Visual Odometry Based on Structural Matching of Local Invariant Features Using Stereo Camera Sensor

PubMed Central

Núñez, Pedro; Vázquez-Martín, Ricardo; Bandera, Antonio

2011-01-01

This paper describes a novel sensor system to estimate the motion of a stereo camera. Local invariant image features are matched between pairs of frames and linked into image trajectories at video rate, providing the so-called visual odometry, i.e., motion estimates from visual input alone. Our proposal conducts two matching sessions: the first one between sets of features associated to the images of the stereo pairs and the second one between sets of features associated to consecutive frames. With respect to previously proposed approaches, the main novelty of this proposal is that both matching algorithms are conducted by means of a fast matching algorithm which combines absolute and relative feature constraints. Finding the largest-valued set of mutually consistent matches is equivalent to finding the maximum-weighted clique on a graph. The stereo matching allows to represent the scene view as a graph which emerge from the features of the accepted clique. On the other hand, the frame-to-frame matching defines a graph whose vertices are features in 3D space. The efficiency of the approach is increased by minimizing the geometric and algebraic errors to estimate the final displacement of the stereo camera between consecutive acquired frames. The proposed approach has been tested for mobile robotics navigation purposes in real environments and using different features. Experimental results demonstrate the performance of the proposal, which could be applied in both industrial and service robot fields. PMID:22164016

A new template matching method based on contour information

NASA Astrophysics Data System (ADS)

Cai, Huiying; Zhu, Feng; Wu, Qingxiao; Li, Sicong

2014-11-01

Template matching is a significant approach in machine vision due to its effectiveness and robustness. However, most of the template matching methods are so time consuming that they can't be used to many real time applications. The closed contour matching method is a popular kind of template matching methods. This paper presents a new closed contour template matching method which is suitable for two dimensional objects. Coarse-to-fine searching strategy is used to improve the matching efficiency and a partial computation elimination scheme is proposed to further speed up the searching process. The method consists of offline model construction and online matching. In the process of model construction, triples and distance image are obtained from the template image. A certain number of triples which are composed by three points are created from the contour information that is extracted from the template image. The rule to select the three points is that the template contour is divided equally into three parts by these points. The distance image is obtained here by distance transform. Each point on the distance image represents the nearest distance between current point and the points on the template contour. During the process of matching, triples of the searching image are created with the same rule as the triples of the model. Through the similarity that is invariant to rotation, translation and scaling between triangles, the triples corresponding to the triples of the model are found. Then we can obtain the initial RST (rotation, translation and scaling) parameters mapping the searching contour to the template contour. In order to speed up the searching process, the points on the searching contour are sampled to reduce the number of the triples. To verify the RST parameters, the searching contour is projected into the distance image, and the mean distance can be computed rapidly by simple operations of addition and multiplication. In the fine searching process

Quantification of organ motion based on an adaptive image-based scale invariant feature method

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

Paganelli, Chiara; Peroni, Marta; Baroni, Guido

2013-11-15

Purpose: The availability of corresponding landmarks in IGRT image series allows quantifying the inter and intrafractional motion of internal organs. In this study, an approach for the automatic localization of anatomical landmarks is presented, with the aim of describing the nonrigid motion of anatomo-pathological structures in radiotherapy treatments according to local image contrast.Methods: An adaptive scale invariant feature transform (SIFT) was developed from the integration of a standard 3D SIFT approach with a local image-based contrast definition. The robustness and invariance of the proposed method to shape-preserving and deformable transforms were analyzed in a CT phantom study. The application ofmore » contrast transforms to the phantom images was also tested, in order to verify the variation of the local adaptive measure in relation to the modification of image contrast. The method was also applied to a lung 4D CT dataset, relying on manual feature identification by an expert user as ground truth. The 3D residual distance between matches obtained in adaptive-SIFT was then computed to verify the internal motion quantification with respect to the expert user. Extracted corresponding features in the lungs were used as regularization landmarks in a multistage deformable image registration (DIR) mapping the inhale vs exhale phase. The residual distances between the warped manual landmarks and their reference position in the inhale phase were evaluated, in order to provide a quantitative indication of the registration performed with the three different point sets.Results: The phantom study confirmed the method invariance and robustness properties to shape-preserving and deformable transforms, showing residual matching errors below the voxel dimension. The adapted SIFT algorithm on the 4D CT dataset provided automated and accurate motion detection of peak to peak breathing motion. The proposed method resulted in reduced residual errors with respect to

A scale-invariant change detection method for land use/cover change research

NASA Astrophysics Data System (ADS)

Xing, Jin; Sieber, Renee; Caelli, Terrence

2018-07-01

Land Use/Cover Change (LUCC) detection relies increasingly on comparing remote sensing images with different spatial and spectral scales. Based on scale-invariant image analysis algorithms in computer vision, we propose a scale-invariant LUCC detection method to identify changes from scale heterogeneous images. This method is composed of an entropy-based spatial decomposition, two scale-invariant feature extraction methods, Maximally Stable Extremal Region (MSER) and Scale-Invariant Feature Transformation (SIFT) algorithms, a spatial regression voting method to integrate MSER and SIFT results, a Markov Random Field-based smoothing method, and a support vector machine classification method to assign LUCC labels. We test the scale invariance of our new method with a LUCC case study in Montreal, Canada, 2005-2012. We found that the scale-invariant LUCC detection method provides similar accuracy compared with the resampling-based approach but this method avoids the LUCC distortion incurred by resampling.

Position, rotation, and intensity invariant recognizing method

DOEpatents

Ochoa, Ellen; Schils, George F.; Sweeney, Donald W.

1989-01-01

A method for recognizing the presence of a particular target in a field of view which is target position, rotation, and intensity invariant includes the preparing of a target-specific invariant filter from a combination of all eigen-modes of a pattern of the particular target. Coherent radiation from the field of view is then imaged into an optical correlator in which the invariant filter is located. The invariant filter is rotated in the frequency plane of the optical correlator in order to produce a constant-amplitude rotational response in a correlation output plane when the particular target is present in the field of view. Any constant response is thus detected in the output The U.S. Government has rights in this invention pursuant to Contract No. DE-AC04-76DP00789 between the U.S. Department of Energy and AT&T Technologies, Inc.

Quark matter in the perturbation QCD model with a rapidly convergent matching-invariant running coupling

NASA Astrophysics Data System (ADS)

Xu, Jian-Feng; Luo, Yan-An; Li, Lei; Peng, Guang-Xiong

The properties of dense quark matter are investigated in the perturbation theory with a rapidly convergent matching-invariant running coupling. The fast convergence is mainly due to the resummation of an infinite number of known logarithmic terms in a compact form. The only parameter in this model, the ratio of the renormalization subtraction point to the chemical potential, is restricted to be about 2.64 according to the Witten-Bodmer conjecture, which gives the maximum mass and the biggest radius of quark stars to be, respectively, two times the solar mass and 11.7km.

False match elimination for face recognition based on SIFT algorithm

NASA Astrophysics Data System (ADS)

Gu, Xuyuan; Shi, Ping; Shao, Meide

2011-06-01

The SIFT (Scale Invariant Feature Transform) is a well known algorithm used to detect and describe local features in images. It is invariant to image scale, rotation and robust to the noise and illumination. In this paper, a novel method used for face recognition based on SIFT is proposed, which combines the optimization of SIFT, mutual matching and Progressive Sample Consensus (PROSAC) together and can eliminate the false matches of face recognition effectively. Experiments on ORL face database show that many false matches can be eliminated and better recognition rate is achieved.

A novel image registration approach via combining local features and geometric invariants

PubMed Central

Lu, Yan; Gao, Kun; Zhang, Tinghua; Xu, Tingfa

2018-01-01

Image registration is widely used in many fields, but the adaptability of the existing methods is limited. This work proposes a novel image registration method with high precision for various complex applications. In this framework, the registration problem is divided into two stages. First, we detect and describe scale-invariant feature points using modified computer vision-oriented fast and rotated brief (ORB) algorithm, and a simple method to increase the performance of feature points matching is proposed. Second, we develop a new local constraint of rough selection according to the feature distances. Evidence shows that the existing matching techniques based on image features are insufficient for the images with sparse image details. Then, we propose a novel matching algorithm via geometric constraints, and establish local feature descriptions based on geometric invariances for the selected feature points. Subsequently, a new price function is constructed to evaluate the similarities between points and obtain exact matching pairs. Finally, we employ the progressive sample consensus method to remove wrong matches and calculate the space transform parameters. Experimental results on various complex image datasets verify that the proposed method is more robust and significantly reduces the rate of false matches while retaining more high-quality feature points. PMID:29293595

Rotation invariants of vector fields from orthogonal moments

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

Yang, Bo; Kostková, Jitka; Flusser, Jan

Vector field images are a type of new multidimensional data that appear in many engineering areas. Although the vector fields can be visualized as images, they differ from graylevel and color images in several aspects. In order to analyze them, special methods and algorithms must be originally developed or substantially adapted from the traditional image processing area. Here, we propose a method for the description and matching of vector field patterns under an unknown rotation of the field. Rotation of a vector field is so-called total rotation, where the action is applied not only on the spatial coordinates but alsomore » on the field values. Invariants of vector fields with respect to total rotation constructed from orthogonal Gaussian–Hermite moments and Zernike moments are introduced. Their numerical stability is shown to be better than that of the invariants published so far. We demonstrate their usefulness in a real world template matching application of rotated vector fields.« less

Rotation invariants of vector fields from orthogonal moments

DOE PAGES

Yang, Bo; Kostková, Jitka; Flusser, Jan; ...

2017-09-11

Vector field images are a type of new multidimensional data that appear in many engineering areas. Although the vector fields can be visualized as images, they differ from graylevel and color images in several aspects. In order to analyze them, special methods and algorithms must be originally developed or substantially adapted from the traditional image processing area. Here, we propose a method for the description and matching of vector field patterns under an unknown rotation of the field. Rotation of a vector field is so-called total rotation, where the action is applied not only on the spatial coordinates but alsomore » on the field values. Invariants of vector fields with respect to total rotation constructed from orthogonal Gaussian–Hermite moments and Zernike moments are introduced. Their numerical stability is shown to be better than that of the invariants published so far. We demonstrate their usefulness in a real world template matching application of rotated vector fields.« less

On the falsifiability of matching theory.

PubMed Central

McDowell, J J

1986-01-01

Herrnstein's matching theory requires the parameter, k, which appears in the single-alternative form of the matching equation, to remain invariant with respect to changes in reinforcement parameters like magnitude or immediacy. Recent experiments have disconfirmed matching theory by showing that the invariant-k requirement does not hold. However, the theory can be asserted in a purely algebraic form that does not require an invariant k and that is not disconfirmed by the recent findings. In addition, both the original and the purely algebraic versions of matching theory can be asserted in forms that allow for commonly observed deviations from matching (bias, undermatching, and overmatching). The recent finding of a variable k does not disconfirm these versions of matching theory either. As a consequence, matching remains a viable theory of behavior, the strength of which lies in its general conceptualization of all behavior as choice, and in its unified mathematical treatment of single- and multialternative environments. PMID:3950535

A robust rotation-invariance displacement measurement method for a micro-/nano-positioning system

NASA Astrophysics Data System (ADS)

Zhang, Xiang; Zhang, Xianmin; Wu, Heng; Li, Hai; Gan, Jinqiang

2018-05-01

A robust and high-precision displacement measurement method for a compliant mechanism-based micro-/nano-positioning system is proposed. The method is composed of an integer-pixel and a sub-pixel matching procedure. In the proposed algorithm (Pro-A), an improved ring projection transform (IRPT) and gradient information are used as features for approximating the coarse candidates and fine locations, respectively. Simulations are conducted and the results show that the Pro-A has the ability of rotation-invariance and strong robustness, with a theoretical accuracy of 0.01 pixel. To validate the practical performance, a series of experiments are carried out using a computer micro-vision and laser interferometer system (LIMS). The results demonstrate that both the LIMS and Pro-A can achieve high precision, while the Pro-A has better stability and adaptability.

Good match exploration for infrared face recognition

NASA Astrophysics Data System (ADS)

Yang, Changcai; Zhou, Huabing; Sun, Sheng; Liu, Renfeng; Zhao, Ji; Ma, Jiayi

2014-11-01

Establishing good feature correspondence is a critical prerequisite and a challenging task for infrared (IR) face recognition. Recent studies revealed that the scale invariant feature transform (SIFT) descriptor outperforms other local descriptors for feature matching. However, it only uses local appearance information for matching, and hence inevitably leads to a number of false matches. To address this issue, this paper explores global structure information (GSI) among SIFT correspondences, and proposes a new method SIFT-GSI for good match exploration. This is achieved by fitting a smooth mapping function for the underlying correct matches, which involves softassign and deterministic annealing. Quantitative comparisons with state-of-the-art methods on a publicly available IR human face database demonstrate that SIFT-GSI significantly outperforms other methods for feature matching, and hence it is able to improve the reliability of IR face recognition systems.

Position, rotation, and intensity invariant recognizing method

DOEpatents

Ochoa, E.; Schils, G.F.; Sweeney, D.W.

1987-09-15

A method for recognizing the presence of a particular target in a field of view which is target position, rotation, and intensity invariant includes the preparing of a target-specific invariant filter from a combination of all eigen-modes of a pattern of the particular target. Coherent radiation from the field of view is then imaged into an optical correlator in which the invariant filter is located. The invariant filter is rotated in the frequency plane of the optical correlator in order to produce a constant-amplitude rotational response in a correlation output plane when the particular target is present in the field of view. Any constant response is thus detected in the output plane to determine whether a particular target is present in the field of view. Preferably, a temporal pattern is imaged in the output plane with a optical detector having a plurality of pixels and a correlation coefficient for each pixel is determined by accumulating the intensity and intensity-square of each pixel. The orbiting of the constant response caused by the filter rotation is also preferably eliminated either by the use of two orthogonal mirrors pivoted correspondingly to the rotation of the filter or the attaching of a refracting wedge to the filter to remove the offset angle. Detection is preferably performed of the temporal pattern in the output plane at a plurality of different angles with angular separation sufficient to decorrelate successive frames. 1 fig.

Robust polygon recognition method with similarity invariants applied to star identification

NASA Astrophysics Data System (ADS)

Hernández, E. Antonio; Alonso, Miguel A.; Chávez, Edgar; Covarrubias, David H.; Conte, Roberto

2017-02-01

In the star identification process the goal is to recognize a star by using the celestial bodies in its vicinity as context. An additional requirement is to avoid having to perform an exhaustive scan of the star database. In this paper we present a novel approach to star identification using similarity invariants. More specifically, the proposed algorithm defines a polygon for each star, using the neighboring celestial bodies in the field of view as vertices. The mapping is insensitive to similarity transformation; that is, the image of the polygon under the transformation is not affected by rotation, scaling or translations. Each polygon is associated with an essentially unique complex number. We perform an exhaustive experimental validation of the proposed algorithm using synthetic data generated from the star catalog with uniformly-distributed positional noise introduced to each star. The star identification method that we present is proven to be robust, achieving a recognition rate of 99.68% when noise levels of up to ± 424 μ radians are introduced to the location of the stars. In our tests the proposed algorithm proves that if a polygon match is found, it always corresponds to the star under analysis; no mismatches are found. In its present form our method cannot identify polygons in cases where there exist missing or false stars in the analyzed images, in those situations it only indicates that no match was found.

Combined invariants to similarity transformation and to blur using orthogonal Zernike moments

PubMed Central

Beijing, Chen; Shu, Huazhong; Zhang, Hui; Coatrieux, Gouenou; Luo, Limin; Coatrieux, Jean-Louis

2011-01-01

The derivation of moment invariants has been extensively investigated in the past decades. In this paper, we construct a set of invariants derived from Zernike moments which is simultaneously invariant to similarity transformation and to convolution with circularly symmetric point spread function (PSF). Two main contributions are provided: the theoretical framework for deriving the Zernike moments of a blurred image and the way to construct the combined geometric-blur invariants. The performance of the proposed descriptors is evaluated with various PSFs and similarity transformations. The comparison of the proposed method with the existing ones is also provided in terms of pattern recognition accuracy, template matching and robustness to noise. Experimental results show that the proposed descriptors perform on the overall better. PMID:20679028

Iris recognition using possibilistic fuzzy matching on local features.

PubMed

Tsai, Chung-Chih; Lin, Heng-Yi; Taur, Jinshiuh; Tao, Chin-Wang

2012-02-01

In this paper, we propose a novel possibilistic fuzzy matching strategy with invariant properties, which can provide a robust and effective matching scheme for two sets of iris feature points. In addition, the nonlinear normalization model is adopted to provide more accurate position before matching. Moreover, an effective iris segmentation method is proposed to refine the detected inner and outer boundaries to smooth curves. For feature extraction, the Gabor filters are adopted to detect the local feature points from the segmented iris image in the Cartesian coordinate system and to generate a rotation-invariant descriptor for each detected point. After that, the proposed matching algorithm is used to compute a similarity score for two sets of feature points from a pair of iris images. The experimental results show that the performance of our system is better than those of the systems based on the local features and is comparable to those of the typical systems.

Spectral-Spatial Scale Invariant Feature Transform for Hyperspectral Images.

PubMed

Al-Khafaji, Suhad Lateef; Jun Zhou; Zia, Ali; Liew, Alan Wee-Chung

2018-02-01

Spectral-spatial feature extraction is an important task in hyperspectral image processing. In this paper we propose a novel method to extract distinctive invariant features from hyperspectral images for registration of hyperspectral images with different spectral conditions. Spectral condition means images are captured with different incident lights, viewing angles, or using different hyperspectral cameras. In addition, spectral condition includes images of objects with the same shape but different materials. This method, which is named spectral-spatial scale invariant feature transform (SS-SIFT), explores both spectral and spatial dimensions simultaneously to extract spectral and geometric transformation invariant features. Similar to the classic SIFT algorithm, SS-SIFT consists of keypoint detection and descriptor construction steps. Keypoints are extracted from spectral-spatial scale space and are detected from extrema after 3D difference of Gaussian is applied to the data cube. Two descriptors are proposed for each keypoint by exploring the distribution of spectral-spatial gradient magnitude in its local 3D neighborhood. The effectiveness of the SS-SIFT approach is validated on images collected in different light conditions, different geometric projections, and using two hyperspectral cameras with different spectral wavelength ranges and resolutions. The experimental results show that our method generates robust invariant features for spectral-spatial image matching.

Combining color and shape information for illumination-viewpoint invariant object recognition.

PubMed

Diplaros, Aristeidis; Gevers, Theo; Patras, Ioannis

2006-01-01

In this paper, we propose a new scheme that merges color- and shape-invariant information for object recognition. To obtain robustness against photometric changes, color-invariant derivatives are computed first. Color invariance is an important aspect of any object recognition scheme, as color changes considerably with the variation in illumination, object pose, and camera viewpoint. These color invariant derivatives are then used to obtain similarity invariant shape descriptors. Shape invariance is equally important as, under a change in camera viewpoint and object pose, the shape of a rigid object undergoes a perspective projection on the image plane. Then, the color and shape invariants are combined in a multidimensional color-shape context which is subsequently used as an index. As the indexing scheme makes use of a color-shape invariant context, it provides a high-discriminative information cue robust against varying imaging conditions. The matching function of the color-shape context allows for fast recognition, even in the presence of object occlusion and cluttering. From the experimental results, it is shown that the method recognizes rigid objects with high accuracy in 3-D complex scenes and is robust against changing illumination, camera viewpoint, object pose, and noise.

An effective image classification method with the fusion of invariant feature and a new color descriptor

NASA Astrophysics Data System (ADS)

Mansourian, Leila; Taufik Abdullah, Muhamad; Nurliyana Abdullah, Lili; Azman, Azreen; Mustaffa, Mas Rina

2017-02-01

Pyramid Histogram of Words (PHOW), combined Bag of Visual Words (BoVW) with the spatial pyramid matching (SPM) in order to add location information to extracted features. However, different PHOW extracted from various color spaces, and they did not extract color information individually, that means they discard color information, which is an important characteristic of any image that is motivated by human vision. This article, concatenated PHOW Multi-Scale Dense Scale Invariant Feature Transform (MSDSIFT) histogram and a proposed Color histogram to improve the performance of existing image classification algorithms. Performance evaluation on several datasets proves that the new approach outperforms other existing, state-of-the-art methods.

Reflection symmetry detection using locally affine invariant edge correspondence.

PubMed

Wang, Zhaozhong; Tang, Zesheng; Zhang, Xiao

2015-04-01

Reflection symmetry detection receives increasing attentions in recent years. The state-of-the-art algorithms mainly use the matching of intensity-based features (such as the SIFT) within a single image to find symmetry axes. This paper proposes a novel approach by establishing the correspondence of locally affine invariant edge-based features, which are superior to the intensity based in the aspects that it is insensitive to illumination variations, and applicable to textureless objects. The locally affine invariance is achieved by simple linear algebra for efficient and robust computations, making the algorithm suitable for detections under object distortions like perspective projection. Commonly used edge detectors and a voting process are, respectively, used before and after the edge description and matching steps to form a complete reflection detection pipeline. Experiments are performed using synthetic and real-world images with both multiple and single reflection symmetry axis. The test results are compared with existing algorithms to validate the proposed method.

A theory of phase singularities for image representation and its applications to object tracking and image matching.

PubMed

Qiao, Yu; Wang, Wei; Minematsu, Nobuaki; Liu, Jianzhuang; Takeda, Mitsuo; Tang, Xiaoou

2009-10-01

This paper studies phase singularities (PSs) for image representation. We show that PSs calculated with Laguerre-Gauss filters contain important information and provide a useful tool for image analysis. PSs are invariant to image translation and rotation. We introduce several invariant features to characterize the core structures around PSs and analyze the stability of PSs to noise addition and scale change. We also study the characteristics of PSs in a scale space, which lead to a method to select key scales along phase singularity curves. We demonstrate two applications of PSs: object tracking and image matching. In object tracking, we use the iterative closest point algorithm to determine the correspondences of PSs between two adjacent frames. The use of PSs allows us to precisely determine the motions of tracked objects. In image matching, we combine PSs and scale-invariant feature transform (SIFT) descriptor to deal with the variations between two images and examine the proposed method on a benchmark database. The results indicate that our method can find more correct matching pairs with higher repeatability rates than some well-known methods.

Method of synthesized phase objects for pattern recognition with rotation invariance

NASA Astrophysics Data System (ADS)

Ostroukh, Alexander P.; Butok, Alexander M.; Shvets, Rostislav A.; Yezhov, Pavel V.; Kim, Jin-Tae; Kuzmenko, Alexander V.

2015-11-01

We present a development of the method of synthesized phase objects (SPO-method) [1] for the rotation-invariant pattern recognition. For the standard method of recognition and the SPO-method, the comparison of the parameters of correlation signals for a number of amplitude objects is executed at the realization of a rotation in an optical-digital correlator with the joint Fourier transformation. It is shown that not only the invariance relative to a rotation at a realization of the joint correlation for synthesized phase objects (SP-objects) but also the main advantage of the method of SP-objects over the reference one such as the unified δ-like recognition signal with the largest possible signal-to-noise ratio independent of the type of an object are attained.

Target matching based on multi-view tracking

NASA Astrophysics Data System (ADS)

Liu, Yahui; Zhou, Changsheng

2011-01-01

A feature matching method is proposed based on Maximally Stable Extremal Regions (MSER) and Scale Invariant Feature Transform (SIFT) to solve the problem of the same target matching in multiple cameras. Target foreground is extracted by using frame difference twice and bounding box which is regarded as target regions is calculated. Extremal regions are got by MSER. After fitted into elliptical regions, those regions will be normalized into unity circles and represented with SIFT descriptors. Initial matching is obtained from the ratio of the closest distance to second distance less than some threshold and outlier points are eliminated in terms of RANSAC. Experimental results indicate the method can reduce computational complexity effectively and is also adapt to affine transformation, rotation, scale and illumination.

Calculation of NMR chemical shifts. 7. Gauge-invariant INDO method

NASA Astrophysics Data System (ADS)

Fukui, H.; Miura, K.; Hirai, A.

A gauge-invariant INDO method based on the coupled Hartree-Fuck perturbation theory is presented and applied to the calculation of 1H and 13C chemical shifts of hydrocarbons including ring compounds. Invariance of the diamagnetic and paramagnetic shieldings with respect to displacement of the coordinate origin is discussed. Comparison between calculated and experimental results exhibits fairly good agreement, provided that the INDO parameters of Ellis et al. (J. Am. Chem. Soc.94, 4069 (1972)) are used with the inclusion of all multicenter one-electron integrals.

Super-resolution image reconstruction from UAS surveillance video through affine invariant interest point-based motion estimation

NASA Astrophysics Data System (ADS)

He, Qiang; Schultz, Richard R.; Wang, Yi; Camargo, Aldo; Martel, Florent

2008-01-01

In traditional super-resolution methods, researchers generally assume that accurate subpixel image registration parameters are given a priori. In reality, accurate image registration on a subpixel grid is the single most critically important step for the accuracy of super-resolution image reconstruction. In this paper, we introduce affine invariant features to improve subpixel image registration, which considerably reduces the number of mismatched points and hence makes traditional image registration more efficient and more accurate for super-resolution video enhancement. Affine invariant interest points include those corners that are invariant to affine transformations, including scale, rotation, and translation. They are extracted from the second moment matrix through the integration and differentiation covariance matrices. Our tests are based on two sets of real video captured by a small Unmanned Aircraft System (UAS) aircraft, which is highly susceptible to vibration from even light winds. The experimental results from real UAS surveillance video show that affine invariant interest points are more robust to perspective distortion and present more accurate matching than traditional Harris/SIFT corners. In our experiments on real video, all matching affine invariant interest points are found correctly. In addition, for the same super-resolution problem, we can use many fewer affine invariant points than Harris/SIFT corners to obtain good super-resolution results.

An Integrated Ransac and Graph Based Mismatch Elimination Approach for Wide-Baseline Image Matching

NASA Astrophysics Data System (ADS)

Hasheminasab, M.; Ebadi, H.; Sedaghat, A.

2015-12-01

In this paper we propose an integrated approach in order to increase the precision of feature point matching. Many different algorithms have been developed as to optimizing the short-baseline image matching while because of illumination differences and viewpoints changes, wide-baseline image matching is so difficult to handle. Fortunately, the recent developments in the automatic extraction of local invariant features make wide-baseline image matching possible. The matching algorithms which are based on local feature similarity principle, using feature descriptor as to establish correspondence between feature point sets. To date, the most remarkable descriptor is the scale-invariant feature transform (SIFT) descriptor , which is invariant to image rotation and scale, and it remains robust across a substantial range of affine distortion, presence of noise, and changes in illumination. The epipolar constraint based on RANSAC (random sample consensus) method is a conventional model for mismatch elimination, particularly in computer vision. Because only the distance from the epipolar line is considered, there are a few false matches in the selected matching results based on epipolar geometry and RANSAC. Aguilariu et al. proposed Graph Transformation Matching (GTM) algorithm to remove outliers which has some difficulties when the mismatched points surrounded by the same local neighbor structure. In this study to overcome these limitations, which mentioned above, a new three step matching scheme is presented where the SIFT algorithm is used to obtain initial corresponding point sets. In the second step, in order to reduce the outliers, RANSAC algorithm is applied. Finally, to remove the remained mismatches, based on the adjacent K-NN graph, the GTM is implemented. Four different close range image datasets with changes in viewpoint are utilized to evaluate the performance of the proposed method and the experimental results indicate its robustness and capability.

Direct matching methods for coils and preamplifiers in MRI

NASA Astrophysics Data System (ADS)

Cao, Xueming; Fischer, Elmar; Hennig, Jürgen; Zaitsev, Maxim

2018-05-01

In this paper, direct matching methods for coils and preamplifiers in receiver arrays are presented. Instead of compensating the reactance of the input impedance of preamplifiers, in our method, the reactance was used to resonate with the coil matching networks and thus to decouple the coils. Furthermore, coil matching networks and preamplifier input matching networks were combined, meaning the coil loop can be matched to the transistor in the preamplifier directly. These matching methods and, for comparison, the conventional matching method were implemented with custom-made preamplifiers and coils. Decoupling and noise-matching performance were compared between these three configurations. Phase shifting networks between coils and preamplifiers are not necessary in our matching methods. With fewer components, these matching networks showed lower noise factors, while similar preamplifier-decoupling performance was found for all three methods.

Shaping propagation invariant laser beams

NASA Astrophysics Data System (ADS)

Soskind, Michael; Soskind, Rose; Soskind, Yakov

2015-11-01

Propagation-invariant structured laser beams possess several unique properties and play an important role in various photonics applications. The majority of propagation invariant beams are produced in the form of laser modes emanating from stable laser cavities. Therefore, their spatial structure is limited by the intracavity mode formation. We show that several types of anamorphic optical systems (AOSs) can be effectively employed to shape laser beams into a variety of propagation invariant structured fields with different shapes and phase distributions. We present a propagation matrix approach for designing AOSs and defining mode-matching conditions required for preserving propagation invariance of the output shaped fields. The propagation matrix approach was selected, as it provides a more straightforward approach in designing AOSs for shaping propagation-invariant laser beams than the alternative technique based on the Gouy phase evolution, especially in the case of multielement AOSs. Several practical configurations of optical systems that are suitable for shaping input laser beams into a diverse variety of structured propagation invariant laser beams are also presented. The laser beam shaping approach was applied by modeling propagation characteristics of several input laser beam types, including Hermite-Gaussian, Laguerre-Gaussian, and Ince-Gaussian structured field distributions. The influence of the Ince-Gaussian beam semifocal separation parameter and the azimuthal orientation between the input laser beams and the AOSs onto the resulting shape of the propagation invariant laser beams is presented as well.

A scale-invariant keypoint detector in log-polar space

NASA Astrophysics Data System (ADS)

Tao, Tao; Zhang, Yun

2017-02-01

The scale-invariant feature transform (SIFT) algorithm is devised to detect keypoints via the difference of Gaussian (DoG) images. However, the DoG data lacks the high-frequency information, which can lead to a performance drop of the algorithm. To address this issue, this paper proposes a novel log-polar feature detector (LPFD) to detect scale-invariant blubs (keypoints) in log-polar space, which, in contrast, can retain all the image information. The algorithm consists of three components, viz. keypoint detection, descriptor extraction and descriptor matching. Besides, the algorithm is evaluated in detecting keypoints from the INRIA dataset by comparing with the SIFT algorithm and one of its fast versions, the speed up robust features (SURF) algorithm in terms of three performance measures, viz. correspondences, repeatability, correct matches and matching score.

On the use of INS to improve Feature Matching

NASA Astrophysics Data System (ADS)

Masiero, A.; Guarnieri, A.; Vettore, A.; Pirotti, F.

2014-11-01

The continuous technological improvement of mobile devices opens the frontiers of Mobile Mapping systems to very compact systems, i.e. a smartphone or a tablet. This motivates the development of efficient 3D reconstruction techniques based on the sensors typically embedded in such devices, i.e. imaging sensors, GPS and Inertial Navigation System (INS). Such methods usually exploits photogrammetry techniques (structure from motion) to provide an estimation of the geometry of the scene. Actually, 3D reconstruction techniques (e.g. structure from motion) rely on use of features properly matched in different images to compute the 3D positions of objects by means of triangulation. Hence, correct feature matching is of fundamental importance to ensure good quality 3D reconstructions. Matching methods are based on the appearance of features, that can change as a consequence of variations of camera position and orientation, and environment illumination. For this reason, several methods have been developed in recent years in order to provide feature descriptors robust (ideally invariant) to such variations, e.g. Scale-Invariant Feature Transform (SIFT), Affine SIFT, Hessian affine and Harris affine detectors, Maximally Stable Extremal Regions (MSER). This work deals with the integration of information provided by the INS in the feature matching procedure: a previously developed navigation algorithm is used to constantly estimate the device position and orientation. Then, such information is exploited to estimate the transformation of feature regions between two camera views. This allows to compare regions from different images but associated to the same feature as seen by the same point of view, hence significantly easing the comparison of feature characteristics and, consequently, improving matching. SIFT-like descriptors are used in order to ensure good matching results in presence of illumination variations and to compensate the approximations related to the estimation

Revisiting the Scale-Invariant, Two-Dimensional Linear Regression Method

ERIC Educational Resources Information Center

Patzer, A. Beate C.; Bauer, Hans; Chang, Christian; Bolte, Jan; Su¨lzle, Detlev

2018-01-01

The scale-invariant way to analyze two-dimensional experimental and theoretical data with statistical errors in both the independent and dependent variables is revisited by using what we call the triangular linear regression method. This is compared to the standard least-squares fit approach by applying it to typical simple sets of example data…

MatchingLand, geospatial data testbed for the assessment of matching methods.

PubMed

Xavier, Emerson M A; Ariza-López, Francisco J; Ureña-Cámara, Manuel A

2017-12-05

This article presents datasets prepared with the aim of helping the evaluation of geospatial matching methods for vector data. These datasets were built up from mapping data produced by official Spanish mapping agencies. The testbed supplied encompasses the three geometry types: point, line and area. Initial datasets were submitted to geometric transformations in order to generate synthetic datasets. These transformations represent factors that might influence the performance of geospatial matching methods, like the morphology of linear or areal features, systematic transformations, and random disturbance over initial data. We call our 11 GiB benchmark data 'MatchingLand' and we hope it can be useful for the geographic information science research community.

A Coarse-to-Fine Geometric Scale-Invariant Feature Transform for Large Size High Resolution Satellite Image Registration

PubMed Central

Chang, Xueli; Du, Siliang; Li, Yingying; Fang, Shenghui

2018-01-01

Large size high resolution (HR) satellite image matching is a challenging task due to local distortion, repetitive structures, intensity changes and low efficiency. In this paper, a novel matching approach is proposed for the large size HR satellite image registration, which is based on coarse-to-fine strategy and geometric scale-invariant feature transform (SIFT). In the coarse matching step, a robust matching method scale restrict (SR) SIFT is implemented at low resolution level. The matching results provide geometric constraints which are then used to guide block division and geometric SIFT in the fine matching step. The block matching method can overcome the memory problem. In geometric SIFT, with area constraints, it is beneficial for validating the candidate matches and decreasing searching complexity. To further improve the matching efficiency, the proposed matching method is parallelized using OpenMP. Finally, the sensing image is rectified to the coordinate of reference image via Triangulated Irregular Network (TIN) transformation. Experiments are designed to test the performance of the proposed matching method. The experimental results show that the proposed method can decrease the matching time and increase the number of matching points while maintaining high registration accuracy. PMID:29702589

Gauge-free cluster variational method by maximal messages and moment matching.

PubMed

Domínguez, Eduardo; Lage-Castellanos, Alejandro; Mulet, Roberto; Ricci-Tersenghi, Federico

2017-04-01

We present an implementation of the cluster variational method (CVM) as a message passing algorithm. The kind of message passing algorithm used for CVM, usually named generalized belief propagation (GBP), is a generalization of the belief propagation algorithm in the same way that CVM is a generalization of the Bethe approximation for estimating the partition function. However, the connection between fixed points of GBP and the extremal points of the CVM free energy is usually not a one-to-one correspondence because of the existence of a gauge transformation involving the GBP messages. Our contribution is twofold. First, we propose a way of defining messages (fields) in a generic CVM approximation, such that messages arrive on a given region from all its ancestors, and not only from its direct parents, as in the standard parent-to-child GBP. We call this approach maximal messages. Second, we focus on the case of binary variables, reinterpreting the messages as fields enforcing the consistency between the moments of the local (marginal) probability distributions. We provide a precise rule to enforce all consistencies, avoiding any redundancy, that would otherwise lead to a gauge transformation on the messages. This moment matching method is gauge free, i.e., it guarantees that the resulting GBP is not gauge invariant. We apply our maximal messages and moment matching GBP to obtain an analytical expression for the critical temperature of the Ising model in general dimensions at the level of plaquette CVM. The values obtained outperform Bethe estimates, and are comparable with loop corrected belief propagation equations. The method allows for a straightforward generalization to disordered systems.

Gauge-free cluster variational method by maximal messages and moment matching

NASA Astrophysics Data System (ADS)

Domínguez, Eduardo; Lage-Castellanos, Alejandro; Mulet, Roberto; Ricci-Tersenghi, Federico

2017-04-01

We present an implementation of the cluster variational method (CVM) as a message passing algorithm. The kind of message passing algorithm used for CVM, usually named generalized belief propagation (GBP), is a generalization of the belief propagation algorithm in the same way that CVM is a generalization of the Bethe approximation for estimating the partition function. However, the connection between fixed points of GBP and the extremal points of the CVM free energy is usually not a one-to-one correspondence because of the existence of a gauge transformation involving the GBP messages. Our contribution is twofold. First, we propose a way of defining messages (fields) in a generic CVM approximation, such that messages arrive on a given region from all its ancestors, and not only from its direct parents, as in the standard parent-to-child GBP. We call this approach maximal messages. Second, we focus on the case of binary variables, reinterpreting the messages as fields enforcing the consistency between the moments of the local (marginal) probability distributions. We provide a precise rule to enforce all consistencies, avoiding any redundancy, that would otherwise lead to a gauge transformation on the messages. This moment matching method is gauge free, i.e., it guarantees that the resulting GBP is not gauge invariant. We apply our maximal messages and moment matching GBP to obtain an analytical expression for the critical temperature of the Ising model in general dimensions at the level of plaquette CVM. The values obtained outperform Bethe estimates, and are comparable with loop corrected belief propagation equations. The method allows for a straightforward generalization to disordered systems.

Learning Rotation-Invariant Local Binary Descriptor.

PubMed

Duan, Yueqi; Lu, Jiwen; Feng, Jianjiang; Zhou, Jie

2017-08-01

In this paper, we propose a rotation-invariant local binary descriptor (RI-LBD) learning method for visual recognition. Compared with hand-crafted local binary descriptors, such as local binary pattern and its variants, which require strong prior knowledge, local binary feature learning methods are more efficient and data-adaptive. Unlike existing learning-based local binary descriptors, such as compact binary face descriptor and simultaneous local binary feature learning and encoding, which are susceptible to rotations, our RI-LBD first categorizes each local patch into a rotational binary pattern (RBP), and then jointly learns the orientation for each pattern and the projection matrix to obtain RI-LBDs. As all the rotation variants of a patch belong to the same RBP, they are rotated into the same orientation and projected into the same binary descriptor. Then, we construct a codebook by a clustering method on the learned binary codes, and obtain a histogram feature for each image as the final representation. In order to exploit higher order statistical information, we extend our RI-LBD to the triple rotation-invariant co-occurrence local binary descriptor (TRICo-LBD) learning method, which learns a triple co-occurrence binary code for each local patch. Extensive experimental results on four different visual recognition tasks, including image patch matching, texture classification, face recognition, and scene classification, show that our RI-LBD and TRICo-LBD outperform most existing local descriptors.

Are face representations depth cue invariant?

PubMed

Dehmoobadsharifabadi, Armita; Farivar, Reza

2016-06-01

The visual system can process three-dimensional depth cues defining surfaces of objects, but it is unclear whether such information contributes to complex object recognition, including face recognition. The processing of different depth cues involves both dorsal and ventral visual pathways. We investigated whether facial surfaces defined by individual depth cues resulted in meaningful face representations-representations that maintain the relationship between the population of faces as defined in a multidimensional face space. We measured face identity aftereffects for facial surfaces defined by individual depth cues (Experiments 1 and 2) and tested whether the aftereffect transfers across depth cues (Experiments 3 and 4). Facial surfaces and their morphs to the average face were defined purely by one of shading, texture, motion, or binocular disparity. We obtained identification thresholds for matched (matched identity between adapting and test stimuli), non-matched (non-matched identity between adapting and test stimuli), and no-adaptation (showing only the test stimuli) conditions for each cue and across different depth cues. We found robust face identity aftereffect in both experiments. Our results suggest that depth cues do contribute to forming meaningful face representations that are depth cue invariant. Depth cue invariance would require integration of information across different areas and different pathways for object recognition, and this in turn has important implications for cortical models of visual object recognition.

New Matching Method for Accelerometers in Gravity Gradiometer

PubMed Central

Wei, Hongwei; Wu, Meiping; Cao, Juliang

2017-01-01

The gravity gradiometer is widely used in mineral prospecting, including in the exploration of mineral, oil and gas deposits. The mismatch of accelerometers adversely affects the measuring precision of rotating accelerometer-based gravity gradiometers. Several strategies have been investigated to address the imbalance of accelerometers in gradiometers. These strategies, however, complicate gradiometer structures because feedback loops and re-designed accelerometers are needed in these strategies. In this paper, we present a novel matching method, which is based on a new configuration of accelerometers in a gravity gradiometer. In the new configuration, an angle was introduced between the measurement direction of the accelerometer and the spin direction. With the introduced angle, accelerometers could measure the centrifugal acceleration generated by the rotating disc. Matching was realized by updating the scale factors of the accelerometers with the help of centrifugal acceleration. Further simulation computations showed that after adopting the new matching method, signal-to-noise ratio improved from −41 dB to 22 dB. Compared with other matching methods, our method is more flexible and costs less. The matching accuracy of this new method is similar to that of other methods. Our method provides a new idea for matching methods in gravity gradiometer measurement. PMID:28757584

Wide baseline stereo matching based on double topological relationship consistency

NASA Astrophysics Data System (ADS)

Zou, Xiaohong; Liu, Bin; Song, Xiaoxue; Liu, Yang

2009-07-01

Stereo matching is one of the most important branches in computer vision. In this paper, an algorithm is proposed for wide-baseline stereo vision matching. Here, a novel scheme is presented called double topological relationship consistency (DCTR). The combination of double topological configuration includes the consistency of first topological relationship (CFTR) and the consistency of second topological relationship (CSTR). It not only sets up a more advanced model on matching, but discards mismatches by iteratively computing the fitness of the feature matches and overcomes many problems of traditional methods depending on the powerful invariance to changes in the scale, rotation or illumination across large view changes and even occlusions. Experimental examples are shown where the two cameras have been located in very different orientations. Also, epipolar geometry can be recovered using RANSAC by far the most widely method adopted possibly. By the method, we can obtain correspondences with high precision on wide baseline matching problems. Finally, the effectiveness and reliability of this method are demonstrated in wide-baseline experiments on the image pairs.

Selection method of terrain matching area for TERCOM algorithm

NASA Astrophysics Data System (ADS)

Zhang, Qieqie; Zhao, Long

2017-10-01

The performance of terrain aided navigation is closely related to the selection of terrain matching area. The different matching algorithms have different adaptability to terrain. This paper mainly studies the adaptability to terrain of TERCOM algorithm, analyze the relation between terrain feature and terrain characteristic parameters by qualitative and quantitative methods, and then research the relation between matching probability and terrain characteristic parameters by the Monte Carlo method. After that, we propose a selection method of terrain matching area for TERCOM algorithm, and verify the method correctness with real terrain data by simulation experiment. Experimental results show that the matching area obtained by the method in this paper has the good navigation performance and the matching probability of TERCOM algorithm is great than 90%

Negative electric susceptibility and magnetism from translational invariance and rotational invariance

NASA Astrophysics Data System (ADS)

Koo, Je Huan

2015-02-01

In this work we investigate magnetic effects in terms of the translational and rotational invariances of magnetisation. Whilst Landau-type diamagnetism originates from translational invariance, a new diamagnetism could result from rotational invariance. Translational invariance results in only conventional Landau-type diamagnetism, whereas rotational invariance can induce a paramagnetic susceptibility for localised electrons and also a new kind of diamagnetism that is specific to conducting electrons. In solids, the moving electron shows a paramagnetic susceptibility but the surrounding screening of electrons may produce a new diamagnetic response by Lenz's law, resulting in a total susceptibility that tends to zero. For electricity, similar behaviours are obtained. We also derive the DC-type negative electric susceptibility via two methods in analogy with Landau diamagnetism.

View-invariant gait recognition method by three-dimensional convolutional neural network

NASA Astrophysics Data System (ADS)

Xing, Weiwei; Li, Ying; Zhang, Shunli

2018-01-01

Gait as an important biometric feature can identify a human at a long distance. View change is one of the most challenging factors for gait recognition. To address the cross view issues in gait recognition, we propose a view-invariant gait recognition method by three-dimensional (3-D) convolutional neural network. First, 3-D convolutional neural network (3DCNN) is introduced to learn view-invariant feature, which can capture the spatial information and temporal information simultaneously on normalized silhouette sequences. Second, a network training method based on cross-domain transfer learning is proposed to solve the problem of the limited gait training samples. We choose the C3D as the basic model, which is pretrained on the Sports-1M and then fine-tune C3D model to adapt gait recognition. In the recognition stage, we use the fine-tuned model to extract gait features and use Euclidean distance to measure the similarity of gait sequences. Sufficient experiments are carried out on the CASIA-B dataset and the experimental results demonstrate that our method outperforms many other methods.

Scale invariant texture descriptors for classifying celiac disease

PubMed Central

Hegenbart, Sebastian; Uhl, Andreas; Vécsei, Andreas; Wimmer, Georg

2013-01-01

Scale invariant texture recognition methods are applied for the computer assisted diagnosis of celiac disease. In particular, emphasis is given to techniques enhancing the scale invariance of multi-scale and multi-orientation wavelet transforms and methods based on fractal analysis. After fine-tuning to specific properties of our celiac disease imagery database, which consists of endoscopic images of the duodenum, some scale invariant (and often even viewpoint invariant) methods provide classification results improving the current state of the art. However, not each of the investigated scale invariant methods is applicable successfully to our dataset. Therefore, the scale invariance of the employed approaches is explicitly assessed and it is found that many of the analyzed methods are not as scale invariant as they theoretically should be. Results imply that scale invariance is not a key-feature required for successful classification of our celiac disease dataset. PMID:23481171

Two-loop matching factors for light quark masses and three-loop mass anomalous dimensions in the regularization invariant symmetric momentum-subtraction schemes

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

Almeida, Leandro G.; Physics Department, Brookhaven National Laboratory, Upton, New York 11973; Sturm, Christian

2010-09-01

Light quark masses can be determined through lattice simulations in regularization invariant momentum-subtraction (RI/MOM) schemes. Subsequently, matching factors, computed in continuum perturbation theory, are used in order to convert these quark masses from a RI/MOM scheme to the MS scheme. We calculate the two-loop corrections in QCD to these matching factors as well as the three-loop mass anomalous dimensions for the RI/SMOM and RI/SMOM{sub {gamma}{sub {mu}} }schemes. These two schemes are characterized by a symmetric subtraction point. Providing the conversion factors in the two different schemes allows for a better understanding of the systematic uncertainties. The two-loop expansion coefficients ofmore » the matching factors for both schemes turn out to be small compared to the traditional RI/MOM schemes. For n{sub f}=3 quark flavors they are about 0.6%-0.7% and 2%, respectively, of the leading order result at scales of about 2 GeV. Therefore, they will allow for a significant reduction of the systematic uncertainty of light quark mass determinations obtained through this approach. The determination of these matching factors requires the computation of amputated Green's functions with the insertions of quark bilinear operators. As a by-product of our calculation we also provide the corresponding results for the tensor operator.« less

Invariant recognition drives neural representations of action sequences

PubMed Central

Poggio, Tomaso

2017-01-01

Recognizing the actions of others from visual stimuli is a crucial aspect of human perception that allows individuals to respond to social cues. Humans are able to discriminate between similar actions despite transformations, like changes in viewpoint or actor, that substantially alter the visual appearance of a scene. This ability to generalize across complex transformations is a hallmark of human visual intelligence. Advances in understanding action recognition at the neural level have not always translated into precise accounts of the computational principles underlying what representations of action sequences are constructed by human visual cortex. Here we test the hypothesis that invariant action discrimination might fill this gap. Recently, the study of artificial systems for static object perception has produced models, Convolutional Neural Networks (CNNs), that achieve human level performance in complex discriminative tasks. Within this class, architectures that better support invariant object recognition also produce image representations that better match those implied by human and primate neural data. However, whether these models produce representations of action sequences that support recognition across complex transformations and closely follow neural representations of actions remains unknown. Here we show that spatiotemporal CNNs accurately categorize video stimuli into action classes, and that deliberate model modifications that improve performance on an invariant action recognition task lead to data representations that better match human neural recordings. Our results support our hypothesis that performance on invariant discrimination dictates the neural representations of actions computed in the brain. These results broaden the scope of the invariant recognition framework for understanding visual intelligence from perception of inanimate objects and faces in static images to the study of human perception of action sequences. PMID:29253864

A geometrical defect detection method for non-silicon MEMS part based on HU moment invariants of skeleton image

NASA Astrophysics Data System (ADS)

Cheng, Xu; Jin, Xin; Zhang, Zhijing; Lu, Jun

2014-01-01

In order to improve the accuracy of geometrical defect detection, this paper presented a method based on HU moment invariants of skeleton image. This method have four steps: first of all, grayscale images of non-silicon MEMS parts are collected and converted into binary images, secondly, skeletons of binary images are extracted using medialaxis- transform method, and then HU moment invariants of skeleton images are calculated, finally, differences of HU moment invariants between measured parts and qualified parts are obtained to determine whether there are geometrical defects. To demonstrate the availability of this method, experiments were carried out between skeleton images and grayscale images, and results show that: when defects of non-silicon MEMS part are the same, HU moment invariants of skeleton images are more sensitive than that of grayscale images, and detection accuracy is higher. Therefore, this method can more accurately determine whether non-silicon MEMS parts qualified or not, and can be applied to nonsilicon MEMS part detection system.

Deformation Invariant Attribute Vector for Deformable Registration of Longitudinal Brain MR Images

PubMed Central

Li, Gang; Guo, Lei; Liu, Tianming

2009-01-01

This paper presents a novel approach to define deformation invariant attribute vector (DIAV) for each voxel in 3D brain image for the purpose of anatomic correspondence detection. The DIAV method is validated by using synthesized deformation in 3D brain MRI images. Both theoretic analysis and experimental studies demonstrate that the proposed DIAV is invariant to general nonlinear deformation. Moreover, our experimental results show that the DIAV is able to capture rich anatomic information around the voxels and exhibit strong discriminative ability. The DIAV has been integrated into a deformable registration algorithm for longitudinal brain MR images, and the results on both simulated and real brain images are provided to demonstrate the good performance of the proposed registration algorithm based on matching of DIAVs. PMID:19369031

Tests of Measurement Invariance without Subgroups: A Generalization of Classical Methods

ERIC Educational Resources Information Center

Merkle, Edgar C.; Zeileis, Achim

2013-01-01

The issue of measurement invariance commonly arises in factor-analytic contexts, with methods for assessment including likelihood ratio tests, Lagrange multiplier tests, and Wald tests. These tests all require advance definition of the number of groups, group membership, and offending model parameters. In this paper, we study tests of measurement…

Effect of silhouetting and inversion on view invariance in the monkey inferotemporal cortex

PubMed Central

2017-01-01

We effortlessly recognize objects across changes in viewpoint, but we know relatively little about the features that underlie viewpoint invariance in the brain. Here, we set out to characterize how viewpoint invariance in monkey inferior temporal (IT) neurons is influenced by two image manipulations—silhouetting and inversion. Reducing an object into its silhouette removes internal detail, so this would reveal how much viewpoint invariance depends on the external contours. Inverting an object retains but rearranges features, so this would reveal how much viewpoint invariance depends on the arrangement and orientation of features. Our main findings are 1) view invariance is weakened by silhouetting but not by inversion; 2) view invariance was stronger in neurons that generalized across silhouetting and inversion; 3) neuronal responses to natural objects matched early with that of silhouettes and only later to that of inverted objects, indicative of coarse-to-fine processing; and 4) the impact of silhouetting and inversion depended on object structure. Taken together, our results elucidate the underlying features and dynamics of view-invariant object representations in the brain. NEW & NOTEWORTHY We easily recognize objects across changes in viewpoint, but the underlying features are unknown. Here, we show that view invariance in the monkey inferotemporal cortex is driven mainly by external object contours and is not specialized for object orientation. We also find that the responses to natural objects match with that of their silhouettes early in the response, and with inverted versions later in the response—indicative of a coarse-to-fine processing sequence in the brain. PMID:28381484

Effect of silhouetting and inversion on view invariance in the monkey inferotemporal cortex.

