramid is used for multi-scale image fusion. The principal component analysis (PCA) method is used on the high frequency part and the spatial frequency method is used on the low frequency part. Finally, the fused image is obtained by inverse Laplacian pyramid transform. Our algorithm is validated by experiments. The experiments were performed on mammoDPC instrumentation at the Paul Scherrer Institut in Villigen, Switzerland. The results show that our algorithm can significantly show the advantages of three kinds of information in the fused image, which is very helpful for the breast cancer diagnosis.

  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. PMID:26409228

  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 texture-based level-set segmentation of breast B-mode images.

    PubMed

    Lang, Itai; Sklair-Levy, Miri; Spitzer, Hedva

    2016-05-01

    Automatic segmentation of ultrasonographic breast lesions is very challenging, due to the lesions' spiculated nature and the variance in shape and texture of the B-mode ultrasound images. Many studies have tried to answer this challenge by applying a variety of computational methods including: Markov random field, artificial neural networks, and active contours and level-set techniques. These studies focused on creating an automatic contour, with maximal resemblance to a manual contour, delineated by a trained radiologist. In this study, we have developed an algorithm, designed to capture the spiculated boundary of the lesion by using the properties from the corresponding ultrasonic image. This is primarily achieved through a unique multi-scale texture identifier (inspired by visual system models) integrated in a level-set framework. The algorithm׳s performance has been evaluated quantitatively via contour-based and region-based error metrics. We compared the algorithm-generated contour to a manual contour delineated by an expert radiologist. In addition, we suggest here a new method for performance evaluation where corrections made by the radiologist replace the algorithm-generated (original) result in the correction zones. The resulting corrected contour is then compared to the original version. The evaluation showed: (1) Mean absolute error of 0.5 pixels between the original and the corrected contour; (2) Overlapping area of 99.2% between the lesion regions, obtained by the algorithm and the corrected contour. These results are significantly better than those previously reported. In addition, we have examined the potential of our segmentation results to contribute to the discrimination between malignant and benign lesions. PMID:27010737

  10. Landslide mapping with multi-scale object-based image analysis - a case study in the Baichi watershed, Taiwan

    NASA Astrophysics Data System (ADS)

    Lahousse, T.; Chang, K. T.; Lin, Y. H.

    2011-10-01

    We developed a multi-scale OBIA (object-based image analysis) landslide detection technique to map shallow landslides in the Baichi watershed, Taiwan, after the 2004 Typhoon Aere event. Our semi-automated detection method selected multiple scales through landslide size statistics analysis for successive classification rounds. The detection performance achieved a modified success rate (MSR) of 86.5% with the training dataset and 86% with the validation dataset. This performance level was due to the multi-scale aspect of our methodology, as the MSR for single scale classification was substantially lower, even after spectral difference segmentation, with a maximum of 74%. Our multi-scale technique was capable of detecting landslides of varying sizes, including very small landslides, up to 95 m2. The method presented certain limitations: the thresholds we established for classification were specific to the study area, to the landslide type in the study area, and to the spectral characteristics of the satellite image. Because updating site-specific and image-specific classification thresholds is easy with OBIA software, our multi-scale technique is expected to be useful for mapping shallow landslides at watershed level.

  11. Object-Oriented Change Detection for Remote Sensing Images Based on Multi-Scale Fusion

    NASA Astrophysics Data System (ADS)

    Feng, Wenqing; Sui, Haigang; Tu, Jihui

    2016-06-01

    In the process of object-oriented change detection, the determination of the optimal segmentation scale is directly related to the subsequent change information extraction and analysis. Aiming at this problem, this paper presents a novel object-level change detection method based on multi-scale segmentation and fusion. First of all, the fine to coarse segmentation is used to obtain initial objects of different sizes; then, according to the features of the objects, Change Vector Analysis is used to obtain the change detection results of various scales. Furthermore, in order to improve the accuracy of change detection, this paper introduces fuzzy fusion and two kinds of decision level fusion methods to get the results of multi-scale fusion. Based on these methods, experiments are done with SPOT5 multi-spectral remote sensing imagery. Compared with pixel-level change detection methods, the overall accuracy of our method has been improved by nearly 10%, and the experimental results prove the feasibility and effectiveness of the fusion strategies.

  12. 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

  13. 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.

  14. Peripheral nerve enhancement based on multi-scale Hessian matrix

    NASA Astrophysics Data System (ADS)

    Ma, Xiuli; Li, Hui; Zhou, Xueli; Wan, Wanggen

    2011-06-01

    To improve the precision of nerve segmentation in CT images, a new comparability function is proposed in this paper to enhance the contrast between nerve structure and other surrounding tissues. It is based on nerve's characteristic, i.e. dark tubular structure, and a thorough analysis of the multi-scale Hessian matrix. By comparability function, the gray range of interested nerve structure can be automatically determined, which combines the multi-scale Hessian matrix eigenvalues with intensity information of original nerve CT images. The experimental results show that the improved algorithm can not only enhance the continuous nerve of tubular structure, but also clearly reflect its bifurcations and crossovers. It is very important and significant to the computer-aided disease diagnosis of peripheral nervous system.

  15. 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

  16. Multi-scale Heat Kernel based Volumetric Morphology Signature

    PubMed Central

    Wang, Gang; Wang, Yalin

    2015-01-01

    Here we introduce a novel multi-scale heat kernel based regional shape statistical approach that may improve statistical power on the structural analysis. The mechanism of this analysis is driven by the graph spectrum and the heat kernel theory, to capture the volumetric geometry information in the constructed tetrahedral mesh. In order to capture profound volumetric changes, we first use the volumetric Laplace-Beltrami operator to determine the point pair correspondence between two boundary surfaces by computing the streamline in the tetrahedral mesh. Secondly, we propose a multi-scale volumetric morphology signature to describe the transition probability by random walk between the point pairs, which reflects the inherent geometric characteristics. Thirdly, a point distribution model is applied to reduce the dimensionality of the volumetric morphology signatures and generate the internal structure features. The multi-scale and physics based internal structure features may bring stronger statistical power than other traditional methods for volumetric morphology analysis. To validate our method, we apply support vector machine to classify synthetic data and brain MR images. In our experiments, the proposed work outperformed FreeSurfer thickness features in Alzheimer's disease patient and normal control subject classification analysis. PMID:26550613

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

    PubMed Central

    2012-01-01

    Background Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. Method The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. Results The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice. PMID:22236465

  18. 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.

  19. Boundary-constrained multi-scale segmentation method for remote sensing images

    NASA Astrophysics Data System (ADS)

    Zhang, Xueliang; Xiao, Pengfeng; Song, Xiaoqun; She, Jiangfeng

    2013-04-01

    Image segmentation is the key step of Object-Based Image Analysis (OBIA) in remote sensing. This paper proposes a Boundary-Constrained Multi-Scale Segmentation (BCMS) method. Firstly, adjacent pixels are aggregated to generate initial segmentation according to the local best region growing strategy. Then, the Region Adjacency Graph (RAG) is built based on initial segmentation. Finally, the local mutual best region merging strategy is applied on RAG to produce multi-scale segmentation results. During the region merging process, a Step-Wise Scale Parameter (SWSP) strategy is proposed to produce boundary-constrained multi-scale segmentation results. Moreover, in order to improve the accuracy of object boundaries, the property of edge strength is introduced as a merging criterion. A set of high spatial resolution remote sensing images is used in the experiment, e.g., QuickBird, WorldView, and aerial image, to evaluate the effectiveness of the proposed method. The segmentation results of BCMS are compared with those of the commercial image analysis software eCognition. The experiment shows that BCMS can produce nested multi-scale segmentations with accurate and smooth boundaries, which proves the robustness of the proposed method.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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. PMID:26800540

  7. Single image dehazing by multi-scale fusion.

    PubMed

    Ancuti, Codruta Orniana; Ancuti, Cosmin

    2013-08-01

    Haze is an atmospheric phenomenon that significantly degrades the visibility of outdoor scenes. This is mainly due to the atmosphere particles that absorb and scatter the light. This paper introduces a novel single image approach that enhances the visibility of such degraded images. Our method is a fusion-based strategy that derives from two original hazy image inputs by applying a white balance and a contrast enhancing procedure. To blend effectively the information of the derived inputs to preserve the regions with good visibility, we filter their important features by computing three measures (weight maps): luminance, chromaticity, and saliency. To minimize artifacts introduced by the weight maps, our approach is designed in a multiscale fashion, using a Laplacian pyramid representation. We are the first to demonstrate the utility and effectiveness of a fusion-based technique for dehazing based on a single degraded image. The method performs in a per-pixel fashion, which is straightforward to implement. The experimental results demonstrate that the method yields results comparative to and even better than the more complex state-of-the-art techniques, having the advantage of being appropriate for real-time applications. PMID:23674449

  8. The application of the multi-scale GVF model based on the B-spline lifting wavelet in medical images segmentation

    NASA Astrophysics Data System (ADS)

    Xue, Juntao; Liu, Zhengguang; Zhang, Hongwei; Wang, Shucheng

    2007-01-01

    Snakes, or active contours, are used extensively in computer vision and image processing application, particularly to locate object boundaries. GVF (Gradient Vector Flow) model has resolved two key problems of the traditional deformable model. However, it still requires both the initial contour being close to the target and a large amount of computation. And it is difficult to process the cupped target edge. This paper analysis the characteristics of deformable model firstly, then proposed a new method based on B-spline lifting wavelet. Experimentations based on GVF model and MRI segmentation show that the proposed method is a good resolution to the initialization sensitivity and the large computation.

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

    PubMed Central

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

    2014-01-01

    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. PMID:24761376

  10. 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.

  11. A multi-scale non-local means algorithm for image de-noising

    NASA Astrophysics Data System (ADS)

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

    2012-06-01

    A highly studied problem in image processing and the field of electrical engineering in general is the recovery of a true signal from its noisy version. Images can be corrupted by noise during their acquisition or transmission stages. As noisy images are visually very poor in quality, and complicate further processing stages of computer vision systems, it is imperative to develop algorithms which effectively remove noise in images. In practice, it is a difficult task to effectively remove the noise while simultaneously retaining the edge structures within the image. Accordingly, many de-noising algorithms have been considered attempt to intelligent smooth the image while still preserving its details. Recently, a non-local means (NLM) de-noising algorithm was introduced, which exploited the redundant nature of images to achieve image de-noising. The algorithm was shown to outperform current de-noising standards, including Gaussian filtering, anisotropic diffusion, total variation minimization, and multi-scale transform coefficient thresholding. However, the NLM algorithm was developed in the spatial domain, and therefore, does not leverage the benefit that multi-scale transforms provide a framework in which signals can be better distinguished by noise. Accordingly, in this paper, a multi-scale NLM (MS-NLM) algorithm is proposed, which combines the advantage of the NLM algorithm and multi-scale image processing techniques. Experimental results via computer simulations illustrate that the MS-NLM algorithm outperforms the NLM, both visually and quantitatively.

  12. Consideration of shear modulus in biomechanical analysis of peri-implant jaw bone: accuracy verification using image-based multi-scale simulation.

