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Sample records for detects regular spatial

  1. Statistical analysis of 3D images detects regular spatial distributions of centromeres and chromocenters in animal and plant nuclei.

    Directory of Open Access Journals (Sweden)

    Philippe Andrey

    Full Text Available In eukaryotes, the interphase nucleus is organized in morphologically and/or functionally distinct nuclear "compartments". Numerous studies highlight functional relationships between the spatial organization of the nucleus and gene regulation. This raises the question of whether nuclear organization principles exist and, if so, whether they are identical in the animal and plant kingdoms. We addressed this issue through the investigation of the three-dimensional distribution of the centromeres and chromocenters. We investigated five very diverse populations of interphase nuclei at different differentiation stages in their physiological environment, belonging to rabbit embryos at the 8-cell and blastocyst stages, differentiated rabbit mammary epithelial cells during lactation, and differentiated cells of Arabidopsis thaliana plantlets. We developed new tools based on the processing of confocal images and a new statistical approach based on G- and F- distance functions used in spatial statistics. Our original computational scheme takes into account both size and shape variability by comparing, for each nucleus, the observed distribution against a reference distribution estimated by Monte-Carlo sampling over the same nucleus. This implicit normalization allowed similar data processing and extraction of rules in the five differentiated nuclei populations of the three studied biological systems, despite differences in chromosome number, genome organization and heterochromatin content. We showed that centromeres/chromocenters form significantly more regularly spaced patterns than expected under a completely random situation, suggesting that repulsive constraints or spatial inhomogeneities underlay the spatial organization of heterochromatic compartments. The proposed technique should be useful for identifying further spatial features in a wide range of cell types.

  2. Hidden Regular Variation: Detection and Estimation

    CERN Document Server

    Mitra, Abhimanyu

    2010-01-01

    Hidden regular variation defines a subfamily of distributions satisfying multivariate regular variation on $\\mathbb{E} = [0, \\infty]^d \\backslash \\{(0,0, ..., 0) \\} $ and models another regular variation on the sub-cone $\\mathbb{E}^{(2)} = \\mathbb{E} \\backslash \\cup_{i=1}^d \\mathbb{L}_i$, where $\\mathbb{L}_i$ is the $i$-th axis. We extend the concept of hidden regular variation to sub-cones of $\\mathbb{E}^{(2)}$ as well. We suggest a procedure of detecting the presence of hidden regular variation, and if it exists, propose a method of estimating the limit measure exploiting its semi-parametric structure. We exhibit examples where hidden regular variation yields better estimates of probabilities of risk sets.

  3. Spatially varying regularization of deconvolution in 3D microscopy.

    Science.gov (United States)

    Seo, J; Hwang, S; Lee, J-M; Park, H

    2014-08-01

    Confocal microscopy has become an essential tool to explore biospecimens in 3D. Confocal microcopy images are still degraded by out-of-focus blur and Poisson noise. Many deconvolution methods including the Richardson-Lucy (RL) method, Tikhonov method and split-gradient (SG) method have been well received. The RL deconvolution method results in enhanced image quality, especially for Poisson noise. Tikhonov deconvolution method improves the RL method by imposing a prior model of spatial regularization, which encourages adjacent voxels to appear similar. The SG method also contains spatial regularization and is capable of incorporating many edge-preserving priors resulting in improved image quality. The strength of spatial regularization is fixed regardless of spatial location for the Tikhonov and SG method. The Tikhonov and the SG deconvolution methods are improved upon in this study by allowing the strength of spatial regularization to differ for different spatial locations in a given image. The novel method shows improved image quality. The method was tested on phantom data for which ground truth and the point spread function are known. A Kullback-Leibler (KL) divergence value of 0.097 is obtained with applying spatially variable regularization to the SG method, whereas KL value of 0.409 is obtained with the Tikhonov method. In tests on a real data, for which the ground truth is unknown, the reconstructed data show improved noise characteristics while maintaining the important image features such as edges.

  4. Spatially adaptive regularized iterative high-resolution image reconstruction algorithm

    Science.gov (United States)

    Lim, Won Bae; Park, Min K.; Kang, Moon Gi

    2000-12-01

    High resolution images are often required in applications such as remote sensing, frame freeze in video, military and medical imaging. Digital image sensor arrays, which are used for image acquisition in many imaging systems, are not dense enough to prevent aliasing, so the acquired images will be degraded by aliasing effects. To prevent aliasing without loss of resolution, a dense detector array is required. But it may be very costly or unavailable, thus, many imaging systems are designed to allow some level of aliasing during image acquisition. The purpose of our work is to reconstruct an unaliased high resolution image from the acquired aliased image sequence. In this paper, we propose a spatially adaptive regularized iterative high resolution image reconstruction algorithm for blurred, noisy and down-sampled image sequences. The proposed approach is based on a Constrained Least Squares (CLS) high resolution reconstruction algorithm, with spatially adaptive regularization operators and parameters. These regularization terms are shown to improve the reconstructed image quality by forcing smoothness, while preserving edges in the reconstructed high resolution image. Accurate sub-pixel motion registration is the key of the success of the high resolution image reconstruction algorithm. However, sub-pixel motion registration may have some level of registration error. Therefore, a reconstruction algorithm which is robust against the registration error is required. The registration algorithm uses a gradient based sub-pixel motion estimator which provides shift information for each of the recorded frames. The proposed algorithm is based on a technique of high resolution image reconstruction, and it solves spatially adaptive regularized constrained least square minimization functionals. In this paper, we show that the reconstruction algorithm gives dramatic improvements in the resolution of the reconstructed image and is effective in handling the aliased information. The

  5. Longitudinal deformation models, spatial regularizations and learning strategies to quantify Alzheimer's disease progression.

    Science.gov (United States)

    Fiot, Jean-Baptiste; Raguet, Hugo; Risser, Laurent; Cohen, Laurent D; Fripp, Jurgen; Vialard, François-Xavier

    2014-01-01

    In the context of Alzheimer's disease, two challenging issues are (1) the characterization of local hippocampal shape changes specific to disease progression and (2) the identification of mild-cognitive impairment patients likely to convert. In the literature, (1) is usually solved first to detect areas potentially related to the disease. These areas are then considered as an input to solve (2). As an alternative to this sequential strategy, we investigate the use of a classification model using logistic regression to address both issues (1) and (2) simultaneously. The classification of the patients therefore does not require any a priori definition of the most representative hippocampal areas potentially related to the disease, as they are automatically detected. We first quantify deformations of patients' hippocampi between two time points using the large deformations by diffeomorphisms framework and transport these deformations to a common template. Since the deformations are expected to be spatially structured, we perform classification combining logistic loss and spatial regularization techniques, which have not been explored so far in this context, as far as we know. The main contribution of this paper is the comparison of regularization techniques enforcing the coefficient maps to be spatially smooth (Sobolev), piecewise constant (total variation) or sparse (fused LASSO) with standard regularization techniques which do not take into account the spatial structure (LASSO, ridge and ElasticNet). On a dataset of 103 patients out of ADNI, the techniques using spatial regularizations lead to the best classification rates. They also find coherent areas related to the disease progression.

  6. Diffuse light tomography to detect blood vessels using Tikhonov regularization

    Science.gov (United States)

    Kazanci, Huseyin O.; Jacques, Steven L.

    2016-04-01

    Detection of blood vessels within light-scattering tissues involves detection of subtle shadows as blood absorbs light. These shadows are diffuse but measurable by a set of source-detector pairs in a spatial array of sources and detectors on the tissue surface. The measured shadows can reconstruct the internal position(s) of blood vessels. The tomographic method involves a set of Ns sources and Nd detectors such that Nsd = Ns x Nd source-detector pairs produce Nsd measurements, each interrogating the tissue with a unique perspective, i.e., a unique region of sensitivity to voxels within the tissue. This tutorial report describes the reconstruction of the image of a blood vessel within a soft tissue based on such source-detector measurements, by solving a matrix equation using Tikhonov regularization. This is not a novel contribution, but rather a simple introduction to a well-known method, demonstrating its use in mapping blood perfusion.

  7. A Regularized Solution to Edge Detection.

    Science.gov (United States)

    1985-05-01

    Hildreth, E. C. "Implementation of a theory of edge detection ," AI-TR-579, MIT Al Lab, 1980. Lunscher, W. H. H. "The asymptotic optimal frequency domain...filter for edge detection," IEEE Trans. PAMI, 6, 678-680, 1983. Marr, D. C. and Hildreth, E. C. " Theory of edge detection ," Proc. R. Soc. Lond. B

  8. Longitudinal deformation models, spatial regularizations and learning strategies to quantify Alzheimer's disease progression

    Directory of Open Access Journals (Sweden)

    Jean-Baptiste Fiot

    2014-01-01

    Full Text Available In the context of Alzheimer's disease, two challenging issues are (1 the characterization of local hippocampal shape changes specific to disease progression and (2 the identification of mild-cognitive impairment patients likely to convert. In the literature, (1 is usually solved first to detect areas potentially related to the disease. These areas are then considered as an input to solve (2. As an alternative to this sequential strategy, we investigate the use of a classification model using logistic regression to address both issues (1 and (2 simultaneously. The classification of the patients therefore does not require any a priori definition of the most representative hippocampal areas potentially related to the disease, as they are automatically detected. We first quantify deformations of patients' hippocampi between two time points using the large deformations by diffeomorphisms framework and transport these deformations to a common template. Since the deformations are expected to be spatially structured, we perform classification combining logistic loss and spatial regularization techniques, which have not been explored so far in this context, as far as we know. The main contribution of this paper is the comparison of regularization techniques enforcing the coefficient maps to be spatially smooth (Sobolev, piecewise constant (total variation or sparse (fused LASSO with standard regularization techniques which do not take into account the spatial structure (LASSO, ridge and ElasticNet. On a dataset of 103 patients out of ADNI, the techniques using spatial regularizations lead to the best classification rates. They also find coherent areas related to the disease progression.

  9. Automatic Constraint Detection for 2D Layout Regularization

    KAUST Repository

    Jiang, Haiyong

    2015-09-18

    In this paper, we address the problem of constraint detection for layout regularization. As layout we consider a set of two-dimensional elements where each element is represented by its bounding box. Layout regularization is important for digitizing plans or images, such as floor plans and facade images, and for the improvement of user created contents, such as architectural drawings and slide layouts. To regularize a layout, we aim to improve the input by detecting and subsequently enforcing alignment, size, and distance constraints between layout elements. Similar to previous work, we formulate the layout regularization as a quadratic programming problem. In addition, we propose a novel optimization algorithm to automatically detect constraints. In our results, we evaluate the proposed framework on a variety of input layouts from different applications, which demonstrates our method has superior performance to the state of the art.

  10. Automatic Constraint Detection for 2D Layout Regularization.

    Science.gov (United States)

    Jiang, Haiyong; Nan, Liangliang; Yan, Dong-Ming; Dong, Weiming; Zhang, Xiaopeng; Wonka, Peter

    2016-08-01

    In this paper, we address the problem of constraint detection for layout regularization. The layout we consider is a set of two-dimensional elements where each element is represented by its bounding box. Layout regularization is important in digitizing plans or images, such as floor plans and facade images, and in the improvement of user-created contents, such as architectural drawings and slide layouts. To regularize a layout, we aim to improve the input by detecting and subsequently enforcing alignment, size, and distance constraints between layout elements. Similar to previous work, we formulate layout regularization as a quadratic programming problem. In addition, we propose a novel optimization algorithm that automatically detects constraints. We evaluate the proposed framework using a variety of input layouts from different applications. Our results demonstrate that our method has superior performance to the state of the art.

  11. Visual mismatch negativity reveals automatic detection of sequential regularity violation

    Directory of Open Access Journals (Sweden)

    Gábor eStefanics

    2011-05-01

    Full Text Available Sequential regularities are abstract rules based on repeating sequences of environmental events, which are useful to make predictions about future events. As the processes underlying visual mismatch negativity (vMMN are sensitive to complex stimulus changes, this event-related potential component, like its auditory counterpart, may be an index of a primitive system of intelligence. Here we tested whether the visual system is capable to detect abstract sequential regularity in unattended stimulus sequences. In our first experiment we investigated the emergence of vMMN and other change-related activity to stimuli violating abstract rules. Red and green disk patterns were delivered in pairs. When in the majority of pairs the colors were identical within the pairs, deviant pairs with different colors for the second member of the pair elicited vMMN. Spatially more extended vMMN responses with longer latency were observed for deviants with 10% compared to 30% probability. In our second experiment utilizing oddball sequences, we tested the emergence of vMMN to violations of a concrete, feature-based rule of a repetition of a standard color. Deviant colors elicited a vMMN response in the oddball sequences. VMMN was larger for the second member of the pair, i.e. after a shorter stimulus onset asynchrony (SOA. This result corresponds to the expected SOA/(vMMN relationship. Our results show that the system underlying vMMN is sensitive to abstract probability rules and this component can be considered as a correlate of violated predictions about the characteristics of environmental events.

  12. Spatially-Variant Tikhonov Regularization for Double-Difference Waveform Inversion

    Energy Technology Data Exchange (ETDEWEB)

    Lin, Youzuo [Los Alamos National Laboratory; Huang, Lianjie [Los Alamos National Laboratory; Zhang, Zhigang [Los Alamos National Laboratory

    2011-01-01

    Double-difference waveform inversion is a potential tool for quantitative monitoring for geologic carbon storage. It jointly inverts time-lapse seismic data for changes in reservoir geophysical properties. Due to the ill-posedness of waveform inversion, it is a great challenge to obtain reservoir changes accurately and efficiently, particularly when using time-lapse seismic reflection data. Regularization techniques can be utilized to address the issue of ill-posedness. The regularization parameter controls the smoothness of inversion results. A constant regularization parameter is normally used in waveform inversion, and an optimal regularization parameter has to be selected. The resulting inversion results are a trade off among regions with different smoothness or noise levels; therefore the images are either over regularized in some regions while under regularized in the others. In this paper, we employ a spatially-variant parameter in the Tikhonov regularization scheme used in double-difference waveform tomography to improve the inversion accuracy and robustness. We compare the results obtained using a spatially-variant parameter with those obtained using a constant regularization parameter and those produced without any regularization. We observe that, utilizing a spatially-variant regularization scheme, the target regions are well reconstructed while the noise is reduced in the other regions. We show that the spatially-variant regularization scheme provides the flexibility to regularize local regions based on the a priori information without increasing computational costs and the computer memory requirement.

  13. Formation of regular spatial patterns in ratio-dependent predator-prey model driven by spatial colored-noise

    OpenAIRE

    Liu, Quan-Xing; Jin, Zhen

    2006-01-01

    Results are reported concerning the formation of spatial patterns in the two-species ratio-dependent predator-prey model driven by spatial colored-noise. The results show that there is a critical value with respect to the intensity of spatial noise for this system when the parameters are in the Turing space, above which the regular spatial patterns appear in two dimensions, but under which there are not regular spatial patterns produced. In particular, we investigate in two-dimensional space ...

  14. Models with hidden regular variation: Generation and detection

    Directory of Open Access Journals (Sweden)

    Bikramjit Das

    2015-12-01

    Full Text Available We review the notions of multivariate regular variation (MRV and hidden regular variation (HRV for distributions of random vectors and then discuss methods for generating models exhibiting both properties concentrating on the non-negative orthant in dimension two. Furthermore we suggest diagnostic techniques that detect these properties in multivariate data and indicate when models exhibiting both MRV and HRV are plausible fits for the data. We illustrate our techniques on simulated data, as well as two real Internet data sets.

  15. First contact distributions for spatial patterns: regularity and estimation

    NARCIS (Netherlands)

    Hansen, M.B.; Baddeley, A.J.; Gill, R.D.

    2001-01-01

    For applications in spatial statistics an important property of a random set X in Rk is its rst contact distribution This is the distribution of the distance from a xed point to the nearest point of X where distance is measured using scalar dilations of a xed test set B We show that if B is convex

  16. Detecting spatial regimes in ecosystems

    Science.gov (United States)

    Sundstrom, Shana M.; Eason, Tarsha; Nelson, R. John; Angeler, David G.; Barichievy, Chris; Garmestani, Ahjond S.; Graham, Nicholas A.J.; Granholm, Dean; Gunderson, Lance; Knutson, Melinda; Nash, Kirsty L.; Spanbauer, Trisha; Stow, Craig A.; Allen, Craig R.

    2017-01-01

    Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory-based method, on both terrestrial and aquatic animal data (U.S. Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps and multivariate analyses such as nMDS and cluster analysis. We successfully detected spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change.

  17. The growth regularity and detective technique of collapse column

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Z. [Xingtai Coal Mining Bureau (China)

    1997-12-01

    The paper summarizes the growth regularity and the related factors of collapse column in Duongpang Coal Mine, introduces the applicability of roadway explorations, drillings and geophysical prospecting methods, expounds how to select an economic and quick exploration method according to the characteristics of each method and difference geological conditions for detecting the place, shape, size and water-bearing property of collapse column. 4 figs.

  18. Spatially varying Riemannian elasticity regularization: Application to thoracic CT registration in image-guided radiotherapy

    DEFF Research Database (Denmark)

    Bjerre, Troels; Hansen, Mads Fogtmann; Aznar, M.;

    2012-01-01

    For deformable registration of computed tomography (CT) scans in image guided radiation therapy (IGRT) we apply Riemannian elasticity regularization. We explore the use of spatially varying elasticity parameters to encourage bone rigidity and local tissue volume change only in the gross tumor......-model we achieved a total mean target registration error (TRE) of 0.92 ± 0.49 mm. Using spatially varying regularization for the HL case, deformation was limited to the GTV and lungs....

  19. Spherical Deconvolution of Multichannel Diffusion MRI Data with Non-Gaussian Noise Models and Spatial Regularization.

    Directory of Open Access Journals (Sweden)

    Erick J Canales-Rodríguez

    Full Text Available Spherical deconvolution (SD methods are widely used to estimate the intra-voxel white-matter fiber orientations from diffusion MRI data. However, while some of these methods assume a zero-mean Gaussian distribution for the underlying noise, its real distribution is known to be non-Gaussian and to depend on many factors such as the number of coils and the methodology used to combine multichannel MRI signals. Indeed, the two prevailing methods for multichannel signal combination lead to noise patterns better described by Rician and noncentral Chi distributions. Here we develop a Robust and Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD technique, intended to deal with realistic MRI noise, based on a Richardson-Lucy (RL algorithm adapted to Rician and noncentral Chi likelihood models. To quantify the benefits of using proper noise models, RUMBA-SD was compared with dRL-SD, a well-established method based on the RL algorithm for Gaussian noise. Another aim of the study was to quantify the impact of including a total variation (TV spatial regularization term in the estimation framework. To do this, we developed TV spatially-regularized versions of both RUMBA-SD and dRL-SD algorithms. The evaluation was performed by comparing various quality metrics on 132 three-dimensional synthetic phantoms involving different inter-fiber angles and volume fractions, which were contaminated with noise mimicking patterns generated by data processing in multichannel scanners. The results demonstrate that the inclusion of proper likelihood models leads to an increased ability to resolve fiber crossings with smaller inter-fiber angles and to better detect non-dominant fibers. The inclusion of TV regularization dramatically improved the resolution power of both techniques. The above findings were also verified in human brain data.

  20. Spherical Deconvolution of Multichannel Diffusion MRI Data with Non-Gaussian Noise Models and Spatial Regularization.

    Science.gov (United States)

    Canales-Rodríguez, Erick J; Daducci, Alessandro; Sotiropoulos, Stamatios N; Caruyer, Emmanuel; Aja-Fernández, Santiago; Radua, Joaquim; Yurramendi Mendizabal, Jesús M; Iturria-Medina, Yasser; Melie-García, Lester; Alemán-Gómez, Yasser; Thiran, Jean-Philippe; Sarró, Salvador; Pomarol-Clotet, Edith; Salvador, Raymond

    2015-01-01

    Spherical deconvolution (SD) methods are widely used to estimate the intra-voxel white-matter fiber orientations from diffusion MRI data. However, while some of these methods assume a zero-mean Gaussian distribution for the underlying noise, its real distribution is known to be non-Gaussian and to depend on many factors such as the number of coils and the methodology used to combine multichannel MRI signals. Indeed, the two prevailing methods for multichannel signal combination lead to noise patterns better described by Rician and noncentral Chi distributions. Here we develop a Robust and Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD) technique, intended to deal with realistic MRI noise, based on a Richardson-Lucy (RL) algorithm adapted to Rician and noncentral Chi likelihood models. To quantify the benefits of using proper noise models, RUMBA-SD was compared with dRL-SD, a well-established method based on the RL algorithm for Gaussian noise. Another aim of the study was to quantify the impact of including a total variation (TV) spatial regularization term in the estimation framework. To do this, we developed TV spatially-regularized versions of both RUMBA-SD and dRL-SD algorithms. The evaluation was performed by comparing various quality metrics on 132 three-dimensional synthetic phantoms involving different inter-fiber angles and volume fractions, which were contaminated with noise mimicking patterns generated by data processing in multichannel scanners. The results demonstrate that the inclusion of proper likelihood models leads to an increased ability to resolve fiber crossings with smaller inter-fiber angles and to better detect non-dominant fibers. The inclusion of TV regularization dramatically improved the resolution power of both techniques. The above findings were also verified in human brain data.

  1. Spatially varying regularization based on retrieved support in diffuse optical tomography

    Science.gov (United States)

    Sabir, Sohail; Cho, Sanghoon; Cho, Seunryong

    2017-03-01

    Diffuse optical tomography (DOT) is a promising noninvasive imaging modality capable of providing the functional characteristics (oxygen saturation and hemodynamic states) of thick biological tissue by quantifying the optical parameters. The parameter recovery problem in DOT is a nonlinear, ill-posed and ill conditioned inverse problem. The non-linear iterative methods are usually employed for image reconstruction in DOT by utilizing Tikhonov based regularization approach. These methods employ l2-norm based regularization where the constant regularization parameter is determined either empirically or generalized cross validation methods or L curve method. The reconstructed images look smoother or noisy depending on the chosen value of the regularization constant. Moreover the edges information of the inclusions appeared to be blurred in such constant regularization methods. In this study we proposed a method to retrieve and utilized a non-zero support (possible tumor location) to generate a spatially varying regularization map. The inclusions locations were determined by considering the imaging problem as a multiple measurements vector (MMV) problem. Based on the recovered inclusion positions spatially regularization map was generated to be used in non-linear image reconstruction framework. The results retrieved with such spatially varying priors shows slightly improved image reconstruction in terms of better contrast recovery, reduction in background noise and preservation of edge information of inclusions compared with the constant regularization approach.

  2. MEG Connectivity and Power Detections with Minimum Norm Estimates Require Different Regularization Parameters.

    Science.gov (United States)

    Hincapié, Ana-Sofía; Kujala, Jan; Mattout, Jérémie; Daligault, Sebastien; Delpuech, Claude; Mery, Domingo; Cosmelli, Diego; Jerbi, Karim

    2016-01-01

    Minimum Norm Estimation (MNE) is an inverse solution method widely used to reconstruct the source time series that underlie magnetoencephalography (MEG) data. MNE addresses the ill-posed nature of MEG source estimation through regularization (e.g., Tikhonov regularization). Selecting the best regularization parameter is a critical step. Generally, once set, it is common practice to keep the same coefficient throughout a study. However, it is yet to be known whether the optimal lambda for spectral power analysis of MEG source data coincides with the optimal regularization for source-level oscillatory coupling analysis. We addressed this question via extensive Monte-Carlo simulations of MEG data, where we generated 21,600 configurations of pairs of coupled sources with varying sizes, signal-to-noise ratio (SNR), and coupling strengths. Then, we searched for the Tikhonov regularization coefficients (lambda) that maximize detection performance for (a) power and (b) coherence. For coherence, the optimal lambda was two orders of magnitude smaller than the best lambda for power. Moreover, we found that the spatial extent of the interacting sources and SNR, but not the extent of coupling, were the main parameters affecting the best choice for lambda. Our findings suggest using less regularization when measuring oscillatory coupling compared to power estimation.

  3. The regularized monotonicity method: detecting irregular indefinite inclusions

    DEFF Research Database (Denmark)

    Garde, Henrik; Staboulis, Stratos

    2017-01-01

    In inclusion detection in electrical impedance tomography, the support of perturbations (inclusion) from a known background conductivity is typically reconstructed from idealized continuum data modelled by a Neumann-to-Dirichlet map. Only few reconstruction methods apply when detecting indefinite...... of approximative measurement models, including the Complete Electrode Model, hence making the method robust against modelling error and noise. In particular, we demonstrate that for a convergent family of approximative models there exists a sequence of regularization parameters such that the outer shape...... of the inclusions is asymptotically exactly characterized. Finally, a peeling-type reconstruction algorithm is presented and, for the first time in literature, numerical examples of monotonicity reconstructions for indefinite inclusions are presented....

  4. Functional dissociation between regularity encoding and deviance detection along the auditory hierarchy.

    Science.gov (United States)

    Aghamolaei, Maryam; Zarnowiec, Katarzyna; Grimm, Sabine; Escera, Carles

    2016-02-01

    Auditory deviance detection based on regularity encoding appears as one of the basic functional properties of the auditory system. It has traditionally been assessed with the mismatch negativity (MMN) long-latency component of the auditory evoked potential (AEP). Recent studies have found earlier correlates of deviance detection based on regularity encoding. They occur in humans in the first 50 ms after sound onset, at the level of the middle-latency response of the AEP, and parallel findings of stimulus-specific adaptation observed in animal studies. However, the functional relationship between these different levels of regularity encoding and deviance detection along the auditory hierarchy has not yet been clarified. Here we addressed this issue by examining deviant-related responses at different levels of the auditory hierarchy to stimulus changes varying in their degree of deviation regarding the spatial location of a repeated standard stimulus. Auditory stimuli were presented randomly from five loudspeakers at azimuthal angles of 0°, 12°, 24°, 36° and 48° during oddball and reversed-oddball conditions. Middle-latency responses and MMN were measured. Our results revealed that middle-latency responses were sensitive to deviance but not the degree of deviation, whereas the MMN amplitude increased as a function of deviance magnitude. These findings indicated that acoustic regularity can be encoded at the level of the middle-latency response but that it takes a higher step in the auditory hierarchy for deviance magnitude to be encoded, thus providing a functional dissociation between regularity encoding and deviance detection along the auditory hierarchy. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  5. Hyperspectral imagery super-resolution by compressive sensing inspired dictionary learning and spatial-spectral regularization.

    Science.gov (United States)

    Huang, Wei; Xiao, Liang; Liu, Hongyi; Wei, Zhihui

    2015-01-19

    Due to the instrumental and imaging optics limitations, it is difficult to acquire high spatial resolution hyperspectral imagery (HSI). Super-resolution (SR) imagery aims at inferring high quality images of a given scene from degraded versions of the same scene. This paper proposes a novel hyperspectral imagery super-resolution (HSI-SR) method via dictionary learning and spatial-spectral regularization. The main contributions of this paper are twofold. First, inspired by the compressive sensing (CS) framework, for learning the high resolution dictionary, we encourage stronger sparsity on image patches and promote smaller coherence between the learned dictionary and sensing matrix. Thus, a sparsity and incoherence restricted dictionary learning method is proposed to achieve higher efficiency sparse representation. Second, a variational regularization model combing a spatial sparsity regularization term and a new local spectral similarity preserving term is proposed to integrate the spectral and spatial-contextual information of the HSI. Experimental results show that the proposed method can effectively recover spatial information and better preserve spectral information. The high spatial resolution HSI reconstructed by the proposed method outperforms reconstructed results by other well-known methods in terms of both objective measurements and visual evaluation.

  6. On the Lipschitz Regularity in Signal Singularity Detection

    Institute of Scientific and Technical Information of China (English)

    LUO Li-chun

    2003-01-01

    The concepts of Lipschitz regularity and Hlder one are reviewed. They are not equivalent except for α<1. A modification for Definition 1 on Lipschitz regularity in Ref.[1], which is not rigorous, is offered. Two propositions on Hlder regularity are given and proven.

  7. Accurate mask-based spatially regularized correlation filter for visual tracking

    Science.gov (United States)

    Gu, Xiaodong; Xu, Xinping

    2017-01-01

    Recently, discriminative correlation filter (DCF)-based trackers have achieved extremely successful results in many competitions and benchmarks. These methods utilize a periodic assumption of the training samples to efficiently learn a classifier. However, this assumption will produce unwanted boundary effects, which severely degrade the tracking performance. Correlation filters with limited boundaries and spatially regularized DCFs were proposed to reduce boundary effects. However, their methods used the fixed mask or predesigned weights function, respectively, which was unsuitable for large appearance variation. We propose an accurate mask-based spatially regularized correlation filter for visual tracking. Our augmented objective can reduce the boundary effect even in large appearance variation. In our algorithm, the masking matrix is converted into the regularized function that acts on the correlation filter in frequency domain, which makes the algorithm fast convergence. Our online tracking algorithm performs favorably against state-of-the-art trackers on OTB-2015 Benchmark in terms of efficiency, accuracy, and robustness.

  8. The ultra-rate spatial enhancement using Huber regularization MSRR and Huber high-spectrum expectation

    Science.gov (United States)

    Patanavijit, Vorapoj

    2017-02-01

    The high spatial resolution images are ultimately demanded due to the requirement of the advance digital signal processing (DSP) and digital image processing (DIP) in modern implementations thereby the image spatial enhancements, especially for an ultra-rate spatial enhanced rate, have been ultimately investigated in the DSP and DIP society in the last twenty five years. The ultra-rate spatial enhancement employed by MSRR with Huber ML (Maximum Likelihood) regularization technique and SSRR with Huber high-spectrum expectation is proposed for enhancing upto 16x spatial rate in this paper. Initially, the collection of low spatial resolution images with noise is processed by MSRR for attenuating the noise and enhancing the spatial resolution. Later, the enhanced image is processed by SSRR for calculating the high-spectrum information in order to reconstruct the extortionate spatial enhancement with 16x spatial enhanced rate. In the performance evaluation section, the simulated consequences of the proposed ultra-rate spatial enhancement are compared with other previous state-of-art (such as a bicubic interpolation technique, a classical MSRR and a classical SSRR) in both PSNR (Peak Signal to Noise Ratio) and virtual quality attitude. From the performance evaluation consequence of four noise types at many noise powers, the proposed ultra-rate spatial enhancement has a superior performance than other previous state-of-art.

  9. Moving object detection via low-rank total variation regularization

    Science.gov (United States)

    Wang, Pengcheng; Chen, Qian; Shao, Na

    2016-09-01

    Moving object detection is a challenging task in video surveillance. Recently proposed Robust Principal Component Analysis (RPCA) can recover the outlier patterns from the low-rank data under some mild conditions. However, the l-penalty in RPCA doesn't work well in moving object detection because the irrepresentable condition is often not satisfied. In this paper, a method based on total variation (TV) regularization scheme is proposed. In our model, image sequences captured with a static camera are highly related, which can be described using a low-rank matrix. Meanwhile, the low-rank matrix can absorb background motion, e.g. periodic and random perturbation. The foreground objects in the sequence are usually sparsely distributed and drifting continuously, and can be treated as group outliers from the highly-related background scenes. Instead of l-penalty, we exploit the total variation of the foreground. By minimizing the total variation energy, the outliers tend to collapse and finally converge to be the exact moving objects. The TV-penalty is superior to the l-penalty especially when the outlier is in the majority for some pixels, and our method can estimate the outlier explicitly with less bias but higher variance. To solve the problem, a joint optimization function is formulated and can be effectively solved through the inexact Augmented Lagrange Multiplier (ALM) method. We evaluate our method along with several state-of-the-art approaches in MATLAB. Both qualitative and quantitative results demonstrate that our proposed method works effectively on a large range of complex scenarios.

  10. From Matched Spatial Filtering towards the Fused Statistical Descriptive Regularization Method for Enhanced Radar Imaging

    Directory of Open Access Journals (Sweden)

    Shkvarko Yuriy

    2006-01-01

    Full Text Available We address a new approach to solve the ill-posed nonlinear inverse problem of high-resolution numerical reconstruction of the spatial spectrum pattern (SSP of the backscattered wavefield sources distributed over the remotely sensed scene. An array or synthesized array radar (SAR that employs digital data signal processing is considered. By exploiting the idea of combining the statistical minimum risk estimation paradigm with numerical descriptive regularization techniques, we address a new fused statistical descriptive regularization (SDR strategy for enhanced radar imaging. Pursuing such an approach, we establish a family of the SDR-related SSP estimators, that encompass a manifold of existing beamforming techniques ranging from traditional matched filter to robust and adaptive spatial filtering, and minimum variance methods.

  11. Correction of multi-spectral MRI intensity non-uniformity via spatially regularized feature condensing

    Science.gov (United States)

    Vovk, Uros; Pernus, Franjo; Likar, Bostjan

    2003-05-01

    In MRI, image intensity non-uniformity is an adverse phenomenon that increases inter-tissue overlapping. The aim of this study was to provide a novel general framework, named regularized feature condensing (RFC), for condensing the distribution of image features and apply it to correct intensity non-uniformity via spatial regularization. The proposed RCF method is an iterative procedure, which consists of four basic steps. First, creation of a feature space, which consists of multi-spectral image intensities and corresponding second derivatives. Second, estimation of the intensity condensing map in feature space, i.e. the estimation of the increase of feature probability densities by a well-established mean shift procedure. Third, regularization of intensity condensing map in image space, which yields the estimation of intensity non-uniformity. Fourth, applying the estimation of non-uniformity correction to the input image. In this way, the intensity distributions of distinct tissues are gradually condensed via spatial regularization. The method was tested on simulated and real MR brain images for which gold standard segmentations were available. The results showed that the method did not induce additional intensity variations in simulated uniform images and efficiently removed intensity non-uniformity in real MR brain images. The proposed RCF method is a powerful fully automated intensity non-uniformity correction method that makes no a prior assumptions on the image intensity distribution and provides non-parametric non-uniformity correction.

  12. Detection of Spatial Changes using Spatial Data Mining

    CERN Document Server

    Kodge, B G

    2011-01-01

    This paper uses the techniques of spatial data mining (SDM) and change detection (CD) in the field of geospatial information processing. Assuming the feasibility of discovering knowledge from spatial database and the demands of knowledge for change detection, the paper presents that change detection needs knowledge and technology of SDM should be integrated into applications of change detection. Special knowledge for change detection of linear feature, area feature and terrain are studied. Relationship between accuracy of change detection and errors of image registration is discussed. Change detection of linear feature, area feature and terrain based on SDM are investigated respectively. Change detection based on multivariate statistical analysis and training samples are analyzed. Land use/cover change detection based on SDM is discussed.

  13. Learning optimal spatially-dependent regularization parameters in total variation image denoising

    Science.gov (United States)

    Van Chung, Cao; De los Reyes, J. C.; Schönlieb, C. B.

    2017-07-01

    We consider a bilevel optimization approach in function space for the choice of spatially dependent regularization parameters in TV image denoising models. First- and second-order optimality conditions for the bilevel problem are studied when the spatially-dependent parameter belongs to the Sobolev space {{H}1}≤ft(Ω \\right) . A combined Schwarz domain decomposition-semismooth Newton method is proposed for the solution of the full optimality system and local superlinear convergence of the semismooth Newton method is verified. Exhaustive numerical computations are finally carried out to show the suitability of the approach.

  14. Topological chaos of the spatial prisoner's dilemma game on regular networks.

    Science.gov (United States)

    Jin, Weifeng; Chen, Fangyue

    2016-02-21

    The spatial version of evolutionary prisoner's dilemma on infinitely large regular lattice with purely deterministic strategies and no memories among players is investigated in this paper. Based on the statistical inferences, it is pertinent to confirm that the frequency of cooperation for characterizing its macroscopic behaviors is very sensitive to the initial conditions, which is the most practically significant property of chaos. Its intrinsic complexity is then justified on firm ground from the theory of symbolic dynamics; that is, this game is topologically mixing and possesses positive topological entropy on its subsystems. It is demonstrated therefore that its frequency of cooperation could not be adopted by simply averaging over several steps after the game reaches the equilibrium state. Furthermore, the chaotically changing spatial patterns via empirical observations can be defined and justified in view of symbolic dynamics. It is worth mentioning that the procedure proposed in this work is also applicable to other deterministic spatial evolutionary games therein.

  15. EEG/MEG Source Reconstruction with Spatial-Temporal Two-Way Regularized Regression

    KAUST Repository

    Tian, Tian Siva

    2013-07-11

    In this work, we propose a spatial-temporal two-way regularized regression method for reconstructing neural source signals from EEG/MEG time course measurements. The proposed method estimates the dipole locations and amplitudes simultaneously through minimizing a single penalized least squares criterion. The novelty of our methodology is the simultaneous consideration of three desirable properties of the reconstructed source signals, that is, spatial focality, spatial smoothness, and temporal smoothness. The desirable properties are achieved by using three separate penalty functions in the penalized regression framework. Specifically, we impose a roughness penalty in the temporal domain for temporal smoothness, and a sparsity-inducing penalty and a graph Laplacian penalty in the spatial domain for spatial focality and smoothness. We develop a computational efficient multilevel block coordinate descent algorithm to implement the method. Using a simulation study with several settings of different spatial complexity and two real MEG examples, we show that the proposed method outperforms existing methods that use only a subset of the three penalty functions. © 2013 Springer Science+Business Media New York.

  16. Quantitative Monitoring for Enhanced Geothermal Systems Using Double-Difference Waveform Inversion with Spatially-Variant Total-Variation Regularization

    Energy Technology Data Exchange (ETDEWEB)

    Lin, Youzuo [Los Alamos National Laboratory; Huang, Lianjie [Los Alamos National Laboratory; Zhang, Zhigang [Los Alamos National Laboratory

    2011-01-01

    Double-difference waveform inversion is a promising tool for quantitative monitoring for enhanced geothermal systems (EGS). The method uses time-lapse seismic data to jointly inverts for reservoir changes. Due to the ill-posedness of waveform inversion, it is a great challenge to obtain reservoir changes accurately and efficiently, particularly when using timelapse seismic reflection data. To improve reconstruction, we develop a spatially-variant total-variation regularization scheme into double-difference waveform inversion to improve the inversion accuracy and robustness. The new regularization scheme employs different regularization parameters in different regions of the model to obtain an optimal regularization in each area. We compare the results obtained using a spatially-variant parameter with those obtained using a constant regularization parameter. Utilizing a spatially-variant regularization scheme, the target monitoring regions are well reconstructed and the image noise is significantly reduced outside the monitoring regions. Our numerical examples demonstrate that the spatially-variant total-variation regularization scheme provides the flexibility to regularize local regions based on the a priori spatial information without increasing computational costs and the computer memory requirement.

  17. Analysis of Regularly and Irregularly Sampled Spatial, Multivariate, and Multi-temporal Data

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    1994-01-01

    analysis techniques in this context. Geostatistics is described in Chapter 1. Tools as the semivariogram, the cross-semivariogram and different types of kriging are described. As an independent re-invention 2-D sample semivariograms, cross-semivariograms and cova functions, and modelling of 2-D sample semi...... maximize the variance represented by each component, MAFs maximize the spatial autocorrelation represented by each component, and MNFs maximize a measure of signal-to-noise ratio represented by each component. In the literature MAF/MNF analysis is described for regularly gridded data only. Here...

  18. EXTENDING LKN CLIMATE REGIONALIZATION WITH SPATIAL REGULARIZATION: AN APPLICATION TO EPIDEMIOLOGICAL RESEARCH

    Directory of Open Access Journals (Sweden)

    A. Liss

    2016-06-01

    Full Text Available Regional climate is a critical factor in public health research, adaptation studies, climate change burden analysis, and decision support frameworks. Existing climate regionalization schemes are not well suited for these tasks as they rarely take population density into account. In this work, we are extending our recently developed method for automated climate regionalization (LKN-method to incorporate the spatial features of target population. The LKN method consists of the data limiting step (L-step to reduce dimensionality by applying principal component analysis, a classification step (K-step to produce hierarchical candidate regions using k-means unsupervised classification algorithm, and a nomination step (N-step to determine the number of candidate climate regions using cluster validity indexes. LKN method uses a comprehensive set of multiple satellite data streams, arranged as time series, and allows us to define homogeneous climate regions. The proposed approach extends the LKN method to include regularization terms reflecting the spatial distribution of target population. Such tailoring allows us to determine the optimal number and spatial distribution of climate regions and thus, to ensure more uniform population coverage across selected climate categories. We demonstrate how the extended LKN method produces climate regionalization can be better tailored to epidemiological research in the context of decision support framework.

  19. Extending Lkn Climate Regionalization with Spatial Regularization: AN Application to Epidemiological Research

    Science.gov (United States)

    Liss, Alexander; Gel, Yulia R.; Kulinkina, Alexandra; Naumova, Elena N.

    2016-06-01

    Regional climate is a critical factor in public health research, adaptation studies, climate change burden analysis, and decision support frameworks. Existing climate regionalization schemes are not well suited for these tasks as they rarely take population density into account. In this work, we are extending our recently developed method for automated climate regionalization (LKN-method) to incorporate the spatial features of target population. The LKN method consists of the data limiting step (L-step) to reduce dimensionality by applying principal component analysis, a classification step (K-step) to produce hierarchical candidate regions using k-means unsupervised classification algorithm, and a nomination step (N-step) to determine the number of candidate climate regions using cluster validity indexes. LKN method uses a comprehensive set of multiple satellite data streams, arranged as time series, and allows us to define homogeneous climate regions. The proposed approach extends the LKN method to include regularization terms reflecting the spatial distribution of target population. Such tailoring allows us to determine the optimal number and spatial distribution of climate regions and thus, to ensure more uniform population coverage across selected climate categories. We demonstrate how the extended LKN method produces climate regionalization can be better tailored to epidemiological research in the context of decision support framework.

  20. Anomaly detection in homogenous populations: A sparse multiple kernel-based regularization method

    DEFF Research Database (Denmark)

    Chen, Tianshi; Andersen, Martin S.; Chiuso, Alessandro;

    2014-01-01

    A problem of anomaly detection in homogenous populations consisting of linear stable systems is studied. The recently introduced sparse multiple kernel based regularization method is applied to solve the problem. A common problem with the existing regularization methods is that there lacks...... an efficient and systematic way to tune the involved regularization parameters. In contrast, the hyper-parameters (some of them can be interpreted as regularization parameters) involved in the proposed method are tuned in an automatic way, and in fact estimated by using the empirical Bayes method. What's more...

  1. Detecting regularities in soccer dynamics: A T-pattern approach

    Directory of Open Access Journals (Sweden)

    Valentino Zurloni

    2014-01-01

    Full Text Available La dinámica del juego en partidos de fútbol profesional es un fenómeno complejo que no ha estado resuelto de forma óptima a través delas vías tradicionales que han pretendido la cuantificación en deportes de equipo. El objetivo de este estudio es el de detectar la dinámica existente mediante un análisis de patrones temporales. Específicamente, se pretenden revelar las estructuras ocultas pero estables que subyacen a las situaciones interactivas que determinan las acciones de ataque en el fútbol. El planteamiento metodológico se basa en un diseño observacional, y con apoyo de registros digitales y análisis informatizados. Los datos se analizaron mediante el programa Theme 6 beta, el cual permite detectar la estructura temporaly secuencial de las series de datos, poniendo de manifiesto patrones que regular o irregularmente ocurren repetidamente en un período de observación. El Theme ha detectado muchos patrones temporales (T-patterns en los partidos de fútbol analizados. Se hallaron notables diferencias entre los partidos ganados y perdidos. El número de distintos T-patterns detectados fue mayor para los partidos perdidos, y menor para los ganados, mientras que el número de eventos codificados fue similar. El programa Theme y los T-patterns mejoran las posibilidades investigadoras respecto a un análisis de rendimiento basado en la frecuencia, y hacen que esta metodología sea eficaz para la investigación y constituya un apoyo procedimental en el análisis del deporte. Nuestros resultados indican que se requieren posteriores investigaciones relativas a posibles conexiones entre la detección de estas estructuras temporales y las observaciones humanas respecto al rendimiento en el fútbol. Este planteamiento sería un apoyo tanto para los miembros de los equipos como para los entrenadores, permitiendo alcanzar una mejor comprensión de la dinámica del juego y aportando una información que no ofrecen los métodos tradicionales.

  2. [Regularities of the egocentric spatial memory development in children aged 24-60 months].

    Science.gov (United States)

    Dashniani, M G; Chkhikivishvili, N Ts; Naneĭshvili, T L; Burdzhanadze, M A; Maglakelidze, G A

    2009-09-01

    In order to assess development of the egocentric system of the spatial short-term memory in children (n=66) of different ages (24-60 months) the Inverted Delayed Reaction test has been used. It was found that in the children aged 24-36 months regularities of performance of the Inverted Delayed Reaction test significantly differ in conditions of different loads onto the mechanisms of dead reckoning; the children aged 36-60 months do not show sensitivity to different loads. In children aged 42+/-4 months functional elimination of any of the sensory system (visual, kinesthetic, vestibular) during rotation significantly deteriorated results of the Inverted Delayed Reaction test performance, while in children aged 60+/-4 months number of correct responses decreased if two or three sensory systems were eliminated simultaneously. The data obtained permit to conclude that the Inverted Delayed Reaction test is sufficiently sensitive for evaluation development of the egocentric spatial memory system in children and that formation of the dead reckoning mechanisms starts in an age of 24 months and in the period of 24-60 months its further upgrading does occur.

  3. Detecting spatial regimes in ecosystems | Science Inventory ...

    Science.gov (United States)

    Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory based method, on both terrestrial and aquatic animal data (US Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps, and multivariate analysis such as nMDS (non-metric Multidimensional Scaling) and cluster analysis. We successfully detect spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change. Use an information theory based method to identify ecological boundaries and compare our results to traditional early warning

  4. Spatial cluster detection using dynamic programming

    Directory of Open Access Journals (Sweden)

    Sverchkov Yuriy

    2012-03-01

    Full Text Available Abstract Background The task of spatial cluster detection involves finding spatial regions where some property deviates from the norm or the expected value. In a probabilistic setting this task can be expressed as finding a region where some event is significantly more likely than usual. Spatial cluster detection is of interest in fields such as biosurveillance, mining of astronomical data, military surveillance, and analysis of fMRI images. In almost all such applications we are interested both in the question of whether a cluster exists in the data, and if it exists, we are interested in finding the most accurate characterization of the cluster. Methods We present a general dynamic programming algorithm for grid-based spatial cluster detection. The algorithm can be used for both Bayesian maximum a-posteriori (MAP estimation of the most likely spatial distribution of clusters and Bayesian model averaging over a large space of spatial cluster distributions to compute the posterior probability of an unusual spatial clustering. The algorithm is explained and evaluated in the context of a biosurveillance application, specifically the detection and identification of Influenza outbreaks based on emergency department visits. A relatively simple underlying model is constructed for the purpose of evaluating the algorithm, and the algorithm is evaluated using the model and semi-synthetic test data. Results When compared to baseline methods, tests indicate that the new algorithm can improve MAP estimates under certain conditions: the greedy algorithm we compared our method to was found to be more sensitive to smaller outbreaks, while as the size of the outbreaks increases, in terms of area affected and proportion of individuals affected, our method overtakes the greedy algorithm in spatial precision and recall. The new algorithm performs on-par with baseline methods in the task of Bayesian model averaging. Conclusions We conclude that the dynamic

  5. Oil Spill Detection and Tracking Using Lipschitz Regularity and Multiscale Techniques in Synthetic Aperture Radar Imagery

    Science.gov (United States)

    Ajadi, O. A.; Meyer, F. J.

    2014-12-01

    Automatic oil spill detection and tracking from Synthetic Aperture Radar (SAR) images is a difficult task, due in large part to the inhomogeneous properties of the sea surface, the high level of speckle inherent in SAR data, the complexity and the highly non-Gaussian nature of amplitude information, and the low temporal sampling that is often achieved with SAR systems. This research presents a promising new oil spill detection and tracking method that is based on time series of SAR images. Through the combination of a number of advanced image processing techniques, the develop approach is able to mitigate some of these previously mentioned limitations of SAR-based oil-spill detection and enables fully automatic spill detection and tracking across a wide range of spatial scales. The method combines an initial automatic texture analysis with a consecutive change detection approach based on multi-scale image decomposition. The first step of the approach, a texture transformation of the original SAR images, is performed in order to normalize the ocean background and enhance the contrast between oil-covered and oil-free ocean surfaces. The Lipschitz regularity (LR), a local texture parameter, is used here due to its proven ability to normalize the reflectivity properties of ocean water and maximize the visibly of oil in water. To calculate LR, the images are decomposed using two-dimensional continuous wavelet transform (2D-CWT), and transformed into Holder space to measure LR. After texture transformation, the now normalized images are inserted into our multi-temporal change detection algorithm. The multi-temporal change detection approach is a two-step procedure including (1) data enhancement and filtering and (2) multi-scale automatic change detection. The performance of the developed approach is demonstrated by an application to oil spill areas in the Gulf of Mexico. In this example, areas affected by oil spills were identified from a series of ALOS PALSAR images

  6. SPATIAL MODELING OF SOLID-STATE REGULAR POLYHEDRA (SOLIDS OF PLATON IN AUTOCAD SYSTEM

    Directory of Open Access Journals (Sweden)

    P. V. Bezditko

    2009-03-01

    Full Text Available This article describes the technology of modeling regular polyhedra by graphic methods. The authors came to the conclusion that in order to create solid models of regular polyhedra the method of extrusion is best to use.

  7. An Improved Fitness Evaluation Mechanism with Memory in Spatial Prisoner's Dilemma Game on Regular Lattices

    Institute of Scientific and Technical Information of China (English)

    WANG Juan; LIU Li-Na; DONG En-Zeng; WANG Li

    2013-01-01

    To deeply understand the emergence of cooperation in natural,social and economical systems,we present an improved fitness evaluation mechanism with memory in spatial prisoner's dilemma game on regular lattices.In our model,the individual fitness is not only determined by the payoff in the current game round,but also by the payoffs in previous round bins.A tunable parameter,termed as the memory strength (μ),which lies between 0 and 1,is introduced into the model to regulate the ratio of payoffs of current and previous game rounds in the individual fitness calculation.When μ =0,our model is reduced to the standard prisoner's dilemma game; while μ =1 represents the case in which the payoff is totally determined by the initial strategies and thus it is far from the realistic ones.Extensive numerical simulations indicate that the memory effect can substantially promote the evolution of cooperation.For μ < 1,the stronger the memory effect,the higher the cooperation level,but μ = 1 leads to a pathological state of cooperation,but can partially enhance the cooperation in the very large temptation parameter.The current results are of great significance for us to account for the role of memory effect during the evolution of cooperation among selfish players.

  8. Hemagglutinin outer contour detection methods based on regular hexagon bar template

    Science.gov (United States)

    Tian, Miaomiao; Jing, Wenbo; Duan, Jin; Wang, Xiaoman

    2014-11-01

    In order to extract hemagglutinin outer contour accurately in the hemagglutinin image, analyzes the hemagglutinin protein content by the size of detected contour, presents a regular hexagon bar circle detection algorithm which uses regular hexagon bar detection template to detect outer contour of the hemagglutinin. Firstly, the hemagglutinin image thresholded by using OTSU adaptive thresholding method; and then using regular hexagon bar detection template method to rough align hemagglutinin after thresholded, intersection of detection template and the hemagglutinin contour area is attained, the noise near hemagglutinin contour is reduced by using the standardization relationship of the hexagon bars, so the hemagglutinin pixels are accurately obtained; finally the hemagglutinin outer contour information is gained by the geometric relationship of pixels, the hemagglutinin position is achieved precisely. The experimental results show that: the contour detection error due to the density uneven and the edge unclearly of hemagglutinin image protein is better reduced, the detection accuracy is increased by a factor of 0.47, detection speed is increased by a factor of 0.56.The hemagglutinin contour can be dected stablely, fastly, accurately and the is significant to the study of the hemagglutinin protein content.

  9. Robust Spectral Detection of Global Structures in the Data by Learning a Regularization

    CERN Document Server

    Zhang, Pan

    2016-01-01

    Spectral methods are popular in detecting global structures in the given data that can be represented as a matrix. However when the data matrix is sparse or noisy, classic spectral methods usually fail to work, due to localization of eigenvectors (or singular vectors) induced by the sparsity or noise. In this work, we propose a general method to solve the localization problem by learning a regularization matrix from the localized eigenvectors. Using matrix perturbation analysis, we demonstrate that the learned regularizations suppress down the eigenvalues associated with localized eigenvectors and enable us to recover the informative eigenvectors representing the global structure. We show applications of our method in several inference problems: community detection in networks, clustering from pairwise similarities, rank estimation and matrix completion problems. Using extensive experiments, we illustrate that our method solves the localization problem and works down to the theoretical detectability limits in...

  10. Spatial regularity of InAs-GaAs quantum dots: quantifying the dependence of lateral ordering on growth rate

    Science.gov (United States)

    Konishi, T.; Clarke, E.; Burrows, C. W.; Bomphrey, J. J.; Murray, R.; Bell, G. R.

    2017-02-01

    The lateral ordering of arrays of self-assembled InAs-GaAs quantum dots (QDs) has been quantified as a function of growth rate, using the Hopkins-Skellam index (HSI). Coherent QD arrays have a spatial distribution which is neither random nor ordered, but intermediate. The lateral ordering improves as the growth rate is increased and can be explained by more spatially regular nucleation as the QD density increases. By contrast, large and irregular 3D islands are distributed randomly on the surface. This is consistent with a random selection of the mature QDs relaxing by dislocation nucleation at a later stage in the growth, independently of each QD’s surroundings. In addition we explore the statistical variability of the HSI as a function of the number N of spatial points analysed, and we recommend N > 103 to reliably distinguish random from ordered arrays.

  11. Regularized discriminant analysis for multi-sensor decision fusion and damage detection with Lamb waves

    Science.gov (United States)

    Mishra, Spandan; Vanli, O. Arda; Huffer, Fred W.; Jung, Sungmoon

    2016-04-01

    In this study we propose a regularized linear discriminant analysis approach for damage detection which does not require an intermediate feature extraction step and therefore more efficient in handling data with high-dimensionality. A robust discriminant model is obtained by shrinking of the covariance matrix to a diagonal matrix and thresholding redundant predictors without hurting the predictive power of the model. The shrinking and threshold parameters of the discriminant function (decision boundary) are estimated to minimize the classification error. Furthermore, it is shown how the damage classification achieved by the proposed method can be extended to multiple sensors by following a Bayesian decision-fusion formulation. The detection probability of each sensor is used as a prior condition to estimate the posterior detection probability of the entire network and the posterior detection probability is used as a quantitative basis to make the final decision about the damage.

  12. Detecting regular sound changes in linguistics as events of concerted evolution.

    Science.gov (United States)

    Hruschka, Daniel J; Branford, Simon; Smith, Eric D; Wilkins, Jon; Meade, Andrew; Pagel, Mark; Bhattacharya, Tanmoy

    2015-01-05

    Concerted evolution is normally used to describe parallel changes at different sites in a genome, but it is also observed in languages where a specific phoneme changes to the same other phoneme in many words in the lexicon—a phenomenon known as regular sound change. We develop a general statistical model that can detect concerted changes in aligned sequence data and apply it to study regular sound changes in the Turkic language family. Linguistic evolution, unlike the genetic substitutional process, is dominated by events of concerted evolutionary change. Our model identified more than 70 historical events of regular sound change that occurred throughout the evolution of the Turkic language family, while simultaneously inferring a dated phylogenetic tree. Including regular sound changes yielded an approximately 4-fold improvement in the characterization of linguistic change over a simpler model of sporadic change, improved phylogenetic inference, and returned more reliable and plausible dates for events on the phylogenies. The historical timings of the concerted changes closely follow a Poisson process model, and the sound transition networks derived from our model mirror linguistic expectations. We demonstrate that a model with no prior knowledge of complex concerted or regular changes can nevertheless infer the historical timings and genealogical placements of events of concerted change from the signals left in contemporary data. Our model can be applied wherever discrete elements—such as genes, words, cultural trends, technologies, or morphological traits—can change in parallel within an organism or other evolving group. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  13. Cardiac C-arm computed tomography using a 3D + time ROI reconstruction method with spatial and temporal regularization

    Energy Technology Data Exchange (ETDEWEB)

    Mory, Cyril, E-mail: cyril.mory@philips.com [Université de Lyon, CREATIS, CNRS UMR5220, Inserm U1044, INSA-Lyon, Université Lyon 1, F-69621 Villeurbanne Cedex (France); Philips Research Medisys, 33 rue de Verdun, 92156 Suresnes (France); Auvray, Vincent; Zhang, Bo [Philips Research Medisys, 33 rue de Verdun, 92156 Suresnes (France); Grass, Michael; Schäfer, Dirk [Philips Research, Röntgenstrasse 24–26, D-22335 Hamburg (Germany); Chen, S. James; Carroll, John D. [Department of Medicine, Division of Cardiology, University of Colorado Denver, 12605 East 16th Avenue, Aurora, Colorado 80045 (United States); Rit, Simon [Université de Lyon, CREATIS, CNRS UMR5220, Inserm U1044, INSA-Lyon, Université Lyon 1 (France); Centre Léon Bérard, 28 rue Laënnec, F-69373 Lyon (France); Peyrin, Françoise [Université de Lyon, CREATIS, CNRS UMR5220, Inserm U1044, INSA-Lyon, Université Lyon 1, F-69621 Villeurbanne Cedex (France); X-ray Imaging Group, European Synchrotron, Radiation Facility, BP 220, F-38043 Grenoble Cedex (France); Douek, Philippe; Boussel, Loïc [Université de Lyon, CREATIS, CNRS UMR5220, Inserm U1044, INSA-Lyon, Université Lyon 1 (France); Hospices Civils de Lyon, 28 Avenue du Doyen Jean Lépine, 69500 Bron (France)

    2014-02-15

    Purpose: Reconstruction of the beating heart in 3D + time in the catheter laboratory using only the available C-arm system would improve diagnosis, guidance, device sizing, and outcome control for intracardiac interventions, e.g., electrophysiology, valvular disease treatment, structural or congenital heart disease. To obtain such a reconstruction, the patient's electrocardiogram (ECG) must be recorded during the acquisition and used in the reconstruction. In this paper, the authors present a 4D reconstruction method aiming to reconstruct the heart from a single sweep 10 s acquisition. Methods: The authors introduce the 4D RecOnstructiOn using Spatial and TEmporal Regularization (short 4D ROOSTER) method, which reconstructs all cardiac phases at once, as a 3D + time volume. The algorithm alternates between a reconstruction step based on conjugate gradient and four regularization steps: enforcing positivity, averaging along time outside a motion mask that contains the heart and vessels, 3D spatial total variation minimization, and 1D temporal total variation minimization. Results: 4D ROOSTER recovers the different temporal representations of a moving Shepp and Logan phantom, and outperforms both ECG-gated simultaneous algebraic reconstruction technique and prior image constrained compressed sensing on a clinical case. It generates 3D + time reconstructions with sharp edges which can be used, for example, to estimate the patient's left ventricular ejection fraction. Conclusions: 4D ROOSTER can be applied for human cardiac C-arm CT, and potentially in other dynamic tomography areas. It can easily be adapted to other problems as regularization is decoupled from projection and back projection.

  14. The Regularized Iteratively Reweighted MAD Method for Change Detection in Multi- and Hyperspectral Data

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2007-01-01

    This paper describes new extensions to the previously published multivariate alteration detection (MAD) method for change detection in bi-temporal, multi- and hypervariate data such as remote sensing imagery. Much like boosting methods often applied in data mining work, the iteratively reweighted...... an agricultural region in Kenya, and hyperspectral airborne HyMap data from a small rural area in southeastern Germany are given. The latter case demonstrates the need for regularization....... (IR) MAD method in a series of iterations places increasing focus on “difficult” observations, here observations whose change status over time is uncertain. The MAD method is based on the established technique of canonical correlation analysis: for the multivariate data acquired at two points in time...

  15. Redistribution population data across a regular spatial grid according to buildings characteristics

    Science.gov (United States)

    Calka, Beata; Bielecka, Elzbieta; Zdunkiewicz, Katarzyna

    2016-12-01

    Population data are generally provided by state census organisations at the predefined census enumeration units. However, these datasets very are often required at userdefined spatial units that differ from the census output levels. A number of population estimation techniques have been developed to address these problems. This article is one of those attempts aimed at improving county level population estimates by using spatial disaggregation models with support of buildings characteristic, derived from national topographic database, and average area of a flat. The experimental gridded population surface was created for Opatów county, sparsely populated rural region located in Central Poland. The method relies on geolocation of population counts in buildings, taking into account the building volume and structural building type and then aggregation the people total in 1 km quadrilateral grid. The overall quality of population distribution surface expressed by the mean of RMSE equals 9 persons, and the MAE equals 0.01. We also discovered that nearly 20% of total county area is unpopulated and 80% of people lived on 33% of the county territory.

  16. CRISPR Recognition Tool (CRT): a tool for automatic detection ofclustered regularly interspaced palindromic repeats

    Energy Technology Data Exchange (ETDEWEB)

    Bland, Charles; Ramsey, Teresa L.; Sabree, Fareedah; Lowe,Micheal; Brown, Kyndall; Kyrpides, Nikos C.; Hugenholtz, Philip

    2007-05-01

    Clustered Regularly Interspaced Palindromic Repeats (CRISPRs) are a novel type of direct repeat found in a wide range of bacteria and archaea. CRISPRs are beginning to attract attention because of their proposed mechanism; that is, defending their hosts against invading extrachromosomal elements such as viruses. Existing repeat detection tools do a poor job of identifying CRISPRs due to the presence of unique spacer sequences separating the repeats. In this study, a new tool, CRT, is introduced that rapidly and accurately identifies CRISPRs in large DNA strings, such as genomes and metagenomes. CRT was compared to CRISPR detection tools, Patscan and Pilercr. In terms of correctness, CRT was shown to be very reliable, demonstrating significant improvements over Patscan for measures precision, recall and quality. When compared to Pilercr, CRT showed improved performance for recall and quality. In terms of speed, CRT also demonstrated superior performance, especially for genomes containing large numbers of repeats. In this paper a new tool was introduced for the automatic detection of CRISPR elements. This tool, CRT, was shown to be a significant improvement over the current techniques for CRISPR identification. CRT's approach to detecting repetitive sequences is straightforward. It uses a simple sequential scan of a DNA sequence and detects repeats directly without any major conversion or preprocessing of the input. This leads to a program that is easy to describe and understand; yet it is very accurate, fast and memory efficient, being O(n) in space and O(nm/l) in time.

  17. CT Image Reconstruction by Spatial-Radon Domain Data-Driven Tight Frame Regularization

    CERN Document Server

    Zhan, Ruohan

    2016-01-01

    This paper proposes a spatial-Radon domain CT image reconstruction model based on data-driven tight frames (SRD-DDTF). The proposed SRD-DDTF model combines the idea of joint image and Radon domain inpainting model of \\cite{Dong2013X} and that of the data-driven tight frames for image denoising \\cite{cai2014data}. It is different from existing models in that both CT image and its corresponding high quality projection image are reconstructed simultaneously using sparsity priors by tight frames that are adaptively learned from the data to provide optimal sparse approximations. An alternative minimization algorithm is designed to solve the proposed model which is nonsmooth and nonconvex. Convergence analysis of the algorithm is provided. Numerical experiments showed that the SRD-DDTF model is superior to the model by \\cite{Dong2013X} especially in recovering some subtle structures in the images.

  18. Spherical deconvolution of multichannel diffusion MRI data with non-Gaussian noise models and total variation spatial regularization

    CERN Document Server

    Canales-Rodríguez, Erick J; Sotiropoulos, Stamatios N; Caruyer, Emmanuel; Aja-Fernández, Santiago; Radua, Joaquim; Mendizabal, Yosu Yurramendi; Iturria-Medina, Yasser; Melie-García, Lester; Alemán-Gómez, Yasser; Thiran, Jean-Philippe; Sarró, Salvador; Pomarol-Clotet, Edith; Salvador, Raymond

    2014-01-01

    Due to a higher capability in resolving white matter fiber crossings, Spherical Deconvolution (SD) methods have become very popular in brain fiber-tracking applications. However, while some of these estimation algorithms assume a central Gaussian distribution for the MRI noise, its real distribution is known to be non-Gaussian and to depend on many factors such as the number of coils and the methodology used to combine multichannel signals. Indeed, the two prevailing methods for multichannel signal combination lead to noise patterns better described by Rician and noncentral Chi distributions. Here we develop a Robust and Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD) technique intended to deal with realistic MRI noise. The algorithm relies on a maximum a posteriori formulation based on Rician and noncentral Chi likelihood models and includes a total variation (TV) spatial regularization term. By means of a synthetic phantom contaminated with noise mimicking patterns generated by data processing in mu...

  19. Diffeomorphic registration with self-adaptive spatial regularization for the segmentation of non-human primate brains.

    Science.gov (United States)

    Risser, Laurent; Dolius, Lionel; Fonta, Caroline; Mescam, Muriel

    2014-01-01

    Cerebral aging has been linked to structural and functional changes in the brain throughout life. Here, we study the marmoset, a small non-human primate, in order to get insights into the mechanisms of brain aging in normal and pathological conditions. Imaging the brain of small animals with techniques such as MRI, quickly becomes a challenging task when compared with human brain imaging. Very often, a simple pre-processing step such as brain extraction cannot be achieved with classical tools. In this paper, we propose a diffeomorphic registration algorithm, which makes use of learned constraints to propagate the manual segmentation of a marmoset brain template to other MR images of marmoset brains. The main methological contribution of our paper is to explore a new strategy to automatically tune the spatial regularization of the deformations. Results show that we obtain a robust segmentation of the brain, even for images with a low contrast.

  20. Spatial Temporal Land Use Change Detection Using Google Earth Data

    Science.gov (United States)

    Wibowo, Adi; Osman Salleh, Khairulmaini; Sitanala Frans, F. Th. R.; Mulyo Semedi, Jarot

    2016-11-01

    Land use as representation of human activities had different type. Human activity needs land for home, food, school, work, and leisure. Land use changed depends on human activity in the world within spatial and temporal term. This study aims to identify land use change using Google Earth data spatially and temporally. To answer the aim of this research, Google Earth data within five-year used for the analysis. This technique use for detection and mapping the land use change. The result saw the spatial-temporal land use change each year. This result addressed very importance of Google Earth Data as spatial temporal land use detection for land use mapping.

  1. Multispectral photoacoustic decomposition with localized regularization for detecting targeted contrast agent

    Science.gov (United States)

    Tavakoli, Behnoosh; Chen, Ying; Guo, Xiaoyu; Kang, Hyun Jae; Pomper, Martin; Boctor, Emad M.