PubMed

Ratan Murty, N Apurva; Arun, S P

2017-07-01

We effortlessly recognize objects across changes in viewpoint, but we know relatively little about the features that underlie viewpoint invariance in the brain. Here, we set out to characterize how viewpoint invariance in monkey inferior temporal (IT) neurons is influenced by two image manipulations-silhouetting and inversion. Reducing an object into its silhouette removes internal detail, so this would reveal how much viewpoint invariance depends on the external contours. Inverting an object retains but rearranges features, so this would reveal how much viewpoint invariance depends on the arrangement and orientation of features. Our main findings are 1 ) view invariance is weakened by silhouetting but not by inversion; 2 ) view invariance was stronger in neurons that generalized across silhouetting and inversion; 3 ) neuronal responses to natural objects matched early with that of silhouettes and only later to that of inverted objects, indicative of coarse-to-fine processing; and 4 ) the impact of silhouetting and inversion depended on object structure. Taken together, our results elucidate the underlying features and dynamics of view-invariant object representations in the brain. NEW & NOTEWORTHY We easily recognize objects across changes in viewpoint, but the underlying features are unknown. Here, we show that view invariance in the monkey inferotemporal cortex is driven mainly by external object contours and is not specialized for object orientation. We also find that the responses to natural objects match with that of their silhouettes early in the response, and with inverted versions later in the response-indicative of a coarse-to-fine processing sequence in the brain. Copyright © 2017 the American Physiological Society.

A Method for Matching Leadership Mentors and Proteges.

ERIC Educational Resources Information Center

Daresh, John C.; Playko, Marsha A.

A method for matching leadership mentors with beginning teachers is described in this paper, with emphasis on personality types and psychosocial characteristics. A review of literature on guide matching concludes that research is inconclusive and that matching is often based on availability. Five fundamental assumptions of the personnel matching…

A novel scheme for automatic nonrigid image registration using deformation invariant feature and geometric constraint

NASA Astrophysics Data System (ADS)

Deng, Zhipeng; Lei, Lin; Zhou, Shilin

2015-10-01

Automatic image registration is a vital yet challenging task, particularly for non-rigid deformation images which are more complicated and common in remote sensing images, such as distorted UAV (unmanned aerial vehicle) images or scanning imaging images caused by flutter. Traditional non-rigid image registration methods are based on the correctly matched corresponding landmarks, which usually needs artificial markers. It is a rather challenging task to locate the accurate position of the points and get accurate homonymy point sets. In this paper, we proposed an automatic non-rigid image registration algorithm which mainly consists of three steps: To begin with, we introduce an automatic feature point extraction method based on non-linear scale space and uniform distribution strategy to extract the points which are uniform distributed along the edge of the image. Next, we propose a hybrid point matching algorithm using DaLI (Deformation and Light Invariant) descriptor and local affine invariant geometric constraint based on triangulation which is constructed by K-nearest neighbor algorithm. Based on the accurate homonymy point sets, the two images are registrated by the model of TPS (Thin Plate Spline). Our method is demonstrated by three deliberately designed experiments. The first two experiments are designed to evaluate the distribution of point set and the correctly matching rate on synthetic data and real data respectively. The last experiment is designed on the non-rigid deformation remote sensing images and the three experimental results demonstrate the accuracy, robustness, and efficiency of the proposed algorithm compared with other traditional methods.

Fully Numerical Methods for Continuing Families of Quasi-Periodic Invariant Tori in Astrodynamics

NASA Astrophysics Data System (ADS)

Baresi, Nicola; Olikara, Zubin P.; Scheeres, Daniel J.

2018-06-01

Quasi-periodic invariant tori are of great interest in astrodynamics because of their capability to further expand the design space of satellite missions. However, there is no general consent on what is the best methodology for computing these dynamical structures. This paper compares the performance of four different approaches available in the literature. The first two methods compute invariant tori of flows by solving a system of partial differential equations via either central differences or Fourier techniques. In contrast, the other two strategies calculate invariant curves of maps via shooting algorithms: one using surfaces of section, and one using a stroboscopic map. All of the numerical procedures are tested in the co-rotating frame of the Earth as well as in the planar circular restricted three-body problem. The results of our numerical simulations show which of the reviewed procedures should be preferred for future studies of astrodynamics systems.

Fully Numerical Methods for Continuing Families of Quasi-Periodic Invariant Tori in Astrodynamics

NASA Astrophysics Data System (ADS)

Baresi, Nicola; Olikara, Zubin P.; Scheeres, Daniel J.

2018-01-01

Quasi-periodic invariant tori are of great interest in astrodynamics because of their capability to further expand the design space of satellite missions. However, there is no general consent on what is the best methodology for computing these dynamical structures. This paper compares the performance of four different approaches available in the literature. The first two methods compute invariant tori of flows by solving a system of partial differential equations via either central differences or Fourier techniques. In contrast, the other two strategies calculate invariant curves of maps via shooting algorithms: one using surfaces of section, and one using a stroboscopic map. All of the numerical procedures are tested in the co-rotating frame of the Earth as well as in the planar circular restricted three-body problem. The results of our numerical simulations show which of the reviewed procedures should be preferred for future studies of astrodynamics systems.

Static analysis of class invariants in Java programs

NASA Astrophysics Data System (ADS)

Bonilla-Quintero, Lidia Dionisia

2011-12-01

This paper presents a technique for the automatic inference of class invariants from Java bytecode. Class invariants are very important for both compiler optimization and as an aid to programmers in their efforts to reduce the number of software defects. We present the original DC-invariant analysis from Adam Webber, talk about its shortcomings and suggest several different ways to improve it. To apply the DC-invariant analysis to identify DC-invariant assertions, all that one needs is a monotonic method analysis function and a suitable assertion domain. The DC-invariant algorithm is very general; however, the method analysis can be highly tuned to the problem in hand. For example, one could choose shape analysis as the method analysis function and use the DC-invariant analysis to simply extend it to an analysis that would yield class-wide invariants describing the shapes of linked data structures. We have a prototype implementation: a system we refer to as "the analyzer" that infers DC-invariant unary and binary relations and provides them to the user in a human readable format. The analyzer uses those relations to identify unnecessary array bounds checks in Java programs and perform null-reference analysis. It uses Adam Webber's relational constraint technique for the class-invariant binary relations. Early results with the analyzer were very imprecise in the presence of "dirty-called" methods. A dirty-called method is one that is called, either directly or transitively, from any constructor of the class, or from any method of the class at a point at which a disciplined field has been altered. This result was unexpected and forced an extensive search for improved techniques. An important contribution of this paper is the suggestion of several ways to improve the results by changing the way dirty-called methods are handled. The new techniques expand the set of class invariants that can be inferred over Webber's original results. The technique that produces better

Evaluation of subset matching methods and forms of covariate balance.

PubMed

de Los Angeles Resa, María; Zubizarreta, José R

2016-11-30

This paper conducts a Monte Carlo simulation study to evaluate the performance of multivariate matching methods that select a subset of treatment and control observations. The matching methods studied are the widely used nearest neighbor matching with propensity score calipers and the more recently proposed methods, optimal matching of an optimally chosen subset and optimal cardinality matching. The main findings are: (i) covariate balance, as measured by differences in means, variance ratios, Kolmogorov-Smirnov distances, and cross-match test statistics, is better with cardinality matching because by construction it satisfies balance requirements; (ii) for given levels of covariate balance, the matched samples are larger with cardinality matching than with the other methods; (iii) in terms of covariate distances, optimal subset matching performs best; (iv) treatment effect estimates from cardinality matching have lower root-mean-square errors, provided strong requirements for balance, specifically, fine balance, or strength-k balance, plus close mean balance. In standard practice, a matched sample is considered to be balanced if the absolute differences in means of the covariates across treatment groups are smaller than 0.1 standard deviations. However, the simulation results suggest that stronger forms of balance should be pursued in order to remove systematic biases due to observed covariates when a difference in means treatment effect estimator is used. In particular, if the true outcome model is additive, then marginal distributions should be balanced, and if the true outcome model is additive with interactions, then low-dimensional joints should be balanced. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Illumination Invariant Change Detection (iicd): from Earth to Mars

NASA Astrophysics Data System (ADS)

Wan, X.; Liu, J.; Qin, M.; Li, S. Y.

2018-04-01

Multi-temporal Earth Observation and Mars orbital imagery data with frequent repeat coverage provide great capability for planetary surface change detection. When comparing two images taken at different times of day or in different seasons for change detection, the variation of topographic shades and shadows caused by the change of sunlight angle can be so significant that it overwhelms the real object and environmental changes, making automatic detection unreliable. An effective change detection algorithm therefore has to be robust to the illumination variation. This paper presents our research on developing and testing an Illumination Invariant Change Detection (IICD) method based on the robustness of phase correlation (PC) to the variation of solar illumination for image matching. The IICD is based on two key functions: i) initial change detection based on a saliency map derived from pixel-wise dense PC matching and ii) change quantization which combines change type identification, motion estimation and precise appearance change identification. Experiment using multi-temporal Landsat 7 ETM+ satellite images, Rapid eye satellite images and Mars HiRiSE images demonstrate that our frequency based image matching method can reach sub-pixel accuracy and thus the proposed IICD method can effectively detect and precisely segment large scale change such as landslide as well as small object change such as Mars rover, under daily and seasonal sunlight changes.

A Robust False Matching Points Detection Method for Remote Sensing Image Registration

NASA Astrophysics Data System (ADS)

Shan, X. J.; Tang, P.

2015-04-01

Given the influences of illumination, imaging angle, and geometric distortion, among others, false matching points still occur in all image registration algorithms. Therefore, false matching points detection is an important step in remote sensing image registration. Random Sample Consensus (RANSAC) is typically used to detect false matching points. However, RANSAC method cannot detect all false matching points in some remote sensing images. Therefore, a robust false matching points detection method based on Knearest- neighbour (K-NN) graph (KGD) is proposed in this method to obtain robust and high accuracy result. The KGD method starts with the construction of the K-NN graph in one image. K-NN graph can be first generated for each matching points and its K nearest matching points. Local transformation model for each matching point is then obtained by using its K nearest matching points. The error of each matching point is computed by using its transformation model. Last, L matching points with largest error are identified false matching points and removed. This process is iterative until all errors are smaller than the given threshold. In addition, KGD method can be used in combination with other methods, such as RANSAC. Several remote sensing images with different resolutions and terrains are used in the experiment. We evaluate the performance of KGD method, RANSAC + KGD method, RANSAC, and Graph Transformation Matching (GTM). The experimental results demonstrate the superior performance of the KGD and RANSAC + KGD methods.

Evaluation of the Match External Load in Soccer: Methods Comparison.

PubMed

Castagna, Carlo; Varley, Matthew; Póvoas, Susana C A; D'Ottavio, Stefano

2017-04-01

To test the interchangeability of 2 match-analysis approaches for external-load detection considering arbitrary selected speeds and metabolic power (MP) thresholds in male top-level soccer. Data analyses were performed considering match physical performance of 60 matches (1200 player cases) of randomly selected Spanish, German, and English first-division championship matches (2013-14 season). Match analysis was performed with a validated semiautomated multicamera system operating at 25 Hz. During a match, players covered 10,673 ± 348 m, of which 1778 ± 208 m and 2759 ± 241 m were performed at high intensity, as measured using speed (≥16 km/h, HI) and metabolic power (≥20 W/kg, MPHI) notations. High-intensity notations were nearly perfectly associated (r = .93, P < .0001). A huge method bias (980.63 ± 87.82 m, d = 11.67) was found when considering MPHI and HI. Very large correlations were found between match total distance covered and MPHI (r = .84, P < .0001) and HI (r = .74, P < .0001). Player high-intensity decelerations (≥-2 m/s 2 ) were very largely associated with MPHI (r = .73, P < .0001). The speed and MP methods are highly interchangeable at relative level (magnitude rank) but not absolute level (measure magnitude). The 2 physical match-analysis methods can be independently used to track match external load in elite-level players. However, match-analyst decisions must be based on use of a single method to avoid bias in external-load determination.

Electrosensory Midbrain Neurons Display Feature Invariant Responses to Natural Communication Stimuli.

PubMed

Aumentado-Armstrong, Tristan; Metzen, Michael G; Sproule, Michael K J; Chacron, Maurice J

2015-10-01

Neurons that respond selectively but in an invariant manner to a given feature of natural stimuli have been observed across species and systems. Such responses emerge in higher brain areas, thereby suggesting that they occur by integrating afferent input. However, the mechanisms by which such integration occurs are poorly understood. Here we show that midbrain electrosensory neurons can respond selectively and in an invariant manner to heterogeneity in behaviorally relevant stimulus waveforms. Such invariant responses were not seen in hindbrain electrosensory neurons providing afferent input to these midbrain neurons, suggesting that response invariance results from nonlinear integration of such input. To test this hypothesis, we built a model based on the Hodgkin-Huxley formalism that received realistic afferent input. We found that multiple combinations of parameter values could give rise to invariant responses matching those seen experimentally. Our model thus shows that there are multiple solutions towards achieving invariant responses and reveals how subthreshold membrane conductances help promote robust and invariant firing in response to heterogeneous stimulus waveforms associated with behaviorally relevant stimuli. We discuss the implications of our findings for the electrosensory and other systems.

Cartan invariants and event horizon detection

NASA Astrophysics Data System (ADS)

Brooks, D.; Chavy-Waddy, P. C.; Coley, A. A.; Forget, A.; Gregoris, D.; MacCallum, M. A. H.; McNutt, D. D.

2018-04-01

We show that it is possible to locate the event horizon of a black hole (in arbitrary dimensions) by the zeros of certain Cartan invariants. This approach accounts for the recent results on the detection of stationary horizons using scalar polynomial curvature invariants, and improves upon them since the proposed method is computationally less expensive. As an application, we produce Cartan invariants that locate the event horizons for various exact four-dimensional and five-dimensional stationary, asymptotically flat (or (anti) de Sitter), black hole solutions and compare the Cartan invariants with the corresponding scalar curvature invariants that detect the event horizon.

Scale invariance in biophysics

NASA Astrophysics Data System (ADS)

Stanley, H. Eugene

2000-06-01

In this general talk, we offer an overview of some problems of interest to biophysicists, medical physicists, and econophysicists. These include DNA sequences, brain plaques in Alzheimer patients, heartbeat intervals, and time series giving price fluctuations in economics. These problems have the common feature that they exhibit features that appear to be scale invariant. Particularly vexing is the problem that some of these scale invariant phenomena are not stationary-their statistical properties vary from one time interval to the next or form one position to the next. We will discuss methods, such as wavelet methods and multifractal methods, to cope with these problems. .

Hybrid generative-discriminative approach to age-invariant face recognition

NASA Astrophysics Data System (ADS)

Sajid, Muhammad; Shafique, Tamoor

2018-03-01

Age-invariant face recognition is still a challenging research problem due to the complex aging process involving types of facial tissues, skin, fat, muscles, and bones. Most of the related studies that have addressed the aging problem are focused on generative representation (aging simulation) or discriminative representation (feature-based approaches). Designing an appropriate hybrid approach taking into account both the generative and discriminative representations for age-invariant face recognition remains an open problem. We perform a hybrid matching to achieve robustness to aging variations. This approach automatically segments the eyes, nose-bridge, and mouth regions, which are relatively less sensitive to aging variations compared with the rest of the facial regions that are age-sensitive. The aging variations of age-sensitive facial parts are compensated using a demographic-aware generative model based on a bridged denoising autoencoder. The age-insensitive facial parts are represented by pixel average vector-based local binary patterns. Deep convolutional neural networks are used to extract relative features of age-sensitive and age-insensitive facial parts. Finally, the feature vectors of age-sensitive and age-insensitive facial parts are fused to achieve the recognition results. Extensive experimental results on morphological face database II (MORPH II), face and gesture recognition network (FG-NET), and Verification Subset of cross-age celebrity dataset (CACD-VS) demonstrate the effectiveness of the proposed method for age-invariant face recognition well.

Areal Feature Matching Based on Similarity Using Critic Method

NASA Astrophysics Data System (ADS)

Kim, J.; Yu, K.

2015-10-01

In this paper, we propose an areal feature matching method that can be applied for many-to-many matching, which involves matching a simple entity with an aggregate of several polygons or two aggregates of several polygons with fewer user intervention. To this end, an affine transformation is applied to two datasets by using polygon pairs for which the building name is the same. Then, two datasets are overlaid with intersected polygon pairs that are selected as candidate matching pairs. If many polygons intersect at this time, we calculate the inclusion function between such polygons. When the value is more than 0.4, many of the polygons are aggregated as single polygons by using a convex hull. Finally, the shape similarity is calculated between the candidate pairs according to the linear sum of the weights computed in CRITIC method and the position similarity, shape ratio similarity, and overlap similarity. The candidate pairs for which the value of the shape similarity is more than 0.7 are determined as matching pairs. We applied the method to two geospatial datasets: the digital topographic map and the KAIS map in South Korea. As a result, the visual evaluation showed two polygons that had been well detected by using the proposed method. The statistical evaluation indicates that the proposed method is accurate when using our test dataset with a high F-measure of 0.91.

Interferometric measurement method for Z2 invariants of time-reversal invariant topological insulators

NASA Astrophysics Data System (ADS)

Grusdt, Fabian; Abanin, Dmitry; Demler, Eugene

2013-05-01

Recently experiments with ultracold atoms started to explore topological phases in 1D optical lattices. While transport measurements are challenging in these systems, ways to directly measure topological quantum numbers using a combination of Bloch oscillations and Ramsey interferometry have been explored (Atala et al., arXiv:1212.0572). In this talk I will present ways to measure the Z2 topological quantum numbers of two and three dimensional time-reversal invariant (TR) topological insulators. In this case non-Abelian Bloch oscillations can be combined with Ramsey interferometry to map out the topological properties of a given band-structure. Our method is very general and works even in the presence of accidental degeneracies. The applicability of the scheme is discussed for different theoretically proposed implementations of TR topological insulators using ultracold atoms. F. G. is grateful to Harvard University for hospitality and acknowledges financial support from Graduate School Materials Science in Mainz (MAINZ).

Multiscale moment-based technique for object matching and recognition

NASA Astrophysics Data System (ADS)

Thio, HweeLi; Chen, Liya; Teoh, Eam-Khwang

2000-03-01

A new method is proposed to extract features from an object for matching and recognition. The features proposed are a combination of local and global characteristics -- local characteristics from the 1-D signature function that is defined to each pixel on the object boundary, global characteristics from the moments that are generated from the signature function. The boundary of the object is first extracted, then the signature function is generated by computing the angle between two lines from every point on the boundary as a function of position along the boundary. This signature function is position, scale and rotation invariant (PSRI). The shape of the signature function is then described quantitatively by using moments. The moments of the signature function are the global characters of a local feature set. Using moments as the eventual features instead of the signature function reduces the time and complexity of an object matching application. Multiscale moments are implemented to produce several sets of moments that will generate more accurate matching. Basically multiscale technique is a coarse to fine procedure and makes the proposed method more robust to noise. This method is proposed to match and recognize objects under simple transformation, such as translation, scale changes, rotation and skewing. A simple logo indexing system is implemented to illustrate the performance of the proposed method.

Method of electric powertrain matching for battery-powered electric cars

NASA Astrophysics Data System (ADS)

Ning, Guobao; Xiong, Lu; Zhang, Lijun; Yu, Zhuoping

2013-05-01

The current match method of electric powertrain still makes use of longitudinal dynamics, which can't realize maximum capacity for on-board energy storage unit and can't reach lowest equivalent fuel consumption as well. Another match method focuses on improving available space considering reasonable layout of vehicle to enlarge rated energy capacity for on-board energy storage unit, which can keep the longitudinal dynamics performance almost unchanged but can't reach lowest fuel consumption. Considering the characteristics of driving motor, method of electric powertrain matching utilizing conventional longitudinal dynamics for driving system and cut-and-try method for energy storage system is proposed for passenger cars converted from traditional ones. Through combining the utilization of vehicle space which contributes to the on-board energy amount, vehicle longitudinal performance requirements, vehicle equivalent fuel consumption level, passive safety requirements and maximum driving range requirement together, a comprehensive optimal match method of electric powertrain for battery-powered electric vehicle is raised. In simulation, the vehicle model and match method is built in Matlab/simulink, and the Environmental Protection Agency (EPA) Urban Dynamometer Driving Schedule (UDDS) is chosen as a test condition. The simulation results show that 2.62% of regenerative energy and 2% of energy storage efficiency are increased relative to the traditional method. The research conclusions provide theoretical and practical solutions for electric powertrain matching for modern battery-powered electric vehicles especially for those converted from traditional ones, and further enhance dynamics of electric vehicles.

Deformed Palmprint Matching Based on Stable Regions.

PubMed

Wu, Xiangqian; Zhao, Qiushi

2015-12-01

Palmprint recognition (PR) is an effective technology for personal recognition. A main problem, which deteriorates the performance of PR, is the deformations of palmprint images. This problem becomes more severe on contactless occasions, in which images are acquired without any guiding mechanisms, and hence critically limits the applications of PR. To solve the deformation problems, in this paper, a model for non-linearly deformed palmprint matching is derived by approximating non-linear deformed palmprint images with piecewise-linear deformed stable regions. Based on this model, a novel approach for deformed palmprint matching, named key point-based block growing (KPBG), is proposed. In KPBG, an iterative M-estimator sample consensus algorithm based on scale invariant feature transform features is devised to compute piecewise-linear transformations to approximate the non-linear deformations of palmprints, and then, the stable regions complying with the linear transformations are decided using a block growing algorithm. Palmprint feature extraction and matching are performed over these stable regions to compute matching scores for decision. Experiments on several public palmprint databases show that the proposed models and the KPBG approach can effectively solve the deformation problem in palmprint verification and outperform the state-of-the-art methods.

Two methods for measuring Bell nonlocality via local unitary invariants of two-qubit systems in Hong-Ou-Mandel interferometers

NASA Astrophysics Data System (ADS)

Bartkiewicz, Karol; Chimczak, Grzegorz

2018-01-01

We describe a direct method to experimentally determine local two-qubit invariants by performing interferometric measurements on multiple copies of a given two-qubit state. We use this framework to analyze two different kinds of two-qubit invariants of Makhlin and Jing et al. These invariants allow us to fully reconstruct any two-qubit state up to local unitaries. We demonstrate that measuring three invariants is sufficient to find, e.g., the optimal Bell inequality violation. These invariants can be measured with local or nonlocal measurements. We show that the nonlocal strategy that follows from Makhlin's invariants is more resource efficient than local strategy following from the invariants of Jing et al. To measure all of the Makhlin's invariants directly one needs to use both two-qubit singlets and three-qubit W -state projections on multiple copies of the two-qubit state. This problem is equivalent to a coordinate system handedness measurement. We demonstrate that these three-qubit measurements can be performed by utilizing Hong-Ou-Mandel interference, which gives significant speedup in comparison to the classical handedness measurement. Finally, we point to potential applications of our results in quantum secret sharing.

Assessing factorial invariance of two-way rating designs using three-way methods

PubMed Central

Kroonenberg, Pieter M.

2015-01-01

Assessing the factorial invariance of two-way rating designs such as ratings of concepts on several scales by different groups can be carried out with three-way models such as the Parafac and Tucker models. By their definitions these models are double-metric factorially invariant. The differences between these models lie in their handling of the links between the concept and scale spaces. These links may consist of unrestricted linking (Tucker2 model), invariant component covariances but variable variances per group and per component (Parafac model), zero covariances and variances different per group but not per component (Replicated Tucker3 model) and strict invariance (Component analysis on the average matrix). This hierarchy of invariant models, and the procedures by which to evaluate the models against each other, is illustrated in some detail with an international data set from attachment theory. PMID:25620936

Invariant approach to the character classification

NASA Astrophysics Data System (ADS)

Šariri, Kristina; Demoli, Nazif

2008-04-01

Image moments analysis is a very useful tool which allows image description invariant to translation and rotation, scale change and some types of image distortions. The aim of this work was development of simple method for fast and reliable classification of characters by using Hu's and affine moment invariants. Measure of Eucleidean distance was used as a discrimination feature with statistical parameters estimated. The method was tested in classification of Times New Roman font letters as well as sets of the handwritten characters. It is shown that using all Hu's and three affine invariants as discrimination set improves recognition rate by 30%.

A Lyapunov method for stability analysis of piecewise-affine systems over non-invariant domains

NASA Astrophysics Data System (ADS)

Rubagotti, Matteo; Zaccarian, Luca; Bemporad, Alberto

2016-05-01

This paper analyses stability of discrete-time piecewise-affine systems, defined on possibly non-invariant domains, taking into account the possible presence of multiple dynamics in each of the polytopic regions of the system. An algorithm based on linear programming is proposed, in order to prove exponential stability of the origin and to find a positively invariant estimate of its region of attraction. The results are based on the definition of a piecewise-affine Lyapunov function, which is in general discontinuous on the boundaries of the regions. The proposed method is proven to lead to feasible solutions in a broader range of cases as compared to a previously proposed approach. Two numerical examples are shown, among which a case where the proposed method is applied to a closed-loop system, to which model predictive control was applied without a-priori guarantee of stability.

Object-Based Dense Matching Method for Maintaining Structure Characteristics of Linear Buildings

PubMed Central

Yan, Yiming; Qiu, Mingjie; Zhao, Chunhui; Wang, Liguo

2018-01-01

In this paper, we proposed a novel object-based dense matching method specially for the high-precision disparity map of building objects in urban areas, which can maintain accurate object structure characteristics. The proposed framework mainly includes three stages. Firstly, an improved edge line extraction method is proposed for the edge segments to fit closely to building outlines. Secondly, a fusion method is proposed for the outlines under the constraint of straight lines, which can maintain the building structural attribute with parallel or vertical edges, which is very useful for the dense matching method. Finally, we proposed an edge constraint and outline compensation (ECAOC) dense matching method to maintain building object structural characteristics in the disparity map. In the proposed method, the improved edge lines are used to optimize matching search scope and matching template window, and the high-precision building outlines are used to compensate the shape feature of building objects. Our method can greatly increase the matching accuracy of building objects in urban areas, especially at building edges. For the outline extraction experiments, our fusion method verifies the superiority and robustness on panchromatic images of different satellites and different resolutions. For the dense matching experiments, our ECOAC method shows great advantages for matching accuracy of building objects in urban areas compared with three other methods. PMID:29596393

Self-Similar Spin Images for Point Cloud Matching

NASA Astrophysics Data System (ADS)

Pulido, Daniel

The rapid growth of Light Detection And Ranging (Lidar) technologies that collect, process, and disseminate 3D point clouds have allowed for increasingly accurate spatial modeling and analysis of the real world. Lidar sensors can generate massive 3D point clouds of a collection area that provide highly detailed spatial and radiometric information. However, a Lidar collection can be expensive and time consuming. Simultaneously, the growth of crowdsourced Web 2.0 data (e.g., Flickr, OpenStreetMap) have provided researchers with a wealth of freely available data sources that cover a variety of geographic areas. Crowdsourced data can be of varying quality and density. In addition, since it is typically not collected as part of a dedicated experiment but rather volunteered, when and where the data is collected is arbitrary. The integration of these two sources of geoinformation can provide researchers the ability to generate products and derive intelligence that mitigate their respective disadvantages and combine their advantages. Therefore, this research will address the problem of fusing two point clouds from potentially different sources. Specifically, we will consider two problems: scale matching and feature matching. Scale matching consists of computing feature metrics of each point cloud and analyzing their distributions to determine scale differences. Feature matching consists of defining local descriptors that are invariant to common dataset distortions (e.g., rotation and translation). Additionally, after matching the point clouds they can be registered and processed further (e.g., change detection). The objective of this research is to develop novel methods to fuse and enhance two point clouds from potentially disparate sources (e.g., Lidar and crowdsourced Web 2.0 datasets). The scope of this research is to investigate both scale and feature matching between two point clouds. The specific focus of this research will be in developing a novel local descriptor

A new pre-classification method based on associative matching method

NASA Astrophysics Data System (ADS)

Katsuyama, Yutaka; Minagawa, Akihiro; Hotta, Yoshinobu; Omachi, Shinichiro; Kato, Nei

2010-01-01

Reducing the time complexity of character matching is critical to the development of efficient Japanese Optical Character Recognition (OCR) systems. To shorten processing time, recognition is usually split into separate preclassification and recognition stages. For high overall recognition performance, the pre-classification stage must both have very high classification accuracy and return only a small number of putative character categories for further processing. Furthermore, for any practical system, the speed of the pre-classification stage is also critical. The associative matching (AM) method has often been used for fast pre-classification, because its use of a hash table and reliance solely on logical bit operations to select categories makes it highly efficient. However, redundant certain level of redundancy exists in the hash table because it is constructed using only the minimum and maximum values of the data on each axis and therefore does not take account of the distribution of the data. We propose a modified associative matching method that satisfies the performance criteria described above but in a fraction of the time by modifying the hash table to reflect the underlying distribution of training characters. Furthermore, we show that our approach outperforms pre-classification by clustering, ANN and conventional AM in terms of classification accuracy, discriminative power and speed. Compared to conventional associative matching, the proposed approach results in a 47% reduction in total processing time across an evaluation test set comprising 116,528 Japanese character images.

Line segment confidence region-based string matching method for map conflation

NASA Astrophysics Data System (ADS)

Huh, Yong; Yang, Sungchul; Ga, Chillo; Yu, Kiyun; Shi, Wenzhong

2013-04-01

In this paper, a method to detect corresponding point pairs between polygon object pairs with a string matching method based on a confidence region model of a line segment is proposed. The optimal point edit sequence to convert the contour of a target object into that of a reference object was found by the string matching method which minimizes its total error cost, and the corresponding point pairs were derived from the edit sequence. Because a significant amount of apparent positional discrepancies between corresponding objects are caused by spatial uncertainty and their confidence region models of line segments are therefore used in the above matching process, the proposed method obtained a high F-measure for finding matching pairs. We applied this method for built-up area polygon objects in a cadastral map and a topographical map. Regardless of their different mapping and representation rules and spatial uncertainties, the proposed method with a confidence level at 0.95 showed a matching result with an F-measure of 0.894.

Improved artificial bee colony algorithm based gravity matching navigation method.

PubMed

Gao, Wei; Zhao, Bo; Zhou, Guang Tao; Wang, Qiu Ying; Yu, Chun Yang

2014-07-18

Gravity matching navigation algorithm is one of the key technologies for gravity aided inertial navigation systems. With the development of intelligent algorithms, the powerful search ability of the Artificial Bee Colony (ABC) algorithm makes it possible to be applied to the gravity matching navigation field. However, existing search mechanisms of basic ABC algorithms cannot meet the need for high accuracy in gravity aided navigation. Firstly, proper modifications are proposed to improve the performance of the basic ABC algorithm. Secondly, a new search mechanism is presented in this paper which is based on an improved ABC algorithm using external speed information. At last, modified Hausdorff distance is introduced to screen the possible matching results. Both simulations and ocean experiments verify the feasibility of the method, and results show that the matching rate of the method is high enough to obtain a precise matching position.

Methods for Assessing Item, Step, and Threshold Invariance in Polytomous Items Following the Partial Credit Model

ERIC Educational Resources Information Center

Penfield, Randall D.; Myers, Nicholas D.; Wolfe, Edward W.

2008-01-01

Measurement invariance in the partial credit model (PCM) can be conceptualized in several different but compatible ways. In this article the authors distinguish between three forms of measurement invariance in the PCM: step invariance, item invariance, and threshold invariance. Approaches for modeling these three forms of invariance are proposed,…

Matching methods evaluation framework for stereoscopic breast x-ray images.

PubMed

Rousson, Johanna; Naudin, Mathieu; Marchessoux, Cédric

2016-01-01

Three-dimensional (3-D) imaging has been intensively studied in the past few decades. Depth information is an important added value of 3-D systems over two-dimensional systems. Special focuses were devoted to the development of stereo matching methods for the generation of disparity maps (i.e., depth information within a 3-D scene). Dedicated frameworks were designed to evaluate and rank the performance of different stereo matching methods but never considering x-ray medical images. Yet, 3-D x-ray acquisition systems and 3-D medical displays have already been introduced into the diagnostic market. To access the depth information within x-ray stereoscopic images, computing accurate disparity maps is essential. We aimed at developing a framework dedicated to x-ray stereoscopic breast images used to evaluate and rank several stereo matching methods. A multiresolution pyramid optimization approach was integrated to the framework to increase the accuracy and the efficiency of the stereo matching techniques. Finally, a metric was designed to score the results of the stereo matching compared with the ground truth. Eight methods were evaluated and four of them [locally scaled sum of absolute differences (LSAD), zero mean sum of absolute differences, zero mean sum of squared differences, and locally scaled mean sum of squared differences] appeared to perform equally good with an average error score of 0.04 (0 is the perfect matching). LSAD was selected for generating the disparity maps.

Systems and methods for measuring component matching

NASA Technical Reports Server (NTRS)

Courter, Kelly J. (Inventor); Slenk, Joel E. (Inventor)

2006-01-01

Systems and methods for measuring a contour match between adjacent components are disclosed. In one embodiment, at least two pressure sensors are located between adjacent components. Each pressure sensor is adapted to obtain a pressure measurement at a location a predetermined distance away from the other pressure sensors, and to output a pressure measurement for each sensor location. An output device is adapted to receive the pressure measurements from at least two pressure sensors and display the pressure measurements. In one aspect, the pressure sensors include flexible thin film pressure sensors. In accordance with other aspects of the invention, a method is provided for measuring a contour match between two interfacing components including measuring at least one pressure applied to at least one sensor between the interfacing components.

Relating Measurement Invariance, Cross-Level Invariance, and Multilevel Reliability.

PubMed

Jak, Suzanne; Jorgensen, Terrence D

2017-01-01

Data often have a nested, multilevel structure, for example when data are collected from children in classrooms. This kind of data complicate the evaluation of reliability and measurement invariance, because several properties can be evaluated at both the individual level and the cluster level, as well as across levels. For example, cross-level invariance implies equal factor loadings across levels, which is needed to give latent variables at the two levels a similar interpretation. Reliability at a specific level refers to the ratio of true score variance over total variance at that level. This paper aims to shine light on the relation between reliability, cross-level invariance, and strong factorial invariance across clusters in multilevel data. Specifically, we will illustrate how strong factorial invariance across clusters implies cross-level invariance and perfect reliability at the between level in multilevel factor models.

Improved Artificial Bee Colony Algorithm Based Gravity Matching Navigation Method

PubMed Central

Gao, Wei; Zhao, Bo; Zhou, Guang Tao; Wang, Qiu Ying; Yu, Chun Yang

2014-01-01

Gravity matching navigation algorithm is one of the key technologies for gravity aided inertial navigation systems. With the development of intelligent algorithms, the powerful search ability of the Artificial Bee Colony (ABC) algorithm makes it possible to be applied to the gravity matching navigation field. However, existing search mechanisms of basic ABC algorithms cannot meet the need for high accuracy in gravity aided navigation. Firstly, proper modifications are proposed to improve the performance of the basic ABC algorithm. Secondly, a new search mechanism is presented in this paper which is based on an improved ABC algorithm using external speed information. At last, modified Hausdorff distance is introduced to screen the possible matching results. Both simulations and ocean experiments verify the feasibility of the method, and results show that the matching rate of the method is high enough to obtain a precise matching position. PMID:25046019

Blurred image recognition by legendre moment invariants

PubMed Central

Zhang, Hui; Shu, Huazhong; Han, Guo-Niu; Coatrieux, Gouenou; Luo, Limin; Coatrieux, Jean-Louis

2010-01-01

Processing blurred images is a key problem in many image applications. Existing methods to obtain blur invariants which are invariant with respect to centrally symmetric blur are based on geometric moments or complex moments. In this paper, we propose a new method to construct a set of blur invariants using the orthogonal Legendre moments. Some important properties of Legendre moments for the blurred image are presented and proved. The performance of the proposed descriptors is evaluated with various point-spread functions and different image noises. The comparison of the present approach with previous methods in terms of pattern recognition accuracy is also provided. The experimental results show that the proposed descriptors are more robust to noise and have better discriminative power than the methods based on geometric or complex moments. PMID:19933003

Scope and applications of translation invariant wavelets to image registration

NASA Technical Reports Server (NTRS)

Chettri, Samir; LeMoigne, Jacqueline; Campbell, William

1997-01-01

The first part of this article introduces the notion of translation invariance in wavelets and discusses several wavelets that have this property. The second part discusses the possible applications of such wavelets to image registration. In the case of registration of affinely transformed images, we would conclude that the notion of translation invariance is not really necessary. What is needed is affine invariance and one way to do this is via the method of moment invariants. Wavelets or, in general, pyramid processing can then be combined with the method of moment invariants to reduce the computational load.

Function Invariant and Parameter Scale-Free Transformation Methods

ERIC Educational Resources Information Center

Bentler, P. M.; Wingard, Joseph A.

1977-01-01

A scale-invariant simple structure function of previously studied function components for principal component analysis and factor analysis is defined. First and second partial derivatives are obtained, and Newton-Raphson iterations are utilized. The resulting solutions are locally optimal and subjectively pleasing. (Author/JKS)

Differential invariants in nonclassical models of hydrodynamics

NASA Astrophysics Data System (ADS)

Bublik, Vasily V.

2017-10-01

In this paper, differential invariants are used to construct solutions for equations of the dynamics of a viscous heat-conducting gas and the dynamics of a viscous incompressible fluid modified by nanopowder inoculators. To describe the dynamics of a viscous heat-conducting gas, we use the complete system of Navier—Stokes equations with allowance for heat fluxes. Mathematical description of the dynamics of liquid metals under high-energy external influences (laser radiation or plasma flow) includes, in addition to the Navier—Stokes system of an incompressible viscous fluid, also heat fluxes and processes of nonequilibrium crystallization of a deformable fluid. Differentially invariant solutions are a generalization of partially invariant solutions, and their active study for various models of continuous medium mechanics is just beginning. Differentially invariant solutions can also be considered as solutions with differential constraints; therefore, when developing them, the approaches and methods developed by the science schools of academicians N. N. Yanenko and A. F. Sidorov will be actively used. In the construction of partially invariant and differentially invariant solutions, there are overdetermined systems of differential equations that require a compatibility analysis. The algorithms for reducing such systems to involution in a finite number of steps are described by Cartan, Finikov, Kuranishi, and other authors. However, the difficultly foreseeable volume of intermediate calculations complicates their practical application. Therefore, the methods of computer algebra are actively used here, which largely helps in solving this difficult problem. It is proposed to use the constructed exact solutions as tests for formulas, algorithms and their software implementations when developing and creating numerical methods and computational program complexes. This combination of effective numerical methods, capable of solving a wide class of problems, with

Spatially Invariant Vector Quantization: A pattern matching algorithm for multiple classes of image subject matter including pathology.

PubMed

Hipp, Jason D; Cheng, Jerome Y; Toner, Mehmet; Tompkins, Ronald G; Balis, Ulysses J

2011-02-26

HISTORICALLY, EFFECTIVE CLINICAL UTILIZATION OF IMAGE ANALYSIS AND PATTERN RECOGNITION ALGORITHMS IN PATHOLOGY HAS BEEN HAMPERED BY TWO CRITICAL LIMITATIONS: 1) the availability of digital whole slide imagery data sets and 2) a relative domain knowledge deficit in terms of application of such algorithms, on the part of practicing pathologists. With the advent of the recent and rapid adoption of whole slide imaging solutions, the former limitation has been largely resolved. However, with the expectation that it is unlikely for the general cohort of contemporary pathologists to gain advanced image analysis skills in the short term, the latter problem remains, thus underscoring the need for a class of algorithm that has the concurrent properties of image domain (or organ system) independence and extreme ease of use, without the need for specialized training or expertise. In this report, we present a novel, general case pattern recognition algorithm, Spatially Invariant Vector Quantization (SIVQ), that overcomes the aforementioned knowledge deficit. Fundamentally based on conventional Vector Quantization (VQ) pattern recognition approaches, SIVQ gains its superior performance and essentially zero-training workflow model from its use of ring vectors, which exhibit continuous symmetry, as opposed to square or rectangular vectors, which do not. By use of the stochastic matching properties inherent in continuous symmetry, a single ring vector can exhibit as much as a millionfold improvement in matching possibilities, as opposed to conventional VQ vectors. SIVQ was utilized to demonstrate rapid and highly precise pattern recognition capability in a broad range of gross and microscopic use-case settings. With the performance of SIVQ observed thus far, we find evidence that indeed there exist classes of image analysis/pattern recognition algorithms suitable for deployment in settings where pathologists alone can effectively incorporate their use into clinical workflow, as a

Methods and statistics for combining motif match scores.

PubMed

Bailey, T L; Gribskov, M

1998-01-01

Position-specific scoring matrices are useful for representing and searching for protein sequence motifs. A sequence family can often be described by a group of one or more motifs, and an effective search must combine the scores for matching a sequence to each of the motifs in the group. We describe three methods for combining match scores and estimating the statistical significance of the combined scores and evaluate the search quality (classification accuracy) and the accuracy of the estimate of statistical significance of each. The three methods are: 1) sum of scores, 2) sum of reduced variates, 3) product of score p-values. We show that method 3) is superior to the other two methods in both regards, and that combining motif scores indeed gives better search accuracy. The MAST sequence homology search algorithm utilizing the product of p-values scoring method is available for interactive use and downloading at URL http:/(/)www.sdsc.edu/MEME.

Measurement Invariance versus Selection Invariance: Is Fair Selection Possible?

ERIC Educational Resources Information Center

Borsman, Denny; Romeijn, Jan-Willem; Wicherts, Jelte M.

2008-01-01

This article shows that measurement invariance (defined in terms of an invariant measurement model in different groups) is generally inconsistent with selection invariance (defined in terms of equal sensitivity and specificity across groups). In particular, when a unidimensional measurement instrument is used and group differences are present in…

The scale invariant generator technique for quantifying anisotropic scale invariance

NASA Astrophysics Data System (ADS)

Lewis, G. M.; Lovejoy, S.; Schertzer, D.; Pecknold, S.

1999-11-01

Scale invariance is rapidly becoming a new paradigm for geophysics. However, little attention has been paid to the anisotropy that is invariably present in geophysical fields in the form of differential stratification and rotation, texture and morphology. In order to account for scaling anisotropy, the formalism of generalized scale invariance (GSI) was developed. Until now there has existed only a single fairly ad hoc GSI analysis technique valid for studying differential rotation. In this paper, we use a two-dimensional representation of the linear approximation to generalized scale invariance, to obtain a much improved technique for quantifying anisotropic scale invariance called the scale invariant generator technique (SIG). The accuracy of the technique is tested using anisotropic multifractal simulations and error estimates are provided for the geophysically relevant range of parameters. It is found that the technique yields reasonable estimates for simulations with a diversity of anisotropic and statistical characteristics. The scale invariant generator technique can profitably be applied to the scale invariant study of vertical/horizontal and space/time cross-sections of geophysical fields as well as to the study of the texture/morphology of fields.

An efficient photogrammetric stereo matching method for high-resolution images

NASA Astrophysics Data System (ADS)

Li, Yingsong; Zheng, Shunyi; Wang, Xiaonan; Ma, Hao

2016-12-01

Stereo matching of high-resolution images is a great challenge in photogrammetry. The main difficulty is the enormous processing workload that involves substantial computing time and memory consumption. In recent years, the semi-global matching (SGM) method has been a promising approach for solving stereo problems in different data sets. However, the time complexity and memory demand of SGM are proportional to the scale of the images involved, which leads to very high consumption when dealing with large images. To solve it, this paper presents an efficient hierarchical matching strategy based on the SGM algorithm using single instruction multiple data instructions and structured parallelism in the central processing unit. The proposed method can significantly reduce the computational time and memory required for large scale stereo matching. The three-dimensional (3D) surface is reconstructed by triangulating and fusing redundant reconstruction information from multi-view matching results. Finally, three high-resolution aerial date sets are used to evaluate our improvement. Furthermore, precise airborne laser scanner data of one data set is used to measure the accuracy of our reconstruction. Experimental results demonstrate that our method remarkably outperforms in terms of time and memory savings while maintaining the density and precision of the 3D cloud points derived.

Single-subject structural networks with closed-form rotation invariant matching mprove power in developmental studies of the cortex.

PubMed

Kandel, Benjamin M; Wang, Danny J J; Gee, James C; Avants, Brian B

2014-01-01

Although much attention has recently been focused on single-subject functional networks, using methods such as resting-state functional MRI, methods for constructing single-subject structural networks are in their infancy. Single-subject cortical networks aim to describe the self-similarity across the cortical structure, possibly signifying convergent developmental pathways. Previous methods for constructing single-subject cortical networks have used patch-based correlations and distance metrics based on curvature and thickness. We present here a method for constructing similarity-based cortical structural networks that utilizes a rotation-invariant representation of structure. The resulting graph metrics are closely linked to age and indicate an increasing degree of closeness throughout development in nearly all brain regions, perhaps corresponding to a more regular structure as the brain matures. The derived graph metrics demonstrate a four-fold increase in power for detecting age as compared to cortical thickness. This proof of concept study indicates that the proposed metric may be useful in identifying biologically relevant cortical patterns.

Curvelet-domain multiple matching method combined with cubic B-spline function

NASA Astrophysics Data System (ADS)

Wang, Tong; Wang, Deli; Tian, Mi; Hu, Bin; Liu, Chengming

2018-05-01

Since the large amount of surface-related multiple existed in the marine data would influence the results of data processing and interpretation seriously, many researchers had attempted to develop effective methods to remove them. The most successful surface-related multiple elimination method was proposed based on data-driven theory. However, the elimination effect was unsatisfactory due to the existence of amplitude and phase errors. Although the subsequent curvelet-domain multiple-primary separation method achieved better results, poor computational efficiency prevented its application. In this paper, we adopt the cubic B-spline function to improve the traditional curvelet multiple matching method. First, select a little number of unknowns as the basis points of the matching coefficient; second, apply the cubic B-spline function on these basis points to reconstruct the matching array; third, build constraint solving equation based on the relationships of predicted multiple, matching coefficients, and actual data; finally, use the BFGS algorithm to iterate and realize the fast-solving sparse constraint of multiple matching algorithm. Moreover, the soft-threshold method is used to make the method perform better. With the cubic B-spline function, the differences between predicted multiple and original data diminish, which results in less processing time to obtain optimal solutions and fewer iterative loops in the solving procedure based on the L1 norm constraint. The applications to synthetic and field-derived data both validate the practicability and validity of the method.

Incorrect Match Detection Method for Arctic Sea-Ice Reconstruction Using Uav Images

NASA Astrophysics Data System (ADS)

Kim, J.-I.; Kim, H.-C.

2018-05-01

Shapes and surface roughness, which are considered as key indicators in understanding Arctic sea-ice, can be measured from the digital surface model (DSM) of the target area. Unmanned aerial vehicle (UAV) flying at low altitudes enables theoretically accurate DSM generation. However, the characteristics of sea-ice with textureless surface and incessant motion make image matching difficult for DSM generation. In this paper, we propose a method for effectively detecting incorrect matches before correcting a sea-ice DSM derived from UAV images. The proposed method variably adjusts the size of search window to analyze the matching results of DSM generated and distinguishes incorrect matches. Experimental results showed that the sea-ice DSM produced large errors along the textureless surfaces, and that the incorrect matches could be effectively detected by the proposed method.

Machine learning strategies for systems with invariance properties

NASA Astrophysics Data System (ADS)

Ling, Julia; Jones, Reese; Templeton, Jeremy

2016-08-01

In many scientific fields, empirical models are employed to facilitate computational simulations of engineering systems. For example, in fluid mechanics, empirical Reynolds stress closures enable computationally-efficient Reynolds Averaged Navier Stokes simulations. Likewise, in solid mechanics, constitutive relations between the stress and strain in a material are required in deformation analysis. Traditional methods for developing and tuning empirical models usually combine physical intuition with simple regression techniques on limited data sets. The rise of high performance computing has led to a growing availability of high fidelity simulation data. These data open up the possibility of using machine learning algorithms, such as random forests or neural networks, to develop more accurate and general empirical models. A key question when using data-driven algorithms to develop these empirical models is how domain knowledge should be incorporated into the machine learning process. This paper will specifically address physical systems that possess symmetry or invariance properties. Two different methods for teaching a machine learning model an invariance property are compared. In the first method, a basis of invariant inputs is constructed, and the machine learning model is trained upon this basis, thereby embedding the invariance into the model. In the second method, the algorithm is trained on multiple transformations of the raw input data until the model learns invariance to that transformation. Results are discussed for two case studies: one in turbulence modeling and one in crystal elasticity. It is shown that in both cases embedding the invariance property into the input features yields higher performance at significantly reduced computational training costs.

An accelerated image matching technique for UAV orthoimage registration

NASA Astrophysics Data System (ADS)

Tsai, Chung-Hsien; Lin, Yu-Ching

2017-06-01

Using an Unmanned Aerial Vehicle (UAV) drone with an attached non-metric camera has become a popular low-cost approach for collecting geospatial data. A well-georeferenced orthoimage is a fundamental product for geomatics professionals. To achieve high positioning accuracy of orthoimages, precise sensor position and orientation data, or a number of ground control points (GCPs), are often required. Alternatively, image registration is a solution for improving the accuracy of a UAV orthoimage, as long as a historical reference image is available. This study proposes a registration scheme, including an Accelerated Binary Robust Invariant Scalable Keypoints (ABRISK) algorithm and spatial analysis of corresponding control points for image registration. To determine a match between two input images, feature descriptors from one image are compared with those from another image. A "Sorting Ring" is used to filter out uncorrected feature pairs as early as possible in the stage of matching feature points, to speed up the matching process. The results demonstrate that the proposed ABRISK approach outperforms the vector-based Scale Invariant Feature Transform (SIFT) approach where radiometric variations exist. ABRISK is 19.2 times and 312 times faster than SIFT for image sizes of 1000 × 1000 pixels and 4000 × 4000 pixels, respectively. ABRISK is 4.7 times faster than Binary Robust Invariant Scalable Keypoints (BRISK). Furthermore, the positional accuracy of the UAV orthoimage after applying the proposed image registration scheme is improved by an average of root mean square error (RMSE) of 2.58 m for six test orthoimages whose spatial resolutions vary from 6.7 cm to 10.7 cm.