    PubMed

    Matsunaga, Satoru; Naito, Hiroyoshi; Tamatsu, Yuichi; Takano, Naoki; Abe, Shinichi; Ide, Yoshinobu

    2013-01-01

    The aim of this study was to clarify the influence of shear modulus on the analytical accuracy in peri-implant jaw bone simulation. A 3D finite element (FE) model was prepared based on micro-CT data obtained from images of a jawbone containing implants. A precise model that closely reproduced the trabecular architecture, and equivalent models that gave shear modulus values taking the trabecular architecture into account, were prepared. Displacement norms during loading were calculated, and the displacement error was evaluated. The model that gave shear modulus values taking the trabecular architecture into account showed an analytical error of around 10-20% in the cancellous bone region, while in the model that used incorrect shear modulus, the analytical error exceeded 40% in certain regions. The shear modulus should be evaluated precisely in addition to the Young modulus when considering the mechanics of peri-implant trabecular bone structure. PMID:23719004

  13. 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

  14. 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

  15. 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.

  16. 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.

  17. Medical image retrieval and analysis by Markov random fields and multi-scale fractal dimension.

    PubMed

    Backes, André Ricardo; Gerhardinger, Leandro Cavaleri; Batista Neto, João do Espírito Santo; Bruno, Odemir Martinez

    2015-02-01

    Many Content-based Image Retrieval (CBIR) systems and image analysis tools employ color, shape and texture (in a combined fashion or not) as attributes, or signatures, to retrieve images from databases or to perform image analysis in general. Among these attributes, texture has turned out to be the most relevant, as it allows the identification of a larger number of images of a different nature. This paper introduces a novel signature which can be used for image analysis and retrieval. It combines texture with complexity extracted from objects within the images. The approach consists of a texture segmentation step, modeled as a Markov Random Field process, followed by the estimation of the complexity of each computed region. The complexity is given by a Multi-scale Fractal Dimension. Experiments have been conducted using an MRI database in both pattern recognition and image retrieval contexts. The results show the accuracy of the proposed method in comparison with other traditional texture descriptors and also indicate how the performance changes as the level of complexity is altered. PMID:25586375

  18. Medical image retrieval and analysis by Markov random fields and multi-scale fractal dimension

    NASA Astrophysics Data System (ADS)

    Backes, André Ricardo; Cavaleri Gerhardinger, Leandro; do Espírito Santo Batista Neto, João; Martinez Bruno, Odemir

    2015-02-01

    Many Content-based Image Retrieval (CBIR) systems and image analysis tools employ color, shape and texture (in a combined fashion or not) as attributes, or signatures, to retrieve images from databases or to perform image analysis in general. Among these attributes, texture has turned out to be the most relevant, as it allows the identification of a larger number of images of a different nature. This paper introduces a novel signature which can be used for image analysis and retrieval. It combines texture with complexity extracted from objects within the images. The approach consists of a texture segmentation step, modeled as a Markov Random Field process, followed by the estimation of the complexity of each computed region. The complexity is given by a Multi-scale Fractal Dimension. Experiments have been conducted using an MRI database in both pattern recognition and image retrieval contexts. The results show the accuracy of the proposed method in comparison with other traditional texture descriptors and also indicate how the performance changes as the level of complexity is altered.

  19. 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.

  20. 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).

  1. 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

  2. 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.

  3. 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

  4. 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.

  5. 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). PMID:27341026

  6. [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. PMID:22586977

  7. 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

  8. 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. PMID:27525734

  9. 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.

  10. Fast randomized Hough transformation track initiation algorithm based on multi-scale clustering

    NASA Astrophysics Data System (ADS)

    Wan, Minjie; Gu, Guohua; Chen, Qian; Qian, Weixian; Wang, Pengcheng

    2015-10-01

    A fast randomized Hough transformation track initiation algorithm based on multi-scale clustering is proposed to overcome existing problems in traditional infrared search and track system(IRST) which cannot provide movement information of the initial target and select the threshold value of correlation automatically by a two-dimensional track association algorithm based on bearing-only information . Movements of all the targets are presumed to be uniform rectilinear motion throughout this new algorithm. Concepts of space random sampling, parameter space dynamic linking table and convergent mapping of image to parameter space are developed on the basis of fast randomized Hough transformation. Considering the phenomenon of peak value clustering due to shortcomings of peak detection itself which is built on threshold value method, accuracy can only be ensured on condition that parameter space has an obvious peak value. A multi-scale idea is added to the above-mentioned algorithm. Firstly, a primary association is conducted to select several alternative tracks by a low-threshold .Then, alternative tracks are processed by multi-scale clustering methods , through which accurate numbers and parameters of tracks are figured out automatically by means of transforming scale parameters. The first three frames are processed by this algorithm in order to get the first three targets of the track , and then two slightly different gate radius are worked out , mean value of which is used to be the global threshold value of correlation. Moreover, a new model for curvilinear equation correction is applied to the above-mentioned track initiation algorithm for purpose of solving the problem of shape distortion when a space three-dimensional curve is mapped to a two-dimensional bearing-only space. Using sideways-flying, launch and landing as examples to build models and simulate, the application of the proposed approach in simulation proves its effectiveness , accuracy , and adaptivity

  11. Change detection based on integration of multi-scale mixed-resolution information

    NASA Astrophysics Data System (ADS)

    Wei, Li; Wang, Cheng; Wen, Chenglu

    2016-03-01

    In this paper, a new method of unsupervised change detection is proposed by modeling multi-scale change detector based on local mixed information and we present a method of automated threshold. A theoretical analysis is presented to demonstrate that more comprehensive information is taken into account by the integration of multi-scale information. The ROC curves show that change detector based on multi-scale mixed information(MSM) is more effective than based on mixed information(MIX). Experiments on artificial and real-world datasets indicate that the multi-scale change detection of mixed information can eliminate the pseudo-change part of the area. Therefore, the proposed algorithm MSM is an effective method for the application of change detection.

  12. 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

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

    PubMed

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

    2015-11-01

    Automatic fluorescent particle tracking is an essential task to study the dynamics of a large number of biological structures at a sub-cellular level. We have developed a probabilistic particle tracking approach based on multi-scale detection and two-step multi-frame association. The multi-scale detection scheme allows coping with particles in close proximity. For finding associations, we have developed a two-step multi-frame algorithm, which is based on a temporally semiglobal formulation as well as spatially local and global optimization. In the first step, reliable associations are determined for each particle individually in local neighborhoods. In the second step, the global spatial information over multiple frames is exploited jointly to determine optimal associations. The multi-scale detection scheme and the multi-frame association finding algorithm have been combined with a probabilistic tracking approach based on the Kalman filter. We have successfully applied our probabilistic tracking approach to synthetic as well as real microscopy image sequences of virus particles and quantified the performance. We found that the proposed approach outperforms previous approaches. PMID:26208342

  14. Multi-Scale Matching for the Automatic Location of Control Points in Large Scale Aerial Images Using Terrestrial Scenes

    NASA Astrophysics Data System (ADS)

    Berveglieri, A.; Tommaselli, A. M. G.

    2014-03-01

    A technique to automatically locate Ground Control Points (GCPs) in large aerial images is presented considering the availability of low accuracy direct georeferencing data. The approach is based on image chips of GCPs extracted from vertical terrestrial images. A strategy combining image matching techniques was implemented to select correct matches. These matches were used to define a 2D transformation with which the GCP is projected close to its correct position, reducing the search space in the aerial image. Area-based matching with some refinements is used to locate GCPs with sub-pixel precision. Experiments were performed with multi-scale images and assessed with a bundle block adjustment simulating an indirect sensor orientation. The accuracy analysis was accomplished based on discrepancies obtained from GCPs and check points. The results were better than interactive measurements and a planimetric accuracy of 1/5 of the Ground Sample Distance (GSD) for the check points was achieved.

  15. 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.

  16. 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.

  17. 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.

  18. Detection of Neuron Membranes in Electron Microscopy Images Using Multi-scale Context and Radon-Like Features

    SciTech Connect

    Seyedhosseini, Mojtaba; Kumar, Ritwik; Jurrus, Elizabeth R.; Giuly, Richard J.; Ellisman, Mark; Pfister, Hanspeter; Tasdizen, Tolga

    2011-10-01

    Automated neural circuit reconstruction through electron microscopy (EM) images is a challenging problem. In this paper, we present a novel method that exploits multi-scale contextual information together with Radon-like features (RLF) to learn a series of discriminative models. The main idea is to build a framework which is capable of extracting information about cell membranes from a large contextual area of an EM image in a computationally efficient way. Toward this goal, we extract RLF that can be computed efficiently from the input image and generate a scale-space representation of the context images that are obtained at the output of each discriminative model in the series. Compared to a single-scale model, the use of a multi-scale representation of the context image gives the subsequent classifiers access to a larger contextual area in an effective way. Our strategy is general and independent of the classifier and has the potential to be used in any context based framework. We demonstrate that our method outperforms the state-of-the-art algorithms in detection of neuron membranes in EM images.

  19. 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.

  20. Retinal vessel enhancement based on multi-scale top-hat transformation and histogram fitting stretching

    NASA Astrophysics Data System (ADS)

    Liao, Miao; Zhao, Yu-qian; Wang, Xiao-hong; Dai, Pei-shan

    2014-06-01

    Retinal vessels play an important role in the diagnostic procedure of retinopathy. A new retinal vessel enhancement method is proposed in this paper. Firstly, the optimal bright and dim image features of an original retinal image are extracted by a multi-scale top-hat transformation. Then, the retinal image is enhanced preliminarily by adding the optimal bright image features and removing the optimal dim image features. Finally, the preliminarily enhanced image is further processed by linear stretching with histogram Gaussian curve fitting. The experiments results on the DRIVE and STARE databases show that the proposed method improves the contrast and enhances the details of the retinal vessels effectively.

  1. 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%.

  2. 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.

  3. 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.

  4. 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%.

  5. 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.

  6. 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

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

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

    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.

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

    PubMed

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

    2014-02-01

    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

  9. 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

  10. 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. PMID:20879208

  11. Development of a multi-scale seismic imaging method and its application to Newberry volcano

    NASA Astrophysics Data System (ADS)

    Heath, B.; Toomey, D. R.; Hooft, E. E.; Bezada, M. J.

