Correlation among genetic, Euclidean, temporal, and herd ownership distances of porcine reproductive and respiratory syndrome virus strains in Quebec, Canada

Directory of Open Access Journals (Sweden)

Lambert Marie-Ève

2012-06-01

Full Text Available Abstract Background Porcine reproductive and respiratory syndrome (PRRS is a viral disease that has a major economic impact for the swine industry. Its control is mostly directed towards preventing its spread which requires a better understanding of the mechanisms of transmission of the virus between herds. The objectives of this study were to describe the genetic diversity and to assess the correlation among genetic, Euclidean and temporal distances and ownership to better understand pathways of transmission. Results A cross-sectional study was conducted on sites located in a high density area of swine production in Quebec. Geographical coordinates (longitude/latitude, date of submission and ownership were obtained for each site. ORF5 sequencing was attempted on PRRSV positive sites. Proportion of pairwise combinations of strains having ≥98% genetic homology were analysed according to Euclidean distances and ownership. Correlations between genetic, Euclidean and temporal distances and ownership were assessed using Mantel tests on continuous and binary matrices. Sensitivity of the correlations between genetic and Euclidean as well as temporal distances was evaluated for different Euclidean and temporal distance thresholds. An ORF5 sequence was identified for 132 of the 176 (75% PRRSV positive sites; 122 were wild-type strains. The mean (min-max genetic, Euclidean and temporal pairwise distances were 11.6% (0–18.7, 15.0 km (0.04-45.7 and 218 days (0–852, respectively. Significant positive correlations were observed between genetic and ownership, genetic and Euclidean and between genetic and temporal binary distances. The relationship between genetic and ownership suggests either common sources of animals or semen, employees, technical services or vehicles, whereas that between genetic and Euclidean binary distances is compatible with area spread of the virus. The latter correlation was observed only up to 5 km. Conclusions This study

Euclidean distance can identify the mannitol level that produces the most remarkable integral effect on sugarcane micropropagation in temporary immersion bioreactors.

Science.gov (United States)

Gómez, Daviel; Hernández, L Ázaro; Yabor, Lourdes; Beemster, Gerrit T S; Tebbe, Christoph C; Papenbrock, Jutta; Lorenzo, José Carlos

2018-03-15

Plant scientists usually record several indicators in their abiotic factor experiments. The common statistical management involves univariate analyses. Such analyses generally create a split picture of the effects of experimental treatments since each indicator is addressed independently. The Euclidean distance combined with the information of the control treatment could have potential as an integrating indicator. The Euclidean distance has demonstrated its usefulness in many scientific fields but, as far as we know, it has not yet been employed for plant experimental analyses. To exemplify the use of the Euclidean distance in this field, we performed an experiment focused on the effects of mannitol on sugarcane micropropagation in temporary immersion bioreactors. Five mannitol concentrations were compared: 0, 50, 100, 150 and 200 mM. As dependent variables we recorded shoot multiplication rate, fresh weight, and levels of aldehydes, chlorophylls, carotenoids and phenolics. The statistical protocol which we then carried out integrated all dependent variables to easily identify the mannitol concentration that produced the most remarkable integral effect. Results provided by the Euclidean distance demonstrate a gradually increasing distance from the control in function of increasing mannitol concentrations. 200 mM mannitol caused the most significant alteration of sugarcane biochemistry and physiology under the experimental conditions described here. This treatment showed the longest statistically significant Euclidean distance to the control treatment (2.38). In contrast, 50 and 100 mM mannitol showed the lowest Euclidean distances (0.61 and 0.84, respectively) and thus poor integrated effects of mannitol. The analysis shown here indicates that the use of the Euclidean distance can contribute to establishing a more integrated evaluation of the contrasting mannitol treatments.

Identifikasi Huruf Kapital Tulisan Tangan Menggunakan Linear Discriminant Analysis dan Euclidean Distance

Directory of Open Access Journals (Sweden)

Septa Cahyani

2018-04-01

Full Text Available The human ability to recognize a variety of objects, however complex the object, is the special ability that humans possess. Any normal human will have no difficulty in recognizing handwriting objects between an author and another author. With the rapid development of digital technology, the human ability to recognize handwriting objects has been applied in a program known as Computer Vision. This study aims to create identification system different types of handwriting capital letters that have different sizes, thickness, shape, and tilt (distinctive features in handwriting using Linear Discriminant Analysis (LDA and Euclidean Distance methods. LDA is used to obtain characteristic characteristics of the image and provide the distance between the classes becomes larger, while the distance between training data in one class becomes smaller, so that the introduction time of digital image of handwritten capital letter using Euclidean Distance becomes faster computation time (by searching closest distance between training data and data testing. The results of testing the sample data showed that the image resolution of 50x50 pixels is the exact image resolution used for data as much as 1560 handwritten capital letter data compared to image resolution 25x25 pixels and 40x40 pixels. While the test data and training data testing using the method of 10-fold cross validation where 1404 for training data and 156 for data testing showed identification of digital image handwriting capital letter has an average effectiveness of the accuracy rate of 75.39% with the average time computing of 0.4199 seconds.

Euclidean distance and Kolmogorov-Smirnov analyses of multi-day auditory event-related potentials: a longitudinal stability study

Science.gov (United States)

Durato, M. V.; Albano, A. M.; Rapp, P. E.; Nawang, S. A.

2015-06-01

The validity of ERPs as indices of stable neurophysiological traits is partially dependent on their stability over time. Previous studies on ERP stability, however, have reported diverse stability estimates despite using the same component scoring methods. This present study explores a novel approach in investigating the longitudinal stability of average ERPs—that is, by treating the ERP waveform as a time series and then applying Euclidean Distance and Kolmogorov-Smirnov analyses to evaluate the similarity or dissimilarity between the ERP time series of different sessions or run pairs. Nonlinear dynamical analysis show that in the absence of a change in medical condition, the average ERPs of healthy human adults are highly longitudinally stable—as evaluated by both the Euclidean distance and the Kolmogorov-Smirnov test.

Euclidean distance and Kolmogorov-Smirnov analyses of multi-day auditory event-related potentials: a longitudinal stability study

International Nuclear Information System (INIS)

Durato, M V; Nawang, S A; Albano, A M; Rapp, P E

2015-01-01

The validity of ERPs as indices of stable neurophysiological traits is partially dependent on their stability over time. Previous studies on ERP stability, however, have reported diverse stability estimates despite using the same component scoring methods. This present study explores a novel approach in investigating the longitudinal stability of average ERPs—that is, by treating the ERP waveform as a time series and then applying Euclidean Distance and Kolmogorov-Smirnov analyses to evaluate the similarity or dissimilarity between the ERP time series of different sessions or run pairs. Nonlinear dynamical analysis show that in the absence of a change in medical condition, the average ERPs of healthy human adults are highly longitudinally stable—as evaluated by both the Euclidean distance and the Kolmogorov-Smirnov test. (paper)

Steiner tree heuristic in the Euclidean d-space using bottleneck distances

DEFF Research Database (Denmark)

Lorenzen, Stephan Sloth; Winter, Pawel

2016-01-01

Some of the most efficient heuristics for the Euclidean Steiner minimal tree problem in the d-dimensional space, d ≥2, use Delaunay tessellations and minimum spanning trees to determine small subsets of geometrically close terminals. Their low-cost Steiner trees are determined and concatenated...... in a greedy fashion to obtain a low cost tree spanning all terminals. The weakness of this approach is that obtained solutions are topologically related to minimum spanning trees. To avoid this and to obtain even better solutions, bottleneck distances are utilized to determine good subsets of terminals...

Phylogenetic trees and Euclidean embeddings.

Science.gov (United States)

Layer, Mark; Rhodes, John A

2017-01-01

It was recently observed by de Vienne et al. (Syst Biol 60(6):826-832, 2011) that a simple square root transformation of distances between taxa on a phylogenetic tree allowed for an embedding of the taxa into Euclidean space. While the justification for this was based on a diffusion model of continuous character evolution along the tree, here we give a direct and elementary explanation for it that provides substantial additional insight. We use this embedding to reinterpret the differences between the NJ and BIONJ tree building algorithms, providing one illustration of how this embedding reflects tree structures in data.

Detecting Malicious Nodes in Medical Smartphone Networks Through Euclidean Distance-Based Behavioral Profiling

DEFF Research Database (Denmark)

Meng, Weizhi; Li, Wenjuan; Wang, Yu

2017-01-01

and healthcare personnel. The underlying network architecture to support such devices is also referred to as medical smartphone networks (MSNs). Similar to other networks, MSNs also suffer from various attacks like insider attacks (e.g., leakage of sensitive patient information by a malicious insider......). In this work, we focus on MSNs and design a trust-based intrusion detection approach through Euclidean distance-based behavioral profiling to detect malicious devices (or called nodes). In the evaluation, we collaborate with healthcare organizations and implement our approach in a real simulated MSN...

Scaling limits of Euclidean quantum fields

International Nuclear Information System (INIS)

Enss, V.

1981-01-01

The author studies the long-distance and short-distance behaviour of generalized random processes which arise in Euclidean Boson field theories. Among them are Wick-polynomials of free fields and P(PHI) 2 -models. (Auth.)

A Fuzzy Neural Network Based on Non-Euclidean Distance Clustering for Quality Index Model in Slashing Process

Directory of Open Access Journals (Sweden)

Yuxian Zhang

2015-01-01

Full Text Available The quality index model in slashing process is difficult to build by reason of the outliers and noise data from original data. To the above problem, a fuzzy neural network based on non-Euclidean distance clustering is proposed in which the input space is partitioned into many local regions by the fuzzy clustering based on non-Euclidean distance so that the computation complexity is decreased, and fuzzy rule number is determined by validity function based on both the separation and the compactness among clusterings. Then, the premise parameters and consequent parameters are trained by hybrid learning algorithm. The parameters identification is realized; meanwhile the convergence condition of consequent parameters is obtained by Lyapunov function. Finally, the proposed method is applied to build the quality index model in slashing process in which the experimental data come from the actual slashing process. The experiment results show that the proposed fuzzy neural network for quality index model has lower computation complexity and faster convergence time, comparing with GP-FNN, BPNN, and RBFNN.

Transformational plane geometry

CERN Document Server

Umble, Ronald N

2014-01-01

Axioms of Euclidean Plane Geometry The Existence and Incidence Postulates The Distance and Ruler Postulates The Plane Separation Postulate The Protractor Postulate The Side-Angle-Side Postulate and the Euclidean Parallel Postulate Theorems of Euclidean Plane Geometry The Exterior Angle Theorem Triangle Congruence Theorems The Alternate Interior Angles Theorem and the Angle Sum Theorem Similar Triangles Introduction to Transformations, Isometries, and Similarities Transformations Isometries and SimilaritiesAppendix: Proof of Surjectivity Translations, Rotations, and Reflections Translations Rotations Reflections Appendix: Geometer's Sketchpad Commands Required by Exploratory Activities Compositions of Translations, Rotations, and Reflections The Three Points Theorem Rotations as Compositions of Two Reflections Translations as Compositions of Two Halfturns or Two Reflections The Angle Addition Theorem Glide Reflections Classification of Isometries The Fundamental Theorem and Congruence Classification of Isometr...

Texture classification using non-Euclidean Minkowski dilation

Science.gov (United States)

Florindo, Joao B.; Bruno, Odemir M.

2018-03-01

This study presents a new method to extract meaningful descriptors of gray-scale texture images using Minkowski morphological dilation based on the Lp metric. The proposed approach is motivated by the success previously achieved by Bouligand-Minkowski fractal descriptors on texture classification. In essence, such descriptors are directly derived from the morphological dilation of a three-dimensional representation of the gray-level pixels using the classical Euclidean metric. In this way, we generalize the dilation for different values of p in the Lp metric (Euclidean is a particular case when p = 2) and obtain the descriptors from the cumulated distribution of the distance transform computed over the texture image. The proposed method is compared to other state-of-the-art approaches (such as local binary patterns and textons for example) in the classification of two benchmark data sets (UIUC and Outex). The proposed descriptors outperformed all the other approaches in terms of rate of images correctly classified. The interesting results suggest the potential of these descriptors in this type of task, with a wide range of possible applications to real-world problems.

Learning Euclidean Embeddings for Indexing and Classification

National Research Council Canada - National Science Library

Athitsos, Vassilis; Alon, Joni; Sclaroff, Stan; Kollios, George

2004-01-01

BoostMap is a recently proposed method for efficient approximate nearest neighbor retrieval in arbitrary non-Euclidean spaces with computationally expensive and possibly non-metric distance measures...

MEDOF - MINIMUM EUCLIDEAN DISTANCE OPTIMAL FILTER

Science.gov (United States)

Barton, R. S.

1994-01-01

The Minimum Euclidean Distance Optimal Filter program, MEDOF, generates filters for use in optical correlators. The algorithm implemented in MEDOF follows theory put forth by Richard D. Juday of NASA/JSC. This program analytically optimizes filters on arbitrary spatial light modulators such as coupled, binary, full complex, and fractional 2pi phase. MEDOF optimizes these modulators on a number of metrics including: correlation peak intensity at the origin for the centered appearance of the reference image in the input plane, signal to noise ratio including the correlation detector noise as well as the colored additive input noise, peak to correlation energy defined as the fraction of the signal energy passed by the filter that shows up in the correlation spot, and the peak to total energy which is a generalization of PCE that adds the passed colored input noise to the input image's passed energy. The user of MEDOF supplies the functions that describe the following quantities: 1) the reference signal, 2) the realizable complex encodings of both the input and filter SLM, 3) the noise model, possibly colored, as it adds at the reference image and at the correlation detection plane, and 4) the metric to analyze, here taken to be one of the analytical ones like SNR (signal to noise ratio) or PCE (peak to correlation energy) rather than peak to secondary ratio. MEDOF calculates filters for arbitrary modulators and a wide range of metrics as described above. MEDOF examines the statistics of the encoded input image's noise (if SNR or PCE is selected) and the filter SLM's (Spatial Light Modulator) available values. These statistics are used as the basis of a range for searching for the magnitude and phase of k, a pragmatically based complex constant for computing the filter transmittance from the electric field. The filter is produced for the mesh points in those ranges and the value of the metric that results from these points is computed. When the search is concluded, the

Assessment of the Log-Euclidean Metric Performance in Diffusion Tensor Image Segmentation

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Mostafa Charmi

2010-06-01

Full Text Available Introduction: Appropriate definition of the distance measure between diffusion tensors has a deep impact on Diffusion Tensor Image (DTI segmentation results. The geodesic metric is the best distance measure since it yields high-quality segmentation results. However, the important problem with the geodesic metric is a high computational cost of the algorithms based on it. The main goal of this paper is to assess the possible substitution of the geodesic metric with the Log-Euclidean one to reduce the computational cost of a statistical surface evolution algorithm. Materials and Methods: We incorporated the Log-Euclidean metric in the statistical surface evolution algorithm framework. To achieve this goal, the statistics and gradients of diffusion tensor images were defined using the Log-Euclidean metric. Numerical implementation of the segmentation algorithm was performed in the MATLAB software using the finite difference techniques. Results: In the statistical surface evolution framework, the Log-Euclidean metric was able to discriminate the torus and helix patterns in synthesis datasets and rat spinal cords in biological phantom datasets from the background better than the Euclidean and J-divergence metrics. In addition, similar results were obtained with the geodesic metric. However, the main advantage of the Log-Euclidean metric over the geodesic metric was the dramatic reduction of computational cost of the segmentation algorithm, at least by 70 times. Discussion and Conclusion: The qualitative and quantitative results have shown that the Log-Euclidean metric is a good substitute for the geodesic metric when using a statistical surface evolution algorithm in DTIs segmentation.