A spot-matching method using cumulative frequency matrix in 2D gel images

PubMed Central

Han, Chan-Myeong; Park, Joon-Ho; Chang, Chu-Seok; Ryoo, Myung-Chun

2014-01-01

A new method for spot matching in two-dimensional gel electrophoresis images using a cumulative frequency matrix is proposed. The method improves on the weak points of the previous method called ‘spot matching by topological patterns of neighbour spots’. It accumulates the frequencies of neighbour spot pairs produced through the entire matching process and determines spot pairs one by one in order of higher frequency. Spot matching by frequencies of neighbour spot pairs shows a fairly better performance. However, it can give researchers a hint for whether the matching results can be trustworthy or not, which can save researchers a lot of effort for verification of the results. PMID:26019609

Assessment of identity during adolescence using daily diary methods: Measurement invariance across time and sex.

PubMed

Becht, Andrik I; Branje, Susan J T; Vollebergh, Wilma A M; Maciejewski, Dominique F; van Lier, Pol A C; Koot, Hans M; Denissen, Jaap J A; Meeus, Wim H J

2016-06-01

The aim of this study was to assess measurement invariance of adolescents' daily reports on identity across time and sex. Adolescents (N = 497; mean age = 13.32 years at Time 1, 56.7% boys) from the general population reported on their identity commitments, exploration in depth and reconsideration on a daily basis for 3 weeks within 1 year across 5 years. We used the single-item version of the Utrecht Management of Identity Commitments Scale (UMICS; Klimstra et al., 2010), a broad measure of identity-formation processes covering both interpersonal and educational identity domains. This study tested configural, metric, scalar, and strict measurement invariance across days within weeks, across sex, across weeks within years, and across years. Results indicated that daily diary reports show strict measurement invariance across days, across weeks within years, across years, and across boys and girls. These results support the use of daily diary methods to assess identity at various time intervals ranging from days to years and across sex. Results are discussed with regard to future implications to study identity processes, both on smaller and larger time intervals. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Binary optical filters for scale invariant pattern recognition

NASA Technical Reports Server (NTRS)

Reid, Max B.; Downie, John D.; Hine, Butler P.

1992-01-01

Binary synthetic discriminant function (BSDF) optical filters which are invariant to scale changes in the target object of more than 50 percent are demonstrated in simulation and experiment. Efficient databases of scale invariant BSDF filters can be designed which discriminate between two very similar objects at any view scaled over a factor of 2 or more. The BSDF technique has considerable advantages over other methods for achieving scale invariant object recognition, as it also allows determination of the object's scale. In addition to scale, the technique can be used to design recognition systems invariant to other geometric distortions.

Real-time pose invariant logo and pattern detection

NASA Astrophysics Data System (ADS)

Sidla, Oliver; Kottmann, Michal; Benesova, Wanda

2011-01-01

The detection of pose invariant planar patterns has many practical applications in computer vision and surveillance systems. The recognition of company logos is used in market studies to examine the visibility and frequency of logos in advertisement. Danger signs on vehicles could be detected to trigger warning systems in tunnels, or brand detection on transport vehicles can be used to count company-specific traffic. We present the results of a study on planar pattern detection which is based on keypoint detection and matching of distortion invariant 2d feature descriptors. Specifically we look at the keypoint detectors of type: i) Lowe's DoG approximation from the SURF algorithm, ii) the Harris Corner Detector, iii) the FAST Corner Detector and iv) Lepetit's keypoint detector. Our study then compares the feature descriptors SURF and compact signatures based on Random Ferns: we use 3 sets of sample images to detect and match 3 logos of different structure to find out which combinations of keypoint detector/feature descriptors work well. A real-world test tries to detect vehicles with a distinctive logo in an outdoor environment under realistic lighting and weather conditions: a camera was mounted on a suitable location for observing the entrance to a parking area so that incoming vehicles could be monitored. In this 2 hour long recording we can successfully detect a specific company logo without false positives.

A novel method for rotation invariant palm print image stitching

NASA Astrophysics Data System (ADS)

Rao, Shishir Paramathma; Panetta, Karen; Agaian, Sos S.

2017-05-01

Although not as popular as fingerprint biometrics, palm prints have garnered interest in scientific community for the rich amount of distinctive information available on the palm. In this paper, a novel method for touchless palm print stitching to increase the effective area is presented. The method is not only rotation invariant but also able to robustly handle many distortions of touchless systems like illumination variations, pose variations etc. The proposed method also can handle partial palmprints, which have a high chance of occurrence in a scene of crime, by stitching them together to produce a much larger-to-full size palmprint for authentication purpose. Experiment results are shown for IIT-D palmprint database, from which pseudo partial palmprints were generated by cropping and randomly rotating them. Furthermore, the quality of stitching algorithm is determined by extensive computer simulations and visual analysis of the stitched image. Experimental results also show that the stitching significantly increases the area of palm image for feature point detection and hence provides a way to increase the accuracy and reliability of detection.

The Use of Invariance and Bootstrap Procedures as a Method to Establish the Reliability of Research Results.

ERIC Educational Resources Information Center

Sandler, Andrew B.

Statistical significance is misused in educational and psychological research when it is applied as a method to establish the reliability of research results. Other techniques have been developed which can be correctly utilized to establish the generalizability of findings. Methods that do provide such estimates are known as invariance or…

Invariants for the generalized Lotka-Volterra equations

NASA Astrophysics Data System (ADS)

Cairó, Laurent; Feix, Marc R.; Goedert, Joao

A generalisation of Lotka-Volterra System is given when self limiting terms are introduced in the model. We use a modification of the Carleman embedding method to find invariants for this system of equations. The position and stability of the equilibrium point and the regression of system under invariant conditions are studied.

Graphic matching based on shape contexts and reweighted random walks

NASA Astrophysics Data System (ADS)

Zhang, Mingxuan; Niu, Dongmei; Zhao, Xiuyang; Liu, Mingjun

2018-04-01

Graphic matching is a very critical issue in all aspects of computer vision. In this paper, a new graphics matching algorithm combining shape contexts and reweighted random walks was proposed. On the basis of the local descriptor, shape contexts, the reweighted random walks algorithm was modified to possess stronger robustness and correctness in the final result. Our main process is to use the descriptor of the shape contexts for the random walk on the iteration, of which purpose is to control the random walk probability matrix. We calculate bias matrix by using descriptors and then in the iteration we use it to enhance random walks' and random jumps' accuracy, finally we get the one-to-one registration result by discretization of the matrix. The algorithm not only preserves the noise robustness of reweighted random walks but also possesses the rotation, translation, scale invariance of shape contexts. Through extensive experiments, based on real images and random synthetic point sets, and comparisons with other algorithms, it is confirmed that this new method can produce excellent results in graphic matching.

Image Segmentation, Registration, Compression, and Matching

NASA Technical Reports Server (NTRS)

Yadegar, Jacob; Wei, Hai; Yadegar, Joseph; Ray, Nilanjan; Zabuawala, Sakina

2011-01-01

A novel computational framework was developed of a 2D affine invariant matching exploiting a parameter space. Named as affine invariant parameter space (AIPS), the technique can be applied to many image-processing and computer-vision problems, including image registration, template matching, and object tracking from image sequence. The AIPS is formed by the parameters in an affine combination of a set of feature points in the image plane. In cases where the entire image can be assumed to have undergone a single affine transformation, the new AIPS match metric and matching framework becomes very effective (compared with the state-of-the-art methods at the time of this reporting). No knowledge about scaling or any other transformation parameters need to be known a priori to apply the AIPS framework. An automated suite of software tools has been created to provide accurate image segmentation (for data cleaning) and high-quality 2D image and 3D surface registration (for fusing multi-resolution terrain, image, and map data). These tools are capable of supporting existing GIS toolkits already in the marketplace, and will also be usable in a stand-alone fashion. The toolkit applies novel algorithmic approaches for image segmentation, feature extraction, and registration of 2D imagery and 3D surface data, which supports first-pass, batched, fully automatic feature extraction (for segmentation), and registration. A hierarchical and adaptive approach is taken for achieving automatic feature extraction, segmentation, and registration. Surface registration is the process of aligning two (or more) data sets to a common coordinate system, during which the transformation between their different coordinate systems is determined. Also developed here are a novel, volumetric surface modeling and compression technique that provide both quality-guaranteed mesh surface approximations and compaction of the model sizes by efficiently coding the geometry and connectivity

Method and apparatus for measuring flow velocity using matched filters

DOEpatents

Raptis, A.C.

1983-09-06

An apparatus and method for measuring the flow velocities of individual phase flow components of a multiphase flow utilizes matched filters. Signals arising from flow noise disturbance are extracted from the flow, at upstream and downstream locations. The signals are processed through pairs of matched filters which are matched to the flow disturbance frequency characteristics of the phase flow component to be measured. The processed signals are then cross-correlated to determine the transit delay time of the phase flow component between sensing positions. 8 figs.

Method and apparatus for measuring flow velocity using matched filters

DOEpatents

Raptis, Apostolos C.

1983-01-01

An apparatus and method for measuring the flow velocities of individual phase flow components of a multiphase flow utilizes matched filters. Signals arising from flow noise disturbance are extracted from the flow, at upstream and downstream locations. The signals are processed through pairs of matched filters which are matched to the flow disturbance frequency characteristics of the phase flow component to be measured. The processed signals are then cross-correlated to determine the transit delay time of the phase flow component between sensing positions.

Machine learning strategies for systems with invariance properties

DOE PAGES

Ling, Julia; Jones, Reese E.; Templeton, Jeremy Alan

2016-05-06

Here, in many scientific fields, empirical models are employed to facilitate computational simulations of engineering systems. For example, in fluid mechanics, empirical Reynolds stress closures enable computationally-efficient Reynolds-Averaged Navier-Stokes simulations. Likewise, in solid mechanics, constitutive relations between the stress and strain in a material are required in deformation analysis. Traditional methods for developing and tuning empirical models usually combine physical intuition with simple regression techniques on limited data sets. The rise of high-performance computing has led to a growing availability of high-fidelity simulation data, which open up the possibility of using machine learning algorithms, such as random forests or neuralmore » networks, to develop more accurate and general empirical models. A key question when using data-driven algorithms to develop these models is how domain knowledge should be incorporated into the machine learning process. This paper will specifically address physical systems that possess symmetry or invariance properties. Two different methods for teaching a machine learning model an invariance property are compared. In the first , a basis of invariant inputs is constructed, and the machine learning model is trained upon this basis, thereby embedding the invariance into the model. In the second method, the algorithm is trained on multiple transformations of the raw input data until the model learns invariance to that transformation. Results are discussed for two case studies: one in turbulence modeling and one in crystal elasticity. It is shown that in both cases embedding the invariance property into the input features yields higher performance with significantly reduced computational training costs.« less

Machine learning strategies for systems with invariance properties

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

Ling, Julia; Jones, Reese E.; Templeton, Jeremy Alan

Here, in many scientific fields, empirical models are employed to facilitate computational simulations of engineering systems. For example, in fluid mechanics, empirical Reynolds stress closures enable computationally-efficient Reynolds-Averaged Navier-Stokes simulations. Likewise, in solid mechanics, constitutive relations between the stress and strain in a material are required in deformation analysis. Traditional methods for developing and tuning empirical models usually combine physical intuition with simple regression techniques on limited data sets. The rise of high-performance computing has led to a growing availability of high-fidelity simulation data, which open up the possibility of using machine learning algorithms, such as random forests or neuralmore » networks, to develop more accurate and general empirical models. A key question when using data-driven algorithms to develop these models is how domain knowledge should be incorporated into the machine learning process. This paper will specifically address physical systems that possess symmetry or invariance properties. Two different methods for teaching a machine learning model an invariance property are compared. In the first , a basis of invariant inputs is constructed, and the machine learning model is trained upon this basis, thereby embedding the invariance into the model. In the second method, the algorithm is trained on multiple transformations of the raw input data until the model learns invariance to that transformation. Results are discussed for two case studies: one in turbulence modeling and one in crystal elasticity. It is shown that in both cases embedding the invariance property into the input features yields higher performance with significantly reduced computational training costs.« less

Invariance algorithms for processing NDE signals

NASA Astrophysics Data System (ADS)

Mandayam, Shreekanth; Udpa, Lalita; Udpa, Satish S.; Lord, William

1996-11-01

Signals that are obtained in a variety of nondestructive evaluation (NDE) processes capture information not only about the characteristics of the flaw, but also reflect variations in the specimen's material properties. Such signal changes may be viewed as anomalies that could obscure defect related information. An example of this situation occurs during in-line inspection of gas transmission pipelines. The magnetic flux leakage (MFL) method is used to conduct noninvasive measurements of the integrity of the pipe-wall. The MFL signals contain information both about the permeability of the pipe-wall and the dimensions of the flaw. Similar operational effects can be found in other NDE processes. This paper presents algorithms to render NDE signals invariant to selected test parameters, while retaining defect related information. Wavelet transform based neural network techniques are employed to develop the invariance algorithms. The invariance transformation is shown to be a necessary pre-processing step for subsequent defect characterization and visualization schemes. Results demonstrating the successful application of the method are presented.

Automated transformation-invariant shape recognition through wavelet multiresolution

NASA Astrophysics Data System (ADS)

Brault, Patrice; Mounier, Hugues

2001-12-01

We present here new results in Wavelet Multi-Resolution Analysis (W-MRA) applied to shape recognition in automatic vehicle driving applications. Different types of shapes have to be recognized in this framework. They pertain to most of the objects entering the sensors field of a car. These objects can be road signs, lane separation lines, moving or static obstacles, other automotive vehicles, or visual beacons. The recognition process must be invariant to global, affine or not, transformations which are : rotation, translation and scaling. It also has to be invariant to more local, elastic, deformations like the perspective (in particular with wide angle camera lenses), and also like deformations due to environmental conditions (weather : rain, mist, light reverberation) or optical and electrical signal noises. To demonstrate our method, an initial shape, with a known contour, is compared to the same contour altered by rotation, translation, scaling and perspective. The curvature computed for each contour point is used as a main criterion in the shape matching process. The original part of this work is to use wavelet descriptors, generated with a fast orthonormal W-MRA, rather than Fourier descriptors, in order to provide a multi-resolution description of the contour to be analyzed. In such way, the intrinsic spatial localization property of wavelet descriptors can be used and the recognition process can be speeded up. The most important part of this work is to demonstrate the potential performance of Wavelet-MRA in this application of shape recognition.

Computation of pattern invariance in brain-like structures.

PubMed

Ullman, S; Soloviev, S

1999-10-01

A fundamental capacity of the perceptual systems and the brain in general is to deal with the novel and the unexpected. In vision, we can effortlessly recognize a familiar object under novel viewing conditions, or recognize a new object as a member of a familiar class, such as a house, a face, or a car. This ability to generalize and deal efficiently with novel stimuli has long been considered a challenging example of brain-like computation that proved extremely difficult to replicate in artificial systems. In this paper we present an approach to generalization and invariant recognition. We focus our discussion on the problem of invariance to position in the visual field, but also sketch how similar principles could apply to other domains.The approach is based on the use of a large repertoire of partial generalizations that are built upon past experience. In the case of shift invariance, visual patterns are described as the conjunction of multiple overlapping image fragments. The invariance to the more primitive fragments is built into the system by past experience. Shift invariance of complex shapes is obtained from the invariance of their constituent fragments. We study by simulations aspects of this shift invariance method and then consider its extensions to invariant perception and classification by brain-like structures.

Bayesian SEM for Specification Search Problems in Testing Factorial Invariance.

PubMed

Shi, Dexin; Song, Hairong; Liao, Xiaolan; Terry, Robert; Snyder, Lori A

2017-01-01

Specification search problems refer to two important but under-addressed issues in testing for factorial invariance: how to select proper reference indicators and how to locate specific non-invariant parameters. In this study, we propose a two-step procedure to solve these issues. Step 1 is to identify a proper reference indicator using the Bayesian structural equation modeling approach. An item is selected if it is associated with the highest likelihood to be invariant across groups. Step 2 is to locate specific non-invariant parameters, given that a proper reference indicator has already been selected in Step 1. A series of simulation analyses show that the proposed method performs well under a variety of data conditions, and optimal performance is observed under conditions of large magnitude of non-invariance, low proportion of non-invariance, and large sample sizes. We also provide an empirical example to demonstrate the specific procedures to implement the proposed method in applied research. The importance and influences are discussed regarding the choices of informative priors with zero mean and small variances. Extensions and limitations are also pointed out.

A fast invariant imbedding method for multiple scattering calculations and an application to equivalent widths of CO2 lines on Venus

NASA Technical Reports Server (NTRS)

Sato, M.; Kawabata, K.; Hansen, J. E.

1977-01-01

The invariant imbedding method considered is based on an equation which describes the change in the reflected radiation when an optically thin layer is added to the top of the atmosphere. The equation is used to treat the problem of reflection from a planetary atmosphere as an initial value problem. A fast method is discussed for the solution of the invariant imbedding equation. The speed and accuracy of the new method are illustrated by comparing it with the doubling program published by Hansen and Travis (1974). Computations are performed of the equivalent widths of carbon dioxide absorption lines in solar radiation reflected by Venus for several models of the planetary atmosphere.

Local coding based matching kernel method for image classification.

PubMed

Song, Yan; McLoughlin, Ian Vince; Dai, Li-Rong

2014-01-01

This paper mainly focuses on how to effectively and efficiently measure visual similarity for local feature based representation. Among existing methods, metrics based on Bag of Visual Word (BoV) techniques are efficient and conceptually simple, at the expense of effectiveness. By contrast, kernel based metrics are more effective, but at the cost of greater computational complexity and increased storage requirements. We show that a unified visual matching framework can be developed to encompass both BoV and kernel based metrics, in which local kernel plays an important role between feature pairs or between features and their reconstruction. Generally, local kernels are defined using Euclidean distance or its derivatives, based either explicitly or implicitly on an assumption of Gaussian noise. However, local features such as SIFT and HoG often follow a heavy-tailed distribution which tends to undermine the motivation behind Euclidean metrics. Motivated by recent advances in feature coding techniques, a novel efficient local coding based matching kernel (LCMK) method is proposed. This exploits the manifold structures in Hilbert space derived from local kernels. The proposed method combines advantages of both BoV and kernel based metrics, and achieves a linear computational complexity. This enables efficient and scalable visual matching to be performed on large scale image sets. To evaluate the effectiveness of the proposed LCMK method, we conduct extensive experiments with widely used benchmark datasets, including 15-Scenes, Caltech101/256, PASCAL VOC 2007 and 2011 datasets. Experimental results confirm the effectiveness of the relatively efficient LCMK method.

A self-recalibration method based on scale-invariant registration for structured light measurement systems

NASA Astrophysics Data System (ADS)

Chen, Rui; Xu, Jing; Zhang, Song; Chen, Heping; Guan, Yong; Chen, Ken

2017-01-01

The accuracy of structured light measurement depends on delicate offline calibration. However, in some practical applications, the system is supposed to be reconfigured so frequently to track the target that an online calibration is required. To this end, this paper proposes a rapid and autonomous self-recalibration method. For the proposed method, first, the rotation matrix and the normalized translation vector are attained from the fundamental matrix; second, the scale factor is acquired based on scale-invariant registration such that the actual translation vector is obtained. Experiments have been conducted to verify the effectiveness of our proposed method and the results indicate a high degree of accuracy.

Contact-free palm-vein recognition based on local invariant features.

PubMed

Kang, Wenxiong; Liu, Yang; Wu, Qiuxia; Yue, Xishun

2014-01-01

Contact-free palm-vein recognition is one of the most challenging and promising areas in hand biometrics. In view of the existing problems in contact-free palm-vein imaging, including projection transformation, uneven illumination and difficulty in extracting exact ROIs, this paper presents a novel recognition approach for contact-free palm-vein recognition that performs feature extraction and matching on all vein textures distributed over the palm surface, including finger veins and palm veins, to minimize the loss of feature information. First, a hierarchical enhancement algorithm, which combines a DOG filter and histogram equalization, is adopted to alleviate uneven illumination and to highlight vein textures. Second, RootSIFT, a more stable local invariant feature extraction method in comparison to SIFT, is adopted to overcome the projection transformation in contact-free mode. Subsequently, a novel hierarchical mismatching removal algorithm based on neighborhood searching and LBP histograms is adopted to improve the accuracy of feature matching. Finally, we rigorously evaluated the proposed approach using two different databases and obtained 0.996% and 3.112% Equal Error Rates (EERs), respectively, which demonstrate the effectiveness of the proposed approach.

Contact-Free Palm-Vein Recognition Based on Local Invariant Features

PubMed Central

Kang, Wenxiong; Liu, Yang; Wu, Qiuxia; Yue, Xishun

2014-01-01

Contact-free palm-vein recognition is one of the most challenging and promising areas in hand biometrics. In view of the existing problems in contact-free palm-vein imaging, including projection transformation, uneven illumination and difficulty in extracting exact ROIs, this paper presents a novel recognition approach for contact-free palm-vein recognition that performs feature extraction and matching on all vein textures distributed over the palm surface, including finger veins and palm veins, to minimize the loss of feature information. First, a hierarchical enhancement algorithm, which combines a DOG filter and histogram equalization, is adopted to alleviate uneven illumination and to highlight vein textures. Second, RootSIFT, a more stable local invariant feature extraction method in comparison to SIFT, is adopted to overcome the projection transformation in contact-free mode. Subsequently, a novel hierarchical mismatching removal algorithm based on neighborhood searching and LBP histograms is adopted to improve the accuracy of feature matching. Finally, we rigorously evaluated the proposed approach using two different databases and obtained 0.996% and 3.112% Equal Error Rates (EERs), respectively, which demonstrate the effectiveness of the proposed approach. PMID:24866176

Combinatorial invariants and covariants as tools for conical intersections.

PubMed

Ryb, Itai; Baer, Roi

2004-12-01

The combinatorial invariant and covariant are introduced as practical tools for analysis of conical intersections in molecules. The combinatorial invariant is a quantity depending on adiabatic electronic states taken at discrete nuclear configuration points. It is invariant to the phase choice (gauge) of these states. In the limit that the points trace a loop in nuclear configuration space, the value of the invariant approaches the corresponding Berry phase factor. The Berry phase indicates the presence of an odd or even number of conical intersections on surfaces bounded by these loops. Based on the combinatorial invariant, we develop a computationally simple and efficient method for locating conical intersections. The method is robust due to its use of gauge invariant nature. It does not rely on the landscape of intersecting potential energy surfaces nor does it require the computation of nonadiabatic couplings. We generalize the concept to open paths and combinatorial covariants for higher dimensions obtaining a technique for the construction of the gauge-covariant adiabatic-diabatic transformation matrix. This too does not make use of nonadiabatic couplings. The importance of using gauge-covariant expressions is underlined throughout. These techniques can be readily implemented by standard quantum chemistry codes. (c) 2004 American Institute of Physics.

Depth estimation of features in video frames with improved feature matching technique using Kinect sensor

NASA Astrophysics Data System (ADS)

Sharma, Kajal; Moon, Inkyu; Kim, Sung Gaun

2012-10-01

Estimating depth has long been a major issue in the field of computer vision and robotics. The Kinect sensor's active sensing strategy provides high-frame-rate depth maps and can recognize user gestures and human pose. This paper presents a technique to estimate the depth of features extracted from video frames, along with an improved feature-matching method. In this paper, we used the Kinect camera developed by Microsoft, which captured color and depth images for further processing. Feature detection and selection is an important task for robot navigation. Many feature-matching techniques have been proposed earlier, and this paper proposes an improved feature matching between successive video frames with the use of neural network methodology in order to reduce the computation time of feature matching. The features extracted are invariant to image scale and rotation, and different experiments were conducted to evaluate the performance of feature matching between successive video frames. The extracted features are assigned distance based on the Kinect technology that can be used by the robot in order to determine the path of navigation, along with obstacle detection applications.

Finite Group Invariance and Solution of Jaynes-Cummings Hamiltonian

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

Haydargil, Derya; Koc, Ramazan

2004-10-04

The finite group invariance of the E x {beta} and Jaynes-Cummings models are studied. A method is presented to obtain finite group invariance of the E x {beta} system.A suitable transformation of a Jaynes-Cummings Hamiltonian leads to equivalence of E x {beta} system. Then a general method is applied to obtain the solution of Jaynes-Cummings Hamiltonian with Kerr nonlinearity. Number operator for this structure and the generators of su(2) algebra are used to find the eigenvalues of the Jaynes-Cummings Hamiltonian for different states. By using the invariance of number operator the solution of modified Jaynes-Cummings Hamiltonian is also discussed.

FOCUSR: Feature Oriented Correspondence using Spectral Regularization–A Method for Precise Surface Matching

PubMed Central

Lombaert, Herve; Grady, Leo; Polimeni, Jonathan R.; Cheriet, Farida

2013-01-01

Existing methods for surface matching are limited by the trade-off between precision and computational efficiency. Here we present an improved algorithm for dense vertex-to-vertex correspondence that uses direct matching of features defined on a surface and improves it by using spectral correspondence as a regularization. This algorithm has the speed of both feature matching and spectral matching while exhibiting greatly improved precision (distance errors of 1.4%). The method, FOCUSR, incorporates implicitly such additional features to calculate the correspondence and relies on the smoothness of the lowest-frequency harmonics of a graph Laplacian to spatially regularize the features. In its simplest form, FOCUSR is an improved spectral correspondence method that nonrigidly deforms spectral embeddings. We provide here a full realization of spectral correspondence where virtually any feature can be used as additional information using weights on graph edges, but also on graph nodes and as extra embedded coordinates. As an example, the full power of FOCUSR is demonstrated in a real case scenario with the challenging task of brain surface matching across several individuals. Our results show that combining features and regularizing them in a spectral embedding greatly improves the matching precision (to a sub-millimeter level) while performing at much greater speed than existing methods. PMID:23868776

Passive estimation of the waveguide invariant per pair of modes.

PubMed

Le Gall, Yann; Bonnel, Julien

2013-08-01

In many oceanic waveguides, acoustic propagation is characterized by a parameter called waveguide invariant. This property is used in many passive and active sonar applications where knowledge of the waveguide invariant value is required. The waveguide invariant is classically considered as scalar but several studies show that it is better modeled by a distribution because of its dependence on frequency and mode pairs. This paper presents a new method for estimating the waveguide invariant distribution. Using the noise radiated by a distant ship and a single hydrophone, the proposed methodology allows estimating the waveguide invariant for each pair of modes in shallow water. Performance is evaluated on simulated data.

Evaluation of Deep Learning Based Stereo Matching Methods: from Ground to Aerial Images

NASA Astrophysics Data System (ADS)

Liu, J.; Ji, S.; Zhang, C.; Qin, Z.

2018-05-01

Dense stereo matching has been extensively studied in photogrammetry and computer vision. In this paper we evaluate the application of deep learning based stereo methods, which were raised from 2016 and rapidly spread, on aerial stereos other than ground images that are commonly used in computer vision community. Two popular methods are evaluated. One learns matching cost with a convolutional neural network (known as MC-CNN); the other produces a disparity map in an end-to-end manner by utilizing both geometry and context (known as GC-net). First, we evaluate the performance of the deep learning based methods for aerial stereo images by a direct model reuse. The models pre-trained on KITTI 2012, KITTI 2015 and Driving datasets separately, are directly applied to three aerial datasets. We also give the results of direct training on target aerial datasets. Second, the deep learning based methods are compared to the classic stereo matching method, Semi-Global Matching(SGM), and a photogrammetric software, SURE, on the same aerial datasets. Third, transfer learning strategy is introduced to aerial image matching based on the assumption of a few target samples available for model fine tuning. It experimentally proved that the conventional methods and the deep learning based methods performed similarly, and the latter had greater potential to be explored.

Blind readers break mirror invariance as sighted do.

PubMed

de Heering, Adélaïde; Collignon, Olivier; Kolinsky, Régine

2018-04-01

Mirror invariance refers to a predisposition of humans, including infants and animals, which urge them to consider mirrored images as corresponding to the same object. Yet in order to learn to read a written system that incorporates mirrored letters (e.g., vs. in the Latin alphabet), humans learn to break this perceptual bias. Here we examined the role visual experience and input modality play in the emergence of this bias. To this end, we tested congenital blind (CB) participants in two same-different tactile comparison tasks including pairs of mirrored and non-mirrored Braille letters as well as embossed unfamiliar geometric shapes and Latin letters, and compared their results to those of age-matched sighted participants involved in similar but visually-presented tasks. Sighted participants showed a classical pattern of results for their material of expertise, Latin letters. CB's results signed for their expertise with the Braille script compared to the other two materials that they processed according to an internal frame of reference. They also evidenced that they automatically break mirror invariance for different materials explored through the tactile modality, including Braille letters. Altogether, these results demonstrate that learning to read Braille through the tactile modality allows breaking mirror invariance in a comparable way to what is observed in sighted individuals for the mirrored letters of the Latin alphabet. Copyright © 2018 Elsevier Ltd. All rights reserved.

Metric invariance in object recognition: a review and further evidence.

PubMed

Cooper, E E; Biederman, I; Hummel, J E

1992-06-01

Phenomenologically, human shape recognition appears to be invariant with changes of orientation in depth (up to parts occlusion), position in the visual field, and size. Recent versions of template theories (e.g., Ullman, 1989; Lowe, 1987) assume that these invariances are achieved through the application of transformations such as rotation, translation, and scaling of the image so that it can be matched metrically to a stored template. Presumably, such transformations would require time for their execution. We describe recent priming experiments in which the effects of a prior brief presentation of an image on its subsequent recognition are assessed. The results of these experiments indicate that the invariance is complete: The magnitude of visual priming (as distinct from name or basic level concept priming) is not affected by a change in position, size, orientation in depth, or the particular lines and vertices present in the image, as long as representations of the same components can be activated. An implemented seven layer neural network model (Hummel & Biederman, 1992) that captures these fundamental properties of human object recognition is described. Given a line drawing of an object, the model activates a viewpoint-invariant structural description of the object, specifying its parts and their interrelations. Visual priming is interpreted as a change in the connection weights for the activation of: a) cells, termed geon feature assemblies (GFAs), that conjoin the output of units that represent invariant, independent properties of a single geon and its relations (such as its type, aspect ratio, relations to other geons), or b) a change in the connection weights by which several GFAs activate a cell representing an object.

Potential energy surface fitting by a statistically localized, permutationally invariant, local interpolating moving least squares method for the many-body potential: Method and application to N{sub 4}

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

Bender, Jason D.; Doraiswamy, Sriram; Candler, Graham V., E-mail: truhlar@umn.edu, E-mail: candler@aem.umn.edu

2014-02-07

Fitting potential energy surfaces to analytic forms is an important first step for efficient molecular dynamics simulations. Here, we present an improved version of the local interpolating moving least squares method (L-IMLS) for such fitting. Our method has three key improvements. First, pairwise interactions are modeled separately from many-body interactions. Second, permutational invariance is incorporated in the basis functions, using permutationally invariant polynomials in Morse variables, and in the weight functions. Third, computational cost is reduced by statistical localization, in which we statistically correlate the cutoff radius with data point density. We motivate our discussion in this paper with amore » review of global and local least-squares-based fitting methods in one dimension. Then, we develop our method in six dimensions, and we note that it allows the analytic evaluation of gradients, a feature that is important for molecular dynamics. The approach, which we call statistically localized, permutationally invariant, local interpolating moving least squares fitting of the many-body potential (SL-PI-L-IMLS-MP, or, more simply, L-IMLS-G2), is used to fit a potential energy surface to an electronic structure dataset for N{sub 4}. We discuss its performance on the dataset and give directions for further research, including applications to trajectory calculations.« less

Retrieving quasi-phase-matching structure with discrete layer-peeling method.

PubMed

Zhang, Q W; Zeng, X L; Wang, M; Wang, T Y; Chen, X F

2012-07-02

An approach to reconstruct a quasi-phase-matching grating by using a discrete layer-peeling algorithm is presented. Experimentally measured output spectra of Šolc-type filters, based on uniform and chirped QPM structures, are used in the discrete layer-peeling algorithm. The reconstructed QPM structures are in agreement with the exact structures used in the experiment and the method is verified to be accurate and efficient in quality inspection on quasi-phase-matching grating.

Reducing preference reversals: The role of preference imprecision and nontransparent methods.

PubMed

Pinto-Prades, José Luis; Sánchez-Martínez, Fernando Ignacio; Abellán-Perpiñán, José María; Martínez-Pérez, Jorge E

2018-05-16

Preferences elicited with matching and choice usually diverge (as characterised by preference reversals), violating a basic rationality requirement, namely, procedure invariance. We report the results of an experiment that shows that preference reversals between matching (Standard Gamble in our case) and choice are reduced when the matching task is conducted using nontransparent methods. Our results suggest that techniques based on nontransparent methods are less influenced by biases (i.e., compatibility effects) than transparent methods. We also observe that imprecision of preferences influences the degree of preference reversals. The preference reversal phenomenon is less strong in subjects with more precise preferences. Copyright © 2018 John Wiley & Sons, Ltd.

Defending the beauty of the Invariance Principle

NASA Astrophysics Data System (ADS)

Barkana, Itzhak

2014-01-01

Customary stability analysis methods for nonlinear nonautonomous systems seem to require a strict condition of uniform continuity. Although extensions of LaSalle's Invariance Principle to nonautonomous systems that mitigate this condition have been available for a long time, they have remained surprisingly unknown or open to misinterpretations. The large scope of the Principle might have misled the prospective users and its application to Control problems has been received with amazing yet clear uneasiness. Counterexamples have been used in order to claim that the Invariance Principle cannot be applied to nonlinear nonautonomous systems. Because the original formulation of the Invariance Principle still imposes conditions that are not necessarily needed, this paper presents a new Invariance Principle that further mitigates previous conditions and thus further expands the scope of stability analysis. A brief comparative review of various alternatives to stability analysis of nonautonomous nonlinear systems and their implications is also presented in order to illustrate that thorough analysis of same examples may actually confirm the efficiency of the Invariance Principle approach when dealing with stability of nonautonomous nonlinear systems problems that may look difficult or even unsolvable otherwise.

Convex Graph Invariants

DTIC Science & Technology

2010-12-02

Motzkin, T. and Straus, E. (1965). Maxima for graphs and a new proof of a theorem of Turan . Canad. J. Math. 17 533–540. [33] Rendl, F. and Sotirov, R...Convex Graph Invariants Venkat Chandrasekaran, Pablo A . Parrilo, and Alan S. Willsky ∗ Laboratory for Information and Decision Systems Department of...this paper we study convex graph invariants, which are graph invariants that are convex functions of the adjacency matrix of a graph. Some examples

Poor textural image tie point matching via graph theory

NASA Astrophysics Data System (ADS)

Yuan, Xiuxiao; Chen, Shiyu; Yuan, Wei; Cai, Yang

2017-07-01

Feature matching aims to find corresponding points to serve as tie points between images. Robust matching is still a challenging task when input images are characterized by low contrast or contain repetitive patterns, occlusions, or homogeneous textures. In this paper, a novel feature matching algorithm based on graph theory is proposed. This algorithm integrates both geometric and radiometric constraints into an edge-weighted (EW) affinity tensor. Tie points are then obtained by high-order graph matching. Four pairs of poor textural images covering forests, deserts, bare lands, and urban areas are tested. For comparison, three state-of-the-art matching techniques, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), and features from accelerated segment test (FAST), are also used. The experimental results show that the matching recall obtained by SIFT, SURF, and FAST varies from 0 to 35% in different types of poor textures. However, through the integration of both geometry and radiometry and the EW strategy, the recall obtained by the proposed algorithm is better than 50% in all four image pairs. The better matching recall improves the number of correct matches, dispersion, and positional accuracy.

Bifurcation from an invariant to a non-invariant attractor

NASA Astrophysics Data System (ADS)

Mandal, D.

2016-12-01

Switching dynamical systems are very common in many areas of physics and engineering. We consider a piecewise linear map that periodically switches between more than one different functional forms. We show that in such systems it is possible to have a border collision bifurcation where the system transits from an invariant attractor to a non-invariant attractor.

A Novel Real-Time Reference Key Frame Scan Matching Method

PubMed Central

Mohamed, Haytham; Moussa, Adel; Elhabiby, Mohamed; El-Sheimy, Naser; Sesay, Abu

2017-01-01

Unmanned aerial vehicles represent an effective technology for indoor search and rescue operations. Typically, most indoor missions’ environments would be unknown, unstructured, and/or dynamic. Navigation of UAVs in such environments is addressed by simultaneous localization and mapping approach using either local or global approaches. Both approaches suffer from accumulated errors and high processing time due to the iterative nature of the scan matching method. Moreover, point-to-point scan matching is prone to outlier association processes. This paper proposes a low-cost novel method for 2D real-time scan matching based on a reference key frame (RKF). RKF is a hybrid scan matching technique comprised of feature-to-feature and point-to-point approaches. This algorithm aims at mitigating errors accumulation using the key frame technique, which is inspired from video streaming broadcast process. The algorithm depends on the iterative closest point algorithm during the lack of linear features which is typically exhibited in unstructured environments. The algorithm switches back to the RKF once linear features are detected. To validate and evaluate the algorithm, the mapping performance and time consumption are compared with various algorithms in static and dynamic environments. The performance of the algorithm exhibits promising navigational, mapping results and very short computational time, that indicates the potential use of the new algorithm with real-time systems. PMID:28481285

A Novel Real-Time Reference Key Frame Scan Matching Method.

PubMed

Mohamed, Haytham; Moussa, Adel; Elhabiby, Mohamed; El-Sheimy, Naser; Sesay, Abu

2017-05-07

Unmanned aerial vehicles represent an effective technology for indoor search and rescue operations. Typically, most indoor missions' environments would be unknown, unstructured, and/or dynamic. Navigation of UAVs in such environments is addressed by simultaneous localization and mapping approach using either local or global approaches. Both approaches suffer from accumulated errors and high processing time due to the iterative nature of the scan matching method. Moreover, point-to-point scan matching is prone to outlier association processes. This paper proposes a low-cost novel method for 2D real-time scan matching based on a reference key frame (RKF). RKF is a hybrid scan matching technique comprised of feature-to-feature and point-to-point approaches. This algorithm aims at mitigating errors accumulation using the key frame technique, which is inspired from video streaming broadcast process. The algorithm depends on the iterative closest point algorithm during the lack of linear features which is typically exhibited in unstructured environments. The algorithm switches back to the RKF once linear features are detected. To validate and evaluate the algorithm, the mapping performance and time consumption are compared with various algorithms in static and dynamic environments. The performance of the algorithm exhibits promising navigational, mapping results and very short computational time, that indicates the potential use of the new algorithm with real-time systems.

Tests of Lorentz invariance with atomic clocks

NASA Astrophysics Data System (ADS)

Mohan, Lakshmi

Lorentz invariance has been the cornerstone of special relativity. Recent theories have been proposed which suggest violations of Lorentz invariance. Experiments have been conducted using clocks that place the strictest limits on these theories. The thesis focuses on the Mansouri and Sexl formulation and I calculate using this framework the Doppler effect, Compton effect, Maxwell's equations, Hydrogen energy levels and other effects. I conclude the thesis by suggesting a possible method of testing my results using atomic clocks.

Consensus of satellite cluster flight using an energy-matching optimal control method

NASA Astrophysics Data System (ADS)

Luo, Jianjun; Zhou, Liang; Zhang, Bo

2017-11-01

This paper presents an optimal control method for consensus of satellite cluster flight under a kind of energy matching condition. Firstly, the relation between energy matching and satellite periodically bounded relative motion is analyzed, and the satellite energy matching principle is applied to configure the initial conditions. Then, period-delayed errors are adopted as state variables to establish the period-delayed errors dynamics models of a single satellite and the cluster. Next a novel satellite cluster feedback control protocol with coupling gain is designed, so that the satellite cluster periodically bounded relative motion consensus problem (period-delayed errors state consensus problem) is transformed to the stability of a set of matrices with the same low dimension. Based on the consensus region theory in the research of multi-agent system consensus issues, the coupling gain can be obtained to satisfy the requirement of consensus region and decouple the satellite cluster information topology and the feedback control gain matrix, which can be determined by Linear quadratic regulator (LQR) optimal method. This method can realize the consensus of satellite cluster period-delayed errors, leading to the consistency of semi-major axes (SMA) and the energy-matching of satellite cluster. Then satellites can emerge the global coordinative cluster behavior. Finally the feasibility and effectiveness of the present energy-matching optimal consensus for satellite cluster flight is verified through numerical simulations.

Multiple objects tracking with HOGs matching in circular windows

NASA Astrophysics Data System (ADS)

Miramontes-Jaramillo, Daniel; Kober, Vitaly; Díaz-Ramírez, Víctor H.

2014-09-01

In recent years tracking applications with development of new technologies like smart TVs, Kinect, Google Glass and Oculus Rift become very important. When tracking uses a matching algorithm, a good prediction algorithm is required to reduce the search area for each object to be tracked as well as processing time. In this work, we analyze the performance of different tracking algorithms based on prediction and matching for a real-time tracking multiple objects. The used matching algorithm utilizes histograms of oriented gradients. It carries out matching in circular windows, and possesses rotation invariance and tolerance to viewpoint and scale changes. The proposed algorithm is implemented in a personal computer with GPU, and its performance is analyzed in terms of processing time in real scenarios. Such implementation takes advantage of current technologies and helps to process video sequences in real-time for tracking several objects at the same time.

A Real-Time Infrared Ultra-Spectral Signature Classification Method via Spatial Pyramid Matching

PubMed Central

Mei, Xiaoguang; Ma, Yong; Li, Chang; Fan, Fan; Huang, Jun; Ma, Jiayi

2015-01-01

The state-of-the-art ultra-spectral sensor technology brings new hope for high precision applications due to its high spectral resolution. However, it also comes with new challenges, such as the high data dimension and noise problems. In this paper, we propose a real-time method for infrared ultra-spectral signature classification via spatial pyramid matching (SPM), which includes two aspects. First, we introduce an infrared ultra-spectral signature similarity measure method via SPM, which is the foundation of the matching-based classification method. Second, we propose the classification method with reference spectral libraries, which utilizes the SPM-based similarity for the real-time infrared ultra-spectral signature classification with robustness performance. Specifically, instead of matching with each spectrum in the spectral library, our method is based on feature matching, which includes a feature library-generating phase. We calculate the SPM-based similarity between the feature of the spectrum and that of each spectrum of the reference feature library, then take the class index of the corresponding spectrum having the maximum similarity as the final result. Experimental comparisons on two publicly-available datasets demonstrate that the proposed method effectively improves the real-time classification performance and robustness to noise. PMID:26205263

Preliminary evaluation of a gel tube agglutination major cross-match method in dogs.

PubMed

Villarnovo, Dania; Burton, Shelley A; Horney, Barbara S; MacKenzie, Allan L; Vanderstichel, Raphaël

2016-09-01

A major cross-match gel tube test is available for use in dogs yet has not been clinically evaluated. This study compared cross-match results obtained using the gel tube and the standard tube methods for canine samples. Study 1 included 107 canine sample donor-recipient pairings cross-match tested with the RapidVet-H method gel tube test and compared results with the standard tube method. Additionally, 120 pairings using pooled sera containing anti-canine erythrocyte antibody at various concentrations were tested with leftover blood from a hospital population to assess sensitivity and specificity of the gel tube method in comparison with the standard method. The gel tube method had a good relative specificity of 96.1% in detecting lack of agglutination (compatibility) compared to the standard tube method. Agreement between the 2 methods was moderate. Nine of 107 pairings showed agglutination/incompatibility on either test, too few to allow reliable calculation of relative sensitivity. Fifty percent of the gel tube method results were difficult to interpret due to sample spreading in the reaction and/or negative control tubes. The RapidVet-H method agreed with the standard cross-match method on compatible samples, but detected incompatibility in some sample pairs that were compatible with the standard method. Evaluation using larger numbers of incompatible pairings is needed to assess diagnostic utility. The gel tube method results were difficult to categorize due to sample spreading. Weak agglutination reactions or other factors such as centrifuge model may be responsible. © 2016 American Society for Veterinary Clinical Pathology.

Robust Frequency Invariant Beamforming with Low Sidelobe for Speech Enhancement

NASA Astrophysics Data System (ADS)

Zhu, Yiting; Pan, Xiang

2018-01-01

Frequency invariant beamformers (FIBs) are widely used in speech enhancement and source localization. There are two traditional optimization methods for FIB design. The first one is convex optimization, which is simple but the frequency invariant characteristic of the beam pattern is poor with respect to frequency band of five octaves. The least squares (LS) approach using spatial response variation (SRV) constraint is another optimization method. Although, it can provide good frequency invariant property, it usually couldn’t be used in speech enhancement for its lack of weight norm constraint which is related to the robustness of a beamformer. In this paper, a robust wideband beamforming method with a constant beamwidth is proposed. The frequency invariant beam pattern is achieved by resolving an optimization problem of the SRV constraint to cover speech frequency band. With the control of sidelobe level, it is available for the frequency invariant beamformer (FIB) to prevent distortion of interference from the undesirable direction. The approach is completed in time-domain by placing tapped delay lines(TDL) and finite impulse response (FIR) filter at the output of each sensor which is more convenient than the Frost processor. By invoking the weight norm constraint, the robustness of the beamformer is further improved against random errors. Experiment results show that the proposed method has a constant beamwidth and almost the same white noise gain as traditional delay-and-sum (DAS) beamformer.

Fired Cartridge Case Identification Using Optical Images and the Congruent Matching Cells (CMC) Method.

PubMed

Tong, Mingsi; Song, John; Chu, Wei; Thompson, Robert M

2014-01-01

The Congruent Matching Cells (CMC) method for ballistics identification was invented at the National Institute of Standards and Technology (NIST). The CMC method is based on the correlation of pairs of small correlation cells instead of the correlation of entire images. Four identification parameters - T CCF, T θ, T x and T y are proposed for identifying correlated cell pairs originating from the same firearm. The correlation conclusion (matching or non-matching) is determined by whether the number of CMC is ≥ 6. This method has been previously validated using a set of 780 pair-wise 3D topography images. However, most ballistic images stored in current local and national databases are in an optical intensity (grayscale) format. As a result, the reliability of applying the CMC method on optical intensity images is an important issue. In this paper, optical intensity images of breech face impressions captured on the same set of 40 cartridge cases are correlated and analyzed for the validation test of CMC method using optical images. This includes correlations of 63 pairs of matching images and 717 pairs of non-matching images under top ring lighting. Tests of the method do not produce any false identification (false positive) or false exclusion (false negative) results, which support the CMC method and the proposed identification criterion, C = 6, for firearm breech face identifications using optical intensity images.

Fired Cartridge Case Identification Using Optical Images and the Congruent Matching Cells (CMC) Method

PubMed Central

Tong, Mingsi; Song, John; Chu, Wei; Thompson, Robert M

2014-01-01

The Congruent Matching Cells (CMC) method for ballistics identification was invented at the National Institute of Standards and Technology (NIST). The CMC method is based on the correlation of pairs of small correlation cells instead of the correlation of entire images. Four identification parameters – TCCF, Tθ, Tx and Ty are proposed for identifying correlated cell pairs originating from the same firearm. The correlation conclusion (matching or non-matching) is determined by whether the number of CMC is ≥ 6. This method has been previously validated using a set of 780 pair-wise 3D topography images. However, most ballistic images stored in current local and national databases are in an optical intensity (grayscale) format. As a result, the reliability of applying the CMC method on optical intensity images is an important issue. In this paper, optical intensity images of breech face impressions captured on the same set of 40 cartridge cases are correlated and analyzed for the validation test of CMC method using optical images. This includes correlations of 63 pairs of matching images and 717 pairs of non-matching images under top ring lighting. Tests of the method do not produce any false identification (false positive) or false exclusion (false negative) results, which support the CMC method and the proposed identification criterion, C = 6, for firearm breech face identifications using optical intensity images. PMID:26601045

Slow feature analysis: unsupervised learning of invariances.

PubMed

Wiskott, Laurenz; Sejnowski, Terrence J

2002-04-01

Invariant features of temporally varying signals are useful for analysis and classification. Slow feature analysis (SFA) is a new method for learning invariant or slowly varying features from a vectorial input signal. It is based on a nonlinear expansion of the input signal and application of principal component analysis to this expanded signal and its time derivative. It is guaranteed to find the optimal solution within a family of functions directly and can learn to extract a large number of decorrelated features, which are ordered by their degree of invariance. SFA can be applied hierarchically to process high-dimensional input signals and extract complex features. SFA is applied first to complex cell tuning properties based on simple cell output, including disparity and motion. Then more complicated input-output functions are learned by repeated application of SFA. Finally, a hierarchical network of SFA modules is presented as a simple model of the visual system. The same unstructured network can learn translation, size, rotation, contrast, or, to a lesser degree, illumination invariance for one-dimensional objects, depending on only the training stimulus. Surprisingly, only a few training objects suffice to achieve good generalization to new objects. The generated representation is suitable for object recognition. Performance degrades if the network is trained to learn multiple invariances simultaneously.

An Application of Rotation- and Translation-Invariant Overcomplete Wavelets to the registration of Remotely Sensed Imagery

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline; Zavorine, Ilya

1999-01-01

A wavelet-based image registration approach has previously been proposed by the authors. In this work, wavelet coefficient maxima obtained from an orthogonal wavelet decomposition using Daubechies filters were utilized to register images in a multi-resolution fashion. Tested on several remote sensing datasets, this method gave very encouraging results. Despite the lack of translation-invariance of these filters, we showed that when using cross-correlation as a feature matching technique, features of size larger than twice the size of the filters are correctly registered by using the low-frequency subbands of the Daubechies wavelet decomposition. Nevertheless, high-frequency subbands are still sensitive to translation effects. In this work, we are considering a rotation- and translation-invariant representation developed by E. Simoncelli and integrate it in our image registration scheme. The two types of filters, Daubechies and Simoncelli filters, are then being compared from a registration point of view, utilizing synthetic data as well as data from the Landsat/ Thematic Mapper (TM) and from the NOAA Advanced Very High Resolution Radiometer (AVHRR).

An Application of Rotation- and Translation-Invariant Overcomplete Wavelets to the Registration of Remotely Sensed Imagery

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline; Zavorine, Ilya

1999-01-01

A wavelet-based image registration approach has previously been proposed by the authors. In this work, wavelet coefficient maxima obtained from an orthogonal wavelet decomposition using Daubechies filters were utilized to register images in a multi-resolution fashion. Tested on several remote sensing datasets, this method gave very encouraging results. Despite the lack of translation-invariance of these filters, we showed that when using cross-correlation as a feature matching technique, features of size larger than twice the size of the filters are correctly registered by using the low-frequency subbands of the Daubechies wavelet decomposition. Nevertheless, high-frequency subbands are still sensitive to translation effects. In this work, we are considering a rotation- and translation-invariant representation developed by E. Simoncelli and integrate it in our image registration scheme. The two types of filters, Daubechies and Simoncelli filters, are then being compared from a registration point of view, utilizing synthetic data as well as data from the Landsat/ Thematic Mapper (TM) and from the NOAA Advanced Very High Resolution Radiometer (AVHRR).

Image quality enhancement method for on-orbit remote sensing cameras using invariable modulation transfer function.