    2013-12-01

    While some shallow magma reservoirs beneath land volcanoes have been seismically imaged, our understanding of their mid-to lower-crustal magma plumbing systems remains limited. Active source techniques allow for optimizing source geometry to image shallow crustal magmatic systems, but typically do not resolve depths greater than ~6-10 km, since the velocity gradient in the mid-to lower crust limits the energy that turns at these depths. For closely spaced seismic stations, teleseismic data provide constraints on deeper crustal heterogeneity, particularly its lateral variation. On the other hand, teleseismic studies do not resolve vertical variations in crustal structure well because their ray paths are almost vertical, which results in limited crossing rays within the crust. Furthermore, due to the generally lower frequency content of teleseismic arrivals, these data primarily image longer wavelength heterogeneity. Here we develop a multi-scale seismic imaging method that combines high-frequency active source data with lower frequency teleseismic data, and test its usefulness for imaging the crustal structure beneath Newberry Volcano in central Oregon. To constrain the P wave structure throughout the crust, we develop an iterative method that includes 3-D sensitivity kernels and 3-D raytracing. The use of sensitivity kernels provides a physically motivated method that accounts for the different resolving capability of teleseismic and active source data. Various approximations to the sensitivity kernel are explored, with the goal of maximizing both computational efficiency and inversion accuracy. 3-D raytracing determines an accurate ray path, which is important in the highly heterogeneous crust. We verify our approach with synthetic data calculated using finite difference waveform modeling. We discuss our inversion results and our ability to resolve the velocity structure throughout the crust. We will investigate the presence of high and low velocity regions that

  12. Parallel Computing of Multi-scale Finite Element Sheet Forming Analyses Based on Crystallographic Homogenization Method

    SciTech Connect

    Kuramae, Hiroyuki; Okada, Kenji; Uetsuji, Yasutomo; Nakamachi, Eiji; Tam, Nguyen Ngoc; Nakamura, Yasunori

    2005-08-05

    Since the multi-scale finite element analysis (FEA) requires large computation time, development of the parallel computing technique for the multi-scale analysis is inevitable. A parallel elastic/crystalline viscoplastic FEA code based on a crystallographic homogenization method has been developed using PC cluster. The homogenization scheme is introduced to compute macro-continuum plastic deformations and material properties by considering a polycrystal texture. Since the dynamic explicit method is applied to this method, the analysis using micro crystal structures computes the homogenized stresses in parallel based on domain partitioning of macro-continuum without solving simultaneous linear equations. The micro-structure is defined by the Scanning Electron Microscope (SEM) and the Electron Back Scan Diffraction (EBSD) measurement based crystal orientations. In order to improve parallel performance of elastoplasticity analysis, which dynamically and partially increases computational costs during the analysis, a dynamic workload balancing technique is introduced to the parallel analysis. The technique, which is an automatic task distribution method, is realized by adaptation of subdomain size for macro-continuum to maintain the computational load balancing among cluster nodes. The analysis code is applied to estimate the polycrystalline sheet metal formability.

  13. 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.

  14. Infrared/laser multi-sensor fusion and tracking based on the multi-scale model

    NASA Astrophysics Data System (ADS)

    Wang, Bingjian; Hao, Jingya; Yi, Xiang; Wu, Feihong; Li, Min; Qin, Hanlin; Huang, Hanqiao

    2016-03-01

    The state estimation problem of targets detected by infrared/laser composite detection system with different sampling rates was studied in this paper. An effective state estimation algorithm based on data fusion is presented. Because sampling rate of infrared detection system is much higher than that of the laser detection system, the theory of multi-scale analysis is used to establish multi-scale model in this algorithm. At the fine scale, angle information provided by infrared detection system is used to estimate the target state through the unscented Kalman filter. It makes full use of the high frequency characteristic of infrared detection system to improve target state estimation accuracy. At the coarse scale, due to the sampling ratio of infrared and laser detection systems is an integer multiple, the angle information can be fused directly with the distance information of laser detection system to determine the target location. The fused information is served as observation, while the converted measurement Kalman filter (CMKF) is used to estimate the target state, which greatly reduces the complexity of filtering process and gets the optimal fusion estimation. The simulation results of tracking a target in 3-D space by infrared and laser detection systems demonstrate that the proposed algorithm in this paper is efficient and can obtain better performance than traditional algorithm.

  15. Fast multi-scale edge detection algorithm based on wavelet transform

    NASA Astrophysics Data System (ADS)

    Zang, Jie; Song, Yanjun; Li, Shaojuan; Luo, Guoyun

    2011-11-01

    The traditional edge detection algorithms have certain noise amplificat ion, making there is a big error, so the edge detection ability is limited. In analysis of the low-frequency signal of image, wavelet analysis theory can reduce the time resolution; under high time resolution for high-frequency signal of the image, it can be concerned about the transient characteristics of the signal to reduce the frequency resolution. Because of the self-adaptive for signal, the wavelet transform can ext ract useful informat ion from the edge of an image. The wavelet transform is at various scales, wavelet transform of each scale provides certain edge informat ion, so called mult i-scale edge detection. Multi-scale edge detection is that the original signal is first polished at different scales, and then detects the mutation of the original signal by the first or second derivative of the polished signal, and the mutations are edges. The edge detection is equivalent to signal detection in different frequency bands after wavelet decomposition. This article is use of this algorithm which takes into account both details and profile of image to detect the mutation of the signal at different scales, provided necessary edge information for image analysis, target recognition and machine visual, and achieved good results.

  16. 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.

  17. 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

  18. 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. PMID:26264396

  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. Detection of small bowel tumor based on multi-scale curvelet analysis and fractal technology in capsule endoscopy.

    PubMed

    Liu, Gang; Yan, Guozheng; Kuang, Shuai; Wang, Yongbing

    2016-03-01

    Wireless capsule endoscopy (WCE) has been a revolutionary technique to noninvasively inspect gastrointestinal (GI) tract diseases, especially small bowel tumor. However, it is a tedious task for physicians to examine captured images. To develop a computer-aid diagnosis tool for relieving the huge burden of physicians, the intestinal video data from 89 clinical patients with the indications of potential tumors was analyzed. Out of the 89 patients, 15(16.8%) were diagnosed with small bowel tumor. A novel set of textural features that integrate multi-scale curvelet and fractal technology were proposed to distinguish normal images from tumor images. The second order textural descriptors as well as higher order moments between different color channels were computed from images synthesized by the inverse curvelet transform of the selected scales. Then, a classification approach based on support vector machine (SVM) and genetic algorithm (GA) was further employed to select the optimal feature set and classify the real small bowel images. Extensive comparison experiments validate that the proposed automatic diagnosis scheme achieves a promising tumor classification performance of 97.8% sensitivity and 96.7% specificity in the selected images from our clinical data. PMID:26829705

  2. Improved color reproduction based on CIELAB color space in integrated multi-scale retinex

    NASA Astrophysics Data System (ADS)

    Kyung, Wang-Jun; Lee, Tae-Hyoung; Lee, Cheol-Hee; Ha, Yeong-Ho

    2009-01-01

    Recently, tone reproduction is widely used in the field of image enhancement and HDR imaging. This method is especially used to provide the proper luminance so that captured images give the same sensation as the scene. As a result, we can get high contrast and naturalness of colors. There is ample literature on the topic of tone reproduction that has the objective of reproducing natural looking color in digital images. In recent papers, IMSR (Integrated multi-scale Retinex) shows great naturalness in the result images. Most methods, including IMSR, work in RGB or quasi-RGB color spaces, although some method adopted the use of luminance. This raises hue distortion from the point of the human visual system, that is, hue distortion in CIELAB color space. Accordingly, this paper proposes an enhanced IMSR method in a device-independent color space, CIELAB, to preserve hue and obtain high contrast and naturalness. In order to achieve the devised objectives, a captured sRGB image is transformed to the CIELAB color space. IMSR is then applied to only L* values, thus the balance of colors components are preserved. This process causes unnatural saturation, therefore saturation adjustment is performed by applying the ratio of chroma variation at the sRGB gamut boundary according to the corrected luminance. Finally, the adjusted CIELAB values are transformed to sRGB using the inverse transform function. In the result images of the proposed method, containing both high and low luminance regions, visibility in dark shadow and bright regions was improved and color distortion was reduced.

  3. Pore Scale and Continuum Modeling for Gas Flow Pattern obtained by Multi-Scale Optical Imaging Technique

    NASA Astrophysics Data System (ADS)

    Lazik, D.; Samani, S.; Geistlinger, H.

    2008-12-01

    A multi-scale optical imaging technique was developed allowing for the 2D observation of two phase flow in porous media at two different scales simultaneously: Using two coupled camera systems a 2D flow cell (0.5 x 0.5 m²) is recorded entirely at the bench scale and at the pore scale with a spatial resolution of 0.5 mm and 0.01 mm respectively. The technique is applied to study channelized gas flow in saturated 0.5mm glass beads. We analyze the phase distribution at the pore scale and derive a pixel-based method for the measurement of saturation at the larger scale. Pore-Scale-Models: Both a grain-size- and flow rate-dependent transition are observed in the gas flow pattern. Standard quasi-static criteria do not explain the experimental results, since they do not take into account the competition between stabilizing friction forces and destabilizing capillary and gravitational forces. Conceptualizing the steady state tortuous gas flow as core-annular flow and applying Hagen-Poiseuille flow for a straight capillary, we propose a flow rate and grain-size-dependent stability criterion (coherence condition) that accounts for the experimental results. Continuum Scale Models: The main objective of this paper is to test the validity of the continuum approach for two-fluid flow for macroscopic homogeneous media. Using a reasonable log-normal distribution of capillary radii that led to a matrix potential that fits the experimental steady-state capillary pressure, the continuum model (TOUGH2) was able to describe the functional form of the dynamical gas volume, an integral flow property, as a function of the flow rate for the 0.5mm glass beads. On the other hand, the continuum model fails to describe the spatial-temporal distribution of the gas flow. For the first time, we were able to quantify the plateau-like gas distribution using optical tomography. This result is in strong contradiction to the Gaussian-like distribution obtained from the continuum model. Both

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

    PubMed Central

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

    2013-01-01

    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. PMID:24163721

  5. Surrogate-based modeling and dimension reduction techniques for multi-scale mechanics problems

    NASA Astrophysics Data System (ADS)

    Shyy, Wei; Cho, Young-Chang; Du, Wenbo; Gupta, Amit; Tseng, Chien-Chou; Sastry, Ann Marie

    2011-12-01

    Successful modeling and/or design of engineering systems often requires one to address the impact of multiple "design variables" on the prescribed outcome. There are often multiple, competing objectives based on which we assess the outcome of optimization. Since accurate, high fidelity models are typically time consuming and computationally expensive, comprehensive evaluations can be conducted only if an efficient framework is available. Furthermore, informed decisions of the model/hardware's overall performance rely on an adequate understanding of the global, not local, sensitivity of the individual design variables on the objectives. The surrogate-based approach, which involves approximating the objectives as continuous functions of design variables from limited data, offers a rational framework to reduce the number of important input variables, i.e., the dimension of a design or modeling space. In this paper, we review the fundamental issues that arise in surrogate-based analysis and optimization, highlighting concepts, methods, techniques, as well as modeling implications for mechanics problems. To aid the discussions of the issues involved, we summarize recent efforts in investigating cryogenic cavitating flows, active flow control based on dielectric barrier discharge concepts, and lithium (Li)-ion batteries. It is also stressed that many multi-scale mechanics problems can naturally benefit from the surrogate approach for "scale bridging."

  6. 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.

  7. 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.

  8. 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

    2016-01-01

    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 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

  10. 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. PMID:27207578

  11. Inversion of Three Layers Multi-Scale SPM Model Based on Neural Network Technique for the Retrieval of Soil Multi-Scale Roughness and Moisture Parameters

    NASA Astrophysics Data System (ADS)

    Hosni, I.; JaafriGhamki, M.; Bennaceur Farah, L.; Naceur, M. S.

    2015-04-01

    In this paper, a multi-layered multi-scale backscattering model for a lossy medium and a neural network inversion procedure has been presented. We have used a bi-dimensional multi-scale (2D MLS) roughness description where the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each one having a spatial scale using the wavelet transform and the Mallat algorithm to describe natural surface roughness. An adapted three layers 2D MLS small perturbations (SPM) model has been used to describe radar backscattering response of semiarid sub-surfaces. The total reflection coefficients of the natural soil are computed using the multilayer model, and volumetric scattering is approximated by the internal reflections between layers. The original multi-scale SPM model includes only the surface scattering of the natural bare soil, while the multilayer soil modified 2D MLS SPM model includes both the surface scattering and the volumetric scattering within the soil. This multi-layered model has been used to calculate the total surface reflection coefficients of a natural soil surface for both horizontal and vertical co-polarizations. A parametric analysis presents the dependence of the backscattering coefficient on multi scale roughness and soil. The overall objective of this work is to retrieve soil surfaces parameters namely roughness and soil moisture related to the dielectric constant by inverting the radar backscattered signal from natural soil surfaces. To perform the inversion of the modified three layers 2D MLS SPM model, we used a multilayer neural network (NN) architecture trained by a back-propagation learning rule.