Uniform Page Migration Problem in Euclidean Space

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Amanj Khorramian

2016-08-01

Full Text Available The page migration problem in Euclidean space is revisited. In this problem, online requests occur at any location to access a single page located at a server. Every request must be served, and the server has the choice to migrate from its current location to a new location in space. Each service costs the Euclidean distance between the server and request. A migration costs the distance between the former and the new server location, multiplied by the page size. We study the problem in the uniform model, in which the page has size D = 1 . All request locations are not known in advance; however, they are sequentially presented in an online fashion. We design a 2.75 -competitive online algorithm that improves the current best upper bound for the problem with the unit page size. We also provide a lower bound of 2.732 for our algorithm. It was already known that 2.5 is a lower bound for this problem.

Modelling non-Euclidean movement and landscape connectivity in highly structured ecological networks

Science.gov (United States)

Sutherland, Christopher; Fuller, Angela K.; Royle, J. Andrew

2015-01-01

Movement is influenced by landscape structure, configuration and geometry, but measuring distance as perceived by animals poses technical and logistical challenges. Instead, movement is typically measured using Euclidean distance, irrespective of location or landscape structure, or is based on arbitrary cost surfaces. A recently proposed extension of spatial capture-recapture (SCR) models resolves this issue using spatial encounter histories of individuals to calculate least-cost paths (ecological distance: Ecology, 94, 2013, 287) thereby relaxing the Euclidean assumption. We evaluate the consequences of not accounting for movement heterogeneity when estimating abundance in highly structured landscapes, and demonstrate the value of this approach for estimating biologically realistic space-use patterns and landscape connectivity.

Improvement in quality testing of Braille printer output with Euclidean ...

African Journals Online (AJOL)

This paper focuses on quality testing of Braille printed paper using calibrated camera by detecting dots and measuring the Euclidean distances between them with equal gap, vertically and horizontally. For higher accuracy, camera calibration is essential to observe a planar checker board pattern from different distances and ...

Euclidean distance geometry an introduction

CERN Document Server

Liberti, Leo

2017-01-01

This textbook, the first of its kind, presents the fundamentals of distance geometry:  theory, useful methodologies for obtaining solutions, and real world applications. Concise proofs are given and step-by-step algorithms for solving fundamental problems efficiently and precisely are presented in Mathematica®, enabling the reader to experiment with concepts and methods as they are introduced. Descriptive graphics, examples, and problems, accompany the real gems of the text, namely the applications in visualization of graphs, localization of sensor networks, protein conformation from distance data, clock synchronization protocols, robotics, and control of unmanned underwater vehicles, to name several.  Aimed at intermediate undergraduates, beginning graduate students, researchers, and practitioners, the reader with a basic knowledge of linear algebra will gain an understanding of the basic theories of distance geometry and why they work in real life.

Broadband invisibility by non-Euclidean cloaking.

Science.gov (United States)

Leonhardt, Ulf; Tyc, Tomás

2009-01-02

Invisibility and negative refraction are both applications of transformation optics where the material of a device performs a coordinate transformation for electromagnetic fields. The device creates the illusion that light propagates through empty flat space, whereas in physical space, light is bent around a hidden interior or seems to run backward in space or time. All of the previous proposals for invisibility require materials with extreme properties. Here we show that transformation optics of a curved, non-Euclidean space (such as the surface of a virtual sphere) relax these requirements and can lead to invisibility in a broad band of the spectrum.

Large parallel volumes of finite and compact sets in d-dimensional Euclidean space

DEFF Research Database (Denmark)

Kampf, Jürgen; Kiderlen, Markus

The r-parallel volume V (Cr) of a compact subset C in d-dimensional Euclidean space is the volume of the set Cr of all points of Euclidean distance at most r > 0 from C. According to Steiner’s formula, V (Cr) is a polynomial in r when C is convex. For finite sets C satisfying a certain geometric...

An adaptive distance measure for use with nonparametric models

International Nuclear Information System (INIS)

Garvey, D. R.; Hines, J. W.

2006-01-01

Distance measures perform a critical task in nonparametric, locally weighted regression. Locally weighted regression (LWR) models are a form of 'lazy learning' which construct a local model 'on the fly' by comparing a query vector to historical, exemplar vectors according to a three step process. First, the distance of the query vector to each of the exemplar vectors is calculated. Next, these distances are passed to a kernel function, which converts the distances to similarities or weights. Finally, the model output or response is calculated by performing locally weighted polynomial regression. To date, traditional distance measures, such as the Euclidean, weighted Euclidean, and L1-norm have been used as the first step in the prediction process. Since these measures do not take into consideration sensor failures and drift, they are inherently ill-suited for application to 'real world' systems. This paper describes one such LWR model, namely auto associative kernel regression (AAKR), and describes a new, Adaptive Euclidean distance measure that can be used to dynamically compensate for faulty sensor inputs. In this new distance measure, the query observations that lie outside of the training range (i.e. outside the minimum and maximum input exemplars) are dropped from the distance calculation. This allows for the distance calculation to be robust to sensor drifts and failures, in addition to providing a method for managing inputs that exceed the training range. In this paper, AAKR models using the standard and Adaptive Euclidean distance are developed and compared for the pressure system of an operating nuclear power plant. It is shown that using the standard Euclidean distance for data with failed inputs, significant errors in the AAKR predictions can result. By using the Adaptive Euclidean distance it is shown that high fidelity predictions are possible, in spite of the input failure. In fact, it is shown that with the Adaptive Euclidean distance prediction

Generalized Distance Transforms and Skeletons in Graphics Hardware

NARCIS (Netherlands)

Strzodka, R.; Telea, A.

2004-01-01

We present a framework for computing generalized distance transforms and skeletons of two-dimensional objects using graphics hardware. Our method is based on the concept of footprint splatting. Combining different splats produces weighted distance transforms for different metrics, as well as the

Intrinsic Regularization in a Lorentz invariant non-orthogonal Euclidean Space

OpenAIRE

Tornow, Carmen

2006-01-01

It is shown that the Lorentz transformations can be derived for a non-orthogonal Euclidean space. In this geometry one finds the same relations of special relativity as the ones known from the orthogonal Minkowski space. In order to illustrate the advantage of a non-orthogonal Euclidean metric the two-point Green’s function at x = 0 for a self-interacting scalar field is calculated. In contrast to the Minkowski space the one loop mass correction derived from this function gives a convergent r...

Products of Snowflaked Euclidean Lines Are Not Minimal for Looking Down

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Joseph Matthieu

2017-11-01

Full Text Available We show that products of snowflaked Euclidean lines are not minimal for looking down. This question was raised in Fractured fractals and broken dreams, Problem 11.17, by David and Semmes. The proof uses arguments developed by Le Donne, Li and Rajala to prove that the Heisenberg group is not minimal for looking down. By a method of shortcuts, we define a new distance d such that the product of snowflaked Euclidean lines looks down on (RN , d, but not vice versa.

Dynamic hyperbolic geometry: building intuition and understanding mediated by a Euclidean model

Science.gov (United States)

Moreno-Armella, Luis; Brady, Corey; Elizondo-Ramirez, Rubén

2018-05-01

This paper explores a deep transformation in mathematical epistemology and its consequences for teaching and learning. With the advent of non-Euclidean geometries, direct, iconic correspondences between physical space and the deductive structures of mathematical inquiry were broken. For non-Euclidean ideas even to become thinkable the mathematical community needed to accumulate over twenty centuries of reflection and effort: a precious instance of distributed intelligence at the cultural level. In geometry education after this crisis, relations between intuitions and geometrical reasoning must be established philosophically, rather than taken for granted. One approach seeks intuitive supports only for Euclidean explorations, viewing non-Euclidean inquiry as fundamentally non-intuitive in nature. We argue for moving beyond such an impoverished approach, using dynamic geometry environments to develop new intuitions even in the extremely challenging setting of hyperbolic geometry. Our efforts reverse the typical direction, using formal structures as a source for a new family of intuitions that emerge from exploring a digital model of hyperbolic geometry. This digital model is elaborated within a Euclidean dynamic geometry environment, enabling a conceptual dance that re-configures Euclidean knowledge as a support for building intuitions in hyperbolic space-intuitions based not directly on physical experience but on analogies extending Euclidean concepts.

Transforming distance education curricula through distributive leadership

Directory of Open Access Journals (Sweden)

Mike Keppell

2010-12-01

Full Text Available This paper examines a core leadership strategy for transforming learning and teaching in distance education through flexible and blended learning. It focuses on a project centred on distributive leadership that involves collaboration, shared purpose, responsibility and recognition of leadership irrespective of role or position within an organisation. Distributive leadership was a core principle in facilitating the transformation of learning and teaching through a Teaching Fellowship Scheme that empowered leaders across a regional distance education university. In parallel, a design-based research project analysed the perceptions of the Teaching Fellows in relation to blended learning, time/space, peer learning, innovation and equity issues in relation to distance education.

Asymptotic analysis of fundamental solutions of Dirac operators on even dimensional Euclidean spaces

International Nuclear Information System (INIS)

Arai, A.

1985-01-01

We analyze the short distance asymptotic behavior of some quantities formed out of fundamental solutions of Dirac operators on even dimensional Euclidean spaces with finite dimensional matrix-valued potentials. (orig.)

Multivariate Welch t-test on distances

OpenAIRE

Alekseyenko, Alexander V.

2016-01-01

Motivation: Permutational non-Euclidean analysis of variance, PERMANOVA, is routinely used in exploratory analysis of multivariate datasets to draw conclusions about the significance of patterns visualized through dimension reduction. This method recognizes that pairwise distance matrix between observations is sufficient to compute within and between group sums of squares necessary to form the (pseudo) F statistic. Moreover, not only Euclidean, but arbitrary distances can be used. This method...

Euclidean supergravity

Science.gov (United States)

de Wit, Bernard; Reys, Valentin

2017-12-01

Supergravity with eight supercharges in a four-dimensional Euclidean space is constructed at the full non-linear level by performing an off-shell time-like reduction of five-dimensional supergravity. The resulting four-dimensional theory is realized off-shell with the Weyl, vector and tensor supermultiplets and a corresponding multiplet calculus. Hypermultiplets are included as well, but they are themselves only realized with on-shell supersymmetry. We also briefly discuss the non-linear supermultiplet. The off-shell reduction leads to a full understanding of the Euclidean theory. A complete multiplet calculus is presented along the lines of the Minkowskian theory. Unlike in Minkowski space, chiral and anti-chiral multiplets are real and supersymmetric actions are generally unbounded from below. Precisely as in the Minkowski case, where one has different formulations of Poincaré supergravity upon introducing different compensating supermultiplets, one can also obtain different versions of Euclidean supergravity.

Clustering by Partitioning around Medoids using Distance-Based ...

African Journals Online (AJOL)

OLUWASOGO

outperforms both the Euclidean and Manhattan distance metrics in certain situations. KEYWORDS: PAM ... version of a dataset, compare the quality of clusters obtained from the Euclidean .... B. Theoretical Framework and Methodology.

Optimized curve design for image analysis using localized geodesic distance transformations

Science.gov (United States)

Braithwaite, Billy; Niska, Harri; Pöllänen, Irene; Ikonen, Tiia; Haataja, Keijo; Toivanen, Pekka; Tolonen, Teemu

2015-03-01

We consider geodesic distance transformations for digital images. Given a M × N digital image, a distance image is produced by evaluating local pixel distances. Distance Transformation on Curved Space (DTOCS) evaluates shortest geodesics of a given pixel neighborhood by evaluating the height displacements between pixels. In this paper, we propose an optimization framework for geodesic distance transformations in a pattern recognition scheme, yielding more accurate machine learning based image analysis, exemplifying initial experiments using complex breast cancer images. Furthermore, we will outline future research work, which will complete the research work done for this paper.

TOPSIS with statistical distances: A new approach to MADM

Directory of Open Access Journals (Sweden)

Vijaya Babu Vommi

2017-01-01

Full Text Available Multiple attribute decision making (MADM methods are very useful in choosing the best alternative among the available finite but conflicting alternatives. TOPSIS is one of the MADM methods, which is simple in its methodology and logic. In TOPSIS, Euclidean distances of each alternative from the positive and negative ideal solutions are utilized to find the best alternative. In literature, apart from Euclidean distances, the city block distances have also been tried to find the separations measures. In general, the attribute data are distributed with unequal ranges and also possess moderate to high correlations. Hence, in the present paper, use of statistical distances is proposed in place of Euclidean distances. Procedures to find the best alternatives are developed using statistical and weighted statistical distances respectively. The proposed methods are illustrated with some industrial problems taken from literature. Results show that the proposed methods can be used as new alternatives in MADM for choosing the best solutions.

A ROBUST METHOD FOR STEREO VISUAL ODOMETRY BASED ON MULTIPLE EUCLIDEAN DISTANCE CONSTRAINT AND RANSAC ALGORITHM

Directory of Open Access Journals (Sweden)

Q. Zhou

2017-07-01

Full Text Available Visual Odometry (VO is a critical component for planetary robot navigation and safety. It estimates the ego-motion using stereo images frame by frame. Feature points extraction and matching is one of the key steps for robotic motion estimation which largely influences the precision and robustness. In this work, we choose the Oriented FAST and Rotated BRIEF (ORB features by considering both accuracy and speed issues. For more robustness in challenging environment e.g., rough terrain or planetary surface, this paper presents a robust outliers elimination method based on Euclidean Distance Constraint (EDC and Random Sample Consensus (RANSAC algorithm. In the matching process, a set of ORB feature points are extracted from the current left and right synchronous images and the Brute Force (BF matcher is used to find the correspondences between the two images for the Space Intersection. Then the EDC and RANSAC algorithms are carried out to eliminate mismatches whose distances are beyond a predefined threshold. Similarly, when the left image of the next time matches the feature points with the current left images, the EDC and RANSAC are iteratively performed. After the above mentioned, there are exceptional remaining mismatched points in some cases, for which the third time RANSAC is applied to eliminate the effects of those outliers in the estimation of the ego-motion parameters (Interior Orientation and Exterior Orientation. The proposed approach has been tested on a real-world vehicle dataset and the result benefits from its high robustness.