PubMed

Li, Jin; Liu, Zilong

2017-07-24

Remote sensing cameras in the visible/near infrared range are essential tools in Earth-observation, deep-space exploration, and celestial navigation. Their imaging performance, i.e. image quality here, directly determines the target-observation performance of a spacecraft, and even the successful completion of a space mission. Unfortunately, the camera itself, such as a optical system, a image sensor, and a electronic system, limits the on-orbit imaging performance. Here, we demonstrate an on-orbit high-resolution imaging method based on the invariable modulation transfer function (IMTF) of cameras. The IMTF, which is stable and invariable to the changing of ground targets, atmosphere, and environment on orbit or on the ground, depending on the camera itself, is extracted using a pixel optical focal-plane (PFP). The PFP produces multiple spatial frequency targets, which are used to calculate the IMTF at different frequencies. The resulting IMTF in combination with a constrained least-squares filter compensates for the IMTF, which represents the removal of the imaging effects limited by the camera itself. This method is experimentally confirmed. Experiments on an on-orbit panchromatic camera indicate that the proposed method increases 6.5 times of the average gradient, 3.3 times of the edge intensity, and 1.56 times of the MTF value compared to the case when IMTF is not used. This opens a door to push the limitation of a camera itself, enabling high-resolution on-orbit optical imaging.

Dimensional analysis using toric ideals: primitive invariants.

PubMed

Atherton, Mark A; Bates, Ronald A; Wynn, Henry P

2014-01-01

Classical dimensional analysis in its original form starts by expressing the units for derived quantities, such as force, in terms of power products of basic units [Formula: see text] etc. This suggests the use of toric ideal theory from algebraic geometry. Within this the Graver basis provides a unique primitive basis in a well-defined sense, which typically has more terms than the standard Buckingham approach. Some textbook examples are revisited and the full set of primitive invariants found. First, a worked example based on convection is introduced to recall the Buckingham method, but using computer algebra to obtain an integer [Formula: see text] matrix from the initial integer [Formula: see text] matrix holding the exponents for the derived quantities. The [Formula: see text] matrix defines the dimensionless variables. But, rather than this integer linear algebra approach it is shown how, by staying with the power product representation, the full set of invariants (dimensionless groups) is obtained directly from the toric ideal defined by [Formula: see text]. One candidate for the set of invariants is a simple basis of the toric ideal. This, although larger than the rank of [Formula: see text], is typically not unique. However, the alternative Graver basis is unique and defines a maximal set of invariants, which are primitive in a simple sense. In addition to the running example four examples are taken from: a windmill, convection, electrodynamics and the hydrogen atom. The method reveals some named invariants. A selection of computer algebra packages is used to show the considerable ease with which both a simple basis and a Graver basis can be found.

Estimating the Counterfactual Impact of Conservation Programs on Land Cover Outcomes: The Role of Matching and Panel Regression Techniques.

PubMed

Jones, Kelly W; Lewis, David J

2015-01-01

Deforestation and conversion of native habitats continues to be the leading driver of biodiversity and ecosystem service loss. A number of conservation policies and programs are implemented--from protected areas to payments for ecosystem services (PES)--to deter these losses. Currently, empirical evidence on whether these approaches stop or slow land cover change is lacking, but there is increasing interest in conducting rigorous, counterfactual impact evaluations, especially for many new conservation approaches, such as PES and REDD, which emphasize additionality. In addition, several new, globally available and free high-resolution remote sensing datasets have increased the ease of carrying out an impact evaluation on land cover change outcomes. While the number of conservation evaluations utilizing 'matching' to construct a valid control group is increasing, the majority of these studies use simple differences in means or linear cross-sectional regression to estimate the impact of the conservation program using this matched sample, with relatively few utilizing fixed effects panel methods--an alternative estimation method that relies on temporal variation in the data. In this paper we compare the advantages and limitations of (1) matching to construct the control group combined with differences in means and cross-sectional regression, which control for observable forms of bias in program evaluation, to (2) fixed effects panel methods, which control for observable and time-invariant unobservable forms of bias, with and without matching to create the control group. We then use these four approaches to estimate forest cover outcomes for two conservation programs: a PES program in Northeastern Ecuador and strict protected areas in European Russia. In the Russia case we find statistically significant differences across estimators--due to the presence of unobservable bias--that lead to differences in conclusions about effectiveness. The Ecuador case illustrates that

Invariant visual object recognition: a model, with lighting invariance.

PubMed

Rolls, Edmund T; Stringer, Simon M

2006-01-01

How are invariant representations of objects formed in the visual cortex? We describe a neurophysiological and computational approach which focusses on a feature hierarchy model in which invariant representations can be built by self-organizing learning based on the statistics of the visual input. The model can use temporal continuity in an associative synaptic learning rule with a short term memory trace, and/or it can use spatial continuity in Continuous Transformation learning. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and in this paper we show also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in for example spatial and object search tasks. The model has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene.

A two-step database search method improves sensitivity in peptide sequence matches for metaproteomics and proteogenomics studies.

PubMed

Jagtap, Pratik; Goslinga, Jill; Kooren, Joel A; McGowan, Thomas; Wroblewski, Matthew S; Seymour, Sean L; Griffin, Timothy J

2013-04-01

Large databases (>10(6) sequences) used in metaproteomic and proteogenomic studies present challenges in matching peptide sequences to MS/MS data using database-search programs. Most notably, strict filtering to avoid false-positive matches leads to more false negatives, thus constraining the number of peptide matches. To address this challenge, we developed a two-step method wherein matches derived from a primary search against a large database were used to create a smaller subset database. The second search was performed against a target-decoy version of this subset database merged with a host database. High confidence peptide sequence matches were then used to infer protein identities. Applying our two-step method for both metaproteomic and proteogenomic analysis resulted in twice the number of high confidence peptide sequence matches in each case, as compared to the conventional one-step method. The two-step method captured almost all of the same peptides matched by the one-step method, with a majority of the additional matches being false negatives from the one-step method. Furthermore, the two-step method improved results regardless of the database search program used. Our results show that our two-step method maximizes the peptide matching sensitivity for applications requiring large databases, especially valuable for proteogenomics and metaproteomics studies. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Distinctive Feature Extraction for Indian Sign Language (ISL) Gesture using Scale Invariant Feature Transform (SIFT)

NASA Astrophysics Data System (ADS)

Patil, Sandeep Baburao; Sinha, G. R.

2017-02-01

India, having less awareness towards the deaf and dumb peoples leads to increase the communication gap between deaf and hard hearing community. Sign language is commonly developed for deaf and hard hearing peoples to convey their message by generating the different sign pattern. The scale invariant feature transform was introduced by David Lowe to perform reliable matching between different images of the same object. This paper implements the various phases of scale invariant feature transform to extract the distinctive features from Indian sign language gestures. The experimental result shows the time constraint for each phase and the number of features extracted for 26 ISL gestures.

Research on Matching Method of Power Supply Parameters for Dual Energy Source Electric Vehicles

NASA Astrophysics Data System (ADS)

Jiang, Q.; Luo, M. J.; Zhang, S. K.; Liao, M. W.

2018-03-01

A new type of power source is proposed, which is based on the traffic signal matching method of the dual energy source power supply composed of the batteries and the supercapacitors. First, analyzing the power characteristics is required to meet the excellent dynamic characteristics of EV, studying the energy characteristics is required to meet the mileage requirements and researching the physical boundary characteristics is required to meet the physical conditions of the power supply. Secondly, the parameter matching design with the highest energy efficiency is adopted to select the optimal parameter group with the method of matching deviation. Finally, the simulation analysis of the vehicle is carried out in MATLABSimulink, The mileage and energy efficiency of dual energy sources are analyzed in different parameter models, and the rationality of the matching method is verified.

Identification Male Fertility Through Abnormalities Sperm Based Morphology (Teratospermia) using Invariant Moment Method

NASA Astrophysics Data System (ADS)

Syahputra, M. F.; Chairani, R.; Seniman; Rahmat, R. F.; Abdullah, D.; Napitupulu, D.; Setiawan, M. I.; Albra, W.; Erliana, C. I.; Andayani, U.

2018-03-01

Sperm morphology is still a standard laboratory analysis in diagnosing infertility in men. Manually identification of sperm form is still not accurate, the difficulty in seeing the form of the invisible sperm from the digital microscope image is often a weakness in the process of identification and takes a long time. Therefore, male fertility identification application system is needed Through sperm abnormalities based on sperm morphology (teratospermia). The method used is invariant moment method. This study uses 15 data testing and 20 data training sperm image. That the process of male fertility identification through sperm abnormalities based on sperm morphology (teratospermia) has an accuracy rate of 80.77%. Use of time to process Identification of male fertility through sperm abnormalities Based on sperm morphology (teratospermia) during 0.4369 seconds.

MR Image Reconstruction Using Block Matching and Adaptive Kernel Methods.

PubMed

Schmidt, Johannes F M; Santelli, Claudio; Kozerke, Sebastian

2016-01-01

An approach to Magnetic Resonance (MR) image reconstruction from undersampled data is proposed. Undersampling artifacts are removed using an iterative thresholding algorithm applied to nonlinearly transformed image block arrays. Each block array is transformed using kernel principal component analysis where the contribution of each image block to the transform depends in a nonlinear fashion on the distance to other image blocks. Elimination of undersampling artifacts is achieved by conventional principal component analysis in the nonlinear transform domain, projection onto the main components and back-mapping into the image domain. Iterative image reconstruction is performed by interleaving the proposed undersampling artifact removal step and gradient updates enforcing consistency with acquired k-space data. The algorithm is evaluated using retrospectively undersampled MR cardiac cine data and compared to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT reconstruction. Evaluation of image quality and root-mean-squared-error (RMSE) reveal improved image reconstruction for up to 8-fold undersampled data with the proposed approach relative to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT. In conclusion, block matching and kernel methods can be used for effective removal of undersampling artifacts in MR image reconstruction and outperform methods using standard compressed sensing and ℓ1-regularized parallel imaging methods.

Galilean invariant resummation schemes of cosmological perturbations

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

Peloso, Marco; Pietroni, Massimo, E-mail: peloso@physics.umn.edu, E-mail: massimo.pietroni@unipr.it

2017-01-01

Many of the methods proposed so far to go beyond Standard Perturbation Theory break invariance under time-dependent boosts (denoted here as extended Galilean Invariance, or GI). This gives rise to spurious large scale effects which spoil the small scale predictions of these approximation schemes. By using consistency relations we derive fully non-perturbative constraints that GI imposes on correlation functions. We then introduce a method to quantify the amount of GI breaking of a given scheme, and to correct it by properly tailored counterterms. Finally, we formulate resummation schemes which are manifestly GI, discuss their general features, and implement them inmore » the so called Time-Flow, or TRG, equations.« less

Learning viewpoint invariant perceptual representations from cluttered images.

PubMed

Spratling, Michael W

2005-05-01

In order to perform object recognition, it is necessary to form perceptual representations that are sufficiently specific to distinguish between objects, but that are also sufficiently flexible to generalize across changes in location, rotation, and scale. A standard method for learning perceptual representations that are invariant to viewpoint is to form temporal associations across image sequences showing object transformations. However, this method requires that individual stimuli be presented in isolation and is therefore unlikely to succeed in real-world applications where multiple objects can co-occur in the visual input. This paper proposes a simple modification to the learning method that can overcome this limitation and results in more robust learning of invariant representations.

THTM: A template matching algorithm based on HOG descriptor and two-stage matching

NASA Astrophysics Data System (ADS)

Jiang, Yuanjie; Ruan, Li; Xiao, Limin; Liu, Xi; Yuan, Feng; Wang, Haitao

2018-04-01

We propose a novel method for template matching named THTM - a template matching algorithm based on HOG (histogram of gradient) and two-stage matching. We rely on the fast construction of HOG and the two-stage matching that jointly lead to a high accuracy approach for matching. TMTM give enough attention on HOG and creatively propose a twice-stage matching while traditional method only matches once. Our contribution is to apply HOG to template matching successfully and present two-stage matching, which is prominent to improve the matching accuracy based on HOG descriptor. We analyze key features of THTM and perform compared to other commonly used alternatives on a challenging real-world datasets. Experiments show that our method outperforms the comparison method.

Hydrograph matching method for measuring model performance

NASA Astrophysics Data System (ADS)

Ewen, John

2011-09-01

SummaryDespite all the progress made over the years on developing automatic methods for analysing hydrographs and measuring the performance of rainfall-runoff models, automatic methods cannot yet match the power and flexibility of the human eye and brain. Very simple approaches are therefore being developed that mimic the way hydrologists inspect and interpret hydrographs, including the way that patterns are recognised, links are made by eye, and hydrological responses and errors are studied and remembered. In this paper, a dynamic programming algorithm originally designed for use in data mining is customised for use with hydrographs. It generates sets of "rays" that are analogous to the visual links made by the hydrologist's eye when linking features or times in one hydrograph to the corresponding features or times in another hydrograph. One outcome from this work is a new family of performance measures called "visual" performance measures. These can measure differences in amplitude and timing, including the timing errors between simulated and observed hydrographs in model calibration. To demonstrate this, two visual performance measures, one based on the Nash-Sutcliffe Efficiency and the other on the mean absolute error, are used in a total of 34 split-sample calibration-validation tests for two rainfall-runoff models applied to the Hodder catchment, northwest England. The customised algorithm, called the Hydrograph Matching Algorithm, is very simple to apply; it is given in a few lines of pseudocode.

Developing a statistically powerful measure for quartet tree inference using phylogenetic identities and Markov invariants.

PubMed

Sumner, Jeremy G; Taylor, Amelia; Holland, Barbara R; Jarvis, Peter D

2017-12-01

Recently there has been renewed interest in phylogenetic inference methods based on phylogenetic invariants, alongside the related Markov invariants. Broadly speaking, both these approaches give rise to polynomial functions of sequence site patterns that, in expectation value, either vanish for particular evolutionary trees (in the case of phylogenetic invariants) or have well understood transformation properties (in the case of Markov invariants). While both approaches have been valued for their intrinsic mathematical interest, it is not clear how they relate to each other, and to what extent they can be used as practical tools for inference of phylogenetic trees. In this paper, by focusing on the special case of binary sequence data and quartets of taxa, we are able to view these two different polynomial-based approaches within a common framework. To motivate the discussion, we present three desirable statistical properties that we argue any invariant-based phylogenetic method should satisfy: (1) sensible behaviour under reordering of input sequences; (2) stability as the taxa evolve independently according to a Markov process; and (3) explicit dependence on the assumption of a continuous-time process. Motivated by these statistical properties, we develop and explore several new phylogenetic inference methods. In particular, we develop a statistically bias-corrected version of the Markov invariants approach which satisfies all three properties. We also extend previous work by showing that the phylogenetic invariants can be implemented in such a way as to satisfy property (3). A simulation study shows that, in comparison to other methods, our new proposed approach based on bias-corrected Markov invariants is extremely powerful for phylogenetic inference. The binary case is of particular theoretical interest as-in this case only-the Markov invariants can be expressed as linear combinations of the phylogenetic invariants. A wider implication of this is that, for

Feedback-Driven Dynamic Invariant Discovery

NASA Technical Reports Server (NTRS)

Zhang, Lingming; Yang, Guowei; Rungta, Neha S.; Person, Suzette; Khurshid, Sarfraz

2014-01-01

Program invariants can help software developers identify program properties that must be preserved as the software evolves, however, formulating correct invariants can be challenging. In this work, we introduce iDiscovery, a technique which leverages symbolic execution to improve the quality of dynamically discovered invariants computed by Daikon. Candidate invariants generated by Daikon are synthesized into assertions and instrumented onto the program. The instrumented code is executed symbolically to generate new test cases that are fed back to Daikon to help further re ne the set of candidate invariants. This feedback loop is executed until a x-point is reached. To mitigate the cost of symbolic execution, we present optimizations to prune the symbolic state space and to reduce the complexity of the generated path conditions. We also leverage recent advances in constraint solution reuse techniques to avoid computing results for the same constraints across iterations. Experimental results show that iDiscovery converges to a set of higher quality invariants compared to the initial set of candidate invariants in a small number of iterations.

An improved principal component analysis based region matching method for fringe direction estimation

NASA Astrophysics Data System (ADS)

He, A.; Quan, C.

2018-04-01

The principal component analysis (PCA) and region matching combined method is effective for fringe direction estimation. However, its mask construction algorithm for region matching fails in some circumstances, and the algorithm for conversion of orientation to direction in mask areas is computationally-heavy and non-optimized. We propose an improved PCA based region matching method for the fringe direction estimation, which includes an improved and robust mask construction scheme, and a fast and optimized orientation-direction conversion algorithm for the mask areas. Along with the estimated fringe direction map, filtered fringe pattern by automatic selective reconstruction modification and enhanced fast empirical mode decomposition (ASRm-EFEMD) is used for Hilbert spiral transform (HST) to demodulate the phase. Subsequently, windowed Fourier ridge (WFR) method is used for the refinement of the phase. The robustness and effectiveness of proposed method are demonstrated by both simulated and experimental fringe patterns.

Chaotic jumps in the generalized first adiabatic invariant in current sheets

NASA Technical Reports Server (NTRS)

Brittnacher, M. J.; Whipple, E. C.

1991-01-01

The present study examines how the changes in the generalized first adiabatic invariant J derived from the separatrix crossing theory can be incorporated into the drift variable approach to generating distribution functions. A method is proposed for determining distribution functions for an ensemble of particles following interaction with the tail current sheet by treating the interaction as a scattering problem characterized by changes in the invariant. Generalized drift velocities are obtained for a 1D tail configuration by using the generalized first invariant. The invariant remained constant except for the discrete changes caused by chaotic scattering as the particles cross the separatrix.

Effects of using a posteriori methods for the conservation of integral invariants. [for weather forecasting

NASA Technical Reports Server (NTRS)

Takacs, Lawrence L.

1988-01-01

The nature and effect of using a posteriori adjustments to nonconservative finite-difference schemes to enforce integral invariants of the corresponding analytic system are examined. The method of a posteriori integral constraint restoration is analyzed for the case of linear advection, and the harmonic response associated with the a posteriori adjustments is examined in detail. The conservative properties of the shallow water system are reviewed, and the constraint restoration algorithm applied to the shallow water equations are described. A comparison is made between forecasts obtained using implicit and a posteriori methods for the conservation of mass, energy, and potential enstrophy in the complete nonlinear shallow-water system.

Issues associated with Galilean invariance on a moving solid boundary in the lattice Boltzmann method

NASA Astrophysics Data System (ADS)

Peng, Cheng; Geneva, Nicholas; Guo, Zhaoli; Wang, Lian-Ping

2017-01-01

In lattice Boltzmann simulations involving moving solid boundaries, the momentum exchange between the solid and fluid phases was recently found to be not fully consistent with the principle of local Galilean invariance (GI) when the bounce-back schemes (BBS) and the momentum exchange method (MEM) are used. In the past, this inconsistency was resolved by introducing modified MEM schemes so that the overall moving-boundary algorithm could be more consistent with GI. However, in this paper we argue that the true origin of this violation of Galilean invariance (VGI) in the presence of a moving solid-fluid interface is due to the BBS itself, as the VGI error not only exists in the hydrodynamic force acting on the solid phase, but also in the boundary force exerted on the fluid phase, according to Newton's Third Law. The latter, however, has so far gone unnoticed in previously proposed modified MEM schemes. Based on this argument, we conclude that the previous modifications to the momentum exchange method are incomplete solutions to the VGI error in the lattice Boltzmann method (LBM). An implicit remedy to the VGI error in the LBM and its limitation is then revealed. To address the VGI error for a case when this implicit remedy does not exist, a bounce-back scheme based on coordinate transformation is proposed. Numerical tests in both laminar and turbulent flows show that the proposed scheme can effectively eliminate the errors associated with the usual bounce-back implementations on a no-slip solid boundary, and it can maintain an accurate momentum exchange calculation with minimal computational overhead.

Recognition Of Complex Three Dimensional Objects Using Three Dimensional Moment Invariants

NASA Astrophysics Data System (ADS)

Sadjadi, Firooz A.

1985-01-01

A technique for the recognition of complex three dimensional objects is presented. The complex 3-D objects are represented in terms of their 3-D moment invariants, algebraic expressions that remain invariant independent of the 3-D objects' orientations and locations in the field of view. The technique of 3-D moment invariants has been used successfully for simple 3-D object recognition in the past. In this work we have extended this method for the representation of more complex objects. Two complex objects are represented digitally; their 3-D moment invariants have been calculated, and then the invariancy of these 3-D invariant moment expressions is verified by changing the orientation and the location of the objects in the field of view. The results of this study have significant impact on 3-D robotic vision, 3-D target recognition, scene analysis and artificial intelligence.

A short feature vector for image matching: The Log-Polar Magnitude feature descriptor

PubMed Central

Hast, Anders; Wählby, Carolina; Sintorn, Ida-Maria

2017-01-01

The choice of an optimal feature detector-descriptor combination for image matching often depends on the application and the image type. In this paper, we propose the Log-Polar Magnitude feature descriptor—a rotation, scale, and illumination invariant descriptor that achieves comparable performance to SIFT on a large variety of image registration problems but with much shorter feature vectors. The descriptor is based on the Log-Polar Transform followed by a Fourier Transform and selection of the magnitude spectrum components. Selecting different frequency components allows optimizing for image patterns specific for a particular application. In addition, by relying only on coordinates of the found features and (optionally) feature sizes our descriptor is completely detector independent. We propose 48- or 56-long feature vectors that potentially can be shortened even further depending on the application. Shorter feature vectors result in better memory usage and faster matching. This combined with the fact that the descriptor does not require a time-consuming feature orientation estimation (the rotation invariance is achieved solely by using the magnitude spectrum of the Log-Polar Transform) makes it particularly attractive to applications with limited hardware capacity. Evaluation is performed on the standard Oxford dataset and two different microscopy datasets; one with fluorescence and one with transmission electron microscopy images. Our method performs better than SURF and comparable to SIFT on the Oxford dataset, and better than SIFT on both microscopy datasets indicating that it is particularly useful in applications with microscopy images. PMID:29190737

Invariants for models of interacting populations

NASA Astrophysics Data System (ADS)

Cairó, L.; Feix, M. R.; Goedert, J.

1989-10-01

The generalised Lotka-Volterra system is studied. We use a modification of the Carleman embedding method. The position of the equilibrium point, the possibility of obtaining invariants, the asymptotic cyclic motions and the connection to the Volterra model are discussed.

Invariant object recognition based on the generalized discrete radon transform

NASA Astrophysics Data System (ADS)

Easley, Glenn R.; Colonna, Flavia

2004-04-01

We introduce a method for classifying objects based on special cases of the generalized discrete Radon transform. We adjust the transform and the corresponding ridgelet transform by means of circular shifting and a singular value decomposition (SVD) to obtain a translation, rotation and scaling invariant set of feature vectors. We then use a back-propagation neural network to classify the input feature vectors. We conclude with experimental results and compare these with other invariant recognition methods.

Phylogenetic Invariants for Metazoan Mitochondrial Genome Evolution.

PubMed

Sankoff; Blanchette

1998-01-01

The method of phylogenetic invariants was developed to apply to aligned sequence data generated, according to a stochastic substitution model, for N species related through an unknown phylogenetic tree. The invariants are functions of the probabilities of the observable N-tuples, which are identically zero, over all choices of branch length, for some trees. Evaluating the invariants associated with all possible trees, using observed N-tuple frequencies over all sequence positions, enables us to rapidly infer the generating tree. An aspect of evolution at the genomic level much studied recently is the rearrangements of gene order along the chromosome from one species to another. Instead of the substitutions responsible for sequence evolution, we examine the non-local processes responsible for genome rearrangements such as inversion of arbitrarily long segments of chromosomes. By treating the potential adjacency of each possible pair of genes as a position", an appropriate substitution" model can be recognized as governing the rearrangement process, and a probabilistically principled phylogenetic inference can be set up. We calculate the invariants for this process for N=5, and apply them to mitochondrial genome data from coelomate metazoans, showing how they resolve key aspects of branching order.

Modularization of biochemical networks based on classification of Petri net t-invariants

PubMed Central

Grafahrend-Belau, Eva; Schreiber, Falk; Heiner, Monika; Sackmann, Andrea; Junker, Björn H; Grunwald, Stefanie; Speer, Astrid; Winder, Katja; Koch, Ina

2008-01-01

Background Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior. With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Methods Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted

Signature detection and matching for document image retrieval.

PubMed

Zhu, Guangyu; Zheng, Yefeng; Doermann, David; Jaeger, Stefan

2009-11-01

As one of the most pervasive methods of individual identification and document authentication, signatures present convincing evidence and provide an important form of indexing for effective document image processing and retrieval in a broad range of applications. However, detection and segmentation of free-form objects such as signatures from clustered background is currently an open document analysis problem. In this paper, we focus on two fundamental problems in signature-based document image retrieval. First, we propose a novel multiscale approach to jointly detecting and segmenting signatures from document images. Rather than focusing on local features that typically have large variations, our approach captures the structural saliency using a signature production model and computes the dynamic curvature of 2D contour fragments over multiple scales. This detection framework is general and computationally tractable. Second, we treat the problem of signature retrieval in the unconstrained setting of translation, scale, and rotation invariant nonrigid shape matching. We propose two novel measures of shape dissimilarity based on anisotropic scaling and registration residual error and present a supervised learning framework for combining complementary shape information from different dissimilarity metrics using LDA. We quantitatively study state-of-the-art shape representations, shape matching algorithms, measures of dissimilarity, and the use of multiple instances as query in document image retrieval. We further demonstrate our matching techniques in offline signature verification. Extensive experiments using large real-world collections of English and Arabic machine-printed and handwritten documents demonstrate the excellent performance of our approaches.

Practical method for appearance match between soft copy and hard copy

NASA Astrophysics Data System (ADS)

Katoh, Naoya

1994-04-01

CRT monitors are often used as a soft proofing device for the hard copy image output. However, what the user sees on the monitor does not match its output, even if the monitor and the output device are calibrated with CIE/XYZ or CIE/Lab. This is especially obvious when correlated color temperature (CCT) of CRT monitor's white point significantly differs from ambient light. In a typical office environment, one uses a computer graphic monitor having a CCT of 9300K in a room of white fluorescent light of 4150K CCT. In such a case, human visual system is partially adapted to the CRT monitor's white point and partially to the ambient light. The visual experiments were performed on the effect of the ambient lighting. Practical method for soft copy color reproduction that matches the hard copy image in appearance is presented in this paper. This method is fundamentally based on a simple von Kries' adaptation model and takes into account the human visual system's partial adaptation and contrast matching.

Lorentz invariance with an invariant energy scale.

PubMed

Magueijo, João; Smolin, Lee

2002-05-13

We propose a modification of special relativity in which a physical energy, which may be the Planck energy, joins the speed of light as an invariant, in spite of a complete relativity of inertial frames and agreement with Einstein's theory at low energies. This is accomplished by a nonlinear modification of the action of the Lorentz group on momentum space, generated by adding a dilatation to each boost in such a way that the Planck energy remains invariant. The associated algebra has unmodified structure constants. We also discuss the resulting modifications of field theory and suggest a modification of the equivalence principle which determines how the new theory is embedded in general relativity.

Shift-invariant optical associative memories

NASA Astrophysics Data System (ADS)

Psaltis, Demetri; Hong, John

1987-01-01

Shift invariance in the context of associative memories is discussed. Two optical systems that exhibit shift invariance are described in detail with attention given to the analysis of storage capacities. It is shown that full shift invariance cannot be achieved with systems that employ only linear interconnections to store the associations.

Data series embedding and scale invariant statistics.

PubMed

Michieli, I; Medved, B; Ristov, S

2010-06-01

Data sequences acquired from bio-systems such as human gait data, heart rate interbeat data, or DNA sequences exhibit complex dynamics that is frequently described by a long-memory or power-law decay of autocorrelation function. One way of characterizing that dynamics is through scale invariant statistics or "fractal-like" behavior. For quantifying scale invariant parameters of physiological signals several methods have been proposed. Among them the most common are detrended fluctuation analysis, sample mean variance analyses, power spectral density analysis, R/S analysis, and recently in the realm of the multifractal approach, wavelet analysis. In this paper it is demonstrated that embedding the time series data in the high-dimensional pseudo-phase space reveals scale invariant statistics in the simple fashion. The procedure is applied on different stride interval data sets from human gait measurements time series (Physio-Bank data library). Results show that introduced mapping adequately separates long-memory from random behavior. Smaller gait data sets were analyzed and scale-free trends for limited scale intervals were successfully detected. The method was verified on artificially produced time series with known scaling behavior and with the varying content of noise. The possibility for the method to falsely detect long-range dependence in the artificially generated short range dependence series was investigated. (c) 2009 Elsevier B.V. All rights reserved.

Invariants of polarization transformations.

PubMed

Sadjadi, Firooz A

2007-05-20

The use of polarization-sensitive sensors is being explored in a variety of applications. Polarization diversity has been shown to improve the performance of the automatic target detection and recognition in a significant way. However, it also brings out the problems associated with processing and storing more data and the problem of polarization distortion during transmission. We present a technique for extracting attributes that are invariant under polarization transformations. The polarimetric signatures are represented in terms of the components of the Stokes vectors. Invariant algebra is then used to extract a set of signature-related attributes that are invariant under linear transformation of the Stokes vectors. Experimental results using polarimetric infrared signatures of a number of manmade and natural objects undergoing systematic linear transformations support the invariancy of these attributes.

Hierarchical Structure and Cross-Cultural Measurement Invariance of the Norwegian Version of the Personality Inventory for DSM-5.

PubMed

Thimm, Jens C; Jordan, Stian; Bach, Bo

2017-01-01

The Personality Inventory for DSM-5 (PID-5) was created to aid a trait-based diagnostic system for personality disorders (PDs) in the Diagnostic and Statistical Manual of Mental Disorders (5th ed. [DSM-5]; American Psychiatric Association, 2013a ). In this study, we aimed to evaluate the Norwegian version of the PID-5 by examining its score reliability, hierarchical structure, congruency with international findings, and cross-cultural measurement invariance with a matched U.S. For this purpose, 503 university students (76% females) were administered the PID-5. The Norwegian PID-5 showed good score reliability and structural validity from 1 to 5 factors. The 5-factor structure was generally congruent with international findings, and support for measurement invariance across the Norwegian and a matched U.S. sample was found. Conclusively, the results indicate that scores on the Norwegian PID-5 have sound psychometric properties, which are substantially comparable with the original U.S. version, supporting its use in a Norwegian population.

Traffic sign recognition based on a context-aware scale-invariant feature transform approach

NASA Astrophysics Data System (ADS)

Yuan, Xue; Hao, Xiaoli; Chen, Houjin; Wei, Xueye

2013-10-01

A new context-aware scale-invariant feature transform (CASIFT) approach is proposed, which is designed for the use in traffic sign recognition (TSR) systems. The following issues remain in previous works in which SIFT is used for matching or recognition: (1) SIFT is unable to provide color information; (2) SIFT only focuses on local features while ignoring the distribution of global shapes; (3) the template with the maximum number of matching points selected as the final result is instable, especially for images with simple patterns; and (4) SIFT is liable to result in errors when different images share the same local features. In order to resolve these problems, a new CASIFT approach is proposed. The contributions of the work are as follows: (1) color angular patterns are used to provide the color distinguishing information; (2) a CASIFT which effectively combines local and global information is proposed; and (3) a method for computing the similarity between two images is proposed, which focuses on the distribution of the matching points, rather than using the traditional SIFT approach of selecting the template with maximum number of matching points as the final result. The proposed approach is particularly effective in dealing with traffic signs which have rich colors and varied global shape distribution. Experiments are performed to validate the effectiveness of the proposed approach in TSR systems, and the experimental results are satisfying even for images containing traffic signs that have been rotated, damaged, altered in color, have undergone affine transformations, or images which were photographed under different weather or illumination conditions.

A KARAOKE System Singing Evaluation Method that More Closely Matches Human Evaluation

NASA Astrophysics Data System (ADS)

Takeuchi, Hideyo; Hoguro, Masahiro; Umezaki, Taizo

KARAOKE is a popular amusement for old and young. Many KARAOKE machines have singing evaluation function. However, it is often said that the scores given by KARAOKE machines do not match human evaluation. In this paper a KARAOKE scoring method strongly correlated with human evaluation is proposed. This paper proposes a way to evaluate songs based on the distance between singing pitch and musical scale, employing a vibrato extraction method based on template matching of spectrum. The results show that correlation coefficients between scores given by the proposed system and human evaluation are -0.76∼-0.89.

The First Fundamental Theorem of Invariant Theory for the Orthosymplectic Supergroup

NASA Astrophysics Data System (ADS)

Lehrer, G. I.; Zhang, R. B.

2017-01-01

We give an elementary and explicit proof of the first fundamental theorem of invariant theory for the orthosymplectic supergroup by generalising the geometric method of Atiyah, Bott and Patodi to the supergroup context. We use methods from super-algebraic geometry to convert invariants of the orthosymplectic supergroup into invariants of the corresponding general linear supergroup on a different space. In this way, super Schur-Weyl-Brauer duality is established between the orthosymplectic supergroup of superdimension ( m|2 n) and the Brauer algebra with parameter m - 2 n. The result may be interpreted either in terms of the group scheme OSp( V) over C, where V is a finite dimensional super space, or as a statement about the orthosymplectic Lie supergroup over the infinite dimensional Grassmann algebra {Λ}. We take the latter point of view here, and also state a corresponding theorem for the orthosymplectic Lie superalgebra, which involves an extra invariant generator, the super-Pfaffian.

Binocular stereo matching method based on structure tensor

NASA Astrophysics Data System (ADS)

Song, Xiaowei; Yang, Manyi; Fan, Yubo; Yang, Lei

2016-10-01

In a binocular visual system, to recover the three-dimensional information of the object, the most important step is to acquire matching points. Structure tensor is the vector representation of each point in its local neighborhood. Therefore, structure tensor performs well in region detection of local structure, and it is very suitable for detecting specific graphics such as pedestrians, cars and road signs in the image. In this paper, the structure tensor is combined with the luminance information to form the extended structure tensor. The directional derivatives of luminance in x and y directions are calculated, so that the local structure of the image is more prominent. Meanwhile, the Euclidean distance between the eigenvectors of key points is used as the similarity determination metric of key points in the two images. By matching, the coordinates of the matching points in the detected target are precisely acquired. In this paper, experiments were performed on the captured left and right images. After the binocular calibration, image matching was done to acquire the matching points, and then the target depth was calculated according to these matching points. By comparison, it is proved that the structure tensor can accurately acquire the matching points in binocular stereo matching.

Using the Kernel Method of Test Equating for Estimating the Standard Errors of Population Invariance Measures

ERIC Educational Resources Information Center

Moses, Tim

2008-01-01

Equating functions are supposed to be population invariant, meaning that the choice of subpopulation used to compute the equating function should not matter. The extent to which equating functions are population invariant is typically assessed in terms of practical difference criteria that do not account for equating functions' sampling…

Invariance of Woodcock-Johnson III Scores for Students with Learning Disorders and Students without Learning Disorders

ERIC Educational Resources Information Center

Benson, Nicholas; Taub, Gordon E.

2013-01-01

The purpose of this study was to test the invariance of scores derived from the Woodcock-Johnson III Tests of Cognitive Ability (WJ III COG) and Woodcock-Johnson III Tests of Academic Achievement (WJ III ACH) across a group of students diagnosed with learning disorders (n = 994) and a matched sample of students without known clinical diagnoses (n…

Communication: Fitting potential energy surfaces with fundamental invariant neural network

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

Shao, Kejie; Chen, Jun; Zhao, Zhiqiang

A more flexible neural network (NN) method using the fundamental invariants (FIs) as the input vector is proposed in the construction of potential energy surfaces for molecular systems involving identical atoms. Mathematically, FIs finitely generate the permutation invariant polynomial (PIP) ring. In combination with NN, fundamental invariant neural network (FI-NN) can approximate any function to arbitrary accuracy. Because FI-NN minimizes the size of input permutation invariant polynomials, it can efficiently reduce the evaluation time of potential energy, in particular for polyatomic systems. In this work, we provide the FIs for all possible molecular systems up to five atoms. Potential energymore » surfaces for OH{sub 3} and CH{sub 4} were constructed with FI-NN, with the accuracy confirmed by full-dimensional quantum dynamic scattering and bound state calculations.« less

Intensity invariance properties of auditory neurons compared to the statistics of relevant natural signals in grasshoppers.

PubMed

Clemens, Jan; Weschke, Gerroth; Vogel, Astrid; Ronacher, Bernhard

2010-04-01

The temporal pattern of amplitude modulations (AM) is often used to recognize acoustic objects. To identify objects reliably, intensity invariant representations have to be formed. We approached this problem within the auditory pathway of grasshoppers. We presented AM patterns modulated at different time scales and intensities. Metric space analysis of neuronal responses allowed us to determine how well, how invariantly, and at which time scales AM frequency is encoded. We find that in some neurons spike-count cues contribute substantially (20-60%) to the decoding of AM frequency at a single intensity. However, such cues are not robust when intensity varies. The general intensity invariance of the system is poor. However, there exists a range of AM frequencies around 83 Hz where intensity invariance of local interneurons is relatively high. In this range, natural communication signals exhibit much variation between species, suggesting an important behavioral role for this frequency band. We hypothesize, just as has been proposed for human speech, that the communication signals might have evolved to match the processing properties of the receivers. This contrasts with optimal coding theory, which postulates that neuronal systems are adapted to the statistics of the relevant signals.

Image Mosaic Method Based on SIFT Features of Line Segment

PubMed Central

Zhu, Jun; Ren, Mingwu

2014-01-01

This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform) feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling. PMID:24511326

Scale invariance in Newton–Cartan and Hořava–Lifshitz gravity

NASA Astrophysics Data System (ADS)

Olgu Devecioğlu, Deniz; Özdemir, Neşe; Ozkan, Mehmet; Zorba, Utku

2018-06-01

We present a detailed analysis of the construction of z  =  2 and scale invariant Hořava–Lifshitz gravity. The construction procedure is based on the realization of Hořava–Lifshitz gravity as the dynamical Newton–Cartan geometry as well as a non-relativistic tensor calculus in the presence of the scale symmetry. An important consequence of this method is that it provides us with the necessary mechanism to distinguish the local scale invariance from the local Schrödinger invariance. Based on this result we discuss the z  =  2 scale invariant Hořava–Lifshitz gravity and the symmetry enhancement to the full Schrödinger group.

Lorentz Invariance of Gravitational Lagrangians in the Space of Reference Frames

NASA Astrophysics Data System (ADS)

Cognola, G.

1980-06-01

The recently proposed theories of gravitation in the space of reference frames S are based on a Lagrangian invariant with respect to the homogeneous Lorentz group. However, in theories of this kind, the Lorentz invariance is not a necessary consequence of some physical principles, as in the theories formulated in space-time, but rather a purely esthetic request. In the present paper, we give a systematic method for the construction of gravitational theories in the space S, without assuming a priori the Lorentz invariance of the Lagrangian. The Einstein-Cartan equations of gravitation are obtained requiring only that the Lagrangian is invariant under proper rotations and has particular transformation properties under space reflections and space-time dilatations

Modular invariant inflation

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

Kobayashi, Tatsuo; Nitta, Daisuke; Urakawa, Yuko

2016-08-08

Modular invariance is a striking symmetry in string theory, which may keep stringy corrections under control. In this paper, we investigate a phenomenological consequence of the modular invariance, assuming that this symmetry is preserved as well as in a four dimensional (4D) low energy effective field theory. As a concrete setup, we consider a modulus field T whose contribution in the 4D effective field theory remains invariant under the modular transformation and study inflation drived by T. The modular invariance restricts a possible form of the scalar potenntial. As a result, large field models of inflation are hardly realized. Meanwhile,more » a small field model of inflation can be still accomodated in this restricted setup. The scalar potential traced during the slow-roll inflation mimics the hilltop potential V{sub ht}, but it also has a non-negligible deviation from V{sub ht}. Detecting the primordial gravitational waves predicted in this model is rather challenging. Yet, we argue that it may be still possible to falsify this model by combining the information in the reheating process which can be determined self-completely in this setup.« less

Multi-clues image retrieval based on improved color invariants

NASA Astrophysics Data System (ADS)

Liu, Liu; Li, Jian-Xun

2012-05-01

At present, image retrieval has a great progress in indexing efficiency and memory usage, which mainly benefits from the utilization of the text retrieval technology, such as the bag-of-features (BOF) model and the inverted-file structure. Meanwhile, because the robust local feature invariants are selected to establish BOF, the retrieval precision of BOF is enhanced, especially when it is applied to a large-scale database. However, these local feature invariants mainly consider the geometric variance of the objects in the images, and thus the color information of the objects fails to be made use of. Because of the development of the information technology and Internet, the majority of our retrieval objects is color images. Therefore, retrieval performance can be further improved through proper utilization of the color information. We propose an improved method through analyzing the flaw of shadow-shading quasi-invariant. The response and performance of shadow-shading quasi-invariant for the object edge with the variance of lighting are enhanced. The color descriptors of the invariant regions are extracted and integrated into BOF based on the local feature. The robustness of the algorithm and the improvement of the performance are verified in the final experiments.

A layered modulation method for pixel matching in online phase measuring profilometry

NASA Astrophysics Data System (ADS)

Li, Hongru; Feng, Guoying; Bourgade, Thomas; Yang, Peng; Zhou, Shouhuan; Asundi, Anand

2016-10-01

An online phase measuring profilometry with new layered modulation method for pixel matching is presented. In this method and in contrast with previous modulation matching methods, the captured images are enhanced by Retinex theory for better modulation distribution, and all different layer modulation masks are fully used to determine the displacement of a rectilinear moving object. High, medium and low modulation masks are obtained by performing binary segmentation with iterative Otsu method. The final shifting pixels are calculated based on centroid concept, and after that the aligned fringe patterns can be extracted from each frame. After performing Stoilov algorithm and a series of subsequent operations, the object profile on a translation stage is reconstructed. All procedures are carried out automatically, without setting specific parameters in advance. Numerical simulations are detailed and experimental results verify the validity and feasibility of the proposed approach.

A rotation-translation invariant molecular descriptor of partial charges and its use in ligand-based virtual screening

PubMed Central

2014-01-01

Background Measures of similarity for chemical molecules have been developed since the dawn of chemoinformatics. Molecular similarity has been measured by a variety of methods including molecular descriptor based similarity, common molecular fragments, graph matching and 3D methods such as shape matching. Similarity measures are widespread in practice and have proven to be useful in drug discovery. Because of our interest in electrostatics and high throughput ligand-based virtual screening, we sought to exploit the information contained in atomic coordinates and partial charges of a molecule. Results A new molecular descriptor based on partial charges is proposed. It uses the autocorrelation function and linear binning to encode all atoms of a molecule into two rotation-translation invariant vectors. Combined with a scoring function, the descriptor allows to rank-order a database of compounds versus a query molecule. The proposed implementation is called ACPC (AutoCorrelation of Partial Charges) and released in open source. Extensive retrospective ligand-based virtual screening experiments were performed and other methods were compared with in order to validate the method and associated protocol. Conclusions While it is a simple method, it performed remarkably well in experiments. At an average speed of 1649 molecules per second, it reached an average median area under the curve of 0.81 on 40 different targets; hence validating the proposed protocol and implementation. PMID:24887178

Top-of-Climb Matching Method for Reducing Aircraft Trajectory Prediction Errors.

PubMed

Thipphavong, David P

2016-09-01

The inaccuracies of the aircraft performance models utilized by trajectory predictors with regard to takeoff weight, thrust, climb profile, and other parameters result in altitude errors during the climb phase that often exceed the vertical separation standard of 1000 feet. This study investigates the potential reduction in altitude trajectory prediction errors that could be achieved for climbing flights if just one additional parameter is made available: top-of-climb (TOC) time. The TOC-matching method developed and evaluated in this paper is straightforward: a set of candidate trajectory predictions is generated using different aircraft weight parameters, and the one that most closely matches TOC in terms of time is selected. This algorithm was tested using more than 1000 climbing flights in Fort Worth Center. Compared to the baseline trajectory predictions of a real-time research prototype (Center/TRACON Automation System), the TOC-matching method reduced the altitude root mean square error (RMSE) for a 5-minute prediction time by 38%. It also decreased the percentage of flights with absolute altitude error greater than the vertical separation standard of 1000 ft for the same look-ahead time from 55% to 30%.

Top-of-Climb Matching Method for Reducing Aircraft Trajectory Prediction Errors

PubMed Central

Thipphavong, David P.

2017-01-01

The inaccuracies of the aircraft performance models utilized by trajectory predictors with regard to takeoff weight, thrust, climb profile, and other parameters result in altitude errors during the climb phase that often exceed the vertical separation standard of 1000 feet. This study investigates the potential reduction in altitude trajectory prediction errors that could be achieved for climbing flights if just one additional parameter is made available: top-of-climb (TOC) time. The TOC-matching method developed and evaluated in this paper is straightforward: a set of candidate trajectory predictions is generated using different aircraft weight parameters, and the one that most closely matches TOC in terms of time is selected. This algorithm was tested using more than 1000 climbing flights in Fort Worth Center. Compared to the baseline trajectory predictions of a real-time research prototype (Center/TRACON Automation System), the TOC-matching method reduced the altitude root mean square error (RMSE) for a 5-minute prediction time by 38%. It also decreased the percentage of flights with absolute altitude error greater than the vertical separation standard of 1000 ft for the same look-ahead time from 55% to 30%. PMID:28684883

Top-of-Climb Matching Method for Reducing Aircraft Trajectory Prediction Errors

NASA Technical Reports Server (NTRS)

Thipphavong, David P.

2016-01-01

The inaccuracies of the aircraft performance models utilized by trajectory predictors with regard to takeoff weight, thrust, climb profile, and other parameters result in altitude errors during the climb phase that often exceed the vertical separation standard of 1000 feet. This study investigates the potential reduction in altitude trajectory prediction errors that could be achieved for climbing flights if just one additional parameter is made available: top-of-climb (TOC) time. The TOC-matching method developed and evaluated in this paper is straightforward: a set of candidate trajectory predictions is generated using different aircraft weight parameters, and the one that most closely matches TOC in terms of time is selected. This algorithm was tested using more than 1000 climbing flights in Fort Worth Center. Compared to the baseline trajectory predictions of a real-time research prototype (Center/TRACON Automation System), the TOC-matching method reduced the altitude root mean square error (RMSE) for a 5-minute prediction time by 38%. It also decreased the percentage of flights with absolute altitude error greater than the vertical separation standard of 1000 ft for the same look-ahead time from 55% to 30%.

Automatic vertebral bodies detection of x-ray images using invariant multiscale template matching

NASA Astrophysics Data System (ADS)

Sharifi Sarabi, Mona; Villaroman, Diane; Beckett, Joel; Attiah, Mark; Marcus, Logan; Ahn, Christine; Babayan, Diana; Gaonkar, Bilwaj; Macyszyn, Luke; Raghavendra, Cauligi

2017-03-01

Lower back pain and pathologies related to it are one of the most common results for a referral to a neurosurgical clinic in the developed and the developing world. Quantitative evaluation of these pathologies is a challenge. Image based measurements of angles/vertebral heights and disks could provide a potential quantitative biomarker for tracking and measuring these pathologies. Detection of vertebral bodies is a key element and is the focus of the current work. From the variety of medical imaging techniques, MRI and CT scans have been typically used for developing image segmentation methods. However, CT scans are known to give a large dose of x-rays, increasing cancer risk [8]. MRI can be substituted for CTs when the risk is high [8] but are difficult to obtain in smaller facilities due to cost and lack of expertise in the field [2]. X-rays provide another option with its ability to control the x-ray dosage, especially for young people, and its accessibility for smaller facilities. Hence, the ability to create quantitative biomarkers from x-ray data is especially valuable. Here, we develop a multiscale template matching, inspired by [9], to detect centers of vertebral bodies from x-ray data. The immediate application of such detection lies in developing quantitative biomarkers and in querying similar images in a database. Previously, shape similarity classification methods have been used to address this problem, but these are challenging to use in the presence of variation due to gross pathology and even subtle effects [1].

Confirming the cognition of rising scores: Fox and Mitchum (2013) predicts violations of measurement invariance in series completion between age-matched cohorts.

PubMed

Fox, Mark C; Mitchum, Ainsley L

2014-01-01

The trend of rising scores on intelligence tests raises important questions about the comparability of variation within and between time periods. Descriptions of the processes that mediate selection of item responses provide meaningful psychological criteria upon which to base such comparisons. In a recent paper, Fox and Mitchum presented and tested a cognitive theory of rising scores on analogical and inductive reasoning tests that is specific enough to make novel predictions about cohort differences in patterns of item responses for tests such as the Raven's Matrices. In this paper we extend the same proposal in two important ways by (1) testing it against a dataset that enables the effects of cohort to be isolated from those of age, and (2) applying it to two other inductive reasoning tests that exhibit large Flynn effects: Letter Series and Word Series. Following specification and testing of a confirmatory item response model, predicted violations of measurement invariance are observed between two age-matched cohorts that are separated by only 20 years, as members of the later cohort are found to map objects at higher levels of abstraction than members of the earlier cohort who possess the same overall level of ability. Results have implications for the Flynn effect and cognitive aging while underscoring the value of establishing psychological criteria for equating members of distinct groups who achieve the same scores.

Modularization of biochemical networks based on classification of Petri net t-invariants.

PubMed

Grafahrend-Belau, Eva; Schreiber, Falk; Heiner, Monika; Sackmann, Andrea; Junker, Björn H; Grunwald, Stefanie; Speer, Astrid; Winder, Katja; Koch, Ina

2008-02-08

Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior.With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find

The recognition of graphical patterns invariant to geometrical transformation of the models

NASA Astrophysics Data System (ADS)

Ileană, Ioan; Rotar, Corina; Muntean, Maria; Ceuca, Emilian

2010-11-01

In case that a pattern recognition system is used for images recognition (in robot vision, handwritten recognition etc.), the system must have the capacity to identify an object indifferently of its size or position in the image. The problem of the invariance of recognition can be approached in some fundamental modes. One may apply the similarity criterion used in associative recall. The original pattern is replaced by a mathematical transform that assures some invariance (e.g. the value of two-dimensional Fourier transformation is translation invariant, the value of Mellin transformation is scale invariant). In a different approach the original pattern is represented through a set of features, each of them being coded indifferently of the position, orientation or position of the pattern. Generally speaking, it is easy to obtain invariance in relation with one transformation group, but is difficult to obtain simultaneous invariance at rotation, translation and scale. In this paper we analyze some methods to achieve invariant recognition of images, particularly for digit images. A great number of experiments are due and the conclusions are underplayed in the paper.

A Physics-Based Deep Learning Approach to Shadow Invariant Representations of Hyperspectral Images.

PubMed

Windrim, Lloyd; Ramakrishnan, Rishi; Melkumyan, Arman; Murphy, Richard J

2018-02-01

This paper proposes the Relit Spectral Angle-Stacked Autoencoder, a novel unsupervised feature learning approach for mapping pixel reflectances to illumination invariant encodings. This work extends the Spectral Angle-Stacked Autoencoder so that it can learn a shadow-invariant mapping. The method is inspired by a deep learning technique, Denoising Autoencoders, with the incorporation of a physics-based model for illumination such that the algorithm learns a shadow invariant mapping without the need for any labelled training data, additional sensors, a priori knowledge of the scene or the assumption of Planckian illumination. The method is evaluated using datasets captured from several different cameras, with experiments to demonstrate the illumination invariance of the features and how they can be used practically to improve the performance of high-level perception algorithms that operate on images acquired outdoors.

Conformal invariants associated to a measure.