  12. 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).

  13. 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

  14. 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. PMID:22645811

  15. 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. PMID:25795630

  16. 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.

  17. 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

  18. 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.

  19. [Pattern recognition of surface electromyography signal based on multi-scale fuzzy entropy].

    PubMed

    Zou, Xiaoyang; Lei, Min

    2012-12-01

    Action surface electromyography (SEMG) signals can be acquired from human skin surface. Its pattern recognition plays a very important role in practical applications such as human prosthesis and human-computer interface systems. For the purpose of increasing the recognition accuracy, we proposed a new recognition method combining fuzzy entropy (FuzzyEn) with multi-scale analysis. Considering the nonlinear and non-stationary characteristics of the SEMG, a multi-scale fuzzy entropy (MSFuzzyEn) feature was introduced and applied to the pattern recognition of six type action SEMG signals of the forearm. Firstly, multi-scale decomposition was applied to original signal using wavelet decomposition. Then MSFuzzyEn of the decomposed signals were calculated and inputted to support vector machine (SVM) for classification as feature vectors. The mean recognition accuracy reached 97%, which was 3% greater than that when FuzzyEn of original signal is applied to the classification of SEMG signals. The results have proved that the MSFuzzyEn is effective and precise in the classification of action SEMG signals. PMID:23469553

  20. 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

  1. 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.

  2. Multi scale imaging of the Cloudy Zone in the Tazewell IIICD Meteorite

    NASA Astrophysics Data System (ADS)

    Einsle, J. F.; Harrison, R. J.; Nichols, C. I. O.; Blukis, R.; Midgley, P. A.; Eggeman, A.; Saghi, Z.; Bagot, P.

    2015-12-01

    Paleomagnetic studies of iron and stony iron meteorites suggest that many small planetary bodies possessed molten cores resulting in the generation of a magnetic field. As these bodies cooled, Fe-Ni metal trapped within their mantle underwent a series of low-temperature transitions, leading to the familiar Widmanstatten intergrowth of kamacite and taenite. Adjacent to the kamacite/taenite interface is the so-called "cloudy zone" (CZ): a nanoscale intergrowth of tetrataenite islands in an Fe-rich matrix phase formed via spinodal decomposition. It has recently been shown (Bryson et al. 2015, Nature) that the CZ encodes a time-series record of the evolution of the magnetic field generated by the molten core of the planetary body. Extracting meaningful paleomagnetic data from the CZ relies, on a thorough understanding of the 3D chemical and magnetic properties of the intergrowth focsusing on the interactions between the magnetically hard tetrataenite islands and the magnetically soft matrix. Here we present a multi scale study of the chemical and crystallographic make up of the CZ in the Tazewell IIICD meteorite, using a range of advanced microscopy techniques. The results provide unprecedented insight into the architecture of the CZ, with implications for how the CZ acquires chemical transformation remanance during cooling on the parent body. Previous 2D transmission electron microscope studies of the CZ suggested that the matrix is an ordered Fe3Ni phase with the L12 structure. Interpretation of the electron diffraction patterns and chemical maps in these studies was hindered by a failure to resolve signals from overlapping island and matrix phases. Here we obtain high resolution electron diffraction and 3D chemical maps with near atomic resolution using a combination of scanning precession electron diffraction, 3D STEM EDS and atom probe tomography. Using this combined methodology we reslove for the first time the phenomena of secondary precipitation in the

  3. 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. PMID:26344265

  4. 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.

  5. 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.

  6. 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. PMID:25709942

  7. 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

  8. 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

  9. 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. PMID:25245686

  10. Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery

    NASA Astrophysics Data System (ADS)

    Beguet, Benoit; Guyon, Dominique; Boukir, Samia; Chehata, Nesrine

    2014-10-01

    The main goal of this study is to design a method to describe the structure of forest stands from Very High Resolution satellite imagery, relying on some typical variables such as crown diameter, tree height, trunk diameter, tree density and tree spacing. The emphasis is placed on the automatization of the process of identification of the most relevant image features for the forest structure retrieval task, exploiting both spectral and spatial information. Our approach is based on linear regressions between the forest structure variables to be estimated and various spectral and Haralick's texture features. The main drawback of this well-known texture representation is the underlying parameters which are extremely difficult to set due to the spatial complexity of the forest structure. To tackle this major issue, an automated feature selection process is proposed which is based on statistical modeling, exploring a wide range of parameter values. It provides texture measures of diverse spatial parameters hence implicitly inducing a multi-scale texture analysis. A new feature selection technique, we called Random PRiF, is proposed. It relies on random sampling in feature space, carefully addresses the multicollinearity issue in multiple-linear regression while ensuring accurate prediction of forest variables. Our automated forest variable estimation scheme was tested on Quickbird and Pléiades panchromatic and multispectral images, acquired at different periods on the maritime pine stands of two sites in South-Western France. It outperforms two well-established variable subset selection techniques. It has been successfully applied to identify the best texture features in modeling the five considered forest structure variables. The RMSE of all predicted forest variables is improved by combining multispectral and panchromatic texture features, with various parameterizations, highlighting the potential of a multi-resolution approach for retrieving forest structure

  11. Multi-scale Finite-Frequency Travel-time Tomography Applied to Imaging 3-D Velocity Structure of the Upper Mantle Beneath the Southwest United States

    NASA Astrophysics Data System (ADS)

    Yin, Y.; Hung, S.

    2007-12-01

    Seismic tomographic imaging has played a key component to unravel the deep processes that caused the surface morphology and rift magmatism in the southwest United States. Several studies used teleseismic body- wave arrivals recorded by the La Ristra experiment, a dense broadband array of 950-km in length deployed during 1999-2001 and run through the Great Plains, the Rio Grande Rift, and the Colorado Plateau, to construct a 2-D tomographic image of the upper mantle structure beneath this linear array (e.g., Gao et al., 2004). However, because of the inevitable smoothing and damping imposed in the tomographic model, the resulting velocity contrast is too weak to explain distinct P and S waveform changes across the array (Song and Helmberger, 2007). In this study, we include all the data from the La Ristra and available nearby arrays and reexamine finite- frequency travel time delays measured by inter-station cross correlation of waveforms at both high- (0.3-2 Hz for P and 0.1-0.5 Hz for S) and low-frequencies (0.03-0.125 Hz for P and 0.03-0.1 Hz for S). Differing from the previous models that rely on classical ray theory and simple grid parameterization, our inversion considers more realistic 3-D sensitivity kernels for relative travel-time delays and a wavelet-based, multi-scale parameterization that enables to yield robust features with spatially-varying resolutions. Our preliminary P-wave model reveals a prominent low-velocity zone extending from near surface to the depth of 300 km beneath the Rio Grande Rift, while the upper mantle which underlies the Great Plains and the Colorado Plateau is seismically fast. We will demonstrate the difference and improvement of 3-D tomographic models through the use of finite-frequency kernels and multi-scale parameterization.

  12. 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.

  13. 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.

  14. 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). PMID:21737338

  15. 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

  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. 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

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

    DOE PAGESBeta

    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

  19. 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

  20. 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

  1. Motion Estimation Based on Mutual Information and Adaptive Multi-Scale Thresholding.

    PubMed

    Xu, Rui; Taubman, David; Naman, Aous Thabit

    2016-03-01

    This paper proposes a new method of calculating a matching metric for motion estimation. The proposed method splits the information in the source images into multiple scale and orientation subbands, reduces the subband values to a binary representation via an adaptive thresholding algorithm, and uses mutual information to model the similarity of corresponding square windows in each image. A moving window strategy is applied to recover a dense estimated motion field whose properties are explored. The proposed matching metric is a sum of mutual information scores across space, scale, and orientation. This facilitates the exploitation of information diversity in the source images. Experimental comparisons are performed amongst several related approaches, revealing that the proposed matching metric is better able to exploit information diversity, generating more accurate motion fields. PMID:26742132

  2. 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. PMID:27318041

  3. A JFNK-based implicit moment algorithm for self-consistent, multi-scale, plasma simulation

    NASA Astrophysics Data System (ADS)

    Knoll, Dana; Taitano, William; Chacon, Luis

    2010-11-01

    Jacobian-Free-Newton-Krylov method (JFNK) is an advanced non-linear algorithm that allows solution to a coupled systems of non-linear equations [1]. In [2] we have put forward a JFNK-based implicit, consistent, time integration algorithm and demonstrated it's ability to efficiently step over electron time scales, while retaining electron kinetic effects on the ion time scale. Here we extend this work by investigating a JFNK- based implicit-moments approach for the purpose of consistent scale-bridging between the fluid description and kinetic description in order to resolve the transition region. Our preliminary results, based on a reformulated Poisson's equation (RPE) [3], allows solution to the Vlasov-Poisson system for varying grid resolutions. In the limit of local coarse grid size (grid spacing large compared to Debye length), the RPE represents an electric field based on the moment system, while in the limit of local grid spacing resolving the Debye length, the RPE represents an electric field based on the standard Poisson equation. The technique allows smooth transition between the two regimes, consistently, in one simulation. [1] D.A. Knoll and D.E. Keyes,J. Comput. Phys., vol. 193 (2004) [2] W.T. Taitano, Masters Thesis, Nuclear Engineering, University of Idaho (2010) [3] R. Belaouar, N.Crouseilles and P. Degond,J. Sci. Comput., vol. 41 (2009)

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

    PubMed

    Evans, Tom P; Kelley, Hugh

    2004-08-01

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

  5. Multi-Scale Locality-Constrained Spatiotemporal Coding for Local Feature Based Human Action Recognition

    PubMed Central

    Liu, Yu; Wang, Wei; Xu, Wei; Zhang, Maojun

    2013-01-01

    We propose a Multiscale Locality-Constrained Spatiotemporal Coding (MLSC) method to improve the traditional bag of features (BoF) algorithm which ignores the spatiotemporal relationship of local features for human action recognition in video. To model this spatiotemporal relationship, MLSC involves the spatiotemporal position of local feature into feature coding processing. It projects local features into a sub space-time-volume (sub-STV) and encodes them with a locality-constrained linear coding. A group of sub-STV features obtained from one video with MLSC and max-pooling are used to classify this video. In classification stage, the Locality-Constrained Group Sparse Representation (LGSR) is adopted to utilize the intrinsic group information of these sub-STV features. The experimental results on KTH, Weizmann, and UCF sports datasets show that our method achieves better performance than the competing local spatiotemporal feature-based human action recognition methods. PMID:24194681

  6. 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.

  7. 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

  8. 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

    2015-01-01

    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

  9. A hierarchical network-based algorithm for multi-scale watershed delineation

    NASA Astrophysics Data System (ADS)

    Castronova, Anthony M.; Goodall, Jonathan L.