Statistical 2D and 3D shape analysis using Non-Euclidean Metrics

DEFF Research Database (Denmark)

Larsen, Rasmus; Hilger, Klaus Baggesen; Wrobel, Mark Christoph

2002-01-01

We address the problem of extracting meaningful, uncorrelated biological modes of variation from tangent space shape coordinates in 2D and 3D using non-Euclidean metrics. We adapt the maximum autocorrelation factor analysis and the minimum noise fraction transform to shape decomposition. Furtherm......We address the problem of extracting meaningful, uncorrelated biological modes of variation from tangent space shape coordinates in 2D and 3D using non-Euclidean metrics. We adapt the maximum autocorrelation factor analysis and the minimum noise fraction transform to shape decomposition....... Furthermore, we study metrics based on repated annotations of a training set. We define a way of assessing the correlation between landmarks contrary to landmark coordinates. Finally, we apply the proposed methods to a 2D data set consisting of outlines of lungs and a 3D/(4D) data set consisting of sets...

Stereo matching using epipolar distance transform.

Science.gov (United States)

Yang, Qingxiong; Ahuja, Narendra

2012-10-01

In this paper, we propose a simple but effective image transform, called the epipolar distance transform, for matching low-texture regions. It converts image intensity values to a relative location inside a planar segment along the epipolar line, such that pixels in the low-texture regions become distinguishable. We theoretically prove that the transform is affine invariant, thus the transformed images can be directly used for stereo matching. Any existing stereo algorithms can be directly used with the transformed images to improve reconstruction accuracy for low-texture regions. Results on real indoor and outdoor images demonstrate the effectiveness of the proposed transform for matching low-texture regions, keypoint detection, and description for low-texture scenes. Our experimental results on Middlebury images also demonstrate the robustness of our transform for highly textured scenes. The proposed transform has a great advantage, its low computational complexity. It was tested on a MacBook Air laptop computer with a 1.8 GHz Core i7 processor, with a speed of about 9 frames per second for a video graphics array-sized image.

Postoperative radiotherapy for glioma: improved delineation of the clinical target volume using the geodesic distance calculation.

Directory of Open Access Journals (Sweden)

DanFang Yan

Full Text Available OBJECTS: To introduce a new method for generating the clinical target volume (CTV from gross tumor volume (GTV using the geodesic distance calculation for glioma. METHODS: One glioblastoma patient was enrolled. The GTV and natural barriers were contoured on each slice of the computer tomography (CT simulation images. Then, a graphic processing unit based on a parallel Euclidean distance transform was used to generate the CTV considering natural barriers. Three-dimensional (3D visualization technique was applied to show the delineation results. Speed of operation and precision were compared between this new delineation method and the traditional method. RESULTS: In considering spatial barriers, the shortest distance from the point sheltered from these barriers equals the sum of the distance along the shortest path between the two points; this consists of several segments and evades the spatial barriers, rather than being the direct Euclidean distance between two points. The CTV was generated irregularly rather than as a spherical shape. The time required to generate the CTV was greatly reduced. Moreover, this new method improved inter- and intra-observer variability in defining the CTV. CONCLUSIONS: Compared with the traditional CTV delineation, this new method using geodesic distance calculation not only greatly shortens the time to modify the CTV, but also has better reproducibility.

Optimal recovery of linear operators in non-Euclidean metrics

Energy Technology Data Exchange (ETDEWEB)

Osipenko, K Yu [Moscow State Aviation Technological University, Moscow (Russian Federation)

2014-10-31

The paper looks at problems concerning the recovery of operators from noisy information in non-Euclidean metrics. A number of general theorems are proved and applied to recovery problems for functions and their derivatives from the noisy Fourier transform. In some cases, a family of optimal methods is found, from which the methods requiring the least amount of original information are singled out. Bibliography: 25 titles.

Non-euclidean simplex optimization

International Nuclear Information System (INIS)

Silver, G.L.

1977-01-01

Geometric optimization techniques useful for studying chemical equilibrium traditionally rely upon principles of euclidean geometry, but such algorithms may also be based upon principles of a non-euclidean geometry. The sequential simplex method is adapted to the hyperbolic plane, and application of optimization to problems such as the potentiometric titration of plutonium is suggested

Spacetime and Euclidean geometry

Science.gov (United States)

Brill, Dieter; Jacobson, Ted

2006-04-01

Using only the principle of relativity and Euclidean geometry we show in this pedagogical article that the square of proper time or length in a two-dimensional spacetime diagram is proportional to the Euclidean area of the corresponding causal domain. We use this relation to derive the Minkowski line element by two geometric proofs of the spacetime Pythagoras theorem.

Shape anisotropy: tensor distance to anisotropy measure

Science.gov (United States)

Weldeselassie, Yonas T.; El-Hilo, Saba; Atkins, M. S.

2011-03-01

Fractional anisotropy, defined as the distance of a diffusion tensor from its closest isotropic tensor, has been extensively studied as quantitative anisotropy measure for diffusion tensor magnetic resonance images (DT-MRI). It has been used to reveal the white matter profile of brain images, as guiding feature for seeding and stopping in fiber tractography and for the diagnosis and assessment of degenerative brain diseases. Despite its extensive use in DT-MRI community, however, not much attention has been given to the mathematical correctness of its derivation from diffusion tensors which is achieved using Euclidean dot product in 9D space. But, recent progress in DT-MRI has shown that the space of diffusion tensors does not form a Euclidean vector space and thus Euclidean dot product is not appropriate for tensors. In this paper, we propose a novel and robust rotationally invariant diffusion anisotropy measure derived using the recently proposed Log-Euclidean and J-divergence tensor distance measures. An interesting finding of our work is that given a diffusion tensor, its closest isotropic tensor is different for different tensor distance metrics used. We demonstrate qualitatively that our new anisotropy measure reveals superior white matter profile of DT-MR brain images and analytically show that it has a higher signal to noise ratio than fractional anisotropy.

A Streaming Distance Transform Algorithm for Neighborhood-Sequence Distances

Directory of Open Access Journals (Sweden)

Nicolas Normand

2014-09-01

Full Text Available We describe an algorithm that computes a “translated” 2D Neighborhood-Sequence Distance Transform (DT using a look up table approach. It requires a single raster scan of the input image and produces one line of output for every line of input. The neighborhood sequence is specified either by providing one period of some integer periodic sequence or by providing the rate of appearance of neighborhoods. The full algorithm optionally derives the regular (centered DT from the “translated” DT, providing the result image on-the-fly, with a minimal delay, before the input image is fully processed. Its efficiency can benefit all applications that use neighborhood- sequence distances, particularly when pipelined processing architectures are involved, or when the size of objects in the source image is limited.

Extended supersymmetry in four-dimensional Euclidean space

International Nuclear Information System (INIS)

McKeon, D.G.C.; Sherry, T.N.

2000-01-01

Since the generators of the two SU(2) groups which comprise SO(4) are not Hermitian conjugates of each other, the simplest supersymmetry algebra in four-dimensional Euclidean space more closely resembles the N=2 than the N=1 supersymmetry algebra in four-dimensional Minkowski space. An extended supersymmetry algebra in four-dimensional Euclidean space is considered in this paper; its structure resembles that of N=4 supersymmetry in four-dimensional Minkowski space. The relationship of this algebra to the algebra found by dimensionally reducing the N=1 supersymmetry algebra in ten-dimensional Euclidean space to four-dimensional Euclidean space is examined. The dimensional reduction of N=1 super Yang-Mills theory in ten-dimensional Minkowski space to four-dimensional Euclidean space is also considered

Lie sphere transformations and the focal sets of hyper-surfaces

International Nuclear Information System (INIS)

Buyske, S.G.

1988-01-01

Isoparametric hypersurfaces of euclidean or spherical space are those with constant principal curvatures. The image of the hypersurface under a conformal transformation of the ambient space will no longer be isoparametric, but will be Dupin: the principal curvatures will be constant in the principal directions. Dupin hypersurfaces are closely related to taut hypersurfaces, for which almost every distance function is a perfect Morse function (the number of critical points is the minimum for the topology of the hypersurface). A weaker concept is tightness, for which almost every linear height function is required to be a perfect Morse function. Dupin and taut hypersurfaces are preserved not just under conformal, or Moebuius, transformations but also under the more general Lie sphere transformations. Roughly speaking, these are generated by Moebius transformations and parallel transformations. The purpose of this thesis is to study certain taut or Dupin hypersurfaces under Lie sphere transformations including the effect on the focal set. The thesis is divided into four sections. After the introduction, the method of studying hypersurfaces as Lie sphere objects is developed. The third section extends the concepts of tightness and tautness of semi-euclidean space. The final section shows that if a hypersurface is the Lie sphere image of certain standard constructions (tubes, cylinders, and rotations), the resulting family of curvature spheres is taut in the Lie quadric

Reduction of product platform complexity by vectorial Euclidean algorithm

International Nuclear Information System (INIS)

Navarrete, Israel Aguilera; Guzman, Alejandro A. Lozano

2013-01-01

In traditional machine, equipment and devices design, technical solutions are practically independent, thus increasing designs cost and complexity. Overcoming this situation has been tackled just using designer's experience. In this work, a product platform complexity reduction is presented based on a matrix representation of technical solutions versus product properties. This matrix represents the product platform. From this matrix, the Euclidean distances among technical solutions are obtained. Thus, the vectorial distances among technical solutions are identified in a new matrix of order of the number of technical solutions identified. This new matrix can be reorganized in groups with a hierarchical structure, in such a way that modular design of products is now more tractable. As a result of this procedure, the minimum vector distances are found thus being possible to identify the best technical solutions for the design problem raised. Application of these concepts is shown with two examples.

Measuring the Accuracy of Simple Evolving Connectionist System with Varying Distance Formulas

Science.gov (United States)

Al-Khowarizmi; Sitompul, O. S.; Suherman; Nababan, E. B.

2017-12-01

Simple Evolving Connectionist System (SECoS) is a minimal implementation of Evolving Connectionist Systems (ECoS) in artificial neural networks. The three-layer network architecture of the SECoS could be built based on the given input. In this study, the activation value for the SECoS learning process, which is commonly calculated using normalized Hamming distance, is also calculated using normalized Manhattan distance and normalized Euclidean distance in order to compare the smallest error value and best learning rate obtained. The accuracy of measurement resulted by the three distance formulas are calculated using mean absolute percentage error. In the training phase with several parameters, such as sensitivity threshold, error threshold, first learning rate, and second learning rate, it was found that normalized Euclidean distance is more accurate than both normalized Hamming distance and normalized Manhattan distance. In the case of beta fibrinogen gene -455 G/A polymorphism patients used as training data, the highest mean absolute percentage error value is obtained with normalized Manhattan distance compared to normalized Euclidean distance and normalized Hamming distance. However, the differences are very small that it can be concluded that the three distance formulas used in SECoS do not have a significant effect on the accuracy of the training results.

Ideas of space. Euclidean, non-Euclidean and relativistic

Energy Technology Data Exchange (ETDEWEB)

Gray, J

1979-01-01

An historical and chronological account of mathematics is presented in which familiarity with simple equations and elements of trigonometry is needed but no specialist knowledge is assumed although difficult problems are discussed. By discussion of the difficulties and confusions it is hoped to understand mathematics as a dynamic activity. Beginning with early Greek mathematics, the Eastern legacy and the transition to deductive and geometric thinking the problem of parallels is then encountered and discussed. The second part of the book takes the story from Wallis, Saccheri and Lambert through to its resolution by Gauss, Lobachevskii, Bolyai, Riemann and Bettrami. The background of the 19th century theory of surfaces is given. The third part gives an account of Einstein's theories based on what has gone before, moving from a Newtonian-Euclidean picture to an Einsteinian-nonEuclidean one. A brief account of gravitation, the nature of space and black holes concludes the book.

On construction of two-dimensional Riemannian manifolds embedded into enveloping Euclidean (pseudo-Euclidean) space

International Nuclear Information System (INIS)

Saveliev, M.V.

1983-01-01

In the framework of the algebraic approach a construction of exactly integrable two-dimensional Riemannian manifolds embedded into enveloping Euclidean (pseudo-Euclidean) space Rsub(N) of an arbitrary dimension is presented. The construction is based on a reformulation of the Gauss, Peterson-Codazzi and Ricci equations in the form of a Lax-type representation in two-dimensional space. Here the Lax pair operators take the values in algebra SO(N)

Some Properties of the Distance Function and a Conjecture of De Giorgi

OpenAIRE

Eminenti, Manolo; Mantegazza, Carlo

2003-01-01

We analyse the geometric properties of the high derivatives of the distance function from a submanifold of the Euclidean space. In particular, we show some relations with the second fundamental form and its covariant derivatives of independent interest. As an application we prove a conjecture of Ennio De Giorgi on the evolution of submanifolds of the Euclidean space by the gradient of functionals depending on the derivatives of the distance function.

Minimal Paths in the City Block: Human Performance on Euclidean and Non-Euclidean Traveling Salesperson Problems

Science.gov (United States)

Walwyn, Amy L.; Navarro, Daniel J.

2010-01-01

An experiment is reported comparing human performance on two kinds of visually presented traveling salesperson problems (TSPs), those reliant on Euclidean geometry and those reliant on city block geometry. Across multiple array sizes, human performance was near-optimal in both geometries, but was slightly better in the Euclidean format. Even so,…

Measuring and testing dependence by correlation of distances

OpenAIRE

Székely, Gábor J.; Rizzo, Maria L.; Bakirov, Nail K.

2007-01-01

Distance correlation is a new measure of dependence between random vectors. Distance covariance and distance correlation are analogous to product-moment covariance and correlation, but unlike the classical definition of correlation, distance correlation is zero only if the random vectors are independent. The empirical distance dependence measures are based on certain Euclidean distances between sample elements rather than sample moments, yet have a compact representation analogous to the clas...

Local algebras in Euclidean quantum field theory

International Nuclear Information System (INIS)

Guerra, Francesco.