PubMed

Chang, Sun-Yung A; Gursky, Matthew J; Yang, Paul

2006-02-21

In this note, we study some conformal invariants of a Riemannian manifold (M(n), g) equipped with a smooth measure m. In particular, we show that there is a natural definition of the Ricci and scalar curvatures associated to such a space, both of which are conformally invariant. We also adapt the methods of Fefferman and Graham [Fefferman, C. & Graham, C. R. (1985) Astérisque, Numero Hors Serie, 95-116] and Graham, Jenne, Mason, and Sparling [Graham, C. R., Jenne, R., Mason, L. J., & Sparling, G. A. J. (1992) J. London Math. Soc. 46, 557-565] to construct families of conformally covariant operators defined on these spaces. Certain variational problems in this setting are considered, including a generalization of the Einstein-Hilbert action.

Shape invariant potentials in higher dimensions

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

Sandhya, R., E-mail: saudhamini@yahoo.com; Sree Ranjani, S., E-mail: s.sreeranjani@gmail.com; Faculty of Science and Technology, ICFAI foundation for Higher Education,

2015-08-15

In this paper we investigate the shape invariance property of a potential in one dimension. We show that a simple ansatz allows us to reconstruct all the known shape invariant potentials in one dimension. This ansatz can be easily extended to arrive at a large class of new shape invariant potentials in arbitrary dimensions. A reformulation of the shape invariance property and possible generalizations are proposed. These may lead to an important extension of the shape invariance property to Hamiltonians that are related to standard potential problems via space time transformations, which are found useful in path integral formulation ofmore » quantum mechanics.« less

Do scale-invariant fluctuations imply the breaking of de Sitter invariance?

NASA Astrophysics Data System (ADS)

Youssef, A.

2013-01-01

The quantization of the massless minimally coupled (mmc) scalar field in de Sitter spacetime is known to be a non-trivial problem due to the appearance of strong infrared (IR) effects. In particular, the scale-invariance of the CMB power-spectrum - certainly one of the most successful predictions of modern cosmology - is widely believed to be inconsistent with a de Sitter invariant mmc two-point function. Using a Cesaro-summability technique to properly define an otherwise divergent Fourier transform, we show in this Letter that de Sitter symmetry breaking is not a necessary consequence of the scale-invariant fluctuation spectrum. We also generalize our result to the tachyonic scalar fields, i.e. the discrete series of representations of the de Sitter group, that suffer from similar strong IR effects.

A pseudo energy-invariant method for relativistic wave equations with Riesz space-fractional derivatives

NASA Astrophysics Data System (ADS)

Macías-Díaz, J. E.; Hendy, A. S.; De Staelen, R. H.

2018-03-01

In this work, we investigate a general nonlinear wave equation with Riesz space-fractional derivatives that generalizes various classical hyperbolic models, including the sine-Gordon and the Klein-Gordon equations from relativistic quantum mechanics. A finite-difference discretization of the model is provided using fractional centered differences. The method is a technique that is capable of preserving an energy-like quantity at each iteration. Some computational comparisons against solutions available in the literature are performed in order to assess the capability of the method to preserve the invariant. Our experiments confirm that the technique yields good approximations to the solutions considered. As an application of our scheme, we provide simulations that confirm, for the first time in the literature, the presence of the phenomenon of nonlinear supratransmission in Riesz space-fractional Klein-Gordon equations driven by a harmonic perturbation at the boundary.

PIPI: PTM-Invariant Peptide Identification Using Coding Method.

PubMed

Yu, Fengchao; Li, Ning; Yu, Weichuan

2016-12-02

In computational proteomics, the identification of peptides with an unlimited number of post-translational modification (PTM) types is a challenging task. The computational cost associated with database search increases exponentially with respect to the number of modified amino acids and linearly with respect to the number of potential PTM types at each amino acid. The problem becomes intractable very quickly if we want to enumerate all possible PTM patterns. To address this issue, one group of methods named restricted tools (including Mascot, Comet, and MS-GF+) only allow a small number of PTM types in database search process. Alternatively, the other group of methods named unrestricted tools (including MS-Alignment, ProteinProspector, and MODa) avoids enumerating PTM patterns with an alignment-based approach to localizing and characterizing modified amino acids. However, because of the large search space and PTM localization issue, the sensitivity of these unrestricted tools is low. This paper proposes a novel method named PIPI to achieve PTM-invariant peptide identification. PIPI belongs to the category of unrestricted tools. It first codes peptide sequences into Boolean vectors and codes experimental spectra into real-valued vectors. For each coded spectrum, it then searches the coded sequence database to find the top scored peptide sequences as candidates. After that, PIPI uses dynamic programming to localize and characterize modified amino acids in each candidate. We used simulation experiments and real data experiments to evaluate the performance in comparison with restricted tools (i.e., Mascot, Comet, and MS-GF+) and unrestricted tools (i.e., Mascot with error tolerant search, MS-Alignment, ProteinProspector, and MODa). Comparison with restricted tools shows that PIPI has a close sensitivity and running speed. Comparison with unrestricted tools shows that PIPI has the highest sensitivity except for Mascot with error tolerant search and Protein

Verification of Java Programs using Symbolic Execution and Invariant Generation

NASA Technical Reports Server (NTRS)

Pasareanu, Corina; Visser, Willem

2004-01-01

Software verification is recognized as an important and difficult problem. We present a norel framework, based on symbolic execution, for the automated verification of software. The framework uses annotations in the form of method specifications an3 loop invariants. We present a novel iterative technique that uses invariant strengthening and approximation for discovering these loop invariants automatically. The technique handles different types of data (e.g. boolean and numeric constraints, dynamically allocated structures and arrays) and it allows for checking universally quantified formulas. Our framework is built on top of the Java PathFinder model checking toolset and it was used for the verification of several non-trivial Java programs.

Computation of partially invariant solutions for the Einstein Walker manifolds' identifying equations

NASA Astrophysics Data System (ADS)

Nadjafikhah, Mehdi; Jafari, Mehdi

2013-12-01

In this paper, partially invariant solutions (PISs) method is applied in order to obtain new four-dimensional Einstein Walker manifolds. This method is based on subgroup classification for the symmetry group of partial differential equations (PDEs) and can be regarded as the generalization of the similarity reduction method. For this purpose, those cases of PISs which have the defect structure δ=1 and are resulted from two-dimensional subalgebras are considered in the present paper. Also it is shown that the obtained PISs are distinct from the invariant solutions that obtained by similarity reduction method.

Matching weights to simultaneously compare three treatment groups: Comparison to three-way matching

PubMed Central

Yoshida, Kazuki; Hernández-Díaz, Sonia; Solomon, Daniel H.; Jackson, John W.; Gagne, Joshua J.; Glynn, Robert J.; Franklin, Jessica M.

2017-01-01

BACKGROUND Propensity score matching is a commonly used tool. However, its use in settings with more than two treatment groups has been less frequent. We examined the performance of a recently developed propensity score weighting method in the three treatment group setting. METHODS The matching weight method is an extension of inverse probability of treatment weighting (IPTW) that reweights both exposed and unexposed groups to emulate a propensity score matched population. Matching weights can generalize to multiple treatment groups. The performance of matching weights in the three-group setting was compared via simulation to three-way 1:1:1 propensity score matching and IPTW. We also applied these methods to an empirical example that compared the safety of three analgesics. RESULTS Matching weights had similar bias, but better mean squared error (MSE) compared to three-way matching in all scenarios. The benefits were more pronounced in scenarios with a rare outcome, unequally sized treatment groups, or poor covariate overlap. IPTW’s performance was highly dependent on covariate overlap. In the empirical example, matching weights achieved the best balance for 24 out of 35 covariates. Hazard ratios were numerically similar to matching. However, the confidence intervals were narrower for matching weights. CONCLUSIONS Matching weights demonstrated improved performance over three-way matching in terms of MSE, particularly in simulation scenarios where finding matched subjects was difficult. Given its natural extension to settings with even more than three groups, we recommend matching weights for comparing outcomes across multiple treatment groups, particularly in settings with rare outcomes or unequal exposure distributions. PMID:28151746

Sequence-invariant state machines

NASA Technical Reports Server (NTRS)

Whitaker, Sterling R.; Manjunath, Shamanna K.; Maki, Gary K.

1991-01-01

A synthesis method and an MOS VLSI architecture are presented to realize sequential circuits that have the ability to implement any state machine having N states and m inputs, regardless of the actual sequence specified in the flow table. The design method utilizes binary tree structured (BTS) logic to implement regular and dense circuits. The desired state sequence can be hardwired with power supply connections or can be dynamically reallocated if stored in a register. This allows programmable VLSI controllers to be designed with a compact size and performance approaching that of dedicated logic. Results of ICV implementations are reported and an example sequence-invariant state machine is contrasted with implementations based on traditional methods.

Weyl invariance with a nontrivial mass scale

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

Álvarez, Enrique; González-Martín, Sergio; Departamento de Física Teórica, Universidad Autónoma de Madrid,28049 Madrid

2016-09-07

A theory with a mass scale and yet Weyl invariant is presented. The theory is not invariant under all diffeomorphisms but only under transverse ones. This is the reason why Weyl invariance does not imply scale invariance in a free falling frame. Physical implications of this framework are discussed.

Quick probabilistic binary image matching: changing the rules of the game

NASA Astrophysics Data System (ADS)

Mustafa, Adnan A. Y.

2016-09-01

A Probabilistic Matching Model for Binary Images (PMMBI) is presented that predicts the probability of matching binary images with any level of similarity. The model relates the number of mappings, the amount of similarity between the images and the detection confidence. We show the advantage of using a probabilistic approach to matching in similarity space as opposed to a linear search in size space. With PMMBI a complete model is available to predict the quick detection of dissimilar binary images. Furthermore, the similarity between the images can be measured to a good degree if the images are highly similar. PMMBI shows that only a few pixels need to be compared to detect dissimilarity between images, as low as two pixels in some cases. PMMBI is image size invariant; images of any size can be matched at the same quick speed. Near-duplicate images can also be detected without much difficulty. We present tests on real images that show the prediction accuracy of the model.

Comparative analysis of feature extraction methods in satellite imagery

NASA Astrophysics Data System (ADS)

Karim, Shahid; Zhang, Ye; Asif, Muhammad Rizwan; Ali, Saad

2017-10-01

Feature extraction techniques are extensively being used in satellite imagery and getting impressive attention for remote sensing applications. The state-of-the-art feature extraction methods are appropriate according to the categories and structures of the objects to be detected. Based on distinctive computations of each feature extraction method, different types of images are selected to evaluate the performance of the methods, such as binary robust invariant scalable keypoints (BRISK), scale-invariant feature transform, speeded-up robust features (SURF), features from accelerated segment test (FAST), histogram of oriented gradients, and local binary patterns. Total computational time is calculated to evaluate the speed of each feature extraction method. The extracted features are counted under shadow regions and preprocessed shadow regions to compare the functioning of each method. We have studied the combination of SURF with FAST and BRISK individually and found very promising results with an increased number of features and less computational time. Finally, feature matching is conferred for all methods.

Kinetics of matching.

PubMed

Mark, T A; Gallistel, C R

1994-01-01

Rats responded on concurrent variable interval schedules of brain stimulation reward in 2-trial sessions. Between trials, there was a 16-fold reversal in the relative rate of reward. In successive, narrow time windows, the authors compared the ratio of the times spent on the 2 levers to the ratio of the rewards received. Time-allocation ratios tracked wide, random fluctuations in the reward ratio. The adjustment to the midsession reversal in relative rate of reward was largely completed within 1 interreward interval on the leaner schedule. Both results were unaffected by a 16-fold change in the combined rates of reward. The large, rapid, scale-invariant shifts in time-allocation ratios that underlie matching behavior imply that the subjective relative rate of reward can be determined by a very few of the most recent interreward intervals and that this estimate can directly determine the ratio of the expected stay durations.

Evaluation of Existing Image Matching Methods for Deriving Glacier Surface Displacements Globally from Optical Satellite Imagery

NASA Astrophysics Data System (ADS)

Heid, T.; Kääb, A.

2011-12-01

Automatic matching of images from two different times is a method that is often used to derive glacier surface velocity. Nearly global repeat coverage of the Earth's surface by optical satellite sensors now opens the possibility for global-scale mapping and monitoring of glacier flow with a number of applications in, for example, glacier physics, glacier-related climate change and impact assessment, and glacier hazard management. The purpose of this study is to compare and evaluate different existing image matching methods for glacier flow determination over large scales. The study compares six different matching methods: normalized cross-correlation (NCC), the phase correlation algorithm used in the COSI-Corr software, and four other Fourier methods with different normalizations. We compare the methods over five regions of the world with different representative glacier characteristics: Karakoram, the European Alps, Alaska, Pine Island (Antarctica) and southwest Greenland. Landsat images are chosen for matching because they expand back to 1972, they cover large areas, and at the same time their spatial resolution is as good as 15 m for images after 1999 (ETM+ pan). Cross-correlation on orientation images (CCF-O) outperforms the three similar Fourier methods, both in areas with high and low visual contrast. NCC experiences problems in areas with low visual contrast, areas with thin clouds or changing snow conditions between the images. CCF-O has problems on narrow outlet glaciers where small window sizes (about 16 pixels by 16 pixels or smaller) are needed, and it also obtains fewer correct matches than COSI-Corr in areas with low visual contrast. COSI-Corr has problems on narrow outlet glaciers and it obtains fewer correct matches compared to CCF-O when thin clouds cover the surface, or if one of the images contains snow dunes. In total, we consider CCF-O and COSI-Corr to be the two most robust matching methods for global-scale mapping and monitoring of glacier

Rotation-invariant image and video description with local binary pattern features.

PubMed

Zhao, Guoying; Ahonen, Timo; Matas, Jiří; Pietikäinen, Matti

2012-04-01

In this paper, we propose a novel approach to compute rotation-invariant features from histograms of local noninvariant patterns. We apply this approach to both static and dynamic local binary pattern (LBP) descriptors. For static-texture description, we present LBP histogram Fourier (LBP-HF) features, and for dynamic-texture recognition, we present two rotation-invariant descriptors computed from the LBPs from three orthogonal planes (LBP-TOP) features in the spatiotemporal domain. LBP-HF is a novel rotation-invariant image descriptor computed from discrete Fourier transforms of LBP histograms. The approach can be also generalized to embed any uniform features into this framework, and combining the supplementary information, e.g., sign and magnitude components of the LBP, together can improve the description ability. Moreover, two variants of rotation-invariant descriptors are proposed to the LBP-TOP, which is an effective descriptor for dynamic-texture recognition, as shown by its recent success in different application problems, but it is not rotation invariant. In the experiments, it is shown that the LBP-HF and its extensions outperform noninvariant and earlier versions of the rotation-invariant LBP in the rotation-invariant texture classification. In experiments on two dynamic-texture databases with rotations or view variations, the proposed video features can effectively deal with rotation variations of dynamic textures (DTs). They also are robust with respect to changes in viewpoint, outperforming recent methods proposed for view-invariant recognition of DTs.

The Loneliness Questionnaire: Establishing Measurement Invariance Across Ethnic Groups.

PubMed

Ritchwood, Tiarney D; Ebesutani, Chad K; Chin, Eu Gene; Young, John

2017-09-01

A state of loneliness describes an individual's perception of having dissatisfying social connections to others. Though it is notable across the life span, it may have particularly deleterious effects in childhood and adolescence, leading to increased risk of emotional impairment. The current study evaluates a widely used test of loneliness, the Loneliness Questionnaire, for measurement invariance across ethnic groups in a large, representative sample of youth in the 2nd to 12th grades ( N = 12,344; 41% African American) in Mississippi. Analyses were conducted using multigroup confirmatory factor analysis following a published, sequential method to examine invariance in form, factor loadings, and item intercepts. Overall, our results indicated that the instrument was invariant across ethnicities, suggesting that youth with equivalent manifest scores can be discerned as having comparable levels of latent loneliness. The loneliness scores also corresponded significantly with depression and anxiety scores for most subsamples, with one exception. These findings are discussed in the context of previous results comparing levels of loneliness across ethnicities. Additionally, the broader context of the need to expand invariance studies in instrumentation work is highlighted.

A novel rotational invariants target recognition method for rotating motion blurred images

NASA Astrophysics Data System (ADS)

Lan, Jinhui; Gong, Meiling; Dong, Mingwei; Zeng, Yiliang; Zhang, Yuzhen

2017-11-01

The imaging of the image sensor is blurred due to the rotational motion of the carrier and reducing the target recognition rate greatly. Although the traditional mode that restores the image first and then identifies the target can improve the recognition rate, it takes a long time to recognize. In order to solve this problem, a rotating fuzzy invariants extracted model was constructed that recognizes target directly. The model includes three metric layers. The object description capability of metric algorithms that contain gray value statistical algorithm, improved round projection transformation algorithm and rotation-convolution moment invariants in the three metric layers ranges from low to high, and the metric layer with the lowest description ability among them is as the input which can eliminate non pixel points of target region from degenerate image gradually. Experimental results show that the proposed model can improve the correct target recognition rate of blurred image and optimum allocation between the computational complexity and function of region.

Estimating the Counterfactual Impact of Conservation Programs on Land Cover Outcomes: The Role of Matching and Panel Regression Techniques

PubMed Central

Jones, Kelly W.; Lewis, David J.

2015-01-01

Deforestation and conversion of native habitats continues to be the leading driver of biodiversity and ecosystem service loss. A number of conservation policies and programs are implemented—from protected areas to payments for ecosystem services (PES)—to deter these losses. Currently, empirical evidence on whether these approaches stop or slow land cover change is lacking, but there is increasing interest in conducting rigorous, counterfactual impact evaluations, especially for many new conservation approaches, such as PES and REDD, which emphasize additionality. In addition, several new, globally available and free high-resolution remote sensing datasets have increased the ease of carrying out an impact evaluation on land cover change outcomes. While the number of conservation evaluations utilizing ‘matching’ to construct a valid control group is increasing, the majority of these studies use simple differences in means or linear cross-sectional regression to estimate the impact of the conservation program using this matched sample, with relatively few utilizing fixed effects panel methods—an alternative estimation method that relies on temporal variation in the data. In this paper we compare the advantages and limitations of (1) matching to construct the control group combined with differences in means and cross-sectional regression, which control for observable forms of bias in program evaluation, to (2) fixed effects panel methods, which control for observable and time-invariant unobservable forms of bias, with and without matching to create the control group. We then use these four approaches to estimate forest cover outcomes for two conservation programs: a PES program in Northeastern Ecuador and strict protected areas in European Russia. In the Russia case we find statistically significant differences across estimators—due to the presence of unobservable bias—that lead to differences in conclusions about effectiveness. The Ecuador case

An intergrated image matching algorithm and its application in the production of lunar map based on Chang'E-2 images

NASA Astrophysics Data System (ADS)

Wang, F.; Ren, X.; Liu, J.; Li, C.

2012-12-01

An accurate topographic map is a requisite for nearly every phase of research on lunar surface, as well as an essential tool for spacecraft mission planning and operating. Automatic image matching is a key component in this process that could ensure both quality and efficiency in the production of digital topographic map for the whole lunar coverage. It also provides the basis for lunar photographic surveying block adjustment. Image matching is relatively easy when encountered with good image texture conditions. However, on lunar images with characteristics such as constantly changing lighting conditions, large rotation angle, few or homogeneous texture and low image contrasts, it becomes a difficult and challenging job. Thus, we require a robust algorithm that is capable of dealing with light effect and image deformation to fulfill this task. In order to obtain a comprehensive review of currently dominated feature point extraction operators and test whether they are suitable for lunar images, we applied several operators, such as Harris, Forstner, Moravec, SIFT, to images from Chang'E-2 spacecraft. We found that SITF (Scale Invariant Feature Transform) is a scale invariant interest point detector that can provide robustness against errors caused by image distortions from scale, orientation or illumination condition changes. Meanwhile, its capability in detecting blob-like interest points satisfies the image characteristics of Chang'E-2. However, the uneven distributed and low accurate matching results cannot meet the practical requirements in lunar photogrammetry. In contrast, some high-precision corner detectors, such as Harris, Forstner, Moravec, are limited in their sensitivities to geometric rotation. Therefore, this paper proposed a least square matching algorithm that combines the advantages of both local feature detector and corner detector. We experiment this novel method in several sites. The accuracy assessment shows that the overall matching error is

Linear systems with structure group and their feedback invariants

NASA Technical Reports Server (NTRS)

Martin, C.; Hermann, R.

1977-01-01

A general method described by Hermann and Martin (1976) for the study of the feedback invariants of linear systems is considered. It is shown that this method, which makes use of ideas of topology and algebraic geometry, is very useful in the investigation of feedback problems for which the classical methods are not suitable. The transfer function as a curve in the Grassmanian is examined. The general concepts studied in the context of specific systems and applications are organized in terms of the theory of Lie groups and algebraic geometry. Attention is given to linear systems which have a structure group, linear mechanical systems, and feedback invariants. The investigation shows that Lie group techniques are powerful and useful tools for analysis of the feedback structure of linear systems.

A real-time TV logo tracking method using template matching

NASA Astrophysics Data System (ADS)

Li, Zhi; Sang, Xinzhu; Yan, Binbin; Leng, Junmin

2012-11-01

A fast and accurate TV Logo detection method is presented based on real-time image filtering, noise eliminating and recognition of image features including edge and gray level information. It is important to accurately extract the optical template using the time averaging method from the sample video stream, and then different templates are used to match different logos in separated video streams with different resolution based on the topology features of logos. 12 video streams with different logos are used to verify the proposed method, and the experimental result demonstrates that the achieved accuracy can be up to 99%.

Hidden scale invariance of metals

NASA Astrophysics Data System (ADS)

Hummel, Felix; Kresse, Georg; Dyre, Jeppe C.; Pedersen, Ulf R.

2015-11-01

Density functional theory (DFT) calculations of 58 liquid elements at their triple point show that most metals exhibit near proportionality between the thermal fluctuations of the virial and the potential energy in the isochoric ensemble. This demonstrates a general "hidden" scale invariance of metals making the condensed part of the thermodynamic phase diagram effectively one dimensional with respect to structure and dynamics. DFT computed density scaling exponents, related to the Grüneisen parameter, are in good agreement with experimental values for the 16 elements where reliable data were available. Hidden scale invariance is demonstrated in detail for magnesium by showing invariance of structure and dynamics. Computed melting curves of period three metals follow curves with invariance (isomorphs). The experimental structure factor of magnesium is predicted by assuming scale invariant inverse power-law (IPL) pair interactions. However, crystal packings of several transition metals (V, Cr, Mn, Fe, Nb, Mo, Ta, W, and Hg), most post-transition metals (Ga, In, Sn, and Tl), and the metalloids Si and Ge cannot be explained by the IPL assumption. The virial-energy correlation coefficients of iron and phosphorous are shown to increase at elevated pressures. Finally, we discuss how scale invariance explains the Grüneisen equation of state and a number of well-known empirical melting and freezing rules.

Development of 3D Image Measurement System and Stereo-matching Method, and Its Archeological Measurement

NASA Astrophysics Data System (ADS)

Kochi, Nobuo; Ito, Tadayuki; Kitamura, Kazuo; Kaneko, Syun'ichi

The three dimensional measurement & modeling system with digital cameras on PC is now making progress and its need and hope is increasingly felt in terrestrial (close-range) photogrammetry for such sectors as cultural heritage preservation, architecture, civil engineering, manufacturing, measurement etc. Therefore, we have developed a system to improve the accuracy of stereo-matching, which is the very core of 3D measurement. As for stereo-matching method, in order to minimize the mismatching and to be robust in geometric distortions, occlusion, as well as brightness change, we invented Coarse-to-Fine Strategy Method by integrating OCM (Orientation Code Matching) with LSM (Least Squares Matching). Thus this system could attain the accuracy of 0.26mm, when we experimented on a mannequin. And when we actually experimented on the archeological ruins in Greece and Turkey, the accuracy was within the range of 1cm, compared with their blue-print plan. Besides, formally workers used to take at least 1.5 month for this kind of survey operation with the existing method, but now workers need only 3 or 4 days. Thus, its practicality and efficiency was confirmed. This paper demonstrates our new system of 3D measurement and stereo-matching with some concrete examples as its practical application.

Integrable mappings with transcendental invariants

NASA Astrophysics Data System (ADS)

Grammaticos, B.; Ramani, A.

2007-06-01

We examine a family of integrable mappings which possess rational invariants involving polynomials of arbitrarily high degree. Next we extend these mappings to the case where their parameters are functions of the independent variable. The resulting mappings do not preserve any invariant but are solvable by linearisation. Using this result we then proceed to construct the solution of the initial autonomous mappings and use it to explicitly construct the invariant, which turns out to be transcendental in the generic case.

Revisiting measurement invariance in intelligence testing in aging research: Evidence for almost complete metric invariance across age groups.

PubMed

Sprague, Briana N; Hyun, Jinshil; Molenaar, Peter C M

2017-01-01

Invariance of intelligence across age is often assumed but infrequently explicitly tested. Horn and McArdle (1992) tested measurement invariance of intelligence, providing adequate model fit but might not consider all relevant aspects such as sub-test differences. The goal of the current paper is to explore age-related invariance of the WAIS-R using an alternative model that allows direct tests of age on WAIS-R subtests. Cross-sectional data on 940 participants aged 16-75 from the WAIS-R normative values were used. Subtests examined were information, comprehension, similarities, vocabulary, picture completion, block design, picture arrangement, and object assembly. The two intelligence factors considered were fluid and crystallized intelligence. Self-reported ages were divided into young (16-22, n = 300), adult (29-39, n = 275), middle (40-60, n = 205), and older (61-75, n = 160) adult groups. Results suggested partial metric invariance holds. Although most of the subtests reflected fluid and crystalized intelligence similarly across different ages, invariance did not hold for block design on fluid intelligence and picture arrangement on crystallized intelligence for older adults. Additionally, there was evidence of a correlated residual between information and vocabulary for the young adults only. This partial metric invariance model yielded acceptable model fit compared to previously-proposed invariance models of Horn and McArdle (1992). Almost complete metric invariance holds for a two-factor model of intelligence. Most of the subtests were invariant across age groups, suggesting little evidence for age-related bias in the WAIS-R. However, we did find unique relationships between two subtests and intelligence. Future studies should examine age-related differences in subtests when testing measurement invariance in intelligence.

Altered perceptual sensitivity to kinematic invariants in Parkinson's disease.

PubMed

Dayan, Eran; Inzelberg, Rivka; Flash, Tamar

2012-01-01

Ample evidence exists for coupling between action and perception in neurologically healthy individuals, yet the precise nature of the internal representations shared between these domains remains unclear. One experimentally derived view is that the invariant properties and constraints characterizing movement generation are also manifested during motion perception. One prominent motor invariant is the "two-third power law," describing the strong relation between the kinematics of motion and the geometrical features of the path followed by the hand during planar drawing movements. The two-thirds power law not only characterizes various movement generation tasks but also seems to constrain visual perception of motion. The present study aimed to assess whether motor invariants, such as the two thirds power law also constrain motion perception in patients with Parkinson's disease (PD). Patients with PD and age-matched controls were asked to observe the movement of a light spot rotating on an elliptical path and to modify its velocity until it appeared to move most uniformly. As in previous reports controls tended to choose those movements close to obeying the two-thirds power law as most uniform. Patients with PD displayed a more variable behavior, choosing on average, movements closer but not equal to a constant velocity. Our results thus demonstrate impairments in how the two-thirds power law constrains motion perception in patients with PD, where this relationship between velocity and curvature appears to be preserved but scaled down. Recent hypotheses on the role of the basal ganglia in motor timing may explain these irregularities. Alternatively, these impairments in perception of movement may reflect similar deficits in motor production.

A vector matching method for analysing logic Petri nets

NASA Astrophysics Data System (ADS)

Du, YuYue; Qi, Liang; Zhou, MengChu

2011-11-01

Batch processing function and passing value indeterminacy in cooperative systems can be described and analysed by logic Petri nets (LPNs). To directly analyse the properties of LPNs, the concept of transition enabling vector sets is presented and a vector matching method used to judge the enabling transitions is proposed in this article. The incidence matrix of LPNs is defined; an equation about marking change due to a transition's firing is given; and a reachable tree is constructed. The state space explosion is mitigated to a certain extent from directly analysing LPNs. Finally, the validity and reliability of the proposed method are illustrated by an example in electronic commerce.

Invariance in Measurement and Prediction Revisited

ERIC Educational Resources Information Center

Millsap, Roger E.

2007-01-01

Borsboom (Psychometrika, 71:425-440, 2006) noted that recent work on measurement invariance (MI) and predictive invariance (PI) has had little impact on the practice of measurement in psychology. To understand this contention, the definitions of MI and PI are reviewed, followed by results on the consistency between the two forms of invariance in…

Application Profile Matching Method for Employees Online Recruitment

NASA Astrophysics Data System (ADS)

Sunarti; Rangga, Rahmadian Y.; Marlim, Yulvia Nora

2017-12-01

Employees is one of the determinant factors of company’s success. Thus, reliable human resources are needed to support the survival of the company. This research takes case study at PT. Asuransi Bina Dana Arta, Tbk Pekanbaru Branch. Employee recruitment system at PT. Asuransi Bina Dana Arta, Tbk Pekanbaru Branch still uses manual system as seen in application letter files file so it needs long time to determine accepted and rejected the application. For that it needs to built a system or application that allows companies in determining employees who accepted or rejected easily. Pofile Matching Method is a process of competency assessment that is done by comparing the value of written, psychological and interview test between one applicationt with other. PT. Asuransi Bina Dana Arta, Tbk Pekanbaru branch set the percentage to calculate NCF (Core Factor Value) by 60% and NSF (Secondary Factor Value) by 40%, and set the percentage to calculate the total value of written test by 40%, the total value of psycho test by 30%, and the total value of interview 30%. The final result of this study is to determine the rank or ranking of each applicant based on the greater value which, the greater that score of final result of an application get, the greater the chance of the applicant occupy a position or vacancy. Online Recruitment application uses profile matching method can help employee selection process and employee acceptance decisions quickly. This system can be viewed by directors or owners anywhere because it is online and used for other company branch

A Simple and Robust Method for Partially Matched Samples Using the P-Values Pooling Approach

PubMed Central

Kuan, Pei Fen; Huang, Bo

2013-01-01

This paper focuses on statistical analyses in scenarios where some samples from the matched pairs design are missing, resulting in partially matched samples. Motivated by the idea of meta-analysis, we recast the partially matched samples as coming from two experimental designs, and propose a simple yet robust approach based on the weighted Z-test to integrate the p-values computed from these two designs. We show that the proposed approach achieves better operating characteristics in simulations and a case study, compared to existing methods for partially matched samples. PMID:23417968

Probability density functions for CP-violating rephasing invariants

NASA Astrophysics Data System (ADS)

Fortin, Jean-François; Giasson, Nicolas; Marleau, Luc

2018-05-01

The implications of the anarchy principle on CP violation in the lepton sector are investigated. A systematic method is introduced to compute the probability density functions for the CP-violating rephasing invariants of the PMNS matrix from the Haar measure relevant to the anarchy principle. Contrary to the CKM matrix which is hierarchical, it is shown that the Haar measure, and hence the anarchy principle, are very likely to lead to the observed PMNS matrix. Predictions on the CP-violating Dirac rephasing invariant |jD | and Majorana rephasing invariant |j1 | are also obtained. They correspond to 〈 |jD | 〉 Haar = π / 105 ≈ 0.030 and 〈 |j1 | 〉 Haar = 1 / (6 π) ≈ 0.053 respectively, in agreement with the experimental hint from T2K of | jDexp | ≈ 0.032 ± 0.005 (or ≈ 0.033 ± 0.003) for the normal (or inverted) hierarchy.

Development of Matched (migratory Analytical Time Change Easy Detection) Method for Satellite-Tracked Migratory Birds

NASA Astrophysics Data System (ADS)

Doko, Tomoko; Chen, Wenbo; Higuchi, Hiroyoshi

2016-06-01

Satellite tracking technology has been used to reveal the migration patterns and flyways of migratory birds. In general, bird migration can be classified according to migration status. These statuses include the wintering period, spring migration, breeding period, and autumn migration. To determine the migration status, periods of these statuses should be individually determined, but there is no objective method to define 'a threshold date' for when an individual bird changes its status. The research objective is to develop an effective and objective method to determine threshold dates of migration status based on satellite-tracked data. The developed method was named the "MATCHED (Migratory Analytical Time Change Easy Detection) method". In order to demonstrate the method, data acquired from satellite-tracked Tundra Swans were used. MATCHED method is composed by six steps: 1) dataset preparation, 2) time frame creation, 3) automatic identification, 4) visualization of change points, 5) interpretation, and 6) manual correction. Accuracy was tested. In general, MATCHED method was proved powerful to identify the change points between migration status as well as stopovers. Nevertheless, identifying "exact" threshold dates is still challenging. Limitation and application of this method was discussed.

Improved Feature Matching for Mobile Devices with IMU.

PubMed

Masiero, Andrea; Vettore, Antonio

2016-08-05

Thanks to the recent diffusion of low-cost high-resolution digital cameras and to the development of mostly automated procedures for image-based 3D reconstruction, the popularity of photogrammetry for environment surveys is constantly increasing in the last years. Automatic feature matching is an important step in order to successfully complete the photogrammetric 3D reconstruction: this step is the fundamental basis for the subsequent estimation of the geometry of the scene. This paper reconsiders the feature matching problem when dealing with smart mobile devices (e.g., when using the standard camera embedded in a smartphone as imaging sensor). More specifically, this paper aims at exploiting the information on camera movements provided by the inertial navigation system (INS) in order to make the feature matching step more robust and, possibly, computationally more efficient. First, a revised version of the affine scale-invariant feature transform (ASIFT) is considered: this version reduces the computational complexity of the original ASIFT, while still ensuring an increase of correct feature matches with respect to the SIFT. Furthermore, a new two-step procedure for the estimation of the essential matrix E (and the camera pose) is proposed in order to increase its estimation robustness and computational efficiency.

Invariant Imbedded T-Matrix Method for Axial Symmetric Hydrometeors with Extreme Aspect Ratios

NASA Technical Reports Server (NTRS)

Pelissier, Craig; Kuo, Kwo-Sen; Clune, Thomas; Adams, Ian; Munchak, Stephen

2017-01-01

The single-scattering properties (SSPs) of hydrometeors are the fundamental quantities for physics-based precipitation retrievals. Thus, efficient computation of their electromagnetic scattering is of great value. Whereas the semi-analytical T-Matrix methods are likely the most efficient for nonspherical hydrometeors with axial symmetry, they are not suitable for arbitrarily shaped hydrometeors absent of any significant symmetry, for which volume integral methods such as those based on Discrete Dipole Approximation (DDA) are required. Currently the two leading T-matrix methods are the Extended Boundary Condition Method (EBCM) and the Invariant Imbedding T-matrix Method incorporating Lorentz-Mie Separation of Variables (IITM+SOV). EBCM is known to outperform IITM+SOV for hydrometeors with modest aspect ratios. However, in cases when aspect ratios become extreme, such as needle-like particles with large height to diameter values, EBCM fails to converge. Such hydrometeors with extreme aspect ratios are known to be present in solid precipitation and their SSPs are required to model the radiative responses accurately. In these cases, IITM+SOV is shown to converge. An efficient, parallelized C++ implementation for both EBCM and IITM+SOV has been developed to conduct a performance comparison between EBCM, IITM+SOV, and DDSCAT (a popular implementation of DDA). We present the comparison results and discuss details. Our intent is to release the combined ECBM IITM+SOV software to the community under an open source license.

Invariant Imbedding T-Matrix Method for Axial Symmetric Hydrometeors with Extreme Aspect Ratios

NASA Astrophysics Data System (ADS)

Pelissier, C.; Clune, T.; Kuo, K. S.; Munchak, S. J.; Adams, I. S.

2017-12-01

The single-scattering properties (SSPs) of hydrometeors are the fundamental quantities for physics-based precipitation retrievals. Thus, efficient computation of their electromagnetic scattering is of great value. Whereas the semi-analytical T-Matrix methods are likely the most efficient for nonspherical hydrometeors with axial symmetry, they are not suitable for arbitrarily shaped hydrometeors absent of any significant symmetry, for which volume integral methods such as those based on Discrete Dipole Approximation (DDA) are required. Currently the two leading T-matrix methods are the Extended Boundary Condition Method (EBCM) and the Invariant Imbedding T-matrix Method incorporating Lorentz-Mie Separation of Variables (IITM+SOV). EBCM is known to outperform IITM+SOV for hydrometeors with modest aspect ratios. However, in cases when aspect ratios become extreme, such as needle-like particles with large height to diameter values, EBCM fails to converge. Such hydrometeors with extreme aspect ratios are known to be present in solid precipitation and their SSPs are required to model the radiative responses accurately. In these cases, IITM+SOV is shown to converge. An efficient, parallelized C++ implementation for both EBCM and IITM+SOV has been developed to conduct a performance comparison between EBCM, IITM+SOV, and DDSCAT (a popular implementation of DDA). We present the comparison results and discuss details. Our intent is to release the combined ECBM & IITM+SOV software to the community under an open source license.

The concept of invariance in school mathematics

NASA Astrophysics Data System (ADS)

Libeskind, Shlomo; Stupel, Moshe; Oxman, Victor

2018-01-01

In this paper, we highlight examples from school mathematics in which invariance did not receive the attention it deserves. We describe how problems related to invariance stimulated the interest of both teachers and students. In school mathematics, invariance is of particular relevance in teaching and learning geometry. When permitted change leaves some relationships or properties invariant, these properties prove to be inherently interesting to teachers and students.

Invariant algebraic surfaces for a virus dynamics

NASA Astrophysics Data System (ADS)

Valls, Claudia

2015-08-01

In this paper, we provide a complete classification of the invariant algebraic surfaces and of the rational first integrals for a well-known virus system. In the proofs, we use the weight-homogeneous polynomials and the method of characteristic curves for solving linear partial differential equations.

A phase match based frequency estimation method for sinusoidal signals

NASA Astrophysics Data System (ADS)

Shen, Yan-Lin; Tu, Ya-Qing; Chen, Lin-Jun; Shen, Ting-Ao

2015-04-01

Accurate frequency estimation affects the ranging precision of linear frequency modulated continuous wave (LFMCW) radars significantly. To improve the ranging precision of LFMCW radars, a phase match based frequency estimation method is proposed. To obtain frequency estimation, linear prediction property, autocorrelation, and cross correlation of sinusoidal signals are utilized. The analysis of computational complex shows that the computational load of the proposed method is smaller than those of two-stage autocorrelation (TSA) and maximum likelihood. Simulations and field experiments are performed to validate the proposed method, and the results demonstrate the proposed method has better performance in terms of frequency estimation precision than methods of Pisarenko harmonic decomposition, modified covariance, and TSA, which contribute to improving the precision of LFMCW radars effectively.

Asymptotically free theory with scale invariant thermodynamics

NASA Astrophysics Data System (ADS)

Ferrari, Gabriel N.; Kneur, Jean-Loïc; Pinto, Marcus Benghi; Ramos, Rudnei O.

2017-12-01

A recently developed variational resummation technique, incorporating renormalization group properties consistently, has been shown to solve the scale dependence problem that plagues the evaluation of thermodynamical quantities, e.g., within the framework of approximations such as in the hard-thermal-loop resummed perturbation theory. This method is used in the present work to evaluate thermodynamical quantities within the two-dimensional nonlinear sigma model, which, apart from providing a technically simpler testing ground, shares some common features with Yang-Mills theories, like asymptotic freedom, trace anomaly and the nonperturbative generation of a mass gap. The present application confirms that nonperturbative results can be readily generated solely by considering the lowest-order (quasiparticle) contribution to the thermodynamic effective potential, when this quantity is required to be renormalization group invariant. We also show that when the next-to-leading correction from the method is accounted for, the results indicate convergence, apart from optimally preserving, within the approximations here considered, the sought-after scale invariance.

Measurement invariance versus selection invariance: is fair selection possible?

PubMed

Borsboom, Denny; Romeijn, Jan-Willem; Wicherts, Jelte M

2008-06-01

This article shows that measurement invariance (defined in terms of an invariant measurement model in different groups) is generally inconsistent with selection invariance (defined in terms of equal sensitivity and specificity across groups). In particular, when a unidimensional measurement instrument is used and group differences are present in the location but not in the variance of the latent distribution, sensitivity and positive predictive value will be higher in the group at the higher end of the latent dimension, whereas specificity and negative predictive value will be higher in the group at the lower end of the latent dimension. When latent variances are unequal, the differences in these quantities depend on the size of group differences in variances relative to the size of group differences in means. The effect originates as a special case of Simpson's paradox, which arises because the observed score distribution is collapsed into an accept-reject dichotomy. Simulations show the effect can be substantial in realistic situations. It is suggested that the effect may be partly responsible for overprediction in minority groups as typically found in empirical studies on differential academic performance. A methodological solution to the problem is suggested, and social policy implications are discussed. (PsycINFO Database Record (c) 2008 APA, all rights reserved).

An intelligent service matching method for mechanical equipment condition monitoring using the fibre Bragg grating sensor network

NASA Astrophysics Data System (ADS)

Zhang, Fan; Zhou, Zude; Liu, Quan; Xu, Wenjun

2017-02-01

Due to the advantages of being able to function under harsh environmental conditions and serving as a distributed condition information source in a networked monitoring system, the fibre Bragg grating (FBG) sensor network has attracted considerable attention for equipment online condition monitoring. To provide an overall conditional view of the mechanical equipment operation, a networked service-oriented condition monitoring framework based on FBG sensing is proposed, together with an intelligent matching method for supporting monitoring service management. In the novel framework, three classes of progressive service matching approaches, including service-chain knowledge database service matching, multi-objective constrained service matching and workflow-driven human-interactive service matching, are developed and integrated with an enhanced particle swarm optimisation (PSO) algorithm as well as a workflow-driven mechanism. Moreover, the manufacturing domain ontology, FBG sensor network structure and monitoring object are considered to facilitate the automatic matching of condition monitoring services to overcome the limitations of traditional service processing methods. The experimental results demonstrate that FBG monitoring services can be selected intelligently, and the developed condition monitoring system can be re-built rapidly as new equipment joins the framework. The effectiveness of the service matching method is also verified by implementing a prototype system together with its performance analysis.

Computation of Quasiperiodic Normally Hyperbolic Invariant Tori: Rigorous Results

NASA Astrophysics Data System (ADS)

Canadell, Marta; Haro, Àlex

2017-12-01

The development of efficient methods for detecting quasiperiodic oscillations and computing the corresponding invariant tori is a subject of great importance in dynamical systems and their applications in science and engineering. In this paper, we prove the convergence of a new Newton-like method for computing quasiperiodic normally hyperbolic invariant tori carrying quasiperiodic motion in smooth families of real-analytic dynamical systems. The main result is stated as an a posteriori KAM-like theorem that allows controlling the inner dynamics on the torus with appropriate detuning parameters, in order to obtain a prescribed quasiperiodic motion. The Newton-like method leads to several fast and efficient computational algorithms, which are discussed and tested in a companion paper (Canadell and Haro in J Nonlinear Sci, 2017. doi: 10.1007/s00332-017-9388-z), in which new mechanisms of breakdown are presented.

Empirical test of the spectral invariants theory using imaging spectroscopy data from a coniferous forest

NASA Astrophysics Data System (ADS)

Lukeš, Petr; Rautiainen, Miina; Stenberg, Pauline; Malenovský, Zbyněk

2011-08-01

The spectral invariants theory presents an alternative approach for modeling canopy scattering in remote sensing applications. The theory is particularly appealing in the case of coniferous forests, which typically display grouped structures and require computationally intensive calculation to account for the geometric arrangement of their canopies. However, the validity of the spectral invariants theory should be tested with empirical data sets from different vegetation types. In this paper, we evaluate a method to retrieve two canopy spectral invariants, the recollision probability and the escape factor, for a coniferous forest using imaging spectroscopy data from multiangular CHRIS PROBA and NADIR-view AISA Eagle sensors. Our results indicated that in coniferous canopies the spectral invariants theory performs well in the near infrared spectral range. In the visible range, on the other hand, the spectral invariants theory may not be useful. Secondly, our study suggested that retrieval of the escape factor could be used as a new method to describe the BRDF of a canopy.

Applications of invariants in general relativity

NASA Astrophysics Data System (ADS)

Pelavas, Nicos

This thesis explores various kinds of invariants and their use in general relativity. To start, the simplest invariants, those polynomial in the Riemann tensor, are examined and the currently accepted Carminati-Zakhary set is compared to the Carminati-McLenaghan set. A number of algebraic relations linking the two sets are given. The concept of gravitational entropy, as proposed by Penrose, has some physically appealing properties which have motivated attempts to quantify this notion using various invariants. We study this in the context of self-similar spacetimes. A general result is obtained which gives the Lie derivative of any invariant or ratio of invariants along a homothetic trajectory. A direct application of this result shows that the currently used gravitational epoch function fails to satisfy certain criteria. Based on this work, candidates for a gravitational epoch function are proposed that behave accordingly in these models. The instantaneous ergo surface in the Kerr solution is studied and shown to possess conical points at the poles when embedded in three dimensional Euclidean space. These intrinsic singularities had remained undiscovered for a generation. We generalize the Gauss-Bonnet theorem to accommodate these points and use it to compute a topological invariant, the Euler characteristic, for this surface. Interest in solutions admitting a cosmological constant has prompted us to study ergo surfaces in stationary non-asymptotically flat spacetimes. In these cases we show that there is in fact a family of ergo surfaces. By using a kinematic invariant constructed from timelike Killing vectors we try to find a preferred ergo surface. We illustrate to what extent this invariant fails to provide such a measure.

Rosenberg Self-Esteem Scale: Method Effects, Factorial Structure and Scale Invariance Across Migrant Child and Urban Child Populations in China.

PubMed

Wu, Yang; Zuo, Bin; Wen, Fangfang; Yan, Lei

2017-01-01

Using confirmatory factor analyses, this study examined the method effects on a Chinese version of the Rosenberg Self-Esteem Scale (RSES; Rosenberg, 1965 ) in a sample of migrant and urban children in China. In all, 982 children completed the RSES, and 9 models and 9 corresponding variants were specified and tested. The results indicated that the method effects are associated with both positively and negatively worded items and that Item 8 should be treated as a positively worded item. Additionally, the method effects models were invariant across migrant and urban children in China.

Indoor Location Sensing with Invariant Wi-Fi Received Signal Strength Fingerprinting.

PubMed

Husen, Mohd Nizam; Lee, Sukhan

2016-11-11

A method of location fingerprinting based on the Wi-Fi received signal strength (RSS) in an indoor environment is presented. The method aims to overcome the RSS instability due to varying channel disturbances in time by introducing the concept of invariant RSS statistics. The invariant RSS statistics represent here the RSS distributions collected at individual calibration locations under minimal random spatiotemporal disturbances in time. The invariant RSS statistics thus collected serve as the reference pattern classes for fingerprinting. Fingerprinting is carried out at an unknown location by identifying the reference pattern class that maximally supports the spontaneous RSS sensed from individual Wi-Fi sources. A design guideline is also presented as a rule of thumb for estimating the number of Wi-Fi signal sources required to be available for any given number of calibration locations under a certain level of random spatiotemporal disturbances. Experimental results show that the proposed method not only provides 17% higher success rate than conventional ones but also removes the need for recalibration. Furthermore, the resolution is shown finer by 40% with the execution time more than an order of magnitude faster than the conventional methods. These results are also backed up by theoretical analysis.

Reynolds averaged turbulence modelling using deep neural networks with embedded invariance

DOE PAGES

Ling, Julia; Kurzawski, Andrew; Templeton, Jeremy

2016-10-18

There exists significant demand for improved Reynolds-averaged Navier–Stokes (RANS) turbulence models that are informed by and can represent a richer set of turbulence physics. This paper presents a method of using deep neural networks to learn a model for the Reynolds stress anisotropy tensor from high-fidelity simulation data. A novel neural network architecture is proposed which uses a multiplicative layer with an invariant tensor basis to embed Galilean invariance into the predicted anisotropy tensor. It is demonstrated that this neural network architecture provides improved prediction accuracy compared with a generic neural network architecture that does not embed this invariance property.more » Furthermore, the Reynolds stress anisotropy predictions of this invariant neural network are propagated through to the velocity field for two test cases. For both test cases, significant improvement versus baseline RANS linear eddy viscosity and nonlinear eddy viscosity models is demonstrated.« less

Reynolds averaged turbulence modelling using deep neural networks with embedded invariance

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

Ling, Julia; Kurzawski, Andrew; Templeton, Jeremy

There exists significant demand for improved Reynolds-averaged Navier–Stokes (RANS) turbulence models that are informed by and can represent a richer set of turbulence physics. This paper presents a method of using deep neural networks to learn a model for the Reynolds stress anisotropy tensor from high-fidelity simulation data. A novel neural network architecture is proposed which uses a multiplicative layer with an invariant tensor basis to embed Galilean invariance into the predicted anisotropy tensor. It is demonstrated that this neural network architecture provides improved prediction accuracy compared with a generic neural network architecture that does not embed this invariance property.more » Furthermore, the Reynolds stress anisotropy predictions of this invariant neural network are propagated through to the velocity field for two test cases. For both test cases, significant improvement versus baseline RANS linear eddy viscosity and nonlinear eddy viscosity models is demonstrated.« less

Invariant measures in brain dynamics

NASA Astrophysics Data System (ADS)

Boyarsky, Abraham; Góra, Paweł

2006-10-01

This note concerns brain activity at the level of neural ensembles and uses ideas from ergodic dynamical systems to model and characterize chaotic patterns among these ensembles during conscious mental activity. Central to our model is the definition of a space of neural ensembles and the assumption of discrete time ensemble dynamics. We argue that continuous invariant measures draw the attention of deeper brain processes, engendering emergent properties such as consciousness. Invariant measures supported on a finite set of ensembles reflect periodic behavior, whereas the existence of continuous invariant measures reflect the dynamics of nonrepeating ensemble patterns that elicit the interest of deeper mental processes. We shall consider two different ways to achieve continuous invariant measures on the space of neural ensembles: (1) via quantum jitters, and (2) via sensory input accompanied by inner thought processes which engender a “folding” property on the space of ensembles.

Finding Mutual Exclusion Invariants in Temporal Planning Domains

NASA Technical Reports Server (NTRS)

Bernardini, Sara; Smith, David E.

2011-01-01

We present a technique for automatically extracting temporal mutual exclusion invariants from PDDL2.2 planning instances. We first identify a set of invariant candidates by inspecting the domain and then check these candidates against properties that assure invariance. If these properties are violated, we show that it is sometimes possible to refine a candidate by adding additional propositions and turn it into a real invariant. Our technique builds on other approaches to invariant synthesis presented in the literature, but departs from their limited focus on instantaneous discrete actions by addressing temporal and numeric domains. To deal with time, we formulate invariance conditions that account for both the entire structure of the operators (including the conditions, rather than just the effects) and the possible interactions between operators. As a result, we construct a technique that is not only capable of identifying invariants for temporal domains, but is also able to find a broader set of invariants for non-temporal domains than the previous techniques.

Measurement invariance, the lack thereof, and modeling change.