    2015-03-01

    Targeted contrast agents can improve the sensitivity of imaging systems for cancer detection and monitoring the treatment. In order to accurately detect contrast agent concentration from photoacoustic images, we developed a decomposition algorithm to separate photoacoustic absorption spectrum into components from individual absorbers. In this study, we evaluated novel prostate-specific membrane antigen (PSMA) targeted agents for imaging prostate cancer. Three agents were synthesized through conjugating PSMA-targeting urea with optical dyes ICG, IRDye800CW and ATTO740 respectively. In our preliminary PA study, dyes were injected in a thin wall plastic tube embedded in water tank. The tube was illuminated with pulsed laser light using a tunable Q-switch ND-YAG laser. PA signal along with the B-mode ultrasound images were detected with a diagnostic ultrasound probe in orthogonal mode. PA spectrums of each dye at 0.5 to 20 μM concentrations were estimated using the maximum PA signal extracted from images which are obtained at illumination wavelengths of 700nm-850nm. Subsequently, we developed nonnegative linear least square optimization method along with localized regularization to solve the spectral unmixing. The algorithm was tested by imaging mixture of those dyes. The concentration of each dye was estimated with about 20% error on average from almost all mixtures albeit the small separation between dyes spectrums.

  2. CRISPR Recognition Tool (CRT: a tool for automatic detection of clustered regularly interspaced palindromic repeats

    Directory of Open Access Journals (Sweden)

    Brown Kyndall

    2007-06-01

    Full Text Available Abstract Background Clustered Regularly Interspaced Palindromic Repeats (CRISPRs are a novel type of direct repeat found in a wide range of bacteria and archaea. CRISPRs are beginning to attract attention because of their proposed mechanism; that is, defending their hosts against invading extrachromosomal elements such as viruses. Existing repeat detection tools do a poor job of identifying CRISPRs due to the presence of unique spacer sequences separating the repeats. In this study, a new tool, CRT, is introduced that rapidly and accurately identifies CRISPRs in large DNA strings, such as genomes and metagenomes. Results CRT was compared to CRISPR detection tools, Patscan and Pilercr. In terms of correctness, CRT was shown to be very reliable, demonstrating significant improvements over Patscan for measures precision, recall and quality. When compared to Pilercr, CRT showed improved performance for recall and quality. In terms of speed, CRT proved to be a huge improvement over Patscan. Both CRT and Pilercr were comparable in speed, however CRT was faster for genomes containing large numbers of repeats. Conclusion In this paper a new tool was introduced for the automatic detection of CRISPR elements. This tool, CRT, showed some important improvements over current techniques for CRISPR identification. CRT's approach to detecting repetitive sequences is straightforward. It uses a simple sequential scan of a DNA sequence and detects repeats directly without any major conversion or preprocessing of the input. This leads to a program that is easy to describe and understand; yet it is very accurate, fast and memory efficient, being O(n in space and O(nm/l in time.

  3. Spatial emission distribution and carrier recombination dynamics in regularly arrayed InGaN/GaN quantum structure nanocolumns

    Science.gov (United States)

    Oto, Takao; Mizuno, Yutaro; Miyagawa, Rin; Kano, Tatsuya; Yoshida, Jun; Ema, Kazuhiro; Kishino, Katsumi

    2016-10-01

    Emission mechanisms in regularly arrayed InGaN/GaN quantum structures on GaN nanocolumns were investigated, focusing on the spatial emission distribution at the nanocolumn tops and the carrier recombination dynamics. The double-peak emission originated from the dot- and well-like InGaN areas with different In compositions was observed. From the results regarding the spatial emission distribution, we proposed a simple analytical approach to evaluating the carrier recombination dynamics using the rate equations based on the two energy states. The considerable six lifetimes can be uniquely determined from the experimental results. Carrier transfer from the high- to the low-energy state is dominant at high temperatures, producing the increased total emission efficiency of the inner low-energy area. In addition, the internal quantum efficiency should not be simply discussed using only the integrated intensity ratio between low and room temperatures because of the carrier transfer from high- to low-energy states.

  4. Spatial correlation coefficient images for ultrasonic detection.

    Science.gov (United States)

    Cepel, Raina; Ho, K C; Rinker, Brett A; Palmer, Donald D; Lerch, Terrence P; Neal, Steven P

    2007-09-01

    In ultrasonics, image formation and detection are generally based on signal amplitude. In this paper, we introduce correlation coefficient images as a signal-amplitude independent approach for image formation. The correlation coefficients are calculated between A-scans digitized at adjacent measurement positions. In these images, defects are revealed as regions of high or low correlation relative to the background correlations associated with noise. Correlation coefficient and C-scan images are shown to demonstrate flat-bottom-hole detection in a stainless steel annular ring and crack detection in an aluminum aircraft structure.

  5. Spatial Heterodyne Spectrometer for Aviation Hazard Detection Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Physical Sciences Inc (PSI) proposes the development of a longwave infrared (LWIR) imaging spatial heterodyne spectrometer (I-SHS) for standoff detection of clear...

  6. An Improved Direction Relation Detection Model for Spatial Objects

    Institute of Scientific and Technical Information of China (English)

    FENG Yucai; YI Baolin

    2004-01-01

    Direction is a common spatial concept that is used in our daily life. It is frequently used as a selection condition in spatial queries. As a result, it is important for spatial databases to provide a mechanism for modeling and processing direction queries and reasoning. Depending on the direction relation matrix, an inverted direction relation matrix and the concept of direction pre- dominance are proposed to improve the detection of direction relation between objects. Direction predicates of spatial systems are also extended. These techniques can improve the veracity of direction queries and reasoning. Experiments show excellent efficiency and performance in view of direction queries.

  7. A flexibly shaped spatial scan statistic for detecting clusters

    Directory of Open Access Journals (Sweden)

    Takahashi Kunihiko

    2005-05-01

    Full Text Available Abstract Background The spatial scan statistic proposed by Kulldorff has been applied to a wide variety of epidemiological studies for cluster detection. This scan statistic, however, uses a circular window to define the potential cluster areas and thus has difficulty in correctly detecting actual noncircular clusters. A recent proposal by Duczmal and Assunção for detecting noncircular clusters is shown to detect a cluster of very irregular shape that is much larger than the true cluster in our experiences. Methods We propose a flexibly shaped spatial scan statistic that can detect irregular shaped clusters within relatively small neighborhoods of each region. The performance of the proposed spatial scan statistic is compared to that of Kulldorff's circular spatial scan statistic with Monte Carlo simulation by considering several circular and noncircular hot-spot cluster models. For comparison, we also propose a new bivariate power distribution classified by the number of regions detected as the most likely cluster and the number of hot-spot regions included in the most likely cluster. Results The circular spatial scan statistics shows a high level of accuracy in detecting circular clusters exactly. The proposed spatial scan statistic is shown to have good usual powers plus the ability to detect the noncircular hot-spot clusters more accurately than the circular one. Conclusion The proposed spatial scan statistic is shown to work well for small to moderate cluster size, up to say 30. For larger cluster sizes, the method is not practically feasible and a more efficient algorithm is needed.

  8. Regularized discriminate analysis for breast mass detection on full field digital mammograms

    Science.gov (United States)

    Wei, Jun; Sahiner, Berkman; Zhang, Yiheng; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Zhou, Chuan; Ge, Jun; Wu, Yi-Ta

    2006-03-01

    In computer-aided detection (CAD) applications, an important step is to design a classifier for the differentiation of the abnormal from the normal structures. We have previously developed a stepwise linear discriminant analysis (LDA) method with simplex optimization for this purpose. In this study, our goal was to investigate the performance of a regularized discriminant analysis (RDA) classifier in combination with a feature selection method for classification of the masses and normal tissues detected on full field digital mammograms (FFDM). The feature selection scheme combined a forward stepwise feature selection process and a backward stepwise feature elimination process to obtain the best feature subset. An RDA classifier and an LDA classifier in combination with this new feature selection method were compared to an LDA classifier with stepwise feature selection. A data set of 130 patients containing 260 mammograms with 130 biopsy-proven masses was used. All cases had two mammographic views. The true locations of the masses were identified by experienced radiologists. To evaluate the performance of the classifiers, we randomly divided the data set into two independent sets of approximately equal size for training and testing. The training and testing were performed using the 2-fold cross validation method. The detection performance of the CAD system was assessed by free response receiver operating characteristic (FROC) analysis. The average test FROC curve was obtained by averaging the FP rates at the same sensitivity along the two corresponding test FROC curves from the 2-fold cross validation. At the case-based sensitivities of 90%, 80% and 70% on the test set, our RDA classifier with the new feature selection scheme achieved an FP rate of 1.8, 1.1, and 0.6 FPs/image, respectively, compared to 2.1, 1.4, and 0.8 FPs/image with stepwise LDA with simplex optimization. Our results indicate that RDA in combination with the sequential forward inclusion

  9. Effects of regular exercise and dual tasking on spatial and temporal parameters of obstacle negotiation in elderly women.

    Science.gov (United States)

    Guadagnin, E C; da Rocha, E S; Mota, C B; Carpes, F P

    2015-09-01

    This study investigated the effects of regular exercise and dual tasking on bilateral spatial and temporal parameters of obstacle negotiation in elderly women. Sedentary (n=12) and physically active (n=12) elderly women volunteered to participate in this study. Gait kinematics were recorded during obstacle crossing when performing a dual task and when not performing a dual task. Physically active participants crossed obstacles more safely, in terms of clearance or distance to or over the obstacle, both with and without dual tasking, and usually for both lead and trail legs. Performing the dual task increased toe distance, and decreased heel distance and gait speed in the active participants, and increased toe clearance and heel distance, and decreased gait speed in the sedentary participants. Differences between preferred and non-preferred leg were accentuated for toe clearance in the lead limb. These results suggest that specialized exercises may not be needed for improvement in obstacle avoidance skills in the elderly, and participation in multi-activities, including aerobic exercises, may be sufficient. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. Spatial Outlier Detection of CO2 Monitoring Data Based on Spatial Local Outlier Factor

    Directory of Open Access Journals (Sweden)

    Liu Xin

    2015-12-01

    Full Text Available Spatial local outlier factor (SLOF algorithm was adopted in this study for spatial outlier detection because of the limitations of the traditional static threshold detection. Based on the spatial characteristics of CO2 monitoring data obtained in the carbon capture and storage (CCS project, the K-Nearest Neighbour (KNN graph was constructed using the latitude and longitude information of the monitoring points to identify the spatial neighbourhood of the monitoring points. Then SLOF was adopted to calculate the outlier degrees of the monitoring points and the 3σ rule was employed to identify the spatial outlier. Finally, the selection of K value was analysed and the optimal one was selected. The results show that, compared with the static threshold method, the proposed algorithm has a higher detection precision. It can overcome the shortcomings of the static threshold method and improve the accuracy and diversity of local outlier detection, which provides a reliable reference for the safety assessment and warning of CCS monitoring.

  11. Modelling aggregation on the large scale and regularity on the small scale in spatial point pattern datasets

    DEFF Research Database (Denmark)

    Lavancier, Frédéric; Møller, Jesper

    We consider a dependent thinning of a regular point process with the aim of obtaining aggregation on the large scale and regularity on the small scale in the resulting target point process of retained points. Various parametric models for the underlying processes are suggested and the properties ...

  12. Local Regularity Analysis with Wavelet Transform in Gear Tooth Failure Detection

    Science.gov (United States)

    Nissilä, Juhani

    2017-09-01

    Diagnosing gear tooth and bearing failures in industrial power transition situations has been studied a lot but challenges still remain. This study aims to look at the problem from a more theoretical perspective. Our goal is to find out if the local regularity i.e. smoothness of the measured signal can be estimated from the vibrations of epicyclic gearboxes and if the regularity can be linked to the meshing events of the gear teeth. Previously it has been shown that the decreasing local regularity of the measured acceleration signals can reveal the inner race faults in slowly rotating bearings. The local regularity is estimated from the modulus maxima ridges of the signal's wavelet transform. In this study, the measurements come from the epicyclic gearboxes of the Kelukoski water power station (WPS). The very stable rotational speed of the WPS makes it possible to deduce that the gear mesh frequencies of the WPS and a frequency related to the rotation of the turbine blades are the most significant components in the spectra of the estimated local regularity signals.

  13. Spatial Cloud Detection and Retrieval System for Satellite Images

    Directory of Open Access Journals (Sweden)

    Ayman Nasr

    2013-01-01

    Full Text Available In last the decade we witnessed a large increase in data generated by earth observing satellites. Hence, intelligent processing of the huge amount of data received by hundreds of earth receiving stations, with specific satellite image oriented approaches, presents itself as a pressing need. One of the most important steps in earlier stages of satellite image processing is cloud detection. Satellite images having a large percentage of cloud cannot be used in further analysis. While there are many approaches that deal with different semantic meaning, there are rarely approaches that deal specifically with cloud detection and retrieval. In this paper we introduce a novel approach that spatially detect and retrieve clouds in satellite images using their unique properties .Our approach is developed as spatial cloud detection and retrieval system (SCDRS that introduce a complete framework for specific semantic retrieval system. It uses a Query by polygon (QBP paradigm for the content of interest instead of using the more conventional rectangular query by image approach. First, we extract features from the satellite images using multiple tile sizes using spatial and textural properties of cloud regions. Second, we retrieve our tiles using a parametric statistical approach within a multilevel refinement process. Our approach has been experimentally validated against the conventional ones yielding enhanced precision and recall rates in the same time it gives more precise detection of cloud coverage regions.

  14. Spatial-temporal event detection in climate parameter imagery.

    Energy Technology Data Exchange (ETDEWEB)

    McKenna, Sean Andrew; Gutierrez, Karen A.

    2011-10-01

    Previously developed techniques that comprise statistical parametric mapping, with applications focused on human brain imaging, are examined and tested here for new applications in anomaly detection within remotely-sensed imagery. Two approaches to analysis are developed: online, regression-based anomaly detection and conditional differences. These approaches are applied to two example spatial-temporal data sets: data simulated with a Gaussian field deformation approach and weekly NDVI images derived from global satellite coverage. Results indicate that anomalies can be identified in spatial temporal data with the regression-based approach. Additionally, la Nina and el Nino climatic conditions are used as different stimuli applied to the earth and this comparison shows that el Nino conditions lead to significant decreases in NDVI in both the Amazon Basin and in Southern India.

  15. Spatial acuity and prey detection in weakly electric fish.

    Directory of Open Access Journals (Sweden)

    David Babineau

    2007-03-01

    Full Text Available It is well-known that weakly electric fish can exhibit extreme temporal acuity at the behavioral level, discriminating time intervals in the submicrosecond range. However, relatively little is known about the spatial acuity of the electrosense. Here we use a recently developed model of the electric field generated by Apteronotus leptorhynchus to study spatial acuity and small signal extraction. We show that the quality of sensory information available on the lateral body surface is highest for objects close to the fish's midbody, suggesting that spatial acuity should be highest at this location. Overall, however, this information is relatively blurry and the electrosense exhibits relatively poor acuity. Despite this apparent limitation, weakly electric fish are able to extract the minute signals generated by small prey, even in the presence of large background signals. In fact, we show that the fish's poor spatial acuity may actually enhance prey detection under some conditions. This occurs because the electric image produced by a spatially dense background is relatively "blurred" or spatially uniform. Hence, the small spatially localized prey signal "pops out" when fish motion is simulated. This shows explicitly how the back-and-forth swimming, characteristic of these fish, can be used to generate motion cues that, as in other animals, assist in the extraction of sensory information when signal-to-noise ratios are low. Our study also reveals the importance of the structure of complex electrosensory backgrounds. Whereas large-object spacing is favorable for discriminating the individual elements of a scene, small spacing can increase the fish's ability to resolve a single target object against this background.

  16. Fast entanglement detection for unknown states of two spatial qutrits

    CERN Document Server

    Lima, G; Vargas, A; Vianna, R O; Saavedra, C

    2010-01-01

    We investigate the practicality of the method proposed by Maciel et al. [Phys. Rev. A. 80, 032325(2009)] for detecting the entanglement of two spatial qutrits (3-dimensional quantum systems), which are encoded in the discrete transverse momentum of single photons transmitted through a multi-slit aperture. The method is based on the acquisition of partial information of the quantum state through projective measurements, and a data processing analysis done with semi-definite programs. This analysis relies on generating gradually an optimal entanglement witness operator, and numerical investigations have shown that it allows for the entanglement detection of unknown states with a cost much lower than full state tomography.

  17. Analysis of sea-surface radar signatures by means of wavelet-based edge detection and detection of regularities; Analyse von Radarsignaturen der Meeresoberflaeche mittels auf Wavelets basierender Kantenerkennung und Regularitaetsbestimmung

    Energy Technology Data Exchange (ETDEWEB)

    Wolff, U. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Gewaesserphysik

    2000-07-01

    The derivation and implementation of an algorithm for edge detection in images and for the detection of the Lipschitz regularity in edge points are described. The method is based on the use of the wavelet transform for edge detection at different resolutions. The Lipschitz regularity is a measure that characterizes the edges. The description of the derivation is first performed in one dimension. The approach of Mallat is formulated consistently and proved. Subsequently, the two-dimensional case is addressed, for which the derivation, as well as the description of the algorithm, is analogous. The algorithm is applied to detect edges in nautical radar images using images collected at the island of Sylt. The edges discernible in the images and the Lipschitz values provide information about the position and nature of spatial variations in the depth of the seafloor. By comparing images from different periods of measurement, temporal changes in the bottom structures can be localized at different resolutions and interpreted. The method is suited to the monitoring of coastal areas. It is an inexpensive way to observe long-term changes in the seafloor character. Thus, the results of this technique may be used by the authorities responsible for coastal protection to decide whether measures should be taken or not. (orig.)

  18. Detection of epigenetic changes using ANOVA with spatially varying coefficients.

    Science.gov (United States)

    Guanghua, Xiao; Xinlei, Wang; Quincey, LaPlant; Nestler, Eric J; Xie, Yang

    2013-03-13

    Identification of genome-wide epigenetic changes, the stable changes in gene function without a change in DNA sequence, under various conditions plays an important role in biomedical research. High-throughput epigenetic experiments are useful tools to measure genome-wide epigenetic changes, but the measured intensity levels from these high-resolution genome-wide epigenetic profiling data are often spatially correlated with high noise levels. In addition, it is challenging to detect genome-wide epigenetic changes across multiple conditions, so efficient statistical methodology development is needed for this purpose. In this study, we consider ANOVA models with spatially varying coefficients, combined with a hierarchical Bayesian approach, to explicitly model spatial correlation caused by location-dependent biological effects (i.e., epigenetic changes) and borrow strength among neighboring probes to compare epigenetic changes across multiple conditions. Through simulation studies and applications in drug addiction and depression datasets, we find that our approach compares favorably with competing methods; it is more efficient in estimation and more effective in detecting epigenetic changes. In addition, it can provide biologically meaningful results.

  19. Spatial and Spectral Methods for Weed Detection and Localization

    Directory of Open Access Journals (Sweden)

    Truchetet Frédéric

    2002-01-01

    Full Text Available This study concerns the detection and localization of weed patches in order to improve the knowledge on weed-crop competition. A remote control aircraft provided with a camera allowed to obtain low cost and repetitive information. Different processings were involved to detect weed patches using spatial then spectral methods. First, a shift of colorimetric base allowed to separate the soil and plant pixels. Then, a specific algorithm including Gabor filter was applied to detect crop rows on the vegetation image. Weed patches were then deduced from the comparison of vegetation and crop images. Finally, the development of a multispectral acquisition device is introduced. First results for the discrimination of weeds and crops using the spectral properties are shown from laboratory tests. Application of neural networks were mostly studied.

  20. Computer-aided detection of clustered microcalcifications in multiscale bilateral filtering regularized reconstructed digital breast tomosynthesis volume

    Energy Technology Data Exchange (ETDEWEB)

    Samala, Ravi K., E-mail: rsamala@umich.edu; Chan, Heang-Ping; Lu, Yao; Hadjiiski, Lubomir; Wei, Jun; Helvie, Mark A. [Department of Radiology, University of Michigan, Ann Arbor, Michigan 48109-5842 (United States); Sahiner, Berkman [Center for Devices and Radiological Health, U.S. Food and Drug Administration, Maryland 20993 (United States)

    2014-02-15

    Purpose: Develop a computer-aided detection (CADe) system for clustered microcalcifications in digital breast tomosynthesis (DBT) volume enhanced with multiscale bilateral filtering (MSBF) regularization. Methods: With Institutional Review Board approval and written informed consent, two-view DBT of 154 breasts, of which 116 had biopsy-proven microcalcification (MC) clusters and 38 were free of MCs, was imaged with a General Electric GEN2 prototype DBT system. The DBT volumes were reconstructed with MSBF-regularized simultaneous algebraic reconstruction technique (SART) that was designed to enhance MCs and reduce background noise while preserving the quality of other tissue structures. The contrast-to-noise ratio (CNR) of MCs was further improved with enhancement-modulated calcification response (EMCR) preprocessing, which combined multiscale Hessian response to enhance MCs by shape and bandpass filtering to remove the low-frequency structured background. MC candidates were then located in the EMCR volume using iterative thresholding and segmented by adaptive region growing. Two sets of potential MC objects, cluster centroid objects and MC seed objects, were generated and the CNR of each object was calculated. The number of candidates in each set was controlled based on the breast volume. Dynamic clustering around the centroid objects grouped the MC candidates to form clusters. Adaptive criteria were designed to reduce false positive (FP) clusters based on the size, CNR values and the number of MCs in the cluster, cluster shape, and cluster based maximum intensity projection. Free-response receiver operating characteristic (FROC) and jackknife alternative FROC (JAFROC) analyses were used to assess the performance and compare with that of a previous study. Results: Unpaired two-tailedt-test showed a significant increase (p < 0.0001) in the ratio of CNRs for MCs with and without MSBF regularization compared to similar ratios for FPs. For view-based detection, a

  1. Improving PET spatial resolution and detectability for prostate cancer imaging

    Science.gov (United States)

    Bal, H.; Guerin, L.; Casey, M. E.; Conti, M.; Eriksson, L.; Michel, C.; Fanti, S.; Pettinato, C.; Adler, S.; Choyke, P.

    2014-08-01

    Prostate cancer, one of the most common forms of cancer among men, can benefit from recent improvements in positron emission tomography (PET) technology. In particular, better spatial resolution, lower noise and higher detectability of small lesions could be greatly beneficial for early diagnosis and could provide a strong support for guiding biopsy and surgery. In this article, the impact of improved PET instrumentation with superior spatial resolution and high sensitivity are discussed, together with the latest development in PET technology: resolution recovery and time-of-flight reconstruction. Using simulated cancer lesions, inserted in clinical PET images obtained with conventional protocols, we show that visual identification of the lesions and detectability via numerical observers can already be improved using state of the art PET reconstruction methods. This was achieved using both resolution recovery and time-of-flight reconstruction, and a high resolution image with 2 mm pixel size. Channelized Hotelling numerical observers showed an increase in the area under the LROC curve from 0.52 to 0.58. In addition, a relationship between the simulated input activity and the area under the LROC curve showed that the minimum detectable activity was reduced by more than 23%.

  2. -Regular Modules

    Directory of Open Access Journals (Sweden)

    Areej M. Abduldaim

    2013-01-01

    Full Text Available We introduced and studied -regular modules as a generalization of -regular rings to modules as well as regular modules (in the sense of Fieldhouse. An -module is called -regular if for each and , there exist and a positive integer such that . The notion of -pure submodules was introduced to generalize pure submodules and proved that an -module is -regular if and only if every submodule of is -pure iff   is a -regular -module for each maximal ideal of . Many characterizations and properties of -regular modules were given. An -module is -regular iff is a -regular ring for each iff is a -regular ring for finitely generated module . If is a -regular module, then .

  3. Clustering, Randomness, and Regularity: Spatial Distributions and Human Performance on the Traveling Salesperson Problem and Minimum Spanning Tree Problem

    Science.gov (United States)

    Dry, Matthew J.; Preiss, Kym; Wagemans, Johan

    2012-01-01

    We investigated human performance on the Euclidean Traveling Salesperson Problem (TSP) and Euclidean Minimum Spanning Tree Problem (MST-P) in regards to a factor that has previously received little attention within the literature: the spatial distributions of TSP and MST-P stimuli. First, we describe a method for quantifying the relative degree of…

  4. Analysis of Spatial Data Structures for Proximity Detection

    Institute of Scientific and Technical Information of China (English)

    Anupreet Walia; Jochen Teizer

    2008-01-01

    Construction is a dangerous business.According to statistics,in every of the past thirteen years more than 1000 workers died in the USA construction industry.In order to minimize the overall number of these incidents,the research presented in this paper investigates to monitor and analyze the trejectories of construction resources first in a simulated environment and later on the actual job site.Due to the complex nature of the construction environment,three dimensional (3D) positioning data of workers is hardly col-lected.Although technology is available that allows tracking construction assets in real-time,indoors and outdoors,in 3D,at the same time,the continuously changing spatial and temporal arrangement of job sites requires any successfully working data processing system to work in real-time.This research paper focuses is safety on spatial data structures that offer the capability of realigning itself and reporting the distance of the closest neighbor in real-time.This paper presents results to simulations that allow the processing of real-time location data for collision detection and proximity analysis.The presented data structures and perform-ance results to the developed algorithms demonstmte that real-time tracking and proximity detection of re-sources is feasible.

  5. An Examination of Three Spatial Event Cluster Detection Methods

    Directory of Open Access Journals (Sweden)

    Hensley H. Mariathas

    2015-03-01

    Full Text Available In spatial disease surveillance, geographic areas with large numbers of disease cases are to be identified, so that targeted investigations can be pursued. Geographic areas with high disease rates are called disease clusters and statistical cluster detection tests are used to identify geographic areas with higher disease rates than expected by chance alone. In some situations, disease-related events rather than individuals are of interest for geographical surveillance, and methods to detect clusters of disease-related events are called event cluster detection methods. In this paper, we examine three distributional assumptions for the events in cluster detection: compound Poisson, approximate normal and multiple hypergeometric (exact. The methods differ on the choice of distributional assumption for the potentially multiple correlated events per individual. The methods are illustrated on emergency department (ED presentations by children and youth (age < 18 years because of substance use in the province of Alberta, Canada, during 1 April 2007, to 31 March 2008. Simulation studies are conducted to investigate Type I error and the power of the clustering methods.

  6. A superresolution land-cover change detection method using remotely sensed images with different spatial resolutions

    OpenAIRE

    Li, Xiaodong; Ling, Feng; Giles M. Foody; Du, Yun

    2016-01-01

    The development of remote sensing has enabled the acquisition of information on land-cover change at different spatial scales. However, a trade-off between spatial and temporal resolutions normally exists. Fine-spatial-resolution images have low temporal resolutions, whereas coarse spatial resolution images have high temporal repetition rates. A novel super-resolution change detection method (SRCD)is proposed to detect land-cover changes at both fine spatial and temporal resolutions with the ...

  7. Instantaneous detection of spatial gradient errors in differential GNSS

    Science.gov (United States)

    Jing, Jing

    Global Navigation Satellite Systems (GNSS) have become a critical element of modern engineering and scientific applications. GPS is currently being used in the design of navigation systems for both civil and military aviation applications. Differential GPS carrier phase measurements between antennas provide a very precise measurement that is useful for these applications. In fact, ground infrastructure has already been implemented in the Ground Based Augmentation System (GBAS) to take advantage of these precise measurements for use in civil aviation. Furthermore, these antennas can also be used to detect and isolate certain signal-in-space (SIS) failures and anomalies that are hazardous to aviation applications, for example the ionospheric anomalies and ephemeris failures. This realization, in turn, has led to the development of numerous carrier-phase based monitors. One drawback of the majority of these monitors is that their performance within a given configuration is dependent on how antennas are paired to form double differences. In contrast, the null space monitor approach is developed to provide consistent detection performance regardless of how the antennas are paired which combines measurements from multiple, spatially separated ground antennas through a null space transformation. The instantaneous carrier phase monitor cannot detect all gradients due to the presence of integer ambiguities. These ambiguities cannot be resolved because the gradient magnitude is unknown a priori. Furthermore, it has been shown that the performance of such monitors is highly dependent on the reference antenna topology. The range of detectable gradients for all carrier phase monitors depends on two factors: the number of antennas and their configuration. Antenna configuration is often overlooked as a means to improve performance. and heuristic arguments typically prevail in the associated siting decisions. However. such heuristics do not provide the maximum detectable range of

  8. Regular figures

    CERN Document Server

    Tóth, L Fejes; Ulam, S; Stark, M

    1964-01-01

    Regular Figures concerns the systematology and genetics of regular figures. The first part of the book deals with the classical theory of the regular figures. This topic includes description of plane ornaments, spherical arrangements, hyperbolic tessellations, polyhedral, and regular polytopes. The problem of geometry of the sphere and the two-dimensional hyperbolic space are considered. Classical theory is explained as describing all possible symmetrical groupings in different spaces of constant curvature. The second part deals with the genetics of the regular figures and the inequalities fo

  9. Spatial- and Time-Correlated Detection of Fission Fragments

    Directory of Open Access Journals (Sweden)

    Platkevic M.

    2012-02-01

    Full Text Available With the goal to measure angular correlations of fission fragments in rare fission decay (e.g. ternary and quaternary fission, a multi-detector coincidence system based on two and up to four position sensitive pixel detectors Timepix has been built. In addition to the high granularity, wide dynamic range and per pixel signal threshold, these devices are equipped with per pixel energy and time sensitivity providing more information (position, energy, time, enhances particle-type identification and selectivity of event-by-event detection. Operation of the device with the integrated USB 2.0 based readout interface FITPix and the control and data acquisition software tool Pixelman enables online visualization and flexible/adjustable operation for a different type of experiments. Spatially correlated fission fragments can be thus registered in coincidence. Similarly triggered measurements are performed using an integrated spectrometric module with analogue signal chain electronics. The current status of development together with demonstration of the technique with a 252Cf source is presented.

  10. Infrared moving point target detection based on spatial-temporal local contrast filter

    Science.gov (United States)

    Deng, Lizhen; Zhu, Hu; Tao, Chao; Wei, Yantao

    2016-05-01

    Infrared moving point target detection is a challenging task. In this paper, we define a novel spatial local contrast (SLC) and a novel temporal local contrast (TLC) to enhance the target's contrast. Based on the defined spatial local contrast and temporal local contrast, we propose a simple but powerful spatial-temporal local contrast filter (STLCF) to detect moving point target from infrared image sequences. In order to verify the performance of spatial-temporal local contrast filter on detecting moving point target, different detection methods are used to detect the target from several infrared image sequences for comparison. The experimental results show that the proposed spatial-temporal local contrast filter has great superiority in moving point target detection.

  11. Automatic Change Detection of Geo-spatial Data from Imagery

    Institute of Scientific and Technical Information of China (English)

    LI Deren; SUI Haigang; XIAO Ping

    2003-01-01

    The problems and difficulty of current change detection tech-niques are presented. Then, according to whether image registration is donebefore change detection algorithms,the authors classify the change detection into two categories:the change de-tection after image registration and the change detection simultaneous with image registration. For the former,four topics including the change detection between new image and old im-age, the change detection between newimage and old map, the change detection between new image/old image andold map, and the change detection between new multi-source images and old map/image are introduced. For the latter, three categories, I. E. Thechange detection between old DEM,DOM and new non-rectification image,the change detection between oldDLG, DRG and new non-rectificationimage, and the 3D change detectionbetween old 4D products and new multi overlapped photos, are discussed.

  12. In situ, spatially resolved biosignature detection at the microbial scale

    Science.gov (United States)

    Williford, K. H.; Eigenbrode, J. L.; Hallmann, C.; Kitajima, K.; Kozdon, R.; Summons, R. E.; Kudryavstev, A.; Lepot, K.; Schopf, J.; Spicuzza, M.; Sugitani, K.; Ushikubo, T.; van Kranendonk, M.; Valley, J. W.

    2013-12-01

    Whether life has ever existed beyond Earth is one of the great human questions. The Science Definition Team (SDT) for the proposed NASA Mars 2020 rover mission recently announced a suggested approach for NASA to 'demonstrate significant technical progress towards the future return of scientifically selected, well-documented samples to Earth' in part 'to investigate whether Mars was ever inhabited by microbial life.' The SDT further recommended a per-sample volume of 8 cm3 [1] (e.g., a core with a diameter of 1 cm and length of 10 cm). Such samples would be the first available for scientific inquiry with the potential to definitively answer the fundamental question of astrobiology, and their small volume would necessitate analysis with non- or minimally destructive techniques. Potential biosignatures include 'chemical, isotopic, mineralogical, and morphological features that can be created by life and also appear to be inconsistent with nonbiological processes'[1]. Guidelines for biosignature detection in extraterrestrial samples derive in part from the search for evidence of life in the most ancient sedimentary rocks on Earth, wherein the most compelling case for biogenicity is made when these 'chemical, isotopic, mineralogical, and morphological features' occur in association. Sedimentary rocks deposited on Earth prior to ~3.5 billion years ago (i.e., when persistent surface water [e.g., 2] likely supported habitable environments on Mars) have only very rarely escaped severe alteration by metamorphism and metasomatism. Understanding how these processes have operated on Earth through strategic interrogation of biosignature alteration records in (meta)sedimentary rocks is thus a critical task in the search for extraterrestrial life. Here we present techniques for and results of in situ, spatially resolved, non- or minimally destructive detection of morphological, elemental, molecular, and light stable isotopic biosignatures, as well as records of alteration, in

  13. Designing efficient surveys: spatial arrangement of sample points for detection of invasive species

    Science.gov (United States)

    Ludek Berec; John M. Kean; Rebecca Epanchin-Niell; Andrew M. Liebhold; Robert G. Haight

    2015-01-01

    Effective surveillance is critical to managing biological invasions via early detection and eradication. The efficiency of surveillance systems may be affected by the spatial arrangement of sample locations. We investigate how the spatial arrangement of sample points, ranging from random to fixed grid arrangements, affects the probability of detecting a target...

  14. The additional yield of a periodic screening programme for open-angle glaucoma : a population-based comparison of incident glaucoma cases detected in regular ophthalmic care with cases detected during screening

    NARCIS (Netherlands)

    Stoutenbeek, R.; de Voogd, S.; Wolfs, R. C. W.; Hofman, A.; de Jong, P. T. V. M.; Jansonius, N. M.

    2008-01-01

    Aim: To study the additional yield of a periodic screening programme for open-angle glaucoma (OAG) by comparing, in a population-based setting, incident OAG (iOAG) cases detected in regular ophthalmic care with those detected during screening. Methods: Participants aged 55 and over from the populati

  15. Investigation of context, soft spatial, and spatial frequency domain features for buried explosive hazard detection in FL-LWIR

    Science.gov (United States)

    Price, Stanton R.; Anderson, Derek T.; Stone, Kevin; Keller, James M.

    2014-05-01

    It is well-known that a pattern recognition system is only as good as the features it is built upon. In the fields of image processing and computer vision, we have numerous spatial domain and spatial-frequency domain features to extract characteristics of imagery according to its color, shape and texture. However, these approaches extract information across a local neighborhood, or region of interest, which for target detection contains both object(s) of interest and background (surrounding context). A goal of this research is to filter out as much task irrelevant information as possible, e.g., tire tracks, surface texture, etc., to allow a system to place more emphasis on image features in spatial regions that likely belong to the object(s) of interest. Herein, we outline a procedure coined soft feature extraction to refine the focus of spatial domain features. This idea is demonstrated in the context of an explosive hazards detection system using forward looking infrared imagery. We also investigate different ways to spatially contextualize and calculate mathematical features from shearlet filtered candidate image chips. Furthermore, we investigate localization strategies in relation to different ways of grouping image features to reduce the false alarm rate. Performance is explored in the context of receiver operating characteristic curves on data from a U.S. Army test site that contains multiple target and clutter types, burial depths, and times of day.

  16. Detection of Outliers in Spatial-Temporal Data

    Science.gov (United States)

    Rogers, James P.

    2010-01-01

    Outlier detection is an important data mining task that is focused on the discovery of objects that deviate significantly when compared with a set of observations that are considered typical. Outlier detection can reveal objects that behave anomalously with respect to other observations, and these objects may highlight current or future problems. …

  17. Detecting spatial ontogenetic niche shifts in complex dendritic ecological networks

    Science.gov (United States)

    Fields, William R.; Grant, Evan; Lowe, Winsor H.

    2017-01-01

    Ontogenetic niche shifts (ONS) are important drivers of population and community dynamics, but they can be difficult to identify for species with prolonged larval or juvenile stages, or for species that inhabit continuous habitats. Most studies of ONS focus on single transitions among discrete habitat patches at local scales. However, for species with long larval or juvenile periods, affinity for particular locations within connected habitat networks may differ among cohorts. The resulting spatial patterns of distribution can result from a combination of landscape-scale habitat structure, position of a habitat patch within a network, and local habitat characteristics—all of which may interact and change as individuals grow. We estimated such spatial ONS for spring salamanders (Gyrinophilus porphyriticus), which have a larval period that can last 4 years or more. Using mixture models to identify larval cohorts from size frequency data, we fit occupancy models for each age class using two measures of the branching structure of stream networks and three measures of stream network position. Larval salamander cohorts showed different preferences for the position of a site within the stream network, and the strength of these responses depended on the basin-wide spatial structure of the stream network. The isolation of a site had a stronger effect on occupancy in watersheds with more isolated headwater streams, while the catchment area, which is associated with gradients in stream habitat, had a stronger effect on occupancy in watersheds with more paired headwater streams. Our results show that considering the spatial structure of habitat networks can provide new insights on ONS in long-lived species.

  18. An Intelligent System For Effective Forest Fire Detection Using Spatial Data

    CERN Document Server

    Angayarkkani, K

    2010-01-01

    The explosive growth of spatial data and extensive utilization of spatial databases emphasize the necessity for the automated discovery of spatial knowledge. In modern times, spatial data mining has emerged as an area of voluminous research. Forest fires are a chief environmental concern, causing economical and ecological damage while endangering human lives across the world. The fast or early detection of forest fires is a vital element for controlling such phenomenon. The application of remote sensing is at present a significant method for forest fires monitoring, particularly in vast and remote areas. Different methods have been presented by researchers for forest fire detection. The motivation behind this research is to obtain beneficial information from images in the forest spatial data and use the same in the determination of regions at the risk of fires by utilizing Image Processing and Artificial Intelligence techniques. This paper presents an intelligent system to detect the presence of forest fires ...

  19. Enhancing spatial detection accuracy for syndromic surveillance with street level incidence data

    Directory of Open Access Journals (Sweden)

    Alemi Farrokh

    2010-01-01

    Full Text Available Abstract Background The Department of Defense Military Health System operates a syndromic surveillance system that monitors medical records at more than 450 non-combat Military Treatment Facilities (MTF worldwide. The Electronic Surveillance System for Early Notification of Community-based Epidemics (ESSENCE uses both temporal and spatial algorithms to detect disease outbreaks. This study focuses on spatial detection and attempts to improve the effectiveness of the ESSENCE implementation of the spatial scan statistic by increasing the spatial resolution of incidence data from zip codes to street address level. Methods Influenza-Like Illness (ILI was used as a test syndrome to develop methods to improve the spatial accuracy of detected alerts. Simulated incident clusters of various sizes were superimposed on real ILI incidents from the 2008/2009 influenza season. Clusters were detected using the spatial scan statistic and their displacement from simulated loci was measured. Detected cluster size distributions were also evaluated for compliance with simulated cluster sizes. Results Relative to the ESSENCE zip code based method, clusters detected using street level incidents were displaced on average 65% less for 2 and 5 mile radius clusters and 31% less for 10 mile radius clusters. Detected cluster size distributions for the street address method were quasi normal and sizes tended to slightly exceed simulated radii. ESSENCE methods yielded fragmented distributions and had high rates of zero radius and oversized clusters. Conclusions Spatial detection accuracy improved notably with regard to both location and size when incidents were geocoded to street addresses rather than zip code centroids. Since street address geocoding success rates were only 73.5%, zip codes were still used for more than one quarter of ILI cases. Thus, further advances in spatial detection accuracy are dependant on systematic improvements in the collection of individual

  20. Spatial Correlation Coefficient Images for Ultrasonic Detection (Preprint)

    Science.gov (United States)

    2006-07-01

    for image formation and detection based on the similarity of adjacent signals. Signal similarity is quantified in terms of the correlation coefficient calculated...between A-scans digitized at adjacent measurement positions. Correlation coefficient images are introduced for visualizing the similarity...beam field with the defect. Correlation coefficient and C-scan images are shown to demonstrate flat-bottom-hole detection in a stainless steel annular

  1. An Intelligent System For Effective Forest Fire Detection Using Spatial Data

    Directory of Open Access Journals (Sweden)

    K. Angayarkkani

    2010-01-01

    Full Text Available The explosive growth of spatial data and extensive utilization of spatial databases emphasize the necessity for the automated discovery of spatial knowledge. In modern times, spatial data mining has emerged as an area of voluminous research. Forest fires are a chief environmental concern, causing economical and ecological damage while endangering human lives across the world. The fast or early detection of forest fires is a vital element for controlling such phenomenon. The application of remote sensing is at present a significant method for forest fires monitoring, particularly in vast and remote areas. Different methods have been presented by researchers for forest fire detection. The motivation behind this research is to obtain beneficial information from images in the forest spatial data and use the same in the determination of regions at the risk of fires by utilizing Image Processing and Artificial Intelligence techniques. This paper presents an intelligent system to detect the presence of forest fires in the forest spatial data using Artificial Neural Networks. The digital images in the forest spatial data are converted from RGB to XYZ color space and then segmented by employing anisotropic diffusion to identify the fire regions. Subsequently, Radial Basis Function Neural Network is employed in the design of the intelligent system, which is trained with the color space values of the segmented fire regions. Extensive experimental assessments on publicly available spatial data illustrated the efficiency of the proposed system in effectively detecting forest fires.

  2. 一种基于空间规则度的谱图划分提取舰船编队方法%A Ship Team Extraction Method Using Spectral Graph Partitioning Based on Spatial Regularity

    Institute of Scientific and Technical Information of China (English)

    陈海亮; 雷琳; 周石琳

    2012-01-01

    Ship team is an important group target of ships which cruise and battle in the sea. Focusing on the complex problem of team form and order changing, this paper summarizes the spatial regularity existing in the ship team,and establishes the fuzzy reasoning rules based on it to find the spatial regularity quantitatively, then extracts the ship team which has high spatial regularity using spectral graph partitioning. Emulational and real data show that the algorithm can extract the group target which has a team form in the case of disturbance and the team spatial relationship changes.%舰船编队是海上舰船巡航和作战中的重要群目标.针对编队组成和队形变化的复杂情况,本文总结了编队存在的空问规则性,由此制定模糊推理规则得到定量的空间规则度,最后用谱图划分方法提取具有较高空间规则度的编队目标.仿真和实测的数据表明,该方法可以在有干扰和编队空间关系适当变化的情况下提取出具有编队形式的群目标.

  3. Detecting Hotspots from Taxi Trajectory Data Using Spatial Cluster Analysis

    Science.gov (United States)

    Zhao, P. X.; Qin, K.; Zhou, Q.; Liu, C. K.; Chen, Y. X.

    2015-07-01

    A method of trajectory clustering based on decision graph and data field is proposed in this paper. The method utilizes data field to describe spatial distribution of trajectory points, and uses decision graph to discover cluster centres. It can automatically determine cluster parameters and is suitable to trajectory clustering. The method is applied to trajectory clustering on taxi trajectory data, which are on the holiday (May 1st, 2014), weekday (Wednesday, May 7th, 2014) and weekend (Saturday, May 10th, 2014) respectively, in Wuhan City, China. The hotspots in four hours (8:00-9:00, 12:00-13:00, 18:00-19:00 and 23:00-24:00) for three days are discovered and visualized in heat maps. In the future, we will further research the spatiotemporal distribution and laws of these hotspots, and use more data to carry out the experiments.

  4. Improvement of BP-Based CDMA Multiuser Detection by Spatial Coupling

    CERN Document Server

    Takeuchi, Keigo; Kawabata, Tsutomu

    2011-01-01

    Kudekar et al. proved that the belief-propagation (BP) threshold for low-density parity-check (LDPC) codes can be boosted up to the maximum-a-posteriori (MAP) threshold by spatial coupling. In this paper, spatial coupling is applied to randomly-spread code-division multiple-access (CDMA) systems in order to improve the performance of BP-based multiuser detection (MUD). Spatially-coupled CDMA systems can be regarded as multi-code CDMA systems with two transmission phases. The large-system analysis shows that spatial coupling can improve the BP performance, while there is a gap between the BP performance and the optimal performance.

  5. Adaptive regularization

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Rasmussen, Carl Edward; Svarer, C.

    1994-01-01

    Regularization, e.g., in the form of weight decay, is important for training and optimization of neural network architectures. In this work the authors provide a tool based on asymptotic sampling theory, for iterative estimation of weight decay parameters. The basic idea is to do a gradient descent...... in the estimated generalization error with respect to the regularization parameters. The scheme is implemented in the authors' Designer Net framework for network training and pruning, i.e., is based on the diagonal Hessian approximation. The scheme does not require essential computational overhead in addition...... to what is needed for training and pruning. The viability of the approach is demonstrated in an experiment concerning prediction of the chaotic Mackey-Glass series. The authors find that the optimized weight decays are relatively large for densely connected networks in the initial pruning phase, while...

  6. Detecting abrupt dynamic change based on changes in the fractal properties of spatial images

    Science.gov (United States)

    Liu, Qunqun; He, Wenping; Gu, Bin; Jiang, Yundi

    2016-08-01

    Many abrupt climate change events often cannot be detected timely by conventional abrupt detection methods until a few years after these events have occurred. The reason for this lag in detection is that abundant and long-term observational data are required for accurate abrupt change detection by these methods, especially for the detection of a regime shift. So, these methods cannot help us understand and forecast the evolution of the climate system in a timely manner. Obviously, spatial images, generated by a coupled spatiotemporal dynamical model, contain more information about a dynamic system than a single time series, and we find that spatial images show the fractal properties. The fractal properties of spatial images can be quantitatively characterized by the Hurst exponent, which can be estimated by two-dimensional detrended fluctuation analysis (TD-DFA). Based on this, TD-DFA is used to detect an abrupt dynamic change of a coupled spatiotemporal model. The results show that the TD-DFA method can effectively detect abrupt parameter changes in the coupled model by monitoring the changing in the fractal properties of spatial images. The present method provides a new way for abrupt dynamic change detection, which can achieve timely and efficient abrupt change detection results.

  7. Multiscale spatial density smoothing: an application to large-scale radiological survey and anomaly detection

    CERN Document Server

    Tansey, Wesley; Reinhart, Alex; Scott, James G

    2015-01-01

    We consider the problem of estimating a spatially varying density function, motivated by problems that arise in large-scale radiological survey and anomaly detection. In this context, the density functions to be estimated are the background gamma-ray energy spectra at sites spread across a large geographical area, such as nuclear production and waste-storage sites, military bases, medical facilities, university campuses, or the downtown of a city. Several challenges combine to make this a difficult problem. First, the spectral density at any given spatial location may have both smooth and non-smooth features. Second, the spatial correlation in these density functions is neither stationary nor locally isotropic. Third, the spatial correlation decays at different length scales at different locations in the support of the underlying density. Finally, at some spatial locations, there is very little data. We present a method called multiscale spatial density smoothing that successfully addresses these challenges. ...

  8. Robust Detection of Impaired Resting State Functional Connectivity Networks in Alzheimer's Disease Using Elastic Net Regularized Regression

    Science.gov (United States)

    Teipel, Stefan J.; Grothe, Michel J.; Metzger, Coraline D.; Grimmer, Timo; Sorg, Christian; Ewers, Michael; Franzmeier, Nicolai; Meisenzahl, Eva; Klöppel, Stefan; Borchardt, Viola; Walter, Martin; Dyrba, Martin

    2017-01-01

    The large number of multicollinear regional features that are provided by resting state (rs) fMRI data requires robust feature selection to uncover consistent networks of functional disconnection in Alzheimer's disease (AD). Here, we compared elastic net regularized and classical stepwise logistic regression in respect to consistency of feature selection and diagnostic accuracy using rs-fMRI data from four centers of the “German resting-state initiative for diagnostic biomarkers” (psymri.org), comprising 53 AD patients and 118 age and sex matched healthy controls. Using all possible pairs of correlations between the time series of rs-fMRI signal from 84 functionally defined brain regions as the initial set of predictor variables, we calculated accuracy of group discrimination and consistency of feature selection with bootstrap cross-validation. Mean areas under the receiver operating characteristic curves as measure of diagnostic accuracy were 0.70 in unregularized and 0.80 in regularized regression. Elastic net regression was insensitive to scanner effects and recovered a consistent network of functional connectivity decline in AD that encompassed parts of the dorsal default mode as well as brain regions involved in attention, executive control, and language processing. Stepwise logistic regression found no consistent network of AD related functional connectivity decline. Regularized regression has high potential to increase diagnostic accuracy and consistency of feature selection from multicollinear functional neuroimaging data in AD. Our findings suggest an extended network of functional alterations in AD, but the diagnostic accuracy of rs-fMRI in this multicenter setting did not reach the benchmark defined for a useful biomarker of AD. PMID:28101051

  9. Object detection in natural scenes: Independent effects of spatial and category-based attention

    NARCIS (Netherlands)

    Stein, T.; Peelen, M.V.

    2017-01-01

    Humans are remarkably efficient in detecting highly familiar object categories in natural scenes, with evidence suggesting that such object detection can be performed in the (near) absence of attention. Here we systematically explored the influences of both spatial attention and category-based

  10. High-Speed Incoming Infrared Target Detection by Fusion of Spatial and Temporal Detectors

    Science.gov (United States)

    Kim, Sungho

    2015-01-01

    This paper presents a method for detecting high-speed incoming targets by the fusion of spatial and temporal detectors to achieve a high detection rate for an active protection system (APS). The incoming targets have different image velocities according to the target-camera geometry. Therefore, single-target detector-based approaches, such as a 1D temporal filter, 2D spatial filter and 3D matched filter, cannot provide a high detection rate with moderate false alarms. The target speed variation was analyzed according to the incoming angle and target velocity. The speed of the distant target at the firing time is almost stationary and increases slowly. The speed varying targets are detected stably by fusing the spatial and temporal filters. The stationary target detector is activated by an almost zero temporal contrast filter (TCF) and identifies targets using a spatial filter called the modified mean subtraction filter (M-MSF). A small motion (sub-pixel velocity) target detector is activated by a small TCF value and finds targets using the same spatial filter. A large motion (pixel-velocity) target detector works when the TCF value is high. The final target detection is terminated by fusing the three detectors based on the threat priority. The experimental results of the various target sequences show that the proposed fusion-based target detector produces the highest detection rate with an acceptable false alarm rate. PMID:25815448

  11. Towards spatial localisation of harmful algal blooms; statistics-based spatial anomaly detection

    Science.gov (United States)

    Shutler, J. D.; Grant, M. G.; Miller, P. I.

    2005-10-01

    Harmful algal blooms are believed to be increasing in occurrence and their toxins can be concentrated by filter-feeding shellfish and cause amnesia or paralysis when ingested. As a result fisheries and beaches in the vicinity of blooms may need to be closed and the local population informed. For this avoidance planning timely information on the existence of a bloom, its species and an accurate map of its extent would be prudent. Current research to detect these blooms from space has mainly concentrated on spectral approaches towards determining species. We present a novel statistics-based background-subtraction technique that produces improved descriptions of an anomaly's extent from remotely-sensed ocean colour data. This is achieved by extracting bulk information from a background model; this is complemented by a computer vision ramp filtering technique to specifically detect the perimeter of the anomaly. The complete extraction technique uses temporal-variance estimates which control the subtraction of the scene of interest from the time-weighted background estimate, producing confidence maps of anomaly extent. Through the variance estimates the method learns the associated noise present in the data sequence, providing robustness, and allowing generic application. Further, the use of the median for the background model reduces the effects of anomalies that appear within the time sequence used to generate it, allowing seasonal variations in the background levels to be closely followed. To illustrate the detection algorithm's application, it has been applied to two spectrally different oceanic regions.

  12. Robust Fusion of Multi-Band Images with Different Spatial and Spectral Resolutions for Change Detection

    CERN Document Server

    Ferraris, Vinicius; Wei, Qi; Chabert, Marie

    2016-01-01

    Archetypal scenarios for change detection generally consider two images acquired through sensors of the same modality. However, in some specific cases such as emergency situations, the only images available may be those acquired through different kinds of sensors. More precisely, this paper addresses the problem of detecting changes between two multi-band optical images characterized by different spatial and spectral resolutions. This sensor dissimilarity introduces additional issues in the context of operational change detection. To alleviate these issues, classical change detection methods are applied after independent preprocessing steps (e.g., resampling) used to get the same spatial and spectral resolutions for the pair of observed images. Nevertheless, these preprocessing steps tend to throw away relevant information. Conversely, in this paper, we propose a method that more effectively uses the available information by modeling the two observed images as spatial and spectral versions of two (unobserved)...

  13. Unsupervised spatial event detection in targeted domains with applications to civil unrest modeling.

    Directory of Open Access Journals (Sweden)

    Liang Zhao

    Full Text Available Twitter has become a popular data source as a surrogate for monitoring and detecting events. Targeted domains such as crime, election, and social unrest require the creation of algorithms capable of detecting events pertinent to these domains. Due to the unstructured language, short-length messages, dynamics, and heterogeneity typical of Twitter data streams, it is technically difficult and labor-intensive to develop and maintain supervised learning systems. We present a novel unsupervised approach for detecting spatial events in targeted domains and illustrate this approach using one specific domain, viz. civil unrest modeling. Given a targeted domain, we propose a dynamic query expansion algorithm to iteratively expand domain-related terms, and generate a tweet homogeneous graph. An anomaly identification method is utilized to detect spatial events over this graph by jointly maximizing local modularity and spatial scan statistics. Extensive experiments conducted in 10 Latin American countries demonstrate the effectiveness of the proposed approach.

  14. Regular polytopes

    CERN Document Server

    Coxeter, H S M

    1973-01-01

    Polytopes are geometrical figures bounded by portions of lines, planes, or hyperplanes. In plane (two dimensional) geometry, they are known as polygons and comprise such figures as triangles, squares, pentagons, etc. In solid (three dimensional) geometry they are known as polyhedra and include such figures as tetrahedra (a type of pyramid), cubes, icosahedra, and many more; the possibilities, in fact, are infinite! H. S. M. Coxeter's book is the foremost book available on regular polyhedra, incorporating not only the ancient Greek work on the subject, but also the vast amount of information

  15. Spatial biomarker of disease and detection of spatial organization of cellular receptors

    Energy Technology Data Exchange (ETDEWEB)

    Salaita, Khalid S.; Nair, Pradeep M.; Das, Debopriya; Gray, Joe W.; Groves, John T.

    2017-07-18

    A signature of a condition of a live cell is established in an assay that allows distribution of the receptors on the cell surface in response to binding a ligand. The receptors can be optically detected and quantified to provide a value for the condition, Test drugs can be screened for therapeutic potential in the assay: a potentially efficacious drug is identified by an ability to modulate an established signature. The receptor distribution signature can be corroborated with an mRNA expression profile of several genes, indicating, for example, metastasis.

  16. Detection of Aβ-interacting proteins via a novel Aβ-adsorbents that use immobilized regular comb polymer.

    Science.gov (United States)

    Xu, Li; Wang, Conggang; Chen, Linli; Ren, Jun; Xie, Jian; Jia, Lingyun

    2014-11-15

    A detailed study of individual Aβ-interacting proteins has always been a difficult task because Aβ has a wide range of molecular weights and can easily form aggregates. In this study, we established a novel method for isolating Aβ-interacting proteins by utilizing regular comb polymer immobilized on Sepharose CL-4B. To achieve site-directed ligation of Aβ, a cysteine residue was added at the N-terminus of Aβ. Asp and Asp12, which have 2 and 13 carboxyl groups, respectively, were selected as the carriers for the regular comb polymer. Firstly, the N-termini of Asp and Asp12 were immobilized on Sepharose CL-4B. Next, modified Aβ molecules were coupled to the carboxyl groups of Asp and Asp12 using bromoethylamine as a spacer. To obtain homogeneous comb polymer, the efficiency of the reaction was controlled during the synthesis process. Thioflavin T staining indicated that homogeneous Aβ was achieved. The prepared Aβ-adsorbents were used to isolate Aβ-interacting proteins from mice brain extracts. The results showed that the adsorption capacity of the Aβ-adsorbents for proteins in mice brain extracts increased with the ages of the animals. SDS-PAGE analysis of the Aβ-interacting proteins showed that many kinds of brain proteins were selectively adsorbed by the Aβ adsorbents, and the levels of some of these proteins varied with the ages of the animals. The results indicated that Aβ-interacting proteins could be successfully obtained through the use of immobilized comb polymer. Similar method could also be used to isolate other amyloid-interacting proteins.

  17. Research on Ultrasonic Flaw Detection of Steel Weld in Spatial Grid Structure

    Science.gov (United States)

    Du, Tao; Sun, Jiandong; Fu, Shengguang; Zhang, Changquan; Gao, Qing

    2017-06-01

    The welding quality of spatial grid member is an important link in quality control of steel structure. The paper analyzed the reasons that the welding seam of small-bore pipe with thin wall grid structure is difficult to be detected by ultrasonic wave from the theoretical and practical aspects. A series of feasible detection methods was also proposed by improving probe and operation approaches in this paper, and the detection methods were verified by project cases. Over the years, the spatial grid structure is widely used the engineering by virtue of its several outstanding characteristics such as reasonable structure type, standard member, excellent space integrity and quick installation. The wide application of spatial grid structure brings higher requirements on nondestructive test of grid structure. The implementation of new Code for Construction Quality Acceptance of Steel Structure Work GB50205-2001 strengthens the site inspection of steel structure, especially the site inspection of ultrasonic flaw detection in steel weld. The detection for spatial grid member structured by small-bore and thin-walled pipes is difficult due to the irregular influence of sound pressure in near-field region of sound field, sound beam diffusion generated by small bore pipe and reduction of sensitivity. Therefore, it is quite significant to select correct detecting conditions. The spatial grid structure of welding ball and bolt ball is statically determinate structure with high-order axial force which is connected by member bars and joints. It is welded by shrouding or conehead of member bars and of member bar and bolt-node sphere. It is obvious that to ensure the quality of these welding positions is critical to the quality of overall grid structure. However, the complexity of weld structure and limitation of ultrasonic detection method cause many difficulties in detection. No satisfactory results will be obtained by the conventional detection technology, so some special

  18. Selective spatial localization of the atom displacements in one-dimensional hybrid quasi-regular (Thue Morse and Rudin Shapiro)/periodic structures

    Science.gov (United States)

    Montalbán, A.; Velasco, V. R.; Tutor, J.; Fernández-Velicia, F. J.

    2007-06-01

    We have studied the vibrational frequencies and atom displacements of one-dimensional systems formed by combinations of Thue-Morse and Rudin-Shapiro quasi-regular stackings with periodic ones. The materials are described by nearest-neighbor force constants and the corresponding atom masses. These systems exhibit differences in the frequency spectrum as compared to the original simple quasi-regular generations and periodic structures. The most important feature is the presence of separate confinement of the atom displacements in one of the parts forming the total composite structure for different frequency ranges, thus acting as a kind of phononic cavity.

  19. Detection of the support damage of spatial steel structures under earthquakes based on shaking table test

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    There are always some local damages in spatial steel structures induced by strong earthquakes, such as welding cracks of steel nodes,anchor loose of supports etc.If these local damages of spatial steel structures occur,there will be serious dangers to the structural safety.In order to detect the position of local damage under earthquake quickly and accurately,the method of support damage diagnosis of spatial steel structures under earthquakes is studied by using wavelet packet decomposition,data fusion a...

  20. Detecting Changes Between Optical Images of Different Spatial and Spectral Resolutions: a Fusion-Based Approach

    CERN Document Server

    Ferraris, Vinicius; Wei, Qi; Chabert, Marie

    2016-01-01

    Change detection is one of the most challenging issues when analyzing remotely sensed images. Comparing several multi-date images acquired through the same kind of sensor is the most common scenario. Conversely, designing robust, flexible and scalable algorithms for change detection becomes even more challenging when the images have been acquired by two different kinds of sensors. This situation arises in case of emergency under critical constraints. This paper presents, to the best of authors' knowledge, the first strategy to deal with optical images characterized by dissimilar spatial and spectral resolutions. Typical considered scenarios include change detection between panchromatic or multispectral and hyperspectral images. The proposed strategy consists of a 3-step procedure: i) inferring a high spatial and spectral resolution image by fusion of the two observed images characterized one by a low spatial resolution and the other by a low spectral resolution, ii) predicting two images with respectively the...

  1. Detecting spatial-temporal clusters of HFMD from 2007 to 2011 in Shandong Province, China.

    Directory of Open Access Journals (Sweden)

    Yunxia Liu

    Full Text Available BACKGROUND: Hand, foot, and mouth disease (HFMD has caused major public health concerns worldwide, and has become one of the leading causes of children death. China is the most serious epidemic area with a total of 3,419,149 reported cases just from 2008 to 2010, and its different geographic areas might have different spatial epidemiology characteristics at different spatial-temporal scale levels. We conducted spatial and spatial-temporal epidemiology analysis to HFMD at county level in Shandong Province, China. METHODS: Based on the China National Disease Surveillance Reporting and Management System, the spatial-temporal database of HFMD from 2007 to 2011 was built. The global autocorrelation statistic (Moran's I was first used to detect the spatial autocorrelation of HFMD cases in each year. Purely Spatial scan statistics combined with Space-time scan statistic were used to detect epidemic clusters. RESULTS: The annual average incidence rate was 93.70 per 100,000 in Shandong Province. Most HFMD cases (93.94% were aged within 0-5 years old with an average male-to-female sex ratio 1.71, and the incidence seasonal peak was between April and July. The dominant pathogen was EV71 (47.35%, and CoxA16 (26.59%. HFMD had positive spatial autocorrelation at medium spatial scale level (county level with higher Moran's I from 0.31 to 0.62 (P<0.001. Seven spatial-temporal clusters were detected from 2007 to 2011 in the landscape of the whole Shandong, with EV71 or CoxA16 as the dominant pathogen for most hotspots areas. CONCLUSIONS: The spatial-temporal clusters of HFMD wandered around the whole Shandong Province during 2007 to 2011, with EV71 or CoxA16 as the dominant pathogen. These findings suggested that a real-time spatial-temporal surveillance system should be established for identifying high incidence region and conducting prevention to HFMD timely.

  2. Detection efficiency, spatial and timing resolution of thermal and cold neutron counting MCP detectors

    Science.gov (United States)

    Tremsin, A. S.; McPhate, J. B.; Vallerga, J. V.; Siegmund, O. H. W.; Hull, J. S.; Feller, W. B.; Lehmann, E.

    2009-06-01

    Neutron counting detectors with boron or gadolinium doped microchannel plates (MCPs) have very high detection efficiency, spatial and temporal resolution, and have a very low readout noise. In this paper we present the results of both theoretical predictions and experimental evaluations of detection efficiency and spatial resolution measured at cold and thermal neutron beamlines. The quantum detection efficiency of a detector (not fully optimized) was measured to be 43% and 16% for the cold and thermal beamlines, respectively. The experiments also demonstrate that the spatial resolution can be better than 15 μm—highest achievable with the particular MCP pore dimension used in the experiment, although more electronics development is required in order to increase the counting rate capabilities of those <15 μm resolution devices. The timing accuracy of neutron detection is on the scale of few μs and is limited by the neutron absorption depth in the detector. The good agreement between the predicted and measured performance allows the optimization of the detector parameters in order to achieve the highest spatial resolution and detection efficiency in future devices.

  3. Regularized Reduced Order Models

    CERN Document Server

    Wells, David; Xie, Xuping; Iliescu, Traian

    2015-01-01

    This paper puts forth a regularization approach for the stabilization of proper orthogonal decomposition (POD) reduced order models (ROMs) for the numerical simulation of realistic flows. Two regularized ROMs (Reg-ROMs) are proposed: the Leray ROM (L-ROM) and the evolve-then-filter ROM (EF-ROM). These new Reg-ROMs use spatial filtering to smooth (regularize) various terms in the ROMs. Two spatial filters are used: a POD projection onto a POD subspace (Proj) and a new POD differential filter (DF). The four Reg-ROM/filter combinations are tested in the numerical simulation of the one-dimensional Burgers equation with a small diffusion coefficient and the three-dimensional flow past a circular cylinder at a low Reynolds number (Re = 100). Overall, the most accurate Reg-ROM/filter combination is EF-ROM-DF. Furthermore, the DF generally yields better results than Proj. Finally, the four Reg-ROM/filter combinations are computationally efficient and generally more accurate than the standard Galerkin ROM.

  4. Web-based GIS for spatial pattern detection: application to malaria incidence in Vietnam.

    Science.gov (United States)

    Bui, Thanh Quang; Pham, Hai Minh

    2016-01-01

    There is a great concern on how to build up an interoperable health information system of public health and health information technology within the development of public information and health surveillance programme. Technically, some major issues remain regarding to health data visualization, spatial processing of health data, health information dissemination, data sharing and the access of local communities to health information. In combination with GIS, we propose a technical framework for web-based health data visualization and spatial analysis. Data was collected from open map-servers and geocoded by open data kit package and data geocoding tools. The Web-based system is designed based on Open-source frameworks and libraries. The system provides Web-based analyst tool for pattern detection through three spatial tests: Nearest neighbour, K function, and Spatial Autocorrelation. The result is a web-based GIS, through which end users can detect disease patterns via selecting area, spatial test parameters and contribute to managers and decision makers. The end users can be health practitioners, educators, local communities, health sector authorities and decision makers. This web-based system allows for the improvement of health related services to public sector users as well as citizens in a secure manner. The combination of spatial statistics and web-based GIS can be a solution that helps empower health practitioners in direct and specific intersectional actions, thus provide for better analysis, control and decision-making.