1975-06-01

The general structure of the local observable algebras of Euclidean quantum field theory is described, considering the very simple examples of the free scalar field, the vector meson field, and the electromagnetic field. The role of Markov properties, and the relations between Euclidean theory and Hamiltonian theory in Minkowski space-time are especially emphasized. No conflict appears between covariance (in the Euclidean sense) and locality (in the Markov sense) on one hand and positive definiteness of the metric on the other hand [fr

Characterization of separability and entanglement in (2xD)- and (3xD)-dimensional systems by single-qubit and single-qutrit unitary transformations

International Nuclear Information System (INIS)

Giampaolo, Salvatore M.; Illuminati, Fabrizio

2007-01-01

We investigate the geometric characterization of pure state bipartite entanglement of (2xD)- and (3xD)-dimensional composite quantum systems. To this aim, we analyze the relationship between states and their images under the action of particular classes of local unitary operations. We find that invariance of states under the action of single-qubit and single-qutrit transformations is a necessary and sufficient condition for separability. We demonstrate that in the (2xD)-dimensional case the von Neumann entropy of entanglement is a monotonic function of the minimum squared Euclidean distance between states and their images over the set of single qubit unitary transformations. Moreover, both in the (2xD)- and in the (3xD)-dimensional cases the minimum squared Euclidean distance exactly coincides with the linear entropy [and thus as well with the tangle measure of entanglement in the (2xD)-dimensional case]. These results provide a geometric characterization of entanglement measures originally established in informational frameworks. Consequences and applications of the formalism to quantum critical phenomena in spin systems are discussed

Euclidean supersymmetry, twisting and topological sigma models

International Nuclear Information System (INIS)

Hull, C.M.; Lindstroem, U.; Santos, L. Melo dos; Zabzine, M.; Unge, R. von

2008-01-01

We discuss two dimensional N-extended supersymmetry in Euclidean signature and its R-symmetry. For N = 2, the R-symmetry is SO(2) x SO(1, 1), so that only an A-twist is possible. To formulate a B-twist, or to construct Euclidean N = 2 models with H-flux so that the target geometry is generalised Kahler, it is necessary to work with a complexification of the sigma models. These issues are related to the obstructions to the existence of non-trivial twisted chiral superfields in Euclidean superspace.

Properties of octagonal distance transformation (ODT) and its application to recognition of rib images of chest radiograms

International Nuclear Information System (INIS)

Ban, Tatsuya; Yokoi, Shigeki; Toriwaki, Jun-ichiro; Fukumura, Teruo.

1980-01-01

Digital image processing and image pattern recognition have lately become important, and are utilized in every field. The processing techniques common to these applications include smoothing, thinning, threshold processing, distance transformation, edge detection, etc. This paper describes the distance transformation, specifically the transformation based on octagonal distance (ODT). As the distance transformation, diamond distance or square distance has been employed so far, but these have the disadvantage of great deviation from the Euclid distance, and the octagonal distance transformation is considered to prevent such deviation. First, the basic concept and the definition of symbols are given, the octagonal distance skeleton (ODS) is defined, and the possibility of restoring original figure from the ODS is indicated. Next, the sequential algorithm is given, which executes the ODT and the inverse transformation to restore the original figure from the ODS by scanning on the figure 4 times. As an example of the application, the identification of rib images in chest radiograms is adopted, and the capability of reducing the effect of blood vessel images and noises by combining ODT with thinning or other processing, without quadratic function approximation, is described. (J.P.N.)

Founding Gravitation in 4D Euclidean Space-Time Geometry

International Nuclear Information System (INIS)

Winkler, Franz-Guenter

2010-01-01

The Euclidean interpretation of special relativity which has been suggested by the author is a formulation of special relativity in ordinary 4D Euclidean space-time geometry. The natural and geometrically intuitive generalization of this view involves variations of the speed of light (depending on location and direction) and a Euclidean principle of general covariance. In this article, a gravitation model by Jan Broekaert, which implements a view of relativity theory in the spirit of Lorentz and Poincare, is reconstructed and shown to fulfill the principles of the Euclidean approach after an appropriate reinterpretation.

Polynomial degree reduction in the discrete L2-norm equals best Euclidean approximation of h-Bézier coefficients

KAUST Repository

Ait-Haddou, Rachid

2015-01-01

We show that the best degree reduction of a given polynomial P from degree n to m with respect to the discrete (Formula presented.)-norm is equivalent to the best Euclidean distance of the vector of h-Bézier coefficients of P from the vector

Constructive curves in non-Euclidean planes

OpenAIRE

Horváth, Ákos G.

2016-01-01

In this paper we overview the theory of conics and roulettes in four non-Euclidean planes. We collect the literature about these classical concepts, from the eighteenth century to the present, including papers available only on arXiv. The comparison of the four non-Euclidean planes, in terms of the known results on conics and roulettes, reflects only the very subjective view of the author.

Spinors in euclidean field theory, complex structures and discrete symmetries

International Nuclear Information System (INIS)

Wetterich, C.

2011-01-01

We discuss fermions for arbitrary dimensions and signature of the metric, with special emphasis on euclidean space. Generalized Majorana spinors are defined for d=2,3,4,8,9mod8, independently of the signature. These objects permit a consistent analytic continuation of Majorana spinors in Minkowski space to euclidean signature. Compatibility of charge conjugation with complex conjugation requires for euclidean signature a new complex structure which involves a reflection in euclidean time. The possible complex structures for Minkowski and euclidean signature can be understood in terms of a modulo two periodicity in the signature. The concepts of a real action and hermitean observables depend on the choice of the complex structure. For a real action the expectation values of all hermitean multi-fermion observables are real. This holds for arbitrary signature, including euclidean space. In particular, a chemical potential is compatible with a real action for the euclidean theory. We also discuss the discrete symmetries of parity, time reversal and charge conjugation for arbitrary dimension and signature.

New Maximal Two-distance Sets

DEFF Research Database (Denmark)

Lisonek, Petr

1996-01-01

A two-distance set in E^d is a point set X inthe d-dimensional Euclidean spacesuch that the distances between distinct points in Xassume only two different non-zero values. Based on results from classical distance geometry, we developan algorithm to classify, for a given dimension, all maximal...... (largest possible)two-distance sets in E^d.Using this algorithm we have completed the full classificationfor all dimensions less than or equal to 7, andwe have found one set in E^8 whosemaximality follows from Blokhuis' upper bound on sizes of s-distance sets.While in the dimensions less than or equal to 6...

Non-euclidean geometry

CERN Document Server

Coxeter, HSM

1965-01-01

This textbook introduces non-Euclidean geometry, and the third edition adds a new chapter, including a description of the two families of 'mid-lines' between two given lines and an elementary derivation of the basic formulae of spherical trigonometry and hyperbolic trigonometry, and other new material.

Long-distance super-resolution imaging assisted by enhanced spatial Fourier transform.

Science.gov (United States)

Tang, Heng-He; Liu, Pu-Kun

2015-09-07

A new gradient-index (GRIN) lens that can realize enhanced spatial Fourier transform (FT) over optically long distances is demonstrated. By using an anisotropic GRIN metamaterial with hyperbolic dispersion, evanescent wave in free space can be transformed into propagating wave in the metamaterial and then focused outside due to negative-refraction. Both the results based on the ray tracing and the finite element simulation show that the spatial frequency bandwidth of the spatial FT can be extended to 2.7k(0) (k(0) is the wave vector in free space). Furthermore, assisted by the enhanced spatial FT, a new long-distance (in the optical far-field region) super-resolution imaging scheme is also proposed and the super resolved capability of λ/5 (λ is the wavelength in free space) is verified. The work may provide technical support for designing new-type high-speed microscopes with long working distances.

UN MODÈLE PLATONICIEN (EUCLIDIEN-PROJECTIF) POUR LA THÉORIE DE LA RELATIVITÉ RESTREINTE A Platonic model (Euclidean-projective) for the special theory of relativity

OpenAIRE

Jégat , Alain

2014-01-01

The usual framework for Einstein’s special theory of relativity is the pseudo-euclidean spacetime proposed by Hermann Minkowski. This article aims at proposing a different model.The framework is an euclidean four-dimensional space in which all the objects move regularly (it means that, between two observations, whatever their trajectories, they cover the same distance), but where the events are seen in projection according to a privileged direction, as we are going to explain. The remark, rat...

Solution for a bipartite Euclidean traveling-salesman problem in one dimension

Science.gov (United States)

Caracciolo, Sergio; Di Gioacchino, Andrea; Gherardi, Marco; Malatesta, Enrico M.

2018-05-01

The traveling-salesman problem is one of the most studied combinatorial optimization problems, because of the simplicity in its statement and the difficulty in its solution. We characterize the optimal cycle for every convex and increasing cost function when the points are thrown independently and with an identical probability distribution in a compact interval. We compute the average optimal cost for every number of points when the distance function is the square of the Euclidean distance. We also show that the average optimal cost is not a self-averaging quantity by explicitly computing the variance of its distribution in the thermodynamic limit. Moreover, we prove that the cost of the optimal cycle is not smaller than twice the cost of the optimal assignment of the same set of points. Interestingly, this bound is saturated in the thermodynamic limit.

Multivariate Welch t-test on distances.

Science.gov (United States)

Alekseyenko, Alexander V

2016-12-01

Permutational non-Euclidean analysis of variance, PERMANOVA, is routinely used in exploratory analysis of multivariate datasets to draw conclusions about the significance of patterns visualized through dimension reduction. This method recognizes that pairwise distance matrix between observations is sufficient to compute within and between group sums of squares necessary to form the (pseudo) F statistic. Moreover, not only Euclidean, but arbitrary distances can be used. This method, however, suffers from loss of power and type I error inflation in the presence of heteroscedasticity and sample size imbalances. We develop a solution in the form of a distance-based Welch t-test, [Formula: see text], for two sample potentially unbalanced and heteroscedastic data. We demonstrate empirically the desirable type I error and power characteristics of the new test. We compare the performance of PERMANOVA and [Formula: see text] in reanalysis of two existing microbiome datasets, where the methodology has originated. The source code for methods and analysis of this article is available at https://github.com/alekseyenko/Tw2 Further guidance on application of these methods can be obtained from the author. alekseye@musc.edu. © The Author 2016. Published by Oxford University Press.

Periodic anti-phases. Long distance antiphase-order transformations (1961); Antiphases periodiques. Transformation antiphase-ordre a grande distance (1961)

Energy Technology Data Exchange (ETDEWEB)

Hauptman, A; Kleinberger, R; Okuzumi, H; Perio, P; Tournarie, M [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

1961-07-01

Periodic anti-phases are ordered structures in which the movable elements alternates regularly between two available sites, in one or two directions. We study in the present work two particular properties of periodic anti-phases : 1- The irrationality or the continuous variation of the periodic anti-phase. 2- The reversible transition between the anti-phase state and that of long distance order. We have calculated the distribution of the diffracted amplitudes for the 'rational statistic' model. They can easily be identified and the two types of diagram observed are presented. For the long distance anti-phase-order transformation, we propose a model in which a domain grows laterally at the expense of the other. Calculation shows that in this case certain order reflections re-appear accompanied by extra satellites whose amplitude is not proportional to that of the pure anti-phase satellites, the opposite of the case of a double diffraction. The irreversible evolution of Au{sub 3}Mn alloys is then described; in this case interactions between domains of different type occur. Finally a diagram for the alloy Au{sub 3}Mn is given; the anti-phase boundaries are made up of 130 planes. (authors) [French] Les antiphases periodiques sont des structures ordonnees dans lesquelles l'element ordonnable alterne regulierement entre deux sites disponibles, suivant une ou deux directions. Nous etudions, dans le travail presente, deux proprietes particulieres des antiphases periodiques: 1- L'irrationalite ou la variation continue de la periode d'antiphase. 2- La transition reversible entre l'etat antiphase et l'etat d'ordre a grande distance. Nous avons calcule la distribution des amplitudes diffractees pour le modele 'rationnel statistique'. Elles sont facilement identifiables et les deux types de diagrammes observes sont presentes. Pour la transformation antiphase-ordre a longue distance, nous proposons un modele de croissance laterale d'un domaine au detriment de l'autre. Le calcul

Biharmonic Submanifolds with Parallel Mean Curvature Vector in Pseudo-Euclidean Spaces

Energy Technology Data Exchange (ETDEWEB)

Fu, Yu, E-mail: yufudufe@gmail.com [Dongbei University of Finance and Economics, School of Mathematics and Quantitative Economics (China)

2013-12-15

In this paper, we investigate biharmonic submanifolds in pseudo-Euclidean spaces with arbitrary index and dimension. We give a complete classification of biharmonic spacelike submanifolds with parallel mean curvature vector in pseudo-Euclidean spaces. We also determine all biharmonic Lorentzian surfaces with parallel mean curvature vector field in pseudo-Euclidean spaces.

Biharmonic Submanifolds with Parallel Mean Curvature Vector in Pseudo-Euclidean Spaces

International Nuclear Information System (INIS)

Fu, Yu

2013-01-01

In this paper, we investigate biharmonic submanifolds in pseudo-Euclidean spaces with arbitrary index and dimension. We give a complete classification of biharmonic spacelike submanifolds with parallel mean curvature vector in pseudo-Euclidean spaces. We also determine all biharmonic Lorentzian surfaces with parallel mean curvature vector field in pseudo-Euclidean spaces

Variational submanifolds of Euclidean spaces

Science.gov (United States)

Krupka, D.; Urban, Z.; Volná, J.

2018-03-01

Systems of ordinary differential equations (or dynamical forms in Lagrangian mechanics), induced by embeddings of smooth fibered manifolds over one-dimensional basis, are considered in the class of variational equations. For a given non-variational system, conditions assuring variationality (the Helmholtz conditions) of the induced system with respect to a submanifold of a Euclidean space are studied, and the problem of existence of these "variational submanifolds" is formulated in general and solved for second-order systems. The variational sequence theory on sheaves of differential forms is employed as a main tool for the analysis of local and global aspects (variationality and variational triviality). The theory is illustrated by examples of holonomic constraints (submanifolds of a configuration Euclidean space) which are variational submanifolds in geometry and mechanics.