PubMed

Edwards, Michael C; Houts, Carrie R; Wirth, R J

2017-08-17

Measurement invariance issues should be considered during test construction. In this paper, we provide a conceptual overview of measurement invariance and describe how the concept is implemented in several different statistical approaches. Typical applications look for invariance over things such as mode of administration (paper and pencil vs. computer based), language/translation, age, time, and gender, to cite just a few examples. To the extent that the relationships between items and constructs are stable/invariant, we can be more confident in score interpretations. A series of simulated examples are reported which highlight different kinds of non-invariance, the impact it can have, and the effect of appropriately modeling a lack of invariance. One example focuses on the longitudinal context, where measurement invariance is critical to understanding trends over time. Software syntax is provided to help researchers apply these models with their own data. The simulation studies demonstrate the negative impact an erroneous assumption of invariance may have on scores and substantive conclusions drawn from naively analyzing those scores. Measurement invariance implies that the links between the items and the construct of interest are invariant over some domain, grouping, or classification. Examining a new or existing test for measurement invariance should be part of any test construction/implementation plan. In addition to reviewing implications of the simulation study results, we also provide a discussion of the limitations of current approaches and areas in need of additional research.

Basic Theory of Fractional Conformal Invariance of Mei Symmetry and its Applications to Physics

NASA Astrophysics Data System (ADS)

Luo, Shao-Kai; Dai, Yun; Yang, Ming-Jing; Zhang, Xiao-Tian

2018-04-01

In this paper, we present a basic theory of fractional dynamics, i.e., the fractional conformal invariance of Mei symmetry, and find a new kind of conserved quantity led by fractional conformal invariance. For a dynamical system that can be transformed into fractional generalized Hamiltonian representation, we introduce a more general kind of single-parameter fractional infinitesimal transformation of Lie group, the definition and determining equation of fractional conformal invariance are given. And then, we reveal the fractional conformal invariance of Mei symmetry, and the necessary and sufficient condition whether the fractional conformal invariance would be the fractional Mei symmetry is found. In particular, we present the basic theory of fractional conformal invariance of Mei symmetry and it is found that, using the new approach, we can find a new kind of conserved quantity; as a special case, we find that an autonomous fractional generalized Hamiltonian system possesses more conserved quantities. Also, as the new method's applications, we, respectively, find the conserved quantities of a fractional general relativistic Buchduhl model and a fractional Duffing oscillator led by fractional conformal invariance of Mei symmetry.

Matching a Distribution by Matching Quantiles Estimation

PubMed Central

Sgouropoulos, Nikolaos; Yao, Qiwei; Yastremiz, Claudia

2015-01-01

Motivated by the problem of selecting representative portfolios for backtesting counterparty credit risks, we propose a matching quantiles estimation (MQE) method for matching a target distribution by that of a linear combination of a set of random variables. An iterative procedure based on the ordinary least-squares estimation (OLS) is proposed to compute MQE. MQE can be easily modified by adding a LASSO penalty term if a sparse representation is desired, or by restricting the matching within certain range of quantiles to match a part of the target distribution. The convergence of the algorithm and the asymptotic properties of the estimation, both with or without LASSO, are established. A measure and an associated statistical test are proposed to assess the goodness-of-match. The finite sample properties are illustrated by simulation. An application in selecting a counterparty representative portfolio with a real dataset is reported. The proposed MQE also finds applications in portfolio tracking, which demonstrates the usefulness of combining MQE with LASSO. PMID:26692592

Scale invariant feature transform in adaptive radiation therapy: a tool for deformable image registration assessment and re-planning indication

NASA Astrophysics Data System (ADS)

Paganelli, Chiara; Peroni, Marta; Riboldi, Marco; Sharp, Gregory C.; Ciardo, Delia; Alterio, Daniela; Orecchia, Roberto; Baroni, Guido

2013-01-01

Adaptive radiation therapy (ART) aims at compensating for anatomic and pathological changes to improve delivery along a treatment fraction sequence. Current ART protocols require time-consuming manual updating of all volumes of interest on the images acquired during treatment. Deformable image registration (DIR) and contour propagation stand as a state of the ART method to automate the process, but the lack of DIR quality control methods hinder an introduction into clinical practice. We investigated the scale invariant feature transform (SIFT) method as a quantitative automated tool (1) for DIR evaluation and (2) for re-planning decision-making in the framework of ART treatments. As a preliminary test, SIFT invariance properties at shape-preserving and deformable transformations were studied on a computational phantom, granting residual matching errors below the voxel dimension. Then a clinical dataset composed of 19 head and neck ART patients was used to quantify the performance in ART treatments. For the goal (1) results demonstrated SIFT potential as an operator-independent DIR quality assessment metric. We measured DIR group systematic residual errors up to 0.66 mm against 1.35 mm provided by rigid registration. The group systematic errors of both bony and all other structures were also analyzed, attesting the presence of anatomical deformations. The correct automated identification of 18 patients who might benefit from ART out of the total 22 cases using SIFT demonstrated its capabilities toward goal (2) achievement.

Gauge-invariant variables and entanglement entropy

NASA Astrophysics Data System (ADS)

Agarwal, Abhishek; Karabali, Dimitra; Nair, V. P.

2017-12-01

The entanglement entropy (EE) of gauge theories in three spacetime dimensions is analyzed using manifestly gauge-invariant variables defined directly in the continuum. Specifically, we focus on the Maxwell, Maxwell-Chern-Simons (MCS), and non-Abelian Yang-Mills theories. Special attention is paid to the analysis of edge modes and their contribution to EE. The contact term is derived without invoking the replica method and its physical origin is traced to the phase space volume measure for the edge modes. The topological contribution to the EE for the MCS case is calculated. For all the Abelian cases, the EE presented in this paper agrees with known results in the literature. The EE for the non-Abelian theory is computed in a gauge-invariant Gaussian approximation, which incorporates the dynamically generated mass gap. A formulation of the contact term for the non-Abelian case is also presented.

Domain-Invariant Partial-Least-Squares Regression.

PubMed

Nikzad-Langerodi, Ramin; Zellinger, Werner; Lughofer, Edwin; Saminger-Platz, Susanne

2018-05-11

Multivariate calibration models often fail to extrapolate beyond the calibration samples because of changes associated with the instrumental response, environmental condition, or sample matrix. Most of the current methods used to adapt a source calibration model to a target domain exclusively apply to calibration transfer between similar analytical devices, while generic methods for calibration-model adaptation are largely missing. To fill this gap, we here introduce domain-invariant partial-least-squares (di-PLS) regression, which extends ordinary PLS by a domain regularizer in order to align the source and target distributions in the latent-variable space. We show that a domain-invariant weight vector can be derived in closed form, which allows the integration of (partially) labeled data from the source and target domains as well as entirely unlabeled data from the latter. We test our approach on a simulated data set where the aim is to desensitize a source calibration model to an unknown interfering agent in the target domain (i.e., unsupervised model adaptation). In addition, we demonstrate unsupervised, semisupervised, and supervised model adaptation by di-PLS on two real-world near-infrared (NIR) spectroscopic data sets.

A Comparison of Three Conditional Growth Percentile Methods: Student Growth Percentiles, Percentile Rank Residuals, and a Matching Method

ERIC Educational Resources Information Center

Wyse, Adam E.; Seo, Dong Gi

2014-01-01

This article provides a brief overview and comparison of three conditional growth percentile methods; student growth percentiles, percentile rank residuals, and a nonparametric matching method. These approaches seek to describe student growth in terms of the relative percentile ranking of a student in relationship to students that had the same…

Rephasing invariants of the Cabibbo-Kobayashi- Maskawa matrix

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

Pérez R, H.; Kielanowski, P., E-mail: kiel@fis.cinvestav.mx; Juárez W, S. R., E-mail: rebeca@esfm.ipn.mx

2016-03-15

The paper is motivated by the importance of the rephasing invariance of the CKM (Cabibbo-Kobayashi-Maskawa) matrix observables. These observables appear in the discussion of the CP violation in the standard model (Jarlskog invariant) and also in the renormalization group equations for the quark Yukawa couplings. Our discussion is based on the general phase invariant monomials built out of the CKM matrix elements and their conjugates. We show that there exist 30 fundamental phase invariant monomials and 18 of them are a product of 4 CKM matrix elements and 12 are a product of 6 CKM matrix elements. In the mainmore » theorem we show that a general rephasing invariant monomial can be expressed as a product of at most five factors: four of them are fundamental phase invariant monomials and the fifth factor consists of powers of squares of absolute values of the CKM matrix elements. We also show that the imaginary part of any rephasing invariant monomial is proportional to the Jarlskog’s invariant J or is 0.« less

Multi-sensor image registration based on algebraic projective invariants.

PubMed

Li, Bin; Wang, Wei; Ye, Hao

2013-04-22

A new automatic feature-based registration algorithm is presented for multi-sensor images with projective deformation. Contours are firstly extracted from both reference and sensed images as basic features in the proposed method. Since it is difficult to design a projective-invariant descriptor from the contour information directly, a new feature named Five Sequential Corners (FSC) is constructed based on the corners detected from the extracted contours. By introducing algebraic projective invariants, we design a descriptor for each FSC that is ensured to be robust against projective deformation. Further, no gray scale related information is required in calculating the descriptor, thus it is also robust against the gray scale discrepancy between the multi-sensor image pairs. Experimental results utilizing real image pairs are presented to show the merits of the proposed registration method.

Invariant and partially-invariant solutions of the equations describing a non-stationary and isentropic flow for an ideal and compressible fluid in (3 + 1) dimensions

NASA Astrophysics Data System (ADS)

Grundland, A. M.; Lalague, L.

1996-04-01

This paper presents a new method of constructing, certain classes of solutions of a system of partial differential equations (PDEs) describing the non-stationary and isentropic flow for an ideal compressible fluid. A generalization of the symmetry reduction method to the case of partially-invariant solutions (PISs) has been formulated. We present a new algorithm for constructing PISs and discuss in detail the necessary conditions for the existence of non-reducible PISs. All these solutions have the defect structure 0305-4470/29/8/019/img1 and are computed from four-dimensional symmetric subalgebras. These theoretical considerations are illustrated by several examples. Finally, some new classes of invariant solutions obtained by the symmetry reduction method are included. These solutions represent central, conical, rational, spherical, cylindrical and non-scattering double waves.

Generation of spirally polarized propagation-invariant beam using fiber microaxicon.

PubMed

Philip, Geo M; Viswanathan, Nirmal K

2011-10-01

We present here a fiber microaxicon (MA)based method to generate spirally polarized propagation-invariant optical beam. MA chemically etched in the tip of a two-mode fiber efficiently converts the generic cylindrically polarized vortex fiber mode into a spirally polarized propagation-invariant (Bessel-type) beam via radial dependence of polarization rotation angle. The combined roles of helico-conical phase and nonparaxial propagation in the generation and characteristics of the output beam from the fiber MA are discussed. © 2011 Optical Society of America

Contrast Invariant Interest Point Detection by Zero-Norm LoG Filter.

PubMed

Zhenwei Miao; Xudong Jiang; Kim-Hui Yap

2016-01-01

The Laplacian of Gaussian (LoG) filter is widely used in interest point detection. However, low-contrast image structures, though stable and significant, are often submerged by the high-contrast ones in the response image of the LoG filter, and hence are difficult to be detected. To solve this problem, we derive a generalized LoG filter, and propose a zero-norm LoG filter. The response of the zero-norm LoG filter is proportional to the weighted number of bright/dark pixels in a local region, which makes this filter be invariant to the image contrast. Based on the zero-norm LoG filter, we develop an interest point detector to extract local structures from images. Compared with the contrast dependent detectors, such as the popular scale invariant feature transform detector, the proposed detector is robust to illumination changes and abrupt variations of images. Experiments on benchmark databases demonstrate the superior performance of the proposed zero-norm LoG detector in terms of the repeatability and matching score of the detected points as well as the image recognition rate under different conditions.

Galilean-invariant preconditioned central-moment lattice Boltzmann method without cubic velocity errors for efficient steady flow simulations

NASA Astrophysics Data System (ADS)

Hajabdollahi, Farzaneh; Premnath, Kannan N.

2018-05-01

Lattice Boltzmann (LB) models used for the computation of fluid flows represented by the Navier-Stokes (NS) equations on standard lattices can lead to non-Galilean-invariant (GI) viscous stress involving cubic velocity errors. This arises from the dependence of their third-order diagonal moments on the first-order moments for standard lattices, and strategies have recently been introduced to restore Galilean invariance without such errors using a modified collision operator involving corrections to either the relaxation times or the moment equilibria. Convergence acceleration in the simulation of steady flows can be achieved by solving the preconditioned NS equations, which contain a preconditioning parameter that can be used to tune the effective sound speed, and thereby alleviating the numerical stiffness. In the present paper, we present a GI formulation of the preconditioned cascaded central-moment LB method used to solve the preconditioned NS equations, which is free of cubic velocity errors on a standard lattice, for steady flows. A Chapman-Enskog analysis reveals the structure of the spurious non-GI defect terms and it is demonstrated that the anisotropy of the resulting viscous stress is dependent on the preconditioning parameter, in addition to the fluid velocity. It is shown that partial correction to eliminate the cubic velocity defects is achieved by scaling the cubic velocity terms in the off-diagonal third-order moment equilibria with the square of the preconditioning parameter. Furthermore, we develop additional corrections based on the extended moment equilibria involving gradient terms with coefficients dependent locally on the fluid velocity and the preconditioning parameter. Such parameter dependent corrections eliminate the remaining truncation errors arising from the degeneracy of the diagonal third-order moments and fully restore Galilean invariance without cubic defects for the preconditioned LB scheme on a standard lattice. Several

Adiabatic invariance with first integrals of motion

NASA Astrophysics Data System (ADS)

Adib, Artur B.

2002-10-01

The construction of a microthermodynamic formalism for isolated systems based on the concept of adiabatic invariance is an old but seldom appreciated effort in the literature, dating back at least to P. Hertz [Ann. Phys. (Leipzig) 33, 225 (1910)]. An apparently independent extension of such formalism for systems bearing additional first integrals of motion was recently proposed by Hans H. Rugh [Phys. Rev. E 64, 055101 (2001)], establishing the concept of adiabatic invariance even in such singular cases. After some remarks in connection with the formalism pioneered by Hertz, it will be suggested that such an extension can incidentally explain the success of a dynamical method for computing the entropy of classical interacting fluids, at least in some potential applications where the presence of additional first integrals cannot be ignored.

The Concept of Invariance in School Mathematics

ERIC Educational Resources Information Center

Libeskind, Shlomo; Stupel, Moshe; Oxman, Victor

2018-01-01

In this paper, we highlight examples from school mathematics in which invariance did not receive the attention it deserves. We describe how problems related to invariance stimulated the interest of both teachers and students. In school mathematics, invariance is of particular relevance in teaching and learning geometry. When permitted change…

Transformation-invariant and nonparametric monotone smooth estimation of ROC curves.

PubMed

Du, Pang; Tang, Liansheng

2009-01-30

When a new diagnostic test is developed, it is of interest to evaluate its accuracy in distinguishing diseased subjects from non-diseased subjects. The accuracy of the test is often evaluated by receiver operating characteristic (ROC) curves. Smooth ROC estimates are often preferable for continuous test results when the underlying ROC curves are in fact continuous. Nonparametric and parametric methods have been proposed by various authors to obtain smooth ROC curve estimates. However, there are certain drawbacks with the existing methods. Parametric methods need specific model assumptions. Nonparametric methods do not always satisfy the inherent properties of the ROC curves, such as monotonicity and transformation invariance. In this paper we propose a monotone spline approach to obtain smooth monotone ROC curves. Our method ensures important inherent properties of the underlying ROC curves, which include monotonicity, transformation invariance, and boundary constraints. We compare the finite sample performance of the newly proposed ROC method with other ROC smoothing methods in large-scale simulation studies. We illustrate our method through a real life example. Copyright (c) 2008 John Wiley & Sons, Ltd.

Measuring Scale Invariance between and within Subjects.

ERIC Educational Resources Information Center

Benson, Jeri; Hocevar, Dennis

The present paper represents a demonstration of how LISREL V can be used to investigate scale invariance (1) across time (its relationship to test-retest reliability), and (2) across groups. Five criteria were established to test scale invariance across time and four criteria were established to test scale invariance across groups. Using the…

Indoor Location Sensing with Invariant Wi-Fi Received Signal Strength Fingerprinting

PubMed Central

Husen, Mohd Nizam; Lee, Sukhan

2016-01-01

A method of location fingerprinting based on the Wi-Fi received signal strength (RSS) in an indoor environment is presented. The method aims to overcome the RSS instability due to varying channel disturbances in time by introducing the concept of invariant RSS statistics. The invariant RSS statistics represent here the RSS distributions collected at individual calibration locations under minimal random spatiotemporal disturbances in time. The invariant RSS statistics thus collected serve as the reference pattern classes for fingerprinting. Fingerprinting is carried out at an unknown location by identifying the reference pattern class that maximally supports the spontaneous RSS sensed from individual Wi-Fi sources. A design guideline is also presented as a rule of thumb for estimating the number of Wi-Fi signal sources required to be available for any given number of calibration locations under a certain level of random spatiotemporal disturbances. Experimental results show that the proposed method not only provides 17% higher success rate than conventional ones but also removes the need for recalibration. Furthermore, the resolution is shown finer by 40% with the execution time more than an order of magnitude faster than the conventional methods. These results are also backed up by theoretical analysis. PMID:27845711

Three invariant Hi-C interaction patterns: Applications to genome assembly.

PubMed

Oddes, Sivan; Zelig, Aviv; Kaplan, Noam

2018-06-01

Assembly of reference-quality genomes from next-generation sequencing data is a key challenge in genomics. Recently, we and others have shown that Hi-C data can be used to address several outstanding challenges in the field of genome assembly. This principle has since been developed in academia and industry, and has been used in the assembly of several major genomes. In this paper, we explore the central principles underlying Hi-C-based assembly approaches, by quantitatively defining and characterizing three invariant Hi-C interaction patterns on which these approaches can build: Intrachromosomal interaction enrichment, distance-dependent interaction decay and local interaction smoothness. Specifically, we evaluate to what degree each invariant pattern holds on a single locus level in different species, cell types and Hi-C map resolutions. We find that these patterns are generally consistent across species and cell types but are affected by sequencing depth, and that matrix balancing improves consistency of loci with all three invariant patterns. Finally, we overview current Hi-C-based assembly approaches in light of these invariant patterns and demonstrate how local interaction smoothness can be used to easily detect scaffolding errors in extremely sparse Hi-C maps. We suggest that simultaneously considering all three invariant patterns may lead to better Hi-C-based genome assembly methods. Copyright © 2018 Elsevier Inc. All rights reserved.

Complete set of invariants of a 4th order tensor: the 12 tasks of HARDI from ternary quartics.

PubMed

Papadopoulo, Théo; Ghosh, Aurobrata; Deriche, Rachid

2014-01-01

Invariants play a crucial role in Diffusion MRI. In DTI (2nd order tensors), invariant scalars (FA, MD) have been successfully used in clinical applications. But DTI has limitations and HARDI models (e.g. 4th order tensors) have been proposed instead. These, however, lack invariant features and computing them systematically is challenging. We present a simple and systematic method to compute a functionally complete set of invariants of a non-negative 3D 4th order tensor with respect to SO3. Intuitively, this transforms the tensor's non-unique ternary quartic (TQ) decomposition (from Hilbert's theorem) to a unique canonical representation independent of orientation - the invariants. The method consists of two steps. In the first, we reduce the 18 degrees-of-freedom (DOF) of a TQ representation by 3-DOFs via an orthogonal transformation. This transformation is designed to enhance a rotation-invariant property of choice of the 3D 4th order tensor. In the second, we further reduce 3-DOFs via a 3D rotation transformation of coordinates to arrive at a canonical set of invariants to SO3 of the tensor. The resulting invariants are, by construction, (i) functionally complete, (ii) functionally irreducible (if desired), (iii) computationally efficient and (iv) reversible (mappable to the TQ coefficients or shape); which is the novelty of our contribution in comparison to prior work. Results from synthetic and real data experiments validate the method and indicate its importance.

Robust photometric invariant features from the color tensor.

PubMed

van de Weijer, Joost; Gevers, Theo; Smeulders, Arnold W M

2006-01-01

Luminance-based features are widely used as low-level input for computer vision applications, even when color data is available. The extension of feature detection to the color domain prevents information loss due to isoluminance and allows us to exploit the photometric information. To fully exploit the extra information in the color data, the vector nature of color data has to be taken into account and a sound framework is needed to combine feature and photometric invariance theory. In this paper, we focus on the structure tensor, or color tensor, which adequately handles the vector nature of color images. Further, we combine the features based on the color tensor with photometric invariant derivatives to arrive at photometric invariant features. We circumvent the drawback of unstable photometric invariants by deriving an uncertainty measure to accompany the photometric invariant derivatives. The uncertainty is incorporated in the color tensor, hereby allowing the computation of robust photometric invariant features. The combination of the photometric invariance theory and tensor-based features allows for detection of a variety of features such as photometric invariant edges, corners, optical flow, and curvature. The proposed features are tested for noise characteristics and robustness to photometric changes. Experiments show that the proposed features are robust to scene incidental events and that the proposed uncertainty measure improves the applicability of full invariants.

Proton-decaying, light nuclei accessed via the invariant-mass method

NASA Astrophysics Data System (ADS)

Brown, Kyle

2017-01-01

Two-nucleon decay is the most recently discovered nuclear decay mode. For proton-rich nuclei, the majority of multi-proton decays occur via sequential steps of one-proton emission. Direct two-proton (2p) decay was believed to occur only in even-Z nuclei beyond the proton drip line where one-proton decay is energy forbidden. This has been observed for the ground states of around a dozen nuclei including 6Be, the lightest case, and 54Zn, the heaviest case. Direct 2p decay has also recently been observed for isobaric analog states where all possible 1p intermediates are either isospin allowed and energy forbidden, or energy-allowed and isospin forbidden. For light proton emitters, the lifetimes are short enough that the invariant-mass technique is ideal for measuring the decay energy, intrinsic width and, for multi-proton decays, the momentum correlations between the fragments. I will describe recent measurements of proton emitters using the invariant-mass technique with the High Resolution Array (HiRA). I will present a new, high-statistics measurement on the sequential 2p decay of excited states in 17Ne. Measuring the momentum correlations between the decay fragments allow us to determine the 1p intermediate state through which the decay proceeds. I will present data on the isobaric-analog pair 8C and 8BIAS, which highlight the two known types of direct 2p decay. I will also present the first observation of 17Na, which is unbound with respect to three-proton emission. Finally I will present a new measurement on the width of the first-excited state of 9C and compare to recent theoretical calculations.

Neural networks for data compression and invariant image recognition

NASA Technical Reports Server (NTRS)

Gardner, Sheldon

1989-01-01

An approach to invariant image recognition (I2R), based upon a model of biological vision in the mammalian visual system (MVS), is described. The complete I2R model incorporates several biologically inspired features: exponential mapping of retinal images, Gabor spatial filtering, and a neural network associative memory. In the I2R model, exponentially mapped retinal images are filtered by a hierarchical set of Gabor spatial filters (GSF) which provide compression of the information contained within a pixel-based image. A neural network associative memory (AM) is used to process the GSF coded images. We describe a 1-D shape function method for coding of scale and rotationally invariant shape information. This method reduces image shape information to a periodic waveform suitable for coding as an input vector to a neural network AM. The shape function method is suitable for near term applications on conventional computing architectures equipped with VLSI FFT chips to provide a rapid image search capability.

The functional equation truncation method for approximating slow invariant manifolds: a rapid method for computing intrinsic low-dimensional manifolds.

PubMed

Roussel, Marc R; Tang, Terry

2006-12-07

A slow manifold is a low-dimensional invariant manifold to which trajectories nearby are rapidly attracted on the way to the equilibrium point. The exact computation of the slow manifold simplifies the model without sacrificing accuracy on the slow time scales of the system. The Maas-Pope intrinsic low-dimensional manifold (ILDM) [Combust. Flame 88, 239 (1992)] is frequently used as an approximation to the slow manifold. This approximation is based on a linearized analysis of the differential equations and thus neglects curvature. We present here an efficient way to calculate an approximation equivalent to the ILDM. Our method, called functional equation truncation (FET), first develops a hierarchy of functional equations involving higher derivatives which can then be truncated at second-derivative terms to explicitly neglect the curvature. We prove that the ILDM and FET-approximated (FETA) manifolds are identical for the one-dimensional slow manifold of any planar system. In higher-dimensional spaces, the ILDM and FETA manifolds agree to numerical accuracy almost everywhere. Solution of the FET equations is, however, expected to generally be faster than the ILDM method.

Integral reinforcement learning for continuous-time input-affine nonlinear systems with simultaneous invariant explorations.

PubMed

Lee, Jae Young; Park, Jin Bae; Choi, Yoon Ho

2015-05-01

This paper focuses on a class of reinforcement learning (RL) algorithms, named integral RL (I-RL), that solve continuous-time (CT) nonlinear optimal control problems with input-affine system dynamics. First, we extend the concepts of exploration, integral temporal difference, and invariant admissibility to the target CT nonlinear system that is governed by a control policy plus a probing signal called an exploration. Then, we show input-to-state stability (ISS) and invariant admissibility of the closed-loop systems with the policies generated by integral policy iteration (I-PI) or invariantly admissible PI (IA-PI) method. Based on these, three online I-RL algorithms named explorized I-PI and integral Q -learning I, II are proposed, all of which generate the same convergent sequences as I-PI and IA-PI under the required excitation condition on the exploration. All the proposed methods are partially or completely model free, and can simultaneously explore the state space in a stable manner during the online learning processes. ISS, invariant admissibility, and convergence properties of the proposed methods are also investigated, and related with these, we show the design principles of the exploration for safe learning. Neural-network-based implementation methods for the proposed schemes are also presented in this paper. Finally, several numerical simulations are carried out to verify the effectiveness of the proposed methods.

Galilean-invariant algorithm coupling immersed moving boundary conditions and Lees-Edwards boundary conditions

NASA Astrophysics Data System (ADS)

Zhou, Guofeng; Wang, Limin; Wang, Xiaowei; Ge, Wei

2011-12-01

Many investigators have coupled the Lees-Edwards boundary conditions (LEBCs) and suspension methods in the framework of the lattice Boltzmann method to study the pure bulk properties of particle-fluid suspensions. However, these suspension methods are all link-based and are more or less exposed to the disadvantages of violating Galilean invariance. In this paper, we have coupled LEBCs with a node-based suspension method, which is demonstrated to be Galilean invariant in benchmark simulations. We use the coupled algorithm to predict the viscosity of a particle-fluid suspension at very low Reynolds number, and the simulation results are in good agreement with the semiempirical Krieger-Dougherty formula.

An evaluation of exact matching and propensity score methods as applied in a comparative effectiveness study of inhaled corticosteroids in asthma

PubMed Central

Burden, Anne; Roche, Nicolas; Miglio, Cristiana; Hillyer, Elizabeth V; Postma, Dirkje S; Herings, Ron MC; Overbeek, Jetty A; Khalid, Javaria Mona; van Eickels, Daniela; Price, David B

2017-01-01

Background Cohort matching and regression modeling are used in observational studies to control for confounding factors when estimating treatment effects. Our objective was to evaluate exact matching and propensity score methods by applying them in a 1-year pre–post historical database study to investigate asthma-related outcomes by treatment. Methods We drew on longitudinal medical record data in the PHARMO database for asthma patients prescribed the treatments to be compared (ciclesonide and fine-particle inhaled corticosteroid [ICS]). Propensity score methods that we evaluated were propensity score matching (PSM) using two different algorithms, the inverse probability of treatment weighting (IPTW), covariate adjustment using the propensity score, and propensity score stratification. We defined balance, using standardized differences, as differences of <10% between cohorts. Results Of 4064 eligible patients, 1382 (34%) were prescribed ciclesonide and 2682 (66%) fine-particle ICS. The IPTW and propensity score-based methods retained more patients (96%–100%) than exact matching (90%); exact matching selected less severe patients. Standardized differences were >10% for four variables in the exact-matched dataset and <10% for both PSM algorithms and the weighted pseudo-dataset used in the IPTW method. With all methods, ciclesonide was associated with better 1-year asthma-related outcomes, at one-third the prescribed dose, than fine-particle ICS; results varied slightly by method, but direction and statistical significance remained the same. Conclusion We found that each method has its particular strengths, and we recommend at least two methods be applied for each matched cohort study to evaluate the robustness of the findings. Balance diagnostics should be applied with all methods to check the balance of confounders between treatment cohorts. If exact matching is used, the calculation of a propensity score could be useful to identify variables that require

Evolution of heliospheric magnetized configurations via topological invariants

NASA Astrophysics Data System (ADS)

Roth, Ilan

2013-07-01

The analogy between magnetohydrodynamics (MHD) and knot theory is utilized in presenting a new method for an analysis of stability and evolution of complex magnetic heliospheric flux tubes. Planar projection of a three-dimensional magnetic configuration depicts the structure as a two-dimensional diagram with crossings, to which one may assign mathematical operations leading to robust topological invariants. These invariants enrich the topological information of magnetic configurations beyond helicity. It is conjectured that the field which emerges from the solar photosphere is structured as one of the simplest knots-unknot or prime knot-and these flux ropes are then stretched while carried by the solar wind into the interplanetary medium. Preservation of invariants for small diffusivity and large cross section of the emerging magnetic flux makes them impervious to large scale reconnection, allowing us to predict the observed structures at 1 AU as elongated prime knots. Similar structures may be observed in magnetic clouds which got disconnected from their footpoints and in ion drop-out configurations from a compact flare source in solar impulsive solar events. Observation of small scale magnetic features consistent with prime knots may indicate spatial intermittency and non-Gaussian statistics in the turbulent cascade process. For flux tubes with higher resistivity, magnetic energy decay rate should decrease with increased knot complexity as the invariants are then harder to be violated. These observations could be confirmed if adjacent satellites happen to measure distinctly oriented magnetic fields with directionally varying suprathermal particle fluxes.

A method for automatic matching of multi-timepoint findings for enhanced clinical workflow

NASA Astrophysics Data System (ADS)

Raghupathi, Laks; Dinesh, MS; Devarakota, Pandu R.; Valadez, Gerardo Hermosillo; Wolf, Matthias

2013-03-01

Non-interventional diagnostics (CT or MR) enables early identification of diseases like cancer. Often, lesion growth assessment done during follow-up is used to distinguish between benign and malignant ones. Thus correspondences need to be found for lesions localized at each time point. Manually matching the radiological findings can be time consuming as well as tedious due to possible differences in orientation and position between scans. Also, the complicated nature of the disease makes the physicians to rely on multiple modalities (PETCT, PET-MR) where it is even more challenging. Here, we propose an automatic feature-based matching that is robust to change in organ volume, subpar or no registration that can be done with very less computations. Traditional matching methods rely mostly on accurate image registration and applying the resulting deformation map on the findings coordinates. This has disadvantages when accurate registration is time-consuming or may not be possible due to vast organ volume differences between scans. Our novel matching proposes supervised learning by taking advantage of the underlying CAD features that are already present and considering the matching as a classification problem. In addition, the matching can be done extremely fast and at reasonable accuracy even when the image registration fails for some reason. Experimental results∗ on real-world multi-time point thoracic CT data showed an accuracy of above 90% with negligible false positives on a variety of registration scenarios.

Real-space mapping of topological invariants using artificial neural networks

NASA Astrophysics Data System (ADS)

Carvalho, D.; García-Martínez, N. A.; Lado, J. L.; Fernández-Rossier, J.

2018-03-01

Topological invariants allow one to characterize Hamiltonians, predicting the existence of topologically protected in-gap modes. Those invariants can be computed by tracing the evolution of the occupied wave functions under twisted boundary conditions. However, those procedures do not allow one to calculate a topological invariant by evaluating the system locally, and thus require information about the wave functions in the whole system. Here we show that artificial neural networks can be trained to identify the topological order by evaluating a local projection of the density matrix. We demonstrate this for two different models, a one-dimensional topological superconductor and a two-dimensional quantum anomalous Hall state, both with spatially modulated parameters. Our neural network correctly identifies the different topological domains in real space, predicting the location of in-gap states. By combining a neural network with a calculation of the electronic states that uses the kernel polynomial method, we show that the local evaluation of the invariant can be carried out by evaluating a local quantity, in particular for systems without translational symmetry consisting of tens of thousands of atoms. Our results show that supervised learning is an efficient methodology to characterize the local topology of a system.

Some estimation formulae for continuous time-invariant linear systems

NASA Technical Reports Server (NTRS)

Bierman, G. J.; Sidhu, G. S.

1975-01-01

In this brief paper we examine a Riccati equation decomposition due to Reid and Lainiotis and apply the result to the continuous time-invariant linear filtering problem. Exploitation of the time-invariant structure leads to integration-free covariance recursions which are of use in covariance analyses and in filter implementations. A super-linearly convergent iterative solution to the algebraic Riccati equation (ARE) is developed. The resulting algorithm, arranged in a square-root form, is thought to be numerically stable and competitive with other ARE solution methods. Certain covariance relations that are relevant to the fixed-point and fixed-lag smoothing problems are also discussed.

Metric Ranking of Invariant Networks with Belief Propagation

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

Tao, Changxia; Ge, Yong; Song, Qinbao

The management of large-scale distributed information systems relies on the effective use and modeling of monitoring data collected at various points in the distributed information systems. A promising approach is to discover invariant relationships among the monitoring data and generate invariant networks, where a node is a monitoring data source (metric) and a link indicates an invariant relationship between two monitoring data. Such an invariant network representation can help system experts to localize and diagnose the system faults by examining those broken invariant relationships and their related metrics, because system faults usually propagate among the monitoring data and eventually leadmore » to some broken invariant relationships. However, at one time, there are usually a lot of broken links (invariant relationships) within an invariant network. Without proper guidance, it is difficult for system experts to manually inspect this large number of broken links. Thus, a critical challenge is how to effectively and efficiently rank metrics (nodes) of invariant networks according to the anomaly levels of metrics. The ranked list of metrics will provide system experts with useful guidance for them to localize and diagnose the system faults. To this end, we propose to model the nodes and the broken links as a Markov Random Field (MRF), and develop an iteration algorithm to infer the anomaly of each node based on belief propagation (BP). Finally, we validate the proposed algorithm on both realworld and synthetic data sets to illustrate its effectiveness.« less

Permutation invariant polynomial neural network approach to fitting potential energy surfaces. II. Four-atom systems

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

Li, Jun; Jiang, Bin; Guo, Hua, E-mail: hguo@unm.edu

2013-11-28

A rigorous, general, and simple method to fit global and permutation invariant potential energy surfaces (PESs) using neural networks (NNs) is discussed. This so-called permutation invariant polynomial neural network (PIP-NN) method imposes permutation symmetry by using in its input a set of symmetry functions based on PIPs. For systems with more than three atoms, it is shown that the number of symmetry functions in the input vector needs to be larger than the number of internal coordinates in order to include both the primary and secondary invariant polynomials. This PIP-NN method is successfully demonstrated in three atom-triatomic reactive systems, resultingmore » in full-dimensional global PESs with average errors on the order of meV. These PESs are used in full-dimensional quantum dynamical calculations.« less

Assessing cross-cultural differences through use of multiple-group invariance analyses.

PubMed

Stein, Judith A; Lee, Jerry W; Jones, Patricia S

2006-12-01

The use of structural equation modeling in cross-cultural personality research has become a popular method for testing measurement invariance. In this report, we present an example of testing measurement invariance using the Sense of Coherence Scale of Antonovsky (1993) in 3 ethnic groups: Chinese, Japanese, and Whites. In a series of increasingly restrictive constraints on the measurement models of the 3 groups, we demonstrate how to assess differences among the groups. We also provide an example of construct validation.

Memory assessment and depression: testing for factor structure and measurement invariance of the Wechsler Memory Scale-Fourth Edition across a clinical and matched control sample.

PubMed

Pauls, Franz; Petermann, Franz; Lepach, Anja Christina

2013-01-01

Between-group comparisons are permissible and meaningfully interpretable only if diagnostic instruments are proved to measure the same latent dimensions across different groups. Addressing this issue, the present study was carried out to provide a rigorous test of measurement invariance. Confirmatory factor analyses were used to determine which model solution could best explain memory performance as measured by the Wechsler Memory Scale-Fourth Edition (WMS-IV) in a clinical depression sample and in healthy controls. Multigroup confirmatory factor analysis was conducted to evaluate the evidence for measurement invariance. A three-factor model solution including the dimensions of auditory memory, visual memory, and visual working memory was identified to best fit the data in both samples, and measurement invariance was partially satisfied. The results supported clinical utility of the WMS-IV--that is, auditory and visual memory performances of patients with depressive disorders are interpretable on the basis of the WMS-IV standardization data. However, possible differences in visual working memory functions between healthy and depressed individuals could restrict comparisons of the WMS-IV working memory index.

The D 2 k R 4 invariants of mathcal{N} = 8 supergravity

NASA Astrophysics Data System (ADS)

Freedman, Daniel Z.; Tonni, Erik

2011-04-01

The existence of a linearized SUSY invariant for mathcal{N} = 8 supergravity whose gravitational components are usually called R 4 was established long ago by on-shell super-space arguments. Superspace and string theory methods have also established analogous higher dimensional D 2 k R 4 invariants. However, very little is known about the SUSY completions of these operators which involve other fields of the theory. In this paper we find the detailed component expansion of the linearized R 4 invariant starting from the corresponding superamplitude which generates all component matrix elements of the operator. It is then quite straightforward to extend results to the entire set of D 2 k R 4 operators.

An evaluation of exact matching and propensity score methods as applied in a comparative effectiveness study of inhaled corticosteroids in asthma.

PubMed

Burden, Anne; Roche, Nicolas; Miglio, Cristiana; Hillyer, Elizabeth V; Postma, Dirkje S; Herings, Ron Mc; Overbeek, Jetty A; Khalid, Javaria Mona; van Eickels, Daniela; Price, David B

2017-01-01

Cohort matching and regression modeling are used in observational studies to control for confounding factors when estimating treatment effects. Our objective was to evaluate exact matching and propensity score methods by applying them in a 1-year pre-post historical database study to investigate asthma-related outcomes by treatment. We drew on longitudinal medical record data in the PHARMO database for asthma patients prescribed the treatments to be compared (ciclesonide and fine-particle inhaled corticosteroid [ICS]). Propensity score methods that we evaluated were propensity score matching (PSM) using two different algorithms, the inverse probability of treatment weighting (IPTW), covariate adjustment using the propensity score, and propensity score stratification. We defined balance, using standardized differences, as differences of <10% between cohorts. Of 4064 eligible patients, 1382 (34%) were prescribed ciclesonide and 2682 (66%) fine-particle ICS. The IPTW and propensity score-based methods retained more patients (96%-100%) than exact matching (90%); exact matching selected less severe patients. Standardized differences were >10% for four variables in the exact-matched dataset and <10% for both PSM algorithms and the weighted pseudo-dataset used in the IPTW method. With all methods, ciclesonide was associated with better 1-year asthma-related outcomes, at one-third the prescribed dose, than fine-particle ICS; results varied slightly by method, but direction and statistical significance remained the same. We found that each method has its particular strengths, and we recommend at least two methods be applied for each matched cohort study to evaluate the robustness of the findings. Balance diagnostics should be applied with all methods to check the balance of confounders between treatment cohorts. If exact matching is used, the calculation of a propensity score could be useful to identify variables that require balancing, thereby informing the choice of

Using the Kernel Method of Test Equating for Estimating the Standard Errors of Population Invariance Measures. Research Report. ETS RR-06-20

ERIC Educational Resources Information Center

Moses, Tim

2006-01-01

Population invariance is an important requirement of test equating. An equating function is said to be population invariant when the choice of (sub)population used to compute the equating function does not matter. In recent studies, the extent to which equating functions are population invariant is typically addressed in terms of practical…

A scale-invariant internal representation of time.

PubMed

Shankar, Karthik H; Howard, Marc W

2012-01-01

We propose a principled way to construct an internal representation of the temporal stimulus history leading up to the present moment. A set of leaky integrators performs a Laplace transform on the stimulus function, and a linear operator approximates the inversion of the Laplace transform. The result is a representation of stimulus history that retains information about the temporal sequence of stimuli. This procedure naturally represents more recent stimuli more accurately than less recent stimuli; the decrement in accuracy is precisely scale invariant. This procedure also yields time cells that fire at specific latencies following the stimulus with a scale-invariant temporal spread. Combined with a simple associative memory, this representation gives rise to a moment-to-moment prediction that is also scale invariant in time. We propose that this scale-invariant representation of temporal stimulus history could serve as an underlying representation accessible to higher-level behavioral and cognitive mechanisms. In order to illustrate the potential utility of this scale-invariant representation in a variety of fields, we sketch applications using minimal performance functions to problems in classical conditioning, interval timing, scale-invariant learning in autoshaping, and the persistence of the recency effect in episodic memory across timescales.

Equivariant K3 invariants

DOE PAGES

Cheng, Miranda C. N.; Duncan, John F. R.; Harrison, Sarah M.; ...

2017-01-01

In this note, we describe a connection between the enumerative geometry of curves in K3 surfaces and the chiral ring of an auxiliary superconformal field theory. We consider the invariants calculated by Yau–Zaslow (capturing the Euler characters of the moduli spaces of D2-branes on curves of given genus), together with their refinements to carry additional quantum numbers by Katz–Klemm–Vafa (KKV), and Katz–Klemm–Pandharipande (KKP). We show that these invariants can be reproduced by studying the Ramond ground states of an auxiliary chiral superconformal field theory which has recently been observed to give rise to mock modular moonshine for a variety ofmore » sporadic simple groups that are subgroups of Conway’s group. We also study equivariant versions of these invariants. A K3 sigma model is specified by a choice of 4-plane in the K3 D-brane charge lattice. Symmetries of K3 sigma models are naturally identified with 4-plane preserving subgroups of the Conway group, according to the work of Gaberdiel–Hohenegger–Volpato, and one may consider corresponding equivariant refined K3 Gopakumar–Vafa invariants. The same symmetries naturally arise in the auxiliary CFT state space, affording a suggestive alternative view of the same computation. We comment on a lift of this story to the generating function of elliptic genera of symmetric products of K3 surfaces.« less

Photometric calibration of the COMBO-17 survey with the Softassign Procrustes Matching method

NASA Astrophysics Data System (ADS)

Sheikhbahaee, Z.; Nakajima, R.; Erben, T.; Schneider, P.; Hildebrandt, H.; Becker, A. C.

2017-11-01

Accurate photometric calibration of optical data is crucial for photometric redshift estimation. We present the Softassign Procrustes Matching (SPM) method to improve the colour calibration upon the commonly used Stellar Locus Regression (SLR) method for the COMBO-17 survey. Our colour calibration approach can be categorised as a point-set matching method, which is frequently used in medical imaging and pattern recognition. We attain a photometric redshift precision Δz/(1 + zs) of better than 2 per cent. Our method is based on aligning the stellar locus of the uncalibrated stars to that of a spectroscopic sample of the Sloan Digital Sky Survey standard stars. We achieve our goal by finding a correspondence matrix between the two point-sets and applying the matrix to estimate the appropriate translations in multidimensional colour space. The SPM method is able to find the translation between two point-sets, despite the existence of noise and incompleteness of the common structures in the sets, as long as there is a distinct structure in at least one of the colour-colour pairs. We demonstrate the precision of our colour calibration method with a mock catalogue. The SPM colour calibration code is publicly available at https://neuronphysics@bitbucket.org/neuronphysics/spm.git.

The gap values in the profile matching method by fuzzy logic

NASA Astrophysics Data System (ADS)

Sitepu, S. A.; Efendi, S.; Situmorang, Z.

2018-03-01

In this research, the determination of the appropriate values of Gap for the assessment of promotion criteria of position in an institution / company. In this study the authors use Fuzzy Sugeno logic on the determination of Gap values used in Profile Matching method. Test results of 5 employees obtained the eligibility of promotion with the position of Z* values between in 3.20 to 4.11.

How does the brain rapidly learn and reorganize view-invariant and position-invariant object representations in the inferotemporal cortex?

PubMed

Cao, Yongqiang; Grossberg, Stephen; Markowitz, Jeffrey

2011-12-01

All primates depend for their survival on being able to rapidly learn about and recognize objects. Objects may be visually detected at multiple positions, sizes, and viewpoints. How does the brain rapidly learn and recognize objects while scanning a scene with eye movements, without causing a combinatorial explosion in the number of cells that are needed? How does the brain avoid the problem of erroneously classifying parts of different objects together at the same or different positions in a visual scene? In monkeys and humans, a key area for such invariant object category learning and recognition is the inferotemporal cortex (IT). A neural model is proposed to explain how spatial and object attention coordinate the ability of IT to learn invariant category representations of objects that are seen at multiple positions, sizes, and viewpoints. The model clarifies how interactions within a hierarchy of processing stages in the visual brain accomplish this. These stages include the retina, lateral geniculate nucleus, and cortical areas V1, V2, V4, and IT in the brain's What cortical stream, as they interact with spatial attention processes within the parietal cortex of the Where cortical stream. The model builds upon the ARTSCAN model, which proposed how view-invariant object representations are generated. The positional ARTSCAN (pARTSCAN) model proposes how the following additional processes in the What cortical processing stream also enable position-invariant object representations to be learned: IT cells with persistent activity, and a combination of normalizing object category competition and a view-to-object learning law which together ensure that unambiguous views have a larger effect on object recognition than ambiguous views. The model explains how such invariant learning can be fooled when monkeys, or other primates, are presented with an object that is swapped with another object during eye movements to foveate the original object. The swapping procedure is

Geometric invariance of compressible turbulent boundary layers

NASA Astrophysics Data System (ADS)

Bi, Wei-Tao; Wu, Bin; She, Zhen-Su; Hussain, Fazle

2015-11-01

A symmetry based approach is applied to analyze the mean velocity and temperature fields of compressible, flat plate turbulent boundary layers (CTBL). A Reynolds stress length scale and a turbulent heat flux length scale are identified to possess the same defect scaling law in the CTBL bulk, which is solely owing to the constraint of the wall to the geometry of the wall-attached eddies, but invariant to compressibility and wall heat transfer. This invariance is called the geometric invariance of CTBL eddies and is likely the origin of the Mach number invariance of Morkovin's hypothesis, as well as the similarity of energy and momentum transports. A closure for the turbulent transport by using the invariant lengths is attainted to predict the mean velocity and temperature profiles in the CTBL bulk- superior to the van Driest transformation and the Reynolds analogy based relations for its sound physics and higher accuracy. Additionally, our approach offers a new understanding of turbulent Prandtl number.

Multiscale Rotation-Invariant Convolutional Neural Networks for Lung Texture Classification.

PubMed

Wang, Qiangchang; Zheng, Yuanjie; Yang, Gongping; Jin, Weidong; Chen, Xinjian; Yin, Yilong

2018-01-01

We propose a new multiscale rotation-invariant convolutional neural network (MRCNN) model for classifying various lung tissue types on high-resolution computed tomography. MRCNN employs Gabor-local binary pattern that introduces a good property in image analysis-invariance to image scales and rotations. In addition, we offer an approach to deal with the problems caused by imbalanced number of samples between different classes in most of the existing works, accomplished by changing the overlapping size between the adjacent patches. Experimental results on a public interstitial lung disease database show a superior performance of the proposed method to state of the art.

Citation Matching in Sanskrit Corpora Using Local Alignment

NASA Astrophysics Data System (ADS)

Prasad, Abhinandan S.; Rao, Shrisha

Citation matching is the problem of finding which citation occurs in a given textual corpus. Most existing citation matching work is done on scientific literature. The goal of this paper is to present methods for performing citation matching on Sanskrit texts. Exact matching and approximate matching are the two methods for performing citation matching. The exact matching method checks for exact occurrence of the citation with respect to the textual corpus. Approximate matching is a fuzzy string-matching method which computes a similarity score between an individual line of the textual corpus and the citation. The Smith-Waterman-Gotoh algorithm for local alignment, which is generally used in bioinformatics, is used here for calculating the similarity score. This similarity score is a measure of the closeness between the text and the citation. The exact- and approximate-matching methods are evaluated and compared. The methods presented can be easily applied to corpora in other Indic languages like Kannada, Tamil, etc. The approximate-matching method can in particular be used in the compilation of critical editions and plagiarism detection in a literary work.

Comparison of accuracies of an intraoral spectrophotometer and conventional visual method for shade matching using two shade guide systems.

PubMed

Parameswaran, Vidhya; Anilkumar, S; Lylajam, S; Rajesh, C; Narayan, Vivek

2016-01-01

This in vitro study compared the shade matching abilities of an intraoral spectrophotometer and the conventional visual method using two shade guides. The results of previous investigations between color perceived by human observers and color assessed by instruments have been inconclusive. The objectives were to determine accuracies and interrater agreement of both methods and effectiveness of two shade guides with either method. In the visual method, 10 examiners with normal color vision matched target control shade tabs taken from the two shade guides (VITAPAN Classical™ and VITAPAN 3D Master™) with other full sets of the respective shade guides. Each tab was matched 3 times to determine repeatability of visual examiners. The spectrophotometric shade matching was performed by two independent examiners using an intraoral spectrophotometer (VITA Easyshade™) with five repetitions for each tab. Results revealed that visual method had greater accuracy than the spectrophotometer. The spectrophotometer; however, exhibited significantly better interrater agreement as compared to the visual method. While VITAPAN Classical shade guide was more accurate with the spectrophotometer, VITAPAN 3D Master shade guide proved better with visual method. This in vitro study clearly delineates the advantages and limitations of both methods. There were significant differences between the methods with the visual method producing more accurate results than the spectrophotometric method. The spectrophotometer showed far better interrater agreement scores irrespective of the shade guide used. Even though visual shade matching is subjective, it is not inferior and should not be underrated. Judicious combination of both techniques is imperative to attain a successful and esthetic outcome.

Match-bounded String Rewriting Systems

NASA Technical Reports Server (NTRS)

Geser, Alfons; Hofbauer, Dieter; Waldmann, Johannes

2003-01-01

We introduce a new class of automated proof methods for the termination of rewriting systems on strings. The basis of all these methods is to show that rewriting preserves regular languages. To this end, letters are annotated with natural numbers, called match heights. If the minimal height of all positions in a redex is h+1 then every position in the reduct will get height h+1. In a match-bounded system, match heights are globally bounded. Using recent results on deleting systems, we prove that rewriting by a match-bounded system preserves regular languages. Hence it is decidable whether a given rewriting system has a given match bound. We also provide a sufficient criterion for the abence of a match-bound. The problem of existence of a match-bound is still open. Match-boundedness for all strings can be used as an automated criterion for termination, for match-bounded systems are terminating. This criterion can be strengthened by requiring match-boundedness only for a restricted set of strings, for instance the set of right hand sides of forward closures.

The Invar tensor package: Differential invariants of Riemann

NASA Astrophysics Data System (ADS)

Martín-García, J. M.; Yllanes, D.; Portugal, R.

2008-10-01

the distribution. To obtain the Mathematica and Maple database files click on this link. Classification:1.5, 5 Does the new version supersede the previous version?:Yes. The previous version (1.0) only handled algebraic invariants. The current version (2.0) has been extended to cover differential invariants as well. Nature of problem:Manipulation and simplification of scalar polynomial expressions formed from the Riemann tensor and its covariant derivatives. Solution method:Algorithms of computational group theory to simplify expressions with tensors that obey permutation symmetries. Tables of syzygies of the scalar invariants of the Riemann tensor. Reasons for new version:With this new version, the user can manipulate differential invariants of the Riemann tensor. Differential invariants are required in many physical problems in classical and quantum gravity. Summary of revisions:The database of syzygies has been expanded by a factor of 30. New commands were added in order to deal with the enlarged database and to manipulate the covariant derivative. Restrictions:The present version only handles scalars, and not expressions with free indices. Additional comments:The distribution file for this program is over 53 Mbytes and therefore is not delivered directly when download or Email is requested. Instead a html file giving details of how the program can be obtained is sent. Running time:One second to fully reduce any monomial of the Riemann tensor up to degree 7 or order 10 in terms of independent invariants. The Mathematica notebook included in the distribution takes approximately 5 minutes to run.