  5. Real time spatial cluster detection using interpoint distances among precise patient locations

    Directory of Open Access Journals (Sweden)

    Bonetti Marco

    2005-06-01

    Full Text Available Abstract Background Public health departments in the United States are beginning to gain timely access to health data, often as soon as one day after a visit to a health care facility. Consequently, new approaches to outbreak surveillance are being developed. When cases cluster geographically, an analysis of their spatial distribution can facilitate outbreak detection. Our method focuses on detecting perturbations in the distribution of pair-wise distances among all patients in a geographical region. Barring outbreaks, this distribution can be quite stable over time. We sought to exemplify the method by measuring its cluster detection performance, and to determine factors affecting sensitivity to spatial clustering among patients presenting to hospital emergency departments with respiratory syndromes. Methods The approach was to (1 define a baseline spatial distribution of home addresses for a population of patients visiting an emergency department with respiratory syndromes using historical data; (2 develop a controlled feature set simulation by inserting simulated outbreak data with varied parameters into authentic background noise, thereby creating semisynthetic data; (3 compare the observed with the expected spatial distribution; (4 establish the relative value of different alarm strategies so as to maximize sensitivity for the detection of clustering; and (5 measure factors which have an impact on sensitivity. Results Overall sensitivity to detect spatial clustering was 62%. This contrasts with an overall alarm rate of less than 5% for the same number of extra visits when the extra visits were not characterized by geographic clustering. Clusters that produced the least number of alarms were those that were small in size (10 extra visits in a week, where visits per week ranged from 120 to 472, diffusely distributed over an area with a 3 km radius, and located close to the hospital (5 km in a region most densely populated with patients to

  6. Optimal detection of a change-set in a spatial Poisson process

    CERN Document Server

    Ivanoff, B Gail; 10.1214/09-AAP629

    2010-01-01

    We generalize the classic change-point problem to a "change-set" framework: a spatial Poisson process changes its intensity on an unobservable random set. Optimal detection of the set is defined by maximizing the expected value of a gain function. In the case that the unknown change-set is defined by a locally finite set of incomparable points, we present a sufficient condition for optimal detection of the set using multiparameter martingale techniques. Two examples are discussed.

  7. Landscape relatedness: detecting contemporary fine-scale spatial structure in wild populations

    DEFF Research Database (Denmark)

    Norman, Anita J; Strønen, Astrid Vik; Fuglstad, Geir-Arne

    2017-01-01

    Context Methods for detecting contemporary, fine-scale population genetic structure in continuous populations are scarce. Yet such methods are vital for ecological and conservation studies, particularly under a changing landscape. Objectives Here we present a novel, spatially explicit method...... that we call landscape relatedness (LandRel). With this method, we aim to detect contemporary, fine-scale population structure that is sensitive to spatial and temporal changes in the landscape. Methods We interpolate spatially determined relatedness values based on SNP genotypes across the landscape...... population. Further analysis suggests that inbreeding has occurred in at least one of these areas. Conclusions LandRel enabled us to identify previously unknown fine-scale structuring in the population. These results will help direct future research efforts, conservation action and aid in the management...

  8. Tools for Multimode Quantum Information: Modulation, Detection, and Spatial Quantum Correlations

    DEFF Research Database (Denmark)

    Lassen, Mikael Østergaard; Delaubert, Vincent; Janousek, Jirí

    2007-01-01

    We present here all the tools required for continuous variable parallel quantum information protocols based on spatial multi-mode quantum correlations and entanglement. We describe techniques for encoding and detecting this quantum information with high efficiency in the individual modes. We use ...

  9. Spatial Spectroscopy Approach for Detection of Internal Defect of Component without Zero-Position Sensors

    Directory of Open Access Journals (Sweden)

    Qizhou Wu

    2016-01-01

    Full Text Available Conventional approach to detect the internal defect of a component needs sensors to mark the “zero” positions, which is time-consuming and lowers down the detecting efficiency. In this study, we proposed a novelty approach that uses spatial spectroscopy to detect internal defect of objects without zero-position sensors. Specifically, the spatial variation wave of distance between the detecting source and object surface is analyzed, from which a periodical cycle is determined with the correlative approaches. Additionally, a wavelet method is adopted to reduce the noise of the periodic distance signal. This approach is validated by the ultrasound detection of a component with round cross section and elliptical shape in axis. The experimental results demonstrate that this approach greatly saves the time spent on the judgment of a complete cycle and improves the detecting efficiency of internal defect in the component. The approach can be expanded to other physical methods for noninvasive detection of internal defect, such as optical spectroscopy or X-ray scanning, and it can be used for hybrid medium, such as biological tissues.

  10. The effects of spatially heterogeneous prey distributions on detection patterns in foraging seabirds.

    Directory of Open Access Journals (Sweden)

    Octavio Miramontes

    Full Text Available Many attempts to relate animal foraging patterns to landscape heterogeneity are focused on the analysis of foragers movements. Resource detection patterns in space and time are not commonly studied, yet they are tightly coupled to landscape properties and add relevant information on foraging behavior. By exploring simple foraging models in unpredictable environments we show that the distribution of intervals between detected prey (detection statistics is mostly determined by the spatial structure of the prey field and essentially distinct from predator displacement statistics. Detections are expected to be Poissonian in uniform random environments for markedly different foraging movements (e.g. Lévy and ballistic. This prediction is supported by data on the time intervals between diving events on short-range foraging seabirds such as the thick-billed murre (Uria lomvia. However, Poissonian detection statistics is not observed in long-range seabirds such as the wandering albatross (Diomedea exulans due to the fractal nature of the prey field, covering a wide range of spatial scales. For this scenario, models of fractal prey fields induce non-Poissonian patterns of detection in good agreement with two albatross data sets. We find that the specific shape of the distribution of time intervals between prey detection is mainly driven by meso and submeso-scale landscape structures and depends little on the forager strategy or behavioral responses.

  11. Estimating babassu palm density using automatic palm tree detection with very high spatial resolution satellite images.

    Science.gov (United States)

    Dos Santos, Alessio Moreira; Mitja, Danielle; Delaître, Eric; Demagistri, Laurent; de Souza Miranda, Izildinha; Libourel, Thérèse; Petit, Michel

    2017-05-15

    High spatial resolution images as well as image processing and object detection algorithms are recent technologies that aid the study of biodiversity and commercial plantations of forest species. This paper seeks to contribute knowledge regarding the use of these technologies by studying randomly dispersed native palm tree. Here, we analyze the automatic detection of large circular crown (LCC) palm tree using a high spatial resolution panchromatic GeoEye image (0.50 m) taken on the area of a community of small agricultural farms in the Brazilian Amazon. We also propose auxiliary methods to estimate the density of the LCC palm tree Attalea speciosa (babassu) based on the detection results. We used the "Compt-palm" algorithm based on the detection of palm tree shadows in open areas via mathematical morphology techniques and the spatial information was validated using field methods (i.e. structural census and georeferencing). The algorithm recognized individuals in life stages 5 and 6, and the extraction percentage, branching factor and quality percentage factors were used to evaluate its performance. A principal components analysis showed that the structure of the studied species differs from other species. Approximately 96% of the babassu individuals in stage 6 were detected. These individuals had significantly smaller stipes than the undetected ones. In turn, 60% of the stage 5 babassu individuals were detected, showing significantly a different total height and a different number of leaves from the undetected ones. Our calculations regarding resource availability indicate that 6870 ha contained 25,015 adult babassu palm tree, with an annual potential productivity of 27.4 t of almond oil. The detection of LCC palm tree and the implementation of auxiliary field methods to estimate babassu density is an important first step to monitor this industry resource that is extremely important to the Brazilian economy and thousands of families over a large scale.

  12. Early non-destructive biofouling detection and spatial distribution: Application of oxygen sensing optodes

    KAUST Repository

    Farhat, N.M.

    2015-06-11

    Biofouling is a serious problem in reverse osmosis/nanofiltration (RO/NF) applications, reducing membrane performance. Early detection of biofouling plays an essential role in an adequate anti-biofouling strategy. Presently, fouling of membrane filtration systems is mainly determined by measuring changes in pressure drop, which is not exclusively linked to biofouling. Non-destructive imaging of oxygen concentrations (i) is specific for biological activity of biofilms and (ii) may enable earlier detection of biofilm accumulation than pressure drop. The objective of this study was to test whether transparent luminescent planar O2 optodes, in combination with a simple imaging system, can be used for early non-destructive biofouling detection. This biofouling detection is done by mapping the two-dimensional distribution of O2 concentrations and O2 decrease rates inside a membrane fouling simulator (MFS). Results show that at an early stage, biofouling development was detected by the oxygen sensing optodes while no significant increase in pressure drop was yet observed. Additionally, optodes could detect spatial heterogeneities in biofouling distribution at a micro scale. Biofilm development started mainly at the feed spacer crossings. The spatial and quantitative information on biological activity will lead to better understanding of the biofouling processes, contributing to the development of more effective biofouling control strategies.

  13. Early non-destructive biofouling detection and spatial distribution: Application of oxygen sensing optodes.

    Science.gov (United States)

    Farhat, N M; Staal, M; Siddiqui, A; Borisov, S M; Bucs, Sz S; Vrouwenvelder, J S

    2015-10-15

    Biofouling is a serious problem in reverse osmosis/nanofiltration (RO/NF) applications, reducing membrane performance. Early detection of biofouling plays an essential role in an adequate anti-biofouling strategy. Presently, fouling of membrane filtration systems is mainly determined by measuring changes in pressure drop, which is not exclusively linked to biofouling. Non-destructive imaging of oxygen concentrations (i) is specific for biological activity of biofilms and (ii) may enable earlier detection of biofilm accumulation than pressure drop. The objective of this study was to test whether transparent luminescent planar O2 optodes, in combination with a simple imaging system, can be used for early non-destructive biofouling detection. This biofouling detection is done by mapping the two-dimensional distribution of O2 concentrations and O2 decrease rates inside a membrane fouling simulator (MFS). Results show that at an early stage, biofouling development was detected by the oxygen sensing optodes while no significant increase in pressure drop was yet observed. Additionally, optodes could detect spatial heterogeneities in biofouling distribution at a micro scale. Biofilm development started mainly at the feed spacer crossings. The spatial and quantitative information on biological activity will lead to better understanding of the biofouling processes, contributing to the development of more effective biofouling control strategies.

  14. Regularization design for high-quality cone-beam CT of intracranial hemorrhage using statistical reconstruction

    Science.gov (United States)

    Dang, H.; Stayman, J. W.; Xu, J.; Sisniega, A.; Zbijewski, W.; Wang, X.; Foos, D. H.; Aygun, N.; Koliatsos, V. E.; Siewerdsen, J. H.

    2016-03-01

    Intracranial hemorrhage (ICH) is associated with pathologies such as hemorrhagic stroke and traumatic brain injury. Multi-detector CT is the current front-line imaging modality for detecting ICH (fresh blood contrast 40-80 HU, down to 1 mm). Flat-panel detector (FPD) cone-beam CT (CBCT) offers a potential alternative with a smaller scanner footprint, greater portability, and lower cost potentially well suited to deployment at the point of care outside standard diagnostic radiology and emergency room settings. Previous studies have suggested reliable detection of ICH down to 3 mm in CBCT using high-fidelity artifact correction and penalized weighted least-squared (PWLS) image reconstruction with a post-artifact-correction noise model. However, ICH reconstructed by traditional image regularization exhibits nonuniform spatial resolution and noise due to interaction between the statistical weights and regularization, which potentially degrades the detectability of ICH. In this work, we propose three regularization methods designed to overcome these challenges. The first two compute spatially varying certainty for uniform spatial resolution and noise, respectively. The third computes spatially varying regularization strength to achieve uniform "detectability," combining both spatial resolution and noise in a manner analogous to a delta-function detection task. Experiments were conducted on a CBCT test-bench, and image quality was evaluated for simulated ICH in different regions of an anthropomorphic head. The first two methods improved the uniformity in spatial resolution and noise compared to traditional regularization. The third exhibited the highest uniformity in detectability among all methods and best overall image quality. The proposed regularization provides a valuable means to achieve uniform image quality in CBCT of ICH and is being incorporated in a CBCT prototype for ICH imaging.

  15. Breast cancer mitosis detection in histopathological images with spatial feature extraction

    Science.gov (United States)

    Albayrak, Abdülkadir; Bilgin, Gökhan

    2013-12-01

    In this work, cellular mitosis detection in histopathological images has been investigated. Mitosis detection is very expensive and time consuming process. Development of digital imaging in pathology has enabled reasonable and effective solution to this problem. Segmentation of digital images provides easier analysis of cell structures in histopathological data. To differentiate normal and mitotic cells in histopathological images, feature extraction step is very crucial step for the system accuracy. A mitotic cell has more distinctive textural dissimilarities than the other normal cells. Hence, it is important to incorporate spatial information in feature extraction or in post-processing steps. As a main part of this study, Haralick texture descriptor has been proposed with different spatial window sizes in RGB and La*b* color spaces. So, spatial dependencies of normal and mitotic cellular pixels can be evaluated within different pixel neighborhoods. Extracted features are compared with various sample sizes by Support Vector Machines using k-fold cross validation method. According to the represented results, it has been shown that separation accuracy on mitotic and non-mitotic cellular pixels gets better with the increasing size of spatial window.

  16. Detection Performance of Polarization and Spatial Diversities for Indoor GNSS Applications

    Directory of Open Access Journals (Sweden)

    Mohammadreza Zaheri

    2012-01-01

    Full Text Available Multipath fading in the form of signal power fluctuation poses a formidable challenge to GNSS signal detection in harsh multipath environments such as indoors. Antenna diversity techniques such as polarization and spatial diversities can be used to combat multipath fading in wireless propagation channels. This paper studies and compares GPS signal detection performance enhancements arising from the spatial and polarization diversity techniques. Performance enhancements are quantified from a theoretical perspective and later verified based on several test measurements in various indoor environments. Enhancement is quantified based on measuring the correlation coefficient values between diversity branches, SNR levels, and computing the level crossing rate and average fade duration. In addition, the processing gain is quantified and the performance of each individual diversity system is evaluated. Experimental results show that, for a given target detection performance in terms of the probability of false alarm and the probability of detection, the required input SNR level to meet the target detection performance can be significantly reduced utilizing the diversity system.

  17. A Spatially Offset Raman Spectroscopy Method for Non-Destructive Detection of Gelatin-Encapsulated Powders

    Science.gov (United States)

    Chao, Kuanglin; Dhakal, Sagar; Qin, Jianwei; Peng, Yankun; Schmidt, Walter F.; Kim, Moon S.; Chan, Diane E.

    2017-01-01

    Non-destructive subsurface detection of encapsulated, coated, or seal-packaged foods and pharmaceuticals can help prevent distribution and consumption of counterfeit or hazardous products. This study used a Spatially Offset Raman Spectroscopy (SORS) method to detect and identify urea, ibuprofen, and acetaminophen powders contained within one or more (up to eight) layers of gelatin capsules to demonstrate subsurface chemical detection and identification. A 785-nm point-scan Raman spectroscopy system was used to acquire spatially offset Raman spectra for an offset range of 0 to 10 mm from the surfaces of 24 encapsulated samples, using a step size of 0.1 mm to obtain 101 spectral measurements per sample. As the offset distance was increased, the spectral contribution from the subsurface powder gradually outweighed that of the surface capsule layers, allowing for detection of the encapsulated powders. Containing mixed contributions from the powder and capsule, the SORS spectra for each sample were resolved into pure component spectra using self-modeling mixture analysis (SMA) and the corresponding components were identified using spectral information divergence values. As demonstrated here for detecting chemicals contained inside thick capsule layers, this SORS measurement technique coupled with SMA has the potential to be a reliable non-destructive method for subsurface inspection and authentication of foods, health supplements, and pharmaceutical products that are prepared or packaged with semi-transparent materials. PMID:28335453

  18. A Spatially Offset Raman Spectroscopy Method for Non-Destructive Detection of Gelatin-Encapsulated Powders

    Directory of Open Access Journals (Sweden)

    Kuanglin Chao

    2017-03-01

    Full Text Available Non-destructive subsurface detection of encapsulated, coated, or seal-packaged foods and pharmaceuticals can help prevent distribution and consumption of counterfeit or hazardous products. This study used a Spatially Offset Raman Spectroscopy (SORS method to detect and identify urea, ibuprofen, and acetaminophen powders contained within one or more (up to eight layers of gelatin capsules to demonstrate subsurface chemical detection and identification. A 785-nm point-scan Raman spectroscopy system was used to acquire spatially offset Raman spectra for an offset range of 0 to 10 mm from the surfaces of 24 encapsulated samples, using a step size of 0.1 mm to obtain 101 spectral measurements per sample. As the offset distance was increased, the spectral contribution from the subsurface powder gradually outweighed that of the surface capsule layers, allowing for detection of the encapsulated powders. Containing mixed contributions from the powder and capsule, the SORS spectra for each sample were resolved into pure component spectra using self-modeling mixture analysis (SMA and the corresponding components were identified using spectral information divergence values. As demonstrated here for detecting chemicals contained inside thick capsule layers, this SORS measurement technique coupled with SMA has the potential to be a reliable non-destructive method for subsurface inspection and authentication of foods, health supplements, and pharmaceutical products that are prepared or packaged with semi-transparent materials.

  19. A Spatially Offset Raman Spectroscopy Method for Non-Destructive Detection of Gelatin-Encapsulated Powders.

    Science.gov (United States)

    Chao, Kuanglin; Dhakal, Sagar; Qin, Jianwei; Peng, Yankun; Schmidt, Walter F; Kim, Moon S; Chan, Diane E

    2017-03-18

    Non-destructive subsurface detection of encapsulated, coated, or seal-packaged foods and pharmaceuticals can help prevent distribution and consumption of counterfeit or hazardous products. This study used a Spatially Offset Raman Spectroscopy (SORS) method to detect and identify urea, ibuprofen, and acetaminophen powders contained within one or more (up to eight) layers of gelatin capsules to demonstrate subsurface chemical detection and identification. A 785-nm point-scan Raman spectroscopy system was used to acquire spatially offset Raman spectra for an offset range of 0 to 10 mm from the surfaces of 24 encapsulated samples, using a step size of 0.1 mm to obtain 101 spectral measurements per sample. As the offset distance was increased, the spectral contribution from the subsurface powder gradually outweighed that of the surface capsule layers, allowing for detection of the encapsulated powders. Containing mixed contributions from the powder and capsule, the SORS spectra for each sample were resolved into pure component spectra using self-modeling mixture analysis (SMA) and the corresponding components were identified using spectral information divergence values. As demonstrated here for detecting chemicals contained inside thick capsule layers, this SORS measurement technique coupled with SMA has the potential to be a reliable non-destructive method for subsurface inspection and authentication of foods, health supplements, and pharmaceutical products that are prepared or packaged with semi-transparent materials.

  20. Detection and identification of spatial offset: double-judgment psychophysics revisited.

    Science.gov (United States)

    Allik, Jüri; Toom, Mai; Rauk, Marika

    2014-11-01

    In a bull's-eye acuity task, we asked observers to identify in which direction, to the left or the right, a spot had been displaced from the center of a circle and-after that, in the same trial-to detect which of the two presented circles contained the displaced spot. Replicating our previous findings (Allik, Dzhafarov, & Rauk, 1982), the spatial offset direction identification probability was higher than the probability with which the correct observation interval could be detected. All data were explained by a Thurstonian model, according to which the spatial positions of both spots are projected onto an internal axis of representation as two random numbers, x and y, drawn from a random distribution with a fixed standard deviation ς (final sigma). The observed identification and detection probabilities were accurately reproduced, provided that the observer tested two different inequalities: x + y > 0 for the identification, and x (2) - y (2) > 0 for the detection. In order to eliminate small discrepancies between the predicted and the observed data, we proposed that the positional error increases with increasing distance from the center of the annulus. It was concluded that, to explain the superiority of the identification over the detection effect, there is no need to propose separate axes of representation for mono- and bipolar information, as is usually postulated in double-judgment psychophysics.

  1. Simultaneous and spatially separated detection of multiple orbital angular momentum states

    Science.gov (United States)

    Tudor, R.; Mihailescu, M.; Kusko, C.; Paun, I. A.; Nan, A. E.; Kusko, M.

    2016-06-01

    We present a method for spatially separated detection of multiple orbital angular momentum (OAM) states, simultaneous. The starting point is the generation of axially superposed Laguerre-Gauss beams, carrying multiple OAM states using a single computer generated hologram. The information contained in the OAM superposition is transferred to the first diffraction order and is detected at the receiver with a reading mask, which contains two perpendicular superposed fork-like holograms, ensuring the spatial separation of the OAM states. The dynamic of the process is studied in terms of the number of generated OAM states and the constructive parameters values. The experimental investigations use an optical arrangement based on a spatial light modulator in the transmitter unit and an amplitude mask in the receiver unit. This proof of concept experiment demonstrates the possibility of simultaneously detection of multiple OAM states in points located at different coordinates, controlled through the design of the holograms and shows the capability of our proposed method to increase the capacity of free-space optical communication channels.

  2. Integrating landscape genomics and spatially explicit approaches to detect loci under selection in clinal populations.

    Science.gov (United States)

    Jones, Matthew R; Forester, Brenna R; Teufel, Ashley I; Adams, Rachael V; Anstett, Daniel N; Goodrich, Betsy A; Landguth, Erin L; Joost, Stéphane; Manel, Stéphanie

    2013-12-01

    Uncovering the genetic basis of adaptation hinges on the ability to detect loci under selection. However, population genomics outlier approaches to detect selected loci may be inappropriate for clinal populations or those with unclear population structure because they require that individuals be clustered into populations. An alternate approach, landscape genomics, uses individual-based approaches to detect loci under selection and reveal potential environmental drivers of selection. We tested four landscape genomics methods on a simulated clinal population to determine their effectiveness at identifying a locus under varying selection strengths along an environmental gradient. We found all methods produced very low type I error rates across all selection strengths, but elevated type II error rates under "weak" selection. We then applied these methods to an AFLP genome scan of an alpine plant, Campanula barbata, and identified five highly supported candidate loci associated with precipitation variables. These loci also showed spatial autocorrelation and cline patterns indicative of selection along a precipitation gradient. Our results suggest that landscape genomics in combination with other spatial analyses provides a powerful approach for identifying loci potentially under selection and explaining spatially complex interactions between species and their environment.

  3. New Regularization Method in Electrical Impedance Tomography

    Institute of Scientific and Technical Information of China (English)

    侯卫东; 莫玉龙

    2002-01-01

    Image reconstruction in elecrical impedance tomography(EIT)is a highly ill-posed inverse problem,Regularization techniques must be used in order to solve the problem,In this paper,a new regularization method based on the spatial filtering theory is proposed.The new regularized reconstruction for EIT is independent of the estimation of impedance distribution,so it can be implemented more easily than the maxiumum a posteriori(MAP) method.The regularization level in our proposed method varies spatially so as to be suited to the correlation character of the object's impedance distribution.We implemented our regularization method with two dimensional computer simulations.The experimental results indicate that the quality of the reconstructed impedance images with the descibed regularization method based on spatial filtering theory is better than that with Tikhonov method.

  4. Based on time and spatial-resolved SERS mapping strategies for detection of pesticides.

    Science.gov (United States)

    Ma, Bingbing; Li, Pan; Yang, Liangbao; Liu, Jinhuai

    2015-08-15

    For the sensitive and convenient detection of pesticides, several sensing methods and materials have been widely explored. However, it is still a challenge to obtain sensitive, simple detection techniques for pesticides. Here, the simple and sensitive Time-resolved SERS mapping (T-SERS) and Spatial-resolved SERS mapping (S-SERS) are presented for detection of pesticides by using Au@Ag NPs as SERS substrate. The Time-resolved SERS mapping (T-SERS) is based on state translation nanoparticles from the wet state to the dry state to realize SERS measurements. During the SERS measurement, adhesive force drives the particles closer together and then average interparticle gap becomes smaller. Following, air then begins to intersperse into the liquid network and the particles are held together by adhesive forces at the solid-liquid-air interface. In the late stage of water evaporation, all particles are uniformly distributed. Thus, so called hotspots matrix that can hold hotspots between every two adjacent particles in efficient space with minimal polydispersity of particle size are achieved, accompanying the red-shift of surface plasmon peak and appearance of an optimal SPR resonated sharply with excitation wavelength. Here, we found that the T-SERS method exhibits the detection limits of 1-2 orders of magnitude higher than that of S-SERS. On the other hand, the T-SERS is very simple method with high detection sensitivity, better reproducibility (RSD=10.8%) and is beneficial to construction of a calibration curve in comparison with that of Spatial-resolved SERS mapping (S-SERS). Most importantly, as a result of its remarkable sensitivity, T-SERS mapping strategies have been applied to detection of several pesticides and the detect limit can down to 1nM for paraoxon, 0.5nM for sumithion. In short, T-SERS mapping measurement promises to open a market for SERS practical detection with prominent advantages.

  5. Best period for high spatial resolution satellite images for the detection of marks of buried structures

    Directory of Open Access Journals (Sweden)

    Dimitrios Kaimaris

    2012-06-01

    Full Text Available Improvements in sensor technology in recent decades led to the creation of ground, air and space imaging systems, whose data can be used in archaeological studies. Greece is one of the lucky areas that are rich in archaeological heritage. The detection of prehistoric/historic undiscovered constructions on satellite images or aerial photos is a complex and complicated matter. These marks are not visible from the ground, they can, however, be traced on satellite or aerial images, because of the differences in tone and texture. These differences appear as crop, soil and shadow marks. Undoubtedly, the detection of buried structures requires a suitable spatial resolution image, taken under appropriate meteorological conditions and during the best period of the vegetation growing cycle. According to the pertinent literature, detecting covered memorials may be achieved either accidentally or, usually, after a systematic investigation based on historical narratives. The purpose of this study is to determine the factors that facilitate or hinder the detection of buried structures through high spatial resolution satellite imagery. In this study, pan sharpened images from the QuickBird-2 satellite were used, of a spatial resolution of 0.60-0.70 m. This study concerns the detection of marks of the ancient Via Egnatia, from the ancient Amphipolis to Philippi (Eastern Macedonia, Greece. We studied different types of vegetation in the region and their phenological cycle. Taking into account the vegetation phenological cycle of the study area as well as the meteorological data, four pan sharpened QuickBird-2 images of a spatial resolution of 0.60–0.70 m. were used, during four different seasons. By processing the four images, we can determine the one acquired during the most appropriate conditions for the detection of buried structures. The application of this methodology in the study area had positive results, and not only was the main purpose of this

  6. Detection of auditory signals in quiet and noisy backgrounds while performing a visuo-spatial task

    Directory of Open Access Journals (Sweden)

    Vishakha W Rawool

    2016-01-01

    Full Text Available Context: The ability to detect important auditory signals while performing visual tasks may be further compounded by background chatter. Thus, it is important to know how task performance may interact with background chatter to hinder signal detection. Aim: To examine any interactive effects of speech spectrum noise and task performance on the ability to detect signals. Settings and Design: The setting was a sound-treated booth. A repeated measures design was used. Materials and Methods: Auditory thresholds of 20 normal adults were determined at 0.5, 1, 2 and 4 kHz in the following conditions presented in a random order: (1 quiet with attention; (2 quiet with a visuo-spatial task or puzzle (distraction; (3 noise with attention and (4 noise with task. Statistical Analysis: Multivariate analyses of variance (MANOVA with three repeated factors (quiet versus noise, visuo-spatial task versus no task, signal frequency. Results: MANOVA revealed significant main effects for noise and signal frequency and significant noise–frequency and task–frequency interactions. Distraction caused by performing the task worsened the thresholds for tones presented at the beginning of the experiment and had no effect on tones presented in the middle. At the end of the experiment, thresholds (4 kHz were better while performing the task than those obtained without performing the task. These effects were similar across the quiet and noise conditions. Conclusion: Detection of auditory signals is difficult at the beginning of a distracting visuo-spatial task but over time, task learning and auditory training effects can nullify the effect of distraction and may improve detection of high frequency sounds.

  7. Early Detection for Dengue Using Local Indicator of Spatial Association (LISA Analysis

    Directory of Open Access Journals (Sweden)

    Mayra Elizabeth Parra-Amaya

    2016-03-01

    Full Text Available Dengue is a viral disease caused by a flavivirus that is transmitted by mosquitoes of the genus Aedes. There is currently no specific treatment or commercial vaccine for its control and prevention; therefore, mosquito population control is the only alternative for preventing the occurrence of dengue. For this reason, entomological surveillance is recommended by World Health Organization (WHO to measure dengue risk in endemic areas; however, several works have shown that the current methodology (aedic indices is not sufficient for predicting dengue. In this work, we modified indices proposed for epidemic periods. The raw value of the epidemiological wave could be useful for detecting risk in epidemic periods; however, risk can only be detected if analyses incorporate the maximum epidemiological wave. Risk classification was performed according to Local Indicators of Spatial Association (LISA methodology. The modified indices were analyzed using several hypothetical scenarios to evaluate their sensitivity. We found that modified indices could detect spatial and differential risks in epidemic and endemic years, which makes them a useful tool for the early detection of a dengue outbreak. In conclusion, the modified indices could predict risk at the spatio-temporal level in endemic years and could be incorporated in surveillance activities in endemic places.

  8. Application of hotspot detection using spatial scan statistic: Study of criminality in Indonesia

    Science.gov (United States)

    Runadi, Taruga; Widyaningsih, Yekti

    2017-03-01

    According to the police registered data, the number of criminal cases tends to fluctuate during 2011 to 2013. It means there is no significant reduction cases number of criminal acts during that period. Local government needs to observe whether their area was a high risk of criminal case. The objectives of this study are to detect hotspot area of certain criminal cases using spatial scan statistic. This study analyzed the data of 22 criminal types cases based on province in Indonesia that occurred during 2013. The data was obtained from Badan Pusat Statistik (BPS) that was released in 2014. Hotspot detection was performed according to the likelihood ratio of the Poisson model using SaTScanTM software and then mapped using R. The spatial scan statistic method successfully detected provinces that was categorized as hotspot for 22 crime types cases being analyzed with p-value less than 0.05. The local governments of province that were detected as hotspot area of certain crime cases should provide more attention to improve security quality.

  9. Detecting Temporal and Spatial Effects of Epithelial Cancers with Raman Spectroscopy

    Directory of Open Access Journals (Sweden)

    Matthew D. Keller

    2008-01-01

    Full Text Available Epithelial cancers, including those of the skin and cervix, are the most common type of cancers in humans. Many recent studies have attempted to use Raman spectroscopy to diagnose these cancers. In this paper, Raman spectral markers related to the temporal and spatial effects of cervical and skin cancers are examined through four separate but related studies. Results from a clinical cervix study show that previous disease has a significant effect on the Raman signatures of the cervix, which allow for near 100% classification for discriminating previous disease versus a true normal. A Raman microspectroscopy study showed that Raman can detect changes due to adjacent regions of dysplasia or HPV that cannot be detected histologically, while a clinical skin study showed that Raman spectra may be detecting malignancy associated changes in tissues surrounding nonmelanoma skin cancers. Finally, results of an organotypic raft culture study provided support for both the skin and the in vitro cervix results. These studies add to the growing body of evidence that optical spectroscopy, in this case Raman spectral markers, can be used to detect subtle temporal and spatial effects in tissue near cancerous sites that go otherwise undetected by conventional histology.

  10. Spatial and temporal control of thermal waves by using DMDs for interference based crack detection

    Science.gov (United States)

    Thiel, Erik; Kreutzbruck, Marc; Ziegler, Mathias

    2016-02-01

    Active Thermography is a well-established non-destructive testing method and used to detect cracks, voids or material inhomogeneities. It is based on applying thermal energy to a samples' surface whereas inner defects alter the nonstationary heat flow. Conventional excitation of a sample is hereby done spatially, either planar (e.g. using a lamp) or local (e.g. using a focused laser) and temporally, either pulsed or periodical. In this work we combine a high power laser with a Digital Micromirror Device (DMD) allowing us to merge all degrees of freedom to a spatially and temporally controlled heat source. This enables us to exploit the possibilities of coherent thermal wave shaping. Exciting periodically while controlling at the same time phase and amplitude of the illumination source induces - via absorption at the sample's surface - a defined thermal wave propagation through a sample. That means thermal waves can be controlled almost like acoustical or optical waves. However, in contrast to optical or acoustical waves, thermal waves are highly damped due to the diffusive character of the thermal heat flow and therefore limited in penetration depth in relation to the achievable resolution. Nevertheless, the coherence length of thermal waves can be chosen in the mmrange for modulation frequencies below 10 Hz which is perfectly met by DMD technology. This approach gives us the opportunity to transfer known technologies from wave shaping techniques to thermography methods. We will present experiments on spatial and temporal wave shaping, demonstrating interference based crack detection.

  11. A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization.

    Science.gov (United States)

    Rao, Jinmeng; Qiao, Yanjun; Ren, Fu; Wang, Junxing; Du, Qingyun

    2017-08-24

    The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device's built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction.

  12. Evaluation and Comparision of Common Spatial Patterns (CSP and Intelligent Segmentation in P300 Detection

    Directory of Open Access Journals (Sweden)

    Zahra Amini1

    2011-05-01

    Full Text Available In This Paper, two different feature extraction methods were studied and their performances in pattern recognition based- P300 detection were compared. These two methods were Common Spatial Pattern (CSP and intelligent segmentation. Data set II (P300 speller from the BCI competition 2005 was used. After pre-processing and feature extraction, these features were compared. For this purpose, first, a statistical analysis had been applied for evaluating the fitness of each feature in discriminating between target and non target signals. Then, each of these two groups of features was evaluated by a Linear Discriminant Analysis (LDA classifier. Furthermore by using Stepwise Linear Discriminant Analysis (SWLDA, the best set of features was selected. Finally in this research, the best result for P300 detection was 95.25% for intelligent segmentation as a feature extraction method. This result shows that intelligent segmentation is better than CSP method for P300 detection.

  13. Detection of spatial variations in temporal trends with a quadratic function.

    Science.gov (United States)

    Moraga, Paula; Kulldorff, Martin

    2016-08-01

    Methods for the assessment of spatial variations in temporal trends (SVTT) are important tools for disease surveillance, which can help governments to formulate programs to prevent diseases, and measure the progress, impact, and efficacy of preventive efforts already in operation. The linear SVTT method is designed to detect areas with unusual different disease linear trends. In some situations, however, its estimation trend procedure can lead to wrong conclusions. In this article, the quadratic SVTT method is proposed as alternative of the linear SVTT method. The quadratic method provides better estimates of the real trends, and increases the power of detection in situations where the linear SVTT method fails. A performance comparison between the linear and quadratic methods is provided to help illustrate their respective properties. The quadratic method is applied to detect unusual different cervical cancer trends in white women in the United States, over the period 1969 to 1995. © The Author(s) 2013.

  14. A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization

    Directory of Open Access Journals (Sweden)

    Jinmeng Rao

    2017-08-01

    Full Text Available The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device’s built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction.

  15. Zero-crossing detection algorithm for arrays of optical spatial filtering velocimetry sensors

    DEFF Research Database (Denmark)

    Jakobsen, Michael Linde; Pedersen, Finn; Hanson, Steen Grüner

    2008-01-01

    This paper presents a zero-crossing detection algorithm for arrays of compact low-cost optical sensors based on spatial filtering for measuring fluctuations in angular velocity of rotating solid structures. The algorithm is applicable for signals with moderate signal-to-noise ratios, and delivers...... a "real-time" output (0-1 kHz). The sensors use optical spatial-filtering velocimetry on the dynamical speckles arising from scattering off a rotating solid object with a non-specular surface. The technology measures the instantaneous angular velocity of a target, without being biased by any linear...... factor is directly related to the thermal expansion and refractive-index coefficients of the optics (> 10(-5) K-1 for glass). By cascade-coupling an array of sensors, the ensemble-averaged angular velocity is measured in "real-time". This will reduce the influence of pseudo-vibrations arising from...

  16. Spatial-temporal features of thermal images for Carpal Tunnel Syndrome detection

    Science.gov (United States)

    Estupinan Roldan, Kevin; Ortega Piedrahita, Marco A.; Benitez, Hernan D.

    2014-02-01

    Disorders associated with repeated trauma account for about 60% of all occupational illnesses, Carpal Tunnel Syndrome (CTS) being the most consulted today. Infrared Thermography (IT) has come to play an important role in the field of medicine. IT is non-invasive and detects diseases based on measuring temperature variations. IT represents a possible alternative to prevalent methods for diagnosis of CTS (i.e. nerve conduction studies and electromiography). This work presents a set of spatial-temporal features extracted from thermal images taken in healthy and ill patients. Support Vector Machine (SVM) classifiers test this feature space with Leave One Out (LOO) validation error. The results of the proposed approach show linear separability and lower validation errors when compared to features used in previous works that do not account for temperature spatial variability.

  17. Detection of Burn Area and Severity with MODIS Satellite Images and Spatial Autocorrelation Techniques

    Science.gov (United States)

    Kaya, S.; Kavzoglu, T.; Tonbul, H.

    2014-12-01

    Effects of forest fires and implications are one of the most important natural disasters all over the world. Statistical data observed that forest fires had a variable structure in the last century in Turkey, but correspondingly the population growth amount of forest fires and burn area increase widely in recent years. Depending on this, erosion, landslides, desertification and mass loss come into existence. In addition; after forest fires, renewal of forests and vegetation are very important for land management. Classic methods used for detection of burn area and severity requires a long and challenging process due to time and cost factors. Thanks to advanced techniques used in the field of Remote Sensing, burn area and severity can be determined with high detail and precision. The purpose of this study based on blending MODIS (Moderate Resolution Imaging Spectradiometer) satellite images and spatial autocorrelation techniques together, thus detect burn area and severity absolutely. In this context, spatial autocorrelation statistics like Moran's I and Get is-Ord Local Gi indexes were used to measure and analyze to burned area characteristics. Prefire and postfire satellite images were used to determine fire severity depending on spectral indexes corresponding to biomass loss and carbon emissivity intensities. Satellite images have used for identification of fire damages and risks in terms of fire management for a long time. This study was performed using prefire and postfire satellite images and spatial autocorrelation techniques to determining and analyzing forest fires in Antalya, Turkey region which serious fires occurred. In this context, this approach enables the characterization of distinctive texture of burned area and helps forecasting more precisely. Finally, it is observed that mapping of burned area and severity could be performed from local scale to national scale. Key Words: Spatial autocorrelation, MODIS, Fire, Burn Severity

  18. Action change detection in video using a bilateral spatial-temporal constraint

    Science.gov (United States)

    Tian, Jing; Chen, Li

    2016-08-01

    Action change detection in video aims to detect action discontinuity in video. The silhouettes-based features are desirable for action change detection. This paper studies the problem of silhouette-quality assessment. For that, a non-reference approach without the need for ground truth is proposed in this paper to evaluate the quality of silhouettes, by exploiting both the boundary contrast of the silhouettes in the spatial domain and the consistency of the silhouettes in the temporal domain. This is in contrast to that either only spatial information or only temporal information of silhouettes is exploited in conventional approaches. Experiments are conducted using artificially generated degraded silhouettes to show that the proposed approach outperforms conventional approaches to achieve more accurate quality assessment. Furthermore, experiments are performed to show that the proposed approach is able to improve the accuracy performance of conventional action change approaches in two human action video data-sets. The average runtime of the proposed approach for Weizmann action video data-set is 0.08 second for one frame using Matlab programming language. It is computationally efficient and potential to real-time implementations.

  19. Test analysis of detection of damage to a complicated spatial model structure

    Institute of Scientific and Technical Information of China (English)

    Long-He Xu; Zhong-Xian Li; Jia-Ru Qian

    2011-01-01

    A two-stage damage detection approach is proposed and experimentally demonstrated on a complicated spatial model structure with a limited number of measurements. In the experiment, five known damage patterns, including 3 brace damage cases and 2 joint damage cases, were simulated by removing braces and weakening beam-column connections in the structure. The limited acceleration response data generated by hammer impact were used for system identification, and modal parameters were extracted by using the eigensystem realization algorithm. In the first stage, the possible damaged locations are determined by using the damage index and the characteristics of the analytical model itself, and the extent of damage for those substructures identified at stage I is estimated in the second stage by using a second-order eigen-sensitivity approximation method. The main contribution of this paper is to test the two-stage method by using the real dynamic data of a complicated spatial model structure with limited sensors. The analysis results indicate that the two-stage approach is able to detect the location of both damage cases, only the severity of brace damage cases can be assessed, and the reasonable analytical model is critical for successful damage detection.

  20. Topological Relations-Based Detection of Spatial Inconsistency in GLOBELAND30

    Science.gov (United States)

    Kang, S.; Chen, J.; Peng, S.

    2017-09-01

    Land cover is one of the fundamental data sets on environment assessment, land management and biodiversity protection, etc. Hence, data quality control of land cover is extremely critical for geospatial analysis and decision making. Due to the similar remote-sensing reflectance for some land cover types, omission and commission errors occurred in preliminary classification could result to spatial inconsistency between land cover types. In the progress of post-classification, this error checking mainly depends on manual labour to assure data quality, by which it is time-consuming and labour intensive. So a method required for automatic detection in post-classification is still an open issue. From logical inconsistency point of view, an inconsistency detection method is designed. This method consist of a grids extended 4-intersection model (GE4IM) for topological representation in single-valued space, by which three different kinds of topological relations including disjoint, touch, contain or contained-by are described, and an algorithm of region overlay for the computation of spatial inconsistency. The rules are derived from universal law in nature between water body and wetland, cultivated land and artificial surface. Through experiment conducted in Shandong Linqu County, data inconsistency can be pointed out within 6 minutes through calculation of topological inconsistency between cultivated land and artificial surface, water body and wetland. The efficiency evaluation of the presented algorithm is demonstrated by Google Earth images. Through comparative analysis, the algorithm is proved to be promising for inconsistency detection in land cover data.

  1. Evaluation of sliding baseline methods for spatial estimation for cluster detection in the biosurveillance system

    Directory of Open Access Journals (Sweden)

    Leuze Michael

    2009-07-01

    Full Text Available Abstract Background The Centers for Disease Control and Prevention's (CDC's BioSense system provides near-real time situational awareness for public health monitoring through analysis of electronic health data. Determination of anomalous spatial and temporal disease clusters is a crucial part of the daily disease monitoring task. Our study focused on finding useful anomalies at manageable alert rates according to available BioSense data history. Methods The study dataset included more than 3 years of daily counts of military outpatient clinic visits for respiratory and rash syndrome groupings. We applied four spatial estimation methods in implementations of space-time scan statistics cross-checked in Matlab and C. We compared the utility of these methods according to the resultant background cluster rate (a false alarm surrogate and sensitivity to injected cluster signals. The comparison runs used a spatial resolution based on the facility zip code in the patient record and a finer resolution based on the residence zip code. Results Simple estimation methods that account for day-of-week (DOW data patterns yielded a clear advantage both in background cluster rate and in signal sensitivity. A 28-day baseline gave the most robust results for this estimation; the preferred baseline is long enough to remove daily fluctuations but short enough to reflect recent disease trends and data representation. Background cluster rates were lower for the rash syndrome counts than for the respiratory counts, likely because of seasonality and the large scale of the respiratory counts. Conclusion The spatial estimation method should be chosen according to characteristics of the selected data streams. In this dataset with strong day-of-week effects, the overall best detection performance was achieved using subregion averages over a 28-day baseline stratified by weekday or weekend/holiday behavior. Changing the estimation method for particular scenarios involving

  2. Landmine detection with Bayesian cross-categorization on point-wise, contextual and spatial features

    Science.gov (United States)

    Léveillé, Jasmin; Yu, Ssu-Hsin; Gandhe, Avinash

    2016-05-01

    Recently developed feature extraction methods proposed in the explosive hazard detection community have yielded many features that potentially provide complementary information for explosive detection. Finding the right combination of features that is most effective in distinguishing targets from clutter, on the other hand, is extremely challenging due to a large number of potential features to explore. Furthermore, sensors employed for mine and buried explosive hazard detection are typically sensitive to environmental conditions such as soil properties and weather as well as other operating parameters. In this work, we applied Bayesian cross-categorization (CrossCat) to a heterogeneous set of features derived from electromagnetic induction (EMI) sensor time-series for purposes of buried explosive hazard detection. The set of features used here includes simple, point-wise measurements such as the overall magnitude of the EMI response, contextual information such as soil type, and a new feature consisting of spatially aggregated Discrete Spectra of Relaxation Frequencies (DSRFs). Previous work showed that the DSRF characterizes target properties with some invariance to orientation and position. We have developed a novel approach to aggregate point-wise DSRF estimates. The spatial aggregation is based on the Bag-of-Words (BoW) model found in the machine learning and computer vision literatures and aims to enhance the invariance properties of point-wise DSRF estimates. We considered various refinements to the BoW model for purpose of buried explosive hazard detection and tested their usefulness as part of a Bayesian cross-categorization framework on data collected from two different sites. The results show improved performance over classifiers using only point-wise features.

  3. Measurement of Vibration Detection Threshold and Tactile Spatial Acuity in Human Subjects.

    Science.gov (United States)

    Moshourab, Rabih; Frenzel, Henning; Lechner, Stefan; Haseleu, Julia; Bégay, Valérie; Omerbašić, Damir; Lewin, Gary R

    2016-09-01

    Tests that allow the precise determination of psychophysical thresholds for vibration and grating orientation provide valuable information about mechanosensory function that are relevant for clinical diagnosis as well as for basic research. Here, we describe two psychophysical tests designed to determine the vibration detection threshold (automated system) and tactile spatial acuity (handheld device). Both procedures implement a two-interval forced-choice and a transformed-rule up and down experimental paradigm. These tests have been used to obtain mechanosensory profiles for individuals from distinct human cohorts such as twins or people with sensorineural deafness.

  4. Spatially valid proprioceptive cues improve the detection of a visual stimulus

    DEFF Research Database (Denmark)

    Jackson, Carl P T; Miall, R Chris; Balslev, Daniela

    2010-01-01

    , which has been demonstrated for other modality pairings. The aim of this study was to test whether proprioceptive signals can spatially cue a visual target to improve its detection. Participants were instructed to use a planar manipulandum in a forward reaching action and determine during this movement...... whether a near-threshold visual target appeared at either of two lateral positions. The target presentation was followed by a masking stimulus, which made its possible location unambiguous, but not its presence. Proprioceptive cues were given by applying a brief lateral force to the participant's arm......, either in the same direction (validly cued) or in the opposite direction (invalidly cued) to the on-screen location of the mask. The d' detection rate of the target increased when the direction of proprioceptive stimulus was compatible with the location of the visual target compared to when...

  5. Coincidence detection of spatially correlated photon pairs with a monolithic time-resolving detector array

    CERN Document Server

    Unternährer, Manuel; Gasparini, Leonardo; Stoppa, David; Stefanov, André

    2016-01-01

    We demonstrate coincidence measurements of spatially entangled photons by means of a novel type of multi-pixel based detection array. The adopted sensor is a fully digital 8$\\times$16 silicon photomultiplier array allowing not only photon counting but also per-pixel time stamping of the arrived photons with a resolution of 65 ps. Together with a frame rate of 500 kfps, this property exceeds the capabilities of conventional charge-coupled device cameras which have become of growing interest for the detection of transversely correlated photon pairs. The sensor is used to measure a second-order correlation function for various non-collinear configurations of entangled photons generated by spontaneous parametric down-conversion. The experimental results are compared to theory.

  6. Detecting community structure in networks via consensus dynamics and spatial transformation

    Science.gov (United States)

    Yang, Bo; He, He; Hu, Xiaoming

    2017-10-01

    We present a novel clustering algorithm for community detection, based on the dynamics towards consensus and spatial transformation. The community detection problem is translated to a clustering problem in the N-dimensional Euclidean space by three stages: (1) the dynamics running on a network is emulated to a procedure of gas diffusion in a finite space; (2) the pressure distribution vectors are used to describe the influence that each node exerts on the whole network; (3) the similarity measures between two nodes are quantified in the N-dimensional Euclidean space by k-Nearest Neighbors method. After such steps, we could merge clusters according to their similarity distances and show the community structure of a network by a hierarchical clustering tree. Tests on several benchmark networks are presented and the results show the effectiveness and reliability of our algorithm.

  7. COMBINED TRANSMIT ANTENNA SELECTION AND DETECTION OVER SPATIAL CORRELATED MIMO SYSTEMS

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    In this paper a method that combines transmit antenna selection and reduced-constellation detection in spatially correlated Multi-Input Multi-Output (MIMO) fading channels is presented. To mitigate the performance degradation caused by the use of antenna selection that is based on correlation among columns, an iterative receiver scheme that uses only a subset of the constellation points close to the expected symbol value estimated in the previous iteration is proposed. The size of the subset can adapt to the maximum correlation of the sub-matrix after the simple antenna selection. Furthermore, the error rate performance of the scheme under linear Minimum Mean Square Error (MMSE) or Ordered Successive Interference Cancellation (OSIC) for the first run detection and different interleaver lengths is investigated while the transmit antenna selection is considered. The simulation results show a significant advantage both for implementation complexity and for error rate performance under a fixed data rate.

  8. Urban-rural gradient detection using multivariate spatial analysis and landscape metrics

    Directory of Open Access Journals (Sweden)

    Marco Vizzari

    2013-09-01

    Full Text Available The gradient approach allows for an innovative representation of landscape composition and configuration not presupposing spatial discontinuities typical of the conventional methods of analysis. Also the urban-rural dichotomy can be better understood through a continuous landscape gradient whose characterization changes accordingly to natural and anthropic variables taken into account and to the spatio-temporal scale adopted for the study. The research was aimed at the analysis of an urban-rural gradient within a study area located in central Italy, using spatial indicators associated with urbanization, agriculture and natural elements. A multivariate spatial analysis (MSA of such indicators enabled the identification of urban, agricultural and natural dominated areas, as well as specific landscape transitions where the most relevant relationships between agriculture and other landscape components were detected. Landscapes derived from MSA were studied by a set of key landscape pattern metrics within a framework oriented to the structural characterization of the whole urban-rural gradient. The results showed two distinct sub-gradients: one urban-agricultural and one agricultural-natural, both characterized by different fringe areas. This application highlighted how the proposed methodology can represent a reliable approach supporting modern landscape planning and management.

  9. Compressed sensing for super-resolution spatial and temporal laser detection and ranging

    Science.gov (United States)

    Laurenzis, Martin; Schertzer, Stephane; Christnacher, Frank

    2016-10-01

    In the past decades, laser aided electro-optical sensing has reached high maturity and several commercial systems are available at the market for various but specific applications. These systems can be used for detection i.e. imaging as well as ranging. They cover laser scanning devices like LiDAR and staring full frame imaging systems like laser gated viewing or LADAR. The sensing capabilities of these systems is limited by physical parameter (like FPA array size, temporal band width, scanning rate, sampling rate) and is adapted to specific applications. Change of system parameter like an increase of spatial resolution implies the setup of a new sensing device with high development cost or the purchase and installation of a complete new sensor unit. Computational imaging approaches can help to setup sensor devices with flexible or adaptable sensing capabilities. Especially, compressed sensing is an emerging computational method which is a promising candidate to realize super-resolution sensing with the possibility to adapt its performance to various sensing tasks. It is possible to increase sensing capabilities with compressed sensing to gain either higher spatial and/or temporal resolution. Then, the sensing capabilities depend no longer only on the physical performance of the device but also on the computational effort and can be adapted to the application. In this paper, we demonstrate and discuss laser aided imaging using CS for super-resolution tempo-spatial imaging and ranging.

  10. Detectability of change in winter precipitation within mountain landscapes: Spatial patterns and uncertainty

    Science.gov (United States)

    Silverman, N. L.; Maneta, M. P.

    2016-06-01

    Detecting long-term change in seasonal precipitation using ground observations is dependent on the representativity of the point measurement to the surrounding landscape. In mountainous regions, representativity can be poor and lead to large uncertainties in precipitation estimates at high elevations or in areas where observations are sparse. If the uncertainty in the estimate is large compared to the long-term shifts in precipitation, then the change will likely go undetected. In this analysis, we examine the minimum detectable change across mountainous terrain in western Montana, USA. We ask the question: What is the minimum amount of change that is necessary to be detected using our best estimates of precipitation in complex terrain? We evaluate the spatial uncertainty in the precipitation estimates by conditioning historic regional climate model simulations to ground observations using Bayesian inference. By using this uncertainty as a null hypothesis, we test for detectability across the study region. To provide context for the detectability calculations, we look at a range of future scenarios from the Coupled Model Intercomparison Project 5 (CMIP5) multimodel ensemble downscaled to 4 km resolution using the MACAv2-METDATA data set. When using the ensemble averages we find that approximately 65% of the significant increases in winter precipitation go undetected at midelevations. At high elevation, approximately 75% of significant increases in winter precipitation are undetectable. Areas where change can be detected are largely controlled by topographic features. Elevation and aspect are key characteristics that determine whether or not changes in winter precipitation can be detected. Furthermore, we find that undetected increases in winter precipitation at high elevation will likely remain as snow under climate change scenarios. Therefore, there is potential for these areas to offset snowpack loss at lower elevations and confound the effects of climate change

  11. On Weak Regular *-semigroups

    Institute of Scientific and Technical Information of China (English)

    Yong Hua LI; Hai Bin KAN; Bing Jun YU

    2004-01-01

    In this paper, a special kind of partial algebras called projective partial groupoids is defined.It is proved that the inverse image of all projections of a fundamental weak regular *-semigroup under the homomorphism induced by the maximum idempotent-separating congruence of a weak regular *-semigroup has a projective partial groupoid structure. Moreover, a weak regular *-product which connects a fundamental weak regular *-semigroup with corresponding projective partial groupoid is defined and characterized. It is finally proved that every weak regular *-product is in fact a weak regular *-semigroup and any weak regular *-semigroup is constructed in this way.

  12. Using NIR spatial illumination for detection and mapping chromophore changes during cerebral edema

    Science.gov (United States)

    Abookasis, David; Mathews, Marlon S.; Owen, Christopher M.; Binder, Devin K.; Linskey, Mark E.; Frostig, Ron D.; Tromberg, Bruce J.

    2008-02-01

    We used spatially modulated near-infrared (NIR) light to detect and map chromophore changes during cerebral edema in the rat neocortex. Cerebral edema was induced by intraperitoneal injections of free water (35% of body weight). Intracranial pressure (ICP) was measured with an optical fiber based Fabry-Perot interferometer sensor inserted into the parenchyma of the right frontal lobe during water administration. Increase in ICP from a baseline value of 10 cm-water to 145 cm-water was observed. Following induction of cerebral edema, there was a 26+/-1.7% increase in tissue concentration of deoxyhemoglobin and a 47+/-4.7%, 17+/-3% and 37+/-3.7% decrease in oxyhemoglobin, total hemoglobin concentration and cerebral tissue oxygen saturation levels, respectively. To the best of our knowledge, this is the first report describing the use of NIR spatial modulation of light for detecting and mapping changes in tissue concentrations of physiologic chromophores over time in response to cerebral edema.

  13. A novel method for detecting association between DNA methylation and diseases using spatial information

    Science.gov (United States)

    Yip, Wai-Ki; Fier, Heide; DeMeo, Dawn L.; Aryee, Martin; Laird, Nan; Lange, Christoph

    2014-01-01

    DNA methylation may represent an important contributor to the missing heritability described in complex trait genetics. However, technology to measure DNA methylation has outpaced statistical methods for analysis. Taking advantage of the recent finding that methylated sites cluster together, we propose a Spatial Clustering Method (SCM) method to detect differentially methylated regions in the genome in case and control studies using spatial location information. This new method compares the distribution of distances in cases and controls between DNA methylation marks in the genomic region of interest. A statistic is computed based on these distances. Proper type I error rate is maintained and statistical significance is evaluated using permutation test. The effectiveness of the SCM we propose is evaluated by a simulation study. By simulating a simple disease model, we demonstrate that SCM has good power to detect differentially methylated regions associated with the disease. Finally, we applied the SCM to an exploratory analysis of chromosome 14 from a colorectal cancer data set and identified statistically significant genomic regions. Identification of these regions should lead to a better understanding of methylated sites and their contribution to disease. The SCM can be used as a reliable statistical method for the identification of differentially methylated regions associated with disease states in exploratory epigenetic analyses. PMID:25250875

  14. Chemical and explosives point detection through opaque containers using spatially offset Raman spectroscopy (SORS)

    Science.gov (United States)

    Loeffen, Paul W.; Maskall, Guy; Bonthron, Stuart; Bloomfield, Matthew; Tombling, Craig; Matousek, Pavel

    2011-05-01

    Spatially Offset Raman Spectroscopy (SORS) is a novel technique used to identify the chemical Raman signature of threat materials within a few seconds through common non-metallic containers, including those containers which may not yield to inspection by conventional backscatter Raman. In particular, some opaque plastic containers and coloured glass bottles can be difficult to analyze using conventional backscatter Raman because the signal from the contents is often overwhelmed by the much stronger Raman signal and/or fluorescence originating from the container itself. SORS overcomes these difficulties and generates clean Raman spectra from both the container and the contents with no prior knowledge of either. This is achieved by making two, or more, Raman measurements at various offsets between the collection and illumination areas, each containing different proportions of the fingerprint signals from the container and content materials. Using scaled subtraction, or multivariate statistical methods, the two orthogonal signals can be separated numerically, thereby providing a clean Raman spectrum of the contents without contamination from the container. Consequently, SORS promises to significantly improve threat detection capability and decrease the falsealarm rate compared with conventional Raman spectroscopy making it considerably more suitable as an alarm resolution methodology (e.g. at airports). In this paper, the technique and method are described and a study of offset value optimization is described illustrating the difference between one and two fixed spatial offsets. It is concluded that two fixed offsets yield an improvement in the SORS measurement which will help maximize the threat detection capability.

  15. Crosstalk elimination in the detection of dual-beam optical tweezers by spatial filtering

    Energy Technology Data Exchange (ETDEWEB)

    Ott, Dino; Oddershede, Lene B., E-mail: oddershede@nbi.dk [Niels Bohr Institute (NBI), University of Copenhagen, Blegdamsvej 17, DK-2100 Copenhagen (Denmark); Reihani, S. Nader S. [Department of Physics, Sharif University of Technology, 11369-9161 Tehran (Iran, Islamic Republic of)

    2014-05-15

    In dual-beam optical tweezers, the accuracy of position and force measurements is often compromised by crosstalk between the two detected signals, this crosstalk leading to systematic and significant errors on the measured forces and distances. This is true both for dual-beam optical traps where the splitting of the two traps is done by polarization optics and for dual optical traps constructed by other methods, e.g., holographic tweezers. If the two traps are orthogonally polarized, most often crosstalk is minimized by inserting polarization optics in front of the detector; however, this method is not perfect because of the de-polarization of the trapping beam introduced by the required high numerical aperture optics. Here we present a simple and easy-to-implement method to efficiently eliminate crosstalk. The method is based on spatial filtering by simply inserting a pinhole at the correct position and is highly compatible with standard back focal plane photodiode based detection of position and force. Our spatial filtering method reduces crosstalk up to five times better than polarization filtering alone. The effectiveness is dependent on pinhole size and distance between the traps and is here quantified experimentally and reproduced by theoretical modeling. The method here proposed will improve the accuracy of force-distance measurements, e.g., of single molecules, performed by dual-beam optical traps and hence give much more scientific value for the experimental efforts.

  16. Ship detection in high spatial resolution remote sensing image based on improved sea-land segmentation

    Science.gov (United States)

    Li, Na; Zhang, Qiaochu; Zhao, Huijie; Dong, Chao; Meng, Lingjie

    2016-10-01

    A new method to detect ship target at sea based on improved segmentation algorithm is proposed in this paper, in which the improved segmentation algorithm is applied to precisely segment land and sea. Firstly, mean value is replaced instead of average variance value in Otsu method in order to improve the adaptability. Secondly, Mean Shift algorithm is performed to separate the original high spatial resolution remote sensing image into several homogeneous regions. At last, the final sea-land segmentation result can be located combined with the regions in preliminary sea-land segmentation result. The proposed segmentation algorithm performs well on the segment between water and land with affluent texture features and background noise, and produces a result that can be well used in shape and context analyses. Ships are detected with settled shape characteristics, including width, length and its compactness. Mean Shift algorithm can smooth the background noise, utilize the wave's texture features and helps highlight offshore ships. Mean shift algorithm is combined with improved Otsu threshold method in order to maximizes their advantages. Experimental results show that the improved sea-land segmentation algorithm on high spatial resolution remote sensing image with complex texture and background noise performs well in sea-land segmentation, not only enhances the accuracy of land and sea boarder, but also preserves detail characteristic of ships. Compared with traditional methods, this method can achieve accuracy over 90 percent. Experiments on Worldview images show the superior, robustness and precision of the proposed method.

  17. The characteristics and spatial distributions of initially missed and rebiopsy-detected prostate cancers

    Directory of Open Access Journals (Sweden)

    Myung-Won You

    2016-07-01

    Full Text Available Purpose: The purpose of this study was to analyze the characteristics of initially missed and rebiopsy-detected prostate cancers following 12-core transrectal biopsy. Methods: A total of 45 patients with prostate cancers detected on rebiopsy and 45 patients with prostate cancers initially detected on transrectal ultrasound-guided biopsy were included in the study. For result analysis, the prostate was divided into six compartments, and the cancer positive rates, estimated tumor burden, and agreement rates between biopsy and surgical specimens, along with clinical data, were evaluated. Results: The largest mean tumor burden was located in the medial apex in both groups. There were significantly more tumors in this location in the rebiopsy group (44.9% than in the control group (30.1%, P=0.015. The overall sensitivity of biopsy was significantly lower in the rebiopsy group (22.5% vs. 43.4%, P<0.001. The agreement rate of cancer positive cores between biopsy and surgical specimens was significantly lower in the medial apex in the rebiopsy group compared with that of the control group (50.0% vs. 65.6%, P=0.035. The cancer positive rates of target biopsy cores and premalignant lesions in the rebiopsy group were 63.1% and 42.3%, respectively. Conclusion: Rebiopsy-detected prostate cancers showed different spatial distribution and lower cancer detection rate of biopsy cores compared with initially diagnosed cancers. To overcome lower cancer detection rate, target biopsy of abnormal sonographic findings, premalignant lesions and medial apex which revealed larger tumor burden would be recommended when performing rebiopsy.

  18. Development of receiving-detecting circuit for digital radiographic systems with improved spatial resolution

    Science.gov (United States)

    Ryzhikov, Volodymir D.; Opolonin, Oleksandr D.; Galkin, Serhiy M.; Voronkin, Yevheniy F.; Lysetska, Olena K.; Kostyukevych, Serhiy A.

    2009-08-01

    Detection of X-ray radiation by digital radiographic systems (DRS) is realized using multi-element detector arrays of scintillator-photodiode (S-PD) type. Accounting for our experience in development of X-ray introscopy systems, possibilities can be found for improvement of DRS detection efficiency. Namely, a more efficient use of the dynamic range of the analog-to-digit converter by means of instrumental compensation of scatter of detector characteristics and smaller apertures of individual detection channels. However, smaller apertures lead to lower levels of useful signals, and a problem emerges of signal interference over neighboring channels, which is related to optical separation of the scintillation elements. Also, more compact arrangement of electronic components of preamplifiers is achieved. The latter problem is solved by using multi-channel (from 32 to 1024 channels) photoreceiving devices (PRD). PRD has a set of photosensitive elements formed on one crystal, as well as shift registers ensuring preliminary amplification of signals and series connection to one outlet. The work envisages creation of receiving-detecting circuit (RDC) with improved spatial resolution (ISR) with the aim of producing advanced DRS with improved characteristics: density resolution better than 0.9%, and detecting ability allowing detection of θ 0.5 mm steel wire behind 6 mm steel. The work will result in the development of RDC with ISR (800-200 microns). In combination with various ionizing radiation sources and scanning mechanisms this will allow creation of DRS for many tasks of non-destructive testing (NDT) and technical diagnostics (TD), in particular, for check-up of pipelines, objects of oil and gas industries, etc. This work was supported by the Ministry of Education and Science of Ukraine, the U.S. Civilian Research and Development Foundation (CRDF), and by the NATO Science for Peace and Security Program (Project SfP-982823).

  19. The characteristics and spatial distributions of initially missed and rebiopsy-detected prostate cancers

    Energy Technology Data Exchange (ETDEWEB)

    You, Myung Won; Kim, Mi Hyun; Kim, Jeong Kon; Cho, Kyoung Sik [Dept. of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul (Korea, Republic of)

    2016-07-15

    The purpose of this study was to analyze the characteristics of initially missed and rebiopsy-detected prostate cancers following 12-core transrectal biopsy. A total of 45 patients with prostate cancers detected on rebiopsy and 45 patients with prostate cancers initially detected on transrectal ultrasound-guided biopsy were included in the study. For result analysis, the prostate was divided into six compartments, and the cancer positive rates, estimated tumor burden, and agreement rates between biopsy and surgical specimens, along with clinical data, were evaluated. The largest mean tumor burden was located in the medial apex in both groups. There were significantly more tumors in this location in the rebiopsy group (44.9%) than in the control group (30.1%, P=0.015). The overall sensitivity of biopsy was significantly lower in the rebiopsy group (22.5% vs. 43.4%, P<0.001). The agreement rate of cancer positive cores between biopsy and surgical specimens was significantly lower in the medial apex in the rebiopsy group compared with that of the control group (50.0% vs. 65.6%, P=0.035). The cancer positive rates of target biopsy cores and premalignant lesions in the rebiopsy group were 63.1% and 42.3%, respectively. Rebiopsy-detected prostate cancers showed different spatial distribution and lower cancer detection rate of biopsy cores compared with initially diagnosed cancers. To overcome lower cancer detection rate, target biopsy of abnormal sonographic findings, premalignant lesions and medial apex which revealed larger tumor burden would be recommended when performing rebiopsy.

  20. Combining time-frequency and spatial information for the detection of sleep spindles

    Directory of Open Access Journals (Sweden)

    Christian eO'Reilly

    2015-02-01

    Full Text Available EEG sleep spindles are short (0.5-2.0 s bursts of activity in the 11-16 Hz band occurring during non-rapid eye movement (NREM sleep. This sporadic activity is thought to play a role in memory consolidation, brain plasticity, and protection of sleep integrity. Many automatic detectors have been proposed to assist or replace experts for sleep spindle scoring. However, these algorithms usually detect too many events making it difficult to achieve a good tradeoff between sensitivity (Se and false detection rate (FDr. In this work, we propose a semi-automatic detector comprising a sensitivity phase based on well-established criteria followed by a specificity phase using spatial and spectral criteria.In the sensitivity phase, selected events are those which amplitude in the 10 – 16 Hz band and spectral ratio characteristics both reject a null hypothesis (p <0.1 stating that the considered event is not a spindle. This null hypothesis is constructed from events occurring during rapid eye movement (REM sleep epochs. In the specificity phase, a hierarchical clustering of the selected candidates is done based on events’ frequency and spatial position along the anterior-posterior axis. Only events from the classes grouping most (at least 80% spindles scored by an expert are kept. We obtain Se = 93.2% and FDr = 93.0% in the first phase and Se = 85.4% and FDr = 86.2% in the second phase. For these two phases, Matthew’s correlation coefficients are respectively 0.228 and 0.324. Results suggest that spindles are defined by specific spatio-spectral properties and that automatic detection methods can be improved by considering these features.