Quantum algorithms on Walsh transform and Hamming distance for Boolean functions

Science.gov (United States)

Xie, Zhengwei; Qiu, Daowen; Cai, Guangya

2018-06-01

Walsh spectrum or Walsh transform is an alternative description of Boolean functions. In this paper, we explore quantum algorithms to approximate the absolute value of Walsh transform W_f at a single point z0 (i.e., |W_f(z0)|) for n-variable Boolean functions with probability at least 8/π 2 using the number of O(1/|W_f(z_{0)|ɛ }) queries, promised that the accuracy is ɛ , while the best known classical algorithm requires O(2n) queries. The Hamming distance between Boolean functions is used to study the linearity testing and other important problems. We take advantage of Walsh transform to calculate the Hamming distance between two n-variable Boolean functions f and g using O(1) queries in some cases. Then, we exploit another quantum algorithm which converts computing Hamming distance between two Boolean functions to quantum amplitude estimation (i.e., approximate counting). If Ham(f,g)=t≠0, we can approximately compute Ham( f, g) with probability at least 2/3 by combining our algorithm and {Approx-Count(f,ɛ ) algorithm} using the expected number of Θ( √{N/(\\lfloor ɛ t\\rfloor +1)}+√{t(N-t)}/\\lfloor ɛ t\\rfloor +1) queries, promised that the accuracy is ɛ . Moreover, our algorithm is optimal, while the exact query complexity for the above problem is Θ(N) and the query complexity with the accuracy ɛ is O(1/ɛ 2N/(t+1)) in classical algorithm, where N=2n. Finally, we present three exact quantum query algorithms for two promise problems on Hamming distance using O(1) queries, while any classical deterministic algorithm solving the problem uses Ω(2n) queries.

KM-FCM: A fuzzy clustering optimization algorithm based on Mahalanobis distance

Directory of Open Access Journals (Sweden)

Zhiwen ZU

2018-04-01

Full Text Available The traditional fuzzy clustering algorithm uses Euclidean distance as the similarity criterion, which is disadvantageous to the multidimensional data processing. In order to solve this situation, Mahalanobis distance is used instead of the traditional Euclidean distance, and the optimization of fuzzy clustering algorithm based on Mahalanobis distance is studied to enhance the clustering effect and ability. With making the initialization means by Heuristic search algorithm combined with k-means algorithm, and in terms of the validity function which could automatically adjust the optimal clustering number, an optimization algorithm KM-FCM is proposed. The new algorithm is compared with FCM algorithm, FCM-M algorithm and M-FCM algorithm in three standard data sets. The experimental results show that the KM-FCM algorithm is effective. It has higher clustering accuracy than FCM, FCM-M and M-FCM, recognizing high-dimensional data clustering well. It has global optimization effect, and the clustering number has no need for setting in advance. The new algorithm provides a reference for the optimization of fuzzy clustering algorithm based on Mahalanobis distance.

Fuzzy Euclidean wormholes in de Sitter space

Energy Technology Data Exchange (ETDEWEB)

Chen, Pisin; Hu, Yao-Chieh; Yeom, Dong-han, E-mail: pisinchen@phys.ntu.edu.tw, E-mail: r04244003@ntu.edu.tw, E-mail: innocent.yeom@gmail.com [Leung Center for Cosmology and Particle Astrophysics, National Taiwan University, Taipei 10617, Taiwan (China)

2017-07-01

We investigate Euclidean wormholes in Einstein gravity with a massless scalar field in de Sitter space. Euclidean wormholes are possible due to the analytic continuation of the time as well as complexification of fields, where we need to impose the classicality after the Wick-rotation to the Lorentzian signatures. For some parameters, wormholes are preferred than Hawking-Moss instantons, and hence wormholes can be more fundamental than Hawking-Moss type instantons. Euclidean wormholes can be interpreted in three ways: (1) classical big bounce, (2) either tunneling from a small to a large universe or a creation of a collapsing and an expanding universe from nothing, and (3) either a transition from a contracting to a bouncing phase or a creation of two expanding universes from nothing. These various interpretations shed some light on challenges of singularities. In addition, these will help to understand tensions between various kinds of quantum gravity theories.

The non-Euclidean revolution

CERN Document Server

Trudeau, Richard J

1986-01-01

How unique and definitive is Euclidean geometry in describing the "real" space in which we live? Richard Trudeau confronts the fundamental question of truth and its representation through mathematical models in The Non-Euclidean Revolution. First, the author analyzes geometry in its historical and philosophical setting; second, he examines a revolution every bit as significant as the Copernican revolution in astronomy and the Darwinian revolution in biology; third, on the most speculative level, he questions the possibility of absolute knowledge of the world. Trudeau writes in a lively, entertaining, and highly accessible style. His book provides one of the most stimulating and personal presentations of a struggle with the nature of truth in mathematics and the physical world. A portion of the book won the Pólya Prize, a distinguished award from the Mathematical Association of America. "Trudeau meets the challenge of reaching a broad audience in clever ways...(The book) is a good addition to our literature o...

Euclidean null controllability of perturbed infinite delay systems with ...

African Journals Online (AJOL)

Euclidean null controllability of perturbed infinite delay systems with limited control. ... Open Access DOWNLOAD FULL TEXT ... The results are established by placing conditions on the perturbation function which guarantee that, if the linear control base system is completely Euclidean controllable, then the perturbed system ...

Quaternion analyticity and conformally Kaehlerian structure in Euclidean gravity

International Nuclear Information System (INIS)

Guersey, F.; Chia-Hsiung Tze

1984-01-01

Starting from the fact that the d = 4 Euclidean flat spacetime is conformally related to the Kaehler manifold H 2 xS 2 , we show the Euclidean Schwarzschild metric to be conformally related to another Kaehler manifold M 2 xS 2 with M 2 being conformal to H 2 in two dimensions. Both metrics which are conformally Kaehlerian, are form-invariant under the infinite parameter Fueter group, the Euclidean counterpart of Milne's group of clock regraduation. The associated Einstein's equations translate into Fueter's quaternionic analyticity. The latter leads to an infinite number of local continuity equations. (orig.)

Transformational leadership in the local police in Spain: a leader-follower distance approach.

Science.gov (United States)

Álvarez, Octavio; Lila, Marisol; Tomás, Inés; Castillo, Isabel

2014-01-01

Based on the transformational leadership theory (Bass, 1985), the aim of the present study was to analyze the differences in leadership styles according to the various leading ranks and the organizational follower-leader distance reported by a representative sample of 975 local police members (828 male and 147 female) from Valencian Community (Spain). Results showed differences by rank (p leadership in all the variables examined (transformational-leadership behaviors, transactional-leadership behaviors, laissez-faire behaviors, satisfaction with the leader, extra effort by follower, and perceived leadership effectiveness). By contrast, the least optimal profiles were presented by intendents. Finally, the maximum distance (five ranks) generally yielded the most optimal profiles, whereas the 3-rank distance generally produced the least optimal profiles for all variables examined. Outcomes and practical implications for the workforce dimensioning are also discussed.

On the scaling limits in the Euclidean (quantum) field theory

International Nuclear Information System (INIS)

Gielerak, R.

1983-01-01

The author studies the concept of scaling limits in the context of the constructive field theory. He finds that the domain of attraction of a free massless Euclidean scalar field in the two-dimensional space time contains almost all Euclidean self-interacting models of quantum fields so far constructed. The renormalized scaling limit of the Wick polynomials of several self-interacting Euclidean field theory models are shown to be the same as in the free field theory. (Auth.)

Derivatives, forms and vector fields on the κ-deformed Euclidean space

International Nuclear Information System (INIS)

Dimitrijevic, Marija; Moeller, Lutz; Tsouchnika, Efrossini

2004-01-01

The model of κ-deformed space is an interesting example of a noncommutative space, since it allows a deformed symmetry. In this paper, we present new results concerning different sets of derivatives on the coordinate algebra of κ-deformed Euclidean space. We introduce a differential calculus with two interesting sets of one-forms and higher-order forms. The transformation law of vector fields is constructed in accordance with the transformation behaviour of derivatives. The crucial property of the different derivatives, forms and vector fields is that in an n-dimensional spacetime there are always n of them. This is the key difference with respect to conventional approaches, in which the differential calculus is (n + 1)-dimensional. This work shows that derivative-valued quantities such as derivative-valued vector fields appear in a generic way on noncommutative spaces

A general algorithm for computing distance transforms in linear time

NARCIS (Netherlands)

Meijster, A.; Roerdink, J.B.T.M.; Hesselink, W.H.; Goutsias, J; Vincent, L; Bloomberg, DS

2000-01-01

A new general algorithm fur computing distance transforms of digital images is presented. The algorithm consists of two phases. Both phases consist of two scans, a forward and a backward scan. The first phase scans the image column-wise, while the second phase scans the image row-wise. Since the

Euclidean null controllability of nonlinear infinite delay systems with ...

African Journals Online (AJOL)

Sufficient conditions for the Euclidean null controllability of non-linear delay systems with time varying multiple delays in the control and implicit derivative are derived. If the uncontrolled system is uniformly asymptotically stable and if the control system is controllable, then the non-linear infinite delay system is Euclidean null ...

The Minimum Distance of Graph Codes

DEFF Research Database (Denmark)

Høholdt, Tom; Justesen, Jørn

2011-01-01

We study codes constructed from graphs where the code symbols are associated with the edges and the symbols connected to a given vertex are restricted to be codewords in a component code. In particular we treat such codes from bipartite expander graphs coming from Euclidean planes and other...... geometries. We give results on the minimum distances of the codes....

Modeling Internal Radiation Therapy

NARCIS (Netherlands)

van den Broek, Egon; Schouten, Theo E.; Pellegrini, M.; Fred, A.; Filipe, J.; Gamboa, H.

2011-01-01

A new technique is described to model (internal) radiation therapy. It is founded on morphological processing, in particular distance transforms. Its formal basis is presented as well as its implementation via the Fast Exact Euclidean Distance (FEED) transform. Its use for all variations of internal

Euclidean null controllability of linear systems with delays in state ...

African Journals Online (AJOL)

Sufficient conditions are developed for the Euclidean controllability of linear systems with delay in state and in control. Namely, if the uncontrolled system is uniformly asymptotically stable and the control equation proper, then the control system is Euclidean null controllable. Journal of the Nigerian Association of ...

The relation between Euclidean and Lorentzian 2D quantum gravity

NARCIS (Netherlands)

Ambjørn, J.; Correia, J.; Kristjansen, C.; Loll, R.

1999-01-01

Starting from 2D Euclidean quantum gravity, we show that one recovers 2D Lorentzian quantum gravity by removing all baby universes. Using a peeling procedure to decompose the discrete, triangulated geometries along a one-dimensional path, we explicitly associate with each Euclidean space-time a

Isometric immersions and embeddings of locally Euclidean metrics in R2

International Nuclear Information System (INIS)

Sabitov, I Kh

1999-01-01

This paper deals with the problem of isometric immersions and embeddings of two-dimensional locally Euclidean metrics in the Euclidean plane. We find explicit formulae for the immersions of metrics defined on a simply connected domain and a number of sufficient conditions for the existence of isometric embeddings. In the case when the domain is multiply connected we find necessary conditions for the existence of isometric immersions and classify the cases when the metric admits no isometric immersion in the Euclidean plane

Euclidean geometry and its subgeometries

CERN Document Server

Specht, Edward John; Calkins, Keith G; Rhoads, Donald H

2015-01-01

In this monograph, the authors present a modern development of Euclidean geometry from independent axioms, using up-to-date language and providing detailed proofs. The axioms for incidence, betweenness, and plane separation are close to those of Hilbert. This is the only axiomatic treatment of Euclidean geometry that uses axioms not involving metric notions and that explores congruence and isometries by means of reflection mappings. The authors present thirteen axioms in sequence, proving as many theorems as possible at each stage and, in the process, building up subgeometries, most notably the Pasch and neutral geometries. Standard topics such as the congruence theorems for triangles, embedding the real numbers in a line, and coordinatization of the plane are included, as well as theorems of Pythagoras, Desargues, Pappas, Menelaus, and Ceva. The final chapter covers consistency and independence of axioms, as well as independence of definition properties. There are over 300 exercises; solutions to many of the...

Noncommutative products of Euclidean spaces

Science.gov (United States)

Dubois-Violette, Michel; Landi, Giovanni

2018-05-01

We present natural families of coordinate algebras on noncommutative products of Euclidean spaces R^{N_1} × _R R^{N_2} . These coordinate algebras are quadratic ones associated with an R -matrix which is involutive and satisfies the Yang-Baxter equations. As a consequence, they enjoy a list of nice properties, being regular of finite global dimension. Notably, we have eight-dimensional noncommutative euclidean spaces R4 × _R R4 . Among these, particularly well behaved ones have deformation parameter u \\in S^2 . Quotients include seven spheres S7_u as well as noncommutative quaternionic tori TH_u = S^3 × _u S^3 . There is invariance for an action of {{SU}}(2) × {{SU}}(2) on the torus TH_u in parallel with the action of U(1) × U(1) on a `complex' noncommutative torus T^2_θ which allows one to construct quaternionic toric noncommutative manifolds. Additional classes of solutions are disjoint from the classical case.

Clustering by Partitioning around Medoids using Distance-Based Similarity Measures on Interval-Scaled Variables

Directory of Open Access Journals (Sweden)

D. L. Nkweteyim

2018-03-01

Full Text Available It is reported in this paper, the results of a study of the partitioning around medoids (PAM clustering algorithm applied to four datasets, both standardized and not, and of varying sizes and numbers of clusters. The angular distance proximity measure in addition to the two more traditional proximity measures, namely the Euclidean distance and Manhattan distance, was used to compute object-object similarity. The data used in the study comprise three widely available datasets, and one that was constructed from publicly available climate data. Results replicate some of the well known facts about the PAM algorithm, namely that the quality of the clusters generated tend to be much better for small datasets, that the silhouette value is a good, even if not perfect, guide for the optimal number of clusters to generate, and that human intervention is required to interpret generated clusters. Additionally, results also indicate that the angular distance measure, which traditionally has not been widely used in clustering, outperforms both the Euclidean and Manhattan distance metrics in certain situations.

Non-euclidean simplex optimization. [Application to potentiometric titration of Pu

Energy Technology Data Exchange (ETDEWEB)

Silver, G.L.

1977-08-15

Geometric optimization techniques useful for studying chemical equilibrium traditionally rely upon principles of euclidean geometry, but such algorithms may also be based upon principles of a non-euclidean geometry. The sequential simplex method is adapted to the hyperbolic plane, and application of optimization to problems such as the potentiometric titration of plutonium is suggested.

Growth Modeling of Human Mandibles using Non-Euclidean Metrics

DEFF Research Database (Denmark)

Hilger, Klaus Baggesen; Larsen, Rasmus; Wrobel, Mark

2003-01-01

From a set of 31 three-dimensional CT scans we model the temporal shape and size of the human mandible. Each anatomical structure is represented using 14851 semi-landmarks, and mapped into Procrustes tangent space. Exploratory subspace analyses are performed leading to linear models of mandible...... shape evolution in Procrustes space. The traditional variance analysis results in a one-dimensional growth model. However, working in a non-Euclidean metric results in a multimodal model with uncorrelated modes of biological variation. The applied non-Euclidean metric is governed by the correlation...... structure of the estimated noise in the data. The generative models are compared, and evaluated on the basis of a cross validation study. The new non-Euclidean analysis is completely data driven. It not only gives comparable results w.r.t. to previous studies of the mean modelling error, but in addition...