Inflation in a Scale Invariant Universe

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

Ferreira, Pedro G.; Hill, Christopher T.; Noller, Johannes

A scale-invariant universe can have a period of accelerated expansion at early times: inflation. We use a frame-invariant approach to calculate inflationary observables in a scale invariant theory of gravity involving two scalar fields - the spectral indices, the tensor to scalar ratio, the level of isocurvature modes and non-Gaussianity. We show that scale symmetry leads to an exact cancellation of isocurvature modes and that, in the scale-symmetry broken phase, this theory is well described by a single scalar field theory. We find the predictions of this theory strongly compatible with current observations.

Optimal transfers between unstable periodic orbits using invariant manifolds

NASA Astrophysics Data System (ADS)

Davis, Kathryn E.; Anderson, Rodney L.; Scheeres, Daniel J.; Born, George H.

2011-03-01

This paper presents a method to construct optimal transfers between unstable periodic orbits of differing energies using invariant manifolds. The transfers constructed in this method asymptotically depart the initial orbit on a trajectory contained within the unstable manifold of the initial orbit and later, asymptotically arrive at the final orbit on a trajectory contained within the stable manifold of the final orbit. Primer vector theory is applied to a transfer to determine the optimal maneuvers required to create the bridging trajectory that connects the unstable and stable manifold trajectories. Transfers are constructed between unstable periodic orbits in the Sun-Earth, Earth-Moon, and Jupiter-Europa three-body systems. Multiple solutions are found between the same initial and final orbits, where certain solutions retrace interior portions of the trajectory. All transfers created satisfy the conditions for optimality. The costs of transfers constructed using manifolds are compared to the costs of transfers constructed without the use of manifolds. In all cases, the total cost of the transfer is significantly lower when invariant manifolds are used in the transfer construction. In many cases, the transfers that employ invariant manifolds are three times more efficient, in terms of fuel expenditure, than the transfer that do not. The decrease in transfer cost is accompanied by an increase in transfer time of flight.

Gromov-Witten invariants and localization

NASA Astrophysics Data System (ADS)

Morrison, David R.

2017-11-01

We give a pedagogical review of the computation of Gromov-Witten invariants via localization in 2D gauged linear sigma models. We explain the relationship between the two-sphere partition function of the theory and the Kähler potential on the conformal manifold. We show how the Kähler potential can be assembled from classical, perturbative, and non-perturbative contributions, and explain how the non-perturbative contributions are related to the Gromov-Witten invariants of the corresponding Calabi-Yau manifold. We then explain how localization enables efficient calculation of the two-sphere partition function and, ultimately, the Gromov-Witten invariants themselves. This is a contribution to the review issue ‘Localization techniques in quantum field theories’ (ed V Pestun and M Zabzine) which contains 17 chapters, available at [1].

Time reversal invariance for a nonlinear scatterer exhibiting contact acoustic nonlinearity

NASA Astrophysics Data System (ADS)

Blanloeuil, Philippe; Rose, L. R. Francis; Veidt, Martin; Wang, Chun H.

2018-03-01

The time reversal invariance of an ultrasonic plane wave interacting with a contact interface characterized by a unilateral contact law is investigated analytically and numerically. It is shown analytically that despite the contact nonlinearity, the re-emission of a time reversed version of the reflected and transmitted waves can perfectly recover the original pulse shape, thereby demonstrating time reversal invariance for this type of contact acoustic nonlinearity. With the aid of finite element modelling, the time-reversal analysis is extended to finite-size nonlinear scatterers such as closed cracks. The results show that time reversal invariance holds provided that all the additional frequencies generated during the forward propagation, such as higher harmonics, sub-harmonics and zero-frequency component, are fully included in the retro-propagation. If the scattered waves are frequency filtered during receiving or transmitting, such as through the use of narrowband transducers, the recombination of the time-reversed waves will not exactly recover the original incident wave. This discrepancy due to incomplete time invariance can be exploited as a new method for characterizing damage by defining damage indices that quantify the departure from time reversal invariance. The sensitivity of these damage indices for various crack lengths and contact stress levels is investigated computationally, indicating some advantages of this narrowband approach relative to the more conventional measurement of higher harmonic amplitude, which requires broadband transducers.

Cross-National Invariance of Children's Temperament

ERIC Educational Resources Information Center

Benson, Nicholas; Oakland, Thomas; Shermis, Mark

2009-01-01

Measurement of temperament is an important endeavor with international appeal; however, cross-national invariance (i.e., equivalence of test scores across countries as established by empirical comparisons) of temperament tests has not been established in published research. This study examines the cross-national invariance of school-aged…

Convex Hull Aided Registration Method (CHARM).

PubMed

Fan, Jingfan; Yang, Jian; Zhao, Yitian; Ai, Danni; Liu, Yonghuai; Wang, Ge; Wang, Yongtian

2017-09-01

Non-rigid registration finds many applications such as photogrammetry, motion tracking, model retrieval, and object recognition. In this paper we propose a novel convex hull aided registration method (CHARM) to match two point sets subject to a non-rigid transformation. First, two convex hulls are extracted from the source and target respectively. Then, all points of the point sets are projected onto the reference plane through each triangular facet of the hulls. From these projections, invariant features are extracted and matched optimally. The matched feature point pairs are mapped back onto the triangular facets of the convex hulls to remove outliers that are outside any relevant triangular facet. The rigid transformation from the source to the target is robustly estimated by the random sample consensus (RANSAC) scheme through minimizing the distance between the matched feature point pairs. Finally, these feature points are utilized as the control points to achieve non-rigid deformation in the form of thin-plate spline of the entire source point set towards the target one. The experimental results based on both synthetic and real data show that the proposed algorithm outperforms several state-of-the-art ones with respect to sampling, rotational angle, and data noise. In addition, the proposed CHARM algorithm also shows higher computational efficiency compared to these methods.

Case Selection via Matching

ERIC Educational Resources Information Center

Nielsen, Richard A.

2016-01-01

This article shows how statistical matching methods can be used to select "most similar" cases for qualitative analysis. I first offer a methodological justification for research designs based on selecting most similar cases. I then discuss the applicability of existing matching methods to the task of selecting most similar cases and…

Neural Representations that Support Invariant Object Recognition

PubMed Central

Goris, Robbe L. T.; Op de Beeck, Hans P.

2008-01-01

Neural mechanisms underlying invariant behaviour such as object recognition are not well understood. For brain regions critical for object recognition, such as inferior temporal cortex (ITC), there is now ample evidence indicating that single cells code for many stimulus aspects, implying that only a moderate degree of invariance is present. However, recent theoretical and empirical work seems to suggest that integrating responses of multiple non-invariant units may produce invariant representations at population level. We provide an explicit test for the hypothesis that a linear read-out mechanism of a pool of units resembling ITC neurons may achieve invariant performance in an identification task. A linear classifier was trained to decode a particular value in a 2-D stimulus space using as input the response pattern across a population of units. Only one dimension was relevant for the task, and the stimulus location on the irrelevant dimension (ID) was kept constant during training. In a series of identification tests, the stimulus location on the relevant dimension (RD) and ID was manipulated, yielding estimates for both the level of sensitivity and tolerance reached by the network. We studied the effects of several single-cell characteristics as well as population characteristics typically considered in the literature, but found little support for the hypothesis. While the classifier averages out effects of idiosyncratic tuning properties and inter-unit variability, its invariance is very much determined by the (hypothetical) ‘average’ neuron. Consequently, even at population level there exists a fundamental trade-off between selectivity and tolerance, and invariant behaviour does not emerge spontaneously. PMID:19242556

Comparison of accuracies of an intraoral spectrophotometer and conventional visual method for shade matching using two shade guide systems

PubMed Central

Parameswaran, Vidhya; Anilkumar, S.; Lylajam, S.; Rajesh, C.; Narayan, Vivek

2016-01-01

Background and Objectives: This in vitro study compared the shade matching abilities of an intraoral spectrophotometer and the conventional visual method using two shade guides. The results of previous investigations between color perceived by human observers and color assessed by instruments have been inconclusive. The objectives were to determine accuracies and interrater agreement of both methods and effectiveness of two shade guides with either method. Methods: In the visual method, 10 examiners with normal color vision matched target control shade tabs taken from the two shade guides (VITAPAN Classical™ and VITAPAN 3D Master™) with other full sets of the respective shade guides. Each tab was matched 3 times to determine repeatability of visual examiners. The spectrophotometric shade matching was performed by two independent examiners using an intraoral spectrophotometer (VITA Easyshade™) with five repetitions for each tab. Results: Results revealed that visual method had greater accuracy than the spectrophotometer. The spectrophotometer; however, exhibited significantly better interrater agreement as compared to the visual method. While VITAPAN Classical shade guide was more accurate with the spectrophotometer, VITAPAN 3D Master shade guide proved better with visual method. Conclusion: This in vitro study clearly delineates the advantages and limitations of both methods. There were significant differences between the methods with the visual method producing more accurate results than the spectrophotometric method. The spectrophotometer showed far better interrater agreement scores irrespective of the shade guide used. Even though visual shade matching is subjective, it is not inferior and should not be underrated. Judicious combination of both techniques is imperative to attain a successful and esthetic outcome. PMID:27746599

Affine invariants of convex polygons.

PubMed

Flusser, Jan

2002-01-01

In this correspondence, we prove that the affine invariants, for image registration and object recognition, proposed recently by Yang and Cohen (see ibid., vol.8, no.7, p.934-46, July 1999) are algebraically dependent. We show how to select an independent and complete set of the invariants. The use of this new set leads to a significant reduction of the computing complexity without decreasing the discrimination power.

Synchronization invariance under network structural transformations

NASA Astrophysics Data System (ADS)

Arola-Fernández, Lluís; Díaz-Guilera, Albert; Arenas, Alex

2018-06-01

Synchronization processes are ubiquitous despite the many connectivity patterns that complex systems can show. Usually, the emergence of synchrony is a macroscopic observable; however, the microscopic details of the system, as, e.g., the underlying network of interactions, is many times partially or totally unknown. We already know that different interaction structures can give rise to a common functionality, understood as a common macroscopic observable. Building upon this fact, here we propose network transformations that keep the collective behavior of a large system of Kuramoto oscillators invariant. We derive a method based on information theory principles, that allows us to adjust the weights of the structural interactions to map random homogeneous in-degree networks into random heterogeneous networks and vice versa, keeping synchronization values invariant. The results of the proposed transformations reveal an interesting principle; heterogeneous networks can be mapped to homogeneous ones with local information, but the reverse process needs to exploit higher-order information. The formalism provides analytical insight to tackle real complex scenarios when dealing with uncertainty in the measurements of the underlying connectivity structure.

A hybrid method in combining treatment effects from matched and unmatched studies.

PubMed

Byun, Jinyoung; Lai, Dejian; Luo, Sheng; Risser, Jan; Tung, Betty; Hardy, Robert J

2013-12-10

The most common data structures in the biomedical studies have been matched or unmatched designs. Data structures resulting from a hybrid of the two may create challenges for statistical inferences. The question may arise whether to use parametric or nonparametric methods on the hybrid data structure. The Early Treatment for Retinopathy of Prematurity study was a multicenter clinical trial sponsored by the National Eye Institute. The design produced data requiring a statistical method of a hybrid nature. An infant in this multicenter randomized clinical trial had high-risk prethreshold retinopathy of prematurity that was eligible for treatment in one or both eyes at entry into the trial. During follow-up, recognition visual acuity was accessed for both eyes. Data from both eyes (matched) and from only one eye (unmatched) were eligible to be used in the trial. The new hybrid nonparametric method is a meta-analysis based on combining the Hodges-Lehmann estimates of treatment effects from the Wilcoxon signed rank and rank sum tests. To compare the new method, we used the classic meta-analysis with the t-test method to combine estimates of treatment effects from the paired and two sample t-tests. We used simulations to calculate the empirical size and power of the test statistics, as well as the bias, mean square and confidence interval width of the corresponding estimators. The proposed method provides an effective tool to evaluate data from clinical trials and similar comparative studies. Copyright © 2013 John Wiley & Sons, Ltd.

Local and gauge invariant observables in gravity

NASA Astrophysics Data System (ADS)

Khavkine, Igor

2015-09-01

It is well known that general relativity (GR) does not possess any non-trivial local (in a precise standard sense) and diffeomorphism invariant observable. We propose a generalized notion of local observables, which retain the most important properties that follow from the standard definition of locality, yet is flexible enough to admit a large class of diffeomorphism invariant observables in GR. The generalization comes at a small price—that the domain of definition of a generalized local observable may not cover the entire phase space of GR and two such observables may have distinct domains. However, the subset of metrics on which generalized local observables can be defined is in a sense generic (its open interior is non-empty in the Whitney strong topology). Moreover, generalized local gauge invariant observables are sufficient to separate diffeomorphism orbits on this admissible subset of the phase space. Connecting the construction with the notion of differential invariants gives a general scheme for defining generalized local gauge invariant observables in arbitrary gauge theories, which happens to agree with well-known results for Maxwell and Yang-Mills theories.

Coherent superposition of propagation-invariant laser beams

NASA Astrophysics Data System (ADS)

Soskind, R.; Soskind, M.; Soskind, Y. G.

2012-10-01

The coherent superposition of propagation-invariant laser beams represents an important beam-shaping technique, and results in new beam shapes which retain the unique property of propagation invariance. Propagation-invariant laser beam shapes depend on the order of the propagating beam, and include Hermite-Gaussian and Laguerre-Gaussian beams, as well as the recently introduced Ince-Gaussian beams which additionally depend on the beam ellipticity parameter. While the superposition of Hermite-Gaussian and Laguerre-Gaussian beams has been discussed in the past, the coherent superposition of Ince-Gaussian laser beams has not received significant attention in literature. In this paper, we present the formation of propagation-invariant laser beams based on the coherent superposition of Hermite-Gaussian, Laguerre-Gaussian, and Ince-Gaussian beams of different orders. We also show the resulting field distributions of the superimposed Ince-Gaussian laser beams as a function of the ellipticity parameter. By changing the beam ellipticity parameter, we compare the various shapes of the superimposed propagation-invariant laser beams transitioning from Laguerre-Gaussian beams at one ellipticity extreme to Hermite-Gaussian beams at the other extreme.

Approximating Reflectance and Transmittance of Vegetation Using Multiple Spectral Invariants

NASA Astrophysics Data System (ADS)

Mottus, M.

2011-12-01

Canopy spectral invariants, eigenvalues of the radiative transfer equation and photon recollision probability are some of the new theoretical tools that have been applied in remote sensing of vegetation and atmosphere. The theoretical approach based on spectral invariants, informally also referred to as the p-theory, owns its attractivity to several factors. Firstly, it provides a rapid and physically-based way of describing canopy scattering. Secondly, the p-theory aims at parameterizing canopy structure in reflectance models using a simple and intuitive concept which can be applied at various structural levels, from shoot to tree crown. The theory has already been applied at scales from the molecular level to forest stands. The most important shortcoming of the p-theory lies in its inability to predict the directionality of scattering. The theory is currently based on only one physical parameter, the photon recollision probability p. It is evident that one parameter cannot contain enough information to reasonably predict the observed complex reflectance patterns produced by natural vegetation canopies. Without estimating scattering directionality, however, the theory cannot be compared with even the most simple (and well-tested) two-stream vegetation reflectance models. In this study, we evaluate the possibility to use additional parameters to fit the measured reflectance and transmittance of a vegetation stand. As a first step, the parameters are applied to separate canopy scattering into reflectance and transmittance. New parameters are introduced following the general approach of eigenvector expansion. Thus, the new parameters are coined higher-order spectral invariants. Calculation of higher-order invariants is based on separating first-order scattering from total scattering. Thus, the method explicitly accounts for different view geometries with different fractions of visible sunlit canopy (e.g., hot-spot). It additionally allows to produce different

Rotationally Invariant Image Representation for Viewing Direction Classification in Cryo-EM

PubMed Central

Zhao, Zhizhen; Singer, Amit

2014-01-01

We introduce a new rotationally invariant viewing angle classification method for identifying, among a large number of cryo-EM projection images, similar views without prior knowledge of the molecule. Our rotationally invariant features are based on the bispectrum. Each image is denoised and compressed using steerable principal component analysis (PCA) such that rotating an image is equivalent to phase shifting the expansion coefficients. Thus we are able to extend the theory of bispectrum of 1D periodic signals to 2D images. The randomized PCA algorithm is then used to efficiently reduce the dimensionality of the bispectrum coefficients, enabling fast computation of the similarity between any pair of images. The nearest neighbors provide an initial classification of similar viewing angles. In this way, rotational alignment is only performed for images with their nearest neighbors. The initial nearest neighbor classification and alignment are further improved by a new classification method called vector diffusion maps. Our pipeline for viewing angle classification and alignment is experimentally shown to be faster and more accurate than reference-free alignment with rotationally invariant K-means clustering, MSA/MRA 2D classification, and their modern approximations. PMID:24631969

Measurement invariance study of the training satisfaction questionnaire (TSQ).

PubMed

Sanduvete-Chaves, Susana; Holgado-Tello, F Pablo; Chacón-Moscoso, Salvador; Barbero-García, M Isabel

2013-01-01

This article presents an empirical measurement invariance study in the substantive area of satisfaction evaluation in training programs. Specifically, it (I) provides an empirical solution to the lack of explicit measurement models of satisfaction scales, offering a way of analyzing and operationalizing the substantive theoretical dimensions; (II) outlines and discusses the analytical consequences of considering the effects of categorizing supposedly continuous variables, which are not usually taken into account; (III) presents empirical results from a measurement invariance study based on 5,272 participants' responses to a training satisfaction questionnaire in three different organizations and in two different training methods, taking into account the factor structure of the measured construct and the ordinal nature of the recorded data; and (IV) describes the substantive implications in the area of training satisfaction evaluation, such as the usefulness of the training satisfaction questionnaire to measure satisfaction in different organizations and different training methods. It also discusses further research based on these findings.

Improving the precision of the keyword-matching pornographic text filtering method using a hybrid model.

PubMed

Su, Gui-yang; Li, Jian-hua; Ma, Ying-hua; Li, Sheng-hong

2004-09-01

With the flooding of pornographic information on the Internet, how to keep people away from that offensive information is becoming one of the most important research areas in network information security. Some applications which can block or filter such information are used. Approaches in those systems can be roughly classified into two kinds: metadata based and content based. With the development of distributed technologies, content based filtering technologies will play a more and more important role in filtering systems. Keyword matching is a content based method used widely in harmful text filtering. Experiments to evaluate the recall and precision of the method showed that the precision of the method is not satisfactory, though the recall of the method is rather high. According to the results, a new pornographic text filtering model based on reconfirming is put forward. Experiments showed that the model is practical, has less loss of recall than the single keyword matching method, and has higher precision.

Scale invariance in natural and artificial collective systems: a review

PubMed Central

Huepe, Cristián

2017-01-01

Self-organized collective coordinated behaviour is an impressive phenomenon, observed in a variety of natural and artificial systems, in which coherent global structures or dynamics emerge from local interactions between individual parts. If the degree of collective integration of a system does not depend on size, its level of robustness and adaptivity is typically increased and we refer to it as scale-invariant. In this review, we first identify three main types of self-organized scale-invariant systems: scale-invariant spatial structures, scale-invariant topologies and scale-invariant dynamics. We then provide examples of scale invariance from different domains in science, describe their origins and main features and discuss potential challenges and approaches for designing and engineering artificial systems with scale-invariant properties. PMID:29093130

Perfect discretization of reparametrization invariant path integrals

NASA Astrophysics Data System (ADS)

Bahr, Benjamin; Dittrich, Bianca; Steinhaus, Sebastian

2011-05-01

To obtain a well-defined path integral one often employs discretizations. In the case of gravity and reparametrization-invariant systems, the latter of which we consider here as a toy example, discretizations generically break diffeomorphism and reparametrization symmetry, respectively. This has severe implications, as these symmetries determine the dynamics of the corresponding system. Indeed we will show that a discretized path integral with reparametrization-invariance is necessarily also discretization independent and therefore uniquely determined by the corresponding continuum quantum mechanical propagator. We use this insight to develop an iterative method for constructing such a discretized path integral, akin to a Wilsonian RG flow. This allows us to address the problem of discretization ambiguities and of an anomaly-free path integral measure for such systems. The latter is needed to obtain a path integral, that can act as a projector onto the physical states, satisfying the quantum constraints. We will comment on implications for discrete quantum gravity models, such as spin foams.

Rapid multi-modality preregistration based on SIFT descriptor.

PubMed

Chen, Jian; Tian, Jie

2006-01-01

This paper describes the scale invariant feature transform (SIFT) method for rapid preregistration of medical image. This technique originates from Lowe's method wherein preregistration is achieved by matching the corresponding keypoints between two images. The computational complexity has been reduced when we applied SIFT preregistration method before refined registration due to its O(n) exponential calculations. The features of SIFT are highly distinctive and invariant to image scaling and rotation, and partially invariant to change in illumination and contrast, it is robust and repeatable for cursorily matching two images. We also altered the descriptor so our method can deal with multimodality preregistration.

Primer on statistical interpretation or methods report card on propensity-score matching in the cardiology literature from 2004 to 2006: a systematic review.

PubMed

Austin, Peter C

2008-09-01

Propensity-score matching is frequently used in the cardiology literature. Recent systematic reviews have found that this method is, in general, poorly implemented in the medical literature. The study objective was to examine the quality of the implementation of propensity-score matching in the general cardiology literature. A total of 44 articles published in the American Heart Journal, the American Journal of Cardiology, Circulation, the European Heart Journal, Heart, the International Journal of Cardiology, and the Journal of the American College of Cardiology between January 1, 2004, and December 31, 2006, were examined. Twenty of the 44 studies did not provide adequate information on how the propensity-score-matched pairs were formed. Fourteen studies did not report whether matching on the propensity score balanced baseline characteristics between treated and untreated subjects in the matched sample. Only 4 studies explicitly used statistical methods appropriate for matched studies to compare baseline characteristics between treated and untreated subjects. Only 11 (25%) of the 44 studies explicitly used statistical methods appropriate for the analysis of matched data when estimating the effect of treatment on the outcomes. Only 2 studies described the matching method used, assessed balance in baseline covariates by appropriate methods, and used appropriate statistical methods to estimate the treatment effect and its significance. Application of propensity-score matching was poor in the cardiology literature. Suggestions for improving the reporting and analysis of studies that use propensity-score matching are provided.

A novel method for pair-matching using three-dimensional digital models of bone: mesh-to-mesh value comparison.

PubMed

Karell, Mara A; Langstaff, Helen K; Halazonetis, Demetrios J; Minghetti, Caterina; Frelat, Mélanie; Kranioti, Elena F

2016-09-01

The commingling of human remains often hinders forensic/physical anthropologists during the identification process, as there are limited methods to accurately sort these remains. This study investigates a new method for pair-matching, a common individualization technique, which uses digital three-dimensional models of bone: mesh-to-mesh value comparison (MVC). The MVC method digitally compares the entire three-dimensional geometry of two bones at once to produce a single value to indicate their similarity. Two different versions of this method, one manual and the other automated, were created and then tested for how well they accurately pair-matched humeri. Each version was assessed using sensitivity and specificity. The manual mesh-to-mesh value comparison method was 100 % sensitive and 100 % specific. The automated mesh-to-mesh value comparison method was 95 % sensitive and 60 % specific. Our results indicate that the mesh-to-mesh value comparison method overall is a powerful new tool for accurately pair-matching commingled skeletal elements, although the automated version still needs improvement.

Noise-invariant Neurons in the Avian Auditory Cortex: Hearing the Song in Noise

PubMed Central

Moore, R. Channing; Lee, Tyler; Theunissen, Frédéric E.

2013-01-01

Given the extraordinary ability of humans and animals to recognize communication signals over a background of noise, describing noise invariant neural responses is critical not only to pinpoint the brain regions that are mediating our robust perceptions but also to understand the neural computations that are performing these tasks and the underlying circuitry. Although invariant neural responses, such as rotation-invariant face cells, are well described in the visual system, high-level auditory neurons that can represent the same behaviorally relevant signal in a range of listening conditions have yet to be discovered. Here we found neurons in a secondary area of the avian auditory cortex that exhibit noise-invariant responses in the sense that they responded with similar spike patterns to song stimuli presented in silence and over a background of naturalistic noise. By characterizing the neurons' tuning in terms of their responses to modulations in the temporal and spectral envelope of the sound, we then show that noise invariance is partly achieved by selectively responding to long sounds with sharp spectral structure. Finally, to demonstrate that such computations could explain noise invariance, we designed a biologically inspired noise-filtering algorithm that can be used to separate song or speech from noise. This novel noise-filtering method performs as well as other state-of-the-art de-noising algorithms and could be used in clinical or consumer oriented applications. Our biologically inspired model also shows how high-level noise-invariant responses could be created from neural responses typically found in primary auditory cortex. PMID:23505354

Noise-invariant neurons in the avian auditory cortex: hearing the song in noise.

PubMed

Moore, R Channing; Lee, Tyler; Theunissen, Frédéric E

2013-01-01

Given the extraordinary ability of humans and animals to recognize communication signals over a background of noise, describing noise invariant neural responses is critical not only to pinpoint the brain regions that are mediating our robust perceptions but also to understand the neural computations that are performing these tasks and the underlying circuitry. Although invariant neural responses, such as rotation-invariant face cells, are well described in the visual system, high-level auditory neurons that can represent the same behaviorally relevant signal in a range of listening conditions have yet to be discovered. Here we found neurons in a secondary area of the avian auditory cortex that exhibit noise-invariant responses in the sense that they responded with similar spike patterns to song stimuli presented in silence and over a background of naturalistic noise. By characterizing the neurons' tuning in terms of their responses to modulations in the temporal and spectral envelope of the sound, we then show that noise invariance is partly achieved by selectively responding to long sounds with sharp spectral structure. Finally, to demonstrate that such computations could explain noise invariance, we designed a biologically inspired noise-filtering algorithm that can be used to separate song or speech from noise. This novel noise-filtering method performs as well as other state-of-the-art de-noising algorithms and could be used in clinical or consumer oriented applications. Our biologically inspired model also shows how high-level noise-invariant responses could be created from neural responses typically found in primary auditory cortex.

Efficient Implementation of the Invariant Imbedding T-Matrix Method and the Separation of Variables Method Applied to Large Nonspherical Inhomogeneous Particles

NASA Technical Reports Server (NTRS)

Bi, Lei; Yang, Ping; Kattawar, George W.; Mishchenko, Michael I.

2012-01-01

Three terms, ''Waterman's T-matrix method'', ''extended boundary condition method (EBCM)'', and ''null field method'', have been interchangeable in the literature to indicate a method based on surface integral equations to calculate the T-matrix. Unlike the previous method, the invariant imbedding method (IIM) calculates the T-matrix by the use of a volume integral equation. In addition, the standard separation of variables method (SOV) can be applied to compute the T-matrix of a sphere centered at the origin of the coordinate system and having a maximal radius such that the sphere remains inscribed within a nonspherical particle. This study explores the feasibility of a numerical combination of the IIM and the SOV, hereafter referred to as the IIMþSOV method, for computing the single-scattering properties of nonspherical dielectric particles, which are, in general, inhomogeneous. The IIMþSOV method is shown to be capable of solving light-scattering problems for large nonspherical particles where the standard EBCM fails to converge. The IIMþSOV method is flexible and applicable to inhomogeneous particles and aggregated nonspherical particles (overlapped circumscribed spheres) representing a challenge to the standard superposition T-matrix method. The IIMþSOV computational program, developed in this study, is validated against EBCM simulated spheroid and cylinder cases with excellent numerical agreement (up to four decimal places). In addition, solutions for cylinders with large aspect ratios, inhomogeneous particles, and two-particle systems are compared with results from discrete dipole approximation (DDA) computations, and comparisons with the improved geometric-optics method (IGOM) are found to be quite encouraging.

Cotton-type and joint invariants for linear elliptic systems.

PubMed

Aslam, A; Mahomed, F M

2013-01-01

Cotton-type invariants for a subclass of a system of two linear elliptic equations, obtainable from a complex base linear elliptic equation, are derived both by spliting of the corresponding complex Cotton invariants of the base complex equation and from the Laplace-type invariants of the system of linear hyperbolic equations equivalent to the system of linear elliptic equations via linear complex transformations of the independent variables. It is shown that Cotton-type invariants derived from these two approaches are identical. Furthermore, Cotton-type and joint invariants for a general system of two linear elliptic equations are also obtained from the Laplace-type and joint invariants for a system of two linear hyperbolic equations equivalent to the system of linear elliptic equations by complex changes of the independent variables. Examples are presented to illustrate the results.

Cotton-Type and Joint Invariants for Linear Elliptic Systems

PubMed Central

Aslam, A.; Mahomed, F. M.

2013-01-01

Cotton-type invariants for a subclass of a system of two linear elliptic equations, obtainable from a complex base linear elliptic equation, are derived both by spliting of the corresponding complex Cotton invariants of the base complex equation and from the Laplace-type invariants of the system of linear hyperbolic equations equivalent to the system of linear elliptic equations via linear complex transformations of the independent variables. It is shown that Cotton-type invariants derived from these two approaches are identical. Furthermore, Cotton-type and joint invariants for a general system of two linear elliptic equations are also obtained from the Laplace-type and joint invariants for a system of two linear hyperbolic equations equivalent to the system of linear elliptic equations by complex changes of the independent variables. Examples are presented to illustrate the results. PMID:24453871

Holographic fluorescence mapping using space-division matching method

NASA Astrophysics Data System (ADS)

Abe, Ryosuke; Hayasaki, Yoshio

2017-10-01

Three-dimensional mapping of fluorescence light sources was performed by using self-interference digital holography. The positions of the sources were quantitatively determined by using Gaussian fitting of the axial and lateral intensity distributions obtained from diffraction calculations through position calibration from the observation space to the sample space. A space-division matching method was developed to perform the mapping of many fluorescence light sources, in this experiment, 500 nm fluorescent nanoparticles fixed in gelatin. A fluorescence digital holographic microscope having a 60 × objective lens with a numerical aperture of 1.25 detected 13 fluorescence light sources in a measurable region with a radius of ∼ 20 μm and a height of ∼ 5 μm. It was found that the measurable region had a conical shape resulting from the overlap between two beams.

Learning to Be (In)Variant: Combining Prior Knowledge and Experience to Infer Orientation Invariance in Object Recognition

ERIC Educational Resources Information Center

Austerweil, Joseph L.; Griffiths, Thomas L.; Palmer, Stephen E.

2017-01-01

How does the visual system recognize images of a novel object after a single observation despite possible variations in the viewpoint of that object relative to the observer? One possibility is comparing the image with a prototype for invariance over a relevant transformation set (e.g., translations and dilations). However, invariance over…

Feature extraction and descriptor calculation methods for automatic georeferencing of Philippines' first microsatellite imagery

NASA Astrophysics Data System (ADS)

Tupas, M. E. A.; Dasallas, J. A.; Jiao, B. J. D.; Magallon, B. J. P.; Sempio, J. N. H.; Ramos, M. K. F.; Aranas, R. K. D.; Tamondong, A. M.

2017-10-01

The FAST-SIFT corner detector and descriptor extractor combination was used to automatically georeference DIWATA-1 Spaceborne Multispectral Imager images. Features from the Fast Accelerated Segment Test (FAST) algorithm detects corners or keypoints in an image, and these robustly detected keypoints have well-defined positions. Descriptors were computed using Scale-Invariant Feature Transform (SIFT) extractor. FAST-SIFT method effectively SMI same-subscene images detected by the NIR sensor. The method was also tested in stitching NIR images with varying subscene swept by the camera. The slave images were matched to the master image. The keypoints served as the ground control points. Random sample consensus was used to eliminate fall-out matches and ensure accuracy of the feature points from which the transformation parameters were derived. Keypoints are matched based on their descriptor vector. Nearest-neighbor matching is employed based on a metric distance between the descriptors. The metrics include Euclidean and city block, among others. Rough matching outputs not only the correct matches but also the faulty matches. A previous work in automatic georeferencing incorporates a geometric restriction. In this work, we applied a simplified version of the learning method. RANSAC was used to eliminate fall-out matches and ensure accuracy of the feature points. This method identifies if a point fits the transformation function and returns inlier matches. The transformation matrix was solved by Affine, Projective, and Polynomial models. The accuracy of the automatic georeferencing method were determined by calculating the RMSE of interest points, selected randomly, between the master image and transformed slave image.

A Numerical Combination of Extended Boundary Condition Method and Invariant Imbedding Method Applied to Light Scattering by Large Spheroids and Cylinders

NASA Technical Reports Server (NTRS)

Bi, Lei; Yang, Ping; Kattawar, George W.; Mishchenko, Michael I.

2013-01-01

The extended boundary condition method (EBCM) and invariant imbedding method (IIM) are two fundamentally different T-matrix methods for the solution of light scattering by nonspherical particles. The standard EBCM is very efficient but encounters a loss of precision when the particle size is large, the maximum size being sensitive to the particle aspect ratio. The IIM can be applied to particles in a relatively large size parameter range but requires extensive computational time due to the number of spherical layers in the particle volume discretization. A numerical combination of the EBCM and the IIM (hereafter, the EBCM+IIM) is proposed to overcome the aforementioned disadvantages of each method. Even though the EBCM can fail to obtain the T-matrix of a considered particle, it is valuable for decreasing the computational domain (i.e., the number of spherical layers) of the IIM by providing the initial T-matrix associated with an iterative procedure in the IIM. The EBCM+IIM is demonstrated to be more efficient than the IIM in obtaining the optical properties of large size parameter particles beyond the convergence limit of the EBCM. The numerical performance of the EBCM+IIM is illustrated through representative calculations in spheroidal and cylindrical particle cases.

Gauge invariant spectral Cauchy characteristic extraction

NASA Astrophysics Data System (ADS)

Handmer, Casey J.; Szilágyi, Béla; Winicour, Jeffrey

2015-12-01

We present gauge invariant spectral Cauchy characteristic extraction. We compare gravitational waveforms extracted from a head-on black hole merger simulated in two different gauges by two different codes. We show rapid convergence, demonstrating both gauge invariance of the extraction algorithm and consistency between the legacy Pitt null code and the much faster spectral Einstein code (SpEC).

Locally optimal transfer trajectories between libration point orbits using invariant manifolds

NASA Astrophysics Data System (ADS)

Davis, Kathryn E.

2009-12-01

Techniques from dynamical systems theory and primer vector theory have been applied to the construction of locally optimal transfer trajectories between libration point orbits. When two libration point orbits have different energies, it has been found that the unstable manifold of the first orbit can be connected to the stable manifold of the second orbit with a bridging trajectory. A bounding sphere centered on the secondary, with a radius less than the radius of the sphere of influence of the secondary, was used to study the stable and unstable manifold trajectories. It was numerically demonstrated that within the bounding sphere, the two-body parameters of the unstable and stable manifold trajectories could be analyzed to locate low transfer costs. It was shown that as the two-body parameters of an unstable manifold trajectory more closely matched the two-body parameters of a stable manifold trajectory, the total DeltaV necessary to complete the transfer decreased. Primer vector theory was successfully applied to a transfer to determine the optimal maneuvers required to create the bridging trajectory that connected the unstable manifold of the first orbit to the stable manifold of the second orbit. Transfer trajectories were constructed between halo orbits in the Sun-Earth and Earth-Moon three-body systems. Multiple solutions were found between the same initial and final orbits, where certain solutions retraced interior portions of the trajectory. All of the trajectories created satisfied the conditions for optimality. The costs of transfers constructed using invariant manifolds were compared to the costs of transfers constructed without the use of invariant manifolds, when data was available. In all cases, the total cost of the transfers were significantly lower when invariant manifolds were used in the transfer construction. In many cases, the transfers that employed invariant manifolds were three to four times more efficient, in terms of fuel expenditure

Face identity matching is selectively impaired in developmental prosopagnosia.

PubMed

Fisher, Katie; Towler, John; Eimer, Martin

2017-04-01

Individuals with developmental prosopagnosia (DP) have severe face recognition deficits, but the mechanisms that are responsible for these deficits have not yet been fully identified. We assessed whether the activation of visual working memory for individual faces is selectively impaired in DP. Twelve DPs and twelve age-matched control participants were tested in a task where they reported whether successively presented faces showed the same or two different individuals, and another task where they judged whether the faces showed the same or different facial expressions. Repetitions versus changes of the other currently irrelevant attribute were varied independently. DPs showed impaired performance in the identity task, but performed at the same level as controls in the expression task. An electrophysiological marker for the activation of visual face memory by identity matches (N250r component) was strongly attenuated in the DP group, and the size of this attenuation was correlated with poor performance in a standardized face recognition test. Results demonstrate an identity-specific deficit of visual face memory in DPs. Their reduced sensitivity to identity matches in the presence of other image changes could result from earlier deficits in the perceptual extraction of image-invariant visual identity cues from face images. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Procrustes Matching by Congruence Coefficients

ERIC Educational Resources Information Center

Korth, Bruce; Tucker, L. R.

1976-01-01

Matching by Procrustes methods involves the transformation of one matrix to match with another. A special least squares criterion, the congruence coefficient, has advantages as a criterion for some factor analytic interpretations. A Procrustes method maximizing the congruence coefficient is given. (Author/JKS)

Other Historical and Philosophical Perspectives on Invariance in Measurement

ERIC Educational Resources Information Center

Fisher, William P., Jr.

2008-01-01

Engelhard draws out the similarities and differences in Guttman's, Rasch's, and Mokken's perspectives on invariance in measurement. He provides a valuable model in evaluating the extent to which different measurement theories and methods serve as a basis for achieving the fundamental goals of quantification. The full extent of this point will…

Parallel algorithm for determining motion vectors in ice floe images by matching edge features

NASA Technical Reports Server (NTRS)

Manohar, M.; Ramapriyan, H. K.; Strong, J. P.

1988-01-01

A parallel algorithm is described to determine motion vectors of ice floes using time sequences of images of the Arctic ocean obtained from the Synthetic Aperture Radar (SAR) instrument flown on-board the SEASAT spacecraft. Researchers describe a parallel algorithm which is implemented on the MPP for locating corresponding objects based on their translationally and rotationally invariant features. The algorithm first approximates the edges in the images by polygons or sets of connected straight-line segments. Each such edge structure is then reduced to a seed point. Associated with each seed point are the descriptions (lengths, orientations and sequence numbers) of the lines constituting the corresponding edge structure. A parallel matching algorithm is used to match packed arrays of such descriptions to identify corresponding seed points in the two images. The matching algorithm is designed such that fragmentation and merging of ice floes are taken into account by accepting partial matches. The technique has been demonstrated to work on synthetic test patterns and real image pairs from SEASAT in times ranging from .5 to 0.7 seconds for 128 x 128 images.

[Using neural networks based template matching method to obtain redshifts of normal galaxies].

PubMed

Xu, Xin; Luo, A-li; Wu, Fu-chao; Zhao, Yong-heng

2005-06-01

Galaxies can be divided into two classes: normal galaxy (NG) and active galaxy (AG). In order to determine NG redshifts, an automatic effective method is proposed in this paper, which consists of the following three main steps: (1) From the template of normal galaxy, the two sets of samples are simulated, one with the redshift of 0.0-0.3, the other of 0.3-0.5, then the PCA is used to extract the main components, and train samples are projected to the main component subspace to obtain characteristic spectra. (2) The characteristic spectra are used to train a Probabilistic Neural Network to obtain a Bayes classifier. (3) An unknown real NG spectrum is first inputted to this Bayes classifier to determine the possible range of redshift, then the template matching is invoked to locate the redshift value within the estimated range. Compared with the traditional template matching technique with an unconstrained range, our proposed method not only halves the computational load, but also increases the estimation accuracy. As a result, the proposed method is particularly useful for automatic spectrum processing produced from a large-scale sky survey project.

A Balanced Comparison of Object Invariances in Monkey IT Neurons.

PubMed

Ratan Murty, N Apurva; Arun, Sripati P

2017-01-01

Our ability to recognize objects across variations in size, position, or rotation is based on invariant object representations in higher visual cortex. However, we know little about how these invariances are related. Are some invariances harder than others? Do some invariances arise faster than others? These comparisons can be made only upon equating image changes across transformations. Here, we targeted invariant neural representations in the monkey inferotemporal (IT) cortex using object images with balanced changes in size, position, and rotation. Across the recorded population, IT neurons generalized across size and position both stronger and faster than to rotations in the image plane as well as in depth. We obtained a similar ordering of invariances in deep neural networks but not in low-level visual representations. Thus, invariant neural representations dynamically evolve in a temporal order reflective of their underlying computational complexity.

Invariant solutions to the conformal Killing-Yano equation on Lie groups

NASA Astrophysics Data System (ADS)

Andrada, A.; Barberis, M. L.; Dotti, I. G.

2015-08-01

We search for invariant solutions of the conformal Killing-Yano equation on Lie groups equipped with left invariant Riemannian metrics, focusing on 2-forms. We show that when the Lie group is compact equipped with a bi-invariant metric or 2-step nilpotent, the only invariant solutions occur on the 3-dimensional sphere or on a Heisenberg group. We classify the 3-dimensional Lie groups with left invariant metrics carrying invariant conformal Killing-Yano 2-forms.

Wall-crossing invariants: from quantum mechanics to knots

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

Galakhov, D., E-mail: galakhov@itep.ru, E-mail: galakhov@physics.rutgers.edu; Mironov, A., E-mail: mironov@lpi.ru; Morozov, A., E-mail: morozov@itep.ru

2015-03-15

We offer a pedestrian-level review of the wall-crossing invariants. The story begins from the scattering theory in quantum mechanics where the spectrum reshuffling can be related to permutations of S-matrices. In nontrivial situations, starting from spin chains and matrix models, the S-matrices are operatorvalued and their algebra is described in terms of R- and mixing (Racah) U-matrices. Then the Kontsevich-Soibelman (KS) invariants are nothing but the standard knot invariants made out of these data within the Reshetikhin-Turaev-Witten approach. The R and Racah matrices acquire a relatively universal form in the semiclassical limit, where the basic reshufflings with the change ofmore » moduli are those of the Stokes line. Natural from this standpoint are matrices provided by the modular transformations of conformal blocks (with the usual identification R = T and U = S), and in the simplest case of the first degenerate field (2, 1), when the conformal blocks satisfy a second-order Shrödinger-like equation, the invariants coincide with the Jones (N = 2) invariants of the associated knots. Another possibility to construct knot invariants is to realize the cluster coordinates associated with reshufflings of the Stokes lines immediately in terms of check-operators acting on solutions of the Knizhnik-Zamolodchikov equations. Then the R-matrices are realized as products of successive mutations in the cluster algebra and are manifestly described in terms of quantum dilogarithms, ultimately leading to the Hikami construction of knot invariants.« less

Systems, methods and apparatus for pattern matching in procedure development and verification

NASA Technical Reports Server (NTRS)

Hinchey, Michael G. (Inventor); Rouff, Christopher A. (Inventor); Rash, James L. (Inventor)

2011-01-01

Systems, methods and apparatus are provided through which, in some embodiments, a formal specification is pattern-matched from scenarios, the formal specification is analyzed, and flaws in the formal specification are corrected. The systems, methods and apparatus may include pattern-matching an equivalent formal model from an informal specification. Such a model can be analyzed for contradictions, conflicts, use of resources before the resources are available, competition for resources, and so forth. From such a formal model, an implementation can be automatically generated in a variety of notations. The approach can improve the resulting implementation, which, in some embodiments, is provably equivalent to the procedures described at the outset, which in turn can improve confidence that the system reflects the requirements, and in turn reduces system development time and reduces the amount of testing required of a new system. Moreover, in some embodiments, two or more implementations can be "reversed" to appropriate formal models, the models can be combined, and the resulting combination checked for conflicts. Then, the combined, error-free model can be used to generate a new (single) implementation that combines the functionality of the original separate implementations, and may be more likely to be correct.

Invariants of the Axisymmetric Plasma Flows

NASA Astrophysics Data System (ADS)

Bogoyavlenskij, Oleg

2018-06-01

Infinite families of new functionally independent invariants are derived for the axisymmetric dynamics of viscous plasmas with zero electrical resistance. As a consequence, we find that, if two axisymmetric plasma states are dynamically connected, then their total number of magnetic rings must be equal (the same as for the total numbers of magnetic blobs) and the corresponding infinitely many new invariants must coincide.

Scale-invariant fluctuations from Galilean genesis

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

Wang, Yi; Brandenberger, Robert, E-mail: wangyi@physics.mcgill.ca, E-mail: rhb@physics.mcgill.ca

2012-10-01

We study the spectrum of cosmological fluctuations in scenarios such as Galilean Genesis \\cite(Nicolis) in which a spectator scalar field acquires a scale-invariant spectrum of perturbations during an early phase which asymptotes in the far past to Minkowski space-time. In the case of minimal coupling to gravity and standard scalar field Lagrangian, the induced curvature fluctuations depend quadratically on the spectator field and are hence non-scale-invariant and highly non-Gaussian. We show that if higher dimensional operators (the same operators that lead to the η-problem for inflation) are considered, a linear coupling between background and spectator field fluctuations is induced whichmore » leads to scale-invariant and Gaussian curvature fluctuations.« less

Evaluation of Scaling Invariance Embedded in Short Time Series

PubMed Central

Pan, Xue; Hou, Lei; Stephen, Mutua; Yang, Huijie; Zhu, Chenping

2014-01-01

Scaling invariance of time series has been making great contributions in diverse research fields. But how to evaluate scaling exponent from a real-world series is still an open problem. Finite length of time series may induce unacceptable fluctuation and bias to statistical quantities and consequent invalidation of currently used standard methods. In this paper a new concept called correlation-dependent balanced estimation of diffusion entropy is developed to evaluate scale-invariance in very short time series with length . Calculations with specified Hurst exponent values of show that by using the standard central moving average de-trending procedure this method can evaluate the scaling exponents for short time series with ignorable bias () and sharp confidential interval (standard deviation ). Considering the stride series from ten volunteers along an approximate oval path of a specified length, we observe that though the averages and deviations of scaling exponents are close, their evolutionary behaviors display rich patterns. It has potential use in analyzing physiological signals, detecting early warning signals, and so on. As an emphasis, the our core contribution is that by means of the proposed method one can estimate precisely shannon entropy from limited records. PMID:25549356

A temperature match based optimization method for daily load prediction considering DLC effect

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

Yu, Z.

This paper presents a unique optimization method for short term load forecasting. The new method is based on the optimal template temperature match between the future and past temperatures. The optimal error reduction technique is a new concept introduced in this paper. Two case studies show that for hourly load forecasting, this method can yield results as good as the rather complicated Box-Jenkins Transfer Function method, and better than the Box-Jenkins method; for peak load prediction, this method is comparable in accuracy to the neural network method with back propagation, and can produce more accurate results than the multi-linear regressionmore » method. The DLC effect on system load is also considered in this method.« less

A Balanced Comparison of Object Invariances in Monkey IT Neurons

PubMed Central

2017-01-01

Abstract Our ability to recognize objects across variations in size, position, or rotation is based on invariant object representations in higher visual cortex. However, we know little about how these invariances are related. Are some invariances harder than others? Do some invariances arise faster than others? These comparisons can be made only upon equating image changes across transformations. Here, we targeted invariant neural representations in the monkey inferotemporal (IT) cortex using object images with balanced changes in size, position, and rotation. Across the recorded population, IT neurons generalized across size and position both stronger and faster than to rotations in the image plane as well as in depth. We obtained a similar ordering of invariances in deep neural networks but not in low-level visual representations. Thus, invariant neural representations dynamically evolve in a temporal order reflective of their underlying computational complexity. PMID:28413827

Gauge invariance for a whole Abelian model

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

Chauca, J.; Doria, R.; Soares, W.

Light invariance is a fundamental principle for physics be done. It generates Maxwell equations, relativity, Lorentz group. However there is still space for a fourth picture be developed which is to include fields with same Lorentz nature. It brings a new room for field theory. It says that light invariance does not work just to connect space and time but it also associates different fields with same nature. Thus for the ((1/2),(1/2)) representation there is a fields family {l_brace}A{sub {mu}I}{r_brace} to be studied. This means that given such fields association one should derive its corresponding gauge theory. This is themore » effort at this work. Show that there is a whole gauge theory to cover these fields relationships. Considering the abelian case, prove its gauge invariance. It yields the kinetic, massive, trilinear and quadrilinear gauge invariant terms.« less

Testing Measurement Invariance in the Target Rotated Multigroup Exploratory Factor Model

ERIC Educational Resources Information Center

Dolan, Conor V.; Oort, Frans J.; Stoel, Reinoud D.; Wicherts, Jelte M.

2009-01-01

We propose a method to investigate measurement invariance in the multigroup exploratory factor model, subject to target rotation. We consider both oblique and orthogonal target rotation. This method has clear advantages over other approaches, such as the use of congruence measures. We demonstrate that the model can be implemented readily in the…

Lorentz Invariance:. Present Experimental Status

NASA Astrophysics Data System (ADS)

Lämmerzahl, Claus

2006-02-01

Being one of the pillars of modern physics, Lorentz invariance has to be tested as precisely as possible. We review the present status of laboratory tests of Lorentz invariance. This includes the tests of properties of light propagation which are covered by the famous Michelson-Morley, Kennedy-Thorndike, and Ives-Stilwell experiments, as well as tests on dynamical properties of matter as, e.g., tests exploring the maximum velocity of massive particles or tests of the isotropy of quantum particles in Hughes-Drever experiments.

Inertial Spontaneous Symmetry Breaking and Quantum Scale Invariance

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

Ferreira, Pedro G.; Hill, Christopher T.; Ross, Graham G.

Weyl invariant theories of scalars and gravity can generate all mass scales spontaneously, initiated by a dynamical process of "inertial spontaneous symmetry breaking" that does not involve a potential. This is dictated by the structure of the Weyl current,more » $$K_\\mu$$, and a cosmological phase during which the universe expands and the Einstein-Hilbert effective action is formed. Maintaining exact Weyl invariance in the renormalised quantum theory is straightforward when renormalisation conditions are referred back to the VEV's of fields in the action of the theory, which implies a conserved Weyl current. We do not require scale invariant regulators. We illustrate the computation of a Weyl invariant Coleman-Weinberg potential.« less

Registration of 3D spectral OCT volumes using 3D SIFT feature point matching

NASA Astrophysics Data System (ADS)

Niemeijer, Meindert; Garvin, Mona K.; Lee, Kyungmoo; van Ginneken, Bram; Abràmoff, Michael D.; Sonka, Milan

2009-02-01

The recent introduction of next generation spectral OCT scanners has enabled routine acquisition of high resolution, 3D cross-sectional volumetric images of the retina. 3D OCT is used in the detection and management of serious eye diseases such as glaucoma and age-related macular degeneration. For follow-up studies, image registration is a vital tool to enable more precise, quantitative comparison of disease states. This work presents a registration method based on a recently introduced extension of the 2D Scale-Invariant Feature Transform (SIFT) framework1 to 3D.2 The SIFT feature extractor locates minima and maxima in the difference of Gaussian scale space to find salient feature points. It then uses histograms of the local gradient directions around each found extremum in 3D to characterize them in a 4096 element feature vector. Matching points are found by comparing the distance between feature vectors. We apply this method to the rigid registration of optic nerve head- (ONH) and macula-centered 3D OCT scans of the same patient that have only limited overlap. Three OCT data set pairs with known deformation were used for quantitative assessment of the method's robustness and accuracy when deformations of rotation and scaling were considered. Three-dimensional registration accuracy of 2.0+/-3.3 voxels was observed. The accuracy was assessed as average voxel distance error in N=1572 matched locations. The registration method was applied to 12 3D OCT scans (200 x 200 x 1024 voxels) of 6 normal eyes imaged in vivo to demonstrate the clinical utility and robustness of the method in a real-world environment.