    2014-11-01

    Watershed delineation is a process for defining a land area that contributes surface water flow to a single outlet point. It is a commonly used in water resources analysis to define the domain in which hydrologic process calculations are applied. There has been a growing effort over the past decade to improve surface elevation measurements in the U.S., which has had a significant impact on the accuracy of hydrologic calculations. Traditional watershed processing on these elevation rasters, however, becomes more burdensome as data resolution increases. As a result, processing of these datasets can be troublesome on standard desktop computers. This challenge has resulted in numerous works that aim to provide high performance computing solutions to large data, high resolution data, or both. This work proposes an efficient watershed delineation algorithm for use in desktop computing environments that leverages existing data, U.S. Geological Survey (USGS) National Hydrography Dataset Plus (NHD+), and open source software tools to construct watershed boundaries. This approach makes use of U.S. national-level hydrography data that has been precomputed using raster processing algorithms coupled with quality control routines. Our approach uses carefully arranged data and mathematical graph theory to traverse river networks and identify catchment boundaries. We demonstrate this new watershed delineation technique, compare its accuracy with traditional algorithms that derive watershed solely from digital elevation models, and then extend our approach to address subwatershed delineation. Our findings suggest that the open-source hierarchical network-based delineation procedure presented in the work is a promising approach to watershed delineation that can be used summarize publicly available datasets for hydrologic model input pre-processing. Through our analysis, we explore the benefits of reusing the NHD+ datasets for watershed delineation, and find that the our technique

  10. 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

  11. 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.

  12. 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. PMID:26116515

  13. 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.

  14. 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. PMID:26794770

  15. 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.

  16. 4D Arctic: Structure and evolution of Arctic crust and mantle based on multi-scale geophysical studies

    NASA Astrophysics Data System (ADS)

    Gaina, Carmen; Koulakov, Ivan; Faleide, Jan Inge; Schweitzer, Johannes

    2013-04-01

    Arctic geological history contains many grey zones. In particular, the structure of the lithosphere and the spatial and temporal interaction between the crust and upper mantle has been meagerly explored, yet it may hold some of the answers for the formation of passive margins, sedimentary basins, oceanic bathymetric features and volcanic provinces. As part of an interdisciplinary collaborative project between Norway and Russia, we aim to build multi-scale models that will unravel the structure and evolution of Arctic's crust and mantle and their interaction through time. In this contribution we will review the present status of knowledge regarding the present structure of the Arctic crust and mantle, and the tectonic evolution of this region since the Late Jurassic. To infer first order outlines of major tectonic blocks, boundaries between continental and oceanic areas, crustal heterogeneities and ages of oceanic crust, we have used the magnetic and gravity anomaly maps of the Arctic region (Gaina et al., 2011 and Saltus et al., 2011) and other available geological and geophysical data. A much more detailed upper mantle structure could be deciphered from the recently published three dimensional model of P velocity based on tomographic inversion of ISC global data (Jakolev et al., 2012). These datasets and models are jointly interpreted and a preliminary scenario for the Arctic region evolution since the Late Jurassic is presented. References Gaina, C. et al. (2011) Geol. Soc. London, Memoirs 35; 39-48. Jakolev et al. (2012) Russian Geology and Geophysics, 53; 963-971 Saltus et al. (2011) Geol. Soc. London, Memoirs 35; 49-60.

  17. 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. PMID:26614653

  18. 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

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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

  6. 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

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. 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

  12. Multi-scale statistical analysis of coronal solar activity

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

    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 statistical analysis of coronal solar activity

    DOE PAGESBeta

    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.

  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. 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

  17. The Abridgment and Relaxation Time for a Linear Multi-Scale Model Based on Multiple Site Phosphorylation

    PubMed Central

    Wang, Shuo; Cao, Yang

    2015-01-01

    Random effect in cellular systems is an important topic in systems biology and often simulated with Gillespie’s stochastic simulation algorithm (SSA). Abridgment refers to model reduction that approximates a group of reactions by a smaller group with fewer species and reactions. This paper presents a theoretical analysis, based on comparison of the first exit time, for the abridgment on a linear chain reaction model motivated by systems with multiple phosphorylation sites. The analysis shows that if the relaxation time of the fast subsystem is much smaller than the mean firing time of the slow reactions, the abridgment can be applied with little error. This analysis is further verified with numerical experiments for models of bistable switch and oscillations in which linear chain system plays a critical role. PMID:26263559

  18. A multi-scale investigation into seafloor topography of the northern Mid-Atlantic Ridge based on geographic information system analysis

    NASA Astrophysics Data System (ADS)

    Niedzielski, Tomasz; Høines, Åge; Shields, Mark A.; Linley, Thomas D.; Priede, Imants G.

    2013-12-01

    The Mid Atlantic Ridge (MAR) has been identified as an important component of the lower bathyal (800-3500 m depth) benthic biogeographic province in the North Atlantic Ocean. We performed a multi-scale characterization of seafloor topography of the MAR. In the basin-scale analysis, we have used the 30″ General Bathymetric Chart of the Oceans (GEBCO) grid to estimate the area of different components of lower bathyal habitat in the main North Atlantic basin and to produce a corresponding depth-area relationship. The regional-scale investigation is based on swath bathymetry surveys which show the flanks to MAR to comprise a series of sediment-draped flat plains (37.65% of area) with intervening gentle slopes ranging from 5° to 30° (56.70% of area) and slopes steeper than 30° (5.65% of area). The steep slopes have significant areas of hard substrate (70%) comprising bare cliff faces and rock outcrops. Within the local-scale approach, detailed surveys of such steep areas were done by multi-beam sonar and cameras mounted on a Remotely Operated Vehicle (ROV). In several locations, the terrace-like seafloor topography has also been identified. Overall, it has been shown that the MAR lower bathyal is 95% covered with soft sediment.

  19. 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

    2015-12-01

    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. PMID:26559788

  20. 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

  1. 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.

  2. 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.

  3. Multi-scale agent-based brain cancer modeling and prediction of TKI treatment response: Incorporating EGFR signaling pathway and angiogenesis

    PubMed Central

    2012-01-01

    Background The epidermal growth factor receptor (EGFR) signaling pathway and angiogenesis in brain cancer act as an engine for tumor initiation, expansion and response to therapy. Since the existing literature does not have any models that investigate the impact of both angiogenesis and molecular signaling pathways on treatment, we propose a novel multi-scale, agent-based computational model that includes both angiogenesis and EGFR modules to study the response of brain cancer under tyrosine kinase inhibitors (TKIs) treatment. Results The novel angiogenesis module integrated into the agent-based tumor model is based on a set of reaction–diffusion equations that describe the spatio-temporal evolution of the distributions of micro-environmental factors such as glucose, oxygen, TGFα, VEGF and fibronectin. These molecular species regulate tumor growth during angiogenesis. Each tumor cell is equipped with an EGFR signaling pathway linked to a cell-cycle pathway to determine its phenotype. EGFR TKIs are delivered through the blood vessels of tumor microvasculature and the response to treatment is studied. Conclusions Our simulations demonstrated that entire tumor growth profile is a collective behaviour of cells regulated by the EGFR signaling pathway and the cell cycle. We also found that angiogenesis has a dual effect under TKI treatment: on one hand, through neo-vasculature TKIs are delivered to decrease tumor invasion; on the other hand, the neo-vasculature can transport glucose and oxygen to tumor cells to maintain their metabolism, which results in an increase of cell survival rate in the late simulation stages. PMID:22935054

  4. Toward a Multi-Scale Computational Model of Arterial Adaptation in Hypertension: Verification of a Multi-Cell Agent Based Model

    PubMed Central

    Thorne, Bryan C.; Hayenga, Heather N.; Humphrey, Jay D.; Peirce, Shayn M.

    2011-01-01

    Agent-based models (ABMs) represent a novel approach to study and simulate complex mechano chemo-biological responses at the cellular level. Such models have been used to simulate a variety of emergent responses in the vasculature, including angiogenesis and vasculogenesis. Although not used previously to study large vessel adaptations, we submit that ABMs will prove equally useful in such studies when combined with well-established continuum models to form multi-scale models of tissue-level phenomena. In order to couple agent-based and continuum models, however, there is a need to ensure that each model faithfully represents the best data available at the relevant scale and that there is consistency between models under baseline conditions. Toward this end, we describe the development and verification of an ABM of endothelial and smooth muscle cell responses to mechanical stimuli in a large artery. A refined rule-set is proposed based on a broad literature search, a new scoring system for assigning confidence in the rules, and a parameter sensitivity study. To illustrate the utility of these new methods for rule selection, as well as the consistency achieved with continuum-level models, we simulate the behavior of a mouse aorta during homeostasis and in response to both transient and sustained increases in pressure. The simulated responses depend on the altered cellular production of seven key mitogenic, synthetic, and proteolytic biomolecules, which in turn control the turnover of intramural cells and extracellular matrix. These events are responsible for gross changes in vessel wall morphology. This new ABM is shown to be appropriately stable under homeostatic conditions, insensitive to transient elevations in blood pressure, and responsive to increased intramural wall stress in hypertension. PMID:21720536

  5. Multi-scale edge detection with local noise estimate

    NASA Astrophysics Data System (ADS)

    Jiang, Bo; Rahman, Zia-ur

    2010-08-01

    The (unrealistic) assumption that noise can be modeled as independent, additive and uniform can lead to problems when edge detection methods are applied to real or natural images. The main reason for this is because filter scale and threshold for the gradient are difficult to determine at a regional or local scale when the noise estimate is on a global scale. A filter with one global scale might under-smooth areas of high noise, but over-smooth less noisy area. Similarly, a static, global threshold may not be appropriate for the entire image because different regions have different degrees of detail. Thus, some methods use more than one filter for detecting edges and discard the thresholding method in edge discrimination. Multi-scale description of the image mimics the receptive fields of neurons in the early visual cortex of animals. At the small scale, details can be reliably detected. At the larger scale, the contours or the frame get more attention. So, the image features can be fully represented by combining a range of scales. The proposed multi-scale edge detection algorithm utilizes this hierarchical organization to detect and localize edges. Furthermore, instead of using one default global threshold, local dynamic threshold is introduced to discriminate edge or non-edge. Based on a critical value function, the local dynamic threshold for each scale is determined using a novel local noise estimation (LNE) method. Additionally, the proposed algorithm performs connectivity analysis on edge map to ensure that small, disconnected edges are removed. Experiments where this method is applied to a sequence of images of the same scene but with different signal-noise-ratio (SNR), show the method to be robust to noise.

  6. Multi-scale Shock Technique

    Energy Science and Technology Software Center (ESTSC)

    2009-08-01

    The code to be released is a new addition to the LAMMPS molecular dynamics code. LAMMPS is developed and maintained by Sandia, is publicly available, and is used widely by both natioanl laboratories and academics. The new addition to be released enables LAMMPS to perform molecular dynamics simulations of shock waves using the Multi-scale Shock Simulation Technique (MSST) which we have developed and has been previously published. This technique enables molecular dynamics simulations of shockmore » waves in materials for orders of magnitude longer timescales than the direct, commonly employed approach.« less

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

    PubMed

    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

  8. 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

  9. 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

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Multiscale Segmentation of Polarimetric SAR Image Based on Srm Superpixels

    NASA Astrophysics Data System (ADS)

    Lang, F.; Yang, J.; Wu, L.; Li, D.