Distance of Sample Measurement Points to Prototype Catalog Curve

DEFF Research Database (Denmark)

Hjorth, Poul G.; Karamehmedovic, Mirza; Perram, John

2006-01-01

We discuss strategies for comparing discrete data points to a catalog (reference) curve by means of the Euclidean distance from each point to the curve in a pump's head H vs. flow Qdiagram. In particular we find that a method currently in use is inaccurate. We propose several alternatives...

The elements of non-Euclidean geometry

CERN Document Server

Sommerville, D MY

2012-01-01

Renowned for its lucid yet meticulous exposition, this classic allows students to follow the development of non-Euclidean geometry from a fundamental analysis of the concept of parallelism to more advanced topics. 1914 edition. Includes 133 figures.

Non-Euclidean geometry

CERN Document Server

Kulczycki, Stefan

2008-01-01

This accessible approach features two varieties of proofs: stereometric and planimetric, as well as elementary proofs that employ only the simplest properties of the plane. A short history of geometry precedes a systematic exposition of the principles of non-Euclidean geometry.Starting with fundamental assumptions, the author examines the theorems of Hjelmslev, mapping a plane into a circle, the angle of parallelism and area of a polygon, regular polygons, straight lines and planes in space, and the horosphere. Further development of the theory covers hyperbolic functions, the geometry of suff

FAST DISCRETE CURVELET TRANSFORM BASED ANISOTROPIC FEATURE EXTRACTION FOR IRIS RECOGNITION

Directory of Open Access Journals (Sweden)

Amol D. Rahulkar

2010-11-01

Full Text Available The feature extraction plays a very important role in iris recognition. Recent researches on multiscale analysis provide good opportunity to extract more accurate information for iris recognition. In this work, a new directional iris texture features based on 2-D Fast Discrete Curvelet Transform (FDCT is proposed. The proposed approach divides the normalized iris image into six sub-images and the curvelet transform is applied independently on each sub-image. The anisotropic feature vector for each sub-image is derived using the directional energies of the curvelet coefficients. These six feature vectors are combined to create the resultant feature vector. During recognition, the nearest neighbor classifier based on Euclidean distance has been used for authentication. The effectiveness of the proposed approach has been tested on two different databases namely UBIRIS and MMU1. Experimental results show the superiority of the proposed approach.

Epileptic Seizure Detection with Log-Euclidean Gaussian Kernel-Based Sparse Representation.

Science.gov (United States)

Yuan, Shasha; Zhou, Weidong; Wu, Qi; Zhang, Yanli

2016-05-01

Epileptic seizure detection plays an important role in the diagnosis of epilepsy and reducing the massive workload of reviewing electroencephalography (EEG) recordings. In this work, a novel algorithm is developed to detect seizures employing log-Euclidean Gaussian kernel-based sparse representation (SR) in long-term EEG recordings. Unlike the traditional SR for vector data in Euclidean space, the log-Euclidean Gaussian kernel-based SR framework is proposed for seizure detection in the space of the symmetric positive definite (SPD) matrices, which form a Riemannian manifold. Since the Riemannian manifold is nonlinear, the log-Euclidean Gaussian kernel function is applied to embed it into a reproducing kernel Hilbert space (RKHS) for performing SR. The EEG signals of all channels are divided into epochs and the SPD matrices representing EEG epochs are generated by covariance descriptors. Then, the testing samples are sparsely coded over the dictionary composed by training samples utilizing log-Euclidean Gaussian kernel-based SR. The classification of testing samples is achieved by computing the minimal reconstructed residuals. The proposed method is evaluated on the Freiburg EEG dataset of 21 patients and shows its notable performance on both epoch-based and event-based assessments. Moreover, this method handles multiple channels of EEG recordings synchronously which is more speedy and efficient than traditional seizure detection methods.

Euclidean and Minkowski space formulations of linearized gravitational potential in various gauges

International Nuclear Information System (INIS)

Lim, S.C.

1979-01-01

We show that there exists a unitary map connecting linearized theories of gravitational potential in vacuum, formulated in various covariant gauges and noncovariant radiation gauge. The free Euclidean gravitational potentials in covariant gauges satisfy the Markov property of Nelson, but are nonreflexive. For the noncovariant radiation gauge, the corresponding Euclidean field is reflexive but it only satisfies the Markov property with respect to special half spaces. The Feynman--Kac--Nelson formula is established for the Euclidean gravitational potential in radiation gauge

Some nonunitary, indecomposable representations of the Euclidean algebra e(3)

International Nuclear Information System (INIS)

Douglas, Andrew; De Guise, Hubert

2010-01-01

The Euclidean group E(3) is the noncompact, semidirect product group E(3)≅R 3 x SO(3). It is the Lie group of orientation-preserving isometries of three-dimensional Euclidean space. The Euclidean algebra e(3) is the complexification of the Lie algebra of E(3). We construct three distinct families of finite-dimensional, nonunitary representations of e(3) and show that each representation is indecomposable. The representations of the first family are explicitly realized as subspaces of the polynomial ring F[X,Y,Z] with the action of e(3) given by differential operators. The other families are constructed via duals and tensor products of the representations within the first family. We describe subrepresentations, quotients and duals of these indecomposable representations.

Majorization in Euclidean Geometry and Beyond

Czech Academy of Sciences Publication Activity Database

Fiedler, Miroslav

2015-01-01

Roč. 466, 1 February (2015), s. 233-240 ISSN 0024-3795 Institutional support: RVO:67985807 Keywords : Majorization * Doubly stochastic matrix * Euclidean simplex * Star * Regular simplex * Volume of a simplex Subject RIV: BA - General Mathematics Impact factor: 0.965, year: 2015

Uniqueness of Gibbs states and global Markov property for Euclidean fields

International Nuclear Information System (INIS)

Albeverio, S.; Hoeegh-Krohn, R.

1981-01-01

The authors briefly discuss the proof of the uniqueness of solutions of the DLR equations (uniqueness of Gibbs states) in the class of regular generalized random fields (in the sense of having second moments bounded by those of some Euclidean field), for the Euclidean fields with trigonometric interaction. (Auth.)

ORDERED WEIGHTED DISTANCE MEASURE

Institute of Scientific and Technical Information of China (English)

Zeshui XU; Jian CHEN

2008-01-01

The aim of this paper is to develop an ordered weighted distance (OWD) measure, which is thegeneralization of some widely used distance measures, including the normalized Hamming distance, the normalized Euclidean distance, the normalized geometric distance, the max distance, the median distance and the min distance, etc. Moreover, the ordered weighted averaging operator, the generalized ordered weighted aggregation operator, the ordered weighted geometric operator, the averaging operator, the geometric mean operator, the ordered weighted square root operator, the square root operator, the max operator, the median operator and the min operator axe also the special cases of the OWD measure. Some methods depending on the input arguments are given to determine the weights associated with the OWD measure. The prominent characteristic of the OWD measure is that it can relieve (or intensify) the influence of unduly large or unduly small deviations on the aggregation results by assigning them low (or high) weights. This desirable characteristic makes the OWD measure very suitable to be used in many actual fields, including group decision making, medical diagnosis, data mining, and pattern recognition, etc. Finally, based on the OWD measure, we develop a group decision making approach, and illustrate it with a numerical example.

Flexible intuitions of Euclidean geometry in an Amazonian indigene group

Science.gov (United States)

Izard, Véronique; Pica, Pierre; Spelke, Elizabeth S.; Dehaene, Stanislas

2011-01-01

Kant argued that Euclidean geometry is synthesized on the basis of an a priori intuition of space. This proposal inspired much behavioral research probing whether spatial navigation in humans and animals conforms to the predictions of Euclidean geometry. However, Euclidean geometry also includes concepts that transcend the perceptible, such as objects that are infinitely small or infinitely large, or statements of necessity and impossibility. We tested the hypothesis that certain aspects of nonperceptible Euclidian geometry map onto intuitions of space that are present in all humans, even in the absence of formal mathematical education. Our tests probed intuitions of points, lines, and surfaces in participants from an indigene group in the Amazon, the Mundurucu, as well as adults and age-matched children controls from the United States and France and younger US children without education in geometry. The responses of Mundurucu adults and children converged with that of mathematically educated adults and children and revealed an intuitive understanding of essential properties of Euclidean geometry. For instance, on a surface described to them as perfectly planar, the Mundurucu's estimations of the internal angles of triangles added up to ∼180 degrees, and when asked explicitly, they stated that there exists one single parallel line to any given line through a given point. These intuitions were also partially in place in the group of younger US participants. We conclude that, during childhood, humans develop geometrical intuitions that spontaneously accord with the principles of Euclidean geometry, even in the absence of training in mathematics. PMID:21606377

Axioms for Euclidean Green's functions. Pt. 2

International Nuclear Information System (INIS)

Osterwalder, K.; Schrader, R.

1975-01-01

We give new (necessary and) sufficient conditions for Euclidean Green's functions to have analytic continuations to a relativistic field theory. These results extend and correct a previous paper. (orig.) [de

Hubble expansion in a Euclidean framework

International Nuclear Information System (INIS)

Alfven, H.

1979-01-01

There now seems to be strong evidence for a non-cosmological interpretation of the QSO redshift - in any case, so strong that it is of interest to investigate the consequences. The purpose of this paper is to construct a model of the Hubble expansion which is as far as possible from the conventional Big Bang model without coming in conflict with any well-established observational results (while introducing no new laws of physics). This leads to an essentially Euclidean metagalactic model (see Table I) with very little mass outside one-third or half of the Hubble radius. The total kinetic energy of the Hubble expansion need only to be about 5% of the rest mass energy. Present observations support backwards in time extrapolation of the Hubble expansion to a 'minimum size galaxy' Rsub(m), which may have any value in 0 26 cm. Other arguments speak in favor of a size close to the upper value, say Rsub(m) = 10 26 cm (Table II). As this size is probably about 100 times the Schwarzschild limit, an essentially Euclidean description is allowed. The kinetic energy of the Hubble expansion may derive from an intense QSO-like activity in the minimum size metagalaxy, with an energy release corresponding to the annihilation of a few solar masses per galaxy per year. Some of the conclusions based on the Big Bang hypothesis are criticized and in several cases alternative interpretations are suggested. A comparison between the Euclidean and the conventional models is given in Table III. (orig.)

Evaluating the impact of distance measures on deforestation simulations in the fluvial landscapes of amazonia.

Science.gov (United States)

Salonen, Maria; Maeda, Eduardo Eiji; Toivonen, Tuuli

2014-10-01

Land use and land cover change (LUCC) models frequently employ different accessibility measures as a proxy for human influence on land change processes. Here, we simulate deforestation in Peruvian Amazonia and evaluate different accessibility measures as LUCC model inputs. We demonstrate how the selection, and different combinations, of accessibility measures impact simulation results. Out of the individual measures, time distance to market center catches the essential aspects of accessibility in our study area. The most accurate simulation is achieved when time distance to market center is used in association with distance to transport network and additional landscape variables. Although traditional Euclidean measures result in clearly lower simulation accuracy when used separately, the combination of two complementary Euclidean measures enhances simulation accuracy significantly. Our results highlight the need for site and context sensitive selection of accessibility variables. More sophisticated accessibility measures can potentially improve LUCC models' spatial accuracy, which often remains low.

What if? Exploring the multiverse through Euclidean wormholes

Science.gov (United States)

Bouhmadi-López, Mariam; Krämer, Manuel; Morais, João; Robles-Pérez, Salvador

2017-10-01

We present Euclidean wormhole solutions describing possible bridges within the multiverse. The study is carried out in the framework of third quantisation. The matter content is modelled through a scalar field which supports the existence of a whole collection of universes. The instanton solutions describe Euclidean solutions that connect baby universes with asymptotically de Sitter universes. We compute the tunnelling probability of these processes. Considering the current bounds on the energy scale of inflation and assuming that all the baby universes are nucleated with the same probability, we draw some conclusions about which universes are more likely to tunnel and therefore undergo a standard inflationary era.

What if? Exploring the multiverse through Euclidean wormholes

International Nuclear Information System (INIS)

Bouhmadi-Lopez, Mariam; Kraemer, Manuel; Morais, Joao; Robles-Perez, Salvador

2017-01-01

We present Euclidean wormhole solutions describing possible bridges within the multiverse. The study is carried out in the framework of third quantisation. The matter content is modelled through a scalar field which supports the existence of a whole collection of universes. The instanton solutions describe Euclidean solutions that connect baby universes with asymptotically de Sitter universes. We compute the tunnelling probability of these processes. Considering the current bounds on the energy scale of inflation and assuming that all the baby universes are nucleated with the same probability, we draw some conclusions about which universes are more likely to tunnel and therefore undergo a standard inflationary era. (orig.)

What if? Exploring the multiverse through Euclidean wormholes

Energy Technology Data Exchange (ETDEWEB)

Bouhmadi-Lopez, Mariam [University of the Basque Country UPV/EHU, Department of Theoretical Physics, Bilbao (Spain); Ikerbasque, Basque Foundation for Science, Bilbao (Spain); Kraemer, Manuel [University of Szczecin, Institute of Physics, Szczecin (Poland); Morais, Joao [University of the Basque Country UPV/EHU, Department of Theoretical Physics, Bilbao (Spain); Robles-Perez, Salvador [Instituto de Fisica Fundamental, CSIC, Madrid (Spain); Estacion Ecologica de Biocosmologia, Medellin (Spain)

2017-10-15

We present Euclidean wormhole solutions describing possible bridges within the multiverse. The study is carried out in the framework of third quantisation. The matter content is modelled through a scalar field which supports the existence of a whole collection of universes. The instanton solutions describe Euclidean solutions that connect baby universes with asymptotically de Sitter universes. We compute the tunnelling probability of these processes. Considering the current bounds on the energy scale of inflation and assuming that all the baby universes are nucleated with the same probability, we draw some conclusions about which universes are more likely to tunnel and therefore undergo a standard inflationary era. (orig.)

Statistical mechanics, gravity, and Euclidean theory

International Nuclear Information System (INIS)

Fursaev, Dmitri V.