  1. A novel spatial-temporal detection method of dim infrared moving small target

    Science.gov (United States)

    Chen, Zhong; Deng, Tao; Gao, Lei; Zhou, Heng; Luo, Song

    2014-09-01

    Moving small target detection under complex background in infrared image sequence is one of the major challenges of modern military in Early Warning Systems (EWS) and the use of Long-Range Strike (LRS). However, because of the low SNR and undulating background, the infrared moving small target detection is a difficult problem in a long time. To solve this problem, a novel spatial-temporal detection method based on bi-dimensional empirical mode decomposition (EMD) and time-domain difference is proposed in this paper. This method is downright self-data decomposition and do not rely on any transition kernel function, so it has a strong adaptive capacity. Firstly, we generalized the 1D EMD algorithm to the 2D case. In this process, the project has solved serial issues in 2D EMD, such as large amount of data operations, define and identify extrema in 2D case, and two-dimensional signal boundary corrosion. The EMD algorithm studied in this project can be well adapted to the automatic detection of small targets under low SNR and complex background. Secondly, considering the characteristics of moving target, we proposed an improved filtering method based on three-frame difference on basis of the original difference filtering in time-domain, which greatly improves the ability of anti-jamming algorithm. Finally, we proposed a new time-space fusion method based on a combined processing of 2D EMD and improved time-domain differential filtering. And, experimental results show that this method works well in infrared small moving target detection under low SNR and complex background.

  2. Spatially offset Raman spectroscopy (SORS) for the analysis and detection of packaged pharmaceuticals and concealed drugs.

    Science.gov (United States)

    Olds, William J; Jaatinen, Esa; Fredericks, Peter; Cletus, Biju; Panayiotou, Helen; Izake, Emad L

    2011-10-10

    Spatially offset Raman spectroscopy (SORS) is a powerful new technique for the non-invasive detection and identification of concealed substances and drugs. Here, we demonstrate the SORS technique in several scenarios that are relevant to customs screening, postal screening, drug detection and forensics applications. The examples include analysis of a multi-layered postal package to identify a concealed substance; identification of an antibiotic capsule inside its plastic blister pack; analysis of an envelope containing a powder; and identification of a drug dissolved in a clear solvent, contained in a non-transparent plastic bottle. As well as providing practical examples of SORS, the results highlight several considerations regarding the use of SORS in the field, including the advantages of different analysis geometries and the ability to tailor instrument parameters and optics to suit different types of packages and samples. We also discuss the features and benefits of SORS in relation to existing Raman techniques, including confocal microscopy, wide area illumination and the conventional backscattered Raman spectroscopy. The results will contribute to the recognition of SORS as a promising method for the rapid, chemically specific analysis and detection of drugs and pharmaceuticals.

  3. Early Detection of Summer Crops Using High Spatial Resolution Optical Image Time Series

    Directory of Open Access Journals (Sweden)

    Claire Marais Sicre

    2016-07-01

    Full Text Available In the context of climate change, agricultural managers have the imperative to combine sufficient productivity with durability of the resources. Many studies have shown the interest of recent satellite missions as suitable tools for agricultural surveys. Nevertheless, they are not predictive methods. A system able to detect summer crops as early as possible is important in order to obtain valuable information for a better water management strategy. The detection of summer crops before the beginning of the irrigation period is therefore our objective. The study area is located near Toulouse (southwestern France, and is a region of mixed farming with a wide variety of irrigated and non-irrigated crops. Using the reference data for the years concerned, a set of fixed thresholds are applied to a vegetation index (the Normalized Difference Vegetation Index, NDVI for each agricultural season of multi-spectral satellite optical imagery acquired at decametric spatial resolutions from 2006 to 2013. The performance (i.e., accuracy is contrasted according to the agricultural practices, the development states of the different crops and the number of acquisition dates (one to three in the results presented here. The detection of summer crops reaches 64% to 88% with a single date, 80% to 88% with two dates and 90% to 99% with three dates. The robustness of this method is tested for several years (showing an impact of meteorological conditions on the actual choice of images, several sensors and several resolutions.

  4. Nanoscale avalanche photodiodes for highly sensitive and spatially resolved photon detection.

    Science.gov (United States)

    Hayden, Oliver; Agarwal, Ritesh; Lieber, Charles M

    2006-05-01

    Integrating nanophotonics with electronics could enhance and/or enable opportunities in areas ranging from communications and computing to novel diagnostics. Light sources and detectors are important elements for integration, and key progress has been made using semiconducting nanowires and carbon nanotubes to yield electrically driven sources and photoconductor detectors. Detection with photoconductors has relatively poor sensitivity at the nanometre scale, and thus large amplification is required to detect low light levels and ultimately single photons with reasonable response time. Here, we report avalanche multiplication of the photocurrent in nanoscale p-n diodes consisting of crossed silicon-cadmium sulphide nanowires. Electrical transport and optical measurements demonstrate that the nanowire avalanche photodiodes (nanoAPDs) have ultrahigh sensitivity with detection limits of less than 100 photons, and subwavelength spatial resolution of at least 250 nm. Crossed nanowire arrays also show that nanoAPDs are reproducible and can be addressed independently without cross-talk. NanoAPDs and arrays could open new opportunities for ultradense integrated systems, sensing and imaging applications.

  5. Spatial uncertainty explains exogenous and endogenous attentional cuing effects in visual signal detection.

    Science.gov (United States)

    Gould, Ian C; Wolfgang, Bradley J; Smith, Philip L

    2007-10-15

    Attentional cues may increase the detectability of a stimulus by increasing its signal-to-noise ratio (signal enhancement) or by increasing the efficiency of the observer's decision making by reducing uncertainty about the location of the stimulus (uncertainty reduction). Although signal enhancement has typically been found in detection tasks only when stimuli are backwardly masked, some recent studies have reported signal enhancement with unmasked stimuli under conditions of spatial uncertainty (E. L. Cameron, J. C. Tai, & M. Carrasco, 2002; M. Carrasco, C. Penpeci-Talgar, & M. Eckstein, 2000). To test whether these increases in sensitivity in unmasked displays were due to signal enhancement or uncertainty reduction, observers judged the orientation of unmasked Gabor patch stimuli in the presence or absence of fiducial markers that indicated their position in the display. Consistent with an uncertainty reduction hypothesis, cues produced large increases in sensitivity when stimuli were not localized perceptually but produced little or no systematic increase when they were localized by fiducial markers. The same general pattern of results was obtained with cues designed to engage the exogenous and endogenous orienting systems. The data suggest that, in practiced observers, the cuing effect for detecting unmasked stimuli is mainly due to uncertainty reduction.

  6. A hierarchical model for estimating the spatial distribution and abundance of animals detected by continuous-time recorders

    Science.gov (United States)

    Dorazio, Robert; Karanth, K. Ullas

    2017-01-01

    MotivationSeveral spatial capture-recapture (SCR) models have been developed to estimate animal abundance by analyzing the detections of individuals in a spatial array of traps. Most of these models do not use the actual dates and times of detection, even though this information is readily available when using continuous-time recorders, such as microphones or motion-activated cameras. Instead most SCR models either partition the period of trap operation into a set of subjectively chosen discrete intervals and ignore multiple detections of the same individual within each interval, or they simply use the frequency of detections during the period of trap operation and ignore the observed times of detection. Both practices make inefficient use of potentially important information in the data.Model and data analysisWe developed a hierarchical SCR model to estimate the spatial distribution and abundance of animals detected with continuous-time recorders. Our model includes two kinds of point processes: a spatial process to specify the distribution of latent activity centers of individuals within the region of sampling and a temporal process to specify temporal patterns in the detections of individuals. We illustrated this SCR model by analyzing spatial and temporal patterns evident in the camera-trap detections of tigers living in and around the Nagarahole Tiger Reserve in India. We also conducted a simulation study to examine the performance of our model when analyzing data sets of greater complexity than the tiger data.BenefitsOur approach provides three important benefits: First, it exploits all of the information in SCR data obtained using continuous-time recorders. Second, it is sufficiently versatile to allow the effects of both space use and behavior of animals to be specified as functions of covariates that vary over space and time. Third, it allows both the spatial distribution and abundance of individuals to be estimated, effectively providing a species

  7. A hierarchical model for estimating the spatial distribution and abundance of animals detected by continuous-time recorders.

    Science.gov (United States)

    Dorazio, Robert M; Karanth, K Ullas

    2017-01-01

    Several spatial capture-recapture (SCR) models have been developed to estimate animal abundance by analyzing the detections of individuals in a spatial array of traps. Most of these models do not use the actual dates and times of detection, even though this information is readily available when using continuous-time recorders, such as microphones or motion-activated cameras. Instead most SCR models either partition the period of trap operation into a set of subjectively chosen discrete intervals and ignore multiple detections of the same individual within each interval, or they simply use the frequency of detections during the period of trap operation and ignore the observed times of detection. Both practices make inefficient use of potentially important information in the data. We developed a hierarchical SCR model to estimate the spatial distribution and abundance of animals detected with continuous-time recorders. Our model includes two kinds of point processes: a spatial process to specify the distribution of latent activity centers of individuals within the region of sampling and a temporal process to specify temporal patterns in the detections of individuals. We illustrated this SCR model by analyzing spatial and temporal patterns evident in the camera-trap detections of tigers living in and around the Nagarahole Tiger Reserve in India. We also conducted a simulation study to examine the performance of our model when analyzing data sets of greater complexity than the tiger data. Our approach provides three important benefits: First, it exploits all of the information in SCR data obtained using continuous-time recorders. Second, it is sufficiently versatile to allow the effects of both space use and behavior of animals to be specified as functions of covariates that vary over space and time. Third, it allows both the spatial distribution and abundance of individuals to be estimated, effectively providing a species distribution model, even in cases where

  8. Event Detection at Vehicle Location Points using Spatial Time Invariant Model

    Directory of Open Access Journals (Sweden)

    R.C.Karpagalakshmi

    2014-05-01

    Full Text Available The localization and recognition of moving objects from single monocular intensity images has been a popular issue in image analysis and computer vision over many years. It is also one of the fundamental crisis in model based vehicle localization and recognition. The recently used scheme is model based on simple object recognition and localization of road vehicles using the position and orientation of vehicle image data. But the drawback of the approach is that the shape of the vehicle and its pose varies in multiple junction coordination, the model based recognition is an inefficient one. To overcome the issues, our first work implemented a surveillance image object recognition and localization using improved local gradient model. The vehicle-object shape recognition and pose recovery in the traffic junction is carried out for varied traffic densities. But the drawback of the approach is that it considers only the vehicle shape and pose variations in the road network and does not discuss about the occurrences of event at the vehicle junction points. Now we have to focus on the process of occurrences of event like accident met at traffic junctions. For this, in this work, spatial time invariant model is introduced to measure the event occurrences of the vehicle traffic location points. The event which has been takes place is recorded as the reference context for standardization of the traffic modality. With the reference context, the detector can easily find out the reason of the event takes place. An experimental evaluation is carried out to estimate the performance of the proposed event detection at vehicle location points using spatial time invariant model (EDSTIM in terms of spatial events, multiple time scales, traffic controlling time and compared with an existing model based on simple object recognition and localization and the previous work Surveillance of Vehicle Object Recognition and Localization.

  9. Effects of Normalized Difference Vegetation Index and Related Wavebands' Characteristics on Detecting Spatial Heterogeneity Using Variogram-based Analysis

    Institute of Scientific and Technical Information of China (English)

    WEN Zhaofei; ZHANG Ce; ZHANG Shuqing; DING Changhong; LIU Chunyue; PAN Xin; LI Huapeng; SUN Yan

    2012-01-01

    Spatial heterogeneity is widely used in diverse applications,such as recognizing ecological process,guiding ecological restoration,managing land use,etc.Many researches have focused on the inherent scale multiplicity of spatial heterogeneity by using various environmental variables.How these variables affect their corresponding spatial heterogeneities,however,have received little attention.In this paper,we examined the effects of characteristics of normalized difference vegetation index (NDVI) and its related bands variable images,namely red and near infrared (NIR),on their corresponding spatial heterogeneity detection based on variogram models.In a coastal wetland region,two groups of study sites with distinct fractal vegetation cover were tested and analyzed.The results show that:1) in high fractal vegetation cover (H-FVC) area,NDVI and NIR variables display a similar ability in detecting the spatial heterogeneity caused by vegetation growing status structure; 2) in low fractal vegetation cover (L-FVC) area,the NIR and red variables outperform NDVI in the survey of soil spatial heterogeneity; and 3) generally,NIR variable is ubiquitously applicable for vegetation spatial heterogeneity investigation in different fractal vegetation covers.Moreover,as variable selection for remote sensing applications should fully take the characteristics of variables and the study object into account,the proposed variogram analysis method can make the variable selection objectively and scientifically,especially in studies related to spatial heterogeneity using remotely sensed data.

  10. Detection of particle flow patterns in tumor by directional spatial frequency analysis

    Science.gov (United States)

    Russell, Stewart; Camara, Hawa; Shi, Lingyan; Hoopes, P. Jack; Kaufman, Peter; Pogue, Brian; Alfano, Robert

    2016-04-01

    Drug delivery to tumors is well known to be chaotic and limited, partly from dysfunctional vasculature, but also because of microscopic regional variations in composition. Modeling the of transport of nanoparticle therapeutics, therefore must include not only a description of vascular permeability, but also of the movement of the drug as suspended in tumor interstitial fluid (TIF) once it leaves the blood vessel. Understanding of this area is limited because we currently lack the tools and analytical methods to characterize it. We have previously shown that directional anisotropy of drug delivery can be detected using Directional Fourier Spatial Frequency (DFSF) Analysis. Here we extend this approach to generate flow line maps of nanoparticle transport in TIF relative to tumor ultrastructure, and show that features of tumor spatial heterogeneity can be identified that are directly related to local flow isometries. The identification of these regions of limited flow may be used as a metric for determining response to therapy, or for the optimization of adjuvant therapies such as radiation pre-treatment, or enzymatic degradation.

  11. Detecting spatial patterns with the cumulant function – Part 1: The theory

    Directory of Open Access Journals (Sweden)

    P. Naveau

    2008-02-01

    Full Text Available In climate studies, detecting spatial patterns that largely deviate from the sample mean still remains a statistical challenge. Although a Principal Component Analysis (PCA, or equivalently a Empirical Orthogonal Functions (EOF decomposition, is often applied for this purpose, it provides meaningful results only if the underlying multivariate distribution is Gaussian. Indeed, PCA is based on optimizing second order moments, and the covariance matrix captures the full dependence structure of multivariate Gaussian vectors. Whenever the application at hand can not satisfy this normality hypothesis (e.g. precipitation data, alternatives and/or improvements to PCA have to be developed and studied. To go beyond this second order statistics constraint, that limits the applicability of the PCA, we take advantage of the cumulant function that can produce higher order moments information. The cumulant function, well-known in the statistical literature, allows us to propose a new, simple and fast procedure to identify spatial patterns for non-Gaussian data. Our algorithm consists in maximizing the cumulant function. Three families of multivariate random vectors, for which explicit computations are obtained, are implemented to illustrate our approach. In addition, we show that our algorithm corresponds to selecting the directions along which projected data display the largest spread over the marginal probability density tails.

  12. NOETHERIAN GR-REGULAR RINGS ARE REGULAR

    Institute of Scientific and Technical Information of China (English)

    LIHUISHI

    1994-01-01

    It is proved that for a left Noetherian z-graded ring A,if every finitely generated graded A-module has finite projective dimension(i.e-,A is gr-regular)then every finitely generated A-module has finite projective dimension(i.e.,A is regular).Some applications of this result to filtered rings and some classical cases are also given.

  13. Temporal Data-Driven Sleep Scheduling and Spatial Data-Driven Anomaly Detection for Clustered Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Gang Li

    2016-09-01

    Full Text Available The spatial–temporal correlation is an important feature of sensor data in wireless sensor networks (WSNs. Most of the existing works based on the spatial–temporal correlation can be divided into two parts: redundancy reduction and anomaly detection. These two parts are pursued separately in existing works. In this work, the combination of temporal data-driven sleep scheduling (TDSS and spatial data-driven anomaly detection is proposed, where TDSS can reduce data redundancy. The TDSS model is inspired by transmission control protocol (TCP congestion control. Based on long and linear cluster structure in the tunnel monitoring system, cooperative TDSS and spatial data-driven anomaly detection are then proposed. To realize synchronous acquisition in the same ring for analyzing the situation of every ring, TDSS is implemented in a cooperative way in the cluster. To keep the precision of sensor data, spatial data-driven anomaly detection based on the spatial correlation and Kriging method is realized to generate an anomaly indicator. The experiment results show that cooperative TDSS can realize non-uniform sensing effectively to reduce the energy consumption. In addition, spatial data-driven anomaly detection is quite significant for maintaining and improving the precision of sensor data.

  14. Reliability and Minimum Detectable Change of Temporal-Spatial, Kinematic, and Dynamic Stability Measures during Perturbed Gait.

    Directory of Open Access Journals (Sweden)

    Christopher A Rábago

    Full Text Available Temporal-spatial, kinematic variability, and dynamic stability measures collected during perturbation-based assessment paradigms are often used to identify dysfunction associated with gait instability. However, it remains unclear which measures are most reliable for detecting and tracking responses to perturbations. This study systematically determined the between-session reliability and minimum detectable change values of temporal-spatial, kinematic variability, and dynamic stability measures during three types of perturbed gait. Twenty young healthy adults completed two identical testing sessions two weeks apart, comprised of an unperturbed and three perturbed (cognitive, physical, and visual walking conditions in a virtual reality environment. Within each session, perturbation responses were compared to unperturbed walking using paired t-tests. Between-session reliability and minimum detectable change values were also calculated for each measure and condition. All temporal-spatial, kinematic variability and dynamic stability measures demonstrated fair to excellent between-session reliability. Minimal detectable change values, normalized to mean values ranged from 1-50%. Step width mean and variability measures demonstrated the greatest response to perturbations with excellent between-session reliability and low minimum detectable change values. Orbital stability measures demonstrated specificity to perturbation direction and sensitivity with excellent between-session reliability and low minimum detectable change values. We observed substantially greater between-session reliability and lower minimum detectable change values for local stability measures than previously described which may be the result of averaging across trials within a session and using velocity versus acceleration data for reconstruction of state spaces. Across all perturbation types, temporal-spatial, orbital and local measures were the most reliable measures with the

  15. Pixels simultaneous detection probabilities and spatial resolution determination of pixelized detectors by means of correlation measurements

    CERN Document Server

    Grabskii, V

    2007-01-01

    A novel method to estimate the pixels simultaneous detection probability and the spatial resolution of pixelized detectors is proposed, which is based on the determination of the statistical correlations between detector neighbor pixels. The correlations are determined by means of noise variance measurement for a isolated pixels and the difference between neighbor pixels. The method is validated using images from the two different GE Senographe 2000D mammographic units. The pixelized detector has been irradiated using x-rays along its entire surface. It is shown that the pixel simultaneous detection probabilities can be estimated within accuracy 0.001 - 0.003, where the systematic error is estimated to be smaller than 0.005. The presampled two-dimensional point-spread function (PSF0) is determined using a single Gaussian and a sum of two Gaussian approximations. The obtained results for the presampled PSF0 show that the single Gaussian approximation is not appropriate, and the sum of two Gaussian approximatio...

  16. Joint spatial-spectral feature space clustering for speech activity detection from ECoG signals.

    Science.gov (United States)

    Kanas, Vasileios G; Mporas, Iosif; Benz, Heather L; Sgarbas, Kyriakos N; Bezerianos, Anastasios; Crone, Nathan E

    2014-04-01

    Brain-machine interfaces for speech restoration have been extensively studied for more than two decades. The success of such a system will depend in part on selecting the best brain recording sites and signal features corresponding to speech production. The purpose of this study was to detect speech activity automatically from electrocorticographic signals based on joint spatial-frequency clustering of the ECoG feature space. For this study, the ECoG signals were recorded while a subject performed two different syllable repetition tasks. We found that the optimal frequency resolution to detect speech activity from ECoG signals was 8 Hz, achieving 98.8% accuracy by employing support vector machines as a classifier. We also defined the cortical areas that held the most information about the discrimination of speech and nonspeech time intervals. Additionally, the results shed light on the distinct cortical areas associated with the two syllables repetition tasks and may contribute to the development of portable ECoG-based communication.

  17. Regular Expression Pocket Reference

    CERN Document Server

    Stubblebine, Tony

    2007-01-01

    This handy little book offers programmers a complete overview of the syntax and semantics of regular expressions that are at the heart of every text-processing application. Ideal as a quick reference, Regular Expression Pocket Reference covers the regular expression APIs for Perl 5.8, Ruby (including some upcoming 1.9 features), Java, PHP, .NET and C#, Python, vi, JavaScript, and the PCRE regular expression libraries. This concise and easy-to-use reference puts a very powerful tool for manipulating text and data right at your fingertips. Composed of a mixture of symbols and text, regular exp

  18. A microwave detection way by electromagnetic and elastic resonance: Breaking the bottleneck of spatial resolution in microwave imaging

    Science.gov (United States)

    Ji, Zhong; Lou, Cunguang; Shi, Yujiao; Ding, Wenzheng; Yang, Sihua; Xing, Da

    2015-10-01

    The spatial resolution of microwave imaging depends on the geometrical size of the detector. The existing techniques mainly focus on optimizing the antenna design to achieve high detection sensitivity. However, since the optimal antenna size is closely related to the wavelength to be measured, and the miniaturization of the geometrical size is challenging, this limits the spatial resolution of microwave imaging. In this letter, a microwave detection technique based on the electromagnetic-elastic resonance effect is proposed. The piezoelectric materials can produce mechanical responses under microwave excitation, and the amplitude of the microwave can be detected by measuring these responses. In contrast to conventional microwave detection method, the proposed method has distinct advantages in terms of high sensitivity and wide spectral response. Most importantly, it overcomes the limitation of detector size, thus, significantly improving the detection resolution. Therefore, the proposed method has potential for microwave imaging in biomedical applications.

  19. Dimensional regularization is generic

    CERN Document Server

    Fujikawa, Kazuo

    2016-01-01

    The absence of the quadratic divergence in the Higgs sector of the Standard Model in the dimensional regularization is usually regarded to be an exceptional property of a specific regularization. To understand what is going on in the dimensional regularization, we illustrate how to reproduce the results of the dimensional regularization for the $\\lambda\\phi^{4}$ theory in the more conventional regularization such as the higher derivative regularization; the basic postulate involved is that the quadratically divergent induced mass, which is independent of the scale change of the physical mass, is kinematical and unphysical. This is consistent with the derivation of the Callan-Symanzik equation, which is a comparison of two theories with slightly different masses, for the $\\lambda\\phi^{4}$ theory without encountering the quadratic divergence. We thus suggest that the dimensional regularization is generic in a bottom-up approach starting with a successful low-energy theory. We also define a modified version of t...

  20. Major Depression Detection from EEG Signals Using Kernel Eigen-Filter-Bank Common Spatial Patterns

    Directory of Open Access Journals (Sweden)

    Shih-Cheng Liao

    2017-06-01

    Full Text Available Major depressive disorder (MDD has become a leading contributor to the global burden of disease; however, there are currently no reliable biological markers or physiological measurements for efficiently and effectively dissecting the heterogeneity of MDD. Here we propose a novel method based on scalp electroencephalography (EEG signals and a robust spectral-spatial EEG feature extractor called kernel eigen-filter-bank common spatial pattern (KEFB-CSP. The KEFB-CSP first filters the multi-channel raw EEG signals into a set of frequency sub-bands covering the range from theta to gamma bands, then spatially transforms the EEG signals of each sub-band from the original sensor space to a new space where the new signals (i.e., CSPs are optimal for the classification between MDD and healthy controls, and finally applies the kernel principal component analysis (kernel PCA to transform the vector containing the CSPs from all frequency sub-bands to a lower-dimensional feature vector called KEFB-CSP. Twelve patients with MDD and twelve healthy controls participated in this study, and from each participant we collected 54 resting-state EEGs of 6 s length (5 min and 24 s in total. Our results show that the proposed KEFB-CSP outperforms other EEG features including the powers of EEG frequency bands, and fractal dimension, which had been widely applied in previous EEG-based depression detection studies. The results also reveal that the 8 electrodes from the temporal areas gave higher accuracies than other scalp areas. The KEFB-CSP was able to achieve an average EEG classification accuracy of 81.23% in single-trial analysis when only the 8-electrode EEGs of the temporal area and a support vector machine (SVM classifier were used. We also designed a voting-based leave-one-participant-out procedure to test the participant-independent individual classification accuracy. The voting-based results show that the mean classification accuracy of about 80% can be

  1. Tomographic laser absorption spectroscopy using Tikhonov regularization.

    Science.gov (United States)

    Guha, Avishek; Schoegl, Ingmar

    2014-12-01

    The application of tunable diode laser absorption spectroscopy (TDLAS) to flames with nonhomogeneous temperature and concentration fields is an area where only few studies exist. Experimental work explores the performance of tomographic reconstructions of species concentration and temperature profiles from wavelength-modulated TDLAS measurements within the plume of an axisymmetric McKenna burner. Water vapor transitions at 1391.67 and 1442.67 nm are probed using calibration-free wavelength modulation spectroscopy with second harmonic detection (WMS-2f). A single collimated laser beam is swept parallel to the burner surface, where scans yield pairs of line-of-sight (LOS) data at multiple radial locations. Radial profiles of absorption data are reconstructed using Tikhonov regularized Abel inversion, which suppresses the amplification of experimental noise that is typically observed for reconstructions with high spatial resolution. Based on spectral data reconstructions, temperatures and mole fractions are calculated point-by-point. Here, a least-squares approach addresses difficulties due to modulation depths that cannot be universally optimized due to a nonuniform domain. Experimental results show successful reconstructions of temperature and mole fraction profiles based on two-transition, nonoptimally modulated WMS-2f and Tikhonov regularized Abel inversion, and thus validate the technique as a viable diagnostic tool for flame measurements.

  2. Pan-European modelling of riverine nutrient concentrations - spatial patterns, source detection, trend analyses, scenario modelling

    Science.gov (United States)

    Bartosova, Alena; Arheimer, Berit; Capell, Rene; Donnelly, Chantal; Strömqvist, Johan

    2016-04-01

    Nutrient transport models are important tools for large scale assessments of macro-nutrient fluxes (nitrogen, phosphorus) and thus can serve as support tool for environmental assessment and management. Results from model applications over large areas, i.e. from major river basin to continental scales can fill a gap where monitoring data is not available. Here, we present results from the pan-European rainfall-runoff and nutrient transfer model E-HYPE, which is based on open data sources. We investigate the ability of the E-HYPE model to replicate the spatial and temporal variations found in observed time-series of riverine N and P concentrations, and illustrate the model usefulness for nutrient source detection, trend analyses, and scenario modelling. The results show spatial patterns in N concentration in rivers across Europe which can be used to further our understanding of nutrient issues across the European continent. E-HYPE results show hot spots with highest concentrations of total nitrogen in Western Europe along the North Sea coast. Source apportionment was performed to rank sources of nutrient inflow from land to sea along the European coast. An integrated dynamic model as E-HYPE also allows us to investigate impacts of climate change and measure programs, which was illustrated in a couple of scenarios for the Baltic Sea. Comparing model results with observations shows large uncertainty in many of the data sets and the assumptions used in the model set-up, e.g. point source release estimates. However, evaluation of model performance at a number of measurement sites in Europe shows that mean N concentration levels are generally well simulated. P levels are less well predicted which is expected as the variability of P concentrations in both time and space is higher. Comparing model performance with model set-ups using local data for the Weaver River (UK) did not result in systematically better model performance which highlights the complexity of model

  3. A comparison of spatial clustering and cluster detection techniques for childhood leukemia incidence in Ohio, 1996 – 2003

    Directory of Open Access Journals (Sweden)

    Wheeler David C

    2007-03-01

    Full Text Available Abstract Background Spatial cluster detection is an important tool in cancer surveillance to identify areas of elevated risk and to generate hypotheses about cancer etiology. There are many cluster detection methods used in spatial epidemiology to investigate suspicious groupings of cancer occurrences in regional count data and case-control data, where controls are sampled from the at-risk population. Numerous studies in the literature have focused on childhood leukemia because of its relatively large incidence among children compared with other malignant diseases and substantial public concern over elevated leukemia incidence. The main focus of this paper is an analysis of the spatial distribution of leukemia incidence among children from 0 to 14 years of age in Ohio from 1996–2003 using individual case data from the Ohio Cancer Incidence Surveillance System (OCISS. Specifically, we explore whether there is statistically significant global clustering and if there are statistically significant local clusters of individual leukemia cases in Ohio using numerous published methods of spatial cluster detection, including spatial point process summary methods, a nearest neighbor method, and a local rate scanning method. We use the K function, Cuzick and Edward's method, and the kernel intensity function to test for significant global clustering and the kernel intensity function and Kulldorff's spatial scan statistic in SaTScan to test for significant local clusters. Results We found some evidence, although inconclusive, of significant local clusters in childhood leukemia in Ohio, but no significant overall clustering. The findings from the local cluster detection analyses are not consistent for the different cluster detection techniques, where the spatial scan method in SaTScan does not find statistically significant local clusters, while the kernel intensity function method suggests statistically significant clusters in areas of central, southern

  4. A spatial hazard model for cluster detection on continuous indicators of disease: application to somatic cell score.

    Science.gov (United States)

    Gay, Emilie; Senoussi, Rachid; Barnouin, Jacques

    2007-01-01

    Methods for spatial cluster detection dealing with diseases quantified by continuous variables are few, whereas several diseases are better approached by continuous indicators. For example, subclinical mastitis of the dairy cow is evaluated using a continuous marker of udder inflammation, the somatic cell score (SCS). Consequently, this study proposed to analyze spatialized risk and cluster components of herd SCS through a new method based on a spatial hazard model. The dataset included annual SCS for 34 142 French dairy herds for the year 2000, and important SCS risk factors: mean parity, percentage of winter and spring calvings, and herd size. The model allowed the simultaneous estimation of the effects of known risk factors and of potential spatial clusters on SCS, and the mapping of the estimated clusters and their range. Mean parity and winter and spring calvings were significantly associated with subclinical mastitis risk. The model with the presence of 3 clusters was highly significant, and the 3 clusters were attractive, i.e. closeness to cluster center increased the occurrence of high SCS. The three localizations were the following: close to the city of Troyes in the northeast of France; around the city of Limoges in the center-west; and in the southwest close to the city of Tarbes. The semi-parametric method based on spatial hazard modeling applies to continuous variables, and takes account of both risk factors and potential heterogeneity of the background population. This tool allows a quantitative detection but assumes a spatially specified form for clusters.

  5. Robust Sparse Analysis Regularization

    CERN Document Server

    Vaiter, Samuel; Dossal, Charles; Fadili, Jalal

    2011-01-01

    This paper studies the properties of L1-analysis regularization for the resolution of linear inverse problems. Most previous works consider sparse synthesis priors where the sparsity is measured as the L1 norm of the coefficients that synthesize the signal in a given dictionary. In contrast, the more general analysis regularization minimizes the L1 norm of the correlations between the signal and the atoms in the dictionary. The corresponding variational problem includes several well-known regularizations such as the discrete total variation and the fused lasso. We first prove that a solution of analysis regularization is a piecewise affine function of the observations. Similarly, it is a piecewise affine function of the regularization parameter. This allows us to compute the degrees of freedom associated to sparse analysis estimators. Another contribution gives a sufficient condition to ensure that a signal is the unique solution of the analysis regularization when there is no noise in the observations. The s...

  6. 软土基坑变形时空演化规律研究%A Study on the Spatial-Temporal Evolution Regularity of the Deformation of a Foundation Pit in Soft Soil

    Institute of Scientific and Technical Information of China (English)

    林志斌; 李元海; 刘继强

    2016-01-01

    软土基坑开挖引起的土工公害问题日益突出。为得到软土基坑开挖引起的基坑变形时空演化规律,文章以深圳地铁11号线前海湾站基坑工程为背景,采用FLAC3D建立考虑淤泥地层蠕变特性影响和混凝土支撑强度随时间变化的三维数值计算模型,研究分析了基坑围护结构变形、地表沉降、支撑内力等随基坑开挖的时空变化规律。研究结果表明:随着基坑的逐步开挖,基坑桩最大位移位置将逐渐下移,桩位移形态由“前倾形”变为“弓形”,桩最大位移与基坑开挖时间大致呈指数衰减关系;基坑两侧地表沉降沿横向均呈“凹槽”分布模式且在距基坑边缘约6.5 m处出现沉降最大值,该值大小与开挖时间呈线性关系。%The geotechnical hazards caused by the excavation of foundation pits in soft soil are becoming increas⁃ingly prominent. In order to obtain the spatial-temporal evolution regularity of foundation pit deformation caused by excavation in soft soil, a 3D numerical model that takes into account the influence of silt layer creep properties and the concrete brace strength changes over time was built using FLAC3D for the Qianhaiwan Station foundation pit of Shenzhen Metro Line 11. Through modelling simulations, this paper studies and analyzes the spatial-temporal evolu⁃tion regularity of the support structure deformation of a foundation pit, as well as the surface settlement and internal force of the support as it changes with excavation. The results show that: 1) the maximum displacement position of the foundation pit pile will move downward with excavation, and the pile displacement pattern will change from a"forward-shaped"one to a"bow-shaped"one;2) the maximum pile displacement approximately exhibits a tenden⁃cy of exponential decay with the passing of excavation time; 3) surface subsidences on both sides of the foundation pit present a"groove-shaped"form along the

  7. Improved contour detection model with spatial summation properties based on nonclassical receptive field

    Science.gov (United States)

    Lin, Chuan; Xu, Guili; Cao, Yijun; Liang, Chenghua; Li, Ya

    2016-07-01

    The responses of cortical neurons to a stimulus in a classical receptive field (CRF) can be modulated by stimulating the non-CRF (nCRF) of neurons in the primary visual cortex (V1). In the very early stages (at around 40 ms), a neuron in V1 exhibits strong responses to a small set of stimuli. Later, however (after 100 ms), the neurons in V1 become sensitive to the scene's global organization. As per these visual cortical mechanisms, a contour detection model based on the spatial summation properties is proposed. Unlike in previous studies, the responses of the nCRF to the higher visual cortex that results in the inhibition of the neuronal responses in the primary visual cortex by the feedback pathway are considered. In this model, the individual neurons in V1 receive global information from the higher visual cortex to participate in the inhibition process. Computationally, global Gabor energy features are involved, leading to the more coherent physiological characteristics of the nCRF. We conducted an experiment where we compared our model with those proposed by other researchers. Our model explains the role of the mutual inhibition of neurons in V1, together with an approach for object recognition in machine vision.

  8. The performance of spatially offset Raman spectroscopy for liquid explosive detection

    Science.gov (United States)

    Loeffen, Paul W.; Maskall, Guy; Bonthron, Stuart; Bloomfield, Matthew; Tombling, Craig; Matousek, Pavel

    2016-10-01

    Aviation security requirements adopted in 2014 require liquids to be screened at most airports throughout Europe, North America and Australia. Cobalt's unique Spatially Offset Raman Spectroscopy (SORS™) technology has proven extremely effective at screening liquids, aerosols and gels (LAGS) with extremely low false alarm rates. SORS is compatible with a wide range of containers, including coloured, opaque or clear plastics, glass and paper, as well as duty-free bottles in STEBs (secure tamper-evident bags). Our award-winning Insight range has been specially developed for table-top screening at security checkpoints. Insight systems use our patented SORS technology for rapid and accurate chemical analysis of substances in unopened non-metallic containers. Insight100M™ and the latest member of the range - Insight200M™ - also screen metallic containers. Our unique systems screen liquids, aerosols and gels with the highest detection capability and lowest false alarm rates of any ECAC-approved scanner, with several hundred units already in use at airports including eight of the top ten European hubs. This paper presents an analysis of real performance data for these systems.

  9. Detection of spatial correlations of fundamental plane residuals, and cosmological implications

    CERN Document Server

    Joachimi, Benjamin; Mandelbaum, Rachel

    2015-01-01

    The fundamental plane (FP) is a widely used tool to investigate the properties of early-type galaxies, and the tight relation between its parameters has spawned several cosmological applications, including its use as a distance indicator for peculiar velocity surveys and as a means to suppress intrinsic noise in cosmic size magnification measurements. Systematic trends with the large-scale structure across the FP could cause serious biases for these cosmological probes, but may also yield new insights into the early-type population. Here we report the first detection of spatial correlations among offsets in galaxy size from an FP that explicitly accounts for redshift trends, using a sample of about $95,000$ elliptical galaxies from the Sloan Digital Sky Survey. We show that these offsets correlate with the density field out to at least $10h^{-1}$Mpc at $4\\sigma$ significance in a way that cannot be explained by systematic errors in galaxy size estimates. We propose a physical explanation for the correlations ...

  10. Regular expressions cookbook

    CERN Document Server

    Goyvaerts, Jan

    2009-01-01

    This cookbook provides more than 100 recipes to help you crunch data and manipulate text with regular expressions. Every programmer can find uses for regular expressions, but their power doesn't come worry-free. Even seasoned users often suffer from poor performance, false positives, false negatives, or perplexing bugs. Regular Expressions Cookbook offers step-by-step instructions for some of the most common tasks involving this tool, with recipes for C#, Java, JavaScript, Perl, PHP, Python, Ruby, and VB.NET. With this book, you will: Understand the basics of regular expressions through a

  11. Non-Linear Detection for Joint Space-Frequency Block Coding and Spatial Multiplexing in OFDM-MIMO Systems

    DEFF Research Database (Denmark)

    Rahman, Imadur Mohamed; Marchetti, Nicola; Fitzek, Frank;

    2005-01-01

    In this work, we have analyzed a joint spatial diversity and multiplexing transmission structure for MIMO-OFDM system, where Orthogonal Space-Frequency Block Coding (OSFBC) is used across all spatial multiplexing branches. We have derived a BLAST-like non-linear Successive Interference Cancellation...... in this paper. We have found that a linear two-stage receiver for the proposed system [1] performs very close to the non-linear receiver studied in this work. Finally, we compared the system performance in spatially correlated scenario. It is found that higher amount of spatial correlation at the transmitter...... (SIC) receiver where the detection is done on subcarrier by sub-carrier basis based on both Zero Forcing (ZF) and Minimum Mean Square Error (MMSE) nulling criterion for the system. In terms of Frame Error Rate (FER), MMSE based SIC receiver performs better than all other receivers compared...

  12. Spatial distributions of photons in plastic scintillator detected by multi-anode photomultiplier for heavy-ion position determination

    Energy Technology Data Exchange (ETDEWEB)

    Omika, S. [Department of Physics, Saitama University, Saitama 338-8570 (Japan); Yamaguchi, T., E-mail: yamaguti@phy.saitama-u.ac.jp [Department of Physics, Saitama University, Saitama 338-8570 (Japan); Fukuda, M. [Department of Physics, Osaka University, Toyonaka, Osaka 560-0043 (Japan); Kitagawa, A. [National Institute of Radiological Sciences, Chiba 263-8555 (Japan); Matsunaga, S. [Department of Physics, Saitama University, Saitama 338-8570 (Japan); Nagae, D. [Institute of Physics, University of Tsukuba, Ibaraki 305-8571 (Japan); Nishimura, D. [Department of Physics, Tokyo University of Science, Noda 278-8510 (Japan); Nishimura, T. [Department of Physics, Saitama University, Saitama 338-8570 (Japan); Ozawa, A. [Institute of Physics, University of Tsukuba, Ibaraki 305-8571 (Japan); Sato, S. [National Institute of Radiological Sciences, Chiba 263-8555 (Japan); Sawahata, K. [Institute of Physics, University of Tsukuba, Ibaraki 305-8571 (Japan); Suzuki, T.; Takeuchi, Y. [Department of Physics, Saitama University, Saitama 338-8570 (Japan)

    2015-10-11

    The spatial distributions of scintillation photons in a plastic scintillation detector were measured using a multi-anode photomultiplier H7546A coupled with 1-mm-diameter optical fibers. A row of several tens of fibers connected to the scintillator generates one-dimensional spatial distributions of photons induced by the swift passage of heavy ions. The pulse heights from each channel change depending on the beam position. This can be utilized to determine the positions of the heavy ions. To test the performance of the proposed detection method, an experiment using a {sup 84}Kr beam with intermediate energies ranging from 40 to 85 MeV/nucleon was performed at the heavy-ion medical accelerator in Chiba (HIMAC). The photon spatial distributions were successfully observed. By optimizing the photomultiplier bias voltage and threshold in the pulse height analyses, a detection efficiency of 98% and a position resolution of 1.1 mm in σ were achieved simultaneously.

  13. Collapse of ordered spatial pattern in neuronal network

    Science.gov (United States)

    Song, Xinlin; Wang, Chunni; Ma, Jun; Ren, Guodong

    2016-06-01

    Spatiotemporal systems can emerge some regular spatial patterns due to self organization or under external periodical pacing while external attack or intrinsic collapse can destroy the regularity in the spatial system. For an example, the electrical activities of neurons in nervous system show regular spatial distribution under appropriate coupling and connection. It is believed that distinct regularity could be induced in the media by appropriate forcing or feedback, while a diffusive collapse induced by continuous destruction can cause breakdown of the media. In this paper, the collapse of ordered spatial distribution is investigated in a regular network of neurons (Morris-Lecar, Hindmarsh-Rose) in two-dimensional array. A stable target wave is developed regular spatial distribution emerges by imposing appropriate external forcing with diversity, or generating heterogeneity (parameter diversity in space). The diffusive invasion could be produced by continuous parameter collapse or switch in local area, e.g, the diffusive poisoning in ion channels of potassium in Morris-Lecar neurons causes breakdown in conductance of channels. It is found that target wave-dominated regularity can be suppressed when the collapsed area is diffused in random. Statistical correlation functions for sampled nodes (neurons) are defined to detect the collapse of ordered state by series analysis.

  14. Regularization in kernel learning

    CERN Document Server

    Mendelson, Shahar; 10.1214/09-AOS728

    2010-01-01

    Under mild assumptions on the kernel, we obtain the best known error rates in a regularized learning scenario taking place in the corresponding reproducing kernel Hilbert space (RKHS). The main novelty in the analysis is a proof that one can use a regularization term that grows significantly slower than the standard quadratic growth in the RKHS norm.

  15. Regular database update logics

    NARCIS (Netherlands)

    Spruit, Paul; Wieringa, Roel; Meyer, John-Jules

    2001-01-01

    We study regular first-order update logic (FUL), which is a variant of regular dynamic logic in which updates to function symbols as well as to predicate symbols are possible. We fi1rst study FUL without making assumptions about atomic updates. Second, we look at relational algebra update logic (RAU

  16. Detection of spatial frequency in brain-damaged patients: influence of hemispheric asymmetries and hemineglect

    Directory of Open Access Journals (Sweden)

    Natanael Antonio Dos Santos

    2013-04-01

    Full Text Available Hemispheric specialization for spatial frequency processing was investigated by measuring the contrast sensitivity curves of sine-wave gratings in 30 left or right brain-damaged patients using different spatial frequencies compared with healthy participants. The results showed that left brain-damaged patients were selectively impaired in processing high frequencies, whereas right brain-damaged patients were more impaired in the processing low frequencies, regardless of the presence of visuo-spatial neglect. These visual processing results can be interpreted in terms of spatial frequency discrimination, with both hemispheres participating in this process in different ways.

  17. Single-trial detection of visual evoked potentials by common spatial patterns and wavelet filtering for brain-computer interface.

    Science.gov (United States)

    Tu, Yiheng; Huang, Gan; Hung, Yeung Sam; Hu, Li; Hu, Yong; Zhang, Zhiguo

    2013-01-01

    Event-related potentials (ERPs) are widely used in brain-computer interface (BCI) systems as input signals conveying a subject's intention. A fast and reliable single-trial ERP detection method can be used to develop a BCI system with both high speed and high accuracy. However, most of single-trial ERP detection methods are developed for offline EEG analysis and thus have a high computational complexity and need manual operations. Therefore, they are not applicable to practical BCI systems, which require a low-complexity and automatic ERP detection method. This work presents a joint spatial-time-frequency filter that combines common spatial patterns (CSP) and wavelet filtering (WF) for improving the signal-to-noise (SNR) of visual evoked potentials (VEP), which can lead to a single-trial ERP-based BCI.

  18. The effects of incidentally learned temporal and spatial predictability on response times and visual fixations during target detection and discrimination.

    Directory of Open Access Journals (Sweden)

    Melissa R Beck

    Full Text Available Responses are quicker to predictable stimuli than if the time and place of appearance is uncertain. Studies that manipulate target predictability often involve overt cues to speed up response times. However, less is known about whether individuals will exhibit faster response times when target predictability is embedded within the inter-trial relationships. The current research examined the combined effects of spatial and temporal target predictability on reaction time (RT and allocation of overt attention in a sustained attention task. Participants responded as quickly as possible to stimuli while their RT and eye movements were measured. Target temporal and spatial predictability were manipulated by altering the number of: 1 different time intervals between a response and the next target; and 2 possible spatial locations of the target. The effects of target predictability on target detection (Experiment 1 and target discrimination (Experiment 2 were tested. For both experiments, shorter RTs as target predictability increased across both space and time were found. In addition, the influences of spatial and temporal target predictability on RT and the overt allocation of attention were task dependent; suggesting that effective orienting of attention relies on both spatial and temporal predictability. These results indicate that stimulus predictability can be increased without overt cues and detected purely through inter-trial relationships over the course of repeated stimulus presentations.

  19. The effects of incidentally learned temporal and spatial predictability on response times and visual fixations during target detection and discrimination.

    Science.gov (United States)

    Beck, Melissa R; Hong, S Lee; van Lamsweerde, Amanda E; Ericson, Justin M

    2014-01-01

    Responses are quicker to predictable stimuli than if the time and place of appearance is uncertain. Studies that manipulate target predictability often involve overt cues to speed up response times. However, less is known about whether individuals will exhibit faster response times when target predictability is embedded within the inter-trial relationships. The current research examined the combined effects of spatial and temporal target predictability on reaction time (RT) and allocation of overt attention in a sustained attention task. Participants responded as quickly as possible to stimuli while their RT and eye movements were measured. Target temporal and spatial predictability were manipulated by altering the number of: 1) different time intervals between a response and the next target; and 2) possible spatial locations of the target. The effects of target predictability on target detection (Experiment 1) and target discrimination (Experiment 2) were tested. For both experiments, shorter RTs as target predictability increased across both space and time were found. In addition, the influences of spatial and temporal target predictability on RT and the overt allocation of attention were task dependent; suggesting that effective orienting of attention relies on both spatial and temporal predictability. These results indicate that stimulus predictability can be increased without overt cues and detected purely through inter-trial relationships over the course of repeated stimulus presentations.

  20. Effect of harmonicity on the detection of a signal in a complex masker and on spatial release from masking.

    Directory of Open Access Journals (Sweden)

    Astrid Klinge

    Full Text Available The amount of masking of sounds from one source (signals by sounds from a competing source (maskers heavily depends on the sound characteristics of the masker and the signal and on their relative spatial location. Numerous studies investigated the ability to detect a signal in a speech or a noise masker or the effect of spatial separation of signal and masker on the amount of masking, but there is a lack of studies investigating the combined effects of many cues on the masking as is typical for natural listening situations. The current study using free-field listening systematically evaluates the combined effects of harmonicity and inharmonicity cues in multi-tone maskers and cues resulting from spatial separation of target signal and masker on the detection of a pure tone in a multi-tone or a noise masker. A linear binaural processing model was implemented to predict the masked thresholds in order to estimate whether the observed thresholds can be accounted for by energetic masking in the auditory periphery or whether other effects are involved. Thresholds were determined for combinations of two target frequencies (1 and 8 kHz, two spatial configurations (masker and target either co-located or spatially separated by 90 degrees azimuth, and five different masker types (four complex multi-tone stimuli, one noise masker. A spatial separation of target and masker resulted in a release from masking for all masker types. The amount of masking significantly depended on the masker type and frequency range. The various harmonic and inharmonic relations between target and masker or between components of the masker resulted in a complex pattern of increased or decreased masked thresholds in comparison to the predicted energetic masking. The results indicate that harmonicity cues affect the detectability of a tonal target in a complex masker.

  1. Regularization by External Variables

    DEFF Research Database (Denmark)

    Bossolini, Elena; Edwards, R.; Glendinning, P. A.

    2016-01-01

    Regularization was a big topic at the 2016 CRM Intensive Research Program on Advances in Nonsmooth Dynamics. There are many open questions concerning well known kinds of regularization (e.g., by smoothing or hysteresis). Here, we propose a framework for an alternative and important kind of regula...... of regularization, by external variables that shadow either the state or the switch of the original system. The shadow systems are derived from and inspired by various applications in electronic control, predator-prey preference, time delay, and genetic regulation....

  2. Examining the Satellite-Detected Urban Land Use Spatial Patterns Using Multidimensional Fractal Dimension Indices

    Directory of Open Access Journals (Sweden)

    Dongjie Fu

    2013-10-01

    Full Text Available Understanding the spatial patterns of urban land use at both the macro and the micro levels is a central issue in global change studies. Due to the nonlinear features associated with land use spatial patterns, it is currently necessary to provide some distinct analysis methods to analyze them across a range of remote sensing imagery resolutions. The objective of our study is to quantify urban land use patterns from various perspectives using multidimensional fractal methods. Three commonly used fractal dimensions, i.e., the boundary dimension, the radius dimension, and the information entropy dimension, are introduced as the typical indices to examine the complexity, centrality and balance of land use spatial patterns, respectively. Moreover, a new lacunarity dimension for describing the degree of self-organization of urban land use at the macro level is presented. A cloud-free Landsat ETM+ image acquired on 17 September 2010 was used to extract land use information in Wuhan, China. The results show that there are significant linear relationships represented by good statistical fitness related to these four indices. The results indicate that rapid urbanization has substantially affected the urban landscape pattern, and different land use types show different spatial patterns in response. This analysis reveals that multiple fractal/nonfractal indices provides a more comprehensive understanding of the spatial heterogeneity of urban land use spatial patterns than any single fractal dimension index. These findings can help us to gain deeper insight into the complex spatial patterns of urban land use.

  3. Temporal-spatial Distribution Regularities of Forest Fire Casualties in China%我国森林火灾中人员伤亡时空分布特征研究

    Institute of Scientific and Technical Information of China (English)

    杨光; 舒立福; 孙思琦; 邸雪颖; 刘畅

    2015-01-01

    Based on forest fire statistics (2000-2012) and typical cases available in China, and by using statistical analysis method and ARCMAP spatial analysis method, the forest fire statistics with the same period of the countries where the forest fire frequently occurred in the world are compared, and the temporal-spatial distribu-tion regularities of forest fire casualties in China are analyzed.Results indicate that the forest fires caused heavy casualties during the period of 1988-2012 in China, the proportion of forest fire casualties was much higher than that of North America in that period.There were more forest fire casualties in seriously arid years.Spring was high-occurrence seasons for forest fire casualties, and the forest fire casualties of spring account for 54.2% of the total according to the statistics of 2000-2012.March was high-occurrence months for forest fire casualties, and the for-est fire casualties of March account for 33.7% of the total according to the statistics of 1999-2012.The central and southwestern areas were densely injured areas, the forest fire casualties of the southwestern areas account for 35.5%of the total and the forest fire casualties of the center areas account for 24.3%of the total during the period of 2000-2012.The Yunnan and Hunan were densely injured provinces, the forest fire casualties were found most in Yunnan and mainly involving in minor injury, and the number of minor injury casualties in Yunnan account for 73.0%of the total during the period of 2000-2012 .%基于我国1988-2012年森林火灾统计资料及典型案例,运用统计分析方法和ARCMAP空间分析方法,对比同时期世界上几个森林火灾多发国家的统计数据,分析了我国森林火灾中人员伤亡时空特征。结果表明:1988-2012年我国森林火灾造成的人员伤亡情况较为严重,森林火灾中人员伤亡比例远高于同时期的北美国家;森林火灾中人员伤亡高发于干旱严重的年份;春

  4. Regularized maximum correntropy machine

    KAUST Repository

    Wang, Jim Jing-Yan

    2015-02-12

    In this paper we investigate the usage of regularized correntropy framework for learning of classifiers from noisy labels. The class label predictors learned by minimizing transitional loss functions are sensitive to the noisy and outlying labels of training samples, because the transitional loss functions are equally applied to all the samples. To solve this problem, we propose to learn the class label predictors by maximizing the correntropy between the predicted labels and the true labels of the training samples, under the regularized Maximum Correntropy Criteria (MCC) framework. Moreover, we regularize the predictor parameter to control the complexity of the predictor. The learning problem is formulated by an objective function considering the parameter regularization and MCC simultaneously. By optimizing the objective function alternately, we develop a novel predictor learning algorithm. The experiments on two challenging pattern classification tasks show that it significantly outperforms the machines with transitional loss functions.

  5. Regular Expression Containment

    DEFF Research Database (Denmark)

    Henglein, Fritz; Nielsen, Lasse

    2011-01-01

    We present a new sound and complete axiomatization of regular expression containment. It consists of the conventional axiomatiza- tion of concatenation, alternation, empty set and (the singleton set containing) the empty string as an idempotent semiring, the fixed- point rule E* = 1 + E × E......* for Kleene-star, and a general coin- duction rule as the only additional rule. Our axiomatization gives rise to a natural computational inter- pretation of regular expressions as simple types that represent parse trees, and of containment proofs as coercions. This gives the axiom- atization a Curry......-Howard-style constructive interpretation: Con- tainment proofs do not only certify a language-theoretic contain- ment, but, under our computational interpretation, constructively transform a membership proof of a string in one regular expres- sion into a membership proof of the same string in another regular expression. We...

  6. Sparse regularization techniques provide novel insights into outcome integration processes.

    Science.gov (United States)

    Mohr, Holger; Wolfensteller, Uta; Frimmel, Steffi; Ruge, Hannes

    2015-01-01

    By exploiting information that is contained in the spatial arrangement of neural activations, multivariate pattern analysis (MVPA) can detect distributed brain activations which are not accessible by standard univariate analysis. Recent methodological advances in MVPA regularization techniques have made it feasible to produce sparse discriminative whole-brain maps with highly specific patterns. Furthermore, the most recent refinement, the Graph Net, explicitly takes the 3D-structure of fMRI data into account. Here, these advanced classification methods were applied to a large fMRI sample (N=70) in order to gain novel insights into the functional localization of outcome integration processes. While the beneficial effect of differential outcomes is well-studied in trial-and-error learning, outcome integration in the context of instruction-based learning has remained largely unexplored. In order to examine neural processes associated with outcome integration in the context of instruction-based learning, two groups of subjects underwent functional imaging while being presented with either differential or ambiguous outcomes following the execution of varying stimulus-response instructions. While no significant univariate group differences were found in the resulting fMRI dataset, L1-regularized (sparse) classifiers performed significantly above chance and also clearly outperformed the standard L2-regularized (dense) Support Vector Machine on this whole-brain between-subject classification task. Moreover, additional L2-regularization via the Elastic Net and spatial regularization by the Graph Net improved interpretability of discriminative weight maps but were accompanied by reduced classification accuracies. Most importantly, classification based on sparse regularization facilitated the identification of highly specific regions differentially engaged under ambiguous and differential outcome conditions, comprising several prefrontal regions previously associated with

  7. Regularities of Multifractal Measures

    Indian Academy of Sciences (India)

    Hun Ki Baek

    2008-05-01

    First, we prove the decomposition theorem for the regularities of multifractal Hausdorff measure and packing measure in $\\mathbb{R}^d$. This decomposition theorem enables us to split a set into regular and irregular parts, so that we can analyze each separately, and recombine them without affecting density properties. Next, we give some properties related to multifractal Hausdorff and packing densities. Finally, we extend the density theorem in [6] to any measurable set.

  8. On Regular Linear Relations

    Institute of Scientific and Technical Information of China (English)

    T. (A)LVAREZ

    2012-01-01

    For a closed linear relation in a Banach space the concept of regularity is introduced and studied.It is shown that many of the results of Mbekhta and other authors for operators remain valid in the context of multivalued linear operators.We also extend the punctured neighbourhood theorem for operators to linear relations and as an application we obtain a characterization of semiFredholm linear relations which are regular.

  9. Shaping and detecting mid-IR light with a spatial light modulator

    CSIR Research Space (South Africa)

    Maweza, Elijah L

    2016-10-01

    Full Text Available We demonstrate the operation and calibration of a spatial light modulator in the mid-IR region by creating and measuring the modal content and wavefront of structured light fields at 2um for the first time....

  10. Spatial Resolution and Detectability Limits in Thin-Film X-Ray Microanalysis

    Science.gov (United States)

    Goldstein, J. I.; Lyman, C. E.; Zhang, Jing

    1990-01-01

    The major advantages of performing x-ray microanalysis in the analytical electron microscope (AEM) are the high compositional spatial resolution and the elemental analysis sensitivity. Unfortunately, there is usually a trade-off between these two advantages. This paper discusses the factors involved in the optimization of both spatial resolution and sensitivity during x-ray microanalysis and shows the results of such optimization experiments for several AEM instruments.

  11. Quantifying Forest Spatial Pattern Trends at Multiple Extents: An Approach to Detect Significant Changes at Different Scales

    Directory of Open Access Journals (Sweden)

    Ludovico Frate

    2014-09-01

    Full Text Available We propose a procedure to detect significant changes in forest spatial patterns and relevant scales. Our approach consists of four sequential steps. First, based on a series of multi-temporal forest maps, a set of geographic windows of increasing extents are extracted. Second, for each extent and date, specific stochastic simulations that replicate real-world spatial pattern characteristics are run. Third, by computing pattern metrics on both simulated and real maps, their empirical distributions and confidence intervals are derived. Finally, multi-temporal scalograms are built for each metric. Based on cover maps (1954, 2011 with a resolution of 10 m we analyze forest pattern changes in a central Apennines (Italy reserve at multiple spatial extents (128, 256 and 512 pixels. We identify three types of multi-temporal scalograms, depending on pattern metric behaviors, describing different dynamics of natural reforestation process. The statistical distribution and variability of pattern metrics at multiple extents offers a new and powerful tool to detect forest variations over time. Similar procedures can (i help to identify significant changes in spatial patterns and provide the bases to relate them to landscape processes; (ii minimize the bias when comparing pattern metrics at a single extent and (iii be extended to other landscapes and scales.

  12. 64-pixel NbTiN superconducting nanowire single-photon detector array for spatially resolved photon detection

    CERN Document Server

    Miki, Shigehito; Wang, Zhen; Terai, Hirotaka

    2014-01-01

    We present the characterization of two-dimensionally arranged 64-pixel NbTiN superconducting nanowire single-photon detector array for spatially resolved photon detection. NbTiN films deposited on thermally oxidized Si substrates enabled the high-yield production of high-quality SSPD pixels, and all 64 SSPD pixels showed uniform superconducting characteristics. Furthermore, all of the pixels showed single-photon sensitivity, and 60 of the 64 pixels showed a pulse generation probability higher than 90% after photon absorption. As a result of light irradiation from the single-mode optical fiber at different distances between the fiber tip and the active area, the variations of system detection efficiency in each pixel showed reasonable Gaussian distribution to represent the spatial distributions of photon flux intensity.

  13. Energy functions for regularization algorithms

    Science.gov (United States)

    Delingette, H.; Hebert, M.; Ikeuchi, K.

    1991-01-01

    Regularization techniques are widely used for inverse problem solving in computer vision such as surface reconstruction, edge detection, or optical flow estimation. Energy functions used for regularization algorithms measure how smooth a curve or surface is, and to render acceptable solutions these energies must verify certain properties such as invariance with Euclidean transformations or invariance with parameterization. The notion of smoothness energy is extended here to the notion of a differential stabilizer, and it is shown that to void the systematic underestimation of undercurvature for planar curve fitting, it is necessary that circles be the curves of maximum smoothness. A set of stabilizers is proposed that meet this condition as well as invariance with rotation and parameterization.

  14. Fractional Regularization Term for Variational Image Registration

    Directory of Open Access Journals (Sweden)

    Rafael Verdú-Monedero

    2009-01-01

    Full Text Available Image registration is a widely used task of image analysis with applications in many fields. Its classical formulation and current improvements are given in the spatial domain. In this paper a regularization term based on fractional order derivatives is formulated. This term is defined and implemented in the frequency domain by translating the energy functional into the frequency domain and obtaining the Euler-Lagrange equations which minimize it. The new regularization term leads to a simple formulation and design, being applicable to higher dimensions by using the corresponding multidimensional Fourier transform. The proposed regularization term allows for a real gradual transition from a diffusion registration to a curvature registration which is best suited to some applications and it is not possible in the spatial domain. Results with 3D actual images show the validity of this approach.

  15. Patterns of drug abuse among drug users with regular and irregular attendance for treatment as detected by comprehensive UHPLC-HR-TOF-MS.

    Science.gov (United States)

    Sundström, Mira; Pelander, Anna; Simojoki, Kaarlo; Ojanperä, Ilkka

    2016-01-01

    The most severe consequences of drug abuse include infectious diseases, overdoses, and drug-related deaths. As the range of toxicologically relevant compounds is continually changing due to the emergence of new psychoactive substances (NPS), laboratories are encountering analytical challenges. Current immunoassays are insufficient for determining the whole range of the drugs abused, and a broad-spectrum screening method is therefore needed. Here, the patterns of drug abuse in two groups of drug users were studied from urine samples using a comprehensive screening method based on high-resolution time-of-flight mass spectrometry. The two groups comprised drug abusers undergoing opioid maintenance treatment (OMT) or drug withdrawal therapy and routinely visiting a rehabilitation clinic, and drug abusers with irregular attendance at a harm reduction unit (HRU) and suspected of potential NPS abuse. Polydrug abuse was observed in both groups, but was more pronounced among the HRU subjects with a mean number of concurrent drugs per sample of 3.9, whereas among the regularly treated subjects the corresponding number was 2.1. NPS and pregabalin were more frequent among HRU subjects, and their abuse was always related to drug co-use. The most common drug combination for an HRU subject included amphetamine, cannabis, buprenorphine, benzodiazepine, and alpha-pyrrolidinovalerophenone. A typical set of drugs for treated subjects was buprenorphine, benzodiazepine, and occasionally amphetamine. Abuse of several concurrent drugs poses a higher risk of drug intoxication and a threat of premature termination of OMT. Since the subjects attending treatment used fewer concurrent drugs, this treatment could be valuable in reducing polydrug abuse.

  16. Regularized Structural Equation Modeling.

    Science.gov (United States)

    Jacobucci, Ross; Grimm, Kevin J; McArdle, John J

    A new method is proposed that extends the use of regularization in both lasso and ridge regression to structural equation models. The method is termed regularized structural equation modeling (RegSEM). RegSEM penalizes specific parameters in structural equation models, with the goal of creating easier to understand and simpler models. Although regularization has gained wide adoption in regression, very little has transferred to models with latent variables. By adding penalties to specific parameters in a structural equation model, researchers have a high level of flexibility in reducing model complexity, overcoming poor fitting models, and the creation of models that are more likely to generalize to new samples. The proposed method was evaluated through a simulation study, two illustrative examples involving a measurement model, and one empirical example involving the structural part of the model to demonstrate RegSEM's utility.

  17. Regularity of Bound States

    DEFF Research Database (Denmark)

    Faupin, Jeremy; Møller, Jacob Schach; Skibsted, Erik

    2011-01-01

    We study regularity of bound states pertaining to embedded eigenvalues of a self-adjoint operator H, with respect to an auxiliary operator A that is conjugate to H in the sense of Mourre. We work within the framework of singular Mourre theory which enables us to deal with confined massless Pauli–......–Fierz models, our primary example, and many-body AC-Stark Hamiltonians. In the simpler context of regular Mourre theory, our results boil down to an improvement of results obtained recently in [8, 9]....

  18. Manifold Regularized Reinforcement Learning.

    Science.gov (United States)

    Li, Hongliang; Liu, Derong; Wang, Ding

    2017-01-27

    This paper introduces a novel manifold regularized reinforcement learning scheme for continuous Markov decision processes. Smooth feature representations for value function approximation can be automatically learned using the unsupervised manifold regularization method. The learned features are data-driven, and can be adapted to the geometry of the state space. Furthermore, the scheme provides a direct basis representation extension for novel samples during policy learning and control. The performance of the proposed scheme is evaluated on two benchmark control tasks, i.e., the inverted pendulum and the energy storage problem. Simulation results illustrate the concepts of the proposed scheme and show that it can obtain excellent performance.

  19. Spatial Data Mining using Cluster Analysis

    Directory of Open Access Journals (Sweden)

    Ch.N.Santhosh Kumar

    2012-09-01

    Full Text Available Data mining, which is refers to as Knowledge Discovery in Databases(KDD, means a process of nontrivialexaction of implicit, previously useful and unknown information such as knowledge rules, descriptions,regularities, and major trends from large databases. Data mining is evolved in a multidisciplinary field ,including database technology, machine learning, artificial intelligence, neural network, informationretrieval, and so on. In principle data mining should be applicable to the different kind of data and databasesused in many different applications, including relational databases, transactional databases, datawarehouses, object- oriented databases, and special application- oriented databases such as spatialdatabases, temporal databases, multimedia databases, and time- series databases. Spatial data mining, alsocalled spatial mining, is data mining as applied to the spatial data or spatial databases. Spatial data are thedata that have spatial or location component, and they show the information, which is more complex thanclassical data. A spatial database stores spatial data represents by spatial data types and spatialrelationships and among data. Spatial data mining encompasses various tasks. These include spatialclassification, spatial association rule mining, spatial clustering, characteristic rules, discriminant rules,trend detection. This paper presents how spatial data mining is achieved using clustering.