    2016-06-01

    Multi-scale segmentation of remote sensing image is more systematic and more convenient for the object-oriented image analysis compared to single-scale segmentation. However, the existing pixel-based polarimetric SAR (PolSAR) image multi-scale segmentation algorithms are usually inefficient and impractical. In this paper, we proposed a superpixel-based binary partition tree (BPT) segmentation algorithm by combining the generalized statistical region merging (GSRM) algorithm and the BPT algorithm. First, superpixels are obtained by setting a maximum region number threshold to GSRM. Then, the region merging process of the BPT algorithm is implemented based on superpixels but not pixels. The proposed algorithm inherits the advantages of both GSRM and BPT. The operation efficiency is obviously improved compared to the pixel-based BPT segmentation. Experiments using the Lband ESAR image over the Oberpfaffenhofen test site proved the effectiveness of the proposed method.

  16. Multi-scale elastic graph matching for face detection

    NASA Astrophysics Data System (ADS)

    Sato, Yasuomi D.; Kuriya, Yasutaka

    2013-12-01

    We propose a multi-scale elastic graph matching (MS-EGM) algorithm for face detection, in which the conventional EGM is improved with two simple image processing techniques of the Gabor wavelet-based pyramid and the weak Gabor feature elimination. It is expected to solve difficulties of the real-time process in the conventional EGM. The Gabor wavelet-based pyramid effectively reduces not only the computational cost of the Gabor filtering but also the computational complexity of feature representation of a model face, preserving the facial information. The elimination of the weak Gabor feature extracted from an input image facilitates an accuracy of the Gabor feature similarity computations as unexpected. We then test that the MS-EGM can be capable of rapid face detection processing while achieving a high correct detection rate, comparable to the AdaBoost Haar-like (HL) feature cascade. We also show that the MS-EGM has strong robustness to the image of a face occluded with sunglasses and scarfs because of topologically preserved feature representations.

  17. Multi-Scale Imaging of the Fault Zone Velocity Structure: Double-difference Tomography, Inversion of Fault Zone Headwaves, and Fault Zone Sensitivity Kernels

    NASA Astrophysics Data System (ADS)

    Allam, Amir A.

    In spite of the close relationship between fault zone structure and earthquake mechanics, fault zone structure at seismogenic depths remains poorly understood. How does localization of the primary slip zone vary with depth? Is there a signature of broad persistent damage zones at seismogenic depths? How does fault zone structure merge with regional structure? To answer these questions, we utilize multiple imaging techniques. We apply high-resolution double-difference tomography to the San Jacinto fault zone, invert for velocity structure along the Hayward fault using fault zone head waves, and use analytical results for idealized geometries to validate sensitivity kernels of fault zone phases for use in adjoint tomographic inversions. Double-difference tomography uses the arrival times of P and S waves to invert simultaneously for compressional velocity, shear wave velocity, and source location in three dimensions. We present results in the southern California plate-boundary area, with a focus on the San Jacinto fault zone, which incorporate arrival times of 247,472 P- and 105,448 S-wave picks for 5493 earthquakes recorded at 139 stations. Starting with a layered 1D model, and continuing in later iterations with various updated initial models, we invert the data for Vp and Vs in a 270 km long, 105 km wide and 35 km deep volume using a spatially variable grid with higher density around the San Jacinto. Our final velocity results show zones of low-velocity and high Vp/Vs ratios associated with various fault strands and sedimentary basins, along with clear velocity contrasts across the San Jacinto. While both features are limited to the upper 10km, the low velocity zones generally have higher amplitude and broader distribution in geometrically complex areas, while the velocity contrasts are more pronounced for Vp than Vs. Along the Hayward fault in the San Francisco Bay region, we identify fault zone head waves at eight stations on the northeastern side of the fault

  18. 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

    2015-01-01

    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. PMID:26437382

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

    PubMed Central

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

    2015-01-01

    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. PMID:25808914

  20. 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

  1. 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.

  2. 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.

  3. Ground-based and UAV-Based photogrammetry: A multi-scale, high-resolution mapping tool for structural geology and paleoseismology

    NASA Astrophysics Data System (ADS)

    Bemis, Sean P.; Micklethwaite, Steven; Turner, Darren; James, Mike R.; Akciz, Sinan; Thiele, Sam T.; Bangash, Hasnain Ali

    2014-12-01

    This contribution reviews the use of modern 3D photo-based surface reconstruction techniques for high fidelity surveys of trenches, rock exposures and hand specimens to highlight their potential for paleoseismology and structural geology. We outline the general approach to data acquisition and processing using ground-based photographs acquired from standard DSLR cameras, and illustrate the use of similar processing approaches on imagery from Unmanned Aerial Vehicles (UAVs). It is shown that digital map and trench data can be acquired at ultra-high resolution and in much shorter time intervals than would be normally achievable through conventional grid mapping. The resulting point clouds and textured models are inherently multidimensional (x, y, z, point orientation, colour, texture), archival and easily transformed into orthorectified photomosaics or digital elevation models (DEMs). We provide some examples for the use of such techniques in structural geology and paleoseismology while pointing the interested reader to free and commercial software packages for data processing, visualization and 3D interpretation. Photogrammetric models serve to act as an ideal electronic repository for critical outcrops and observations, similar to the electronic lab book approach employed in the biosciences. This paper also highlights future possibilities for rapid semi-automatic to automatic interpretation of the data and advances in technology.

  4. The application study on the multi-scales integrated prediction method to fractured reservoir description

    NASA Astrophysics Data System (ADS)

    Chen, Shuang-Quan; Zeng, Lian-Bo; Huang, Ping; Sun, Shao-Han; Zhang, Wan-Lu; Li, Xiang-Yang

    2016-03-01

    In this paper, we implement three scales of fracture integrated prediction study by classifying it to macro- (> 1/4 λ), meso- (> 1/100 λ and < 1/4 λ) and micro- (< 1/100 λ) scales. Based on the multi-scales rock physics modelling technique, the seismic azimuthal anisotropy characteristic is analyzed for distinguishing the fractures of meso-scale. Furthermore, by integrating geological core fracture description, image well-logging fracture interpretation, seismic attributes macro-scale fracture prediction and core slice micro-scale fracture characterization, an comprehensive multi-scale fracture prediction methodology and technique workflow are proposed by using geology, well-logging and seismic multi-attributes. Firstly, utilizing the geology core slice observation (Fractures description) and image well-logging data interpretation results, the main governing factors of fracture development are obtained, and then the control factors of the development of regional macro-scale fractures are carried out via modelling of the tectonic stress field. For the meso-scale fracture description, the poststack geometric attributes are used to describe the macro-scale fracture as well, the prestack attenuation seismic attribute is used to predict the meso-scale fracture. Finally, by combining lithological statistic inversion with superposed results of faults, the relationship of the meso-scale fractures, lithology and faults can be reasonably interpreted and the cause of meso-scale fractures can be verified. The micro-scale fracture description is mainly implemented by using the electron microscope scanning of cores. Therefore, the development of fractures in reservoirs is assessed by valuating three classes of fracture prediction results. An integrated fracture prediction application to a real field in Sichuan basin, where limestone reservoir fractures developed, is implemented. The application results in the study area indicates that the proposed multi-scales integrated

  5. 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.

  6. 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. PMID:26999615

  7. 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.

  8. 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

  9. Kolmogorov spectrum consistent optimization for multi-scale flow decomposition

    NASA Astrophysics Data System (ADS)

    Mishra, M.; Liu, X.; Skote, M.; Fu, C.-W.

    2014-05-01

    Multi-scale analysis is widely adopted in turbulence research for studying flow structures corresponding to specific length scales in the Kolmogorov spectrum. In the present work, a new methodology based on novel optimization techniques for scale decomposition is introduced, which leads to a bandpass filter with prescribed properties. With this filter, we can efficiently perform scale decomposition using Fourier transform directly while adequately suppressing Gibbs ringing artifacts. Both 2D and 3D scale decomposition results are presented, together with qualitative and quantitative analysis. The comparison with existing multi-scale analysis technique is conducted to verify the effectiveness of our method. Validation of this decomposition technique is demonstrated both qualitatively and quantitatively. The advantage of the proposed methodology enables a precise specification of continuous length scales while preserving the original structures. These unique features of the proposed methodology may provide future insights into the evolution of turbulent flow structures.

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

    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.

  11. Turbulent Flow Structure Inside a Canopy with Complex Multi-Scale Elements

    NASA Astrophysics Data System (ADS)

    Bai, Kunlun; Katz, Joseph; Meneveau, Charles

    2015-06-01

    Particle image velocimetry laboratory measurements are carried out to study mean flow distributions and turbulent statistics inside a canopy with complex geometry and multiple scales consisting of fractal, tree-like objects. Matching the optical refractive indices of the tree elements with those of the working fluid provides unobstructed optical paths for both illuminations and image acquisition. As a result, the flow fields between tree branches can be resolved in great detail, without optical interference. Statistical distributions of mean velocity, turbulence stresses, and components of dispersive fluxes are documented and discussed. The results show that the trees leave their signatures in the flow by imprinting wake structures with shapes similar to the trees. The velocities in both wake and non-wake regions significantly deviate from the spatially-averaged values. These local deviations result in strong dispersive fluxes, which are important to account for in canopy-flow modelling. In fact, we find that the streamwise normal dispersive flux inside the canopy has a larger magnitude (by up to four times) than the corresponding Reynolds normal stress. Turbulent transport in horizontal planes is studied in the framework of the eddy viscosity model. Scatter plots comparing the Reynolds shear stress and mean velocity gradient are indicative of a linear trend, from which one can calculate the eddy viscosity and mixing length. Similar to earlier results from the wake of a single tree, here we find that inside the canopy the mean mixing length decreases with increasing elevation. This trend cannot be scaled based on a single length scale, but can be described well by a model, which considers the coexistence of multi-scale branches. This agreement indicates that the multi-scale information and the clustering properties of the fractal objects should be taken into consideration in flows inside multi-scale canopies.

  12. Construction of Multi-Scale Consistent Brain Networks: Methods and Applications

    PubMed Central

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

    2015-01-01

    Mapping human brain networks provides a basis for studying brain function and dysfunction, and thus has gained significant interest in recent years. However, modeling human brain networks still faces several challenges including constructing networks at multiple spatial scales and finding common corresponding networks across individuals. As a consequence, many previous methods were designed for a single resolution or scale of brain network, though the brain networks are multi-scale in nature. To address this problem, this paper presents a novel approach to constructing multi-scale common structural brain networks from DTI data via an improved multi-scale spectral clustering applied on our recently developed and validated DICCCOLs (Dense Individualized and Common Connectivity-based Cortical Landmarks). Since the DICCCOL landmarks possess intrinsic structural correspondences across individuals and populations, we employed the multi-scale spectral clustering algorithm to group the DICCCOL landmarks and their connections into sub-networks, meanwhile preserving the intrinsically-established correspondences across multiple scales. Experimental results demonstrated that the proposed method can generate multi-scale consistent and common structural brain networks across subjects, and its reproducibility has been verified by multiple independent datasets. As an application, these multi-scale networks were used to guide the clustering of multi-scale fiber bundles and to compare the fiber integrity in schizophrenia and healthy controls. In general, our methods offer a novel and effective framework for brain network modeling and tract-based analysis of DTI data. PMID:25876038