2002-01-01

A review of computations of free energy for Gibbs states on stationary but not static gravitational and gauge backgrounds is given. On these backgrounds wave equations for free fields are reduced to eigenvalue problems which depend non-linearly on the spectral parameter. We present a method to deal with such problems. In particular, we demonstrate how some results of the spectral theory of second-order elliptic operators, such as heat kernel asymptotics, can be extended to a class of non-linear spectral problems. The method is used to trace down the relation between the canonical definition of the free energy based on summation over the modes and the covariant definition given in Euclidean quantum gravity. As an application, high-temperature asymptotics of the free energy and of the thermal part of the stress-energy tensor in the presence of rotation are derived. We also discuss statistical mechanics in the presence of Killing horizons where canonical and Euclidean theories are related in a non-trivial way

Calculus and analysis in Euclidean space

CERN Document Server

Shurman, Jerry

2016-01-01

The graceful role of analysis in underpinning calculus is often lost to their separation in the curriculum. This book entwines the two subjects, providing a conceptual approach to multivariable calculus closely supported by the structure and reasoning of analysis. The setting is Euclidean space, with the material on differentiation culminating in the inverse and implicit function theorems, and the material on integration culminating in the general fundamental theorem of integral calculus. More in-depth than most calculus books but less technical than a typical analysis introduction, Calculus and Analysis in Euclidean Space offers a rich blend of content to students outside the traditional mathematics major, while also providing transitional preparation for those who will continue on in the subject. The writing in this book aims to convey the intent of ideas early in discussion. The narrative proceeds through figures, formulas, and text, guiding the reader to do mathematics resourcefully by marshaling the skil...

Transformation optics with artificial Riemann sheets

Science.gov (United States)

Xu, Lin; Chen, Huanyang

2013-11-01

The two original versions of ‘invisibility’ cloaks (Leonhardt 2006 Science 312 1777-80 and Pendry et al 2006 Science 312 1780-2) show perfect cloaking but require unphysical singularities in material properties. A non-Euclidean version of cloaking (Leonhardt 2009 Science 323 110-12) was later presented to address these problems, using a very complicated non-Euclidean geometry. In this work, we combine the two original approaches to transformation optics into a more general concept: transformation optics with artificial Riemann sheets. Our method is straightforward and can be utilized to design new kinds of cloaks that can work not only in the realm of geometric optics but also using wave optics. The physics behind this design is similar to that of the conformal cloak for waves. The resonances in the interior region make the phase delay disappear and induce the cloaking effect. Numerical simulations confirm our theoretical results.

Lorentz violations and Euclidean signature metrics

International Nuclear Information System (INIS)

Barbero G, J. Fernando; Villasenor, Eduardo J.S.

2003-01-01

We show that the families of effective actions considered by Jacobson et al. to study Lorentz invariance violations contain a class of models that represent pure general relativity with a Euclidean signature. We also point out that some members of this family of actions preserve Lorentz invariance in a generalized sense

Comparing two distance measures in the spatial mapping of food deserts: The case of Petržalka, Slovakia

Directory of Open Access Journals (Sweden)

Bilková Kristína

2017-06-01

Full Text Available Over the last twenty years or so, researchers’ attention to the issue of food deserts has increased in the geographical literature. Accessibility to large-scale retail units is one of the essential and frequently-used indicators leading to the identification and mapping of food deserts. Numerous accessibility measures of various types are available for this purpose. Euclidean distance and street network distance rank among the most frequently-used approaches, although they may lead to slightly different results. The aim of this paper is to compare various approaches to the accessibility to food stores and to assess the differences in the results gained by these methods. Accessibility was measured for residential block centroids, with applications of various accessibility measures in a GIS environment. The results suggest a strong correspondence between Euclidean distance and a little more accurate street network distance approach, applied in the case of the urban environment of Bratislava-Petržalka, Slovakia.

Tunneling in expanding Universe: Euclidean and Hamiltonian approaches

International Nuclear Information System (INIS)

Goncharov, A.S.; Linde, A.D.

1986-01-01

The theory of the false vacuum decay in de Sitter space and in the inflationary Universe, and also the theory of the Universe creation ''from nothing'' are discussed. This explained why tunneling in the inflationary Universe differs from that in de Sitter space and cannot be exactly homogeneous. It is shown that in several important cases the Euclidean approach should be considerably modified or is absolutely inapplicable for the description of tunneling in the expanding Universe and of the process of the quantum creation of the Universe. The Hamiltonian approach to the theory of tunneling in expanding Universe is developed. The results obtained by this method are compared with the results obtained by the Euclidean approach

On the invariant theory of Weingarten surfaces in Euclidean space

International Nuclear Information System (INIS)

Ganchev, Georgi; Mihova, Vesselka

2010-01-01

On any Weingarten surface in Euclidean space (strongly regular or rotational), we introduce locally geometric principal parameters and prove that such a surface is determined uniquely up to a motion by a special invariant function, which satisfies a natural nonlinear partial differential equation. This result can be interpreted as a solution to the Lund-Regge reduction problem for Weingarten surfaces in Euclidean space. We apply this theory to fractional-linear Weingarten surfaces and obtain the nonlinear partial differential equations describing them.

Contaminant classification using cosine distances based on multiple conventional sensors.

Science.gov (United States)

Liu, Shuming; Che, Han; Smith, Kate; Chang, Tian

2015-02-01

Emergent contamination events have a significant impact on water systems. After contamination detection, it is important to classify the type of contaminant quickly to provide support for remediation attempts. Conventional methods generally either rely on laboratory-based analysis, which requires a long analysis time, or on multivariable-based geometry analysis and sequence analysis, which is prone to being affected by the contaminant concentration. This paper proposes a new contaminant classification method, which discriminates contaminants in a real time manner independent of the contaminant concentration. The proposed method quantifies the similarities or dissimilarities between sensors' responses to different types of contaminants. The performance of the proposed method was evaluated using data from contaminant injection experiments in a laboratory and compared with a Euclidean distance-based method. The robustness of the proposed method was evaluated using an uncertainty analysis. The results show that the proposed method performed better in identifying the type of contaminant than the Euclidean distance based method and that it could classify the type of contaminant in minutes without significantly compromising the correct classification rate (CCR).

Analysis in Euclidean space

CERN Document Server

Hoffman, Kenneth

2007-01-01

Developed for an introductory course in mathematical analysis at MIT, this text focuses on concepts, principles, and methods. Its introductions to real and complex analysis are closely formulated, and they constitute a natural introduction to complex function theory.Starting with an overview of the real number system, the text presents results for subsets and functions related to Euclidean space of n dimensions. It offers a rigorous review of the fundamentals of calculus, emphasizing power series expansions and introducing the theory of complex-analytic functions. Subsequent chapters cover seq

Transformation optics with artificial Riemann sheets

International Nuclear Information System (INIS)

Xu, Lin; Chen, Huanyang

2013-01-01

The two original versions of ‘invisibility’ cloaks (Leonhardt 2006 Science 312 1777–80 and Pendry et al 2006 Science 312 1780–2) show perfect cloaking but require unphysical singularities in material properties. A non-Euclidean version of cloaking (Leonhardt 2009 Science 323 110–12) was later presented to address these problems, using a very complicated non-Euclidean geometry. In this work, we combine the two original approaches to transformation optics into a more general concept: transformation optics with artificial Riemann sheets. Our method is straightforward and can be utilized to design new kinds of cloaks that can work not only in the realm of geometric optics but also using wave optics. The physics behind this design is similar to that of the conformal cloak for waves. The resonances in the interior region make the phase delay disappear and induce the cloaking effect. Numerical simulations confirm our theoretical results. (paper)

Polynomial degree reduction in the discrete L2-norm equals best Euclidean approximation of h-Bézier coefficients

KAUST Repository

Ait-Haddou, Rachid

2015-06-04

We show that the best degree reduction of a given polynomial P from degree n to m with respect to the discrete (Formula presented.)-norm is equivalent to the best Euclidean distance of the vector of h-Bézier coefficients of P from the vector of degree raised h-Bézier coefficients of polynomials of degree m. Moreover, we demonstrate the adequacy of h-Bézier curves for approaching the problem of weighted discrete least squares approximation. Applications to discrete orthogonal polynomials are also presented. © 2015 Springer Science+Business Media Dordrecht

On the Averaging of Cardiac Diffusion Tensor MRI Data: The Effect of Distance Function Selection

Science.gov (United States)

Giannakidis, Archontis; Melkus, Gerd; Yang, Guang; Gullberg, Grant T.

2016-01-01

Diffusion tensor magnetic resonance imaging (DT-MRI) allows a unique insight into the microstructure of highly-directional tissues. The selection of the most proper distance function for the space of diffusion tensors is crucial in enhancing the clinical application of this imaging modality. Both linear and nonlinear metrics have been proposed in the literature over the years. The debate on the most appropriate DT-MRI distance function is still ongoing. In this paper, we presented a framework to compare the Euclidean, affine-invariant Riemannian and log-Euclidean metrics using actual high-resolution DT-MRI rat heart data. We employed temporal averaging at the diffusion tensor level of three consecutive and identically-acquired DT-MRI datasets from each of five rat hearts as a means to rectify the background noise-induced loss of myocyte directional regularity. This procedure is applied here for the first time in the context of tensor distance function selection. When compared with previous studies that used a different concrete application to juxtapose the various DT-MRI distance functions, this work is unique in that it combined the following: (i) Metrics were judged by quantitative –rather than qualitative– criteria, (ii) the comparison tools were non-biased, (iii) a longitudinal comparison operation was used on a same-voxel basis. The statistical analyses of the comparison showed that the three DT-MRI distance functions tend to provide equivalent results. Hence, we came to the conclusion that the tensor manifold for cardiac DT-MRI studies is a curved space of almost zero curvature. The signal to noise ratio dependence of the operations was investigated through simulations. Finally, the “swelling effect” occurrence following Euclidean averaging was found to be too unimportant to be worth consideration. PMID:27754986

On the averaging of cardiac diffusion tensor MRI data: the effect of distance function selection

Science.gov (United States)

Giannakidis, Archontis; Melkus, Gerd; Yang, Guang; Gullberg, Grant T.

2016-11-01

Diffusion tensor magnetic resonance imaging (DT-MRI) allows a unique insight into the microstructure of highly-directional tissues. The selection of the most proper distance function for the space of diffusion tensors is crucial in enhancing the clinical application of this imaging modality. Both linear and nonlinear metrics have been proposed in the literature over the years. The debate on the most appropriate DT-MRI distance function is still ongoing. In this paper, we presented a framework to compare the Euclidean, affine-invariant Riemannian and log-Euclidean metrics using actual high-resolution DT-MRI rat heart data. We employed temporal averaging at the diffusion tensor level of three consecutive and identically-acquired DT-MRI datasets from each of five rat hearts as a means to rectify the background noise-induced loss of myocyte directional regularity. This procedure is applied here for the first time in the context of tensor distance function selection. When compared with previous studies that used a different concrete application to juxtapose the various DT-MRI distance functions, this work is unique in that it combined the following: (i) metrics were judged by quantitative—rather than qualitative—criteria, (ii) the comparison tools were non-biased, (iii) a longitudinal comparison operation was used on a same-voxel basis. The statistical analyses of the comparison showed that the three DT-MRI distance functions tend to provide equivalent results. Hence, we came to the conclusion that the tensor manifold for cardiac DT-MRI studies is a curved space of almost zero curvature. The signal to noise ratio dependence of the operations was investigated through simulations. Finally, the ‘swelling effect’ occurrence following Euclidean averaging was found to be too unimportant to be worth consideration.

Euclidean wormholes with minimally coupled scalar fields

International Nuclear Information System (INIS)

Ruz, Soumendranath; Modak, Bijan; Debnath, Subhra; Sanyal, Abhik Kumar

2013-01-01

A detailed study of quantum and semiclassical Euclidean wormholes for Einstein's theory with a minimally coupled scalar field has been performed for a class of potentials. Massless, constant, massive (quadratic in the scalar field) and inverse (linear) potentials admit the Hawking and Page wormhole boundary condition both in the classically forbidden and allowed regions. An inverse quartic potential has been found to exhibit a semiclassical wormhole configuration. Classical wormholes under a suitable back-reaction leading to a finite radius of the throat, where the strong energy condition is satisfied, have been found for the zero, constant, quadratic and exponential potentials. Treating such classical Euclidean wormholes as an initial condition, a late stage of cosmological evolution has been found to remain unaltered from standard Friedmann cosmology, except for the constant potential which under the back-reaction produces a term like a negative cosmological constant. (paper)

The positive action conjecture and asymptotically euclidean metrics in quantum gravity

International Nuclear Information System (INIS)

Gibbons, G.W.; Pope, C.N.

1979-01-01

The positive action conjecture requires that the action of any asymptotically Euclidean 4-dimensional Riemannian metric be positive, vanishing if and only if the space is flat. Because any Ricci flat, asymptotically Euclidean metric has zero action and is local extremum of the action which is a local minimum at flat space, the conjecture requires that there are no Ricci flat asymptotically Euclidean metrics other than flat space, which would establish that flat space is the only local minimum. We prove this for metrics on R 4 and a large class of more complicated topologies and for self-dual metrics. We show that if Rsupμsubμ >= 0 there are no bound states of the Dirac equation and discuss the relevance to possible baryon non-conserving processes mediated by gravitational instantons. We conclude that these are forbidden in the lowest stationary phase approximation. We give a detailed discussion of instantons invariant under an SU(2) or SO(3) isometry group. We find all regular solutions, none of which is asymptotically Euclidean and all of which possess a further Killing vector. In an appendix we construct an approximate self-dual metric on K3 - the only simply connected compact manifold which admits a self-dual metric. (orig.) [de

Fisher type inequalities for Euclidean t-designs

NARCIS (Netherlands)

Delsarte, Ph.; Seidel, J.J.

1989-01-01

The notion of a Euclidean t-design is analyzed in the framework of appropriate inner product spaces of polynomial functions. Some Fisher type inequalities are obtained in a simple manner by this method. The same approach is used to deal with certain analogous combinatorial designs.

Spatial interpolation of fine particulate matter concentrations using the shortest wind-field path distance.

Directory of Open Access Journals (Sweden)

Longxiang Li

Full Text Available Effective assessments of air-pollution exposure depend on the ability to accurately predict pollutant concentrations at unmonitored locations, which can be achieved through spatial interpolation. However, most interpolation approaches currently in use are based on the Euclidean distance, which cannot account for the complex nonlinear features displayed by air-pollution distributions in the wind-field. In this study, an interpolation method based on the shortest path distance is developed to characterize the impact of complex urban wind-field on the distribution of the particulate matter concentration. In this method, the wind-field is incorporated by first interpolating the observed wind-field from a meteorological-station network, then using this continuous wind-field to construct a cost surface based on Gaussian dispersion model and calculating the shortest wind-field path distances between locations, and finally replacing the Euclidean distances typically used in Inverse Distance Weighting (IDW with the shortest wind-field path distances. This proposed methodology is used to generate daily and hourly estimation surfaces for the particulate matter concentration in the urban area of Beijing in May 2013. This study demonstrates that wind-fields can be incorporated into an interpolation framework using the shortest wind-field path distance, which leads to a remarkable improvement in both the prediction accuracy and the visual reproduction of the wind-flow effect, both of which are of great importance for the assessment of the effects of pollutants on human health.