  20. Spatial frequency characteristics at image decision-point locations for observers with different radiological backgrounds in lung nodule detection

    Science.gov (United States)

    Pietrzyk, Mariusz W.; Manning, David J.; Dix, Alan; Donovan, Tim

    2009-02-01

    Aim: The goal of the study is to determine the spatial frequency characteristics at locations in the image of overt and covert observers' decisions and find out if there are any similarities in different observers' groups: the same radiological experience group or the same accuracy scored level. Background: The radiological task is described as a visual searching decision making procedure involving visual perception and cognitive processing. Humans perceive the world through a number of spatial frequency channels, each sensitive to visual information carried by different spatial frequency ranges and orientations. Recent studies have shown that particular physical properties of local and global image-based elements are correlated with the performance and the level of experience of human observers in breast cancer and lung nodule detections. Neurological findings in visual perception were an inspiration for wavelet applications in vision research because the methodology tries to mimic the brain processing algorithms. Methods: The wavelet approach to the set of postero-anterior chest radiographs analysis has been used to characterize perceptual preferences observers with different levels of experience in the radiological task. Psychophysical methodology has been applied to track eye movements over the image, where particular ROIs related to the observers' fixation clusters has been analysed in the spaces frame by Daubechies functions. Results: Significance differences have been found between the spatial frequency characteristics at the location of different decisions.

  1. Improved spatial regression analysis of diffusion tensor imaging for lesion detection during longitudinal progression of multiple sclerosis in individual subjects

    Science.gov (United States)

    Liu, Bilan; Qiu, Xing; Zhu, Tong; Tian, Wei; Hu, Rui; Ekholm, Sven; Schifitto, Giovanni; Zhong, Jianhui

    2016-03-01

    Subject-specific longitudinal DTI study is vital for investigation of pathological changes of lesions and disease evolution. Spatial Regression Analysis of Diffusion tensor imaging (SPREAD) is a non-parametric permutation-based statistical framework that combines spatial regression and resampling techniques to achieve effective detection of localized longitudinal diffusion changes within the whole brain at individual level without a priori hypotheses. However, boundary blurring and dislocation limit its sensitivity, especially towards detecting lesions of irregular shapes. In the present study, we propose an improved SPREAD (dubbed improved SPREAD, or iSPREAD) method by incorporating a three-dimensional (3D) nonlinear anisotropic diffusion filtering method, which provides edge-preserving image smoothing through a nonlinear scale space approach. The statistical inference based on iSPREAD was evaluated and compared with the original SPREAD method using both simulated and in vivo human brain data. Results demonstrated that the sensitivity and accuracy of the SPREAD method has been improved substantially by adapting nonlinear anisotropic filtering. iSPREAD identifies subject-specific longitudinal changes in the brain with improved sensitivity, accuracy, and enhanced statistical power, especially when the spatial correlation is heterogeneous among neighboring image pixels in DTI.

  2. Spatial-Temporal Synchrophasor Data Characterization and Analytics in Smart Grid Fault Detection, Identification, and Impact Causal Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Huaiguang; Dai, Xiaoxiao; Gao, David Wenzhong; Zhang, Jun Jason; Zhang, Yingchen; Muljadi, Eduard

    2016-09-01

    An approach of big data characterization for smart grids (SGs) and its applications in fault detection, identification, and causal impact analysis is proposed in this paper, which aims to provide substantial data volume reduction while keeping comprehensive information from synchrophasor measurements in spatial and temporal domains. Especially, based on secondary voltage control (SVC) and local SG observation algorithm, a two-layer dynamic optimal synchrophasor measurement devices selection algorithm (OSMDSA) is proposed to determine SVC zones, their corresponding pilot buses, and the optimal synchrophasor measurement devices. Combining the two-layer dynamic OSMDSA and matching pursuit decomposition, the synchrophasor data is completely characterized in the spatial-temporal domain. To demonstrate the effectiveness of the proposed characterization approach, SG situational awareness is investigated based on hidden Markov model based fault detection and identification using the spatial-temporal characteristics generated from the reduced data. To identify the major impact buses, the weighted Granger causality for SGs is proposed to investigate the causal relationship of buses during system disturbance. The IEEE 39-bus system and IEEE 118-bus system are employed to validate and evaluate the proposed approach.

  3. Full-field, high-spatial-resolution detection of local structural damage from low-resolution random strain field measurements

    Science.gov (United States)

    Yang, Yongchao; Sun, Peng; Nagarajaiah, Satish; Bachilo, Sergei M.; Weisman, R. Bruce

    2017-07-01

    Structural damage is typically a local phenomenon that initiates and propagates within a limited area. As such high spatial resolution measurement and monitoring is often needed for accurate damage detection. This requires either significantly increased costs from denser sensor deployment in the case of global simultaneous/parallel measurements, or increased measurement time and labor in the case of global sequential measurements. This study explores the feasibility of an alternative approach to this problem: a computational solution in which a limited set of randomly positioned, low-resolution global strain measurements are used to reconstruct the full-field, high-spatial-resolution, two-dimensional (2D) strain field and rapidly detect local damage. The proposed approach exploits the implicit low-rank and sparse data structure of the 2D strain field: it is highly correlated without many edges and hence has a low-rank structure, unless damage-manifesting itself as sparse local irregularity-is present and alters such a low-rank structure slightly. Therefore, reconstruction of the full-field, high-spatial-resolution strain field from a limited set of randomly positioned low-resolution global measurements is modeled as a low-rank matrix completion framework and damage detection as a sparse decomposition formulation, enabled by emerging convex optimization techniques. Numerical simulations on a plate structure are conducted for validation. The results are discussed and a practical iterative global/local procedure is recommended. This new computational approach should enable the efficient detection of local damage using limited sets of strain measurements.

  4. Regular LAMP and fast LAMP for the detection of Xanthomonas axonopodis pv.citri%柑橘溃疡病菌的普通LAMP及快速LAMP检测方法的建立

    Institute of Scientific and Technical Information of China (English)

    张仑; 殷幼平; 吴瑜佳; 王中康

    2013-01-01

    This study is aimed to establish the regular LAMP and fast LAMP for the detection of Xanthomonas axonopodis pv.citri and make it useful for the grassroots quarantine departments.A specific region of the genome of X.axonopodis pv.citri was used for the design of regular LAMP and fast LAMP primers; the regular LAMP and fast LAMP detection system were established by optimization of reaction conditions; the specificity of the system was verified using genomic DNA of several reference strains and healthy citrus leaves by using a series of gradient dilution of DNA solution of X.axonopodis pv.citri and bacterial suspension.Bacterial suspension and DNA sensitivity of regular LAMP system reached 2.25 × 104 cfu and 2.03× 10-1 ng,respectively,while those of fast LAMP system reached 2.25 cfu and 2.03× 10-5 ng,respectively.In the specificity test,both regular LAMP and fast LAMP system showed high and identical specificity.The total time for the fast LAMP reaction was within 30 minutes,only half of that for the regular LAMP,greatly improving the efficiency of the analysis.The fast LAMP system was ten thousand times as sensitive as the regular LAMP system.Regular LAMP and fast LAMP for the detection of X.axonopodis pv.citri was successfully established.Regular LAMP and fast LAMP system provide a new,fast and easy way for the detection of X.axonopodis pv.citri.%建立柑橘溃疡病菌的普通LAMP和快速LAMP检测方法,使其能应用于基层检验检疫部门对病害的快速检测.利用柑橘溃疡病菌基因组特有的保守区域设计LAMP引物,通过优化反应条件,建立柑橘溃疡病菌的普通LAMP检测体系;在普通LAMP引物的基础上设计一对环引物,建立柑橘溃疡病菌的快速LAMP检测体系,并以多种参比菌DNA以及健康柑橘叶片基因组DNA为模板对普通LAMP和快速LAMP检测体系的特异性进行了验证,利用柑橘溃疡病菌菌液和DNA溶液梯度稀释液对普通LAMP和快速LAMP检测体系的灵敏度进

  5. Annotation of Regular Polysemy

    DEFF Research Database (Denmark)

    Martinez Alonso, Hector

    Regular polysemy has received a lot of attention from the theory of lexical semantics and from computational linguistics. However, there is no consensus on how to represent the sense of underspecified examples at the token level, namely when annotating or disambiguating senses of metonymic words...

  6. Attentional effects on preattentive vision: Spatial precues affect the detection of simple features

    NARCIS (Netherlands)

    Theeuwes, J.; Kramer, A.F.; Atchley, P.

    1999-01-01

    Most accounts of visual perception hold that the detection of primitive features occurs preattentively, in parallel across the visual field. Evidence that preattentive vision operates without attentional limitations comes from visual search tasks in which the detection of the presence or absence of

  7. Aptamer-tagged DNA origami for spatially addressable detection of aflatoxin B1.

    Science.gov (United States)

    Lu, Zhisong; Wang, Ying; Xu, Dan; Pang, Lei

    2017-01-10

    A DNA origami-based platform for detecting aflatoxin B1 has been constructed with the assistance of aptamer probes and its complementary ssDNA-modified gold nanoparticles. This work may open new horizons for the application of DNA origami in the detection of a variety of small molecules.

  8. Evaluation of high spatial resolution imaging of magnetic stray fields for early damage detection

    Science.gov (United States)

    Stegemann, Robert; Cabeza, Sandra; Pelkner, Matthias; Lyamkin, Viktor; Sonntag, Nadja; Bruno, Giovanni; Skrotzki, Birgit; Kreutzbruck, Marc

    2017-02-01

    The paper discusses the evaluation of elastic and plastic strain states in two low-carbon steels of the same steel group with high spatial resolution GMR (giant magneto resistance) sensors. The residual stress distributions of tungsten inert gas welded plates were determined by means of neutron diffraction as a reference. The normal component of local residual magnetic stray fields arise in the vicinity of the positions of maximum stress. The experiments performed on flat tensile specimen indicate that the boundaries of plastic deformations are a source of stray fields. The spatial variations of magnetic stray fields for both the weld and the tensile samples are in the order of the earths magnetic field.

  9. Regularity and predictability of human mobility in personal space.

    Directory of Open Access Journals (Sweden)

    Daniel Austin

    Full Text Available Fundamental laws governing human mobility have many important applications such as forecasting and controlling epidemics or optimizing transportation systems. These mobility patterns, studied in the context of out of home activity during travel or social interactions with observations recorded from cell phone use or diffusion of money, suggest that in extra-personal space humans follow a high degree of temporal and spatial regularity - most often in the form of time-independent universal scaling laws. Here we show that mobility patterns of older individuals in their home also show a high degree of predictability and regularity, although in a different way than has been reported for out-of-home mobility. Studying a data set of almost 15 million observations from 19 adults spanning up to 5 years of unobtrusive longitudinal home activity monitoring, we find that in-home mobility is not well represented by a universal scaling law, but that significant structure (predictability and regularity is uncovered when explicitly accounting for contextual data in a model of in-home mobility. These results suggest that human mobility in personal space is highly stereotyped, and that monitoring discontinuities in routine room-level mobility patterns may provide an opportunity to predict individual human health and functional status or detect adverse events and trends.

  10. Integrated circuit-based electrochemical sensor for spatially resolved detection of redox-active metabolites in biofilms.

    Science.gov (United States)

    Bellin, Daniel L; Sakhtah, Hassan; Rosenstein, Jacob K; Levine, Peter M; Thimot, Jordan; Emmett, Kevin; Dietrich, Lars E P; Shepard, Kenneth L

    2014-01-01

    Despite advances in monitoring spatiotemporal expression patterns of genes and proteins with fluorescent probes, direct detection of metabolites and small molecules remains challenging. A technique for spatially resolved detection of small molecules would benefit the study of redox-active metabolites that are produced by microbial biofilms and can affect their development. Here we present an integrated circuit-based electrochemical sensing platform featuring an array of working electrodes and parallel potentiostat channels. 'Images' over a 3.25 × 0.9 mm(2) area can be captured with a diffusion-limited spatial resolution of 750 μm. We demonstrate that square wave voltammetry can be used to detect, identify and quantify (for concentrations as low as 2.6 μM) four distinct redox-active metabolites called phenazines. We characterize phenazine production in both wild-type and mutant Pseudomonas aeruginosa PA14 colony biofilms, and find correlations with fluorescent reporter imaging of phenazine biosynthetic gene expression.

  11. Integrated circuit-based electrochemical sensor for spatially resolved detection of redox-active metabolites in biofilms

    Science.gov (United States)

    Bellin, Daniel L.; Sakhtah, Hassan; Rosenstein, Jacob K.; Levine, Peter M.; Thimot, Jordan; Emmett, Kevin; Dietrich, Lars E. P.; Shepard, Kenneth L.

    2014-01-01

    Despite advances in monitoring spatiotemporal expression patterns of genes and proteins with fluorescent probes, direct detection of metabolites and small molecules remains challenging. A technique for spatially resolved detection of small molecules would benefit the study of redox-active metabolites produced by microbial biofilms, which can drastically affect colony development. Here we present an integrated circuit-based electrochemical sensing platform featuring an array of working electrodes and parallel potentiostat channels. “Images” over a 3.25 × 0.9 mm area can be captured with a diffusion-limited spatial resolution of 750 μm. We demonstrate that square wave voltammetry can be used to detect, identify, and quantify (for concentrations as low as 2.6 μM) four distinct redox-active metabolites called phenazines. We characterize phenazine production in both wild-type and mutant Pseudomonas aeruginosa PA14 colony biofilms, and find correlations with fluorescent reporter imaging of phenazine biosynthetic gene expression. PMID:24510163

  12. Detection and Spatial Mapping of Anthropogenic Methane Plumes with the Hyperspectral Thermal Emission Spectrometer (HyTES)

    Science.gov (United States)

    Hulley, Glynn; Duren, Riley; Hook, Simon; Hopkins, Francesca

    2016-04-01

    Detection and Spatial Mapping of Anthropogenic Methane Plumes with the Hyperspectral Thermal Emission Spectrometer (HyTES) Glynn Hulley, Simon Hook, Riley Duren, Francesca Hopkins Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA Currently large uncertainties exist associated with attribution and quantification of fugitive emissions of greenhouse gases such as methane across many regions and key economic sectors. A number of observational efforts are currently underway to better quantify and reduce uncertainties associated with these emissions, including agriculture and oil and gas production operations. One such effort led by JPL is the development of the Hyperspectral Thermal Emission Spectrometer (HyTES) - a wide swath Thermal Infrared (TIR) airborne imager with high spectral (256 bands from 7.5 - 12 micron) and spatial resolution (~1.5 m at 1-km AGL altitude) that presents a major advance in airborne TIR remote sensing measurements. Using HyTES we have developed robust and reliable techniques for the detection and high resolution mapping of small scale plumes of anthropogenic (oil and gas fields, landfills, dairies) and non-anthropogenic (natural seeps) sources of methane in the state of California and Colorado. A background on the HyTES sensor, science objectives, gas detection methods, and examples of mapping fugitive methane plumes in California and Colorado will be discussed. These kind of observational efforts and studies will help address critical science questions related to methane budgets and management of future emissions in California and other regions.

  13. Effect of spatial noise of medical grade Liquid Crystal Displays (LCD) on the detection of micro-calcification

    Science.gov (United States)

    Roehrig, Hans; Fan, Jiahua; Dallas, William J.; Krupinski, Elizabeth A.; Johnson, Jeffrey

    2009-08-01

    This presentation describes work in progress that is the result of an NIH SBIR Phase 1 project that addresses the wide- spread concern for the large number of breast-cancers and cancer victims [1,2]. The primary goal of the project is to increase the detection rate of microcalcifications as a result of the decrease of spatial noise of the LCDs used to display the mammograms [3,4]. Noise reduction is to be accomplished with the aid of a high performance CCD camera and subsequent application of local-mean equalization and error diffusion [5,6]. A second goal of the project is the actual detection of breast cancer. Contrary to the approach to mammography, where the mammograms typically have a pixel matrix of approximately 1900 x 2300 pixels, otherwise known as FFDM or Full-Field Digital Mammograms, we will only use sections of mammograms with a pixel matrix of 256 x 256 pixels. This is because at this time, reduction of spatial noise on an LCD can only be done on relatively small areas like 256 x 256 pixels. In addition, judging the efficacy for detection of breast cancer will be done using two methods: One is a conventional ROC study [7], the other is a vision model developed over several years starting at the Sarnoff Research Center and continuing at the Siemens Corporate Research in Princeton NJ [8].

  14. Detecting spatial patterns with the cumulant function – Part 2: An application to El Niño

    Directory of Open Access Journals (Sweden)

    P. Yiou

    2008-02-01

    Full Text Available The spatial coherence of a measured variable (e.g. temperature or pressure is often studied to determine the regions of high variability or to find teleconnections, i.e. correlations between specific regions. While usual methods to find spatial patterns, such as Principal Components Analysis (PCA, are constrained by linear symmetries, the dependence of variables such as temperature or pressure at different locations is generally nonlinear. In particular, large deviations from the sample mean are expected to be strongly affected by such nonlinearities. Here we apply a newly developed nonlinear technique (Maxima of Cumulant Function, MCF for detection of typical spatial patterns that largely deviate from the mean. In order to test the technique and to introduce the methodology, we focus on the El Niño/Southern Oscillation and its spatial patterns. We find nonsymmetric temperature patterns corresponding to El Niño and La Niña, and we compare the results of MCF with other techniques, such as the symmetric solutions of PCA, and the nonsymmetric solutions of Nonlinear PCA (NLPCA. We found that MCF solutions are more reliable than the NLPCA fits, and can capture mixtures of principal components. Finally, we apply Extreme Value Theory on the temporal variations extracted from our methodology. We find that the tails of the distribution of extreme temperatures during La Niña episodes is bounded, while the tail during El Niños is less likely to be bounded. This implies that the mean spatial patterns of the two phases are asymmetric, as well as the behaviour of their extremes.

  15. Detection of Tuberculosis Infection Hotspots Using Activity Spaces Based Spatial Approach in an Urban Tokyo, from 2003 to 2011.

    Directory of Open Access Journals (Sweden)

    Kiyohiko Izumi

    Full Text Available Identifying ongoing tuberculosis infection sites is crucial for breaking chains of transmission in tuberculosis-prevalent urban areas. Previous studies have pointed out that detection of local accumulation of tuberculosis patients based on their residential addresses may be limited by a lack of matching between residences and tuberculosis infection sites. This study aimed to identify possible tuberculosis hotspots using TB genotype clustering statuses and a concept of "activity space", a place where patients spend most of their waking hours. We further compared the spatial distribution by different residential statuses and describe urban environmental features of the detected hotspots.Culture-positive tuberculosis patients notified to Shinjuku city from 2003 to 2011 were enrolled in this case-based cross-sectional study, and their demographic and clinical information, TB genotype clustering statuses, and activity space were collected. Spatial statistics (Global Moran's I and Getis-Ord Gi* statistics identified significant hotspots in 152 census tracts, and urban environmental features and tuberculosis patients' characteristics in these hotspots were assessed.Of the enrolled 643 culture-positive tuberculosis patients, 416 (64.2% were general inhabitants, 42 (6.5% were foreign-born people, and 184 were homeless people (28.6%. The percentage of overall genotype clustering was 43.7%. Genotype-clustered general inhabitants and homeless people formed significant hotspots around a major railway station, whereas the non-clustered general inhabitants formed no hotspots. This suggested the detected hotspots of activity spaces may reflect ongoing tuberculosis transmission sites and were characterized by smaller residential floor size and a higher proportion of non-working households.Activity space-based spatial analysis suggested possible TB transmission sites around the major railway station and it can assist in further comprehension of TB transmission

  16. Spatial and temporal variation and hotspot detection of kala-azar disease in Vaishali district (Bihar, India

    Directory of Open Access Journals (Sweden)

    Bhunia Gouri Sankar

    2013-02-01

    Full Text Available Abstract Background An improved understanding in transmission variation of kala-azar is fundamental to conduct surveillance and implementing disease prevention strategies. This study investigated the spatio-temporal patterns and hotspot detection for reporting kala-azar cases in Vaishali district based on spatial statistical analysis. Methods Epidemiological data from the study area during 2007–2011 was used to examine the dynamic space-time pattern of kala-azar outbreaks, and all cases were geocoded at a village level. Spatial smoothing was applied to reduce random noise in the data. Inverse distance weighting (IDW is used to interpolate and predict the pattern of VL cases distribution across the district. Moran’s I Index (Moran’s I statistics was used to evaluate autocorrelation in kala-azar spatial distribution and test how villages were clustered or dispersed in space. Getis-Ord Gi*(d was used to identify the hotspot and cold spot areas within the study site. Results Mapping kala-azar cases or incidences reflects the spatial heterogeneity in the incidence rate of kala-azar affected villages in Vaishali district. Kala-azar incidence rate map showed most of the highest endemic villages were located in southern, eastern and northwestern part of the district; in the middle part of the district generally show the medium occurrence of VL. There was a significant positive spatial autocorrelation of kala-azar incidences for five consecutive years, with Moran’s I statistic ranging from 0.04-0.17 (P P Conclusions The results pointed to the usefulness of spatial statistical approach to improve our understanding the spatio-temporal dynamics and control of kala-azar. The study also showed the north-western and southern part of Vaishali district is most likely endemic cluster region. To employ exact and geographically suitable risk-reduction programmes, apply of such spatial analysis tools should suit a vital constituent in epidemiology research

  17. Effects from Spatial Cues on Detectability of Alarm Signals in Car Environments

    OpenAIRE

    Kuroda, Naoki; Li, Junfeng; Iwaya, Yukio; Unoki, Masashi; Akagi, Masato

    2009-01-01

    It is crucial to correctly detect alarm signals in noise conditions, for instance, especially in car environments. However, alarm signals are possibly masked by noises from engine, friction between tires and road, etc., in car environments. To design the alarm signals that can be easily detected,it is necessary to first understand the perceptual characteristics of alarm signals in noisy environments. In this paper, the masked thresholds of alarm signals in the presence of car noise were measu...

  18. Spatial Support Vector Regression to Detect Silent Errors in the Exascale Era

    Energy Technology Data Exchange (ETDEWEB)

    Subasi, Omer; Di, Sheng; Bautista-Gomez, Leonardo; Balaprakash, Prasanna; Unsal, Osman; Labarta, Jesus; Cristal, Adrian; Cappello, Franck

    2016-01-01

    As the exascale era approaches, the increasing capacity of high-performance computing (HPC) systems with targeted power and energy budget goals introduces significant challenges in reliability. Silent data corruptions (SDCs) or silent errors are one of the major sources that corrupt the executionresults of HPC applications without being detected. In this work, we explore a low-memory-overhead SDC detector, by leveraging epsilon-insensitive support vector machine regression, to detect SDCs that occur in HPC applications that can be characterized by an impact error bound. The key contributions are three fold. (1) Our design takes spatialfeatures (i.e., neighbouring data values for each data point in a snapshot) into training data, such that little memory overhead (less than 1%) is introduced. (2) We provide an in-depth study on the detection ability and performance with different parameters, and we optimize the detection range carefully. (3) Experiments with eight real-world HPC applications show thatour detector can achieve the detection sensitivity (i.e., recall) up to 99% yet suffer a less than 1% of false positive rate for most cases. Our detector incurs low performance overhead, 5% on average, for all benchmarks studied in the paper. Compared with other state-of-the-art techniques, our detector exhibits the best tradeoff considering the detection ability and overheads.

  19. Spatial Fourier Analysis of a Free-Free Beam for Structural Damage Detection

    Science.gov (United States)

    Bhagat, Mihir; Ganguli, Ranjan

    2014-07-01

    Free-free beams (FFB) are used to model many structures, such as missiles, rockets, MEMS (Micro Electro Mechanical Systems), etc. This paper aims to illustrate a novel structural health monitoring method-Fourier analysis of mode shapes of damaged beams-and extend it to the case of FFB. The damaged mode shapes of FFB are obtained by a finite element model and then studied using spatial Fourier analysis. The effect of noise in the mode shape data is considered and it is found that the Fourier coefficients provide a useful indication about the location and size of damage.

  20. Sparse structure regularized ranking

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-04-17

    Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse structure, we assume that each multimedia object could be represented as a sparse linear combination of all other objects, and combination coefficients are regarded as a similarity measure between objects and used to regularize their ranking scores. Moreover, we propose to learn the sparse combination coefficients and the ranking scores simultaneously. A unified objective function is constructed with regard to both the combination coefficients and the ranking scores, and is optimized by an iterative algorithm. Experiments on two multimedia database retrieval data sets demonstrate the significant improvements of the propose algorithm over state-of-the-art ranking score learning algorithms.

  1. Regularizing portfolio optimization

    Science.gov (United States)

    Still, Susanne; Kondor, Imre

    2010-07-01

    The optimization of large portfolios displays an inherent instability due to estimation error. This poses a fundamental problem, because solutions that are not stable under sample fluctuations may look optimal for a given sample, but are, in effect, very far from optimal with respect to the average risk. In this paper, we approach the problem from the point of view of statistical learning theory. The occurrence of the instability is intimately related to over-fitting, which can be avoided using known regularization methods. We show how regularized portfolio optimization with the expected shortfall as a risk measure is related to support vector regression. The budget constraint dictates a modification. We present the resulting optimization problem and discuss the solution. The L2 norm of the weight vector is used as a regularizer, which corresponds to a diversification 'pressure'. This means that diversification, besides counteracting downward fluctuations in some assets by upward fluctuations in others, is also crucial because it improves the stability of the solution. The approach we provide here allows for the simultaneous treatment of optimization and diversification in one framework that enables the investor to trade off between the two, depending on the size of the available dataset.

  2. Detection and spatial mapping of mercury contamination in water samples using a smart-phone.

    Science.gov (United States)

    Wei, Qingshan; Nagi, Richie; Sadeghi, Kayvon; Feng, Steve; Yan, Eddie; Ki, So Jung; Caire, Romain; Tseng, Derek; Ozcan, Aydogan

    2014-02-25

    Detection of environmental contamination such as trace-level toxic heavy metal ions mostly relies on bulky and costly analytical instruments. However, a considerable global need exists for portable, rapid, specific, sensitive, and cost-effective detection techniques that can be used in resource-limited and field settings. Here we introduce a smart-phone-based hand-held platform that allows the quantification of mercury(II) ions in water samples with parts per billion (ppb) level of sensitivity. For this task, we created an integrated opto-mechanical attachment to the built-in camera module of a smart-phone to digitally quantify mercury concentration using a plasmonic gold nanoparticle (Au NP) and aptamer based colorimetric transmission assay that is implemented in disposable test tubes. With this smart-phone attachment that weighs smart application was utilized to process each acquired transmission image on the same phone to achieve a limit of detection of ∼ 3.5 ppb. Using this smart-phone-based detection platform, we generated a mercury contamination map by measuring water samples at over 50 locations in California (USA), taken from city tap water sources, rivers, lakes, and beaches. With its cost-effective design, field-portability, and wireless data connectivity, this sensitive and specific heavy metal detection platform running on cellphones could be rather useful for distributed sensing, tracking, and sharing of water contamination information as a function of both space and time.

  3. Locating Sensors for Detecting Source-to-Target Patterns of Special Nuclear Material Smuggling: A Spatial Information Theoretic Approach

    Directory of Open Access Journals (Sweden)

    Xuesong Zhou

    2010-08-01

    Full Text Available In this paper, a spatial information-theoretic model is proposed to locate sensors for detecting source-to-target patterns of special nuclear material (SNM smuggling. In order to ship the nuclear materials from a source location with SNM production to a target city, the smugglers must employ global and domestic logistics systems. This paper focuses on locating a limited set of fixed and mobile radiation sensors in a transportation network, with the intent to maximize the expected information gain and minimize the estimation error for the subsequent nuclear material detection stage. A Kalman filtering-based framework is adapted to assist the decision-maker in quantifying the network-wide information gain and SNM flow estimation accuracy.

  4. Locating sensors for detecting source-to-target patterns of special nuclear material smuggling: a spatial information theoretic approach.

    Science.gov (United States)

    Przybyla, Jay; Taylor, Jeffrey; Zhou, Xuesong

    2010-01-01

    In this paper, a spatial information-theoretic model is proposed to locate sensors for detecting source-to-target patterns of special nuclear material (SNM) smuggling. In order to ship the nuclear materials from a source location with SNM production to a target city, the smugglers must employ global and domestic logistics systems. This paper focuses on locating a limited set of fixed and mobile radiation sensors in a transportation network, with the intent to maximize the expected information gain and minimize the estimation error for the subsequent nuclear material detection stage. A Kalman filtering-based framework is adapted to assist the decision-maker in quantifying the network-wide information gain and SNM flow estimation accuracy.

  5. Detecting defective electrical components in heterogeneous infra-red images by spatial control charts

    Science.gov (United States)

    Jamshidieini, Bahman; Fazaee, Reza

    2016-05-01

    Distribution network components connect machines and other loads to electrical sources. If resistance or current of any component is more than specified range, its temperature may exceed the operational limit which can cause major problems. Therefore, these defects should be found and eliminated according to their severity. Although infra-red cameras have been used for inspection of electrical components, maintenance prioritization of distribution cubicles is mostly based on personal perception and lack of training data prevents engineers from developing image processing methods. New research on the spatial control chart encouraged us to use statistical approaches instead of the pattern recognition for the image processing. In the present study, a new scanning pattern which can tolerate heavy autocorrelation among adjacent pixels within infra-red image was developed and for the first time combination of kernel smoothing, spatial control charts and local robust regression were used for finding defects within heterogeneous infra-red images of old distribution cubicles. This method does not need training data and this advantage is crucially important when the training data is not available.

  6. Catching ghosts with a coarse net: use and abuse of spatial sampling data in detecting synchronization.

    Science.gov (United States)

    Petrovskaya, Natalia; Petrovskii, Sergei

    2017-02-01

    Synchronization of population dynamics in different habitats is a frequently observed phenomenon. A common mathematical tool to reveal synchronization is the (cross)correlation coefficient between time courses of values of the population size of a given species where the population size is evaluated from spatial sampling data. The corresponding sampling net or grid is often coarse, i.e. it does not resolve all details of the spatial configuration, and the evaluation error-i.e. the difference between the true value of the population size and its estimated value-can be considerable. We show that this estimation error can make the value of the correlation coefficient very inaccurate or even irrelevant. We consider several population models to show that the value of the correlation coefficient calculated on a coarse sampling grid rarely exceeds 0.5, even if the true value is close to 1, so that the synchronization is effectively lost. We also observe 'ghost synchronization' when the correlation coefficient calculated on a coarse sampling grid is close to 1 but in reality the dynamics are not correlated. Finally, we suggest a simple test to check the sampling grid coarseness and hence to distinguish between the true and artifactual values of the correlation coefficient.

  7. k-Walk-Regular Digraphs

    Institute of Scientific and Technical Information of China (English)

    Wen LIU; Jing LIN

    2011-01-01

    In this paper,we define a class of strongly connected digraph,called the k-walk-regular digraph,study some properties of it,provide its some algebraic characterization and point out that the O-walk-regular digraph is the same as the walk-regular digraph discussed BY Liu and Lin in 2010 and the D-walk-regular digraph is identical with the weakly distance-regular digraph defined by Comellas et al in 2004.

  8. Multispectral band selection and spatial characterization: Application to mitosis detection in breast cancer histopathology.

    Science.gov (United States)

    Irshad, H; Gouaillard, A; Roux, L; Racoceanu, D

    2014-07-01

    Breast cancer is the second most frequent cancer. The reference process for breast cancer prognosis is Nottingham grading system. According to this system, mitosis detection is one of the three important criteria required for grading process and quantifying the locality and prognosis of a tumor. Multispectral imaging, as relatively new to the field of histopathology, has the advantage, over traditional RGB imaging, to capture spectrally resolved information at specific frequencies, across the electromagnetic spectrum. This study aims at evaluating the accuracy of mitosis detection on histopathological multispectral images. The proposed framework includes: selection of spectral bands and focal planes, detection of candidate mitotic regions and computation of morphological and multispectral statistical features. A state-of-the-art of the methods for mitosis classification is also provided. This framework has been evaluated on MITOS multispectral dataset and achieved higher detection rate (67.35%) and F-Measure (63.74%) than the best MITOS contest results (Roux et al., 2013). Our results indicate that the selected multispectral bands have more discriminant information than a single spectral band or all spectral bands for mitotic figures, validating the interest of using multispectral images to improve the quality of the diagnostic in histopathology. Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. Detection of User Independent Single Trial ERPs in Brain Computer Interfaces: An Adaptive Spatial Filtering Approach

    DEFF Research Database (Denmark)

    Leza, Cristina; Puthusserypady, Sadasivan

    2017-01-01

    Brain Computer Interfaces (BCIs) use brain signals to communicate with the external world. The main challenges to address are speed, accuracy and adaptability. Here, a novel algorithm for P300 based BCI spelling system is presented, specifically suited for single-trial detection of Event...

  10. A novel edge detection in medical images by fusing of multi-model from different spatial structure clues.

    Science.gov (United States)

    Jia, Xibin; Huang, Haiyong; Wang, Runyuan

    2014-01-01

    Edge detection has been widely used in medical image processing, automatic diagnosis, et al. A novel edge detection algorithm, based on the fusion model, is proposed by combination with the two proposed models as follows: the matrix of most probable distribution of edge point and the matrix of the difference weight of each point. The most probable distribution of edge point can be obtained by analyzing the variance among 4-connected neighborhood points around each pixel under estimation in the image to label the all candidate edge points in the image. The difference weight of each point can be gotten by analyzing the brightness difference between the neighborhood point and the under-estimating pixel to represent the probability of being edge. The two matrices gotten from the different descriptions of spatial structure are fused together and derive from the final edge image with thresholding method on the fusion matrix. The experiments are performed based on the public diabetic retinopathy database DRIVE. According to the edge images obtained, the proposed method is subjectively analyzed to be complete and close to the Ground Truth image with very low noise in comparison with the Sobel, Canny and LOG edge detectors. The F1 measure, ROC measure and PFOM measure are separately adopted to make quantitative evaluation of the proposed edge detection algorithm. Experimental results show that the proposed method is able to improve the effect of edge detection on medical images.

  11. Low contrast detectability and spatial resolution with model-based iterative reconstructions of MDCT images: a phantom and cadaveric study

    Energy Technology Data Exchange (ETDEWEB)

    Millon, Domitille; Coche, Emmanuel E. [Universite Catholique de Louvain, Department of Radiology and Medical Imaging, Cliniques Universitaires Saint Luc, Brussels (Belgium); Vlassenbroek, Alain [Philips Healthcare, Brussels (Belgium); Maanen, Aline G. van; Cambier, Samantha E. [Universite Catholique de Louvain, Statistics Unit, King Albert II Cancer Institute, Brussels (Belgium)

    2017-03-15

    To compare image quality [low contrast (LC) detectability, noise, contrast-to-noise (CNR) and spatial resolution (SR)] of MDCT images reconstructed with an iterative reconstruction (IR) algorithm and a filtered back projection (FBP) algorithm. The experimental study was performed on a 256-slice MDCT. LC detectability, noise, CNR and SR were measured on a Catphan phantom scanned with decreasing doses (48.8 down to 0.7 mGy) and parameters typical of a chest CT examination. Images were reconstructed with FBP and a model-based IR algorithm. Additionally, human chest cadavers were scanned and reconstructed using the same technical parameters. Images were analyzed to illustrate the phantom results. LC detectability and noise were statistically significantly different between the techniques, supporting model-based IR algorithm (p < 0.0001). At low doses, the noise in FBP images only enabled SR measurements of high contrast objects. The superior CNR of model-based IR algorithm enabled lower dose measurements, which showed that SR was dose and contrast dependent. Cadaver images reconstructed with model-based IR illustrated that visibility and delineation of anatomical structure edges could be deteriorated at low doses. Model-based IR improved LC detectability and enabled dose reduction. At low dose, SR became dose and contrast dependent. (orig.)

  12. Beyond Space For Spatial Networks

    CERN Document Server

    Expert, Paul; Blondel, Vincent D; Lambiotte, Renaud

    2010-01-01

    Many complex systems are organized in the form of a network embedded in space. Important examples include the physical Internet infrastucture, road networks, flight connections, brain functional networks and social networks. The effect of space on network topology has recently come under the spotlight because of the emergence of pervasive technologies based on geo-localization, which constantly fill databases with people's movements and thus reveal their trajectories and spatial behaviour. Extracting patterns and regularities from the resulting massive amount of human mobility data requires the development of appropriate tools for uncovering information in spatially-embedded networks. In contrast with most works that tend to apply standard network metrics to any type of network, we argue in this paper for a careful treatment of the constraints imposed by space on network topology. In particular, we focus on the problem of community detection and propose a modularity function adapted to spatial networks. We sh...

  13. Detecting the Land-Cover Changes Induced by Large-Physical Disturbances Using Landscape Metrics, Spatial Sampling, Simulation and Spatial Analysis

    Directory of Open Access Journals (Sweden)

    Hone-Jay Chu

    2009-08-01

    Full Text Available The objectives of the study are to integrate the conditional Latin Hypercube Sampling (cLHS, sequential Gaussian simulation (SGS and spatial analysis in remotely sensed images, to monitor the effects of large chronological disturbances on spatial characteristics of landscape changes including spatial heterogeneity and variability. The multiple NDVI images demonstrate that spatial patterns of disturbed landscapes were successfully delineated by spatial analysis such as variogram, Moran’I and landscape metrics in the study area. The hybrid method delineates the spatial patterns and spatial variability of landscapes caused by these large disturbances. The cLHS approach is applied to select samples from Normalized Difference Vegetation Index (NDVI images from SPOT HRV images in the Chenyulan watershed of Taiwan, and then SGS with sufficient samples is used to generate maps of NDVI images. In final, the NDVI simulated maps are verified using indexes such as the correlation coefficient and mean absolute error (MAE. Therefore, the statistics and spatial structures of multiple NDVI images present a very robust behavior, which advocates the use of the index for the quantification of the landscape spatial patterns and land cover change. In addition, the results transferred by Open Geospatial techniques can be accessed from web-based and end-user applications of the watershed management.

  14. Detection of Spatially Unresolved (Nominally Sub-Pixel) Submerged and Surface Targets Using Hyperspectral Data

    Science.gov (United States)

    2012-09-01

    to improve the performance of the RXD (Chang & Chiang, 2002). This RXD-UTD method was shown to be effective by Ashton and Schaum (1998) and...Model algorithm, a 29 modified version of the Finite Target Matched Filter model designed by Stocker and Schaum (1997). This real-time automated...731–739). Orlando, FL, USA. Ashton, E.A. & Schaum , A. (1998). Algorithms for the detection of sub-pixel targets in multispectral imagery

  15. Annotation of Regular Polysemy

    DEFF Research Database (Denmark)

    Martinez Alonso, Hector

    Regular polysemy has received a lot of attention from the theory of lexical semantics and from computational linguistics. However, there is no consensus on how to represent the sense of underspecified examples at the token level, namely when annotating or disambiguating senses of metonymic words...... like “London” (Location/Organization) or “cup” (Container/Content). The goal of this dissertation is to assess whether metonymic sense underspecification justifies incorporating a third sense into our sense inventories, thereby treating the underspecified sense as independent from the literal...

  16. From regular modules to von Neumann regular rings via coordinatization

    Directory of Open Access Journals (Sweden)

    Leonard Daus

    2014-07-01

    Full Text Available In this paper we establish a very close link (in terms of von Neu- mann's coordinatization between regular modules introduced by Zel- manowitz, on one hand, and von Neumann regular rings, on the other hand: we prove that the lattice L^{fg}(M of all finitely generated submodules of a finitely generated regular module M, over an arbitrary ring, can be coordinatized as the lattice of all principal right ideals of some von Neumann regular ring S.

  17. Detection of Self Incompatibility Genotypes in Prunus africana: Characterization, Evolution and Spatial Analysis.

    Directory of Open Access Journals (Sweden)

    Judith Ssali Nantongo

    Full Text Available In flowering plants, self-incompatibility is an effective genetic mechanism that prevents self-fertilization. Most Prunus tree species exhibit a homomorphic gametophytic self-incompatibility (GSI system, in which the pollen phenotype is encoded by its own haploid genome. To date, no identification of S-alleles had been done in Prunus africana, the only member of the genus in Africa. To identify S-RNase alleles and hence determine S-genotypes in African cherry (Prunus africana from Mabira Forest Reserve, Uganda, primers flanking the first and second intron were designed and these amplified two bands in most individuals. PCR bands on agarose indicated 26 and 8 different S-alleles for second and first intron respectively. Partial or full sequences were obtained for all these fragments. Comparison with published S-RNase data indicated that the amplified products were S-RNase alleles with very high interspecies homology despite the high intraspecific variation. Against expectations for a locus under balancing selection, frequency and spatial distribution of the alleles in a study plot was not random. Implications of the results to breeding efforts in the species are discussed, and mating experiments are strongly suggested to finally prove the functionality of SI in P. africana.

  18. Detection of Self Incompatibility Genotypes in Prunus africana: Characterization, Evolution and Spatial Analysis.

    Science.gov (United States)

    Nantongo, Judith Ssali; Eilu, Gerald; Geburek, Thomas; Schueler, Silvio; Konrad, Heino

    2016-01-01

    In flowering plants, self-incompatibility is an effective genetic mechanism that prevents self-fertilization. Most Prunus tree species exhibit a homomorphic gametophytic self-incompatibility (GSI) system, in which the pollen phenotype is encoded by its own haploid genome. To date, no identification of S-alleles had been done in Prunus africana, the only member of the genus in Africa. To identify S-RNase alleles and hence determine S-genotypes in African cherry (Prunus africana) from Mabira Forest Reserve, Uganda, primers flanking the first and second intron were designed and these amplified two bands in most individuals. PCR bands on agarose indicated 26 and 8 different S-alleles for second and first intron respectively. Partial or full sequences were obtained for all these fragments. Comparison with published S-RNase data indicated that the amplified products were S-RNase alleles with very high interspecies homology despite the high intraspecific variation. Against expectations for a locus under balancing selection, frequency and spatial distribution of the alleles in a study plot was not random. Implications of the results to breeding efforts in the species are discussed, and mating experiments are strongly suggested to finally prove the functionality of SI in P. africana.

  19. Modular Regularization Algorithms

    DEFF Research Database (Denmark)

    Jacobsen, Michael

    2004-01-01

    The class of linear ill-posed problems is introduced along with a range of standard numerical tools and basic concepts from linear algebra, statistics and optimization. Known algorithms for solving linear inverse ill-posed problems are analyzed to determine how they can be decomposed into indepen......The class of linear ill-posed problems is introduced along with a range of standard numerical tools and basic concepts from linear algebra, statistics and optimization. Known algorithms for solving linear inverse ill-posed problems are analyzed to determine how they can be decomposed...... into independent modules. These modules are then combined to form new regularization algorithms with other properties than those we started out with. Several variations are tested using the Matlab toolbox MOORe Tools created in connection with this thesis. Object oriented programming techniques are explained...... and used to set up the illposed problems in the toolbox. Hereby, we are able to write regularization algorithms that automatically exploit structure in the ill-posed problem without being rewritten explicitly. We explain how to implement a stopping criteria for a parameter choice method based upon...

  20. Structure for Regular Inclusions

    CERN Document Server

    Pitts, David R

    2012-01-01

    We study pairs (C,D) of unital C*-algebras where D is an abelian C*-subalgebra of C which is regular in C. When D is a MASA in C, there exists a unique completely positive unital map E of C into the injective envelope I(D) of D whose restriction to D is the identity on D. We show that the left kernel of E is the unique closed two-sided ideal of C maximal with respect to having trivial intersection with D. We introduce a new class of well behaved state extensions, the compatible states; we identify compatible states when D is a MASA in C in terms of groups constructed from local dynamics near a pure state on D. When C is separable, D is a MASA in C, and the pair (C,D) is regular, the set of pure states on D with unique state extensions to C is dense in D. The map E can be used as a substitute for a conditional expectation in the construction of coordinates for C relative to D. We show that certain classes of compatible states have natural groupoid operations, and we show that constructions of Kumjian and Renau...

  1. Brain-wide mapping of axonal connections: workflow for automated detection and spatial analysis of labeling in microscopic sections

    Directory of Open Access Journals (Sweden)

    Eszter Agnes ePapp

    2016-04-01

    Full Text Available Axonal tracing techniques are powerful tools for exploring the structural organization of neuronal connections. Tracers such as biotinylated dextran amine (BDA and Phaseolus vulgaris leucoagglutinin (Pha-L allow brain-wide mapping of connections through analysis of large series of histological section images. We present a workflow for efficient collection and analysis of tract-tracing datasets with a focus on newly developed modules for image processing and assignment of anatomical location to tracing data. New functionality includes automatic detection of neuronal labeling in large image series, alignment of images to a volumetric brain atlas, and analytical tools for measuring the position and extent of labeling. To evaluate the workflow, we used high-resolution microscopic images from axonal tracing experiments in which different parts of the rat primary somatosensory cortex had been injected with BDA or Pha-L. Parameters from a set of representative images were used to automate detection of labeling in image series covering the entire brain, resulting in binary maps of the distribution of labeling. For high to medium labeling densities, automatic detection was found to provide reliable results when compared to manual analysis, whereas weak labeling required manual curation for optimal detection. To identify brain regions corresponding to labeled areas, section images were aligned to the Waxholm Space (WHS atlas of the Sprague Dawley rat brain (v2 by custom-angle slicing of the MRI template to match individual sections. Based on the alignment, WHS coordinates were obtained for labeled elements and transformed to stereotaxic coordinates. The new workflow modules increase the efficiency and reliability of labeling detection in large series of images from histological sections, and enable anchoring to anatomical atlases for further spatial analysis and comparison with other data.

  2. Spatially resolved detection of crystallized water ice in a TTauri object

    CERN Document Server

    Schegerer, Alexander A

    2010-01-01

    We search for frozen water and its processing around young stellar objects (YSOs of class I/II). We try to detect potential, regional differences in water ice evolution within YSOs, which is relevant to understanding the chemical structure of the progenitors of protoplanetary systems and the evolution of solid materials. Water plays an important role as a reaction bed for rich chemistry and is an indispensable requirement for life as known on Earth. We present our analysis of NAOS-CONICA/VLT spectroscopy of water ice at 3um for the TTauri star YLW 16A in the rho-Ophiuchi molecular cloud. We obtained spectra for different regions of the circumstellar environment. The observed absorption profiles are deconvolved with the mass extinction profiles of amorphous and crystallized ice measured in laboratory. We take into account both absorption and scattering by ice grains. Water ice in YLW 16A is detected with optical depths of between tau=1.8 and tau=2.5. The profiles that are measured can be fitted predominantly b...

  3. Detection and quantification of waterborne microorganisms using an image cytometer based on angular spatial frequency processing

    CERN Document Server

    Pérez, Juan Miguel; Martínez, Pedro; Pruneri, Valerio

    2015-01-01

    We introduce a new image cytometer design for detection of very small particulate and demonstrate its capability in water analysis. The device is a compact microscope composed of off--the--shelf components, such as a light emitting diode (LED) source, a complementary metal--oxide--semiconductor (CMOS) image sensor, and a specific combination of optical lenses that allow, through an appropriate software, Fourier transform processing of the sample volume. Waterborne microorganisms, such as Escherichia coli (E. coli), Legionella pneumophila (L. pneumophila) and Phytoplankton, are detected by interrogating the volume sample either in a fluorescent or label-free mode, i.e. with or without fluorescein isothiocyanate (FITC) molecules attached to the micro-organisms, respectively. We achieve a sensitivity of 50 CFU/ml, which can be further increased to 0.2 CFU/ml by pre-concentrating an initial sample volume of 500 ml with an ad hoc fluidic system. We also prove the capability of the proposed image cytometer of diffe...

  4. Spatial extent and temporal variability of Greenland firn aquifers detected by ground and airborne radars

    Science.gov (United States)

    Miège, Clément; Forster, Richard R.; Brucker, Ludovic; Koenig, Lora S.; Solomon, D. Kip; Paden, John D.; Box, Jason E.; Burgess, Evan W.; Miller, Julie Z.; McNerney, Laura; Brautigam, Noah; Fausto, Robert S.; Gogineni, Sivaprasad

    2016-12-01

    We document the existence of widespread firn aquifers in an elevation range of 1200-2000 m, in the high snow-accumulation regions of the Greenland ice sheet. We use NASA Operation IceBridge accumulation radar data from five campaigns (2010-2014) to estimate a firn-aquifer total extent of 21,900 km2. We investigate two locations in Southeast Greenland, where repeated radar profiles allow mapping of aquifer-extent and water table variations. In the upper part of Helheim Glacier the water table rises in spring following above-average summer melt, showing the direct firn-aquifer response to surface meltwater production changes. After spring 2012, a drainage of the firn-aquifer lower margin (5 km) is inferred from both 750 MHz accumulation radar and 195 MHz multicoherent radar depth sounder data. For 2011-2014, we use a ground-penetrating radar profile located at our Ridgeline field site and find a spatially stable aquifer with a water table fluctuating less than 2.5 m vertically. When combining radar data with surface topography, we find that the upper elevation edge of firn aquifers is located directly downstream of locally high surface slopes. Using a steady state 2-D groundwater flow model, water is simulated to flow laterally in an unconfined aquifer, topographically driven by ice sheet surface undulations until the water encounters crevasses. Simulations suggest that local flow cells form within the Helheim aquifer, allowing water to discharge in the firn at the steep-to-flat transitions of surface topography. Supported by visible imagery, we infer that water drains into crevasses, but its volume and rate remain unconstrained.

  5. Tomographic TDLAS Using WMS-2f and Tikhonov Regularization

    CERN Document Server

    Guha, Avishek

    2014-01-01

    The application of tunable diode laser absorption spectroscopy (TDLAS) to flames with non-homogeneous temperature and concentration fields is an area where only few studies exist. Experimental work explores the performance of tomographic reconstructions of concentration and temperature profiles from wavelength-modulated TDLAS measurements within the plume of an axisymmetric McKenna burner. Water vapor transitions at 1391.67 nm and 1442.67 nm are probed using calibration free wavelength modulation spectroscopy with second harmonic detection (WMS-2f). A single collimated laser beam is swept parallel to the burner surface, where scans yield pairs of line-of-sight (LOS) data at multiple radial locations. Radial profiles of absorption data are reconstructed using Tikhonov regularized Abel inversion, which suppresses the amplification of experimental noise that is typically observed for reconstructions with high spatial resolution. Based on spectral data, temperatures and concentrations are calculated point-by-poin...

  6. Dynamic stabilization of regular linear systems

    NARCIS (Netherlands)

    Weiss, G; Curtain, RF

    We consider a general class of infinite-dimensional linear systems, called regular linear systems, for which convenient representations are known to exist both in time and in frequency domain, For this class of systems, we investigate the concepts of stabilizability and detectability, in particular,

  7. Dynamic stabilization of regular linear systems

    NARCIS (Netherlands)

    Weiss, G; Curtain, RF

    1997-01-01

    We consider a general class of infinite-dimensional linear systems, called regular linear systems, for which convenient representations are known to exist both in time and in frequency domain, For this class of systems, we investigate the concepts of stabilizability and detectability, in particular,

  8. Spatially selective photonic crystal enhanced fluorescence and application to background reduction for biomolecule detection assays.

    Science.gov (United States)

    Chaudhery, Vikram; Huang, Cheng-Sheng; Pokhriyal, Anusha; Polans, James; Cunningham, Brian T

    2011-11-07

    By combining photonic crystal label-free biosensor imaging with photonic crystal enhanced fluorescence, it is possible to selectively enhance the fluorescence emission from regions of the PC surface based upon the density of immobilized capture molecules. A label-free image of the capture molecules enables determination of optimal coupling conditions of the laser used for fluorescence imaging of the photonic crystal surface on a pixel-by-pixel basis, allowing maximization of fluorescence enhancement factor from regions incorporating a biomolecule capture spot and minimization of background autofluorescence from areas between capture spots. This capability significantly improves the contrast of enhanced fluorescent images, and when applied to an antibody protein microarray, provides a substantial advantage over conventional fluorescence microscopy. Using the new approach, we demonstrate detection limits as low as 0.97 pg/ml for a representative protein biomarker in buffer.

  9. Performance analysis of fiber-based free-space optical communications with coherent detection spatial diversity.

    Science.gov (United States)

    Li, Kangning; Ma, Jing; Tan, Liying; Yu, Siyuan; Zhai, Chao

    2016-06-10

    The performances of fiber-based free-space optical (FSO) communications over gamma-gamma distributed turbulence are studied for multiple aperture receiver systems. The equal gain combining (EGC) technique is considered as a practical scheme to mitigate the atmospheric turbulence. Bit error rate (BER) performances for binary-phase-shift-keying-modulated coherent detection fiber-based free-space optical communications are derived and analyzed for EGC diversity receptions through an approximation method. To show the net diversity gain of a multiple aperture receiver system, BER performances of EGC are compared with a single monolithic aperture receiver system with the same total aperture area (same average total incident optical power on the aperture surface) for fiber-based free-space optical communications. The analytical results are verified by Monte Carlo simulations. System performances are also compared for EGC diversity coherent FSO communications with or without considering fiber-coupling efficiencies.

  10. An Object-Based Image Analysis Approach for Detecting Penguin Guano in very High Spatial Resolution Satellite Images

    Directory of Open Access Journals (Sweden)

    Chandi Witharana

    2016-04-01

    Full Text Available The logistical challenges of Antarctic field work and the increasing availability of very high resolution commercial imagery have driven an interest in more efficient search and classification of remotely sensed imagery. This exploratory study employed geographic object-based analysis (GEOBIA methods to classify guano stains, indicative of chinstrap and Adélie penguin breeding areas, from very high spatial resolution (VHSR satellite imagery and closely examined the transferability of knowledge-based GEOBIA rules across different study sites focusing on the same semantic class. We systematically gauged the segmentation quality, classification accuracy, and the reproducibility of fuzzy rules. A master ruleset was developed based on one study site and it was re-tasked “without adaptation” and “with adaptation” on candidate image scenes comprising guano stains. Our results suggest that object-based methods incorporating the spectral, textural, spatial, and contextual characteristics of guano are capable of successfully detecting guano stains. Reapplication of the master ruleset on candidate scenes without modifications produced inferior classification results, while adapted rules produced comparable or superior results compared to the reference image. This work provides a road map to an operational “image-to-assessment pipeline” that will enable Antarctic wildlife researchers to seamlessly integrate VHSR imagery into on-demand penguin population census.

  11. Detecting Spatial Patterns of Disease in Large Collections of Electronic Medical Records Using Neighbor-Based Bootstrapping.

    Science.gov (United States)

    Patterson, Maria T; Grossman, Robert L

    2017-09-01

    We introduce a method called neighbor-based bootstrapping (NB2) that can be used to quantify the geospatial variation of a variable. We applied this method to an analysis of the incidence rates of disease from electronic medical record data (International Classification of Diseases, Ninth Revision codes) for ∼100 million individuals in the United States over a period of 8 years. We considered the incidence rate of disease in each county and its geospatially contiguous neighbors and rank ordered diseases in terms of their degree of geospatial variation as quantified by the NB2 method. We show that this method yields results in good agreement with established methods for detecting spatial autocorrelation (Moran's I method and kriging). Moreover, the NB2 method can be tuned to identify both large area and small area geospatial variations. This method also applies more generally in any parameter space that can be partitioned to consist of regions and their neighbors.

  12. Evolutionary internalized regularities.

    Science.gov (United States)

    Schwartz, R

    2001-08-01

    Roger Shepard's proposals and supporting experiments concerning evolutionary internalized regularities have been very influential in the study of vision and in other areas of psychology and cognitive science. This paper examines issues concerning the need, nature, explanatory role, and justification for postulating such internalized constraints. In particular, I seek further clarification from Shepard on how best to understand his claim that principles of kinematic geometry underlie phenomena of motion perception. My primary focus is on the ecological validity of Shepard's kinematic constraint in the context of ordinary motion perception. First, I explore the analogy Shepard draws between internalized circadian rhythms and the supposed internalization of kinematic geometry. Next, questions are raised about how to interpret and justify applying results from his own and others' experimental studies of apparent motion to more everyday cases of motion perception in richer environments. Finally, some difficulties with Shepard's account of the evolutionary development of his kinematic constraint are considered.

  13. Adaptive Regularization of Neural Classifiers

    DEFF Research Database (Denmark)

    Andersen, Lars Nonboe; Larsen, Jan; Hansen, Lars Kai

    1997-01-01

    We present a regularization scheme which iteratively adapts the regularization parameters by minimizing the validation error. It is suggested to use the adaptive regularization scheme in conjunction with optimal brain damage pruning to optimize the architecture and to avoid overfitting. Furthermo...

  14. Tryptophan PET predicts spatial and temporal patterns of post-treatment glioblastoma progression detected by contrast-enhanced MRI.

    Science.gov (United States)

    Bosnyák, Edit; Kamson, David O; Robinette, Natasha L; Barger, Geoffrey R; Mittal, Sandeep; Juhász, Csaba

    2016-01-01

    Amino acid PET is increasingly utilized for the detection of recurrent gliomas. Increased amino acid uptake is often observed outside the contrast-enhancing brain tumor mass. In this study, we evaluated if non-enhancing PET+ regions could predict spatial and temporal patterns of subsequent MRI progression in previously treated glioblastomas. Twelve patients with a contrast-enhancing area suspicious for glioblastoma recurrence on MRI underwent PET scanning with the amino acid radiotracer alpha-[(11)C]-methyl-L-tryptophan (AMT). Brain regions showing increased AMT uptake in and outside the contrast-enhancing volume were objectively delineated to include high uptake consistent with glioma (as defined by previous studies). Volume and tracer uptake of such non-enhancing PET+ regions were compared to spatial patterns and timing of subsequent progression of the contrast-enhancing lesion, as defined by serial surveillance MRI. Non-enhancing PET+ volumes varied widely across patients and extended up to 24 mm from the edge of MRI contrast enhancement. In ten patients with clear progression of the contrast-enhancing lesion, the non-enhancing PET+ volumes predicted the location of new enhancement, which extended beyond the PET+ brain tissue in six. In two patients, with no PET+ area beyond the initial contrast enhancement, MRI remained stable. There was a negative correlation between AMT uptake in non-enhancing brain and time to subsequent progression (r = -0.77, p = 0.003). Amino acid PET imaging could complement MRI not only for detecting glioma recurrence but also predicting the location and timing of subsequent tumor progression. This could support decisions for surgical intervention or other targeted therapies for recurrent gliomas.

  15. Full L1-regularized Traction Force Microscopy over whole cells.

    Science.gov (United States)

    Suñé-Auñón, Alejandro; Jorge-Peñas, Alvaro; Aguilar-Cuenca, Rocío; Vicente-Manzanares, Miguel; Van Oosterwyck, Hans; Muñoz-Barrutia, Arrate

    2017-08-10

    Traction Force Microscopy (TFM) is a widespread technique to estimate the tractions that cells exert on the surrounding substrate. To recover the tractions, it is necessary to solve an inverse problem, which is ill-posed and needs regularization to make the solution stable. The typical regularization scheme is given by the minimization of a cost functional, which is divided in two terms: the error present in the data or data fidelity term; and the regularization or penalty term. The classical approach is to use zero-order Tikhonov or L2-regularization, which uses the L2-norm for both terms in the cost function. Recently, some studies have demonstrated an improved performance using L1-regularization (L1-norm in the penalty term) related to an increase in the spatial resolution and sensitivity of the recovered traction field. In this manuscript, we present a comparison between the previous two regularization schemes (relying in the L2-norm for the data fidelity term) and the full L1-regularization (using the L1-norm for both terms in the cost function) for synthetic and real data. Our results reveal that L1-regularizations give an improved spatial resolution (more important for full L1-regularization) and a reduction in the background noise with respect to the classical zero-order Tikhonov regularization. In addition, we present an approximation, which makes feasible the recovery of cellular tractions over whole cells on typical full-size microscope images when working in the spatial domain. The proposed full L1-regularization improves the sensitivity to recover small stress footprints. Moreover, the proposed method has been validated to work on full-field microscopy images of real cells, what certainly demonstrates it is a promising tool for biological applications.

  16. Detection of spatial variations in the (D/H) ratio in the local interstellar medium

    Science.gov (United States)

    Vidal-Madjar, Alfred; Lemoine, Martin; Ferlet, Roger; Hebrard, Guillaume; Koester, Detlev; Audouze, Jean; Casse, Michel; Vangioni-Flam, Elisabeth; Webb, John

    1998-10-01

    We present high resolution (Delta lambda = 3.7 km.s^{-1}) HST-GHRS observations of the DA white dwarf G191-B2B, and derive the interstellar D/H ratio on the line of sight. We have observed and analysed simultaneously the interstellar lines of Hi, D i, N i, O i, Si ii and Si iii. We detect three absorbing clouds, and derive a total Hi\\ column density N(Hi)=2.4m0.1 \\times1018cm^{-2}, confirming our Cycle 1 estimate, but in disagreement with other previous measurements. We derive an average D/H ratio over the three absorbing clouds N(D i)_total/N(Hi)_total=1.12m 0.08 \\times 10^{-5}, in disagreement with the previously reported value of the local D/H as reported by Linsky et al. (1995) toward Capella. We re-analyze the GHRS data of the Capella line of sight, and confirm their estimate, as we find (D/H)_Capella=1.56m 0.1 \\times 10^{-5} in the Local Interstellar Cloud in which the solar system is embedded. This shows that the D/H ratio varies by at least im30% within the local interstellar medium. Furthermore, the Local Interstellar Cloud is also detected toward G191-B2B, and we show that the D/H ratio in this component, toward G191-B2B, can be made compatible with that derived toward Capella. However, this comes at the expense of a much smaller value for the D/H ratio as averaged over the other two components, of order 0.9\\times10^{-5}, and in such a way that the D/H ratio as averaged over all three components remains at the above value, {i.e.} (D/H)_Total=1.12\\times10^{-5}$. We thus conclude that, either the D/H ratio varies from cloud to cloud, and/or the D/H ratio varies within the Local Interstellar Cloud, in which the Sun is embedded, although our observations neither prove nor disprove this latter possibility. Based on observations with the NASA/ESA Hubble Space Telescope, obtained at the Hubble Space Telescope Science Institute which is operated by the Association of Universities for Research in Astronomy Inc., under NASA contract NAS5-26555.

  17. Modeling Disease Vector Occurrence when Detection Is Imperfect: Infestation of Amazonian Palm Trees by Triatomine Bugs at Three Spatial Scales

    Science.gov (United States)

    Abad-Franch, Fernando; Ferraz, Gonçalo; Campos, Ciro; Palomeque, Francisco S.; Grijalva, Mario J.; Aguilar, H. Marcelo; Miles, Michael A.

    2010-01-01

    Background Failure to detect a disease agent or vector where it actually occurs constitutes a serious drawback in epidemiology. In the pervasive situation where no sampling technique is perfect, the explicit analytical treatment of detection failure becomes a key step in the estimation of epidemiological parameters. We illustrate this approach with a study of Attalea palm tree infestation by Rhodnius spp. (Triatominae), the most important vectors of Chagas disease (CD) in northern South America. Methodology/Principal Findings The probability of detecting triatomines in infested palms is estimated by repeatedly sampling each palm. This knowledge is used to derive an unbiased estimate of the biologically relevant probability of palm infestation. We combine maximum-likelihood analysis and information-theoretic model selection to test the relationships between environmental covariates and infestation of 298 Amazonian palm trees over three spatial scales: region within Amazonia, landscape, and individual palm. Palm infestation estimates are high (40–60%) across regions, and well above the observed infestation rate (24%). Detection probability is higher (∼0.55 on average) in the richest-soil region than elsewhere (∼0.08). Infestation estimates are similar in forest and rural areas, but lower in urban landscapes. Finally, individual palm covariates (accumulated organic matter and stem height) explain most of infestation rate variation. Conclusions/Significance Individual palm attributes appear as key drivers of infestation, suggesting that CD surveillance must incorporate local-scale knowledge and that peridomestic palm tree management might help lower transmission risk. Vector populations are probably denser in rich-soil sub-regions, where CD prevalence tends to be higher; this suggests a target for research on broad-scale risk mapping. Landscape-scale effects indicate that palm triatomine populations can endure deforestation in rural areas, but become rarer in

  18. Modeling disease vector occurrence when detection is imperfect: infestation of Amazonian palm trees by triatomine bugs at three spatial scales.

    Directory of Open Access Journals (Sweden)

    Fernando Abad-Franch

    Full Text Available BACKGROUND: Failure to detect a disease agent or vector where it actually occurs constitutes a serious drawback in epidemiology. In the pervasive situation where no sampling technique is perfect, the explicit analytical treatment of detection failure becomes a key step in the estimation of epidemiological parameters. We illustrate this approach with a study of Attalea palm tree infestation by Rhodnius spp. (Triatominae, the most important vectors of Chagas disease (CD in northern South America. METHODOLOGY/PRINCIPAL FINDINGS: The probability of detecting triatomines in infested palms is estimated by repeatedly sampling each palm. This knowledge is used to derive an unbiased estimate of the biologically relevant probability of palm infestation. We combine maximum-likelihood analysis and information-theoretic model selection to test the relationships between environmental covariates and infestation of 298 Amazonian palm trees over three spatial scales: region within Amazonia, landscape, and individual palm. Palm infestation estimates are high (40-60% across regions, and well above the observed infestation rate (24%. Detection probability is higher ( approximately 0.55 on average in the richest-soil region than elsewhere ( approximately 0.08. Infestation estimates are similar in forest and rural areas, but lower in urban landscapes. Finally, individual palm covariates (accumulated organic matter and stem height explain most of infestation rate variation. CONCLUSIONS/SIGNIFICANCE: Individual palm attributes appear as key drivers of infestation, suggesting that CD surveillance must incorporate local-scale knowledge and that peridomestic palm tree management might help lower transmission risk. Vector populations are probably denser in rich-soil sub-regions, where CD prevalence tends to be higher; this suggests a target for research on broad-scale risk mapping. Landscape-scale effects indicate that palm triatomine populations can endure deforestation

  19. Spatial and temporal patterns in Arctic river ice breakup revealed by automated ice detection from MODIS imagery

    Science.gov (United States)

    Cooley, Sarah; Pavelsky, Tamlin

    2016-04-01

    The annual spring breakup of river ice has important consequences for northern ecosystems and significant economic implications for Arctic industry and transportation. River ice breakup research is restricted by the sparse distribution of hydrological stations in the Arctic, where limited available data suggests a trend towards earlier ice breakup. The specific climatic mechanisms driving this trend, however, are complex and can vary both regionally and within river systems. Consequently, understanding the response of river ice processes to a warming Arctic requires simultaneous examination of spatial and temporal patterns in breakup timing. Here we present an automated algorithm for river ice breakup detection using MODIS satellite imagery that enables identification of spatial and temporal breakup patterns at large scales. We examine breakup timing on the Mackenzie, Lena, Ob' and Yenisey rivers for the period 2000-2014. First, we split each river into 10 km segments. Next, for each day of the breakup season, we classify each river pixel as snow/ice, mixed ice/water or open water based on MODIS reflectance values and remove all cloud-covered segments using the MODIS cloud product. We then define the breakup date as the first day where the segment is 75% open water. Using this method, we are able to determine breakup dates with a mean uncertainty of +/-1.3 days. We find our remotely sensed breakup dates to be highly correlated to ground breakup dates and the timing of peak discharge. All statistically significant temporal trends in breakup timing are negative, indicating an overall shift towards earlier breakup. Considerable variability in the statistical significance and magnitude of trends along each river suggests that different climatic and physiographic drivers are impacting spatial patterns in breakup. Trends detected on the lower Mackenzie corroborate recent studies indicating weakening ice resistance and earlier breakup timing near the Mackenzie Delta. In

  20. Accounting for regional background and population size in the detection of spatial clusters and outliers using geostatistical filtering and spatial neutral models: the case of lung cancer in Long Island, New York

    Directory of Open Access Journals (Sweden)

    Goovaerts Pierre

    2004-07-01

    methodology allows one to identify geographic pattern above and beyond background variation. The implementation of this approach in spatial statistical software will facilitate the detection of spatial disparities in mortality rates, establishing the rationale for targeted cancer control interventions, including consideration of health services needs, and resource allocation for screening and diagnostic testing. It will allow researchers to systematically evaluate how sensitive their results are to assumptions implicit under alternative null hypotheses.