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

    PubMed

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

    2015-01-01

    Mapping human brain networks provides a basis for studying brain function and dysfunction, and thus has gained significant interest in recent years. However, modeling human brain networks still faces several challenges including constructing networks at multiple spatial scales and finding common corresponding networks across individuals. As a consequence, many previous methods were designed for a single resolution or scale of brain network, though the brain networks are multi-scale in nature. To address this problem, this paper presents a novel approach to constructing multi-scale common structural brain networks from DTI data via an improved multi-scale spectral clustering applied on our recently developed and validated DICCCOLs (Dense Individualized and Common Connectivity-based Cortical Landmarks). Since the DICCCOL landmarks possess intrinsic structural correspondences across individuals and populations, we employed the multi-scale spectral clustering algorithm to group the DICCCOL landmarks and their connections into sub-networks, meanwhile preserving the intrinsically-established correspondences across multiple scales. Experimental results demonstrated that the proposed method can generate multi-scale consistent and common structural brain networks across subjects, and its reproducibility has been verified by multiple independent datasets. As an application, these multi-scale networks were used to guide the clustering of multi-scale fiber bundles and to compare the fiber integrity in schizophrenia and healthy controls. In general, our methods offer a novel and effective framework for brain network modeling and tract-based analysis of DTI data. PMID:25876038

  14. Functional derivatives for multi-scale modeling

    NASA Astrophysics Data System (ADS)

    Reeve, Samuel; Strachan, Alejandro

    2015-03-01

    As we look beyond petascale computing and towards the exascale, effectively utilizing computational resources by using multi-fidelity and multi-scale materials simulations becomes increasingly important. Determining when and where to run high-fidelity simulations in order to have the most effect on a given quantity of interest (QoI) is a difficult problem. This work utilizes functional uncertainty quantification (UQ) for this task. While most UQ focuses on uncertainty in output from uncertainty in input parameters, we focus on uncertainty from the function itself (e.g. from using a specific functional form for an interatomic potential or constitutive law). In the case of a multi-scale simulation with a given constitutive law, calculating the functional derivative of the QoI with respect to that constitutive law can determine where a fine-scale model evaluation will maximize the increase in accuracy of the predicted QoI. Additionally, for a given computational budget the optimal set of coarse and fine-scale simulations can be determined. Numerical calculation of the functional derivative has been developed and methods of including this work within existing multi-fidelity and multi-scale orchestrators are explored.

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

    PubMed

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

    2015-12-01

    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

  16. 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

  17. 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.

  18. 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. PMID:27460959

  19. 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.

  20. 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.

  1. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    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.

  3. 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.

  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. PMID:27056478

  5. 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…

  6. 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

  7. Global and Multi-scale Dynamics of the Magnetosphere

    NASA Astrophysics Data System (ADS)

    Sharma, A. S.; Sitnov, M. I.

    2001-05-01

    Earth's magnetosphere during substorms demonstrates a number of characteristic features such as low effective dimension, hysteresis and power-law spectra of fluctuations on different scales. The dynamics, on the largest scale, associated with substorms, are in reasonable agreement with low-dimensional magnetospheric models and in particular those of inverse bifurcations. However, deviations from the low-dimensional picture are not negligible, making the nonequilibrium phase transition more appropriate as a dynamical analogue of the substorm activity. On the other hand, the multi- scale magnetospheric dynamics cannot be restricted to the self-organized criticality (SOC), which is based on a class of mathematical analogues of sandpiles. Like real sandpiles the magnetosphere demonstrates during substorms the features, which are distinct from SOC and more reminiscent again to conventional phase transitions. While the multi-scale substorm activity resembles second-order phase transitions, the largest substorm avalanches are shown to reveal the features of first-order nonequilibrium transitions including hysteresis phenomenon and global structure of the type of the "temperature-pressure-density" diagram. Moreover, this diagram allows one to compute a critical exponent, consistent with the second-order phase transitions, and reflects the multiscale aspect of the substorm activity, different from power-law frequency and scale spectra of autonomous systems. In contrast to SOC exponents, the exponent relates input and output parameters of the magnetosphere. Using an analogy with the dynamical Ising model in the mean-field approximation we show the connection between this data-derived exponent of nonequilibrium transitions in the magnetosphere and the standard critical exponent β of equilibrium second-order phase transitions. We discuss also further developments of the phase tarnsition approach to modeling magnetospheric activity using the multifractal, mutual information

  8. 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.

  9. 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

  10. 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.

  11. A hybrid approach to multi-scale modelling of cancer.

    PubMed

    Osborne, J M; Walter, A; Kershaw, S K; Mirams, G R; Fletcher, A G; Pathmanathan, P; Gavaghan, D; Jensen, O E; Maini, P K; Byrne, H M

    2010-11-13

    In this paper, we review multi-scale models of solid tumour growth and discuss a middle-out framework that tracks individual cells. By focusing on the cellular dynamics of a healthy colorectal crypt and its invasion by mutant, cancerous cells, we compare a cell-centre, a cell-vertex and a continuum model of cell proliferation and movement. All models reproduce the basic features of a healthy crypt: cells proliferate near the crypt base, they migrate upwards and are sloughed off near the top. The models are used to establish conditions under which mutant cells are able to colonize the crypt either by top-down or by bottom-up invasion. While the continuum model is quicker and easier to implement, it can be difficult to relate system parameters to measurable biophysical quantities. Conversely, the greater detail inherent in the multi-scale models means that experimentally derived parameters can be incorporated and, therefore, these models offer greater scope for understanding normal and diseased crypts, for testing and identifying new therapeutic targets and for predicting their impacts. PMID:20921009

  12. 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

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

    PubMed

    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

  14. Automatic reconstruction of neural morphologies with multi-scale tracking.

    PubMed

    Choromanska, Anna; Chang, Shih-Fu; Yuste, Rafael

    2012-01-01

    Neurons have complex axonal and dendritic morphologies that are the structural building blocks of neural circuits. The traditional method to capture these morphological structures using manual reconstructions is time-consuming and partly subjective, so it appears important to develop automatic or semi-automatic methods to reconstruct neurons. Here we introduce a fast algorithm for tracking neural morphologies in 3D with simultaneous detection of branching processes. The method is based on existing tracking procedures, adding the machine vision technique of multi-scaling. Starting from a seed point, our algorithm tracks axonal or dendritic arbors within a sphere of a variable radius, then moves the sphere center to the point on its surface with the shortest Dijkstra path, detects branching points on the surface of the sphere, scales it until branches are well separated and then continues tracking each branch. We evaluate the performance of our algorithm on preprocessed data stacks obtained by manual reconstructions of neural cells, corrupted with different levels of artificial noise, and unprocessed data sets, achieving 90% precision and 81% recall in branch detection. We also discuss limitations of our method, such as reconstructing highly overlapping neural processes, and suggest possible improvements. Multi-scaling techniques, well suited to detect branching structures, appear a promising strategy for automatic neuronal reconstructions. PMID:22754498

  15. 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

  16. An Adaptive Digital Image Watermarking Algorithm Based on Morphological Haar Wavelet Transform

    NASA Astrophysics Data System (ADS)

    Huang, Xiaosheng; Zhao, Sujuan

    At present, much more of the wavelet-based digital watermarking algorithms are based on linear wavelet transform and fewer on non-linear wavelet transform. In this paper, we propose an adaptive digital image watermarking algorithm based on non-linear wavelet transform--Morphological Haar Wavelet Transform. In the algorithm, the original image and the watermark image are decomposed with multi-scale morphological wavelet transform respectively. Then the watermark information is adaptively embedded into the original image in different resolutions, combining the features of Human Visual System (HVS). The experimental results show that our method is more robust and effective than the ordinary wavelet transform algorithms.

  17. 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

  18. Multi-scale, multi-resolution brain cancer modeling.

    PubMed

    Zhang, Le; Chen, L Leon; Deisboeck, Thomas S

    2009-03-01

    In advancing discrete-based computational cancer models towards clinical applications, one faces the dilemma of how to deal with an ever growing amount of biomedical data that ought to be incorporated eventually in one form or another. Model scalability becomes of paramount interest. In an effort to start addressing this critical issue, here, we present a novel multi-scale and multi-resolution agent-based in silico glioma model. While 'multi-scale' refers to employing an epidermal growth factor receptor (EGFR)-driven molecular network to process cellular phenotypic decisions within the micro-macroscopic environment, 'multi-resolution' is achieved through algorithms that classify cells to either active or inactive spatial clusters, which determine the resolution they are simulated at. The aim is to assign computational resources where and when they matter most for maintaining or improving the predictive power of the algorithm, onto specific tumor areas and at particular times. Using a previously described 2D brain tumor model, we have developed four different computational methods for achieving the multi-resolution scheme, three of which are designed to dynamically train on the high-resolution simulation that serves as control. To quantify the algorithms' performance, we rank them by weighing the distinct computational time savings of the simulation runs versus the methods' ability to accurately reproduce the high-resolution results of the control. Finally, to demonstrate the flexibility of the underlying concept, we show the added value of combining the two highest-ranked methods. The main finding of this work is that by pursuing a multi-resolution approach, one can reduce the computation time of a discrete-based model substantially while still maintaining a comparably high predictive power. This hints at even more computational savings in the more realistic 3D setting over time, and thus appears to outline a possible path to achieve scalability for the all

  19. 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.

  20. 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.

  1. Triad interactions in multi-scale ITG/TEM/ETG turbulence

    NASA Astrophysics Data System (ADS)

    Maeyama, Shinya; Watanabe, Tomohiko; Idomura, Yasuhiro; Nakata, Motoki; Ishizawa, Akihiro; Nunami, Masanori

    2015-11-01

    Most of turbulent transport studies assume scale separation between electron- and ion-scale turbulence. However, latest massively parallel simulations based on gyrokinetics reveal that multi-scale interactions between electron- and ion-scale turbulence can influence turbulent transport [S. Maeyama, Phys. Rev. Lett. 114, 255002 (2015)]. The physical mechanism is investigated by applying triad transfer analysis. It is revealed that short-wave-length ITG turbulent eddies stabilize electron-scale streamers. Additionally, it is found that electron-scale turbulence has a damping effect on zonal flows. As a result, turbulent transport spectrum obtained from the multi-scale turbulence simulation differs from the sum of ones obtained from single-scale simulations. We will discuss gyrokinetic triad transfer analysis and the applicability of its fluid approximation, and explain the physical mechanism of multi-scale interactions by means of triad transfer analysis.

  2. 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

  3. 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

  4. 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

  5. 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.

  6. Multi-scale Observation of Biological Interactions of Nanocarriers: from Nano to Macro

    PubMed Central

    Jin, Su-Eon; Bae, Jin Woo; Hong, Seungpyo

    2010-01-01

    Microscopic observations have played a key role in recent advancements in nanotechnology-based biomedical sciences. In particular, multi-scale observation is necessary to fully understand the nano-bio interfaces where a large amount of unprecedented phenomena have been reported. This review describes how to address the physicochemical and biological interactions of nanocarriers within the biological environments using microscopic tools. The imaging techniques are categorized based on the size scale of detection. For observation of the nano-scale biological interactions of nanocarriers, we discuss atomic force microscopy (AFM), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). For the micro to macro-scale (in vitro and in vivo) observation, we focus on confocal laser scanning microscopy (CLSM) as well as in vivo imaging systems such as magnetic resonance imaging (MRI), superconducting quantum interference devices (SQUIDs), and IVIS®. Additionally, recently developed combined techniques such as AFM-CLSM, correlative Light and Electron Microscopy (CLEM), and SEM-spectroscopy are also discussed. In this review, we describe how each technique helps elucidate certain physicochemical and biological activities of nanocarriers such as dendrimers, polymers, liposomes, and polymeric/inorganic nanoparticles, thus providing a toolbox for bioengineers, pharmaceutical scientists, biologists, and research clinicians. PMID:20232368

  7. 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.