An Absorbing Boundary Condition for the Lattice Boltzmann Method Based on the Perfectly Matched Layer

PubMed Central

Najafi-Yazdi, A.; Mongeau, L.

2012-01-01

The Lattice Boltzmann Method (LBM) is a well established computational tool for fluid flow simulations. This method has been recently utilized for low Mach number computational aeroacoustics. Robust and nonreflective boundary conditions, similar to those used in Navier-Stokes solvers, are needed for LBM-based aeroacoustics simulations. The goal of the present study was to develop an absorbing boundary condition based on the perfectly matched layer (PML) concept for LBM. The derivation of formulations for both two and three dimensional problems are presented. The macroscopic behavior of the new formulation is discussed. The new formulation was tested using benchmark acoustic problems. The perfectly matched layer concept appears to be very well suited for LBM, and yielded very low acoustic reflection factor. PMID:23526050

Orthogonal bases of invariants in tensor models

NASA Astrophysics Data System (ADS)

Diaz, Pablo; Rey, Soo-Jong

2018-02-01

Representation theory provides an efficient framework to count and classify invariants in tensor models of (gauge) symmetry G d = U( N 1) ⊗ · · · ⊗ U( N d ) . We show that there are two natural ways of counting invariants, one for arbitrary G d and another valid for large rank of G d . We construct basis of invariant operators based on the counting, and compute correlators of their elements. The basis associated with finite rank of G d diagonalizes two-point function. It is analogous to the restricted Schur basis used in matrix models. We comment on future directions for investigation.

Near-affine-invariant texture learning for lung tissue analysis using isotropic wavelet frames.

PubMed

Depeursinge, Adrien; Van de Ville, Dimitri; Platon, Alexandra; Geissbuhler, Antoine; Poletti, Pierre-Alexandre; Müller, Henning

2012-07-01

We propose near-affine-invariant texture descriptors derived from isotropic wavelet frames for the characterization of lung tissue patterns in high-resolution computed tomography (HRCT) imaging. Affine invariance is desirable to enable learning of nondeterministic textures without a priori localizations, orientations, or sizes. When combined with complementary gray-level histograms, the proposed method allows a global classification accuracy of 76.9% with balanced precision among five classes of lung tissue using a leave-one-patient-out cross validation, in accordance with clinical practice.

Hurst Estimation of Scale Invariant Processes with Stationary Increments and Piecewise Linear Drift

NASA Astrophysics Data System (ADS)

Modarresi, N.; Rezakhah, S.

The characteristic feature of the discrete scale invariant (DSI) processes is the invariance of their finite dimensional distributions by dilation for certain scaling factor. DSI process with piecewise linear drift and stationary increments inside prescribed scale intervals is introduced and studied. To identify the structure of the process, first, we determine the scale intervals, their linear drifts and eliminate them. Then, a new method for the estimation of the Hurst parameter of such DSI processes is presented and applied to some period of the Dow Jones indices. This method is based on fixed number equally spaced samples inside successive scale intervals. We also present some efficient method for estimating Hurst parameter of self-similar processes with stationary increments. We compare the performance of this method with the celebrated FA, DFA and DMA on the simulated data of fractional Brownian motion (fBm).

Characterizing Responses of Translation Invariant Neurons to Natural Stimuli: Maximally Informative Invariant Dimensions

PubMed Central

Eickenberg, Michael; Rowekamp, Ryan J.; Kouh, Minjoon; Sharpee, Tatyana O.

2012-01-01

Our visual system is capable of recognizing complex objects even when their appearances change drastically under various viewing conditions. Especially in the higher cortical areas, the sensory neurons reflect such functional capacity in their selectivity for complex visual features and invariance to certain object transformations, such as image translation. Due to the strong nonlinearities necessary to achieve both the selectivity and invariance, characterizing and predicting the response patterns of these neurons represents a formidable computational challenge. A related problem is that such neurons are poorly driven by randomized inputs, such as white noise, and respond strongly only to stimuli with complex high-order correlations, such as natural stimuli. Here we describe a novel two-step optimization technique that can characterize both the shape selectivity and the range and coarseness of position invariance from neural responses to natural stimuli. One step in the optimization involves finding the template as the maximally informative dimension given the estimated spatial location where the response could have been triggered within each image. The estimates of the locations that triggered the response are subsequently updated in the next step. Under the assumption of a monotonic relationship between the firing rate and stimulus projections on the template at a given position, the most likely location is the one that has the largest projection on the estimate of the template. The algorithm shows quick convergence during optimization, and the estimation results are reliable even in the regime of small signal-to-noise ratios. When we apply the algorithm to responses of complex cells in the primary visual cortex (V1) to natural movies, we find that responses of the majority of cells were significantly better described by translation invariant models based on one template compared with position-specific models with several relevant features. PMID:22734487

Quantitative characterization and comparison of precipitate and grain shape in Nickel -base superalloys using moment invariants

NASA Astrophysics Data System (ADS)

Callahan, Patrick Gregory

A fundamental objective of materials science and engineering is to understand the structure-property-processing-performance relationship. We need to know the true 3-D microstructure of a material to understand certain geometric properties of a material, and thus fulfill this objective. Focused ion beam (FIB) serial sectioning allows us to find the true 3-D microstructure of Ni-base superalloys. Once the true 3-D microstructure is obtained, an accurate quantitative description and characterization of precipitate and/or grain shapes is needed to understand the microstructure and describe it in an unbiased way. In this thesis, second order moment invariants, the shape quotient Q, a convexity measure relating the volume of an object to the volume of its convex hull, V/Vconv, and Gaussian curvature have been used to compare an experimentally observed polycrystalline IN100 microstructure to three synthetic microstructures. The three synthetic microstructures used different shape classes to produce starting grain shapes. The three shape classes are ellipsoids, superellipsoids, and the shapes generated when truncating a cube with an octahedron. The microstructures are compared using a distance measure, the Hellinger distance. The Hellinger distance is used to compare distributions of shape descriptors for the grains in each microstructure. The synthetic microstructure that has the smallest Hellinger distance, and so best matched the experimentally observed microstructure is the microstructure that used superellipsoids as a starting grain shape. While it has the smallest Hellinger distance, and is approaching realistic grain morphologies, the superellipsoidal microstructure is still not realistic. Second order moment invariants, Q, and V/V conv have also been used to characterize the γ' precipitate shapes from four experimental Ru-containing Ni-base superalloys with differences in alloying additions. The superalloys are designated UM-F9, UM-F18, UM-F19, and UM-F22. The

Modified dispersion relations, inflation, and scale invariance

NASA Astrophysics Data System (ADS)

Bianco, Stefano; Friedhoff, Victor Nicolai; Wilson-Ewing, Edward

2018-02-01

For a certain type of modified dispersion relations, the vacuum quantum state for very short wavelength cosmological perturbations is scale-invariant and it has been suggested that this may be the source of the scale-invariance observed in the temperature anisotropies in the cosmic microwave background. We point out that for this scenario to be possible, it is necessary to redshift these short wavelength modes to cosmological scales in such a way that the scale-invariance is not lost. This requires nontrivial background dynamics before the onset of standard radiation-dominated cosmology; we demonstrate that one possible solution is inflation with a sufficiently large Hubble rate, for this slow roll is not necessary. In addition, we also show that if the slow-roll condition is added to inflation with a large Hubble rate, then for any power law modified dispersion relation quantum vacuum fluctuations become nearly scale-invariant when they exit the Hubble radius.

Accurate single-scattering simulation of ice cloud using the invariant-imbedding T-matrix method and the physical-geometric optics method

NASA Astrophysics Data System (ADS)

Sun, B.; Yang, P.; Kattawar, G. W.; Zhang, X.

2017-12-01

The ice cloud single-scattering properties can be accurately simulated using the invariant-imbedding T-matrix method (IITM) and the physical-geometric optics method (PGOM). The IITM has been parallelized using the Message Passing Interface (MPI) method to remove the memory limitation so that the IITM can be used to obtain the single-scattering properties of ice clouds for sizes in the geometric optics regime. Furthermore, the results associated with random orientations can be analytically achieved once the T-matrix is given. The PGOM is also parallelized in conjunction with random orientations. The single-scattering properties of a hexagonal prism with height 400 (in units of lambda/2*pi, where lambda is the incident wavelength) and an aspect ratio of 1 (defined as the height over two times of bottom side length) are given by using the parallelized IITM and compared to the counterparts using the parallelized PGOM. The two results are in close agreement. Furthermore, the integrated single-scattering properties, including the asymmetry factor, the extinction cross-section, and the scattering cross-section, are given in a completed size range. The present results show a smooth transition from the exact IITM solution to the approximate PGOM result. Because the calculation of the IITM method has reached the geometric regime, the IITM and the PGOM can be efficiently employed to accurately compute the single-scattering properties of ice cloud in a wide spectral range.

Improved medical image fusion based on cascaded PCA and shift invariant wavelet transforms.

PubMed

Reena Benjamin, J; Jayasree, T

2018-02-01

In the medical field, radiologists need more informative and high-quality medical images to diagnose diseases. Image fusion plays a vital role in the field of biomedical image analysis. It aims to integrate the complementary information from multimodal images, producing a new composite image which is expected to be more informative for visual perception than any of the individual input images. The main objective of this paper is to improve the information, to preserve the edges and to enhance the quality of the fused image using cascaded principal component analysis (PCA) and shift invariant wavelet transforms. A novel image fusion technique based on cascaded PCA and shift invariant wavelet transforms is proposed in this paper. PCA in spatial domain extracts relevant information from the large dataset based on eigenvalue decomposition, and the wavelet transform operating in the complex domain with shift invariant properties brings out more directional and phase details of the image. The significance of maximum fusion rule applied in dual-tree complex wavelet transform domain enhances the average information and morphological details. The input images of the human brain of two different modalities (MRI and CT) are collected from whole brain atlas data distributed by Harvard University. Both MRI and CT images are fused using cascaded PCA and shift invariant wavelet transform method. The proposed method is evaluated based on three main key factors, namely structure preservation, edge preservation, contrast preservation. The experimental results and comparison with other existing fusion methods show the superior performance of the proposed image fusion framework in terms of visual and quantitative evaluations. In this paper, a complex wavelet-based image fusion has been discussed. The experimental results demonstrate that the proposed method enhances the directional features as well as fine edge details. Also, it reduces the redundant details, artifacts, distortions.

Color matching of fabric blends: hybrid Kubelka-Munk + artificial neural network based method

NASA Astrophysics Data System (ADS)

Furferi, Rocco; Governi, Lapo; Volpe, Yary

2016-11-01

Color matching of fabric blends is a key issue for the textile industry, mainly due to the rising need to create high-quality products for the fashion market. The process of mixing together differently colored fibers to match a desired color is usually performed by using some historical recipes, skillfully managed by company colorists. More often than desired, the first attempt in creating a blend is not satisfactory, thus requiring the experts to spend efforts in changing the recipe with a trial-and-error process. To confront this issue, a number of computer-based methods have been proposed in the last decades, roughly classified into theoretical and artificial neural network (ANN)-based approaches. Inspired by the above literature, the present paper provides a method for accurate estimation of spectrophotometric response of a textile blend composed of differently colored fibers made of different materials. In particular, the performance of the Kubelka-Munk (K-M) theory is enhanced by introducing an artificial intelligence approach to determine a more consistent value of the nonlinear function relationship between the blend and its components. Therefore, a hybrid K-M+ANN-based method capable of modeling the color mixing mechanism is devised to predict the reflectance values of a blend.

Topological Quantum Phase Transition in Synthetic Non-Abelian Gauge Potential: Gauge Invariance and Experimental Detections

PubMed Central

Sun, Fadi; Yu, Xiao-Lu; Ye, Jinwu; Fan, Heng; Liu, Wu-Ming

2013-01-01

The method of synthetic gauge potentials opens up a new avenue for our understanding and discovering novel quantum states of matter. We investigate the topological quantum phase transition of Fermi gases trapped in a honeycomb lattice in the presence of a synthetic non-Abelian gauge potential. We develop a systematic fermionic effective field theory to describe a topological quantum phase transition tuned by the non-Abelian gauge potential and explore its various important experimental consequences. Numerical calculations on lattice scales are performed to compare with the results achieved by the fermionic effective field theory. Several possible experimental detection methods of topological quantum phase transition are proposed. In contrast to condensed matter experiments where only gauge invariant quantities can be measured, both gauge invariant and non-gauge invariant quantities can be measured by experimentally generating various non-Abelian gauges corresponding to the same set of Wilson loops. PMID:23846153

The relativistic invariance of 4D-shapes

NASA Astrophysics Data System (ADS)

Calosi, Claudio

2015-05-01

A recent debate in the metaphysics of physics focuses on the invariance and intrinsicality of four-dimensional shapes in the Special Theory of Relativity. Davidson (2014) argues that four-dimensional shapes cannot be intrinsic properties of persisting objects because they have to be relativized to reference frames. Balashov (2014a) criticizes such an argument in that it mistakes four-dimensional shapes with their three-dimensional projections on the axes of those frames. This paper adds to that debate. Rather than criticizing an argument against the relativistic invariance of four-dimensional shapes, as Balashov did, it offers a direct argument in favor of such an invariance.

Recognition of rotated images using the multi-valued neuron and rotation-invariant 2D Fourier descriptors

NASA Astrophysics Data System (ADS)

Aizenberg, Evgeni; Bigio, Irving J.; Rodriguez-Diaz, Eladio

2012-03-01

The Fourier descriptors paradigm is a well-established approach for affine-invariant characterization of shape contours. In the work presented here, we extend this method to images, and obtain a 2D Fourier representation that is invariant to image rotation. The proposed technique retains phase uniqueness, and therefore structural image information is not lost. Rotation-invariant phase coefficients were used to train a single multi-valued neuron (MVN) to recognize satellite and human face images rotated by a wide range of angles. Experiments yielded 100% and 96.43% classification rate for each data set, respectively. Recognition performance was additionally evaluated under effects of lossy JPEG compression and additive Gaussian noise. Preliminary results show that the derived rotation-invariant features combined with the MVN provide a promising scheme for efficient recognition of rotated images.

Disformal invariance of curvature perturbation

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

Motohashi, Hayato; White, Jonathan, E-mail: motohashi@kicp.uchicago.edu, E-mail: jwhite@post.kek.jp

2016-02-01

We show that under a general disformal transformation the linear comoving curvature perturbation is not identically invariant, but is invariant on superhorizon scales for any theory that is disformally related to Horndeski's theory. The difference between disformally related curvature perturbations is found to be given in terms of the comoving density perturbation associated with a single canonical scalar field. In General Relativity it is well-known that this quantity vanishes on superhorizon scales through the Poisson equation that is obtained on combining the Hamiltonian and momentum constraints, and we confirm that a similar result holds for any theory that is disformallymore » related to Horndeski's scalar-tensor theory so long as the invertibility condition for the disformal transformation is satisfied. We also consider the curvature perturbation at full nonlinear order in the unitary gauge, and find that it is invariant under a general disformal transformation if we assume that an attractor regime has been reached. Finally, we also discuss the counting of degrees of freedom in theories disformally related to Horndeski's.« less

Dense real-time stereo matching using memory efficient semi-global-matching variant based on FPGAs

NASA Astrophysics Data System (ADS)

Buder, Maximilian

2012-06-01

This paper presents a stereo image matching system that takes advantage of a global image matching method. The system is designed to provide depth information for mobile robotic applications. Typical tasks of the proposed system are to assist in obstacle avoidance, SLAM and path planning. Mobile robots pose strong requirements about size, energy consumption, reliability and output quality of the image matching subsystem. Current available systems either rely on active sensors or on local stereo image matching algorithms. The first are only suitable in controlled environments while the second suffer from low quality depth-maps. Top ranking quality results are only achieved by an iterative approach using global image matching and color segmentation techniques which are computationally demanding and therefore difficult to be executed in realtime. Attempts were made to still reach realtime performance with global methods by simplifying the routines. The depth maps are at the end almost comparable to local methods. An equally named semi-global algorithm was proposed earlier that shows both very good image matching results and relatively simple operations. A memory efficient variant of the Semi-Global-Matching algorithm is reviewed and adopted for an implementation based on reconfigurable hardware. The implementation is suitable for realtime execution in the field of robotics. It will be shown that the modified version of the efficient Semi-Global-Matching method is delivering equivalent result compared to the original algorithm based on the Middlebury dataset. The system has proven to be capable of processing VGA sized images with a disparity resolution of 64 pixel at 33 frames per second based on low cost to mid-range hardware. In case the focus is shifted to a higher image resolution, 1024×1024-sized stereo frames may be processed with the same hardware at 10 fps. The disparity resolution settings stay unchanged. A mobile system that covers preprocessing, matching

No fifth force in a scale invariant universe

DOE PAGES

Ferreira, Pedro G.; Hill, Christopher T.; Ross, Graham G.

2017-03-15

We revisit the possibility that the Planck mass is spontaneously generated in scale-invariant scalar-tensor theories of gravity, typically leading to a “dilaton.” The fifth force, arising from the dilaton, is severely constrained by astrophysical measurements. We explore the possibility that nature is fundamentally scale invariant and argue that, as a consequence, the fifth-force effects are dramatically suppressed and such models are viable. Finally, we discuss possible obstructions to maintaining scale invariance and how these might be resolved.

A new registration method with voxel-matching technique for temporal subtraction images

NASA Astrophysics Data System (ADS)

Itai, Yoshinori; Kim, Hyoungseop; Ishikawa, Seiji; Katsuragawa, Shigehiko; Doi, Kunio

2008-03-01

A temporal subtraction image, which is obtained by subtraction of a previous image from a current one, can be used for enhancing interval changes on medical images by removing most of normal structures. One of the important problems in temporal subtraction is that subtraction images commonly include artifacts created by slight differences in the size, shape, and/or location of anatomical structures. In this paper, we developed a new registration method with voxel-matching technique for substantially removing the subtraction artifacts on the temporal subtraction image obtained from multiple-detector computed tomography (MDCT). With this technique, the voxel value in a warped (or non-warped) previous image is replaced by a voxel value within a kernel, such as a small cube centered at a given location, which would be closest (identical or nearly equal) to the voxel value in the corresponding location in the current image. Our new method was examined on 16 clinical cases with MDCT images. Preliminary results indicated that interval changes on the subtraction images were enhanced considerably, with a substantial reduction of misregistration artifacts. The temporal subtraction images obtained by use of the voxel-matching technique would be very useful for radiologists in the detection of interval changes on MDCT images.

Formation of propagation invariant laser beams with anamorphic optical systems

NASA Astrophysics Data System (ADS)

Soskind, Y. G.

2015-03-01

Propagation invariant structured laser beams play an important role in several photonics applications. A majority of propagation invariant beams are usually produced in the form of laser modes emanating from stable laser cavities. This work shows that anamorphic optical systems can be effectively employed to transform input propagation invariant laser beams and produce a variety of alternative propagation invariant structured laser beam distributions with different shapes and phase structures. This work also presents several types of anamorphic lens systems suitable for transforming the input laser modes into a variety of structured propagation invariant beams. The transformations are applied to different laser mode types, including Hermite-Gaussian, Laguerre-Gaussian, and Ince-Gaussian field distributions. The influence of the relative azimuthal orientation between the input laser modes and the anamorphic optical systems on the resulting transformed propagation invariant beams is presented as well.

Invariant functionals in higher-spin theory

NASA Astrophysics Data System (ADS)

Vasiliev, M. A.

2017-03-01

A new construction for gauge invariant functionals in the nonlinear higher-spin theory is proposed. Being supported by differential forms closed by virtue of the higher-spin equations, invariant functionals are associated with central elements of the higher-spin algebra. In the on-shell AdS4 higher-spin theory we identify a four-form conjectured to represent the generating functional for 3d boundary correlators and a two-form argued to support charges for black hole solutions. Two actions for 3d boundary conformal higher-spin theory are associated with the two parity-invariant higher-spin models in AdS4. The peculiarity of the spinorial formulation of the on-shell AdS3 higher-spin theory, where the invariant functional is supported by a two-form, is conjectured to be related to the holomorphic factorization at the boundary. The nonlinear part of the star-product function F* (B (x)) in the higher-spin equations is argued to lead to divergencies in the boundary limit representing singularities at coinciding boundary space-time points of the factors of B (x), which can be regularized by the point splitting. An interpretation of the RG flow in terms of proposed construction is briefly discussed.

Quantum implications of a scale invariant regularization

NASA Astrophysics Data System (ADS)

Ghilencea, D. M.

2018-04-01

We study scale invariance at the quantum level in a perturbative approach. For a scale-invariant classical theory, the scalar potential is computed at a three-loop level while keeping manifest this symmetry. Spontaneous scale symmetry breaking is transmitted at a quantum level to the visible sector (of ϕ ) by the associated Goldstone mode (dilaton σ ), which enables a scale-invariant regularization and whose vacuum expectation value ⟨σ ⟩ generates the subtraction scale (μ ). While the hidden (σ ) and visible sector (ϕ ) are classically decoupled in d =4 due to an enhanced Poincaré symmetry, they interact through (a series of) evanescent couplings ∝ɛ , dictated by the scale invariance of the action in d =4 -2 ɛ . At the quantum level, these couplings generate new corrections to the potential, as scale-invariant nonpolynomial effective operators ϕ2 n +4/σ2 n. These are comparable in size to "standard" loop corrections and are important for values of ϕ close to ⟨σ ⟩. For n =1 , 2, the beta functions of their coefficient are computed at three loops. In the IR limit, dilaton fluctuations decouple, the effective operators are suppressed by large ⟨σ ⟩, and the effective potential becomes that of a renormalizable theory with explicit scale symmetry breaking by the DR scheme (of μ =constant).

XQ-NLM: Denoising Diffusion MRI Data via x-q Space Non-Local Patch Matching.

PubMed

Chen, Geng; Wu, Yafeng; Shen, Dinggang; Yap, Pew-Thian

2016-10-01

Noise is a major issue influencing quantitative analysis in diffusion MRI. The effects of noise can be reduced by repeated acquisitions, but this leads to long acquisition times that can be unrealistic in clinical settings. For this reason, post-acquisition denoising methods have been widely used to improve SNR. Among existing methods, non-local means (NLM) has been shown to produce good image quality with edge preservation. However, currently the application of NLM to diffusion MRI has been mostly focused on the spatial space (i.e., the x -space), despite the fact that diffusion data live in a combined space consisting of the x -space and the q -space (i.e., the space of wavevectors). In this paper, we propose to extend NLM to both x -space and q -space. We show how patch-matching, as required in NLM, can be performed concurrently in x-q space with the help of azimuthal equidistant projection and rotation invariant features. Extensive experiments on both synthetic and real data confirm that the proposed x-q space NLM (XQ-NLM) outperforms the classic NLM.

Local Subspace Classifier with Transform-Invariance for Image Classification

NASA Astrophysics Data System (ADS)

Hotta, Seiji

A family of linear subspace classifiers called local subspace classifier (LSC) outperforms the k-nearest neighbor rule (kNN) and conventional subspace classifiers in handwritten digit classification. However, LSC suffers very high sensitivity to image transformations because it uses projection and the Euclidean distances for classification. In this paper, I present a combination of a local subspace classifier (LSC) and a tangent distance (TD) for improving accuracy of handwritten digit recognition. In this classification rule, we can deal with transform-invariance easily because we are able to use tangent vectors for approximation of transformations. However, we cannot use tangent vectors in other type of images such as color images. Hence, kernel LSC (KLSC) is proposed for incorporating transform-invariance into LSC via kernel mapping. The performance of the proposed methods is verified with the experiments on handwritten digit and color image classification.

Learning graph matching.

PubMed

Caetano, Tibério S; McAuley, Julian J; Cheng, Li; Le, Quoc V; Smola, Alex J

2009-06-01

As a fundamental problem in pattern recognition, graph matching has applications in a variety of fields, from computer vision to computational biology. In graph matching, patterns are modeled as graphs and pattern recognition amounts to finding a correspondence between the nodes of different graphs. Many formulations of this problem can be cast in general as a quadratic assignment problem, where a linear term in the objective function encodes node compatibility and a quadratic term encodes edge compatibility. The main research focus in this theme is about designing efficient algorithms for approximately solving the quadratic assignment problem, since it is NP-hard. In this paper we turn our attention to a different question: how to estimate compatibility functions such that the solution of the resulting graph matching problem best matches the expected solution that a human would manually provide. We present a method for learning graph matching: the training examples are pairs of graphs and the 'labels' are matches between them. Our experimental results reveal that learning can substantially improve the performance of standard graph matching algorithms. In particular, we find that simple linear assignment with such a learning scheme outperforms Graduated Assignment with bistochastic normalisation, a state-of-the-art quadratic assignment relaxation algorithm.

Texture-specific bag of visual words model and spatial cone matching-based method for the retrieval of focal liver lesions using multiphase contrast-enhanced CT images.

PubMed

Xu, Yingying; Lin, Lanfen; Hu, Hongjie; Wang, Dan; Zhu, Wenchao; Wang, Jian; Han, Xian-Hua; Chen, Yen-Wei

2018-01-01

The bag of visual words (BoVW) model is a powerful tool for feature representation that can integrate various handcrafted features like intensity, texture, and spatial information. In this paper, we propose a novel BoVW-based method that incorporates texture and spatial information for the content-based image retrieval to assist radiologists in clinical diagnosis. This paper presents a texture-specific BoVW method to represent focal liver lesions (FLLs). Pixels in the region of interest (ROI) are classified into nine texture categories using the rotation-invariant uniform local binary pattern method. The BoVW-based features are calculated for each texture category. In addition, a spatial cone matching (SCM)-based representation strategy is proposed to describe the spatial information of the visual words in the ROI. In a pilot study, eight radiologists with different clinical experience performed diagnoses for 20 cases with and without the top six retrieved results. A total of 132 multiphase computed tomography volumes including five pathological types were collected. The texture-specific BoVW was compared to other BoVW-based methods using the constructed dataset of FLLs. The results show that our proposed model outperforms the other three BoVW methods in discriminating different lesions. The SCM method, which adds spatial information to the orderless BoVW model, impacted the retrieval performance. In the pilot trial, the average diagnosis accuracy of the radiologists was improved from 66 to 80% using the retrieval system. The preliminary results indicate that the texture-specific features and the SCM-based BoVW features can effectively characterize various liver lesions. The retrieval system has the potential to improve the diagnostic accuracy and the confidence of the radiologists.

Matching Matched Filtering with Deep Networks for Gravitational-Wave Astronomy.

PubMed

Gabbard, Hunter; Williams, Michael; Hayes, Fergus; Messenger, Chris

2018-04-06

We report on the construction of a deep convolutional neural network that can reproduce the sensitivity of a matched-filtering search for binary black hole gravitational-wave signals. The standard method for the detection of well-modeled transient gravitational-wave signals is matched filtering. We use only whitened time series of measured gravitational-wave strain as an input, and we train and test on simulated binary black hole signals in synthetic Gaussian noise representative of Advanced LIGO sensitivity. We show that our network can classify signal from noise with a performance that emulates that of match filtering applied to the same data sets when considering the sensitivity defined by receiver-operator characteristics.

Matching Matched Filtering with Deep Networks for Gravitational-Wave Astronomy

NASA Astrophysics Data System (ADS)

Gabbard, Hunter; Williams, Michael; Hayes, Fergus; Messenger, Chris

2018-04-01

We report on the construction of a deep convolutional neural network that can reproduce the sensitivity of a matched-filtering search for binary black hole gravitational-wave signals. The standard method for the detection of well-modeled transient gravitational-wave signals is matched filtering. We use only whitened time series of measured gravitational-wave strain as an input, and we train and test on simulated binary black hole signals in synthetic Gaussian noise representative of Advanced LIGO sensitivity. We show that our network can classify signal from noise with a performance that emulates that of match filtering applied to the same data sets when considering the sensitivity defined by receiver-operator characteristics.

The coarticulation/invariance scale: Mutual information as a measure of coarticulation resistance, motor synergy, and articulatory invariance

PubMed Central

Iskarous, Khalil; Mooshammer, Christine; Hoole, Phil; Recasens, Daniel; Shadle, Christine H.; Saltzman, Elliot; Whalen, D. H.

2013-01-01

Coarticulation and invariance are two topics at the center of theorizing about speech production and speech perception. In this paper, a quantitative scale is proposed that places coarticulation and invariance at the two ends of the scale. This scale is based on physical information flow in the articulatory signal, and uses Information Theory, especially the concept of mutual information, to quantify these central concepts of speech research. Mutual Information measures the amount of physical information shared across phonological units. In the proposed quantitative scale, coarticulation corresponds to greater and invariance to lesser information sharing. The measurement scale is tested by data from three languages: German, Catalan, and English. The relation between the proposed scale and several existing theories of coarticulation is discussed, and implications for existing theories of speech production and perception are presented. PMID:23927125

Radiometric Cross-Calibration of GAOFEN-1 Wfv Cameras with LANDSAT-8 Oli and Modis Sensors Based on Radiation and Geometry Matching

NASA Astrophysics Data System (ADS)

Li, J.; Wu, Z.; Wei, X.; Zhang, Y.; Feng, F.; Guo, F.

2018-04-01

Cross-calibration has the advantages of high precision, low resource requirements and simple implementation. It has been widely used in recent years. The four wide-field-of-view (WFV) cameras on-board Gaofen-1 satellite provide high spatial resolution and wide combined coverage (4 × 200 km) without onboard calibration. In this paper, the four-band radiometric cross-calibration coefficients of WFV1 camera were obtained based on radiation and geometry matching taking Landsat 8 OLI (Operational Land Imager) sensor as reference. Scale Invariant Feature Transform (SIFT) feature detection method and distance and included angle weighting method were introduced to correct misregistration of WFV-OLI image pair. The radiative transfer model was used to eliminate difference between OLI sensor and WFV1 camera through the spectral match factor (SMF). The near-infrared band of WFV1 camera encompasses water vapor absorption bands, thus a Look Up Table (LUT) for SMF varies from water vapor amount is established to estimate the water vapor effects. The surface synchronization experiment was designed to verify the reliability of the cross-calibration coefficients, which seem to perform better than the official coefficients claimed by the China Centre for Resources Satellite Data and Application (CCRSDA).

Orthogonal Invariant Sets of the Diffusion Tensor and the Development of a Curvilinear Set Suitable for Low-Anisotropy Tissues

PubMed Central

Damion, Robin A.; Radjenovic, Aleksandra; Ingham, Eileen; Jin, Zhongmin; Ries, Michael E.

2013-01-01

We develop a curvilinear invariant set of the diffusion tensor which may be applied to Diffusion Tensor Imaging measurements on tissues and porous media. This new set is an alternative to the more common invariants such as fractional anisotropy and the diffusion mode. The alternative invariant set possesses a different structure to the other known invariant sets; the second and third members of the curvilinear set measure the degree of orthotropy and oblateness/prolateness, respectively. The proposed advantage of these invariants is that they may work well in situations of low diffusion anisotropy and isotropy, as is often observed in tissues such as cartilage. We also explore the other orthogonal invariant sets in terms of their geometry in relation to eigenvalue space; a cylindrical set, a spherical set (including fractional anisotropy and the mode), and a log-Euclidean set. These three sets have a common structure. The first invariant measures the magnitude of the diffusion, the second and third invariants capture aspects of the anisotropy; the magnitude of the anisotropy and the shape of the diffusion ellipsoid (the manner in which the anisotropy is realised). We also show a simple method to prove the orthogonality of the invariants within a set. PMID:24244366

Lorentz-invariant three-vectors and alternative formulation of relativistic dynamics

NASA Astrophysics Data System (ADS)

RÈ©bilas, Krzysztof

2010-03-01

Besides the well-known scalar invariants, there also exist vectorial invariants in special relativity. It is shown that the three-vector (dp⃗/dt)∥+γv(dp⃗/dt)⊥ is invariant under the Lorentz transformation. The subscripts ∥ and ⊥ denote the respective components with respect to the direction of the velocity of the body v⃗, and p⃗ is the relativistic momentum. We show that this vector is equal to a force F⃗R, which satisfies the classical Newtonian law F⃗R=ma⃗R in the instantaneous inertial rest frame of an accelerating body. Therefore, the relation F⃗R=(dp⃗/dt)∥+γv(dp⃗/dt)⊥, based on the Lorentz-invariant vectors, may be used as an invariant (not merely a covariant) relativistic equation of motion in any inertial system of reference. An alternative approach to classical electrodynamics based on the invariant three-vectors is proposed.

Rotation, scale, and translation invariant pattern recognition using feature extraction

NASA Astrophysics Data System (ADS)

Prevost, Donald; Doucet, Michel; Bergeron, Alain; Veilleux, Luc; Chevrette, Paul C.; Gingras, Denis J.

1997-03-01

A rotation, scale and translation invariant pattern recognition technique is proposed.It is based on Fourier- Mellin Descriptors (FMD). Each FMD is taken as an independent feature of the object, and a set of those features forms a signature. FMDs are naturally rotation invariant. Translation invariance is achieved through pre- processing. A proper normalization of the FMDs gives the scale invariance property. This approach offers the double advantage of providing invariant signatures of the objects, and a dramatic reduction of the amount of data to process. The compressed invariant feature signature is next presented to a multi-layered perceptron neural network. This final step provides some robustness to the classification of the signatures, enabling good recognition behavior under anamorphically scaled distortion. We also present an original feature extraction technique, adapted to optical calculation of the FMDs. A prototype optical set-up was built, and experimental results are presented.

Evaluation of scaling invariance embedded in short time series.

PubMed

Pan, Xue; Hou, Lei; Stephen, Mutua; Yang, Huijie; Zhu, Chenping

2014-01-01

Scaling invariance of time series has been making great contributions in diverse research fields. But how to evaluate scaling exponent from a real-world series is still an open problem. Finite length of time series may induce unacceptable fluctuation and bias to statistical quantities and consequent invalidation of currently used standard methods. In this paper a new concept called correlation-dependent balanced estimation of diffusion entropy is developed to evaluate scale-invariance in very short time series with length ~10(2). Calculations with specified Hurst exponent values of 0.2,0.3,...,0.9 show that by using the standard central moving average de-trending procedure this method can evaluate the scaling exponents for short time series with ignorable bias (≤0.03) and sharp confidential interval (standard deviation ≤0.05). Considering the stride series from ten volunteers along an approximate oval path of a specified length, we observe that though the averages and deviations of scaling exponents are close, their evolutionary behaviors display rich patterns. It has potential use in analyzing physiological signals, detecting early warning signals, and so on. As an emphasis, the our core contribution is that by means of the proposed method one can estimate precisely shannon entropy from limited records.

Rotation invariant features for wear particle classification

NASA Astrophysics Data System (ADS)

Arof, Hamzah; Deravi, Farzin

1997-09-01

This paper investigates the ability of a set of rotation invariant features to classify images of wear particles found in used lubricating oil of machinery. The rotation invariant attribute of the features is derived from the property of the magnitudes of Fourier transform coefficients that do not change with spatial shift of the input elements. By analyzing individual circular neighborhoods centered at every pixel in an image, local and global texture characteristics of an image can be described. A number of input sequences are formed by the intensities of pixels on concentric rings of various radii measured from the center of each neighborhood. Fourier transforming the sequences would generate coefficients whose magnitudes are invariant to rotation. Rotation invariant features extracted from these coefficients were utilized to classify wear particle images that were obtained from a number of different particles captured at different orientations. In an experiment involving images of 6 classes, the circular neighborhood features obtained a 91% recognition rate which compares favorably to a 76% rate achieved by features of a 6 by 6 co-occurrence matrix.

What makes viewpoint-invariant properties perceptually salient?

PubMed

Jacobs, David W

2003-07-01

It has been noted that many of the perceptually salient image properties identified by the Gestalt psychologists, such as collinearity, parallelism, and good continuation, age invariant to changes in viewpoint. However, I show that viewpoint invariance is not sufficient to distinguish these Gestalt properties; one can define an infinite number of viewpoint-invariant properties that are not perceptually salient. I then show that generally, the perceptually salient viewpoint-invariant properties are minimal, in the sense that they can be derived by using less image information than for nonsalient properties. This finding provides support for the hypothesis that the biological relevance of an image property is determined both by the extent to which it provides information about the world and by the ease with which this property can be computed. [An abbreviated version of this work, including technical details that are avoided in this paper, is contained in K. Boyer and S. Sarker, eds., Perceptual Organization for Artificial Vision Systems (Kluwer Academic, Dordrecht, The Netherlands, 2000), pp. 121-138.

Using string invariants for prediction searching for optimal parameters

NASA Astrophysics Data System (ADS)

Bundzel, Marek; Kasanický, Tomáš; Pinčák, Richard

2016-02-01

We have developed a novel prediction method based on string invariants. The method does not require learning but a small set of parameters must be set to achieve optimal performance. We have implemented an evolutionary algorithm for the parametric optimization. We have tested the performance of the method on artificial and real world data and compared the performance to statistical methods and to a number of artificial intelligence methods. We have used data and the results of a prediction competition as a benchmark. The results show that the method performs well in single step prediction but the method's performance for multiple step prediction needs to be improved. The method works well for a wide range of parameters.

Renormalization group invariant of lepton Yukawa couplings

NASA Astrophysics Data System (ADS)

Tsuyuki, Takanao

2015-04-01

By using quark Yukawa matrices only, we can construct renormalization invariants that are exact at the one-loop level in the standard model. One of them, Iq, is accidentally consistent with unity, even though quark masses are strongly hierarchical. We calculate a lepton version of the invariant Il for Dirac and Majorana neutrino cases and find that Il can also be close to unity. For the Dirac neutrino and inverted hierarchy case, if the lightest neutrino mass is 3.0 meV to 8.8 meV, an equality Iq=Il can be satisfied. These invariants are not changed even if new particles couple to the standard model particles, as long as those couplings are generation independent.

Knot invariants from Virasoro related representation and pretzel knots

DOE PAGES

Galakhov, D.; Melnikov, D.; Mironov, A.; ...

2015-08-06

In this study, we remind the method to calculate colored Jones polynomials for the plat representations of knot diagrams from the knowledge of modular transformation (monodromies) of Virasoro conformal blocks with insertions of degenerate fields. As an illustration we use a rich family of pretzel knots, lying on a surface of arbitrary genus g, which was recently analyzed by the evolution method. Further generalizations can be to generic Virasoro modular transformations, provided by integral kernels, which can lead to the Hikami invariants.

Robust iterative closest point algorithm based on global reference point for rotation invariant registration.

PubMed

Du, Shaoyi; Xu, Yiting; Wan, Teng; Hu, Huaizhong; Zhang, Sirui; Xu, Guanglin; Zhang, Xuetao

2017-01-01

The iterative closest point (ICP) algorithm is efficient and accurate for rigid registration but it needs the good initial parameters. It is easily failed when the rotation angle between two point sets is large. To deal with this problem, a new objective function is proposed by introducing a rotation invariant feature based on the Euclidean distance between each point and a global reference point, where the global reference point is a rotation invariant. After that, this optimization problem is solved by a variant of ICP algorithm, which is an iterative method. Firstly, the accurate correspondence is established by using the weighted rotation invariant feature distance and position distance together. Secondly, the rigid transformation is solved by the singular value decomposition method. Thirdly, the weight is adjusted to control the relative contribution of the positions and features. Finally this new algorithm accomplishes the registration by a coarse-to-fine way whatever the initial rotation angle is, which is demonstrated to converge monotonically. The experimental results validate that the proposed algorithm is more accurate and robust compared with the original ICP algorithm.

Robust iterative closest point algorithm based on global reference point for rotation invariant registration

PubMed Central

Du, Shaoyi; Xu, Yiting; Wan, Teng; Zhang, Sirui; Xu, Guanglin; Zhang, Xuetao

2017-01-01

The iterative closest point (ICP) algorithm is efficient and accurate for rigid registration but it needs the good initial parameters. It is easily failed when the rotation angle between two point sets is large. To deal with this problem, a new objective function is proposed by introducing a rotation invariant feature based on the Euclidean distance between each point and a global reference point, where the global reference point is a rotation invariant. After that, this optimization problem is solved by a variant of ICP algorithm, which is an iterative method. Firstly, the accurate correspondence is established by using the weighted rotation invariant feature distance and position distance together. Secondly, the rigid transformation is solved by the singular value decomposition method. Thirdly, the weight is adjusted to control the relative contribution of the positions and features. Finally this new algorithm accomplishes the registration by a coarse-to-fine way whatever the initial rotation angle is, which is demonstrated to converge monotonically. The experimental results validate that the proposed algorithm is more accurate and robust compared with the original ICP algorithm. PMID:29176780

Computation of Quasi-Periodic Normally Hyperbolic Invariant Tori: Algorithms, Numerical Explorations and Mechanisms of Breakdown

NASA Astrophysics Data System (ADS)

Canadell, Marta; Haro, Àlex

2017-12-01

We present several algorithms for computing normally hyperbolic invariant tori carrying quasi-periodic motion of a fixed frequency in families of dynamical systems. The algorithms are based on a KAM scheme presented in Canadell and Haro (J Nonlinear Sci, 2016. doi: 10.1007/s00332-017-9389-y), to find the parameterization of the torus with prescribed dynamics by detuning parameters of the model. The algorithms use different hyperbolicity and reducibility properties and, in particular, compute also the invariant bundles and Floquet transformations. We implement these methods in several 2-parameter families of dynamical systems, to compute quasi-periodic arcs, that is, the parameters for which 1D normally hyperbolic invariant tori with a given fixed frequency do exist. The implementation lets us to perform the continuations up to the tip of the quasi-periodic arcs, for which the invariant curves break down. Three different mechanisms of breakdown are analyzed, using several observables, leading to several conjectures.

KAM tori and whiskered invariant tori for non-autonomous systems

NASA Astrophysics Data System (ADS)

Canadell, Marta; de la Llave, Rafael

2015-08-01

We consider non-autonomous dynamical systems which converge to autonomous (or periodic) systems exponentially fast in time. Such systems appear naturally as models of many physical processes affected by external pulses. We introduce definitions of non-autonomous invariant tori and non-autonomous whiskered tori and their invariant manifolds and we prove their persistence under small perturbations, smooth dependence on parameters and several geometric properties (if the systems are Hamiltonian, the tori are Lagrangian manifolds). We note that such definitions are problematic for general time-dependent systems, but we show that they are unambiguous for systems converging exponentially fast to autonomous. The proof of persistence relies only on a standard Implicit Function Theorem in Banach spaces and it does not require that the rotations in the tori are Diophantine nor that the systems we consider preserve any geometric structure. We only require that the autonomous system preserves these objects. In particular, when the autonomous system is integrable, we obtain the persistence of tori with rational rotational. We also discuss fast and efficient algorithms for their computation. The method also applies to infinite dimensional systems which define a good evolution, e.g. PDE's. When the systems considered are Hamiltonian, we show that the time dependent invariant tori are isotropic. Hence, the invariant tori of maximal dimension are Lagrangian manifolds. We also obtain that the (un)stable manifolds of whiskered tori are Lagrangian manifolds. We also include a comparison with the more global theory developed in Blazevski and de la Llave (2011).

Evaluation of scale invariance in physiological signals by means of balanced estimation of diffusion entropy

NASA Astrophysics Data System (ADS)

Zhang, Wenqing; Qiu, Lu; Xiao, Qin; Yang, Huijie; Zhang, Qingjun; Wang, Jianyong

2012-11-01

By means of the concept of the balanced estimation of diffusion entropy, we evaluate the reliable scale invariance embedded in different sleep stages and stride records. Segments corresponding to waking, light sleep, rapid eye movement (REM) sleep, and deep sleep stages are extracted from long-term electroencephalogram signals. For each stage the scaling exponent value is distributed over a considerably wide range, which tell us that the scaling behavior is subject and sleep cycle dependent. The average of the scaling exponent values for waking segments is almost the same as that for REM segments (˜0.8). The waking and REM stages have a significantly higher value of the average scaling exponent than that for light sleep stages (˜0.7). For the stride series, the original diffusion entropy (DE) and the balanced estimation of diffusion entropy (BEDE) give almost the same results for detrended series. The evolutions of local scaling invariance show that the physiological states change abruptly, although in the experiments great efforts have been made to keep conditions unchanged. The global behavior of a single physiological signal may lose rich information on physiological states. Methodologically, the BEDE can evaluate with considerable precision the scale invariance in very short time series (˜102), while the original DE method sometimes may underestimate scale-invariance exponents or even fail in detecting scale-invariant behavior. The BEDE method is sensitive to trends in time series. The existence of trends may lead to an unreasonably high value of the scaling exponent and consequent mistaken conclusions.

Evaluation of scale invariance in physiological signals by means of balanced estimation of diffusion entropy.

PubMed

Zhang, Wenqing; Qiu, Lu; Xiao, Qin; Yang, Huijie; Zhang, Qingjun; Wang, Jianyong

2012-11-01

By means of the concept of the balanced estimation of diffusion entropy, we evaluate the reliable scale invariance embedded in different sleep stages and stride records. Segments corresponding to waking, light sleep, rapid eye movement (REM) sleep, and deep sleep stages are extracted from long-term electroencephalogram signals. For each stage the scaling exponent value is distributed over a considerably wide range, which tell us that the scaling behavior is subject and sleep cycle dependent. The average of the scaling exponent values for waking segments is almost the same as that for REM segments (∼0.8). The waking and REM stages have a significantly higher value of the average scaling exponent than that for light sleep stages (∼0.7). For the stride series, the original diffusion entropy (DE) and the balanced estimation of diffusion entropy (BEDE) give almost the same results for detrended series. The evolutions of local scaling invariance show that the physiological states change abruptly, although in the experiments great efforts have been made to keep conditions unchanged. The global behavior of a single physiological signal may lose rich information on physiological states. Methodologically, the BEDE can evaluate with considerable precision the scale invariance in very short time series (∼10^{2}), while the original DE method sometimes may underestimate scale-invariance exponents or even fail in detecting scale-invariant behavior. The BEDE method is sensitive to trends in time series. The existence of trends may lead to an unreasonably high value of the scaling exponent and consequent mistaken conclusions.

Testing Factorial Invariance in Multilevel Data: A Monte Carlo Study

ERIC Educational Resources Information Center

Kim, Eun Sook; Kwok, Oi-man; Yoon, Myeongsun

2012-01-01

Testing factorial invariance has recently gained more attention in different social science disciplines. Nevertheless, when examining factorial invariance, it is generally assumed that the observations are independent of each other, which might not be always true. In this study, we examined the impact of testing factorial invariance in multilevel…

Rephasing invariant parametrization of flavor mixing

NASA Astrophysics Data System (ADS)

Lee, Tae-Hun

A new rephasing invariant parametrization for the 3 x 3 CKM matrix, called (x, y) parametrization, is introduced and the properties and applications of the parametrization are discussed. The overall phase condition leads this parametrization to have only six rephsing invariant parameters and two constraints. Its simplicity and regularity become apparent when it is applied to the one-loop RGE (renormalization group equations) for the Yukawa couplings. The implications of this parametrization for unification of the Yukawa couplings are also explored.

Expression-invariant representations of faces.

PubMed

Bronstein, Alexander M; Bronstein, Michael M; Kimmel, Ron

2007-01-01

Addressed here is the problem of constructing and analyzing expression-invariant representations of human faces. We demonstrate and justify experimentally a simple geometric model that allows to describe facial expressions as isometric deformations of the facial surface. The main step in the construction of expression-invariant representation of a face involves embedding of the facial intrinsic geometric structure into some low-dimensional space. We study the influence of the embedding space geometry and dimensionality choice on the representation accuracy and argue that compared to its Euclidean counterpart, spherical embedding leads to notably smaller metric distortions. We experimentally support our claim showing that a smaller embedding error leads to better recognition.

Numeric invariants from multidimensional persistence

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

Skryzalin, Jacek; Carlsson, Gunnar

2017-05-19

In this paper, we analyze the space of multidimensional persistence modules from the perspectives of algebraic geometry. We first build a moduli space of a certain subclass of easily analyzed multidimensional persistence modules, which we construct specifically to capture much of the information which can be gained by using multidimensional persistence over one-dimensional persistence. We argue that the global sections of this space provide interesting numeric invariants when evaluated against our subclass of multidimensional persistence modules. Lastly, we extend these global sections to the space of all multidimensional persistence modules and discuss how the resulting numeric invariants might be usedmore » to study data.« less

Trace anomaly and invariance under transformation of units

NASA Astrophysics Data System (ADS)

Namavarian, Nadereh

2017-05-01

Paying attention to conformal invariance as the invariance under local transformations of units of measure, we take a conformal-invariant quantum field as a quantum matter theory in which one has the freedom to choose the values of units of mass, length, and time arbitrarily at each point. To be able to have this view, it is necessary that the background on which the quantum field is based be conformal invariant as well. Consequently, defining the unambiguous expectation value of the energy-momentum tensor of such a quantum field through the Wald renormalizing prescription necessitates breaking down the conformal symmetry of the background. Then, noticing the field equations suitable for describing the backreaction effect, we show that the existence of the "trace anomaly," known for indicating the brokenness of conformal symmetry in quantum field theory, can also indicate the above "gravitational" conformal symmetry brokenness.

HONTIOR - HIGHER-ORDER NEURAL NETWORK FOR TRANSFORMATION INVARIANT OBJECT RECOGNITION

NASA Technical Reports Server (NTRS)

Spirkovska, L.

1994-01-01

Neural networks have been applied in numerous fields, including transformation invariant object recognition, wherein an object is recognized despite changes in the object's position in the input field, size, or rotation. One of the more successful neural network methods used in invariant object recognition is the higher-order neural network (HONN) method. With a HONN, known relationships are exploited and the desired invariances are built directly into the architecture of the network, eliminating the need for the network to learn invariance to transformations. This results in a significant reduction in the training time required, since the network needs to be trained on only one view of each object, not on numerous transformed views. Moreover, one hundred percent accuracy is guaranteed for images characterized by the built-in distortions, providing noise is not introduced through pixelation. The program HONTIOR implements a third-order neural network having invariance to translation, scale, and in-plane rotation built directly into the architecture, Thus, for 2-D transformation invariance, the network needs only to be trained on just one view of each object. HONTIOR can also be used for 3-D transformation invariant object recognition by training the network only on a set of out-of-plane rotated views. Historically, the major drawback of HONNs has been that the size of the input field was limited to the memory required for the large number of interconnections in a fully connected network. HONTIOR solves this problem by coarse coding the input images (coding an image as a set of overlapping but offset coarser images). Using this scheme, large input fields (4096 x 4096 pixels) can easily be represented using very little virtual memory (30Mb). The HONTIOR distribution consists of three main programs. The first program contains the training and testing routines for a third-order neural network. The second program contains the same training and testing procedures as the

Relationship between measurement invariance and age-related differences in the prevalence of generalized anxiety disorder.