  1. Detecting Bedform Migration in Portsmouth Harbor, New Hampshire, USA on Relatively Short Spatial and Temporal Scales

    Science.gov (United States)

    Felzenberg, J. A.; Ward, L. G.; Rzhanov, Y.; Irish, J. D.; Mayer, L. A.

    2008-12-01

    Multibeam echosounder (MBES) systems have enjoyed recent popularity as a tool in bedform-migration studies due to their ability to produce high-resolution seafloor imagery with complete bottom coverage. Although shallow-water MBES systems may achieve decimeter-scale data resolution, the use of MBES to successfully detect and quantify bedform migration on short time-scales (days to weeks) where the migration distance is relatively small (MBES system. Position, heading and attitude data were acquired with an Applanix POS/MV system with integrated real-time kinematic GPS correctors, providing a horizontal positioning uncertainty of MBES surveys were conducted on June 8, 14 and 15 in 2007 and July 3 and 9 in 2008. Acoustic current meters were deployed at two stations within the survey area in 2008 to provide simultaneous observations of current velocities at a height of 1 m above the bottom. A new approach was developed and used for detecting and quantifying bedform migration from the bathymetry. Our approach utilizes a ridge-extraction algorithm to derive a binary map of dune-crest positions from the bathymetric surface, and then calculates the displacements of small (6.25 m2) subsets of dune crest. Preliminary results indicate that bedform migrations of ≥ 0.1 m were successfully resolved. Morphology of the bedform field is dominated by medium and large, two-dimensional, asymmetrical subaqueous dunes (0.4 to 0.8 m height, 8 to 16 m wavelength). Small, two-dimensional, ebb-oriented subaqueous dunes (0.3 m height, 5 m wavelength) line the eastern margin of the bedform field, which is adjacent to the channel thalweg. Initial analysis indicates that bedforms are active on 24-hour and multi-day cycles, with migrations of > 1.2 m observed on multi-day cycles. The highest bedform-migration rates are observed along the eastern margin where smaller dunes occur. In 2007 we observed a reciprocal pattern of bedform migration, in which dunes in the western half of the bedform

  2. Investigating the effect of pixel size of high spatial resolution FTIR imaging for detection of colorectal cancer

    Science.gov (United States)

    Lloyd, G. R.; Nallala, J.; Stone, N.

    2016-03-01

    FTIR is a well-established technique and there is significant interest in applying this technique to medical diagnostics e.g. to detect cancer. The introduction of focal plane array (FPA) detectors means that FTIR is particularly suited to rapid imaging of biopsy sections as an adjunct to digital pathology. Until recently however each pixel in the image has been limited to a minimum of 5.5 µm which results in a comparatively low magnification image or histology applications and potentially the loss of important diagnostic information. The recent introduction of higher magnification optics gives image pixels that cover approx. 1.1 µm. This reduction in image pixel size gives images of higher magnification and improved spatial detail can be observed. However, the effect of increasing the magnification on spectral quality and the ability to discriminate between disease states is not well studied. In this work we test the discriminatory performance of FTIR imaging using both standard (5.5 µm) and high (1.1 µm) magnification for the detection of colorectal cancer and explore the effect of binning to degrade high resolution images to determine whether similar diagnostic information and performance can be obtained using both magnifications. Results indicate that diagnostic performance using high magnification may be reduced as compared to standard magnification when using existing multivariate approaches. Reduction of the high magnification data to standard magnification via binning can potentially recover some of the lost performance.

  3. A Low-Cost Imaging Method for the Temporal and Spatial Colorimetric Detection of Free Amines on Maize Root Surfaces

    Directory of Open Access Journals (Sweden)

    Truc H. Doan

    2017-08-01

    Full Text Available Plant root exudates are important mediators in the interactions that occur between plants and microorganisms in the soil, yet much remains to be learned about spatial and temporal variation in their production. This work outlines a method utilizing a novel colorimetric paper to detect spatial and temporal changes in the production of nitrogen-containing compounds on the root surface. While existing methods have made it possible to conduct detailed analysis of root exudate composition, relatively less is known about where in the root system exudates are produced and how this localization changes as the root grows. Furthermore, there is much to learn about how exudate localization and composition varies in response to stress. Root exudates are chemically diverse secretions composed of organic acids, amino acids, proteins, sugars, and other metabolites. The sensor utilized for the method, ninhydrin, is a colorless substance in solution that reacts with free amino groups to form a purple dye. A detection paper was developed by formulating ninhydrin into a print solution that was uniformly deposited onto paper with a commercial ink jet printer. This “ninhydrin paper” was used to analyze the chemical makeup of root surfaces from maize seedlings grown vertically on germination paper. Through contact between the ninhydrin paper and seedling root surfaces, combined with images of both the seedlings and dried ninhydrin papers captured using a standard flatbed scanner, nitrogen-containing substances on the root surface can be localized and concentration of signal estimated for over 2 weeks of development. The method was found to be non-inhibiting to plant growth over the analysis period although damage to root hairs was observed. The method is sensitive in the detection of free amines at concentrations as little as 140 μM. Furthermore, ninhydrin paper is stable, showing consistent color changes up to 2 weeks after printing. This relatively simple, low

  4. Rotating regular black holes

    CERN Document Server

    Bambi, Cosimo

    2013-01-01

    The formation of spacetime singularities is a quite common phenomenon in General Relativity and it is regulated by specific theorems. It is widely believed that spacetime singularities do not exist in Nature, but that they represent a limitation of the classical theory. While we do not yet have any solid theory of quantum gravity, toy models of black hole solutions without singularities have been proposed. So far, there are only non-rotating regular black holes in the literature. These metrics can be hardly tested by astrophysical observations, as the black hole spin plays a fundamental role in any astrophysical process. In this letter, we apply the Newman-Janis algorithm to the Hayward and to the Bardeen black hole metrics. In both cases, we obtain a family of rotating solutions. Every solution corresponds to a different matter configuration. Each family has one solution with special properties, which can be written in Kerr-like form in Boyer-Lindquist coordinates. These special solutions are of Petrov type ...

  5. Rotating regular black holes

    Energy Technology Data Exchange (ETDEWEB)

    Bambi, Cosimo, E-mail: bambi@fudan.edu.cn; Modesto, Leonardo, E-mail: lmodesto@fudan.edu.cn

    2013-04-25

    The formation of spacetime singularities is a quite common phenomenon in General Relativity and it is regulated by specific theorems. It is widely believed that spacetime singularities do not exist in Nature, but that they represent a limitation of the classical theory. While we do not yet have any solid theory of quantum gravity, toy models of black hole solutions without singularities have been proposed. So far, there are only non-rotating regular black holes in the literature. These metrics can be hardly tested by astrophysical observations, as the black hole spin plays a fundamental role in any astrophysical process. In this Letter, we apply the Newman–Janis algorithm to the Hayward and to the Bardeen black hole metrics. In both cases, we obtain a family of rotating solutions. Every solution corresponds to a different matter configuration. Each family has one solution with special properties, which can be written in Kerr-like form in Boyer–Lindquist coordinates. These special solutions are of Petrov type D, they are singularity free, but they violate the weak energy condition for a non-vanishing spin and their curvature invariants have different values at r=0 depending on the way one approaches the origin. We propose a natural prescription to have rotating solutions with a minimal violation of the weak energy condition and without the questionable property of the curvature invariants at the origin.

  6. Ensemble manifold regularization.

    Science.gov (United States)

    Geng, Bo; Tao, Dacheng; Xu, Chao; Yang, Linjun; Hua, Xian-Sheng

    2012-06-01

    We propose an automatic approximation of the intrinsic manifold for general semi-supervised learning (SSL) problems. Unfortunately, it is not trivial to define an optimization function to obtain optimal hyperparameters. Usually, cross validation is applied, but it does not necessarily scale up. Other problems derive from the suboptimality incurred by discrete grid search and the overfitting. Therefore, we develop an ensemble manifold regularization (EMR) framework to approximate the intrinsic manifold by combining several initial guesses. Algorithmically, we designed EMR carefully so it 1) learns both the composite manifold and the semi-supervised learner jointly, 2) is fully automatic for learning the intrinsic manifold hyperparameters implicitly, 3) is conditionally optimal for intrinsic manifold approximation under a mild and reasonable assumption, and 4) is scalable for a large number of candidate manifold hyperparameters, from both time and space perspectives. Furthermore, we prove the convergence property of EMR to the deterministic matrix at rate root-n. Extensive experiments over both synthetic and real data sets demonstrate the effectiveness of the proposed framework.

  7. Hyperspectral Image Recovery via Hybrid Regularization

    Science.gov (United States)

    Arablouei, Reza; de Hoog, Frank

    2016-12-01

    Natural images tend to mostly consist of smooth regions with individual pixels having highly correlated spectra. This information can be exploited to recover hyperspectral images of natural scenes from their incomplete and noisy measurements. To perform the recovery while taking full advantage of the prior knowledge, we formulate a composite cost function containing a square-error data-fitting term and two distinct regularization terms pertaining to spatial and spectral domains. The regularization for the spatial domain is the sum of total-variation of the image frames corresponding to all spectral bands. The regularization for the spectral domain is the l1-norm of the coefficient matrix obtained by applying a suitable sparsifying transform to the spectra of the pixels. We use an accelerated proximal-subgradient method to minimize the formulated cost function. We analyze the performance of the proposed algorithm and prove its convergence. Numerical simulations using real hyperspectral images exhibit that the proposed algorithm offers an excellent recovery performance with a number of measurements that is only a small fraction of the hyperspectral image data size. Simulation results also show that the proposed algorithm significantly outperforms an accelerated proximal-gradient algorithm that solves the classical basis-pursuit denoising problem to recover the hyperspectral image.

  8. Active site detection by spatial conformity and electrostatic analysis--unravelling a proteolytic function in shrimp alkaline phosphatase.

    Directory of Open Access Journals (Sweden)

    Sandeep Chakraborty

    Full Text Available Computational methods are increasingly gaining importance as an aid in identifying active sites. Mostly these methods tend to have structural information that supplement sequence conservation based analyses. Development of tools that compute electrostatic potentials has further improved our ability to better characterize the active site residues in proteins. We have described a computational methodology for detecting active sites based on structural and electrostatic conformity - CataLytic Active Site Prediction (CLASP. In our pipelined model, physical 3D signature of any particular enzymatic function as defined by its active sites is used to obtain spatially congruent matches. While previous work has revealed that catalytic residues have large pKa deviations from standard values, we show that for a given enzymatic activity, electrostatic potential difference (PD between analogous residue pairs in an active site taken from different proteins of the same family are similar. False positives in spatially congruent matches are further pruned by PD analysis where cognate pairs with large deviations are rejected. We first present the results of active site prediction by CLASP for two enzymatic activities - β-lactamases and serine proteases, two of the most extensively investigated enzymes. The results of CLASP analysis on motifs extracted from Catalytic Site Atlas (CSA are also presented in order to demonstrate its ability to accurately classify any protein, putative or otherwise, with known structure. The source code and database is made available at www.sanchak.com/clasp/. Subsequently, we probed alkaline phosphatases (AP, one of the well known promiscuous enzymes, for additional activities. Such a search has led us to predict a hitherto unknown function of shrimp alkaline phosphatase (SAP, where the protein acts as a protease. Finally, we present experimental evidence of the prediction by CLASP by showing that SAP indeed has protease activity in

  9. Active site detection by spatial conformity and electrostatic analysis--unravelling a proteolytic function in shrimp alkaline phosphatase.

    Science.gov (United States)

    Chakraborty, Sandeep; Minda, Renu; Salaye, Lipika; Bhattacharjee, Swapan K; Rao, Basuthkar J

    2011-01-01

    Computational methods are increasingly gaining importance as an aid in identifying active sites. Mostly these methods tend to have structural information that supplement sequence conservation based analyses. Development of tools that compute electrostatic potentials has further improved our ability to better characterize the active site residues in proteins. We have described a computational methodology for detecting active sites based on structural and electrostatic conformity - CataLytic Active Site Prediction (CLASP). In our pipelined model, physical 3D signature of any particular enzymatic function as defined by its active sites is used to obtain spatially congruent matches. While previous work has revealed that catalytic residues have large pKa deviations from standard values, we show that for a given enzymatic activity, electrostatic potential difference (PD) between analogous residue pairs in an active site taken from different proteins of the same family are similar. False positives in spatially congruent matches are further pruned by PD analysis where cognate pairs with large deviations are rejected. We first present the results of active site prediction by CLASP for two enzymatic activities - β-lactamases and serine proteases, two of the most extensively investigated enzymes. The results of CLASP analysis on motifs extracted from Catalytic Site Atlas (CSA) are also presented in order to demonstrate its ability to accurately classify any protein, putative or otherwise, with known structure. The source code and database is made available at www.sanchak.com/clasp/. Subsequently, we probed alkaline phosphatases (AP), one of the well known promiscuous enzymes, for additional activities. Such a search has led us to predict a hitherto unknown function of shrimp alkaline phosphatase (SAP), where the protein acts as a protease. Finally, we present experimental evidence of the prediction by CLASP by showing that SAP indeed has protease activity in vitro.

  10. The detection and mapping of the spatial distribution of insect defense compounds by desorption atmospheric pressure photoionization Orbitrap mass spectrometry.

    Science.gov (United States)

    Rejšek, Jan; Vrkoslav, Vladimír; Hanus, Robert; Vaikkinen, Anu; Haapala, Markus; Kauppila, Tiina J; Kostiainen, Risto; Cvačka, Josef

    2015-07-30

    Many insects use chemicals synthesized in exocrine glands and stored in reservoirs to protect themselves. Two chemically defended insects were used as models for the development of a new rapid analytical method based on desorption atmospheric pressure photoionization-mass spectrometry (DAPPI-MS). The distribution of defensive chemicals on the insect body surface was studied. Since these chemicals are predominantly nonpolar, DAPPI was a suitable analytical method. Repeatability of DAPPI-MS signals and effects related to non-planarity and roughness of samples were investigated using acrylic sheets uniformly covered with an analyte. After that, analytical figures of merit of the technique were determined. The spatial distribution of (E)-1-nitropentadec-1-ene, a toxic nitro compound synthesized by soldiers of the termite Prorhinotermes simplex, was investigated. Then, the spatial distribution of the unsaturated aldehydes (E)-hex-2-enal, (E)-4-oxohex-2-enal, (E)-oct-2-enal, (E,E)-deca-2,4-dienal and (E)-dec-2-enal was monitored in the stink bug Graphosoma lineatum. Chemicals present on the body surface were scanned along the median line of the insect from the head to the abdomen and vice versa, employing either the MS or MS(2) mode. In this fast and simple way, the opening of the frontal gland on the frons of termite soldiers and the position of the frontal gland reservoir, extending deep into the abdominal cavity, were localized. In the stink bug, the opening of the metathoracic scent glands (ostiole) on the ventral side of the thorax as well as the gland reservoir in the median position under the ventral surface of the anterior abdomen were detected and localized. The developed method has future prospects in routine laboratory use in life sciences.

  11. Spatial variability of active layer thickness detected by ground-penetrating radar in the Qilian Mountains, Western China

    Science.gov (United States)

    Cao, Bin; Gruber, Stephan; Zhang, Tingjun; Li, Lili; Peng, Xiaoqing; Wang, Kang; Zheng, Lei; Shao, Wanwan; Guo, Hong

    2017-03-01

    The active layer plays a key role in geomorphic, hydrologic, and biogeochemical processes in permafrost regions. We conducted a systematic investigation of active layer thickness (ALT) in northeastern Qinghai-Tibetan Plateau by using ground-penetrating radar (GPR) with 100 and 200 MHz antennas. We used mechanical probing, pit, and soil temperature profiles for evaluating ALT derived from GPR. The results showed that GPR is competent for detecting ALT, and the error was ±0.08 m at common midpoint co-located sites. Considerable spatial variability of ALT owing to variation in elevation, peat thickness, and slope aspect was found. The mean ALT was 1.32 ± 0.29 m with a range from 0.81 to 2.1 m in Eboling Mountain. In Yeniu Gou, mean ALT was 2.72 ± 0.88 m and varied from 1.07 m on the north-facing slope to 4.86 m around the area near the lower boundary of permafrost. ALT in peat decreased with increasing elevation at rates of -1.31 m/km (Eboling Mountain) and -2.1 m/km (Yeniu Gou), and in mineral soil in Yeniu Gou, the rate changed to -4.18 m/km. At the same elevation, ALT on the south-facing slope was about 0.8 m thicker than that on the north-facing slopes, while the difference was only 0.18 m in peat-covered area. Within a 100 m2 area with a local elevation difference of 0.8 m, ALT varied from 0.68 m to 1.25 m. Both field monitoring and modeling studies on spatial ALT variations require rethinking of the current strategy and comprehensive design.

  12. Detection and mapping the spatial distribution of bracken fern weeds using the Landsat 8 OLI new generation sensor

    Science.gov (United States)

    Matongera, Trylee Nyasha; Mutanga, Onisimo; Dube, Timothy; Sibanda, Mbulisi

    2017-05-01

    Bracken fern is an invasive plant that presents serious environmental, ecological and economic problems around the world. An understanding of the spatial distribution of bracken fern weeds is therefore essential for providing appropriate management strategies at both local and regional scales. The aim of this study was to assess the utility of the freely available medium resolution Landsat 8 OLI sensor in the detection and mapping of bracken fern at the Cathedral Peak, South Africa. To achieve this objective, the results obtained from Landsat 8 OLI were compared with those derived using the costly, high spatial resolution WorldView-2 imagery. Since previous studies have already successfully mapped bracken fern using high spatial resolution WorldView-2 image, the comparison was done to investigate the magnitude of difference in accuracy between the two sensors in relation to their acquisition costs. To evaluate the performance of Landsat 8 OLI in discriminating bracken fern compared to that of Worldview-2, we tested the utility of (i) spectral bands; (ii) derived vegetation indices as well as (iii) the combination of spectral bands and vegetation indices based on discriminant analysis classification algorithm. After resampling the training and testing data and reclassifying several times (n = 100) based on the combined data sets, the overall accuracies for both Landsat 8 and WorldView-2 were tested for significant differences based on Mann-Whitney U test. The results showed that the integration of the spectral bands and derived vegetation indices yielded the best overall classification accuracy (80.08% and 87.80% for Landsat 8 OLI and WorldView-2 respectively). Additionally, the use of derived vegetation indices as a standalone data set produced the weakest overall accuracy results of 62.14% and 82.11% for both the Landsat 8 OLI and WorldView-2 images. There were significant differences {U (100) = 569.5, z = -10.8242, p < 0.01} between the classification accuracies

  13. Power-law regularities in human language

    Science.gov (United States)

    Mehri, Ali; Lashkari, Sahar Mohammadpour

    2016-11-01

    Complex structure of human language enables us to exchange very complicated information. This communication system obeys some common nonlinear statistical regularities. We investigate four important long-range features of human language. We perform our calculations for adopted works of seven famous litterateurs. Zipf's law and Heaps' law, which imply well-known power-law behaviors, are established in human language, showing a qualitative inverse relation with each other. Furthermore, the informational content associated with the words ordering, is measured by using an entropic metric. We also calculate fractal dimension of words in the text by using box counting method. The fractal dimension of each word, that is a positive value less than or equal to one, exhibits its spatial distribution in the text. Generally, we can claim that the Human language follows the mentioned power-law regularities. Power-law relations imply the existence of long-range correlations between the word types, to convey an especial idea.

  14. Tracking magnetogram proper motions by multiscale regularization

    Science.gov (United States)

    Jones, Harrison P.

    1995-01-01

    Long uninterrupted sequences of solar magnetograms from the global oscillations network group (GONG) network and from the solar and heliospheric observatory (SOHO) satellite will provide the opportunity to study the proper motions of magnetic features. The possible use of multiscale regularization, a scale-recursive estimation technique which begins with a prior model of how state variables and their statistical properties propagate over scale. Short magnetogram sequences are analyzed with the multiscale regularization algorithm as applied to optical flow. This algorithm is found to be efficient, provides results for all the spatial scales spanned by the data and provides error estimates for the solutions. It is found that the algorithm is less sensitive to evolutionary changes than correlation tracking.

  15. Effort variation regularization in sound field reproduction

    DEFF Research Database (Denmark)

    Stefanakis, Nick; Jacobsen, Finn; Sarris, Ioannis

    2010-01-01

    . Specifically, it is suggested that the phase differential of the source driving signals should be in agreement with the phase differential of the desired sound pressure field. The performance of the suggested method is compared with that of conventional effort regularization, wave field synthesis (WFS......In this paper, active control is used in order to reproduce a given sound field in an extended spatial region. A method is proposed which minimizes the reproduction error at a number of control positions with the reproduction sources holding a certain relation within their complex strengths......), and adaptive wave field synthesis (AWFS), both under free-field conditions and in reverberant rooms. It is shown that effort variation regularization overcomes the problems associated with small spaces and with a low ratio of direct to reverberant energy, improving thus the reproduction accuracy...

  16. Regular Bisimple ω2-semigroups

    Institute of Scientific and Technical Information of China (English)

    汪立民; 商宇

    2008-01-01

    @@ The regular semigroups S with an idempotent set Es = {e0,e1,…,en,…} such that e0 > e1 >…> en >… is called a regular ω-semigroup. In [5] Reilly determined the structure of a regular bisimple ω-semigroup as BR(G,θ),which is the classical Bruck-Reilly extension of a group G.

  17. Completely regular fuzzifying topological spaces

    Directory of Open Access Journals (Sweden)

    A. K. Katsaras

    2005-12-01

    Full Text Available Some of the properties of the completely regular fuzzifying topological spaces are investigated. It is shown that a fuzzifying topology τ is completely regular if and only if it is induced by some fuzzy uniformity or equivalently by some fuzzifying proximity. Also, τ is completely regular if and only if it is generated by a family of probabilistic pseudometrics.

  18. On regular rotating black holes

    Science.gov (United States)

    Torres, R.; Fayos, F.

    2017-01-01

    Different proposals for regular rotating black hole spacetimes have appeared recently in the literature. However, a rigorous analysis and proof of the regularity of this kind of spacetimes is still lacking. In this note we analyze rotating Kerr-like black hole spacetimes and find the necessary and sufficient conditions for the regularity of all their second order scalar invariants polynomial in the Riemann tensor. We also show that the regularity is linked to a violation of the weak energy conditions around the core of the rotating black hole.

  19. Constrained and regularized system identification

    Directory of Open Access Journals (Sweden)

    Tor A. Johansen

    1998-04-01

    Full Text Available Prior knowledge can be introduced into system identification problems in terms of constraints on the parameter space, or regularizing penalty functions in a prediction error criterion. The contribution of this work is mainly an extension of the well known FPE (Final Production Error statistic to the case when the system identification problem is constrained and contains a regularization penalty. The FPECR statistic (Final Production Error with Constraints and Regularization is of potential interest as a criterion for selection of both regularization parameters and structural parameters such as order.

  20. On regular rotating black holes

    CERN Document Server

    Torres, Ramon

    2016-01-01

    Different proposals for regular rotating black hole spacetimes have appeared recently in the literature. However, a rigorous analysis and proof of the regularity of this kind of spacetimes is still lacking. In this note we analyze rotating Kerr-like black hole spacetimes and find the necessary and sufficient conditions for the regularity of all their second order scalar invariants polynomial in the Riemann tensor. We also show that the regularity is linked to a violation of the weak energy conditions around the core of the rotating black hole.

  1. On Ideals of Regular Rings

    Institute of Scientific and Technical Information of China (English)

    CHEN Huan Yin; LI Fu An

    2002-01-01

    In this paper, we investigate ideals of regular rings and give several characterizations for an ideal to satisfy the comparability. In addition, it is shown that, if Ⅰ is a minimal two-sided ideal of a regular ring R, then Ⅰ satisfies the comparability if and only if Ⅰ is separative. Furthermore, we prove that, for ideals with stable range one, Roth's problem has an affirmative solution. These extend the corresponding results on unit-regularity and one-sided unit-regularity.

  2. Detection and spatial distribution of multiple-contaminants in agro-ecological Mediterranean wetlands (Marjal de Pego-Oliva, Spain)

    Science.gov (United States)

    Pascual-Aguilar, Juan Antonio; Andreu, Vicente; Gimeno-García, Eugenia; Picó, Yolanda; Masia, Ana

    2015-04-01

    Socio economic activities are more and more producing amounts (in quantity and quality) of non desirable chemical substances (contaminants) that can be found in open air environments. As many of these products persist and may also circulate among environmental compartments, the cumulative incidence of such multiple contaminants combination may be a cause of treat that should not exists taking only in consideration concentrations of each contaminant individually because the number and the type of compounds are not known, as well as their cumulative and interaction effects. Thus prior to any further work analyzing the environmental risk of multiple contaminants their identification and level of concentration is required. In this work the potential presence of multiple contaminants of anthropogenic origin in a protected agro-ecological Mediterranean wetland is studied: the Pego-Oliva Marsh Natural Park (Valencian Community, Spain), which is characterized by a long history of human pressures, such as marsh transformation for agricultural uses. Two major groups of relevant pollutants have been targeted according o two distinct environmental matrices: seven heavy metals in soils (Cd, Co, Cr, Cu, Ni, Pb and Zn) and fourteen emerging contaminants /drugs of abuse in surface waters of the natural lagoon, rivers and artificial irrigation networks (6-ACMOR, AMP, BECG, COC, ECGME, HER, KET, MAMP, MDA, MDMA, MET, MOR, THC, THC-COOH). The wetland was divided in nine representative zones with different types of land cover and land use. For soils, 24 samples were collected and for waters 33 taking in consideration the spatial representativeness of the above mention nine environments. Spatial analysis applying Geographical Information Systems to determine areas with greater incidence of both types of contaminants were also performed. With regard to heavy metals, Zn showed values under the detection limits in all samples, the remainder metals appeared in concentrations surpassing the

  3. DETECTION OF THE VELOCITY SHEAR EFFECT ON THE SPATIAL DISTRIBUTIONS OF THE GALACTIC SATELLITES IN ISOLATED SYSTEMS

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jounghun [Astronomy Program, Department of Physics and Astronomy, Seoul National University, Seoul 151-747 (Korea, Republic of); Choi, Yun-Young, E-mail: jounghun@astro.snu.ac.kr, E-mail: yy.choi@khu.ac.kr [Department of Astronomy and Space Science, Kyung Hee University, Gyeonggi 446-701 (Korea, Republic of)

    2015-02-01

    We report a detection of the effect of the large-scale velocity shear on the spatial distributions of the galactic satellites around the isolated hosts. Identifying the isolated galactic systems, each of which consists of a single host galaxy and its satellites, from the Seventh Data Release of the Sloan Digital Sky Survey and reconstructing linearly the velocity shear field in the local universe, we measure the alignments between the relative positions of the satellites from their isolated hosts and the principal axes of the local velocity shear tensors projected onto the plane of sky. We find a clear signal that the galactic satellites in isolated systems are located preferentially along the directions of the minor principal axes of the large-scale velocity shear field. Those galactic satellites that are spirals, are brighter, are located at distances larger than the projected virial radii of the hosts, and belong to the spiral hosts yield stronger alignment signals, which implies that the alignment strength depends on the formation and accretion epochs of the galactic satellites. It is also shown that the alignment strength is quite insensitive to the cosmic web environment, as well as the size and luminosity of the isolated hosts. Although this result is consistent with the numerical finding of Libeskind et al. based on an N-body experiment, owing to the very low significance of the observed signals, it remains inconclusive whether or not the velocity shear effect on the satellite distribution is truly universal.

  4. Early detection of tick-borne encephalitis virus spatial distribution and activity in the province of Trento, northern Italy

    Directory of Open Access Journals (Sweden)

    Annapaola Rizzoli

    2007-05-01

    Full Text Available New human cases of tick-borne encephalitis (TBE have recently been recorded outside the recognised foci of this disease, i.e. in the province of Trento in northern Italy. In order to predict the highest risk areas for increased TBE virus activity, we have combined cross-sectional serological data, obtained from 459 domestic goats, with analysis of the autumnal cooling rate based on Moderate Resolution Imaging Spectroradiometer (MODIS land surface temperature (LST data. A significant relationship between finding antibodies against the virus in serum (seroprevalence in goats and the autumnal cooling rate was detected, indicating that the transmission intensity of the virus does not only vary spatially, but also in relation to climatic factors. Virus seroprevalence in goats was correlated with the occurrence of TBE in humans and also with the average number of forestry workers’ tick bites, demonstrating that serological screening of domestic animals, combined with an analysis of the autumnal cooling rate, can be used as early-warning predictors of TBE risk in humans.

  5. Spatial and Temporal Variation of Japanese encephalitis Disease and Detection of Disease Hotspots: a Case Study of Gorakhpur District, Uttar Pradesh, India

    Science.gov (United States)

    Verma, S.; Gupta, R. D.

    2014-11-01

    In recent times, Japanese Encephalitis (JE) has emerged as a serious public health problem. In India, JE outbreaks were recently reported in Uttar Pradesh, Gorakhpur. The present study presents an approach to use GIS for analyzing the reported cases of JE in the Gorakhpur district based on spatial analysis to bring out the spatial and temporal dynamics of the JE epidemic. The study investigates spatiotemporal pattern of the occurrence of disease and detection of the JE hotspot. Spatial patterns of the JE disease can provide an understanding of geographical changes. Geospatial distribution of the JE disease outbreak is being investigated since 2005 in this study. The JE incidence data for the years 2005 to 2010 is used. The data is then geo-coded at block level. Spatial analysis is used to evaluate autocorrelation in JE distribution and to test the cases that are clustered or dispersed in space. The Inverse Distance Weighting interpolation technique is used to predict the pattern of JE incidence distribution prevalent across the study area. Moran's I Index (Moran's I) statistics is used to evaluate autocorrelation in spatial distribution. The Getis-Ord Gi*(d) is used to identify the disease areas. The results represent spatial disease patterns from 2005 to 2010, depicting spatially clustered patterns with significant differences between the blocks. It is observed that the blocks on the built up areas reported higher incidences.

  6. An adaptive Tikhonov regularization method for fluorescence molecular tomography.

    Science.gov (United States)

    Cao, Xu; Zhang, Bin; Wang, Xin; Liu, Fei; Liu, Ke; Luo, Jianwen; Bai, Jing

    2013-08-01

    The high degree of absorption and scattering of photons propagating through biological tissues makes fluorescence molecular tomography (FMT) reconstruction a severe ill-posed problem and the reconstructed result is susceptible to noise in the measurements. To obtain a reasonable solution, Tikhonov regularization (TR) is generally employed to solve the inverse problem of FMT. However, with a fixed regularization parameter, the Tikhonov solutions suffer from low resolution. In this work, an adaptive Tikhonov regularization (ATR) method is presented. Considering that large regularization parameters can smoothen the solution with low spatial resolution, while small regularization parameters can sharpen the solution with high level of noise, the ATR method adaptively updates the spatially varying regularization parameters during the iteration process and uses them to penalize the solutions. The ATR method can adequately sharpen the feasible region with fluorescent probes and smoothen the region without fluorescent probes resorting to no complementary priori information. Phantom experiments are performed to verify the feasibility of the proposed method. The results demonstrate that the proposed method can improve the spatial resolution and reduce the noise of FMT reconstruction at the same time.

  7. Spatial distribution

    DEFF Research Database (Denmark)

    Borregaard, Michael Krabbe; Hendrichsen, Ditte Katrine; Nachman, Gøsta Støger

    2008-01-01

    Living organisms are distributed over the entire surface of the planet. The distribution of the individuals of each species is not random; on the contrary, they are strongly dependent on the biology and ecology of the species, and vary over different spatial scale. The structure of whole...... populations reflects the location and fragmentation pattern of the habitat types preferred by the species, and the complex dynamics of migration, colonization, and population growth taking place over the landscape. Within these, individuals are distributed among each other in regular or clumped patterns......, depending on the nature of intraspecific interactions between them: while the individuals of some species repel each other and partition the available area, others form groups of varying size, determined by the fitness of each group member. The spatial distribution pattern of individuals again strongly...

  8. Regularly timed events amid chaos

    Science.gov (United States)

    Blakely, Jonathan N.; Cooper, Roy M.; Corron, Ned J.

    2015-11-01

    We show rigorously that the solutions of a class of chaotic oscillators are characterized by regularly timed events in which the derivative of the solution is instantaneously zero. The perfect regularity of these events is in stark contrast with the well-known unpredictability of chaos. We explore some consequences of these regularly timed events through experiments using chaotic electronic circuits. First, we show that a feedback loop can be implemented to phase lock the regularly timed events to a periodic external signal. In this arrangement the external signal regulates the timing of the chaotic signal but does not strictly lock its phase. That is, phase slips of the chaotic oscillation persist without disturbing timing of the regular events. Second, we couple the regularly timed events of one chaotic oscillator to those of another. A state of synchronization is observed where the oscillators exhibit synchronized regular events while their chaotic amplitudes and phases evolve independently. Finally, we add additional coupling to synchronize the amplitudes, as well, however in the opposite direction illustrating the independence of the amplitudes from the regularly timed events.

  9. Online co-regularized algorithms

    NARCIS (Netherlands)

    Ruijter, T. de; Tsivtsivadze, E.; Heskes, T.

    2012-01-01

    We propose an online co-regularized learning algorithm for classification and regression tasks. We demonstrate that by sequentially co-regularizing prediction functions on unlabeled data points, our algorithm provides improved performance in comparison to supervised methods on several UCI benchmarks

  10. Online co-regularized algorithms

    NARCIS (Netherlands)

    Ruijter, T. de; Tsivtsivadze, E.; Heskes, T.

    2012-01-01

    We propose an online co-regularized learning algorithm for classification and regression tasks. We demonstrate that by sequentially co-regularizing prediction functions on unlabeled data points, our algorithm provides improved performance in comparison to supervised methods on several UCI benchmarks

  11. Nonconvex Regularization in Remote Sensing

    Science.gov (United States)

    Tuia, Devis; Flamary, Remi; Barlaud, Michel

    2016-11-01

    In this paper, we study the effect of different regularizers and their implications in high dimensional image classification and sparse linear unmixing. Although kernelization or sparse methods are globally accepted solutions for processing data in high dimensions, we present here a study on the impact of the form of regularization used and its parametrization. We consider regularization via traditional squared (2) and sparsity-promoting (1) norms, as well as more unconventional nonconvex regularizers (p and Log Sum Penalty). We compare their properties and advantages on several classification and linear unmixing tasks and provide advices on the choice of the best regularizer for the problem at hand. Finally, we also provide a fully functional toolbox for the community.

  12. Conservative regularization of compressible flow

    CERN Document Server

    Krishnaswami, Govind S; Thyagaraja, Anantanarayanan

    2015-01-01

    Ideal Eulerian flow may develop singularities in vorticity w. Navier-Stokes viscosity provides a dissipative regularization. We find a local, conservative regularization - lambda^2 w times curl(w) of compressible flow and compressible MHD: a three dimensional analogue of the KdV regularization of the one dimensional kinematic wave equation. The regulator lambda is a field subject to the constitutive relation lambda^2 rho = constant. Lambda is like a position-dependent mean-free path. Our regularization preserves Galilean, parity and time-reversal symmetries. We identify locally conserved energy, helicity, linear and angular momenta and boundary conditions ensuring their global conservation. Enstrophy is shown to remain bounded. A swirl velocity field is identified, which transports w/rho and B/rho generalizing the Kelvin-Helmholtz and Alfven theorems. A Hamiltonian and Poisson bracket formulation is given. The regularized equations are used to model a rotating vortex, channel flow, plane flow, a plane vortex ...

  13. Approximate Sparse Regularized Hyperspectral Unmixing

    Directory of Open Access Journals (Sweden)

    Chengzhi Deng

    2014-01-01

    Full Text Available Sparse regression based unmixing has been recently proposed to estimate the abundance of materials present in hyperspectral image pixel. In this paper, a novel sparse unmixing optimization model based on approximate sparsity, namely, approximate sparse unmixing (ASU, is firstly proposed to perform the unmixing task for hyperspectral remote sensing imagery. And then, a variable splitting and augmented Lagrangian algorithm is introduced to tackle the optimization problem. In ASU, approximate sparsity is used as a regularizer for sparse unmixing, which is sparser than l1 regularizer and much easier to be solved than l0 regularizer. Three simulated and one real hyperspectral images were used to evaluate the performance of the proposed algorithm in comparison to l1 regularizer. Experimental results demonstrate that the proposed algorithm is more effective and accurate for hyperspectral unmixing than state-of-the-art l1 regularizer.

  14. Regular Small-World Network

    Institute of Scientific and Technical Information of China (English)

    ZOU Zhi-Yun; MAO Bao-Hua; HAO Hai-Ming; GAO Jian-Zhi; YANG Jie-Jiao

    2009-01-01

    According to the deficiencies in Watts and Strogatz's small-world network model, we present a new regular model to establish the small-world network. Besides the property of the small-world, this model has other properties such as accuracy in controlling the average shortest path length L, and the average clustering coefficient C, also regular network topology as well as enhanced network robustness. This method improves the construction of the small-world network essentially, so that the regular small-world network closely resembles the actual network. We also present studies on the relationships among the quantities of a variety of edges, L and C in regular small-world network in detail. This research lays the foundation for the establishment of the regular small-world network and acts as a good guidance for further research of this model and its applications.

  15. Improving the spatial resolution of soft X-ray detection using an Electron-Multiplying Charge-Coupled Device

    Science.gov (United States)

    Soman, M. R.; Hall, D. J.; Tutt, J. H.; Murray, N. J.; Holland, A. D.; Schmitt, T.; Raabe, J.; Schmitt, B.

    2013-01-01

    The Super Advanced X-ray Emission Spectrometer (SAXES) is an instrument at the Swiss Light Source designed for Resonant Inelastic X-ray Scattering with an energy resolution (E/ΔE) better than 12000 at 930 eV. Improvements to the instrument have been predicted that could allow the energy resolution to be improved by a factor of two. To achieve this, the spatial resolution of the detector (currently a Charge-Coupled Device, CCD) over which the energy spectrum is dispersed would have to be improved to better than 5 μm. X-ray photons with energies between a few hundred to a few thousand electron volts primarily interact within the field-free region of back-illuminated CCDs, where each photon forms an electron cloud that diffuses isotropically before reaching the depleted region close to the electrodes. Each photon's electron cloud is likely to be detected as an event with signal split across multiple pixels. Analysing these split events using centroiding techniques allows the photon's interaction position to be determined to a sub-pixel level. PolLux is a soft X-ray microspectroscopy endstation at the Swiss Light Source that can focus 200 eV to 1200 eV X-rays to a spot size of approximately 20 nm. Previous studies using data taken with a linear scan across the centre of a pixel in 3 μm steps predicted an improved resolution by applying centroiding techniques and using an Electron-Multiplying CCD (EM-CCD). In this study, a full 2D map of the centroiding accuracy in the pixel is presented, formed by rastering in two dimensions across the image plane in single micron steps. The improved spatial resolution from centroiding events in the EM-CCD in all areas of the pixel over the standard CCD is attributed to the improved signal to noise ratio provided by the multiplication register even at high pixel readout speeds (tens of MHz).

  16. GRACE leakage error correction with regularization technique: Case studies in Greenland and Antarctica

    Science.gov (United States)

    Mu, Dapeng; Yan, Haoming; Feng, Wei; Peng, Peng

    2017-01-01

    Filtering is a necessary step in the Gravity Recovery and Climate Experiment (GRACE) data processing, but leads to signal leakage and attenuation obviously, and adversely affects the quality of global and regional mass change estimates. We propose to use the Tikhonov regularization technique with the L-curve method to solve a correction equation which can reduce the leakage error caused by filter involved in GRACE data processing. We first demonstrate that the leakage error caused by the Gaussian filter can be well corrected by our regularization technique with simulation studies in Greenland and Antarctica. Furthermore, our regularization technique can restore the spatial distribution of original mass changes. For example, after applying the regularization method to GRAEC data (2003-2012), we find that GRACE mass changes tend to move from interior to coastal area in Greenland, which are consistent with recent other studies. After being corrected for glacial isostatic adjustment (GIA) effect, our results show that the ice mass loss rates were 274 ± 30 and 107 ± 34 Gt/yr in Greenland and Antarctica from 2003 to 2012, respectively. And a 10 ± 4 Gt/yr increase rate in Greenland interior is also detected.

  17. Evaluation of Different Change Detection Techniques in Forestry for Improvement of Spatial Objects Extraction Algorithms by Very High Resolution Remote Sensing Digital Imagery

    Science.gov (United States)

    Amiri, N.

    2013-09-01

    Earth observations which are being useable by spatial analysis ability play an important role in detecting, management and solving environmental problems such as climate changes, deforestation, disasters, land use, water resource and carbon cycle. Remote sensing technology in combination with geospatial information system (GIS) can render reliable information on vegetation cover. Satellite Remote sensed data and GIS for land cover/use with its changes is a key to many diverse applications such as Forestry. Change detection can be defined as the process of identifying differences in the state of an object or phenomenon by observing it at different times. The analysis of the spatial extent and temporal change of vegetation cover (Forest) by using remotely sensed data is critically importance to natural resource management sciences. The main aim of this review paper is to go through the different change detection methods and algorithms based on very high resolution remote sensing imagery data, evaluate the quality of the spatial individual crown cover extraction in forests with high density, analyse, compare the results by optimized performance of control data for the same objects to provide the improvement in technique for detection and improve the mathematical sides of the change detection algorithms for high dense forests regions with different boundaries.

  18. Automated three-dimensional detection and classification of living organisms using digital holographic microscopy with partial spatial coherent source: application to the monitoring of drinking water resources.

    Science.gov (United States)

    El Mallahi, Ahmed; Minetti, Christophe; Dubois, Frank

    2013-01-01

    In this paper, we investigate the use of a digital holographic microscope working with partially coherent spatial illumination for an automated detection and classification of living organisms. A robust automatic method based on the computation of propagating matrices is proposed to detect the 3D position of organisms. We apply this procedure to the evaluation of drinking water resources by developing a classification process to identify parasitic protozoan Giardia lamblia cysts among two other similar organisms. By selecting textural features from the quantitative optical phase instead of morphological ones, a robust classifier is built to propose a new method for the unambiguous detection of Giardia lamblia cyst that present a critical contamination risk.

  19. A Network-Constrained Integrated Method for Detecting Spatial Cluster and Risk Location of Traffic Crash: A Case Study from Wuhan, China

    Directory of Open Access Journals (Sweden)

    Ke Nie

    2015-03-01

    Full Text Available Research on spatial cluster detection of traffic crash (TC at the city level plays an essential role in safety improvement and urban development. This study aimed to detect spatial cluster pattern and identify riskier road segments (RRSs of TC constrained by network with a two-step integrated method, called NKDE-GLINCS combining density estimation and spatial autocorrelation. The first step is novel and involves in spreading TC count to a density surface using Network-constrained Kernel Density Estimation (NKDE. The second step is the process of calculating local indicators of spatial association (LISA using Network-constrained Getis-Ord Gi* (GLINCS. GLINCS takes the smoothed TC density as input value to identify locations of road segments with high risk. This method was tested using the TC data in 2007 in Wuhan, China. The results demonstrated that the method was valid to delineate TC cluster and identify risk road segments. Besides, it was more effective compared with traditional GLINCS using TC counting as input. Moreover, the top 20 road segments with high-high TC density at the significance level of 0.1 were listed. These results can promote a better identification of RRS, which is valuable in the pursuit of improving transit safety and sustainability in urban road network. Further research should address spatial-temporal analysis and TC factors exploration.

  20. Multi-temporal thermal analyses for submarine groundwater discharge (SGD) detection over large spatial scales in the Mediterranean

    Science.gov (United States)

    Hennig, Hanna; Mallast, Ulf; Merz, Ralf

    2015-04-01

    Submarine groundwater discharge (SGD) sites act as important pathways for nutrients and contaminants that deteriorate marine ecosystems. In the Mediterranean it is estimated that 75% of freshwater input is contributed from karst aquifers. Thermal remote sensing can be used for a pre-screening of potential SGD sites in order to optimize field surveys. Although different platforms (ground-, air- and spaceborne) may serve for thermal remote sensing, the most cost-effective are spaceborne platforms (satellites) that likewise cover the largest spatial scale (>100 km per image). Therefore an automatized and objective approach that uses thermal satellite images from Landsat 7 and Landsat 8 was used to localize potential SGD sites on a large spatial scale. The method using descriptive statistic parameter specially range and standard deviation by (Mallast et al., 2014) was adapted to the Mediterranean Sea. Since the method was developed for the Dead Sea were satellite images with cloud cover are rare and no sea level change occurs through tidal cycles it was essential to adapt the method to a region where tidal cycles occur and cloud cover is more frequent . These adaptations include: (1) an automatic and adaptive coastline detection (2) include and process cloud covered scenes to enlarge the data basis, (3) implement tidal data in order to analyze low tide images as SGD is enhanced during these phases and (4) test the applicability for Landsat 8 images that will provide data in the future once Landsat 7 stops working. As previously shown, the range method shows more accurate results compared to the standard deviation. However, the result exclusively depends on two scenes (minimum and maximum) and is largely influenced by outliers. Counteracting on this drawback we developed a new approach. Since it is assumed that sea surface temperature (SST) is stabilized by groundwater at SGD sites, the slope of a bootstrapped linear model fitted to sorted SST per pixel would be less

  1. An automated flow for directed evolution based on detection of promiscuous scaffolds using spatial and electrostatic properties of catalytic residues.

    Directory of Open Access Journals (Sweden)

    Sandeep Chakraborty

    Full Text Available The aspiration to mimic and accelerate natural evolution has fueled interest in directed evolution experiments, which endow or enhance functionality in enzymes. Barring a few de novo approaches, most methods take a template protein having the desired activity, known active site residues and structure, and proceed to select a target protein which has a pre-existing scaffold congruent to the template motif. Previously, we have established a computational method (CLASP based on spatial and electrostatic properties to detect active sites, and a method to quantify promiscuity in proteins. We exploit the prospect of promiscuous active sites to serve as the starting point for directed evolution and present a method to select a target protein which possesses a significant partial match with the template scaffold (DECAAF. A library of partial motifs, constructed from the active site residues of the template protein, is used to rank a set of target proteins based on maximal significant matches with the partial motifs, and cull out the best candidate from the reduced set as the target protein. Considering the scenario where this 'incubator' protein lacks activity, we identify mutations in the target protein that will mirror the template motif by superimposing the target and template protein based on the partial match. Using this superimposition technique, we analyzed the less than expected gain of activity achieved by an attempt to induce β-lactamase activity in a penicillin binding protein (PBP (PBP-A from T. elongatus, and attributed this to steric hindrance from neighboring residues. We also propose mutations in PBP-5 from E. coli, which does not have similar steric constraints. The flow details have been worked out in an example which aims to select a substitute protein for human neutrophil elastase, preferably related to grapevines, in a chimeric anti-microbial enzyme which bolsters the innate immune defense system of grapevines.

  2. The role of the dentate gyrus, CA3a,b, and CA3c for detecting spatial and environmental novelty.

    Science.gov (United States)

    Hunsaker, Michael R; Rosenberg, Jenna S; Kesner, Raymond P

    2008-01-01

    It has been suggested that the dentate gyrus (DG) and CA3 cooperate to efficiently process spatial information. The DG has been proposed to be important for fine spatial discrimination, and the CA3 has been proposed to mediate larger scale spatial information processing. To evaluate the roles of the DG and CA3a,b for spatial processing, we developed a task that measures responses to either overall environmental novelty or a response to more subtle changes within the environment. Animals with lesions to the DG showed impaired novelty detection for both environment as well as smaller changes in the environment, whereas animals with lesions to CA3a,b showed no such deficits. A closer look at the lesions suggested that the CA3 lesions included only CA3a and CA3b, but spared CA3c. To test the role of the spared CA3c region, animals with selective lesions to CA3c that spared CA3a,b were run on the same task and showed an intermediate pattern of deficits. These results suggest that the DG is critical for spatial information processing. These data also suggest that CA3 is a heterogeneous structure, with CA3c lesioned animals showing greater spatial processing deficits than CA3a,b lesioned animals. These findings extend our knowledge of hippocampal function and need to be accounted for in future computational models.

  3. An ERP study of visual change detection: effects of magnitude of spatial frequency changes on the change-related posterior positivity.

    Science.gov (United States)

    Kimura, Motohiro; Katayama, Jun'ichi; Murohashi, Harumitsu

    2006-10-01

    In event-related brain potential (ERP) studies using a visual S1-S2 matching task, change stimuli elicit a posterior positivity at around 100-200 ms. In the present study, we investigated the effects of magnitude of spatial frequency changes on change-related positivity. Each trial consisted of two sequentially presented stimuli (S1-S2), where S2 was either (1) the same as S1 (i.e., NO-change, p=.40), (2) different from S1 in spatial frequency only (SF-change, .40), (3) different in orientation only (OR-change, .10), or (4) different in both spatial frequency and orientation (BOTH-change, .10). Further, three magnitude conditions (Large, Medium, and Small) were used to examine the effect of the magnitude of the spatial frequency change. Participant's (N=12) task was to respond to S2 with a change in orientation (from vertical to horizontal, or from horizontal to vertical) regardless of the spatial frequency of the stimulus. Changes in the spatial frequency elicited change-related positivity at a latency range of about 120-180 ms, which was followed by a central negativity (N270) and a late positive component (LPC). The amplitude of the change-related positivity tends to be enhanced as the magnitude of the change is increased. These results support the notion that the change-related positivity reflects memory-based change detection in the human visual system.

  4. A Criterion for Regular Sequences

    Indian Academy of Sciences (India)

    D P Patil; U Storch; J Stückrad

    2004-05-01

    Let be a commutative noetherian ring and $f_1,\\ldots,f_r \\in R$. In this article we give (cf. the Theorem in $\\mathcal{x}$2) a criterion for $f_1,\\ldots,f_r$ to be regular sequence for a finitely generated module over which strengthens and generalises a result in [2]. As an immediate consequence we deduce that if $V(g_1,\\ldots,g_r) \\subseteq V(f_1,\\ldots,f_r)$ in Spec and if $f_1,\\ldots,f_r$ is a regular sequence in , then $g_1,\\ldots,g_r$ is also a regular sequence in .

  5. On Regular Power-Substitution

    Institute of Scientific and Technical Information of China (English)

    Huanyin CHEN

    2009-01-01

    The necessary and sufficient conditions under which a ring satisfies regular power-substitution are investigated. It is shown that a ring R satisfies regular power-substitution if and only if a(-~)b in R implies that there exist n ∈ N and a U ∈ GLn(R) such that aU =Ub if and only if for any regular x ∈ R there exist m,n ∈ N and U ∈ GLn(R) such that xmIn = xmUxm, where a(-~)b means that there exists x, y, z ∈ R such that a = ybx, b = xaz and x = xyx = xzx. It is proved that every directly finite simple ring satisfies regular power-substitution. Some applications for stably free R-modules are also obtained.

  6. NONCONVEX REGULARIZATION FOR SHAPE PRESERVATION

    Energy Technology Data Exchange (ETDEWEB)

    CHARTRAND, RICK [Los Alamos National Laboratory

    2007-01-16

    The authors show that using a nonconvex penalty term to regularize image reconstruction can substantially improve the preservation of object shapes. The commonly-used total-variation regularization, {integral}|{del}u|, penalizes the length of the object edges. They show that {integral}|{del}u|{sup p}, 0 < p < 1, only penalizes edges of dimension at least 2-p, and thus finite-length edges not at all. We give numerical examples showing the resulting improvement in shape preservation.

  7. Regularization with a pruning prior

    DEFF Research Database (Denmark)

    Goutte, Cyril; Hansen, Lars Kai

    1997-01-01

    We investigate the use of a regularization priorthat we show has pruning properties. Analyses areconducted both using a Bayesian framework and withthe generalization method, on a simple toyproblem. Results are thoroughly compared withthose obtained with a traditional weight decay.......We investigate the use of a regularization priorthat we show has pruning properties. Analyses areconducted both using a Bayesian framework and withthe generalization method, on a simple toyproblem. Results are thoroughly compared withthose obtained with a traditional weight decay....

  8. Regular and Periodic Tachyon Kinks

    OpenAIRE

    Bazeia, D.; Menezes, R.; Ramos, J. G.

    2004-01-01

    We search for regular tachyon kinks in an extended model, which includes the tachyon action recently proposed to describe the tachyon field. The extended model that we propose adds a new contribution to the tachyon action, and seems to enrich the present scenario for the tachyon field. We have found stable tachyon kinks of regular profile, which may appropriately lead to the singular kink found by Sen sometime ago. Also, under specific conditions we may find periodic array of kink-antikink co...

  9. Commuting Π-regular rings

    Directory of Open Access Journals (Sweden)

    Shervin Sahebi

    2014-05-01

    Full Text Available ‎$R$ is called commuting regular ring (resp‎. ‎semigroupif‎ for each $x,y\\in R$ there exists $a\\in R$‎ such that$xy=yxayx$‎. ‎In this paper‎, ‎we introduce the concept of‎‎commuting $\\pi$-regular rings (resp‎. ‎semigroups and‎‎study various properties of them.

  10. Chimeric mitochondrial peptides from contiguous regular and swinger RNA

    Directory of Open Access Journals (Sweden)

    Hervé Seligmann

    2016-01-01

    Full Text Available Previous mass spectrometry analyses described human mitochondrial peptides entirely translated from swinger RNAs, RNAs where polymerization systematically exchanged nucleotides. Exchanges follow one among 23 bijective transformation rules, nine symmetric exchanges (X ↔ Y, e.g. A ↔ C and fourteen asymmetric exchanges (X → Y → Z → X, e.g. A → C → G → A, multiplying by 24 DNA's protein coding potential. Abrupt switches from regular to swinger polymerization produce chimeric RNAs. Here, human mitochondrial proteomic analyses assuming abrupt switches between regular and swinger transcriptions, detect chimeric peptides, encoded by part regular, part swinger RNA. Contiguous regular- and swinger-encoded residues within single peptides are stronger evidence for translation of swinger RNA than previously detected, entirely swinger-encoded peptides: regular parts are positive controls matched with contiguous swinger parts, increasing confidence in results. Chimeric peptides are 200× rarer than swinger peptides (3/100,000 versus 6/1000. Among 186 peptides with >8 residues for each regular and swinger parts, regular parts of eleven chimeric peptides correspond to six among the thirteen recognized, mitochondrial protein-coding genes. Chimeric peptides matching partly regular proteins are rarer and less expressed than chimeric peptides matching non-coding sequences, suggesting targeted degradation of misfolded proteins. Present results strengthen hypotheses that the short mitogenome encodes far more proteins than hitherto assumed. Entirely swinger-encoded proteins could exist.

  11. Chimeric mitochondrial peptides from contiguous regular and swinger RNA.

    Science.gov (United States)

    Seligmann, Hervé

    2016-01-01

    Previous mass spectrometry analyses described human mitochondrial peptides entirely translated from swinger RNAs, RNAs where polymerization systematically exchanged nucleotides. Exchanges follow one among 23 bijective transformation rules, nine symmetric exchanges (X ↔ Y, e.g. A ↔ C) and fourteen asymmetric exchanges (X → Y → Z → X, e.g. A → C → G → A), multiplying by 24 DNA's protein coding potential. Abrupt switches from regular to swinger polymerization produce chimeric RNAs. Here, human mitochondrial proteomic analyses assuming abrupt switches between regular and swinger transcriptions, detect chimeric peptides, encoded by part regular, part swinger RNA. Contiguous regular- and swinger-encoded residues within single peptides are stronger evidence for translation of swinger RNA than previously detected, entirely swinger-encoded peptides: regular parts are positive controls matched with contiguous swinger parts, increasing confidence in results. Chimeric peptides are 200 × rarer than swinger peptides (3/100,000 versus 6/1000). Among 186 peptides with > 8 residues for each regular and swinger parts, regular parts of eleven chimeric peptides correspond to six among the thirteen recognized, mitochondrial protein-coding genes. Chimeric peptides matching partly regular proteins are rarer and less expressed than chimeric peptides matching non-coding sequences, suggesting targeted degradation of misfolded proteins. Present results strengthen hypotheses that the short mitogenome encodes far more proteins than hitherto assumed. Entirely swinger-encoded proteins could exist.

  12. Condition Number Regularized Covariance Estimation.

    Science.gov (United States)

    Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala

    2013-06-01

    Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the "large p small n" setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required.

  13. Condition Number Regularized Covariance Estimation*

    Science.gov (United States)

    Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala

    2012-01-01

    Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the “large p small n” setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required. PMID:23730197

  14. Implementation of 3D spatial indexing and compression in a large-scale molecular dynamics simulation database for rapid atomic contact detection

    Directory of Open Access Journals (Sweden)

    Toofanny Rudesh D

    2011-08-01

    Full Text Available Abstract Background Molecular dynamics (MD simulations offer the ability to observe the dynamics and interactions of both whole macromolecules and individual atoms as a function of time. Taken in context with experimental data, atomic interactions from simulation provide insight into the mechanics of protein folding, dynamics, and function. The calculation of atomic interactions or contacts from an MD trajectory is computationally demanding and the work required grows exponentially with the size of the simulation system. We describe the implementation of a spatial indexing algorithm in our multi-terabyte MD simulation database that significantly reduces the run-time required for discovery of contacts. The approach is applied to the Dynameomics project data. Spatial indexing, also known as spatial hashing, is a method that divides the simulation space into regular sized bins and attributes an index to each bin. Since, the calculation of contacts is widely employed in the simulation field, we also use this as the basis for testing compression of data tables. We investigate the effects of compression of the trajectory coordinate tables with different options of data and index compression within MS SQL SERVER 2008. Results Our implementation of spatial indexing speeds up the calculation of contacts over a 1 nanosecond (ns simulation window by between 14% and 90% (i.e., 1.2 and 10.3 times faster. For a 'full' simulation trajectory (51 ns spatial indexing reduces the calculation run-time between 31 and 81% (between 1.4 and 5.3 times faster. Compression resulted in reduced table sizes but resulted in no significant difference in the total execution time for neighbour discovery. The greatest compression (~36% was achieved using page level compression on both the data and indexes. Conclusions The spatial indexing scheme significantly decreases the time taken to calculate atomic contacts and could be applied to other multidimensional neighbor discovery

  15. Detection of multimode spatial correlation in PDC and application to the absolute calibration of a CCD camera.

    Science.gov (United States)

    Brida, Giorgio; Degiovanni, Ivo Pietro; Genovese, Marco; Rastello, Maria Luisa; Ruo-Berchera, Ivano

    2010-09-27

    We propose and demonstrate experimentally a new method based on the spatial entanglement for the absolute calibration of analog detectors. The idea consists on measuring the sub-shot-noise intensity correlation between two branches of parametric down conversion, containing many pairwise correlated spatial modes. We calibrate a scientific CCD camera and a preliminary evaluation of the uncertainty indicates the metrological interest of the method.

  16. MONITORING TREE POPULATION DYNAMICS IN ARID ZONE THROUGH MULTIPLE TEMPORAL SCALES: INTEGRATION OF SPATIAL ANALYSIS, CHANGE DETECTION AND FIELD LONG TERM MONITORING

    Directory of Open Access Journals (Sweden)

    S. Isaacson

    2016-06-01

    Full Text Available High mortality rates and lack of recruitment in the acacia populations throughout the Negev Desert and the Arava rift valley of Israel have been reported in previous studies. However, it is difficult to determine whether these reports can be evidence to a significant decline trend of the trees populations. This is because of the slow dynamic processes of acaia tree populations and the lack of long term continuous monitoring data. We suggest a new data analysis technique that expands the time scope of the field long term monitoring of trees in arid environments. This will enables us to improve our understanding of the spatial and temporal changes of these populations. We implemented two different approaches in order to expand the time scope of the acacia population field survey: (1 individual based tree change detection using Corona satellite images and (2 spatial analysis of trees population, converting spatial data into temporal data. The next step was to integrate the results of the two analysis techniques (change detection and spatial analysis with field monitoring. This technique can be implemented to other tree populations in arid environments to help assess the vegetation conditions and dynamics of those ecosystems.

  17. Effect of Soil Sampling Density on Detected Spatial Variability of Soil Organic Carbon in a Red Soil Region of China

    Institute of Scientific and Technical Information of China (English)

    YU Dong-Sheng; ZHANG Zhong-Qi; YANG Hao; SHI Xue-Zheng; TAN Man-Zhi; SUN Wei-Xia; WANG Hong-Jie

    2011-01-01

    Spatial variability of soil organic carbon (SOC) of different land use patterns and soil types was examined in a county-wide red soil region of South China, using six sampling densities, 14, 34, 68, 130, 255, and 525 samples designed by the method of grid sampling in 6 different grid sizes, labeled as D14, D34, D68, D130, D255, and D525, respectively. The results showed that the coefficients of variation (CVs) of SOC decreased gradually from 62.8% to 47.4% with the increase in soil sampling densities. The SOC CVs in the paddy field change slightly from 30.8% to 28.7%, while those of the dry farmland and forest land decreased remarkably from 58.1%to 48.7% and from 99.3% to 64.4%, respectively. The SOC CVs of the paddy soil change slightly, while those of red soil decreased remarkably from 82.8% to 63.9%. About 604, 500, and 353 (P < 0.05) samples would be needed a number of years later if the SOC change was supposedly 1.52 g kg-2, based on the CVs of SOC acquired from the present sampling densities of D14, D68, and D525,respectively. Moreover, based on the same SOC change and the present time CVs at D255, the ratio of samples needed for paddy field, dry farmland, and forest land should be 1:0.81:3.33, while the actual corresponding ratio in an equal interval grid sampling was 1:0.74:0.46. These indicated that the sampling density had important effect on the detection of SOC variability in the county-wide region, the equal interval grid sampling was not efficient enough, and the respective CV of each land use or soil type should be fully considered when determining the sampling number in the future.

  18. The mismatch-negativity (MMN) component of the auditory event-related potential to violations of abstract regularities: a review.

    Science.gov (United States)

    Paavilainen, Petri

    2013-05-01

    The mismatch-negativity (MMN) component of the event-related potential (ERP) has been extensively used to study the preattentive processing and storage of regularities in basic physical stimulus features (e.g., frequency, intensity, spatial location). However, studies reviewed in the present article reveal that the auditory analysis reflected by MMN also includes the detection and use of more complex, "abstract", regularities based, for example, on relationships between various physical features of the stimuli or in patterns present in the auditory stream. When these regularities are violated, then MMN is elicited. Thus, the central auditory system performs even at the pre-attentive, auditory-cortex level surprisingly "cognitive" operations, such as generalization leading to simple concept formation, rule extraction and prediction of future stimuli. The information extracted often seems to be in an implicit form, not directly available to conscious processes and difficult to express verbally. It can nevertheless influence the behavior of the subject, for example, the regularity violations can temporarily impair performance in the primary task. Neural, behavioral and cognitive events associated with the development of the regularity representations are discussed.

  19. Estimating signal loss in regularized GRACE gravity field solutions

    Science.gov (United States)

    Swenson, S. C.; Wahr, J. M.

    2011-05-01

    Gravity field solutions produced using data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are subject to errors that increase as a function of increasing spatial resolution. Two commonly used techniques to improve the signal-to-noise ratio in the gravity field solutions are post-processing, via spectral filters, and regularization, which occurs within the least-squares inversion process used to create the solutions. One advantage of post-processing methods is the ability to easily estimate the signal loss resulting from the application of the spectral filter by applying the filter to synthetic gravity field coefficients derived from models of mass variation. This is a critical step in the construction of an accurate error budget. Estimating the amount of signal loss due to regularization, however, requires the execution of the full gravity field determination process to create synthetic instrument data; this leads to a significant cost in computation and expertise relative to post-processing techniques, and inhibits the rapid development of optimal regularization weighting schemes. Thus, while a number of studies have quantified the effects of spectral filtering, signal modification in regularized GRACE gravity field solutions has not yet been estimated. In this study, we examine the effect of one regularization method. First, we demonstrate that regularization can in fact be performed as a post-processing step if the solution covariance matrix is available. Regularization then is applied as a post-processing step to unconstrained solutions from the Center for Space Research (CSR), using weights reported by the Centre National d'Etudes Spatiales/Groupe de Recherches de geodesie spatiale (CNES/GRGS). After regularization, the power spectra of the CSR solutions agree well with those of the CNES/GRGS solutions. Finally, regularization is performed on synthetic gravity field solutions derived from a land surface model, revealing that in

  20. Structural similarity regularization scheme for multiparameter seismic full waveform inversion

    NARCIS (Netherlands)

    Li, M.; Liang, L.; Abubakar, A.; Van den Berg, P.M.

    2013-01-01

    We introduce a new regularization scheme for multiparameter seismic full-waveform inversion (FWI). Using this scheme, we can constrain spatial variations of parameters which are having a weak sensitivity with the one that having a good sensitivity to the measurement, assuming that these parameters h

  1. Quotient Complexity of Regular Languages

    Directory of Open Access Journals (Sweden)

    Janusz Brzozowski

    2009-07-01

    Full Text Available The past research on the state complexity of operations on regular languages is examined, and a new approach based on an old method (derivatives of regular expressions is presented. Since state complexity is a property of a language, it is appropriate to define it in formal-language terms as the number of distinct quotients of the language, and to call it "quotient complexity". The problem of finding the quotient complexity of a language f(K,L is considered, where K and L are regular languages and f is a regular operation, for example, union or concatenation. Since quotients can be represented by derivatives, one can find a formula for the typical quotient of f(K,L in terms of the quotients of K and L. To obtain an upper bound on the number of quotients of f(K,L all one has to do is count how many such quotients are possible, and this makes automaton constructions unnecessary. The advantages of this point of view are illustrated by many examples. Moreover, new general observations are presented to help in the estimation of the upper bounds on quotient complexity of regular operations.