  8. Multi-scale monitoring of a marine geologic methane source in the Santa Barbara Channel using imaging spectrometry, ARCTAS-CARB in situ sampling and coastal hourly total hydrocarbon measurements

    NASA Astrophysics Data System (ADS)

    Bradley, E. S.; Leifer, I.; Roberts, D.; Dennison, P. E.; Margolis, J.; Moritsch, M.; Diskin, G. S.; Sachse, G. W.

    2009-12-01

    The Coal Oil Point (COP) hydrocarbon seep field off the coast of Santa Barbara, CA is one of the most active and best-studied marine geologic methane sources in the world and contributes to elevated terrestrial methane concentrations downwind. In this study, we investigate the spatiotemporal variability of this local source and the influence of meteorological conditions on transport and concentration. A methane plume emanating from Trilogy Seep was mapped with the Airborne Visible Infrared Imaging Spectrometer at a 7.5 m resolution with a short-wave infrared band ratio technique. This structure agrees with the local wind speed and direction and is orthogonal to the surface currents. ARCTAS-CARB aircraft in situ sampling of lower-troposphere methane is compared to sub-hour total hydrocarbon concentration (THC) measurements from the Santa Barbara Air Pollution Control District (SBAPCD) station located near COP. Hourly SBAPCD THC values from 1980-2008 demonstrate a decrease in seep source strength until the late 1990s, followed by a consistent increase. The occurrence of elevated SBAPCD THC values for onshore wind conditions as well as numerous positive outliers as high as 17 ppm suggests that seep field emissions are both quasi-steady state and transient, direct (bubble) and diffuse (outgassing). As demonstrated for the COP seeps, the combination of imaging spectrometry, aircraft in situ sampling, and ground-based monitoring provides a powerful approach for understanding local methane sources and transport processes.

  9. 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

  10. 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.

  11. Research on Medical Image Enhancement Algorithm Based on GSM Model for Wavelet Coefficients

    NASA Astrophysics Data System (ADS)

    Wang, Lei; Jiang, Nian-de; Ning, Xing

    For the complexity and application diversity of medical CT image, this article presents a medical CT Image enhancing algorithm based on Gaussian Scale Mixture Model for wavelet coefficient in the study of wavelet multi-scale analysis. The noisy image is firstly denoised in auto-adapted Wiener filter. Secondly, through the qualitative analysis and classification of wavelet coefficients for the signal and noise, the wavelet's approximate distribution and statistical characteristics are described, combining GSM(Gaussian scale mixture) model for wavelet coefficient in this paper. It is shown that this algorithm can improve the denoised result and enhanced the medical CT image obviously.

  12. 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.

  13. The research of infrared image enhancement algorithm based on human vision

    NASA Astrophysics Data System (ADS)

    Wang, Chen; Gao, Sili; Tang, Xinyi

    2014-11-01

    Infrared images have their own characteristics: low contrast, great noise, large dynamic range and poor visual effect. The traditional image enhancement algorithms have certain limitations and can't achieve a good visual effect. In order to obtain a good visual effect and improve the target detection and recognition capabilities, the paper studied various enhancement methods. After analyzing the retinex theory, we choose the image enhancement method based on human visual system called retinex to process infrared images. Retinex has been used to enhance the visible light image. To do experiment on infrared image enhancement, multi-scale retinex method gets ideal visual effect. On this basis, we propose an improved multi-scale Retinex (AMSR) method based on adaptive adjustment. This method can adaptively adjust the gray level and contrast of the image, enhance the details, make the weak small targets more conducive to the human eye observation. While, it is impossible to find a method suited for all infrared images with different characteristics. So, we use several traditional image enhancement algorithms to compare with the retinex algorithms. And calculate the objective evaluation factors, including average, standard deviation, entropy and so on. After observation the processing results and analyzing these evaluation factors, the AMSR algorithm is proved having its applicability and superiority. In order to select a suitable infrared image enhancement algorithms, we analyze the applicability of each enhancement methods for infrared image has obvious characteristics, To some extent, the study is significant to the infrared target detection and recognition.

  14. Application of multi-scale feature extraction to surface defect classification of hot-rolled steels

    NASA Astrophysics Data System (ADS)

    Xu, Ke; Ai, Yong-hao; Wu, Xiu-yong

    2013-01-01

    Feature extraction is essential to the classification of surface defect images. The defects of hot-rolled steels distribute in different directions. Therefore, the methods of multi-scale geometric analysis (MGA) were employed to decompose the image into several directional subbands at several scales. Then, the statistical features of each subband were calculated to produce a high-dimensional feature vector, which was reduced to a lower-dimensional vector by graph embedding algorithms. Finally, support vector machine (SVM) was used for defect classification. The multi-scale feature extraction method was implemented via curvelet transform and kernel locality preserving projections (KLPP). Experiment results show that the proposed method is effective for classifying the surface defects of hot-rolled steels and the total classification rate is up to 97.33%.

  15. 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.

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

    NASA Astrophysics Data System (ADS)

    Tuxen Bettman, Karin

    2007-12-01

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

  17. Using Multi-scale Modeling Systems to Study the Precipitation Processes

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo

    2007-01-01

    Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (CRM), (2) a regional scale model, (3) a coupled CRM and global model, and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer processes and the explicit cloud-radiation, and cloudland surface interactive processes are applied in this multi-scale modeling system. 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.

  18. Morphological center operator based infrared and visible image fusion through correlation coefficient

    NASA Astrophysics Data System (ADS)

    Bai, Xiangzhi

    2016-05-01

    It is important to well maintain the information of infrared (IR) and visible images, including image regions and details, in a fusion image. To be effective for fusion, an algorithm for fusion IR and visible images based on the morphological center operator through feature extraction and correlation coefficient is given. This paper utilizes the contrast enlargement strategy for fusion. Firstly, the morphological center or anti-center operator identifies the bright and dim features of the IR and visible images, and these identified features are used for fusion based on the correlation coefficient. Secondly, the multi-scale morphological theory is employed to extract the multi-scale features through the correlation coefficient based strategy to form the final fusion features. Finally, the extracted final fusion features are combined to form the final fusion image by utilizing the contrast enlargement strategy. Because of the effectively feature identifying by the morphological center and anti-center operators, the proposed algorithm has good performance for IR and visible image fusion. Experiments on different IR and visible images verified that the proposed algorithm performed effectively.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Study on multi-scale urban planning supported by spatial information technology

    NASA Astrophysics Data System (ADS)

    Dang, Anrong; He, Xindong; Li, Yongfu

    2008-10-01

    Considering the demand of urban and rural planning and the characteristics of spatial information technology (SIT), the study focuses on the application of SIT to support multi-scale urban planning. Three scales of urban and rural planning, such as city and town system planning, urban master planning, and detailed urban planning, were studied based on SIT. Firstly, tacking Great Beijing Region as an example, which includes Beijing, Tianjin, and northern of Hebei province, the city and town system planning was studied, supported by the theory of spatial interaction between cities and towns, and GIS spatial analysis. Then, for the urban master planning of Beijing, the RS and GIS were applied to do the spatial development analysis based on RS image data and GIS spatial analysis. Regarding to the conservation planning of Beijing's Inner city, the third scale is detailed urban planning. RS, GIS, and VR were integrated to determine the conservation region and digital conservation way as well. Finally, three conclusions were worked out.

  4. A multi-scale strength model with phase transformation

    NASA Astrophysics Data System (ADS)

    Barton, Nathan; Arsenlis, Athanasios; Rhee, Moono; Marian, Jaime; Bernier, Joel V.; Tang, Meijie; Yang, Lin

    2012-03-01

    We present a multi-scale strength model that includes phase transformation. In each phase, strength depends on pressure, strain rate, temperature, and evolving dislocation density descriptors. A donor cell type of approach is used for the transfer of dislocation density between phases. While the shear modulus can be modeled as smooth through the BCC to rhombohedral transformation in vanadium, the multi-phase strength model predicts abrupt changes in the material strength due to changes in dislocation kinetics. In the rhombohedral phase, the dislocation density is decomposed into populations associated with short and long Burgers vectors. Strength model construction employs an information passing paradigm to span from the atomistic level to the continuum level. Simulation methods in the overall hierarchy include density functional theory, molecular statics, molecular dynamics, dislocation dynamics, and continuum based approaches. We demonstrate the behavior of the model through simulations of Rayleigh Taylor instability growth experiments of the type used to assess material strength at high pressure and strain rate.

  5. A multi-scale strength model with phase transformation

    NASA Astrophysics Data System (ADS)

    Barton, N.; Arsenlis, A.; Rhee, M.; Marian, J.; Bernier, J.; Tang, M.; Yang, L.

    2011-06-01

    We present a multi-scale strength model that includes phase transformation. In each phase, strength depends on pressure, strain rate, temperature, and evolving dislocation density descriptors. A donor cell type of approach is used for the transfer of dislocation density between phases. While the shear modulus can be modeled as smooth through the BCC to rhombohedral transformation in vanadium, the multi-phase strength model predicts abrupt changes in the material strength due to changes in dislocation kinetics. In the rhombohedral phase, the dislocation density is decomposed into populations associated with short and long Burgers vectors. Strength model construction employs an information passing paradigm to span from the atomistic level to the continuum level. Simulation methods in the overall hierarchy include density functional theory, molecular statics, molecular dynamics, dislocation dynamics, and continuum based approaches. We demonstrate the behavior of the model through simulations of Rayleigh Taylor instability growth experiments of the type used to assess material strength at high pressure and strain rate. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 (LLNL-ABS-464695).

  6. 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.

  7. 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

  8. 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.

  9. Multi-scale modeling of hemodynamics in the cardiovascular system

    NASA Astrophysics Data System (ADS)

    Liu, Hao; Liang, Fuyou; Wong, Jasmin; Fujiwara, Takashi; Ye, Wenjing; Tsubota, Ken-iti; Sugawara, Michiko

    2015-08-01

    The human cardiovascular system is a closed-loop and complex vascular network with multi-scaled heterogeneous hemodynamic phenomena. Here, we give a selective review of recent progress in macro-hemodynamic modeling, with a focus on geometrical multi-scale modeling of the vascular network, micro-hemodynamic modeling of microcirculation, as well as blood cellular, subcellular, endothelial biomechanics, and their interaction with arterial vessel mechanics. We describe in detail the methodology of hemodynamic modeling and its potential applications in cardiovascular research and clinical practice. In addition, we present major topics for future study: recent progress of patient-specific hemodynamic modeling in clinical applications, micro-hemodynamic modeling in capillaries and blood cells, and the importance and potential of the multi-scale hemodynamic modeling.

  10. Multi-scale Plasmonic Nanoparticles and the Inverse Problem

    PubMed Central

    Odom, Teri W.; You, Eun-Ah; Sweeney, Christina M.

    2012-01-01

    This Perspective describes how multi-scale plasmonic structures with two or more length scales (fine, medium, coarse) provide an experimental route for addressing the inverse problem. Specific near-field and far-field optical properties can be targeted and compiled into a plasmon resonance library by taking advantage of length scales spanning three orders of magnitude, from 1 nm to greater than 1000 nm, in a single particle. Examples of multi-scale 1D, 2D, and 3D gold structures created by nanofabrication tools and templates are discussed, and unexpected optical properties compared to those from their smaller counterparts are emphasized. One application of multi-scale particle dimers for surface-enhanced Raman spectroscopy is also described. PMID:23066451