  2. Regular

    Indian Academy of Sciences (India)

    Ratanpal B S; Sharma Jaita

    2016-03-01

    The charged anisotropic star on paraboloidal space-time is reported by choosing a particular form of radial pressure and electric field intensity. The non-singular solution of Einstein–Maxwell system of equation has been derived and it is shown that the model satisfies all the physical plausibility conditions. It is observed that in the absence of electric field intensity, the model reducesto a particular case of uncharged Sharma and Ratanpal model. It is also observed that the parameter used in the electric field intensity directly affects mass of the star.

  3. Efficient Hyperelastic Regularization for Registration

    DEFF Research Database (Denmark)

    Darkner, Sune; Hansen, Michael Sass; Larsen, Rasmus;

    2011-01-01

    For most image registration problems a smooth one-to-one mapping is desirable, a diffeomorphism. This can be obtained using priors such as volume preservation, certain kinds of elasticity or both. The key principle is to regularize the strain of the deformation which can be done through penalizat......For most image registration problems a smooth one-to-one mapping is desirable, a diffeomorphism. This can be obtained using priors such as volume preservation, certain kinds of elasticity or both. The key principle is to regularize the strain of the deformation which can be done through...... penalization of the eigen values of the stress tensor. We present a computational framework for regularization of image registration for isotropic hyper elasticity. We formulate an efficient and parallel scheme for computing the principal stain based for a given parameterization by decomposing the left Cauchy...

  4. A photonic analog-to-digital converter using phase modulation and self-coherent detection with spatial oversampling.

    Science.gov (United States)

    Golani, Ori; Mauri, Luca; Pasinato, Fabiano; Cattaneo, Cristian; Consonnni, Guido; Balsamo, Stefano; Marom, Dan M

    2014-05-19

    We propose a new type of photonic analog-to-digital converter (ADC), designed for high-resolution (>7 bit) and high sampling rates (scalable to tens of GS/s). It is based on encoding the input analog voltage signal onto the phase of an optical pulse stream originating from a mode-locked laser, and uses spatial oversampling as a means to improve the conversion resolution. This paper describes the concept of spatial oversampling and draws its similarities to the commonly used temporal oversampling. The design and fabrication of a LiNbO(3)/silica hybrid photonic integrated circuit for implementing the spatial oversampling is shown, and its abilities are demonstrated experimentally by digitizing gigahertz signals (frequencies up to 18GHz) at an undersampled rate of 2.56GS/s with a conversion resolution of up to 7.6 effective bits. Oversampling factors of 1-4 are demonstrated.

  5. Spatial repolarization heterogeneity detected by magnetocardiography correlates with cardiac iron overload and adverse cardiac events in beta-thalassemia major.

    Directory of Open Access Journals (Sweden)

    Chun-An Chen

    Full Text Available BACKGROUND: Patients with transfusion-dependent beta-thalassemia major (TM are at risk for myocardial iron overload and cardiac complications. Spatial repolarization heterogeneity is known to be elevated in patients with certain cardiac diseases, but little is known in TM patients. The purpose of this study was to evaluate spatial repolarization heterogeneity in patients with TM, and to investigate the relationships between spatial repolarization heterogeneity, cardiac iron load, and adverse cardiac events. METHODS AND RESULTS: Fifty patients with TM and 55 control subjects received 64-channel magnetocardiography (MCG to determine spatial repolarization heterogeneity, which was evaluated by a smoothness index of QTc (SI-QTc, a standard deviation of QTc (SD-QTc, and a QTc dispersion. Left ventricular function and myocardial T2* values were assessed by cardiac magnetic resonance. Patients with TM had significantly greater SI-QTc, SD-QTc, and QTc dispersion compared to the control subjects (all p values<0.001. Spatial repolarization heterogeneity was even more pronounced in patients with significant iron overload (T2*<20 ms, n = 20 compared to those with normal T2* (all p values<0.001. Loge cardiac T2* correlated with SI-QTc (r = -0.609, p<0.001, SD-QTc (r = -0.572, p<0.001, and QTc dispersion (r = -0.622, p<0.001, while all these indices had no relationship with measurements of the left ventricular geometry or function. At the time of study, 10 patients had either heart failure or arrhythmia. All 3 indices of repolarization heterogeneity were related to the presence of adverse cardiac events, with areas under the receiver operating characteristic curves (ranged between 0.79 and 0.86, similar to that of cardiac T2*. CONCLUSIONS: Multichannel MCG demonstrated that patients with TM had increased spatial repolarization heterogeneity, which is related to myocardial iron load and adverse cardiac events.

  6. Regular algebra and finite machines

    CERN Document Server

    Conway, John Horton

    2012-01-01

    World-famous mathematician John H. Conway based this classic text on a 1966 course he taught at Cambridge University. Geared toward graduate students of mathematics, it will also prove a valuable guide to researchers and professional mathematicians.His topics cover Moore's theory of experiments, Kleene's theory of regular events and expressions, Kleene algebras, the differential calculus of events, factors and the factor matrix, and the theory of operators. Additional subjects include event classes and operator classes, some regulator algebras, context-free languages, communicative regular alg

  7. Disruption of the direct perforant path input to the CA1 subregion of the dorsal hippocampus interferes with spatial working memory and novelty detection.

    Science.gov (United States)

    Vago, David R; Kesner, Raymond P

    2008-06-03

    Subregional analyses of the hippocampus suggest CA1-dependent memory processes rely heavily upon interactions between the CA1 subregion and entorhinal cortex. There is evidence that the direct perforant path (pp) projection to CA1 is selectively modulated by dopamine while having little to no effect on the Schaffer collateral (SC) projection to CA1. The current study takes advantage of this pharmacological dissociation to demonstrate that local infusion of the non-selective dopamine agonist, apomorphine (10, 15 microg), into the CA1 subregion of awake animals produces impairments in working memory at intermediate (5 min), but not short-term (10 s) delays within a delayed non-match-to-place task on a radial arm maze. Sustained impairments were also found in a novel context with similar object-space relationships. Infusion of apomorphine into CA1 is also shown here to produce deficits in spatial, but not non-spatial novelty detection within an object exploration paradigm. In contrast, apomorphine produces no behavioral deficits when infused into the CA3 subregion or overlying cortex. These behavioral studies are supported by previous electrophysiological data that demonstrate local infusion of the same doses of apomorphine significantly modifies evoked responses in the distal dendrites of CA1 following angular bundle stimulation, but produces no significant effects in the proximal dendritic layer following stimulation of the SC. These results support a modulatory role for dopamine in EC-CA1, but not CA3-CA1 circuitry, and suggest the possibility of a fundamental role for EC-CA1 synaptic transmission in terms of detection of spatial novelty, and intermediate-term, but not short-term spatial working memory or object-novelty detection.

  8. UAV-based detection and spatial analyses of periglacial landforms on Demay Point (King George Island, South Shetland Islands, Antarctica)

    Science.gov (United States)

    Dąbski, Maciej; Zmarz, Anna; Pabjanek, Piotr; Korczak-Abshire, Małgorzata; Karsznia, Izabela; Chwedorzewska, Katarzyna J.

    2017-08-01

    High-resolution aerial images allow detailed analyses of periglacial landforms, which is of particular importance in light of climate change and resulting changes in active layer thickness. The aim of this study is to show possibilities of using UAV-based photography to perform spatial analysis of periglacial landforms on the Demay Point peninsula, King George Island, and hence to supplement previous geomorphological studies of the South Shetland Islands. Photogrammetric flights were performed using a PW-ZOOM fixed-winged unmanned aircraft vehicle. Digital elevation models (DEM) and maps of slope and contour lines were prepared in ESRI ArcGIS 10.3 with the Spatial Analyst extension, and three-dimensional visualizations in ESRI ArcScene 10.3 software. Careful interpretation of orthophoto and DEM, allowed us to vectorize polygons of landforms, such as (i) solifluction landforms (solifluction sheets, tongues, and lobes); (ii) scarps, taluses, and a protalus rampart; (iii) patterned ground (hummocks, sorted circles, stripes, nets and labyrinths, and nonsorted nets and stripes); (iv) coastal landforms (cliffs and beaches); (v) landslides and mud flows; and (vi) stone fields and bedrock outcrops. We conclude that geomorphological studies based on commonly accessible aerial and satellite images can underestimate the spatial extent of periglacial landforms and result in incomplete inventories. The PW-ZOOM UAV is well suited to gather detailed geomorphological data and can be used in spatial analysis of periglacial landforms in the Western Antarctic Peninsula region.

  9. Regularization destriping of remote sensing imagery

    Directory of Open Access Journals (Sweden)

    R. Basnayake

    2017-07-01

    Full Text Available We illustrate the utility of variational destriping for ocean color images from both multispectral and hyperspectral sensors. In particular, we examine data from a filter spectrometer, the Visible Infrared Imaging Radiometer Suite (VIIRS on the Suomi National Polar Partnership (NPP orbiter, and an airborne grating spectrometer, the Jet Population Laboratory's (JPL hyperspectral Portable Remote Imaging Spectrometer (PRISM sensor. We solve the destriping problem using a variational regularization method by giving weights spatially to preserve the other features of the image during the destriping process. The target functional penalizes the neighborhood of stripes (strictly, directionally uniform features while promoting data fidelity, and the functional is minimized by solving the Euler–Lagrange equations with an explicit finite-difference scheme. We show the accuracy of our method from a benchmark data set which represents the sea surface temperature off the coast of Oregon, USA. Technical details, such as how to impose continuity across data gaps using inpainting, are also described.

  10. Regularization destriping of remote sensing imagery

    Science.gov (United States)

    Basnayake, Ranil; Bollt, Erik; Tufillaro, Nicholas; Sun, Jie; Gierach, Michelle

    2017-07-01

    We illustrate the utility of variational destriping for ocean color images from both multispectral and hyperspectral sensors. In particular, we examine data from a filter spectrometer, the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar Partnership (NPP) orbiter, and an airborne grating spectrometer, the Jet Population Laboratory's (JPL) hyperspectral Portable Remote Imaging Spectrometer (PRISM) sensor. We solve the destriping problem using a variational regularization method by giving weights spatially to preserve the other features of the image during the destriping process. The target functional penalizes the neighborhood of stripes (strictly, directionally uniform features) while promoting data fidelity, and the functional is minimized by solving the Euler-Lagrange equations with an explicit finite-difference scheme. We show the accuracy of our method from a benchmark data set which represents the sea surface temperature off the coast of Oregon, USA. Technical details, such as how to impose continuity across data gaps using inpainting, are also described.

  11. Regularized Statistical Analysis of Anatomy

    DEFF Research Database (Denmark)

    Sjöstrand, Karl

    2007-01-01

    This thesis presents the application and development of regularized methods for the statistical analysis of anatomical structures. Focus is on structure-function relationships in the human brain, such as the connection between early onset of Alzheimer’s disease and shape changes of the corpus cal...

  12. Regularization in Matrix Relevance Learning

    NARCIS (Netherlands)

    Schneider, Petra; Bunte, Kerstin; Stiekema, Han; Hammer, Barbara; Villmann, Thomas; Biehl, Michael

    2010-01-01

    A In this paper, we present a regularization technique to extend recently proposed matrix learning schemes in learning vector quantization (LVQ). These learning algorithms extend the concept of adaptive distance measures in LVQ to the use of relevance matrices. In general, metric learning can displa

  13. Singularities of slice regular functions

    CERN Document Server

    Stoppato, Caterina

    2010-01-01

    Beginning in 2006, G. Gentili and D.C. Struppa developed a theory of regular quaternionic functions with properties that recall classical results in complex analysis. For instance, in each Euclidean ball centered at 0 the set of regular functions coincides with that of quaternionic power series converging in the same ball. In 2009 the author proposed a classification of singularities of regular functions as removable, essential or as poles and studied poles by constructing the ring of quotients. In that article, not only the statements, but also the proving techniques were confined to the special case of balls centered at 0. In a subsequent paper, F. Colombo, G. Gentili, I. Sabadini and D.C. Struppa (2009) identified a larger class of domains, on which the theory of regular functions is natural and not limited to quaternionic power series. The present article studies singularities in this new context, beginning with the construction of the ring of quotients and of Laurent-type expansions at points other than ...

  14. Regular inference as vertex coloring

    NARCIS (Netherlands)

    Costa Florêncio, C.; Verwer, S.

    2012-01-01

    This paper is concerned with the problem of supervised learning of deterministic finite state automata, in the technical sense of identification in the limit from complete data, by finding a minimal DFA consistent with the data (regular inference). We solve this problem by translating it in its enti

  15. Regularized Generalized Structured Component Analysis

    Science.gov (United States)

    Hwang, Heungsun

    2009-01-01

    Generalized structured component analysis (GSCA) has been proposed as a component-based approach to structural equation modeling. In practice, GSCA may suffer from multi-collinearity, i.e., high correlations among exogenous variables. GSCA has yet no remedy for this problem. Thus, a regularized extension of GSCA is proposed that integrates a ridge…

  16. Regular inference as vertex coloring

    NARCIS (Netherlands)

    Costa Florêncio, C.; Verwer, S.

    2012-01-01

    This paper is concerned with the problem of supervised learning of deterministic finite state automata, in the technical sense of identification in the limit from complete data, by finding a minimal DFA consistent with the data (regular inference). We solve this problem by translating it in its

  17. 76 FR 3629 - Regular Meeting

    Science.gov (United States)

    2011-01-20

    ... meeting of the Board will be held at the offices of the Farm Credit Administration in McLean, Virginia, on...Lean, Virginia 22102. SUPPLEMENTARY INFORMATION: This meeting of the Board will be open to the ] public... CORPORATION Farm Credit System Insurance Corporation Board Regular Meeting SUMMARY: Notice is hereby given of...

  18. Near-Regular Structure Discovery Using Linear Programming

    KAUST Repository

    Huang, Qixing

    2014-06-02

    Near-regular structures are common in manmade and natural objects. Algorithmic detection of such regularity greatly facilitates our understanding of shape structures, leads to compact encoding of input geometries, and enables efficient generation and manipulation of complex patterns on both acquired and synthesized objects. Such regularity manifests itself both in the repetition of certain geometric elements, as well as in the structured arrangement of the elements. We cast the regularity detection problem as an optimization and efficiently solve it using linear programming techniques. Our optimization has a discrete aspect, that is, the connectivity relationships among the elements, as well as a continuous aspect, namely the locations of the elements of interest. Both these aspects are captured by our near-regular structure extraction framework, which alternates between discrete and continuous optimizations. We demonstrate the effectiveness of our framework on a variety of problems including near-regular structure extraction, structure-preserving pattern manipulation, and markerless correspondence detection. Robustness results with respect to geometric and topological noise are presented on synthesized, real-world, and also benchmark datasets. © 2014 ACM.

  19. Sharp spatially constrained inversion

    DEFF Research Database (Denmark)

    Vignoli, Giulio G.; Fiandaca, Gianluca G.; Christiansen, Anders Vest C A.V.C.;

    2013-01-01

    We present sharp reconstruction of multi-layer models using a spatially constrained inversion with minimum gradient support regularization. In particular, its application to airborne electromagnetic data is discussed. Airborne surveys produce extremely large datasets, traditionally inverted...... by using smoothly varying 1D models. Smoothness is a result of the regularization constraints applied to address the inversion ill-posedness. The standard Occam-type regularized multi-layer inversion produces results where boundaries between layers are smeared. The sharp regularization overcomes......, the results are compatible with the data and, at the same time, favor sharp transitions. The focusing strategy can also be used to constrain the 1D solutions laterally, guaranteeing that lateral sharp transitions are retrieved without losing resolution. By means of real and synthetic datasets, sharp...

  20. Recursively-regular subdivisions and applications

    Directory of Open Access Journals (Sweden)

    Rafel Jaume

    2016-05-01

    Full Text Available We generalize regular subdivisions (polyhedral complexes resulting from the projection of the lower faces of a polyhedron introducing the class of recursively-regular subdivisions. Informally speaking, a recursively-regular subdivision is a subdivision that can be obtained by splitting some faces of a regular subdivision by other regular subdivisions (and continue recursively. We also define the finest regular coarsening and the regularity tree of a polyhedral complex. We prove that recursively-regular subdivisions are not necessarily connected by flips and that they are acyclic with respect to the in-front relation. We show that the finest regular coarsening of a subdivision can be efficiently computed, and that whether a subdivision is recursively regular can be efficiently decided. As an application, we also extend a theorem known since 1981 on illuminating space by cones and present connections of recursive regularity to tensegrity theory and graph-embedding problems.     

  1. Automatic optical inspection of regular grid patterns with an inspection camera used below the Shannon-Nyquist criterion for optical resolution

    Science.gov (United States)

    Ferreira, Flávio P.; Forte, Paulo M. F.; Felgueiras, Paulo E. R.; Bret, Boris P. J.; Belsley, Michael S.; Nunes-Pereira, Eduardo J.

    2017-02-01

    An Automatic Optical Inspection (AOI) system for optical inspection of imaging devices used in automotive industry using an inspecting optics of lower spatial resolution than the device under inspection is described. This system is robust and with no moving parts. The cycle time is small. Its main advantage is that it is capable of detecting and quantifying defects in regular patterns, working below the Shannon-Nyquist criterion for optical resolution, using a single low resolution image sensor. It is easily scalable, which is an important advantage in industrial applications, since the same inspecting sensor can be reused for increasingly higher spatial resolutions of the devices to be inspected. The optical inspection is implemented with a notch multi-band Fourier filter, making the procedure especially fitted for regular patterns, like the ones that can be produced in image displays and Head Up Displays (HUDs). The regular patterns are used in production line only, for inspection purposes. For image displays, functional defects are detected at the level of a sub-image display grid element unit. Functional defects are the ones impairing the function of the display, and are preferred in AOI to the direct geometric imaging, since those are the ones directly related with the end-user experience. The shift in emphasis from geometric imaging to functional imaging is critical, since it is this that allows quantitative inspection, below Shannon-Nyquist. For HUDs, the functional detect detection addresses defects resulting from the combined effect of the image display and the image forming optics.

  2. Bamboo-dominated forests of the southwest Amazon: detection, spatial extent, life cycle length and flowering waves.

    Directory of Open Access Journals (Sweden)

    Anelena L de Carvalho

    Full Text Available We map the extent, infer the life-cycle length and describe spatial and temporal patterns of flowering of sarmentose bamboos (Guadua spp in upland forests of the southwest Amazon. We first examine the spectra and the spectral separation of forests with different bamboo life stages. False-color composites from orbital sensors going back to 1975 are capable of distinguishing life stages. These woody bamboos flower produce massive quantities of seeds and then die. Life stage is synchronized, forming a single cohort within each population. Bamboo dominates at least 161,500 km(2 of forest, coincident with an area of recent or ongoing tectonic uplift, rapid mechanical erosion and poorly drained soils rich in exchangeable cations. Each bamboo population is confined to a single spatially continuous patch or to a core patch with small outliers. Using spatial congruence between pairs of mature-stage maps from different years, we estimate an average life cycle of 27-28 y. It is now possible to predict exactly where and approximately when new bamboo mortality events will occur. We also map 74 bamboo populations that flowered between 2001 and 2008 over the entire domain of bamboo-dominated forest. Population size averaged 330 km(2. Flowering events of these populations are temporally and/or spatially separated, restricting or preventing gene exchange. Nonetheless, adjacent populations flower closer in time than expected by chance, forming flowering waves. This may be a consequence of allochronic divergence from fewer ancestral populations and suggests a long history of widespread bamboo in the southwest Amazon.

  3. Study on detecting spatial distribution of neutrons and gamma rays using a multi-imaging plate system.

    Science.gov (United States)

    Tanaka, Kenichi; Sakurai, Yoshinori; Endo, Satoru; Takada, Jun

    2014-06-01

    In order to measure the spatial distributions of neutrons and gamma rays separately using the imaging plate, the requirement for the converter to enhance specific component was investigated with the PHITS code. Consequently, enhancing fast neutrons using recoil protons from epoxy resin was not effective due to high sensitivity of the imaging plate to gamma rays. However, the converter of epoxy resin doped with (10)B was found to have potential for thermal and epithermal neutrons, and graphite for gamma rays.

  4. Towards a Novel Spatially-Resolved Hemolysis Detection Method Using a Fluorescent Indicator and Loaded Ghost Cells: Proof-of-Principle.

    Science.gov (United States)

    Jansen, Sebastian V; Müller, Indra; Kiesendahl, Nicole; Schmitz-Rode, Thomas; Steinseifer, Ulrich

    2015-09-01

    It is of the utmost importance to reduce flow-induced hemolysis in devices such as heart-valve prostheses and blood pumps. Thus, in vitro measurements of hemolysis are performed in order to optimize their design in this regard. However, with existing measurement methods, hemolysis can only be assessed as an integrated value over the complete test-circuit. Currently, there are no spatially-resolved in vitro hemolysis measurement techniques known to the authors that would allow for a determination of the critical regions within a device. In this study, a novel spatially-resolved measurement principle is proposed. Ghost cells (i.e. erythrocytes with a lower hemoglobin concentration) were loaded with a calcium-dicitrato complex, and a fluorescent calcium indicator was suspended in the extracellular medium. Calcium and indicator are separated until the cell membrane ruptures (i.e. hemolysis occurs). In the moment of hemolysis, the two compounds bind to each other and emit a fluorescent signal that can be recorded and spatially-resolved in a setup very similar to a standard Particle Image Velocimetry measurement. A proof-of-principle experiment was performed by intentionally inducing hemolysis in a flow-model with a surfactant. The surfactant-induced hemolysis demonstrated a clear increase of the fluorescent signal compared to that of a negative reference. Furthermore, the signal was spatially restricted to the area of hemolysis. Although further challenges need to be addressed, a successful proof-of-principle for novel spatially-resolved hemolysis detection is presented. This method can contribute to better design optimization of devices with respect to flow-induced hemolysis.

  5. Detection of spatial hot spots and variation for the neon flying squid Ommastrephes bartramii resources in the northwest Pacific Ocean

    Science.gov (United States)

    Feng, Yongjiu; Chen, Xinjun; Liu, Yan

    2016-08-01

    With the increasing effects of global climate change and fishing activities, the spatial distribution of the neon flying squid (Ommastrephes bartramii) is changing in the traditional fishing ground of 150°-160°E and 38°-45°N in the northwest Pacific Ocean. This research aims to identify the spatial hot and cold spots (i.e. spatial clusters) of O. bartramii to reveal its spatial structure using commercial fishery data from 2007 to 2010 collected by Chinese mainland squid-jigging fleets. A relatively strongly-clustered distribution for O. bartramii was observed using an exploratory spatial data analysis (ESDA) method. The results show two hot spots and one cold spot in 2007 while only one hot and one cold spots were identified each year from 2008 to 2010. The hot and cold spots in 2007 occupied 8.2% and 5.6% of the study area, respectively; these percentages for hot and cold spot areas were 5.8% and 3.1% in 2008, 10.2% and 2.9% in 2009, and 16.4% and 11.9% in 2010, respectively. Nearly half (>45%) of the squid from 2007 to 2009 reported by Chinese fleets were caught in hot spot areas while this percentage reached its peak at 68.8% in 2010, indicating that the hot spot areas are central fishing grounds. A further change analysis shows the area centered at 156°E/43.5°N was persistent as a hot spot over the whole period from 2007 to 2010. Furthermore, the hot spots were mainly identified in areas with sea surface temperature (SST) in the range of 15-20°C around warm Kuroshio Currents as well as with the chlorophyll-a (chl-a) concentration above 0.3 mg/m3. The outcome of this research improves our understanding of spatiotemporal hotspots and its variation for O. bartramii and is useful for sustainable exploitation, assessment, and management of this squid.

  6. Detection of spatial hot spots and variation for the neon flying squid Ommastrephes bartramii resources in the northwest Pacific Ocean

    Science.gov (United States)

    Feng, Yongjiu; Chen, Xinjun; Liu, Yan

    2017-07-01

    With the increasing effects of global climate change and fishing activities, the spatial distribution of the neon flying squid ( Ommastrephes bartramii) is changing in the traditional fishing ground of 150°-160°E and 38°-45°N in the northwest Pacific Ocean. This research aims to identify the spatial hot and cold spots (i.e. spatial clusters) of O. bartramii to reveal its spatial structure using commercial fishery data from 2007 to 2010 collected by Chinese mainland squid-jigging fleets. A relatively strongly-clustered distribution for O. bartramii was observed using an exploratory spatial data analysis (ESDA) method. The results show two hot spots and one cold spot in 2007 while only one hot and one cold spots were identified each year from 2008 to 2010. The hot and cold spots in 2007 occupied 8.2% and 5.6% of the study area, respectively; these percentages for hot and cold spot areas were 5.8% and 3.1% in 2008, 10.2% and 2.9% in 2009, and 16.4% and 11.9% in 2010, respectively. Nearly half (>45%) of the squid from 2007 to 2009 reported by Chinese fleets were caught in hot spot areas while this percentage reached its peak at 68.8% in 2010, indicating that the hot spot areas are central fishing grounds. A further change analysis shows the area centered at 156°E/43.5°N was persistent as a hot spot over the whole period from 2007 to 2010. Furthermore, the hot spots were mainly identified in areas with sea surface temperature (SST) in the range of 15-20°C around warm Kuroshio Currents as well as with the chlorophyll- a (chl- a) concentration above 0.3 mg/m3. The outcome of this research improves our understanding of spatiotemporal hotspots and its variation for O. bartramii and is useful for sustainable exploitation, assessment, and management of this squid.

  7. Detection and Classification of Multiple Objects using an RGB-D Sensor and Linear Spatial Pyramid Matching

    DEFF Research Database (Denmark)

    Dimitriou, Michalis; Kounalakis, Tsampikos; Vidakis, Nikolaos

    2013-01-01

    This paper presents a complete system for multiple object detection and classification in a 3D scene using an RGB-D sensor such as the Microsoft Kinect sensor. Successful multiple object detection and classification are crucial features in many 3D computer vision applications. The main goal...... is making machines see and understand objects like humans do. To this goal, the new RGB-D sensors can be utilized since they provide real-time depth map which can be used along with the RGB images for our tasks. In our system we employ effective depth map processing techniques, along with edge detection...

  8. Gevrey Regularity for the Noncutoff Nonlinear Homogeneous Boltzmann Equation with Strong Singularity

    Directory of Open Access Journals (Sweden)

    Shi-you Lin

    2014-01-01

    Full Text Available The Cauchy problem of the nonlinear spatially homogeneous Boltzmann equation without angular cutoff is studied. By using analytic techniques, one proves the Gevrey regularity of the C∞ solutions in non-Maxwellian and strong singularity cases.

  9. General inverse problems for regular variation

    DEFF Research Database (Denmark)

    Damek, Ewa; Mikosch, Thomas Valentin; Rosinski, Jan

    2014-01-01

    Regular variation of distributional tails is known to be preserved by various linear transformations of some random structures. An inverse problem for regular variation aims at understanding whether the regular variation of a transformed random object is caused by regular variation of components ...

  10. Regular Motions of Resonant Asteroids

    Science.gov (United States)

    Ferraz-Mello, S.

    1990-11-01

    RESUMEN. Se revisan resultados analiticos relativos a soluciones regulares del problema asteroidal eliptico promediados en la vecindad de una resonancia con jupiten Mencionamos Ia ley de estructura para libradores de alta excentricidad, la estabilidad de los centros de liberaci6n, las perturbaciones forzadas por la excentricidad de jupiter y las 6rbitas de corotaci6n. ABSTRAC This paper reviews analytical results concerning the regular solutions of the elliptic asteroidal problem averaged in the neighbourhood of a resonance with jupiter. We mention the law of structure for high-eccentricity librators, the stability of the libration centers, the perturbations forced by the eccentricity ofjupiter and the corotation orbits. Key words: ASThROIDS

  11. Physical model of dimensional regularization

    Energy Technology Data Exchange (ETDEWEB)

    Schonfeld, Jonathan F.

    2016-12-15

    We explicitly construct fractals of dimension 4-ε on which dimensional regularization approximates scalar-field-only quantum-field theory amplitudes. The construction does not require fractals to be Lorentz-invariant in any sense, and we argue that there probably is no Lorentz-invariant fractal of dimension greater than 2. We derive dimensional regularization's power-law screening first for fractals obtained by removing voids from 3-dimensional Euclidean space. The derivation applies techniques from elementary dielectric theory. Surprisingly, fractal geometry by itself does not guarantee the appropriate power-law behavior; boundary conditions at fractal voids also play an important role. We then extend the derivation to 4-dimensional Minkowski space. We comment on generalization to non-scalar fields, and speculate about implications for quantum gravity. (orig.)

  12. Maximum mutual information regularized classification

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-09-07

    In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and the true class label. We argue that, with the learned classifier, the uncertainty of the true class label of a data sample should be reduced by knowing its classification response as much as possible. The reduced uncertainty is measured by the mutual information between the classification response and the true class label. To this end, when learning a linear classifier, we propose to maximize the mutual information between classification responses and true class labels of training samples, besides minimizing the classification error and reducing the classifier complexity. An objective function is constructed by modeling mutual information with entropy estimation, and it is optimized by a gradient descend method in an iterative algorithm. Experiments on two real world pattern classification problems show the significant improvements achieved by maximum mutual information regularization.

  13. Improved resolution and reliability in dynamic PET using Bayesian regularization of MRTM2

    DEFF Research Database (Denmark)

    Agn, Mikael; Svarer, Claus; Frokjaer, Vibe G.;

    2014-01-01

    This paper presents a mathematical model that regularizes dynamic PET data by using a Bayesian framework. We base the model on the well known two-parameter multilinear reference tissue method MRTM2 and regularize on the assumption that spatially close regions have similar parameters. The developed...

  14. Central charges in regular mechanics

    CERN Document Server

    Cabo-Montes de Oca, Alejandro; Villanueva, V M

    1997-01-01

    We consider the algebra associated to a group of transformations which are symmetries of a regular mechanical system (i.e. system free of constraints). For time dependent coordinate transformations we show that a central extension may appear at the classical level which is coordinate and momentum independent. A cochain formalism naturally arises in the argument and extends the usual configuration space cochain concepts to phase space.

  15. Fast regularized image interpolation method

    Institute of Scientific and Technical Information of China (English)

    Hongchen Liu; Yong Feng; Linjing Li

    2007-01-01

    The regularized image interpolation method is widely used based on the vector interpolation model in which down-sampling matrix has very large dimension and needs large storage consumption and higher computation complexity. In this paper, a fast algorithm for image interpolation based on the tensor product of matrices is presented, which transforms the vector interpolation model to matrix form. The proposed algorithm can extremely reduce the storage requirement and time consumption. The simulation results verify their validity.

  16. Detecting small-scale spatial heterogeneity and temporal dynamics of soil organic carbon (SOC) stocks: a comparison between automatic chamber-derived C budgets and repeated soil inventories

    Science.gov (United States)

    Hoffmann, Mathias; Jurisch, Nicole; Garcia Alba, Juana; Albiac Borraz, Elisa; Schmidt, Marten; Huth, Vytas; Rogasik, Helmut; Rieckh, Helene; Verch, Gernot; Sommer, Michael; Augustin, Jürgen

    2017-03-01

    Carbon (C) sequestration in soils plays a key role in the global C cycle. It is therefore crucial to adequately monitor dynamics in soil organic carbon (ΔSOC) stocks when aiming to reveal underlying processes and potential drivers. However, small-scale spatial (10-30 m) and temporal changes in SOC stocks, particularly pronounced in arable lands, are hard to assess. The main reasons for this are limitations of the well-established methods. On the one hand, repeated soil inventories, often used in long-term field trials, reveal spatial patterns and trends in ΔSOC but require a longer observation period and a sufficient number of repetitions. On the other hand, eddy covariance measurements of C fluxes towards a complete C budget of the soil-plant-atmosphere system may help to obtain temporal ΔSOC patterns but lack small-scale spatial resolution. To overcome these limitations, this study presents a reliable method to detect both short-term temporal dynamics as well as small-scale spatial differences of ΔSOC using measurements of the net ecosystem carbon balance (NECB) as a proxy. To estimate the NECB, a combination of automatic chamber (AC) measurements of CO2 exchange and empirically modeled aboveground biomass development (NPPshoot) were used. To verify our method, results were compared with ΔSOC observed by soil resampling. Soil resampling and AC measurements were performed from 2010 to 2014 at a colluvial depression located in the hummocky ground moraine landscape of northeastern Germany. The measurement site is characterized by a variable groundwater level (GWL) and pronounced small-scale spatial heterogeneity regarding SOC and nitrogen (Nt) stocks. Tendencies and magnitude of ΔSOC values derived by AC measurements and repeated soil inventories corresponded well. The period of maximum plant growth was identified as being most important for the development of spatial differences in annual ΔSOC. Hence, we were able to confirm that AC-based C budgets are able

  17. Detecting small-scale spatial differences and temporal dynamics of soil organic carbon (SOC) stocks: a comparison between automatic chamber-derived C budgets and repeated soil inventories

    Science.gov (United States)

    Hoffmann, Mathias; Jurisch, Nicole; Garcia Alba, Juana; Albiac Borraz, Elisa; Schmidt, Marten; Huth, Vytas; Rogasik, Helmut; Rieckh, Helene; Verch, Gernot; Sommer, Michael; Augustin, Jürgen

    2017-04-01

    Carbon (C) sequestration in soils plays a key role in the global C cycle. It is therefore crucial to adequately monitor dynamics in soil organic carbon (ΔSOC) stocks when aiming to reveal underlying processes and potential drivers. However, small-scale spatial and temporal changes in SOC stocks, particularly pronounced on arable lands, are hard to assess. The main reasons for this are limitations of the well-established methods. On the one hand, repeated soil inventories, often used in long-term field trials, reveal spatial patterns and trends in ΔSOC but require a longer observation period and a sufficient number of repetitions. On the other hand, eddy covariance measurements of C fluxes towards a complete C budget of the soil-plant-atmosphere system may help to obtain temporal ΔSOC patterns but lack small-scale spatial resolution. To overcome these limitations, this study presents a reliable method to detect both short-term temporal as well as small-scale spatial dynamics of ΔSOC. Therefore, a combination of automatic chamber (AC) measurements of CO2 exchange and empirically modeled aboveground biomass development (NPPshoot) was used. To verify our method, results were compared with ΔSOC observed by soil resampling. AC measurements were performed from 2010 to 2014 under a silage maize/winter fodder rye/sorghum-Sudan grass hybrid/alfalfa crop rotation at a colluvial depression located in the hummocky ground moraine landscape of NE Germany. Widespread in large areas of the formerly glaciated Northern Hemisphere, this depression type is characterized by a variable groundwater level (GWL) and pronounced small-scale spatial heterogeneity in soil properties, such as SOC and nitrogen (Nt). After monitoring the initial stage during 2010, soil erosion was experimentally simulated by incorporating topsoil material from an eroded midslope soil into the plough layer of the colluvial depression. SOC stocks were quantified before and after soil manipulation and at the end

  18. Information theoretic regularization in diffuse optical tomography.

    Science.gov (United States)

    Panagiotou, Christos; Somayajula, Sangeetha; Gibson, Adam P; Schweiger, Martin; Leahy, Richard M; Arridge, Simon R

    2009-05-01

    Diffuse optical tomography (DOT) retrieves the spatially distributed optical characteristics of a medium from external measurements. Recovering the parameters of interest involves solving a nonlinear and highly ill-posed inverse problem. This paper examines the possibility of regularizing DOT via the introduction of a priori information from alternative high-resolution anatomical modalities, using the information theory concepts of mutual information (MI) and joint entropy (JE). Such functionals evaluate the similarity between the reconstructed optical image and the prior image while bypassing the multimodality barrier manifested as the incommensurate relation between the gray value representations of corresponding anatomical features in the two modalities. By introducing structural information, we aim to improve the spatial resolution and quantitative accuracy of the solution. We provide a thorough explanation of the theory from an imaging perspective, accompanied by preliminary results using numerical simulations. In addition we compare the performance of MI and JE. Finally, we have adopted a method for fast marginal entropy evaluation and optimization by modifying the objective function and extending it to the JE case. We demonstrate its use on an image reconstruction framework and show significant computational savings.

  19. Efficient Hyperelastic Regularization for Registration

    DEFF Research Database (Denmark)

    Darkner, Sune; Hansen, Michael S; Larsen, Rasmus;

    2011-01-01

    For most image registration problems a smooth one-to-one mapping is desirable, a diffeomorphism. This can be obtained using priors such as volume preservation, certain kinds of elasticity or both. The key principle is to regularize the strain of the deformation which can be done through penalizat......For most image registration problems a smooth one-to-one mapping is desirable, a diffeomorphism. This can be obtained using priors such as volume preservation, certain kinds of elasticity or both. The key principle is to regularize the strain of the deformation which can be done through...... penalization of the eigen values of the stress tensor. We present a computational framework for regularization of image registration for isotropic hyper elasticity. We formulate an efficient and parallel scheme for computing the principal stain based for a given parameterization by decomposing the left Cauchy...... elastic priors such at the Saint Vernant Kirchoff model, the Ogden material model or Riemanian elasticity. We exemplify the approach through synthetic registration and special tests as well as registration of different modalities; 2D cardiac MRI and 3D surfaces of the human ear. The artificial examples...

  20. Visual signal detection in structured backgrounds. I. Effect of number of possible spatial locations and signal contrast.

    Science.gov (United States)

    Eckstein, M P; Whiting, J S

    1996-09-01

    Several studies have investigated the effect of signal location uncertainty on the detectability of simple visual signals in uncorrelated Gaussian noise with a deterministic background. For this case, human performance in locating a signal in a forced-choice experiment has been successfully predicted for 2-1800 alternative locations with the use of signal detection theory and the usual assumption that the observer's internal response is Gaussian distributed. Gaussian uncorrelated noise is far from realistic medical image noise, which includes not only fluctuations in intensity of quantum origin but also other anatomical objects lying in the x-ray path (structured backgrounds). Our goal is to determine whether signal detection theory with the Gaussian assumption is adequate for the case of structured backgrounds, or whether other more complex models need to be developed to predict human performance as a function of the number of possible signal locations in structured backgrounds. We present experimental data suggesting that an assumed Gaussian internal response accurately predicts the decrease in observer performance as the number of alternative locations is increased. The one exception is a lower-than-predicted performance for the detection of low-contrast signals for two alternative locations. Performance as measured by the index of detectability d' is also found to be linear with signal contrast. Together these findings extend the applicability of signal detection theory with Gaussian internal response functions to the case of complex structured backgrounds.

  1. Determination of Optimal Imaging Mode for Ultrasonographic Detection of Subdermal Contraceptive Rods: Comparison of Spatial Compound, Conventional, and Tissue Harmonic Imaging Methods

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sung Jin; Seo, Kyung; Song, Ho Taek; Park, Ah Young; Kim, Yaena; Yoon, Choon Sik [Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul (Korea, Republic of); Suh, Jin Suck; Kim, Ah Hyun [Dept. of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul (Korea, Republic of); Ryu, Jeong Ah [Dept. of Radiology, Guri Hospital, Hanyang University College of Medicine, Guri (Korea, Republic of); Park, Jeong Seon [Dept. of Radiology, Hanyang University Hospital, Hanyang University College of Medicine, Seoul (Korea, Republic of)

    2012-09-15

    To determine which mode of ultrasonography (US), among the conventional, spatial compound, and tissue-harmonic methods, exhibits the best performance for the detection of Implanon with respect to generation of posterior acoustic shadowing (PAS). A total of 21 patients, referred for localization of impalpable Implanon, underwent US, using the three modes with default settings (i.e., wide focal zone). Representative transverse images of the rods, according to each mode for all patients, were obtained. The resulting 63 images were reviewed by four observers. The observers provided a confidence score for the presence of PAS, using a five-point scale ranging from 1 (definitely absent) to 5 (definitely present), with scores of 4 or 5 for PAS being considered as detection. The average scores of PAS, obtained from the three different modes for each observer, were compared using one-way repeated measure ANOVA. The detection rates were compared using a weighted least square method. Statistically, the tissue harmonic mode was significantly superior to the other two modes, when comparing the average scores of PAS for all observers (p < 0.00-1). The detection rate was also highest for the tissue harmonic mode (p < 0.001). Tissue harmonic mode in US appears to be the most suitable in detecting subdermal contraceptive implant rods.

  2. From Dimensional to Cut-Off Regularization

    CERN Document Server

    Dillig, M

    2006-01-01

    We extent the standard approach of dimensional regularization of Feynman diagrams: we replace the transition to lower dimensions by a 'natural' cut-off regulator. Introducing an external regulator of mass Lambda^(2e), we regain in the limit e -> 0 and e > 0 the results of dimensional and cut-off regularization, respectively. We demonstrate the versatility and adequacy of the different regularization schemes for practical examples (such as non covariant regularization, the axial anomaly or regularization in effective field theories).

  3. Communities of arbuscular mycorrhizal fungi detected in forest soil are spatially heterogeneous but do not vary throughout the growing season.

    Directory of Open Access Journals (Sweden)

    John Davison

    Full Text Available Despite the important ecosystem role played by arbuscular mycorrhizal fungi (AMF, little is known about spatial and temporal variation in soil AMF communities. We used pyrosequencing to characterise AMF communities in soil samples (n = 44 from a natural forest ecosystem. Fungal taxa were identified by BLAST matching of reads against the MaarjAM database of AMF SSU rRNA gene diversity. Sub-sampling within our dataset and experimental shortening of a set of long reads indicated that our approaches to taxonomic identification and diversity analysis were robust to variations in pyrosequencing read length and numbers of reads per sample. Different forest plots (each 10 × 10 m and separated from one another by 30 m contained significantly different soil AMF communities, and the pairwise similarity of communities decreased with distance up to 50 m. However, there were no significant changes in community composition between different time points in the growing season (May-September. Spatial structure in soil AMF communities may be related to the heterogeneous vegetation of the natural forest study system, while the temporal stability of communities suggests that AMF in soil represent a fairly constant local species pool from which mycorrhizae form and disband during the season.

  4. Communities of arbuscular mycorrhizal fungi detected in forest soil are spatially heterogeneous but do not vary throughout the growing season.

    Science.gov (United States)

    Davison, John; Öpik, Maarja; Zobel, Martin; Vasar, Martti; Metsis, Madis; Moora, Mari

    2012-01-01

    Despite the important ecosystem role played by arbuscular mycorrhizal fungi (AMF), little is known about spatial and temporal variation in soil AMF communities. We used pyrosequencing to characterise AMF communities in soil samples (n = 44) from a natural forest ecosystem. Fungal taxa were identified by BLAST matching of reads against the MaarjAM database of AMF SSU rRNA gene diversity. Sub-sampling within our dataset and experimental shortening of a set of long reads indicated that our approaches to taxonomic identification and diversity analysis were robust to variations in pyrosequencing read length and numbers of reads per sample. Different forest plots (each 10 × 10 m and separated from one another by 30 m) contained significantly different soil AMF communities, and the pairwise similarity of communities decreased with distance up to 50 m. However, there were no significant changes in community composition between different time points in the growing season (May-September). Spatial structure in soil AMF communities may be related to the heterogeneous vegetation of the natural forest study system, while the temporal stability of communities suggests that AMF in soil represent a fairly constant local species pool from which mycorrhizae form and disband during the season.

  5. Consistent regularization and renormalization in models with inhomogeneous phases

    CERN Document Server

    Adhikari, Prabal

    2016-01-01

    In many models in condensed matter physics and high-energy physics, one finds inhomogeneous phases at high density and low temperature. These phases are characterized by a spatially dependent condensate or order parameter. A proper calculation requires that one takes the vacuum fluctuations of the model into account. These fluctuations are ultraviolet divergent and must be regularized. We discuss different consistent ways of regularizing and renormalizing quantum fluctuations, focusing on a symmetric energy cutoff scheme and dimensional regularization. We apply these techniques calculating the vacuum energy in the NJL model in 1+1 dimensions in the large-$N_c$ limit and the 3+1 dimensional quark-meson model in the mean-field approximation both for a one-dimensional chiral-density wave.

  6. Consistent regularization and renormalization in models with inhomogeneous phases

    Science.gov (United States)

    Adhikari, Prabal; Andersen, Jens O.

    2017-02-01

    In many models in condensed matter and high-energy physics, one finds inhomogeneous phases at high density and low temperature. These phases are characterized by a spatially dependent condensate or order parameter. A proper calculation requires that one takes the vacuum fluctuations of the model into account. These fluctuations are ultraviolet divergent and must be regularized. We discuss different ways of consistently regularizing and renormalizing quantum fluctuations, focusing on momentum cutoff, symmetric energy cutoff, and dimensional regularization. We apply these techniques calculating the vacuum energy in the Nambu-Jona-Lasinio model in 1 +1 dimensions in the large-Nc limit and in the 3 +1 dimensional quark-meson model in the mean-field approximation both for a one-dimensional chiral-density wave.

  7. Integrated change detection and temporal trajectory analysis of coastal wetlands using high spatial resolution Korean Multi-Purpose Satellite series imagery

    Science.gov (United States)

    Nguyen, Hoang Hai; Tran, Hien; Sunwoo, Wooyeon; Yi, Jong-hyuk; Kim, Dongkyun; Choi, Minha

    2017-04-01

    A series of multispectral high-resolution Korean Multi-Purpose Satellite (KOMPSAT) images was used to detect the geographical changes in four different tidal flats between the Yellow Sea and the west coast of South Korea. The method of unsupervised classification was used to generate a series of land use/land cover (LULC) maps from satellite images, which were then used as input for temporal trajectory analysis to detect the temporal change of coastal wetlands and its association with natural and anthropogenic activities. The accurately classified LULC maps of KOMPSAT images, with overall accuracy ranging from 83.34% to 95.43%, indicate that these multispectral high-resolution satellite data are highly applicable to the generation of high-quality thematic maps for extracting wetlands. The result of the trajectory analysis showed that, while the variation of the tidal flats in the Gyeonggi and Jeollabuk provinces was well correlated with the regular tidal regimes, the reductive trajectory of the wetland areas belonging to the Saemangeum province was caused by a high degree of human-induced activities including large reclamation and urbanization. The conservation of the Jeungdo Wetland Protected Area in the Jeollanam province revealed that effective social and environmental policies could help in protecting coastal wetlands from degradation.

  8. Temporal and spatial changes in persistent organic pollutants in Vietnamese coastal waters detected from plastic resin pellets.

    Science.gov (United States)

    Le, Dung Quang; Takada, Hideshige; Yamashita, Rei; Mizukawa, Kaoruko; Hosoda, Junki; Tuyet, Dao Anh

    2016-08-15

    Plastic resin pellets collected at Minh Chau island and Ba Lat estuary between 2007 and 2014 in Vietnam were analyzed for dichloro-diphenyl-trichloroethanes (DDTs), polychlorinated biphenyls (PCBs) and hexachlorocyclohexanes (HCHs). The study was carried out as part of the International Pellet Watch program for monitoring the global distribution of persistent organic pollutants (POPs). Higher levels of DDTs compared to PCBs indicated agricultural inputs rather than industrial discharges in the region. Most POP concentrations on both beaches decreased over the period, with the exception of HCH isomers. Though the concentration of DDTs showed a drastic decline on both beaches between 2007/2008 and 2014, DDTs accounted for 60-80% of total DDTs, suggesting that there is still a fresh input of these chemicals in the region. This study strongly recommends further investigations to track temporal and spatial patterns of POP levels in the marine environment using plastic resin pellets.

  9. Detecting the spatial and temporal variability of chlorophylla concentration and total suspended solids in Apalachicola Bay, Florida using MODIS imagery

    Science.gov (United States)

    Wang, Hongfang; Hladik, C.M.; Huang, W.; Milla, K.; Edmiston, L.; Harwell, M.A.; Schalles, J.F.

    2010-01-01

    Apalachicola Bay, Florida, accounts for 90% of Florida's and 10% of the nation's eastern oyster (Crassostrea virginica) harvesting. Chlorophyll-a concentration and total suspended solids (TSS) are two important water quality variables, among other environmental factors such as salinity, for eastern oyster production in Apalachicola Bay. In this research, we developed regression models of the relationships between the reflectance of the Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra 250 m data and the two water quality variables based on the Bay-wide field data collected during 14-17 October 2002, a relatively dry period, and 3-5 April 2006, a relatively wet period, respectively. Then we selected the best regression models (highest coefficient of determination, R2) to derive Bay-wide maps of chlorophylla concentration and TSS for the two periods. The MODIS-derived maps revealed large spatial and temporal variations in chlorophylla concentration and TSS across the entire Apalachicola Bay. ?? 2010 Taylor & Francis.

  10. Regularized degenerate multi-solitons

    CERN Document Server

    Correa, Francisco

    2016-01-01

    We report complex PT-symmetric multi-soliton solutions to the Korteweg de-Vries equation that asymptotically contain one-soliton solutions, with each of them possessing the same amount of finite real energy. We demonstrate how these solutions originate from degenerate energy solutions of the Schroedinger equation. Technically this is achieved by the application of Darboux-Crum transformations involving Jordan states with suitable regularizing shifts. Alternatively they may be constructed from a limiting process within the context Hirota's direct method or on a nonlinear superposition obtained from multiple Baecklund transformations. The proposed procedure is completely generic and also applicable to other types of nonlinear integrable systems.

  11. Academic Training Lecture - Regular Programme

    CERN Multimedia

    PH Department

    2011-01-01

    Regular Lecture Programme 9 May 2011 ACT Lectures on Detectors - Inner Tracking Detectors by Pippa Wells (CERN) 10 May 2011 ACT Lectures on Detectors - Calorimeters (2/5) by Philippe Bloch (CERN) 11 May 2011 ACT Lectures on Detectors - Muon systems (3/5) by Kerstin Hoepfner (RWTH Aachen) 12 May 2011 ACT Lectures on Detectors - Particle Identification and Forward Detectors by Peter Krizan (University of Ljubljana and J. Stefan Institute, Ljubljana, Slovenia) 13 May 2011 ACT Lectures on Detectors - Trigger and Data Acquisition (5/5) by Dr. Brian Petersen (CERN) from 11:00 to 12:00 at CERN ( Bldg. 222-R-001 - Filtration Plant )

  12. Regularization methods in Banach spaces

    CERN Document Server

    Schuster, Thomas; Hofmann, Bernd; Kazimierski, Kamil S

    2012-01-01

    Regularization methods aimed at finding stable approximate solutions are a necessary tool to tackle inverse and ill-posed problems. Usually the mathematical model of an inverse problem consists of an operator equation of the first kind and often the associated forward operator acts between Hilbert spaces. However, for numerous problems the reasons for using a Hilbert space setting seem to be based rather on conventions than on an approprimate and realistic model choice, so often a Banach space setting would be closer to reality. Furthermore, sparsity constraints using general Lp-norms or the B

  13. Determination of optimal imaging mode for ultrasonographic detection of subdermal contraceptive rods: comparison of spatial compound, conventional, and tissue harmonic imaging methods.

    Science.gov (United States)

    Kim, Sungjun; Seo, Kyung; Song, Ho-Taek; Suh, Jin-Suck; Yoon, Choon-Sik; Ryu, Jeong Ah; Park, Jeong Seon; Kim, Ah Hyun; Park, Ah Young; Kim, Yaena

    2012-01-01

    To determine which mode of ultrasonography (US), among the conventional, spatial compound, and tissue-harmonic methods, exhibits the best performance for the detection of Implanon® with respect to generation of posterior acoustic shadowing (PAS). A total of 21 patients, referred for localization of impalpable Implanon®, underwent US, using the three modes with default settings (i.e., wide focal zone). Representative transverse images of the rods, according to each mode for all patients, were obtained. The resulting 63 images were reviewed by four observers. The observers provided a confidence score for the presence of PAS, using a five-point scale ranging from 1 (definitely absent) to 5 (definitely present), with scores of 4 or 5 for PAS being considered as detection. The average scores of PAS, obtained from the three different modes for each observer, were compared using one-way repeated measure ANOVA. The detection rates were compared using a weighted least square method. Statistically, the tissue harmonic mode was significantly superior to the other two modes, when comparing the average scores of PAS for all observers (p tissue harmonic mode (p Tissue harmonic mode in uS appears to be the most suitable in detecting subdermal contraceptive implant rods.

  14. An integrated closed-tube 2-plex PCR amplification and hybridization assay with switchable lanthanide luminescence based spatial detection.

    Science.gov (United States)

    Lahdenperä, Susanne; Spangar, Anni; Lempainen, Anna-Maija; Joki, Laura; Soukka, Tero

    2015-06-21

    Switchable lanthanide luminescence is a binary probe technology that inherently enables a high signal modulation in separation-free detection of DNA targets. A luminescent lanthanide complex is formed only when the two probes hybridize adjacently to their target DNA. We have now further adapted this technology for the first time in the integration of a 2-plex polymerase chain reaction (PCR) amplification and hybridization-based solid-phase detection of the amplification products of the Staphylococcus aureus gyrB gene and an internal amplification control (IAC). The assay was performed in a sealed polypropylene PCR chip containing a flat-bottom reaction chamber with two immobilized capture probe spots. The surface of the reaction chamber was functionalized with NHS-PEG-azide and alkyne-modified capture probes for each amplicon, labeled with a light harvesting antenna ligand, and covalently attached as spots to the azide-modified reaction chamber using a copper(i)-catalyzed azide-alkyne cycloaddition. Asymmetric duplex-PCR was then performed with no template, one template or both templates present and with a europium ion carrier chelate labeled probe for each amplicon in the reaction. After amplification europium fluorescence was measured by scanning the reaction chamber as a 10 × 10 raster with 0.6 mm resolution in time-resolved mode. With this assay we were able to co-amplify and detect the amplification products of the gyrB target from 100, 1000 and 10,000 copies of isolated S. aureus DNA together with the amplification products from the initial 5000 copies of the synthetic IAC template in the same sealed reaction chamber. The addition of 10,000 copies of isolated non-target Escherichia coli DNA in the same reaction with 5000 copies of the synthetic IAC template did not interfere with the amplification or detection of the IAC. The dynamic range of the assay for the synthetic S. aureus gyrB target was three orders of magnitude and the limit of detection of 8 p

  15. Detection of Sinkhole Activity in Central Florida with High Spatial-Resolution InSAR Time Series Observations

    Science.gov (United States)

    Oliver-Cabrera, T.; Wdowinski, S.; Kruse, S.

    2016-12-01

    Central Florida's thick carbonate deposits and hydrological conditions make the area prone to sinkhole development. Sinkhole collapse is a major geologic hazard, threatening human life and causing substantial damage to property. Detecting sinkhole deformation before a collapse is a difficult task, due to small and typically unnoticeable surface changes. Most techniques used to map sinkholes, such as ground penetrating radar, require ground contact and are practical for localized (typically 2D, tens to hundreds of meters) surveys but not for broad study areas. In this study we use Persistent Scatterer (PS) time series analysis of Interferometric Synthetic Aperture Radar (InSAR), which is a very useful technique for detecting localized deformation while covering vast areas. We acquired SAR images over four locations in central Florida in order to detect possible pre-collapse or slow subsidence surface movements. The data used in this study were acquired by TerraSAR-X and COSMO-SkyMed satellites with pixel resolutions ranging between 25cm and 2m. To date, we have obtained four datasets, each of 25-30 acquisitions, covering a period of roughly one year over a total of roughly 2200 km2. We also installed two corner reflectors over a subsiding sinkhole located in an open vegetated area, to provide strong scattering and improve coherence over that particular location. We generate PS time series for each of the four datasets. Preliminary results show localized deformation at several houses and commercial buildings in several locations. Deforming areas vary in size from approximately 10mx20m of a single house to 60mx60m for a commercial building. On site ground penetrating radar surveys will be performed in these areas to verify their relationship to possible sinkhole activities. Our results also confirm that the corner reflectors improved PS detection over low coherence areas.

  16. Comparison of spatial frequency domain features for the detection of side attack explosive ballistics in synthetic aperture acoustics

    Science.gov (United States)

    Dowdy, Josh; Anderson, Derek T.; Luke, Robert H.; Ball, John E.; Keller, James M.; Havens, Timothy C.

    2016-05-01

    Explosive hazards in current and former conflict zones are a threat to both military and civilian personnel. As a result, much effort has been dedicated to identifying automated algorithms and systems to detect these threats. However, robust detection is complicated due to factors like the varied composition and anatomy of such hazards. In order to solve this challenge, a number of platforms (vehicle-based, handheld, etc.) and sensors (infrared, ground penetrating radar, acoustics, etc.) are being explored. In this article, we investigate the detection of side attack explosive ballistics via a vehicle-mounted acoustic sensor. In particular, we explore three acoustic features, one in the time domain and two on synthetic aperture acoustic (SAA) beamformed imagery. The idea is to exploit the varying acoustic frequency profile of a target due to its unique geometry and material composition with respect to different viewing angles. The first two features build their angle specific frequency information using a highly constrained subset of the signal data and the last feature builds its frequency profile using all available signal data for a given region of interest (centered on the candidate target location). Performance is assessed in the context of receiver operating characteristic (ROC) curves on cross-validation experiments for data collected at a U.S. Army test site on different days with multiple target types and clutter. Our preliminary results are encouraging and indicate that the top performing feature is the unrolled two dimensional discrete Fourier transform (DFT) of SAA beamformed imagery.

  17. A linear systems approach to the detection of both abrupt and smooth spatial variations in orientation-defined textures.

    Science.gov (United States)

    Kingdom, F A; Keeble, D R

    1996-02-01

    Two distinct paradigms have characterized most previous studies of texture perception: one has dealt with texture segregation, the other with the processing of texture gradients. Typically, studies of texture segregation have used stimuli with abrupt textural variations, whereas studies of texture gradient processing have used stimuli with smooth textural variations. In this study we have asked whether the mechanisms which process abrupt and smooth textural variations are the same, by considering whether a simple linear model can account for the detection of orientation modulation in micropattern-based textures with three types of modulation: sine-wave (SN), square-wave (SQ) and missing fundamental (MF). The MF waveform was constructed by removing the fundamental harmonic from a square-wave. We found a clear overall ordering of sensitivity: SQ > SN > MF. We found that sensitivity to the SQ and MF stimuli could be predicted very well from the SN data if one assumed that the r.m.s. output of a single linear channel underlay the detection of the orientation modulation. This suggests that the detection of both abrupt and smooth changes in orientation-defined textures is subserved by a common mechanism which mimics the operation of a single linear channel.

  18. Parallel ProXimal Algorithm for Image Restoration Using Hybrid Regularization

    CERN Document Server

    Pustelnik, Nelly; Pesquet, Jean-Christophe

    2009-01-01

    Regularization approaches have demonstrated their effectiveness for solving ill-posed problems. However, in the context of variational restoration methods, a challenging question remains, which is how to find a good regularizer. While total variation introduces staircase effects, wavelet domain regularization brings other artefacts, e.g. ringing. However, a compromise can be found by introducing a hybrid regularization including several terms non necessarily acting in the same domain (e.g. spatial and wavelet transform domains). We adopt a convex optimization framework where the criterion to be minimized is split in the sum of more than two terms. For spatial domain regularization, isotropic or anisotropic total variation definitions using various gradient filters are considered. An accelerated version of the Parallel ProXimal Algorithm is proposed to perform the minimization. Some difficulties in the computation of the proximity operators involved in this algorithm are also addressed in this paper. Numerical...

  19. Defect Localization Capabilities of a Global Detection Scheme: Spatial Pattern Recognition Using Full-field Vibration Test Data in Plates

    Science.gov (United States)

    Saleeb, A. F.; Prabhu, M.; Arnold, S. M. (Technical Monitor)

    2002-01-01

    Recently, a conceptually simple approach, based on the notion of defect energy in material space has been developed and extensively studied (from the theoretical and computational standpoints). The present study focuses on its evaluation from the viewpoint of damage localization capabilities in case of two-dimensional plates; i.e., spatial pattern recognition on surfaces. To this end, two different experimental modal test results are utilized; i.e., (1) conventional modal testing using (white noise) excitation and accelerometer-type sensors and (2) pattern recognition using Electronic speckle pattern interferometry (ESPI), a full field method capable of analyzing the mechanical vibration of complex structures. Unlike the conventional modal testing technique (using contacting accelerometers), these emerging ESPI technologies operate in a non-contacting mode, can be used even under hazardous conditions with minimal or no presence of noise and can simultaneously provide measurements for both translations and rotations. Results obtained have clearly demonstrated the robustness and versatility of the global NDE scheme developed. The vectorial character of the indices used, which enabled the extraction of distinct patterns for localizing damages proved very useful. In the context of the targeted pattern recognition paradigm, two algorithms were developed for the interrogation of test measurements; i.e., intensity contour maps for the damaged index, and the associated defect energy vector field plots.

  20. Using the ionospheric response to the solar eclipse on 20 March 2015 to detect spatial structure in the solar corona.

    Science.gov (United States)

    Scott, C J; Bradford, J; Bell, S A; Wilkinson, J; Barnard, L; Smith, D; Tudor, S

    2016-09-28

    The total solar eclipse that occurred over the Arctic region on 20 March 2015 was seen as a partial eclipse over much of Europe. Observations of this eclipse were used to investigate the high time resolution (1 min) decay and recovery of the Earth's ionospheric E-region above the ionospheric monitoring station in Chilton, UK. At the altitude of this region (100 km), the maximum phase of the eclipse was 88.88% obscuration of the photosphere occurring at 9:29:41.5 UT. In comparison, the ionospheric response revealed a maximum obscuration of 66% (leaving a fraction, Φ, of uneclipsed radiation of 34±4%) occurring at 9:29 UT. The eclipse was re-created using data from the Solar Dynamics Observatory to estimate the fraction of radiation incident on the Earth's atmosphere throughout the eclipse from nine different emission wavelengths in the extreme ultraviolet (EUV) and X-ray spectrum. These emissions, having varying spatial distributions, were each obscured differently during the eclipse. Those wavelengths associated with coronal emissions (94, 211 and 335 Å) most closely reproduced the time varying fraction of unobscured radiation observed in the ionosphere. These results could enable historic ionospheric eclipse measurements to be interpreted in terms of the distribution of EUV and X-ray emissions on the solar disc.This article is part of the themed issue 'Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse'.

  1. Detection of slow atoms confined in a Cesium vapor cell by spatially separated pump and probe laser beams

    CERN Document Server

    Todorov, Petko; Maurin, Isabelle; Saltiel, Solomon; Bloch, Daniel

    2013-01-01

    The velocity distribution of atoms in a thermal gas is usually described through a Maxwell-Boltzman distribution of energy, and assumes isotropy. As a consequence, the probability for an atom to leave the surface under an azimuth angle {\\theta} should evolve as cos {\\theta}, in spite of the fact that there is no microscopic basis to justify such a law. The contribution of atoms moving at a grazing incidence towards or from the surface, i.e. atoms with a small normal velocity, here called "slow" atoms, reveals essential in the development of spectroscopic methods probing a dilute atomic vapor in the vicinity of a surface, enabling a sub-Doppler resolution under a normal incidence irradiation. The probability for such "slow" atoms may be reduced by surface roughness and atom-surface interaction. Here, we describe a method to observe and to count these slow atoms relying on a mechanical discrimination, through spatially separated pump and probe beams. We also report on our experimental progresses toward such a g...

  2. Regularized Adaptive Notch Filters for Acoustic Howling Suppression

    DEFF Research Database (Denmark)

    Gil-Cacho, Pepe; van Waterschoot, Toon; Moonen, Marc;

    2009-01-01

    In this paper, a method for the suppression of acoustic howling is developed, based on adaptive notch filters (ANF) with regularization (RANF). The method features three RANFs working in parallel to achieve frequency tracking, howling detection and suppression. The ANF-based approach to howling...

  3. Robust integral stabilization of regular linear systems

    Institute of Scientific and Technical Information of China (English)

    XU Chengzheng; FENG Dexing

    2004-01-01

    We consider regular systems with control and observation. We prove some necessary and sufficient condition for an exponentially stable regular system to admit an integral stabilizing controller. We propose also some robust integral controllers when they exist.

  4. Generalization performance of regularized neural network models

    DEFF Research Database (Denmark)

    Larsen, Jan; Hansen, Lars Kai

    1994-01-01

    Architecture optimization is a fundamental problem of neural network modeling. The optimal architecture is defined as the one which minimizes the generalization error. This paper addresses estimation of the generalization performance of regularized, complete neural network models. Regularization...

  5. A FAST CONVERGENT METHOD OF ITERATED REGULARIZATION

    Institute of Scientific and Technical Information of China (English)

    Huang Xiaowei; Wu Chuansheng; Wu Di

    2009-01-01

    This article presents a fast convergent method of iterated regularization based on the idea of Landweber iterated regularization, and a method for a-posteriori choice by the Morozov discrepancy principle and the optimum asymptotic convergence order of the regularized solution is obtained. Numerical test shows that the method of iterated regu-larization can quicken the convergence speed and reduce the calculation burden efficiently.

  6. Weakly and Strongly Regular Near-rings

    Institute of Scientific and Technical Information of China (English)

    N.Argac; N.J.Groenewald

    2005-01-01

    In this paper, we prove some basic properties of left weakly regular near-rings.We give an affirmative answer to the question whether a left weakly regular near-ring with left unity and satisfying the IFP is also right weakly regular. In the last section, we use among others left 0-prime and left completely prime ideals to characterize strongly regular near-rings.

  7. MAXIMAL POINTS OF A REGULAR TRUTH FUNCTION

    Science.gov (United States)

    Every canonical linearly separable truth function is a regular function, but not every regular truth function is linearly separable. The most...promising method of determining which of the regular truth functions are linearly separable r quires finding their maximal and minimal points. In this...report is developed a quick, systematic method of finding the maximal points of any regular truth function in terms of its arithmetic invariants. (Author)

  8. Multiscale regularized reconstruction for enhancing microcalcification in digital breast tomosynthesis

    Science.gov (United States)

    Lu, Yao; Chan, Heang-Ping; Wei, Jun; Hadjiiski, Lubomir; Zhou, Chuan

    2012-03-01

    Digital breast tomosynthesis (DBT) holds strong promise for improving the sensitivity of detecting subtle mass lesions. Detection of microcalcifications is more difficult because of high noise and subtle signals in the large DBT volume. It is important to enhance the contrast-to-noise ratio (CNR) of microcalcifications in DBT reconstruction. A major challenge of implementing microcalcification enhancement or noise regularization in DBT reconstruction is to preserve the image quality of masses, especially those with ill-defined margins and subtle spiculations. We are developing a new multiscale regularization (MSR) method for the simultaneous algebraic reconstruction technique (SART) to improve the CNR of microcalcifications without compromising the quality of masses. Each DBT slice is stratified into different frequency bands via wavelet decomposition and the regularization method applies different degrees of regularization to different frequency bands to preserve features of interest and suppress noise. Regularization is constrained by a characteristic map to avoid smoothing subtle microcalcifications. The characteristic map is generated via image feature analysis to identify potential microcalcification locations in the DBT volume. The MSR method was compared to the non-convex total pvariation (TpV) method and SART with no regularization (NR) in terms of the CNR and the full width at half maximum of the line profiles intersecting calcifications and mass spiculations in DBT of human subjects. The results demonstrated that SART regularized by the MSR method was superior to the TpV method for subtle microcalcifications in terms of CNR enhancement. The MSR method preserved the quality of subtle spiculations better than the TpV method in comparison to NR.

  9. Natural frequency of regular basins

    Science.gov (United States)

    Tjandra, Sugih S.; Pudjaprasetya, S. R.

    2014-03-01

    Similar to the vibration of a guitar string or an elastic membrane, water waves in an enclosed basin undergo standing oscillatory waves, also known as seiches. The resonant (eigen) periods of seiches are determined by water depth and geometry of the basin. For regular basins, explicit formulas are available. Resonance occurs when the dominant frequency of external force matches the eigen frequency of the basin. In this paper, we implement the conservative finite volume scheme to 2D shallow water equation to simulate resonance in closed basins. Further, we would like to use this scheme and utilizing energy spectra of the recorded signal to extract resonant periods of arbitrary basins. But here we first test the procedure for getting resonant periods of a square closed basin. The numerical resonant periods that we obtain are comparable with those from analytical formulas.

  10. Regularized degenerate multi-solitons

    Science.gov (United States)

    Correa, Francisco; Fring, Andreas

    2016-09-01

    We report complex {P}{T} -symmetric multi-soliton solutions to the Korteweg de-Vries equation that asymptotically contain one-soliton solutions, with each of them possessing the same amount of finite real energy. We demonstrate how these solutions originate from degenerate energy solutions of the Schrödinger equation. Technically this is achieved by the application of Darboux-Crum transformations involving Jordan states with suitable regularizing shifts. Alternatively they may be constructed from a limiting process within the context Hirota's direct method or on a nonlinear superposition obtained from multiple Bäcklund transformations. The proposed procedure is completely generic and also applicable to other types of nonlinear integrable systems.

  11. Modeling polycrystals with regular polyhedra

    Directory of Open Access Journals (Sweden)

    Paulo Rangel Rios

    2006-06-01

    Full Text Available Polycrystalline structure is of paramount importance to materials science and engineering. It provides an important example of a space-filling irregular network structure that also occurs in foams as well as in certain biological tissues. Therefore, seeking an accurate description of the characteristics of polycrystals is of fundamental importance. Recently, one of the authors (MEG published a paper in which a method was devised of representation of irregular networks by regular polyhedra with curved faces. In Glicksman's method a whole class of irregular polyhedra with a given number of faces, N, is represented by a single symmetrical polyhedron with N curved faces. This paper briefly describes the topological and metric properties of these special polyhedra. They are then applied to two important problems of irregular networks: the dimensionless energy 'cost' of irregular networks, and the derivation of a 3D analogue of the von Neumann-Mullins equation for the growth rate of grains in a polycrystal.

  12. Detecting Selection on Temporal and Spatial Scales: A Genomic Time-Series Assessment of Selective Responses to Devil Facial Tumor Disease.

    Directory of Open Access Journals (Sweden)

    Anna Brüniche-Olsen

    Full Text Available Detecting loci under selection is an important task in evolutionary biology. In conservation genetics detecting selection is key to investigating adaptation to the spread of infectious disease. Loci under selection can be detected on a spatial scale, accounting for differences in demographic history among populations, or on a temporal scale, tracing changes in allele frequencies over time. Here we use these two approaches to investigate selective responses to the spread of an infectious cancer--devil facial tumor disease (DFTD--that since 1996 has ravaged the Tasmanian devil (Sarcophilus harrisii. Using time-series 'restriction site associated DNA' (RAD markers from populations pre- and post DFTD arrival, and DFTD free populations, we infer loci under selection due to DFTD and investigate signatures of selection that are incongruent among methods, populations, and times. The lack of congruence among populations influenced by DFTD with respect to inferred loci under selection, and the direction of that selection, fail to implicate a consistent selective role for DFTD. Instead genetic drift is more likely driving the observed allele frequency changes over time. Our study illustrates the importance of applying methods with different performance optima e.g. accounting for population structure and background selection, and assessing congruence of the results.

  13. REGULARITY FOR CERTAIN QUASILINEARELLIPTIC SYSTEMS OF DIVERGENCESTRUCTURE

    Institute of Scientific and Technical Information of China (English)

    周树清; 冉启康

    2001-01-01

    The regularity of the gradient of H lder continuous solutions of quasi-linear elliptic systems of the form -Dj(aij(x, u, Du)Diuk) = -Difik + gkis investigated. Partial regularity and ε-regularity are shown to hold under the structural assumption-Dj(aij(x,u, Du)) = hi ∈ L∞.

  14. Technology Corner: A Regular Expression Training App

    Directory of Open Access Journals (Sweden)

    Nick Flor

    2012-12-01

    Full Text Available Regular expressions enable digital forensic analysts to find information in files. The best way for an analyst to become proficient in writing regular expressions is to practice. This paper presents the code for an app that allows an analyst to practice writing regular expressions.

  15. Counting Rooted Nearly 2-regular Planar Maps

    Institute of Scientific and Technical Information of China (English)

    郝荣霞; 蔡俊亮

    2004-01-01

    The number of rooted nearly 2-regular maps with the valency of rootvertex, the number of non-rooted vertices and the valency of root-face as three parameters is obtained. Furthermore, the explicit expressions of the special cases including loopless nearly 2-regular maps and simple nearly 2-regular maps in terms of the above three parameters are derived.

  16. On the Construction of Regular Orthocryptogroups

    Institute of Scientific and Technical Information of China (English)

    Xiang Zhi KONG

    2002-01-01

    The aim of this paper is to study regular orthocryptogroups. After obtaining some charac-terizations of such semigroups, we establish the construction theorem of regular orthocryptogroups. Asan application, we give the construction theorem of right quasi-normal orthocryptogroups and studyhomomorphisms between two regular orthocryptogroups.

  17. REGULAR RELATIONS AND MONOTONE NORMAL ORDERED SPACES

    Institute of Scientific and Technical Information of China (English)

    XU XIAOQUAN; LIU YINGMING

    2004-01-01

    In this paper the classical theorem of Zareckii about regular relations is generalized and an intrinsic characterization of regularity is obtained. Based on the generalized Zareckii theorem and the intrinsic characterization of regularity, the authors give a characterization of monotone normality of ordered spaces. A new proof of the UrysohnNachbin lemma is presented which is quite different from the classical one.

  18. Regular Pentagons and the Fibonacci Sequence.

    Science.gov (United States)

    French, Doug

    1989-01-01

    Illustrates how to draw a regular pentagon. Shows the sequence of a succession of regular pentagons formed by extending the sides. Calculates the general formula of the Lucas and Fibonacci sequences. Presents a regular icosahedron as an example of the golden ratio. (YP)

  19. QRS classification and spatial combination for robust heart rate detection in low-quality fetal ECG recordings.

    Science.gov (United States)

    Warmerdam, G; Vullings, R; Van Pul, C; Andriessen, P; Oei, S G; Wijn, P

    2013-01-01

    Non-invasive fetal electrocardiography (ECG) can be used for prolonged monitoring of the fetal heart rate (FHR). However, the signal-to-noise-ratio (SNR) of non-invasive ECG recordings is often insufficient for reliable detection of the FHR. To overcome this problem, source separation techniques can be used to enhance the fetal ECG. This study uses a physiology-based source separation (PBSS) technique that has already been demonstrated to outperform widely used blind source separation techniques. Despite the relatively good performance of PBSS in enhancing the fetal ECG, PBSS is still susceptible to artifacts. In this study an augmented PBSS technique is developed to reduce the influence of artifacts. The performance of the developed method is compared to PBSS on multi-channel non-invasive fetal ECG recordings. Based on this comparison, the developed method is shown to outperform PBSS for the enhancement of the fetal ECG.

  20. Detecting Spatial Chromatin Organization by Chromosome Conformation Capture II: Genome-Wide Profiling by Hi-C.

    Science.gov (United States)

    Vietri Rudan, Matteo; Hadjur, Suzana; Sexton, Tom

    2017-01-01

    The chromosome conformation capture (3C) method has been invaluable in studying chromatin interactions in a population of cells at a resolution surpassing that of light microscopy, for example in the detection of functional contacts between enhancers and promoters. Recent developments in sequencing-based chromosomal contact mapping (Hi-C, 5C and 4C-Seq) have allowed researchers to interrogate pairwise chromatin interactions on a wider scale, shedding light on the three-dimensional organization of chromosomes. These methods present significant technical and bioinformatic challenges to consider at the start of the project. Here, we describe two alternative methods for Hi-C, depending on the size of the genome, and discuss the major computational approaches to convert the raw sequencing data into meaningful models of how genomes are organized.

  1. Automated Detection of Cloud and Cloud Shadow in Single-Date Landsat Imagery Using Neural Networks and Spatial Post-Processing

    Directory of Open Access Journals (Sweden)

    M. Joseph Hughes

    2014-05-01

    Full Text Available The use of Landsat data to answer ecological questions is greatly increased by the effective removal of cloud and cloud shadow from satellite images. We develop a novel algorithm to identify and classify clouds and cloud shadow, SPARCS: Spatial Procedures for Automated Removal of Cloud and Shadow. The method uses a neural network approach to determine cloud, cloud shadow, water, snow/ice and clear sky classification memberships of each pixel in a Landsat scene. It then applies a series of spatial procedures to resolve pixels with ambiguous membership by using information, such as the membership values of neighboring pixels and an estimate of cloud shadow locations from cloud and solar geometry. In a comparison with FMask, a high-quality cloud and cloud shadow classification algorithm currently available, SPARCS performs favorably, with substantially lower omission errors for cloud shadow (8.0% and 3.2%, only slightly higher omission errors for clouds (0.9% and 1.3%, respectively and fewer errors of commission (2.6% and 0.3%. Additionally, SPARCS provides a measure of uncertainty in its classification that can be exploited by other algorithms that require clear sky pixels. To illustrate this, we present an application that constructs obstruction-free composites of images acquired on different dates in support of a method for vegetation change detection.

  2. Geo-spatial distribution of serologically detected bovine Foot and Mouth Disease (FMD serotype outbreaks in Ilesha Baruba, Kwara State-Nigeria

    Directory of Open Access Journals (Sweden)

    Hamza Olatunde Olabode

    2014-09-01

    Full Text Available The study was aimed at assessing the prevalence and distribution of bovine Foot and Mouth Disease (FMD serotypes in Ilesha Baruba, Kwara state-Nigeria. To identify the source of epidemics, geo-spatial analysis was done on the FMD outbreak locations (n=15 using Global Positioning Service (GPS device (EtrexR. Randomly sampled bovine sera (n=64 from herd representatives were subjected to FMD 3ABC enzyme-linked immunosorbent assay (FMD 3ABC ELISA and solid-phase competitive ELISA (SP-cELISA, for the screening and serotyping of FMD virus, respectively. Through ELISA, the FMD serotypes detected in this study were- serotype O (83%; n=53/64, serotype A (7.8%; n=5/64, serotype vaccine O (1.6%; n=1/64, and serotype vaccine SAT2 (1.6%; n=1/64. Multiple serotypes were observed in two different combinations; these were O and A (4.7%; n=3/64, and O and SAT2 (1.6%; n=1/64. FMD multiple serotype infections were associated with absence of cross-immunity between serotypes and cross reactivity enhanced by clustered herds, highland study area topography, road and river interconnectivity, possible human settlements, activities and traffic. This study provides baseline information on geo-spatial distribution, and identification of prevalent FMD serotypes in Ilesha Baruba, Kwara state-Nigeria.

  3. Detecting spatial structures in throughfall data: The effect of extent, sample size, sampling design, and variogram estimation method

    Science.gov (United States)

    Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander

    2016-09-01

    In the last decades, an increasing number of studies analyzed spatial patterns in throughfall by means of variograms. The estimation of the variogram from sample data requires an appropriate sampling scheme: most importantly, a large sample and a layout of sampling locations that often has to serve both variogram estimation and geostatistical prediction. While some recommendations on these aspects exist, they focus on Gaussian data and high ratios of the variogram range to the extent of the study area. However, many hydrological data, and throughfall data in particular, do not follow a Gaussian distribution. In this study, we examined the effect of extent, sample size, sampling design, and calculation method on variogram estimation of throughfall data. For our investigation, we first generated non-Gaussian random fields based on throughfall data with large outliers. Subsequently, we sampled the fields with three extents (plots with edge lengths of 25 m, 50 m, and 100 m), four common sampling designs (two grid-based layouts, transect and random sampling) and five sample sizes (50, 100, 150, 200, 400). We then estimated the variogram parameters by method-of-moments (non-robust and robust estimators) and residual maximum likelihood. Our key findings are threefold. First, the choice of the extent has a substantial influence on the estimation of the variogram. A comparatively small ratio of the extent to the correlation length is beneficial for variogram estimation. Second, a combination of a minimum sample size of 150, a design that ensures the sampling of small distances and variogram estimation by residual maximum likelihood offers a good compromise between accuracy and efficiency. Third, studies relying on method-of-moments based variogram estimation may have to employ at least 200 sampling points for reliable variogram estimates. These suggested sample sizes exceed the number recommended by studies dealing with Gaussian data by up to 100 %. Given that most previous

  4. Wave dynamics of regular and chaotic rays

    Energy Technology Data Exchange (ETDEWEB)

    McDonald, S.W.

    1983-09-01

    In order to investigate general relationships between waves and rays in chaotic systems, I study the eigenfunctions and spectrum of a simple model, the two-dimensional Helmholtz equation in a stadium boundary, for which the rays are ergodic. Statistical measurements are performed so that the apparent randomness of the stadium modes can be quantitatively contrasted with the familiar regularities observed for the modes in a circular boundary (with integrable rays). The local spatial autocorrelation of the eigenfunctions is constructed in order to indirectly test theoretical predictions for the nature of the Wigner distribution corresponding to chaotic waves. A portion of the large-eigenvalue spectrum is computed and reported in an appendix; the probability distribution of successive level spacings is analyzed and compared with theoretical predictions. The two principal conclusions are: 1) waves associated with chaotic rays may exhibit randomly situated localized regions of high intensity; 2) the Wigner function for these waves may depart significantly from being uniformly distributed over the surface of constant frequency in the ray phase space.

  5. Effect of regularization parameters on geophysical reconstruction

    Institute of Scientific and Technical Information of China (English)

    Zhou Hui; Wang Zhaolei; Qiu Dongling; Li Guofa; Shen Jinsong

    2009-01-01

    In this paper we discuss the edge-preserving regularization method in the reconstruction of physical parameters from geophysical data such as seismic and ground-penetrating radar data.In the regularization method a potential function of model parameters and its corresponding functions are introduced.This method is stable and able to preserve boundaries, and protect resolution.The effect of regularization depends to a great extent on the suitable choice of regularization parameters.The influence of the edge-preserving parameters on the reconstruction results is investigated and the relationship between the regularization parameters and the error of data is described.

  6. A convex formulation for hyperspectral image superresolution via subspace-based regularization

    CERN Document Server

    Simões, Miguel; Almeida, Luis B; Chanussot, Jocelyn

    2014-01-01

    Hyperspectral remote sensing images (HSIs) usually have high spectral resolution and low spatial resolution. Conversely, multispectral images (MSIs) usually have low spectral and high spatial resolutions. The problem of inferring images which combine the high spectral and high spatial resolutions of HSIs and MSIs, respectively, is a data fusion problem that has been the focus of recent active research due to the increasing availability of HSIs and MSIs retrieved from the same geographical area. We formulate this problem as the minimization of a convex objective function containing two quadratic data-fitting terms and an edge-preserving regularizer. The data-fitting terms account for blur, different resolutions, and additive noise. The regularizer, a form of vector Total Variation, promotes piecewise-smooth solutions with discontinuities aligned across the hyperspectral bands. The downsampling operator accounting for the different spatial resolutions, the non-quadratic and non-smooth nature of the regularizer,...

  7. Spatial planning

    OpenAIRE

    Dimitrov, Nikola; Koteski, Cane

    2016-01-01

    The professional book ,, Space planning "processed chapters on: space, concept and definition of space, space as a system, spatial economics, economic essence of space, space planning, social determinants of spatial planning, spatial planning as a process, factors development and elements in spatial planning, methodology, components and content of spatial planning stages and types of preparation of spatial planning, spatial planning and industrialization, industrialization, urbanization and s...

  8. Spatial planning

    OpenAIRE

    Dimitrov, Nikola; Koteski, Cane

    2016-01-01

    The professional book ,, Space planning "processed chapters on: space, concept and definition of space, space as a system, spatial economics, economic essence of space, space planning, social determinants of spatial planning, spatial planning as a process, factors development and elements in spatial planning, methodology, components and content of spatial planning stages and types of preparation of spatial planning, spatial planning and industrialization, industrialization, urbanization and s...

  9. Regular Black Holes with Cosmological Constant

    Institute of Scientific and Technical Information of China (English)

    MO Wen-Juan; CAI Rong-Gen; SU Ru-Keng

    2006-01-01

    We present a class of regular black holes with cosmological constant Λ in nonlinear electrodynamics. Instead of usual singularity behind black hole horizon, all fields and curvature invariants are regular everywhere for the regular black holes. Through gauge invariant approach, the linearly dynamical stability of the regular black hole is studied. In odd-parity sector, we find that the Λ term does not appear in the master equations of perturbations, which shows that the regular black hole is stable under odd-parity perturbations. On the other hand, for the even-parity sector, the master equations are more complicated than the case without the cosmological constant. We obtain the sufficient conditions for stability of the regular black hole. We also investigate the thermodynamic properties of the regular black hole, and find that those thermodynamic quantities do not satisfy the differential form of first law of black hole thermodynamics. The reason for violating the first law is revealed.

  10. Optimal Population-Level Infection Detection Strategies for Malaria Control and Elimination in a Spatial Model of Malaria Transmission.

    Directory of Open Access Journals (Sweden)

    Jaline Gerardin

    2016-01-01

    Full Text Available Mass campaigns with antimalarial drugs are potentially a powerful tool for local elimination of malaria, yet current diagnostic technologies are insufficiently sensitive to identify all individuals who harbor infections. At the same time, overtreatment of uninfected individuals increases the risk of accelerating emergence of drug resistance and losing community acceptance. Local heterogeneity in transmission intensity may allow campaign strategies that respond to index cases to successfully target subpatent infections while simultaneously limiting overtreatment. While selective targeting of hotspots of transmission has been proposed as a strategy for malaria control, such targeting has not been tested in the context of malaria elimination. Using household locations, demographics, and prevalence data from a survey of four health facility catchment areas in southern Zambia and an agent-based model of malaria transmission and immunity acquisition, a transmission intensity was fit to each household based on neighborhood age-dependent malaria prevalence. A set of individual infection trajectories was constructed for every household in each catchment area, accounting for heterogeneous exposure and immunity. Various campaign strategies-mass drug administration, mass screen and treat, focal mass drug administration, snowball reactive case detection, pooled sampling, and a hypothetical serological diagnostic-were simulated and evaluated for performance at finding infections, minimizing overtreatment, reducing clinical case counts, and interrupting transmission. For malaria control, presumptive treatment leads to substantial overtreatment without additional morbidity reduction under all but the highest transmission conditions. Compared with untargeted approaches, selective targeting of hotspots with drug campaigns is an ineffective tool for elimination due to limited sensitivity of available field diagnostics. Serological diagnosis is potentially an

  11. Learning regularized LDA by clustering.

    Science.gov (United States)

    Pang, Yanwei; Wang, Shuang; Yuan, Yuan

    2014-12-01

    As a supervised dimensionality reduction technique, linear discriminant analysis has a serious overfitting problem when the number of training samples per class is small. The main reason is that the between- and within-class scatter matrices computed from the limited number of training samples deviate greatly from the underlying ones. To overcome the problem without increasing the number of training samples, we propose making use of the structure of the given training data to regularize the between- and within-class scatter matrices by between- and within-cluster scatter matrices, respectively, and simultaneously. The within- and between-cluster matrices are computed from unsupervised clustered data. The within-cluster scatter matrix contributes to encoding the possible variations in intraclasses and the between-cluster scatter matrix is useful for separating extra classes. The contributions are inversely proportional to the number of training samples per class. The advantages of the proposed method become more remarkable as the number of training samples per class decreases. Experimental results on the AR and Feret face databases demonstrate the effectiveness of the proposed method.

  12. Comparison of no-prior and soft-prior regularization in biomedical microwave imaging

    Directory of Open Access Journals (Sweden)

    Amir H Golnabi

    2011-01-01

    Full Text Available Microwave imaging for medical applications is attractive because the range of dielectric properties of different soft tissues can be substantial. Breast cancer detection and monitoring of treatment response are areas where this technology could be important because of the contrast between normal and malignant tissue. Unfortunately, the technique is unable to achieve the high spatial resolution at depth in tissue which is available from other conventional modalities such as x-ray computed tomography (CT or magnetic resonance imaging (MRI. We have incorporated a soft-prior regularization strategy within our microwave reconstruction algorithm and compared it with the images obtained with traditional no-prior (Levenberg-Marquardt regularization. Initial simulation and phantom results show a significant improvement of the recovered electrical properties. Specifically, errors in the microwave property estimates were improved by as much as 95%. The effects of a false-inclusion region were also evaluated and the results show that a small residual property bias of 6% in permittivity and 15% in conductivity can occur that does not otherwise degrade the property recovery accuracy of inclusions that actually exist. The work sets the stage for integrating microwave imaging with MR for improved resolution and functional imaging of the breast in the future.

  13. Detection of novelty, but not memory of spatial habituation, is associated with an increase in phosphorylated cAMP response element-binding protein levels in the hippocampus.

    Science.gov (United States)

    Winograd, Milena; Viola, Haydée

    2004-01-01

    There is a growing body of evidence showing that the formation of associative memories is associated with an increase in phosphorylated cAMP response element-binding protein (pCREB) levels. We recently reported increased pCREB levels in the rat hippocampus after an exploration to a novel environment. In the present work, we studied whether this increment in CREB activation is associated with the formation of memory of habituation to a novel environment or with the detection of novelty. Rats were submitted to consecutive open field sessions at 3-h intervals. Measurement of the hippocampal pCREB level, carried out 1 h after each training session, showed that (1) it did not increase when rats explored a familiar environment; (2) it did not increase after a reexposure that improves the memory of habituation; (3) it increased after a brief novel exploration unable to form memory of habituation; and (4) it increased in amnesic rats for spatial habituation. Taken as a whole, our results suggest that the elevated pCREB level after a single open field exploration is not associated with the memory formation of habituation. It is indeed associated with the detection of a novel environment.

  14. Automated detection of cloud and cloud-shadow in single-date Landsat imagery using neural networks and spatial post-processing

    Energy Technology Data Exchange (ETDEWEB)

    Hughes, Michael J. [University of Tennessee, Knoxville (UTK); Hayes, Daniel J [ORNL

    2014-01-01

    Use of Landsat data to answer ecological questions is contingent on the effective removal of cloud and cloud shadow from satellite images. We develop a novel algorithm to identify and classify clouds and cloud shadow, \\textsc{sparcs}: Spacial Procedures for Automated Removal of Cloud and Shadow. The method uses neural networks to determine cloud, cloud-shadow, water, snow/ice, and clear-sky membership of each pixel in a Landsat scene, and then applies a set of procedures to enforce spatial rules. In a comparison to FMask, a high-quality cloud and cloud-shadow classification algorithm currently available, \\textsc{sparcs} performs favorably, with similar omission errors for clouds (0.8% and 0.9%, respectively), substantially lower omission error for cloud-shadow (8.3% and 1.1%), and fewer errors of commission (7.8% and 5.0%). Additionally, textsc{sparcs} provides a measure of uncertainty in its classification that can be exploited by other processes that use the cloud and cloud-shadow detection. To illustrate this, we present an application that constructs obstruction-free composites of images acquired on different dates in support of algorithms detecting vegetation change.

  15. An experimental method for the determination of spatial-frequency-dependent detective quantum efficiency (DQE) of scintillators used in X-ray imaging detectors

    Energy Technology Data Exchange (ETDEWEB)

    Kandarakis, I.; Cavouras, D. [Technol. Educ. Inst. of Athens (Greece). Dept. of Medical Instrum. Technol.; Panayiotakis, G.S. [Department of Medical Physics, Medical School, University of Patras, 265 00 Patras (Greece); Triantis, D.; Nomicos, C.D. [Department of Electronics, Technological Educational Institution of Athens, Ag. Spyridonos Street, Aigaleo, Athens (Greece)

    1997-11-11

    The spatial-frequency-dependent detective quantum efficiency (DQE) of imaging scintillators was studied independently of the optical detector (film, photocathode, or photodiode) employed in medical imaging devices. A method was developed to experimentally determine the scintillator DQE in terms of its luminescence efficiency (LE), quantum detection efficiency, modulation transfer function, and light emission spectrum. Gd{sub 2}O{sub 2}S:Tb, La{sub 2}O{sub 2}S:Tb, Y{sub 2}O{sub 2}S:Tb and ZnSCdS:Ag scintillating screens were prepared in laboratory and were excited to luminescence by a medical X-ray tube. Maximum DQE values varied between 0.13 and 0.33 depending on the scintillator material, the screen coating weight, and the tube voltage; Gd{sub 2}O{sub 2}S:Tb was superior to La{sub 2}O{sub 2}S:Tb followed by ZnSCdS:Ag and Y{sub 2}O{sub 2}S:Tb. This ranking was maintained at frequencies up to 100 cycles/cm. Considering the same material, DQE of thin screens was found superior to DQE of thicker screens at medium-to-high frequencies. The proposed method allows for the comparison of imaging characteristics of scintillating materials without the inclusion of optical detector imaging properties. (orig.). 20 refs.

  16. Detecting short spatial scale local adaptation and epistatic selection in climate-related candidate genes in European beech (Fagus sylvatica) populations.

    Science.gov (United States)

    Csilléry, Katalin; Lalagüe, Hadrien; Vendramin, Giovanni G; González-Martínez, Santiago C; Fady, Bruno; Oddou-Muratorio, Sylvie

    2014-10-01

    Detecting signatures of selection in tree populations threatened by climate change is currently a major research priority. Here, we investigated the signature of local adaptation over a short spatial scale using 96 European beech (Fagus sylvatica L.) individuals originating from two pairs of populations on the northern and southern slopes of Mont Ventoux (south-eastern France). We performed both single and multilocus analysis of selection based on 53 climate-related candidate genes containing 546 SNPs. FST outlier methods at the SNP level revealed a weak signal of selection, with three marginally significant outliers in the northern populations. At the gene level, considering haplotypes as alleles, two additional marginally significant outliers were detected, one on each slope. To account for the uncertainty of haplotype inference, we averaged the Bayes factors over many possible phase reconstructions. Epistatic selection offers a realistic multilocus model of selection in natural populations. Here, we used a test suggested by Ohta based on the decomposition of the variance of linkage disequilibrium. Overall populations, 0.23% of the SNP pairs (haplotypes) showed evidence of epistatic selection, with nearly 80% of them being within genes. One of the between gene epistatic selection signals arose between an FST outlier and a nonsynonymous mutation in a drought response gene. Additionally, we identified haplotypes containing selectively advantageous allele combinations which were unique to high or low elevations and northern or southern populations. Several haplotypes contained nonsynonymous mutations situated in genes with known functional importance for adaptation to climatic factors.

  17. Detection and Segmentation of Vine Canopy in Ultra-High Spatial Resolution RGB Imagery Obtained from Unmanned Aerial Vehicle (UAV: A Case Study in a Commercial Vineyard

    Directory of Open Access Journals (Sweden)

    Carlos Poblete-Echeverría

    2017-03-01

    Full Text Available The use of Unmanned Aerial Vehicles (UAVs in viticulture permits the capture of aerial Red-Green-Blue (RGB images with an ultra-high spatial resolution. Recent studies have demonstrated that RGB images can be used to monitor spatial variability of vine biophysical parameters. However, for estimating these parameters, accurate and automated segmentation methods are required to extract relevant information from RGB images. Manual segmentation of aerial images is a laborious and time-consuming process. Traditional classification methods have shown satisfactory results in the segmentation of RGB images for diverse applications and surfaces, however, in the case of commercial vineyards, it is necessary to consider some particularities inherent to canopy size in the vertical trellis systems (VSP such as shadow effect and different soil conditions in inter-rows (mixed information of soil and weeds. Therefore, the objective of this study was to compare the performance of four classification methods (K-means, Artificial Neural Networks (ANN, Random Forest (RForest and Spectral Indices (SI to detect canopy in a vineyard trained on VSP. Six flights were carried out from post-flowering to harvest in a commercial vineyard cv. Carménère using a low-cost UAV equipped with a conventional RGB camera. The results show that the ANN and the simple SI method complemented with the Otsu method for thresholding presented the best performance for the detection of the vine canopy with high overall accuracy values for all study days. Spectral indices presented the best performance in the detection of Plant class (Vine canopy with an overall accuracy of around 0.99. However, considering the performance pixel by pixel, the Spectral indices are not able to discriminate between Soil and Shadow class. The best performance in the classification of three classes (Plant, Soil, and Shadow of vineyard RGB images, was obtained when the SI values were used as input data in trained

  18. Analysis of Spatial and Temporal Coverage of Multi-Instrument Optical Images for Change Detection Research on the Mars South Polar Residual Cap

    Science.gov (United States)

    Putri, Alfiah Rizky Diana; Sidiropoulos, Panagiotis; Muller, Jan-Peter; iMars Team

    2016-10-01

    Interest in Mars' surface started in 1965 with Mariner 4. Since then cameras on other fly-by satellites, such as the NASA Mariner 6 (1965), Mariner 7(1971), Mariner 9 (1972) and then orbiting satellites from Viking 1 and 2 (1975-1980), MGS MOC-NA and MOC-WA (1997-2006), Mars Odyssey THEMIS-VIS (2001-present), ESA Mars Express HRSC and SRC (2003-present), NASA MRO HiRISE and CTX (2006-present) and the latest ExoMars TGO CaSSIS launched in March 2016. Both poles of Mars are very fascinating because of their seasonal changes, such as Carbon Dioxide ice layers staying even in summer on South Polar Residual Cap (SPRC). On which features like so-called Swiss Cheese Terrain, spiders, polar dune flow and dust deposition under layers of ice have been identified. To detect changes between images, we need two or more co-registered images of the same area, and from different time periods, for seasonal features. We have studied the spatial and temporal coverage of images over SPRC. Using a single instrument, full SPRC spatial coverage is available for Viking, HRSC, and CTX images. Images from 25cm HiRISE and ≤10m MOC-NA however, are necessary to detect changes at sufficiently high resolution. The longest period for images from one instrument is 5 MY (for CTX and HiRISE, from MY 28-32). Combining multi-instrument images, we can lengthen the period to 10 MY (from MY 23-32, N.B. we are in MY 33 as present). We can compare the surface images over the 10 MY with the surface from MY 12 from Viking Orbiters. Using multi-instrument images we can increase the number of overlapping images over an area. Overlap information for a single instrument is important to obtain stereo-pairs to be used in DTM production. Overlap information from HRSC images and its DTMs can be used to map changes not only horizontally, but also vertically. We will demonstrate in this study the areas which can be most fruitfully employed for change detection research. The research leading to these results has

  19. An adaptive support driven reweighted L1-regularization algorithm for fluorescence molecular tomography.

    Science.gov (United States)

    Shi, Junwei; Liu, Fei; Pu, Huangsheng; Zuo, Simin; Luo, Jianwen; Bai, Jing

    2014-11-01

    Fluorescence molecular tomography (FMT) is a promising in vivo functional imaging modality in preclinical study. When solving the ill-posed FMT inverse problem, L1 regularization can preserve the details and reduce the noise in the reconstruction results effectively. Moreover, compared with the regular L1 regularization, reweighted L1 regularization is recently reported to improve the performance. In order to realize the reweighted L1 regularization for FMT, an adaptive support driven reweighted L1-regularization (ASDR-L1) algorithm is proposed in this work. This algorithm has two integral parts: an adaptive support estimate and the iteratively updated weights. In the iteratively reweighted L1-minimization sub-problem, different weights are equivalent to different regularization parameters at different locations. Thus, ASDR-L1 can be considered as a kind of spatially variant regularization methods for FMT. Physical phantom and in vivo mouse experiments were performed to validate the proposed algorithm. The results demonstrate that the proposed reweighted L1-reguarization algorithm can significantly improve the performance in terms of relative quantitation and spatial resolution.

  20. Ideal regularization for learning kernels from labels.

    Science.gov (United States)

    Pan, Binbin; Lai, Jianhuang; Shen, Lixin

    2014-08-01

    In this paper, we propose a new form of regularization that is able to utilize the label information of a data set for learning kernels. The proposed regularization, referred to as ideal regularization, is a linear function of the kernel matrix to be learned. The ideal regularization allows us to develop efficient algorithms to exploit labels. Three applications of the ideal regularization are considered. Firstly, we use the ideal regularization to incorporate the labels into a standard kernel, making the resulting kernel more appropriate for learning tasks. Next, we employ the ideal regularization to learn a data-dependent kernel matrix from an initial kernel matrix (which contains prior similarity information, geometric structures, and labels of the data). Finally, we incorporate the ideal regularization to some state-of-the-art kernel learning problems. With this regularization, these learning problems can be formulated as simpler ones which permit more efficient solvers. Empirical results show that the ideal regularization exploits the labels effectively and efficiently.

  1. Regularity extraction from non-adjacent sounds

    Directory of Open Access Journals (Sweden)

    Alexandra eBendixen

    2012-05-01

    Full Text Available The regular behavior of sound sources helps us to make sense of the auditory environment. Regular patterns may, for instance, convey information on the identity of a sound source (such as the acoustic signature of a train moving on the rails. Yet typically, this signature overlaps in time with signals emitted from other sound sources. It is generally assumed that auditory regularity extraction cannot operate upon this mixture of signals because it only finds regularities between adjacent sounds. In this view, the auditory environment would be grouped into separate entities by means of readily available acoustic cues such as separation in frequency and location. Regularity extraction processes would then operate upon the resulting groups. Our new experimental evidence challenges this view. We presented two interleaved sound sequences which overlapped in frequency range and shared all acoustic parameters. The sequences only differed in their underlying regular patterns. We inserted deviants into one of the sequences to probe whether the regularity was extracted. In the first experiment, we found that these deviants elicited the mismatch negativity (MMN component. Thus the auditory system was able to find the regularity between the non-adjacent sounds. Regularity extraction was not influenced by sequence cohesiveness as manipulated by the relative duration of tones and silent inter-tone-intervals. In the second experiment, we showed that a regularity connecting non-adjacent sounds was discovered only when the intervening sequence also contained a regular pattern, but not when the intervening sounds were randomly varying. This suggests that separate regular patterns are available to the auditory system as a cue for identifying signals coming from distinct sound sources. Thus auditory regularity extraction is not necessarily confined to a processing stage after initial sound grouping, but may precede grouping when other acoustic cues are unavailable.

  2. Six Regularities of Source Recognition

    Science.gov (United States)

    Glanzer, Murray; Hilford, Andy; Kim, Kisok

    2004-01-01

    In recent work, researchers have shown that source-recognition memory can be incorporated in an extended signal detection model that covers both it and item-recognition memory (A. Hilford, M. Glanzer, K. Kim, & L. T. DeCarlo, 2002). In 5 experiments, using learning variables that have an established effect on item recognition, the authors tested…

  3. Postural instability detection: aging and the complexity of spatial-temporal distributional patterns for virtually contacting the stability boundary in human stance.

    Directory of Open Access Journals (Sweden)

    Melissa C Kilby

    Full Text Available Falls among the older population can severely restrict their functional mobility and even cause death. Therefore, it is crucial to understand the mechanisms and conditions that cause falls, for which it is important to develop a predictive model of falls. One critical quantity for postural instability detection and prediction is the instantaneous stability of quiet upright stance based on motion data. However, well-established measures in the field of motor control that quantify overall postural stability using center-of-pressure (COP or center-of-mass (COM fluctuations are inadequate predictors of instantaneous stability. For this reason, 2D COP/COM virtual-time-to-contact (VTC is investigated to detect the postural stability deficits of healthy older people compared to young adults. VTC predicts the temporal safety margin to the functional stability boundary ( =  limits of the region of feasible COP or COM displacement and, therefore, provides an index of the risk of losing postural stability. The spatial directions with increased instability were also determined using quantities of VTC that have not previously been considered. Further, Lempel-Ziv-Complexity (LZC, a measure suitable for on-line monitoring of stability/instability, was applied to explore the temporal structure or complexity of VTC and the predictability of future postural instability based on previous behavior. These features were examined as a function of age, vision and different load weighting on the legs. The primary findings showed that for old adults the stability boundary was contracted and VTC reduced. Furthermore, the complexity decreased with aging and the direction with highest postural instability also changed in aging compared to the young adults. The findings reveal the sensitivity of the time dependent properties of 2D VTC to the detection of postural instability in aging, availability of visual information and postural stance and potential applicability as a

  4. Regularized Laplacian Estimation and Fast Eigenvector Approximation

    CERN Document Server

    Perry, Patrick O

    2011-01-01

    Recently, Mahoney and Orecchia demonstrated that popular diffusion-based procedures to compute a quick \\emph{approximation} to the first nontrivial eigenvector of a data graph Laplacian \\emph{exactly} solve certain regularized Semi-Definite Programs (SDPs). In this paper, we extend that result by providing a statistical interpretation of their approximation procedure. Our interpretation will be analogous to the manner in which $\\ell_2$-regularized or $\\ell_1$-regularized $\\ell_2$-regression (often called Ridge regression and Lasso regression, respectively) can be interpreted in terms of a Gaussian prior or a Laplace prior, respectively, on the coefficient vector of the regression problem. Our framework will imply that the solutions to the Mahoney-Orecchia regularized SDP can be interpreted as regularized estimates of the pseudoinverse of the graph Laplacian. Conversely, it will imply that the solution to this regularized estimation problem can be computed very quickly by running, e.g., the fast diffusion-base...

  5. Total variation regularization with bounded linear variations

    Science.gov (United States)

    Makovetskii, Artyom; Voronin, Sergei; Kober, Vitaly

    2016-09-01

    One of the most known techniques for signal denoising is based on total variation regularization (TV regularization). A better understanding of TV regularization is necessary to provide a stronger mathematical justification for using TV minimization in signal processing. In this work, we deal with an intermediate case between one- and two-dimensional cases; that is, a discrete function to be processed is two-dimensional radially symmetric piecewise constant. For this case, the exact solution to the problem can be obtained as follows: first, calculate the average values over rings of the noisy function; second, calculate the shift values and their directions using closed formulae depending on a regularization parameter and structure of rings. Despite the TV regularization is effective for noise removal; it often destroys fine details and thin structures of images. In order to overcome this drawback, we use the TV regularization for signal denoising subject to linear signal variations are bounded.

  6. A multiplicative regularization for force reconstruction

    Science.gov (United States)

    Aucejo, M.; De Smet, O.

    2017-02-01

    Additive regularizations, such as Tikhonov-like approaches, are certainly the most popular methods for reconstructing forces acting on a structure. These approaches require, however, the knowledge of a regularization parameter, that can be numerically computed using specific procedures. Unfortunately, these procedures are generally computationally intensive. For this particular reason, it could be of primary interest to propose a method able to proceed without defining any regularization parameter beforehand. In this paper, a multiplicative regularization is introduced for this purpose. By construction, the regularized solution has to be calculated in an iterative manner. In doing so, the amount of regularization is automatically adjusted throughout the resolution process. Validations using synthetic and experimental data highlight the ability of the proposed approach in providing consistent reconstructions.

  7. Regular Disjunction-Free Default Theories

    Institute of Scientific and Technical Information of China (English)

    Xi-ShunZhao

    2004-01-01

    In this paper, the class of regular disjunction-free default theories is introduced and investigated. A transformation from regular default theories to normal default theories is established. The initial theory and the transformed theory have the same extensions when restricted to old variables. Hence, regular default theories enjoy some similar properties (e.g., existence of extensions, semi-monotonicity) as normal default theories. Then, a new algorithm for credulous reasoning of regular theories is developed. This algorithm runs in a time not more than O(1.45n), where n is the number of defaults. In case of regular prerequisite-free or semi-2CNF default theories, the credulous reasoning can be solved in polynomial time. However, credulous reasoning for semi-Horn default theories is shown to be NP-complete although it is tractable for Horn default theories. Moreover, skeptical reasoning for regular unary default theories is co-NP-complete.

  8. Regular Disjunction-Free Default Theories

    Institute of Scientific and Technical Information of China (English)

    Xi-Shun Zhao

    2004-01-01

    In this paper, the class of regular disjunction-free default theories is introduced and investigated.A transformation from regular default theories to normal default theories is established. The initial theory and the transformed theory have the same extensions when restricted to old variables. Hence, regular default theories enjoy some similar properties (e.g., existence of extensions, semi-monotonicity) as normal default theories. Then,a new algorithm for credulous reasoning of regular theories is developed. This algorithm runs in a time not more than O(1.45n), where n is the number of defaults. In case of regular prerequisite-free or semi-2CNF default theories, the credulous reasoning can be solved in polynomial time. However, credulous reasoning for semi-Horn default theories is shown to be NP-complete although it is tractable for Horn default theories. Moreover, skeptical reasoning for regular unary default theories is co-NP-complete.

  9. 正三角形立体管桁架与单层柱面网壳杂交结构的设计与分析%DESIGN AND ANALYSES OF HYBRID-STRUCTURE BY REGULAR TRIANGULAR SPATIAL TRUSSES AND SINGLE-LAYER CYLINDRICAL RETICULATED SHELLS

    Institute of Scientific and Technical Information of China (English)

    王澈泉; 申波; 马克俭; 谢成吉; 李梦

    2014-01-01

    The regular triangular spatial trusses and single-layer cylindrical reticulated shells are integrated into a new roof structure of wave shape , which can give full play to the advantages of the two structures .By analyzing the calculation results of structural design , the structure has a weak seismic response , and through the static calculation the internal force of each bar on the structure greater than that under small earthquakes , strength and stiffness is mainly decided by the static calculation .On the basis of design for the new structure , dynamic elastic-plasticity, linear buckling and nonlinear buckling of considering the initial defects are analysed by using SAP 2000 and ANSYS. The structure has a small amount of plastic hinge under rare earthquake , thus presenting “beam hinge failure”mechanism , which satisfies the requirement of ductility design , elastic-plastic displacement angle can satisfy the requirements of the specification , the structure has good anti-seismic performance .The structure shows local buckling in the middle of reticulated shell under stability analysis , and has higher stability bearing capacity .The weak parts of the structure in the design should be strengthened .%将正三角形立体管桁架和单层柱面网壳结合起来形成一种新型波浪式屋盖造型的结构体系,可充分发挥两种结构形式的优点。通过分析结构设计的计算结果发现,结构对地震反应较弱,静力计算下结构各杆件的内力均大于多遇地震计算,强度及刚度主要由静力计算决定。在对其进行设计的基础上,分别采用SAP 2000、ANSYS对结构进行动力弹塑性分析、线性屈曲分析和考虑初始缺陷的非线性全过程屈曲分析;在罕遇地震作用下结构只出现少量塑性铰,呈“梁铰破坏”机制,满足延性设计要求,弹塑性位移角均满足规范要求,结构抗震性能良好;在稳定性分析中,结构表现为中部网壳

  10. Land drainage system detection using IR and visual imagery taken from autonomous mapping airship and evaluation of physical and spatial parameters of suggested method

    Science.gov (United States)

    Koska, Bronislav; Křemen, Tomáš; Štroner, Martin; Pospíšil, Jiří; Jirka, Vladimír.

    2014-10-01

    An experimental approach to the land drainage system detection and its physical and spatial parameters evaluation by the form of pilot project is presented in this paper. The novelty of the approach is partly based on using of unique unmanned aerial vehicle - airship with some specific properties. The most important parameters are carrying capacity (15 kg) and long flight time (3 hours). A special instrumentation was installed for physical characteristic testing in the locality too. The most important is 30 meter high mast with 3 meter length bracket at the top with sensors recording absolute and comparative temperature, humidity and wind speed and direction in several heights of the mast. There were also installed several measuring units recording local condition in the area. Recorded data were compared with IR images taken from airship platform. The locality is situated around village Domanín in the Czech Republic and has size about 1.8 x 1.5 km. There was build a land drainage system during the 70-ties of the last century which is made from burnt ceramic blocks placed about 70 cm below surface. The project documentation of the land drainage system exists but real state surveying haveńt been never realized. The aim of the project was land surveying of land drainage system based on infrared, visual and its combination high resolution orthophotos (10 cm for VIS and 30 cm for IR) and spatial and physical parameters evaluation of the presented procedure. The orthophoto in VIS and IR spectrum and its combination seems to be suitable for the task.

  11. 一种自适应空间邻域的显著图获取方法研究%Salient region detection using adaptive circular spatial surround

    Institute of Scientific and Technical Information of China (English)

    李海洋; 何东健

    2013-01-01

    In order to improve the situation of low accuracy of image retrieval in complex backgrounds,this paper proposed a retrieval scheme based on adaptive circular spatial surround.Considering the concentric structure of the human eye reception field,it adopted circular spatial surround.Then it calculated the salient values of pixels in that surround through weights generated by a two-dimensional normal distribution.Finally,it employed a simple threshold segmentation process on the saliency to generate a binary image.Experiments were carried out on 2 natural image sets.The results show that,compared with three state-of-the-art salient region detection methods,the proposed method gives improved accuracy in acquiring the saliency.%针对复杂背景下显著图提取精准度不高的问题,提出了一套基于自适应空间邻域的获取方案.该方案考虑人眼神经元感受野的同心圆结构,计算自适应圆形空间邻域;然后结合二维正态分布的显著权值计算空间邻域内每个像素点的显著值,获取图像的显著图,再利用简单的阈值分割算法提取二值图像;最后通过在两个自然图像集进行实验,并与三种经典算法进行比较.实验结果表明,该方法可以在复杂背景下有效地获取精确的显著图.

  12. Chaos at Uranus Spreads Dust Across the Regular Satellites

    Science.gov (United States)

    Tamayo, Dan; Burns, J. A.; Nicholson, P. D.; Hamilton, D. P.

    2012-05-01

    The short collision timescales between the Uranian irregular satellites argue for the past generation of vast quantities of dust at the outer reaches of Uranus’ Hill sphere (Bottke et al. 2010). Uranus’ extreme obliquity (98 degrees) renders the orbits of large objects unstable to eccentricity perturbations in the radial range a ≈ 60 - 75 Rp. (Tremaine et al. 2009). We study the effect on dust by investigating how the instability is modified by radiation pressure. We find that dust particles generated at the orbits of the irregular satellites move inward as radiation forces cause their orbits to decay (Burns et al. 1979). When they reach the unstable region, grain orbits undergo chaotic large-amplitude eccentricity oscillations that bring their pericenters inside the orbits of the regular satellites. We argue that the impact probabilities and expected spatial distribution across the satellite surfaces might explain the observed hemispherical color asymmetries common to the outer four regular satellites.

  13. Regularity effect in prospective memory during aging

    Directory of Open Access Journals (Sweden)

    Geoffrey Blondelle

    2016-10-01

    Full Text Available Background: Regularity effect can affect performance in prospective memory (PM, but little is known on the cognitive processes linked to this effect. Moreover, its impacts with regard to aging remain unknown. To our knowledge, this study is the first to examine regularity effect in PM in a lifespan perspective, with a sample of young, intermediate, and older adults. Objective and design: Our study examined the regularity effect in PM in three groups of participants: 28 young adults (18–30, 16 intermediate adults (40–55, and 25 older adults (65–80. The task, adapted from the Virtual Week, was designed to manipulate the regularity of the various activities of daily life that were to be recalled (regular repeated activities vs. irregular non-repeated activities. We examine the role of several cognitive functions including certain dimensions of executive functions (planning, inhibition, shifting, and binding, short-term memory, and retrospective episodic memory to identify those involved in PM, according to regularity and age. Results: A mixed-design ANOVA showed a main effect of task regularity and an interaction between age and regularity: an age-related difference in PM performances was found for irregular activities (older < young, but not for regular activities. All participants recalled more regular activities than irregular ones with no age effect. It appeared that recalling of regular activities only involved planning for both intermediate and older adults, while recalling of irregular ones were linked to planning, inhibition, short-term memory, binding, and retrospective episodic memory. Conclusion: Taken together, our data suggest that planning capacities seem to play a major role in remembering to perform intended actions with advancing age. Furthermore, the age-PM-paradox may be attenuated when the experimental design is adapted by implementing a familiar context through the use of activities of daily living. The clinical

  14. Ambiguities in Pauli-Villars regularization

    CERN Document Server

    Kleiss, Ronald H P

    2014-01-01

    We investigate regularization of scalar one-loop integrals in the Pauli- Villars subtraction scheme. The results depend on the number of sub- tractions, in particular the finite terms that survive after the diver- gences have been absorbed by renormalization. Therefore the process of Pauli-Villars regularization is ambiguous. We discuss how these am- biguities may be resolved by applying an asymptotically large number of subtractions, which results in a regularization that is automatically valid in any number of dimensions.

  15. Regularized brain reading with shrinkage and smoothing

    OpenAIRE

    Wehbe, Leila; Ramdas, Aaditya; Steorts, Rebecca C.; Shalizi, Cosma Rohilla

    2014-01-01

    Functional neuroimaging measures how the brain responds to complex stimuli. However, sample sizes are modest, noise is substantial, and stimuli are high dimensional. Hence, direct estimates are inherently imprecise and call for regularization. We compare a suite of approaches which regularize via shrinkage: ridge regression, the elastic net (a generalization of ridge regression and the lasso), and a hierarchical Bayesian model based on small area estimation (SAE). We contrast regularization w...

  16. Branch Processes of Regular Magnetic Monopole

    Institute of Scientific and Technical Information of China (English)

    MO Shu-Fan; REN Ji-Rong; ZHU Tao

    2009-01-01

    In this paper, by making use of Duan's topological current theory, the branch process of regular magnetic monopoles is discussed in detail Regular magnetic monopoles are found generating or annihilating at the limit point and encountering, splitting, or merging at the bifurcation point and the degenerate point systematically of the vector order parameter field φ(x).Furthermore, it is also shown that when regular magnetic monopoles split or merge at the degenerate point of field function φ, the total topological charges of the regular magnetic monopoles axe still unchanged.

  17. Iterative Regularization with Minimum-Residual Methods

    DEFF Research Database (Denmark)

    Jensen, Toke Koldborg; Hansen, Per Christian

    2007-01-01

    We study the regularization properties of iterative minimum-residual methods applied to discrete ill-posed problems. In these methods, the projection onto the underlying Krylov subspace acts as a regularizer, and the emphasis of this work is on the role played by the basis vectors of these Krylov...... subspaces. We provide a combination of theory and numerical examples, and our analysis confirms the experience that MINRES and MR-II can work as general regularization methods. We also demonstrate theoretically and experimentally that the same is not true, in general, for GMRES and RRGMRES their success...... as regularization methods is highly problem dependent....

  18. Iterative regularization with minimum-residual methods

    DEFF Research Database (Denmark)

    Jensen, Toke Koldborg; Hansen, Per Christian

    2006-01-01

    We study the regularization properties of iterative minimum-residual methods applied to discrete ill-posed problems. In these methods, the projection onto the underlying Krylov subspace acts as a regularizer, and the emphasis of this work is on the role played by the basis vectors of these Krylov...... subspaces. We provide a combination of theory and numerical examples, and our analysis confirms the experience that MINRES and MR-II can work as general regularization methods. We also demonstrate theoretically and experimentally that the same is not true, in general, for GMRES and RRGMRES - their success...... as regularization methods is highly problem dependent....

  19. Ideal-comparability over Regular Rings

    Institute of Scientific and Technical Information of China (English)

    Huan Yin CHEN; Miao Sen CHEN

    2006-01-01

    We introduce the concept of ideal-comparability condition for regular rings. Let I be an ideal of a regular ring R. If R satisfies the Ⅰ-comparability condition, then R is one-sided unit-regular if and only if so is R/I. Also, we show that a regular ring R satisfies the general comparability if and only if the following hold: (1) R/I satisfies the general comparability; (2) R satisfies the general Ⅰ-comparability condition; (3) The natural map B(R) → B(R/I) is surjective.

  20. Local and Nonlocal Regularization to Image Interpolation

    Directory of Open Access Journals (Sweden)

    Yi Zhan

    2014-01-01

    Full Text Available This paper presents an image interpolation model with local and nonlocal regularization. A nonlocal bounded variation (BV regularizer is formulated by an exponential function including gradient. It acts as the Perona-Malik equation. Thus our nonlocal BV regularizer possesses the properties of the anisotropic diffusion equation and nonlocal functional. The local total variation (TV regularizer dissipates image energy along the orthogonal direction to the gradient to avoid blurring image edges. The derived model efficiently reconstructs the real image, leading to a natural interpolation which reduces blurring and staircase artifacts. We present experimental results that prove the potential and efficacy of the method.

  1. Regularization and error assignment to unfolded distributions

    CERN Document Server

    Zech, Gunter

    2011-01-01

    The commonly used approach to present unfolded data only in graphical formwith the diagonal error depending on the regularization strength is unsatisfac-tory. It does not permit the adjustment of parameters of theories, the exclusionof theories that are admitted by the observed data and does not allow the com-bination of data from different experiments. We propose fixing the regulariza-tion strength by a p-value criterion, indicating the experimental uncertaintiesindependent of the regularization and publishing the unfolded data in additionwithout regularization. These considerations are illustrated with three differentunfolding and smoothing approaches applied to a toy example.

  2. Bit-coded regular expression parsing

    DEFF Research Database (Denmark)

    Nielsen, Lasse; Henglein, Fritz

    2011-01-01

    Regular expression parsing is the problem of producing a parse tree of a string for a given regular expression. We show that a compact bit representation of a parse tree can be produced efficiently, in time linear in the product of input string size and regular expression size, by simplifying...... the DFA-based parsing algorithm due to Dub ´e and Feeley to emit the bits of the bit representation without explicitly materializing the parse tree itself. We furthermore show that Frisch and Cardelli’s greedy regular expression parsing algorithm can be straightforwardly modified to produce bit codings...

  3. The regularity of quotient paratopological groups

    CERN Document Server

    Banakh, Taras

    2010-01-01

    Let $H$ be a closed subgroup of a regular abelian paratopological group $G$. The group reflexion $G^\\flat$ of $G$ is the group $G$ endowed with the strongest group topology, weaker that the original topology of $G$. We show that the quotient $G/H$ is Hausdorff (and regular) if $H$ is closed (and locally compact) in $G^\\flat$. On the other hand, we construct an example of a regular abelian paratopological group $G$ containing a closed discrete subgroup $H$ such that the quotient $G/H$ is Hausdorff but not regular.

  4. Land use change detection and prediction using high spatial resolution Google Earth imagery and GIS techniques: a study on El-Beheira Governorate, Egypt

    Science.gov (United States)

    Abdelaty, Emad Fawzy Saad

    2016-08-01

    Land Use change has become a vital component in current strategies for monitoring environmental changes and managing natural resources. Urban growth has brought serious losses of cultivated land, vegetation land and water bodies. In this study, we have taken North of Damanhour city as a case study to determine the land use change that took place in a period of time about of 6 years from 2008 to 2014 for investigation of changes after the revolution of January 25. The approach used in this study is the integration between Remote Sensing and GIS whereas the Google Earth was the source of data, while ArcGIS for further analysis of the digitized data. Google Earth has positioned itself at the forefront of a spatial information wave through providing free access to high-resolution imagery with simple, user friendly interface. The change detection is performed using historical imagery as a new tool in Google Earth program. Change detection rate shows that built-up area has been increased by 107.22 % between 2008 and 2014 whereas the urban area was 62.07 ha in 2008 and became 128.62 ha in 2014, on the other side the cultivated area has been decreased by 11.15 % between 2008 and 2014 whereas it changed from 596.74 ha in 2008 to 530.19 in 2014. The forecast function was used to predict land use changes between 2014 and 2032 based on 2008-2014 trends. Between 2014 and 2032, it was predicted that agricultural lands would decrease by 37.15% and built-up would increase by 40.70%.

  5. Detecting liquid threats with x-ray diffraction imaging (XDi) using a hybrid approach to navigate trade-offs between photon count statistics and spatial resolution

    Science.gov (United States)

    Skatter, Sondre; Fritsch, Sebastian; Schlomka, Jens-Peter

    2016-05-01

    The performance limits were explored for an X-ray Diffraction based explosives detection system for baggage scanning. This XDi system offers 4D imaging that comprises three spatial dimensions with voxel sizes in the order of ~(0.5cm)3, and one spectral dimension for material discrimination. Because only a very small number of photons are observed for an individual voxel, material discrimination cannot work reliably at the voxel level. Therefore, an initial 3D reconstruction is performed, which allows the identification of objects of interest. Combining all the measured photons that scattered within an object, more reliable spectra are determined on the object-level. As a case study we looked at two liquid materials, one threat and one innocuous, with very similar spectral characteristics, but with 15% difference in electron density. Simulations showed that Poisson statistics alone reduce the material discrimination performance to undesirable levels when the photon counts drop to 250. When additional, uncontrolled variation sources are considered, the photon count plays a less dominant role in detection performance, but limits the performance also for photon counts of 500 and higher. Experimental data confirmed the presence of such non-Poisson variation sources also in the XDi prototype system, which suggests that the present system can still be improved without necessarily increasing the photon flux, but by better controlling and accounting for these variation sources. When the classification algorithm was allowed to use spectral differences in the experimental data, the discrimination between the two materials improved significantly, proving the potential of X-ray diffraction also for liquid materials.

  6. SPATIAL STABILITY

    OpenAIRE

    Pascal Mossay

    2004-01-01

    We consider a continuous spatial economy consisting of pure exchange local economies. Agents are allowed to change their location over time as a response to spatial utility differentials. These spatial adjustments toward higher utility neighborhoods lead the spatial economy to converge to a spatially uniform allocation of resources, provided that the matrix of price effects is quasi-negative definite. Furthermore our model provides a real time interpretation of the tâtonnement story. Also, sp...

  7. Continuum regularization of quantum field theory

    Energy Technology Data Exchange (ETDEWEB)

    Bern, Z.

    1986-04-01

    Possible nonperturbative continuum regularization schemes for quantum field theory are discussed which are based upon the Langevin equation of Parisi and Wu. Breit, Gupta and Zaks made the first proposal for new gauge invariant nonperturbative regularization. The scheme is based on smearing in the ''fifth-time'' of the Langevin equation. An analysis of their stochastic regularization scheme for the case of scalar electrodynamics with the standard covariant gauge fixing is given. Their scheme is shown to preserve the masslessness of the photon and the tensor structure of the photon vacuum polarization at the one-loop level. Although stochastic regularization is viable in one-loop electrodynamics, two difficulties arise which, in general, ruins the scheme. One problem is that the superficial quadratic divergences force a bottomless action for the noise. Another difficulty is that stochastic regularization by fifth-time smearing is incompatible with Zwanziger's gauge fixing, which is the only known nonperturbaive covariant gauge fixing for nonabelian gauge theories. Finally, a successful covariant derivative scheme is discussed which avoids the difficulties encountered with the earlier stochastic regularization by fifth-time smearing. For QCD the regularized formulation is manifestly Lorentz invariant, gauge invariant, ghost free and finite to all orders. A vanishing gluon mass is explicitly verified at one loop. The method is designed to respect relevant symmetries, and is expected to provide suitable regularization for any theory of interest. Hopefully, the scheme will lend itself to nonperturbative analysis. 44 refs., 16 figs.

  8. Regular Decompositions for H(div) Spaces

    Energy Technology Data Exchange (ETDEWEB)

    Kolev, Tzanio [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Center for Applied Scientific Computing; Vassilevski, Panayot [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Center for Applied Scientific Computing

    2012-01-01

    We study regular decompositions for H(div) spaces. In particular, we show that such regular decompositions are closely related to a previously studied “inf-sup” condition for parameter-dependent Stokes problems, for which we provide an alternative, more direct, proof.

  9. Adaptive regularization of noisy linear inverse problems

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Madsen, Kristoffer Hougaard; Lehn-Schiøler, Tue

    2006-01-01

    In the Bayesian modeling framework there is a close relation between regularization and the prior distribution over parameters. For prior distributions in the exponential family, we show that the optimal hyper-parameter, i.e., the optimal strength of regularization, satisfies a simple relation: T...

  10. 12 CFR 725.3 - Regular membership.

    Science.gov (United States)

    2010-01-01

    ... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Regular membership. 725.3 Section 725.3 Banks and Banking NATIONAL CREDIT UNION ADMINISTRATION REGULATIONS AFFECTING CREDIT UNIONS NATIONAL CREDIT UNION ADMINISTRATION CENTRAL LIQUIDITY FACILITY § 725.3 Regular membership. (a) A natural person...

  11. Fast and compact regular expression matching

    DEFF Research Database (Denmark)

    Bille, Philip; Farach-Colton, Martin

    2008-01-01

    We study 4 problems in string matching, namely, regular expression matching, approximate regular expression matching, string edit distance, and subsequence indexing, on a standard word RAM model of computation that allows logarithmic-sized words to be manipulated in constant time. We show how...

  12. Regularity of harmonic maps with the potential

    Institute of Scientific and Technical Information of China (English)

    CHU; Yuming

    2006-01-01

    The aim of this work is to prove the partial regularity of the harmonic maps with potential. The main difficulty caused by the potential is how to find the equation satisfied by the scaling function. Under the assumption on the potential we can obtain the equation, however, for a general potential, even if it is smooth, the partial regularity is still open.

  13. On the Equivalence of Regularization Schemes

    Institute of Scientific and Technical Information of China (English)

    YANG Ji-Feng

    2002-01-01

    We illustrate via the sunset diagram that dimensional regularization ‘deforms' the nonlocal contentsof multi-loop diagrams with its equivalence to cutoff regularization scheme recovered only after sub-divergence wassubtracted. Then we employed a differential equation approach for calculating loop diagrams to verify that dimensionalare argued especially in nonperturbativc perspective.

  14. Regular Event Structures and Finite Petri Nets

    DEFF Research Database (Denmark)

    Nielsen, M.; Thiagarajan, P.S.

    2002-01-01

    We present the notion of regular event structures and conjecture that they correspond exactly to finite 1-safe Petri nets. We show that the conjecture holds for the conflict-free case. Even in this restricted setting, the proof is non-trivial and involves a natural subclass of regular event...

  15. Regularity Re-Revisited: Modality Matters

    Science.gov (United States)

    Tsapkini, Kyrana; Jarema, Gonia; Kehayia, Eva

    2004-01-01

    The issue of regular-irregular past tense formation was examined in a cross-modal lexical decision task in Modern Greek, a language where the orthographic and phonological overlap between present and past tense stems is the same for both regular and irregular verbs. The experiment described here is a follow-up study of previous visual lexical…

  16. Regularization algorithms based on total least squares

    DEFF Research Database (Denmark)

    Hansen, Per Christian; O'Leary, Dianne P.

    1996-01-01

    Discretizations of inverse problems lead to systems of linear equations with a highly ill-conditioned coefficient matrix, and in order to compute stable solutions to these systems it is necessary to apply regularization methods. Classical regularization methods, such as Tikhonov's method or trunc...

  17. A regularized stationary mean-field game

    KAUST Repository

    Yang, Xianjin

    2016-04-19

    In the thesis, we discuss the existence and numerical approximations of solutions of a regularized mean-field game with a low-order regularization. In the first part, we prove a priori estimates and use the continuation method to obtain the existence of a solution with a positive density. Finally, we introduce the monotone flow method and solve the system numerically.

  18. New Algorithms and Sparse Regularization for Synthetic Aperture Radar Imaging

    Science.gov (United States)

    2015-10-26

    AFRL-AFOSR-VA-TR-2015-0343 New Algorithms and Sparse Regularization for Synthetic Aperture Radar Imaging Laurent Demanet MASSACHUSETTS INSTITUTE OF...26-10-2015 2. REPORT TYPE Final Performance 3. DATES COVERED (From - To) 14-06-2014 to 14-06-2015 4. TITLE AND SUBTITLE New Algorithms and Sparse...method must fail -- at the target detection task. The analysis identifies the algorithms that perform well, and those that don’t, even in the case of

  19. Minimal regular 2-graphs and applications

    Institute of Scientific and Technical Information of China (English)

    FAN; Hongbing; LIU; Guizhen; LIU; Jiping

    2006-01-01

    A 2-graph is a hypergraph with edge sizes of at most two. A regular 2-graph is said to be minimal if it does not contain a proper regular factor. Let f2(n) be the maximum value of degrees over all minimal regular 2-graphs of n vertices. In this paper, we provide a structure property of minimal regular 2-graphs, and consequently, prove that f2(n) = n+3-i/3where 1 ≤i≤6, i=n (mod 6) andn≥ 7, which solves a conjecture posed by Fan, Liu, Wu and Wong. As applications in graph theory, we are able to characterize unfactorable regular graphs and provide the best possible factor existence theorem on degree conditions. Moreover, f2(n) and the minimal 2-graphs can be used in the universal switch box designs, which originally motivated this study.

  20. Regular Expression Matching and Operational Semantics

    CERN Document Server

    Rathnayake, Asiri; 10.4204/EPTCS.62.3

    2011-01-01

    Many programming languages and tools, ranging from grep to the Java String library, contain regular expression matchers. Rather than first translating a regular expression into a deterministic finite automaton, such implementations typically match the regular expression on the fly. Thus they can be seen as virtual machines interpreting the regular expression much as if it were a program with some non-deterministic constructs such as the Kleene star. We formalize this implementation technique for regular expression matching using operational semantics. Specifically, we derive a series of abstract machines, moving from the abstract definition of matching to increasingly realistic machines. First a continuation is added to the operational semantics to describe what remains to be matched after the current expression. Next, we represent the expression as a data structure using pointers, which enables redundant searches to be eliminated via testing for pointer equality. From there, we arrive both at Thompson's lock...