Linearization of Euclidean Norm Dependent Inequalities Applied to Multibeam Satellites Design

OpenAIRE

Camino , Jean-Thomas; Artigues , Christian; Houssin , Laurent; Mourgues , Stéphane

2016-01-01

Euclidean norm computations over continuous variables appear naturally in the constraints or in the objective of many problems in the optimization literature, possibly defining non-convex feasible regions or cost functions. When some other variables have discrete domains, it positions the problem in the challenging Mixed Integer Nonlinear Programming (MINLP) class. For any MINLP where the nonlinearity is only present in the form of inequality constraints involving the Euclidean norm, we propo...

General Rotational Surfaces in Pseudo-Euclidean 4-Space with Neutral Metric

OpenAIRE

Aleksieva, Yana; Milousheva, Velichka; Turgay, Nurettin Cenk

2016-01-01

We define general rotational surfaces of elliptic and hyperbolic type in the pseudo-Euclidean 4-space with neutral metric which are analogous to the general rotational surfaces of C. Moore in the Euclidean 4-space. We study Lorentz general rotational surfaces with plane meridian curves and give the complete classification of minimal general rotational surfaces of elliptic and hyperbolic type, general rotational surfaces with parallel normalized mean curvature vector field, flat general rotati...

Noncommutative Geometry of the Moyal Plane: Translation Isometries, Connes' Distance on Coherent States, Pythagoras Equality

Science.gov (United States)

Martinetti, Pierre; Tomassini, Luca

2013-10-01

We study the metric aspect of the Moyal plane from Connes' noncommutative geometry point of view. First, we compute Connes' spectral distance associated with the natural isometric action of on the algebra of the Moyal plane . We show that the distance between any state of and any of its translated states is precisely the amplitude of the translation. As a consequence, we obtain the spectral distance between coherent states of the quantum harmonic oscillator as the Euclidean distance on the plane. We investigate the classical limit, showing that the set of coherent states equipped with Connes' spectral distance tends towards the Euclidean plane as the parameter of deformation goes to zero. The extension of these results to the action of the symplectic group is also discussed, with particular emphasis on the orbits of coherent states under rotations. Second, we compute the spectral distance in the double Moyal plane, intended as the product of (the minimal unitization of) by . We show that on the set of states obtained by translation of an arbitrary state of , this distance is given by the Pythagoras theorem. On the way, we prove some Pythagoras inequalities for the product of arbitrary unital and non-degenerate spectral triples. Applied to the Doplicher- Fredenhagen-Roberts model of quantum spacetime [DFR], these two theorems show that Connes' spectral distance and the DFR quantum length coincide on the set of states of optimal localization.

New solutions of euclidean SU(2) gauge theory

International Nuclear Information System (INIS)

Khan, I.

1983-08-01

New solutions of the Euclidean SU(2) gauge theory having finite field strength everywhere are presented. The solutions are self dual or antidual and constitute a two-parameter family which includes the instantons. (author)

Euclidean to Minkowski Bethe-Salpeter amplitude and observables

International Nuclear Information System (INIS)

Carbonell, J.; Frederico, T.; Karmanov, V.A.

2017-01-01

We propose a method to reconstruct the Bethe-Salpeter amplitude in Minkowski space given the Euclidean Bethe-Salpeter amplitude - or alternatively the light-front wave function - as input. The method is based on the numerical inversion of the Nakanishi integral representation and computing the corresponding weight function. This inversion procedure is, in general, rather unstable, and we propose several ways to considerably reduce the instabilities. In terms of the Nakanishi weight function, one can easily compute the BS amplitude, the LF wave function and the electromagnetic form factor. The latter ones are very stable in spite of residual instabilities in the weight function. This procedure allows both, to continue the Euclidean BS solution in the Minkowski space and to obtain a BS amplitude from a LF wave function. (orig.)

Euclidean to Minkowski Bethe-Salpeter amplitude and observables

Energy Technology Data Exchange (ETDEWEB)

Carbonell, J. [Universite Paris-Sud, IN2P3-CNRS, Institut de Physique Nucleaire, Orsay Cedex (France); Frederico, T. [Instituto Tecnologico de Aeronautica, DCTA, Sao Jose dos Campos (Brazil); Karmanov, V.A. [Lebedev Physical Institute, Moscow (Russian Federation)

2017-01-15

We propose a method to reconstruct the Bethe-Salpeter amplitude in Minkowski space given the Euclidean Bethe-Salpeter amplitude - or alternatively the light-front wave function - as input. The method is based on the numerical inversion of the Nakanishi integral representation and computing the corresponding weight function. This inversion procedure is, in general, rather unstable, and we propose several ways to considerably reduce the instabilities. In terms of the Nakanishi weight function, one can easily compute the BS amplitude, the LF wave function and the electromagnetic form factor. The latter ones are very stable in spite of residual instabilities in the weight function. This procedure allows both, to continue the Euclidean BS solution in the Minkowski space and to obtain a BS amplitude from a LF wave function. (orig.)

Matrices and Graphs in Euclidean Geometry

Czech Academy of Sciences Publication Activity Database

Fiedler, Miroslav

2005-01-01

Roč. 14, - (2005), s. 51-58 E-ISSN 1081-3810 R&D Projects: GA AV ČR IAA1030302 Institutional research plan: CEZ:AV0Z10300504 Keywords : Euclidean space * Gram matrix * biorthogonal bases * simplex * interior angle * Steiner circumscribed ellipsoid * right simplex Subject RIV: BA - General Mathematics http://www.math.technion.ac.il/iic/ ela / ela -articles/14.html

Euclidean self-dual Yang-Mills field configurations

International Nuclear Information System (INIS)

Sartori, G.

1980-01-01

The determination of a large class of regular and singular Euclidean self-dual Yang-Mills field configurations is reduced to the solution of a set of linear algebraic equations. The matrix of the coefficients is a polynomial functions of x and the rules for its construction are elementary. (author)

Metrics for measuring distances in configuration spaces

International Nuclear Information System (INIS)

Sadeghi, Ali; Ghasemi, S. Alireza; Schaefer, Bastian; Mohr, Stephan; Goedecker, Stefan; Lill, Markus A.

2013-01-01

In order to characterize molecular structures we introduce configurational fingerprint vectors which are counterparts of quantities used experimentally to identify structures. The Euclidean distance between the configurational fingerprint vectors satisfies the properties of a metric and can therefore safely be used to measure dissimilarities between configurations in the high dimensional configuration space. In particular we show that these metrics are a perfect and computationally cheap replacement for the root-mean-square distance (RMSD) when one has to decide whether two noise contaminated configurations are identical or not. We introduce a Monte Carlo approach to obtain the global minimum of the RMSD between configurations, which is obtained from a global minimization over all translations, rotations, and permutations of atomic indices

Random walks in Euclidean space

OpenAIRE

Varjú, Péter Pál

2012-01-01

Consider a sequence of independent random isometries of Euclidean space with a previously fixed probability law. Apply these isometries successively to the origin and consider the sequence of random points that we obtain this way. We prove a local limit theorem under a suitable moment condition and a necessary non-degeneracy condition. Under stronger hypothesis, we prove a limit theorem on a wide range of scales: between e^(-cl^(1/4)) and l^(1/2), where l is the number of steps.

Single and multiple object tracking using log-euclidean Riemannian subspace and block-division appearance model.

Science.gov (United States)

Hu, Weiming; Li, Xi; Luo, Wenhan; Zhang, Xiaoqin; Maybank, Stephen; Zhang, Zhongfei

2012-12-01

Object appearance modeling is crucial for tracking objects, especially in videos captured by nonstationary cameras and for reasoning about occlusions between multiple moving objects. Based on the log-euclidean Riemannian metric on symmetric positive definite matrices, we propose an incremental log-euclidean Riemannian subspace learning algorithm in which covariance matrices of image features are mapped into a vector space with the log-euclidean Riemannian metric. Based on the subspace learning algorithm, we develop a log-euclidean block-division appearance model which captures both the global and local spatial layout information about object appearances. Single object tracking and multi-object tracking with occlusion reasoning are then achieved by particle filtering-based Bayesian state inference. During tracking, incremental updating of the log-euclidean block-division appearance model captures changes in object appearance. For multi-object tracking, the appearance models of the objects can be updated even in the presence of occlusions. Experimental results demonstrate that the proposed tracking algorithm obtains more accurate results than six state-of-the-art tracking algorithms.

Pythagoras's theorem on a two-dimensional lattice from a `natural' Dirac operator and Connes's distance formula

Science.gov (United States)

Dai, Jian; Song, Xing-Chang

2001-07-01

One of the key ingredients of Connes's noncommutative geometry is a generalized Dirac operator which induces a metric (Connes's distance) on the pure state space. We generalize such a Dirac operator devised by Dimakis et al, whose Connes distance recovers the linear distance on an one-dimensional lattice, to the two-dimensional case. This Dirac operator has the local eigenvalue property and induces a Euclidean distance on this two-dimensional lattice, which is referred to as `natural'. This kind of Dirac operator can be easily generalized into any higher-dimensional lattices.

Introduction to non-Euclidean geometry

CERN Document Server

Wolfe, Harold E

2012-01-01

One of the first college-level texts for elementary courses in non-Euclidean geometry, this concise, readable volume is geared toward students familiar with calculus. A full treatment of the historical background explores the centuries-long efforts to prove Euclid's parallel postulate and their triumphant conclusion. Numerous original exercises form an integral part of the book.Topics include hyperbolic plane geometry and hyperbolic plane trigonometry, applications of calculus to the solutions of some problems in hyperbolic geometry, elliptic plane geometry and trigonometry, and the consistenc

Classical and quantum integrability of 2D dilaton gravities in Euclidean space

International Nuclear Information System (INIS)

Bergamin, L; Grumiller, D; Kummer, W; Vassilevich, D V

2005-01-01

Euclidean dilaton gravity in two dimensions is studied exploiting its representation as a complexified first order gravity model. All local classical solutions are obtained. A global discussion reveals that for a given model only a restricted class of topologies is consistent with the metric and the dilaton. A particular case of string motivated Liouville gravity is studied in detail. Path integral quantization in generic Euclidean dilaton gravity is performed non-perturbatively by analogy to the Minkowskian case

Euclidean Geometry Codes, minimum weight words and decodable error-patterns using bit-flipping

DEFF Research Database (Denmark)

Høholdt, Tom; Justesen, Jørn; Jonsson, Bergtor

2005-01-01

We determine the number of minimum wigth words in a class of Euclidean Geometry codes and link the performance of the bit-flipping decoding algorithm to the geometry of the error patterns.......We determine the number of minimum wigth words in a class of Euclidean Geometry codes and link the performance of the bit-flipping decoding algorithm to the geometry of the error patterns....

A general Euclidean connection for so(n,m) lie algebra and the algebraic approach to scattering

International Nuclear Information System (INIS)

Ionescu, R.A.

1994-11-01

We obtain a general Euclidean connection for so(n,m). This Euclidean connection allows an algebraic derivation of the S matrix and it reduces to the known one in suitable circumstances. (author). 8 refs

Bianchi-Baecklund transformations, conservation laws, and linearization of various field theories

International Nuclear Information System (INIS)

Chau Wang, L.L.

1980-01-01

The discussion includes: the Sine-Gordon equation, parametric Bianchi-Baecklund transformations and the derivation of local conservation laws; chiral fields, parametric Bianchi-Baecklund transformations, local and non-local conservation laws, and linearization; super chiral fields, a parallel development similar to the chiral field; and self-dual Yang-Mills fields in 4-dimensional Euclidean space; loop-cpace chiral equations, parallel development but with subtlety

A method for assigning species into groups based on generalized Mahalanobis distance between habitat model coefficients

Science.gov (United States)

Williams, C.J.; Heglund, P.J.

2009-01-01

Habitat association models are commonly developed for individual animal species using generalized linear modeling methods such as logistic regression. We considered the issue of grouping species based on their habitat use so that management decisions can be based on sets of species rather than individual species. This research was motivated by a study of western landbirds in northern Idaho forests. The method we examined was to separately fit models to each species and to use a generalized Mahalanobis distance between coefficient vectors to create a distance matrix among species. Clustering methods were used to group species from the distance matrix, and multidimensional scaling methods were used to visualize the relations among species groups. Methods were also discussed for evaluating the sensitivity of the conclusions because of outliers or influential data points. We illustrate these methods with data from the landbird study conducted in northern Idaho. Simulation results are presented to compare the success of this method to alternative methods using Euclidean distance between coefficient vectors and to methods that do not use habitat association models. These simulations demonstrate that our Mahalanobis-distance- based method was nearly always better than Euclidean-distance-based methods or methods not based on habitat association models. The methods used to develop candidate species groups are easily explained to other scientists and resource managers since they mainly rely on classical multivariate statistical methods. ?? 2008 Springer Science+Business Media, LLC.

Euclidean fields: vector mesons and photons

International Nuclear Information System (INIS)

Loffelholz, J.

1979-01-01

Free transverse vector fields of mass >= 0 are studied. The model is related to the usual free vector meson and electromagnetic quantum field theories by extension of the field operators from transverse to arbitrary test functions. The one-particle states in transverse gauge and their localization are described. Reflexion positivity is proved and derived are free Feynman-Kac-Nelson formulas. An Euclidean approach to a photon field in a spherical world using dilatation covariance and inversions is given

Spinors and supersymmetry in four-dimensional Euclidean space

International Nuclear Information System (INIS)

McKeon, D.G.C.; Sherry, T.N.

2001-01-01

Spinors in four-dimensional Euclidean space are treated using the decomposition of the Euclidean space SO(4) symmetry group into SU(2)xSU(2). Both 2- and 4-spinor representations of this SO(4) symmetry group are shown to differ significantly from the corresponding spinor representations of the SO(3, 1) symmetry group in Minkowski space. The simplest self conjugate supersymmetry algebra allowed in four-dimensional Euclidean space is demonstrated to be an N=2 supersymmetry algebra which resembles the N=2 supersymmetry algebra in four-dimensional Minkowski space. The differences between the two supersymmetry algebras gives rise to different representations; in particular an analysis of the Clifford algebra structure shows that the momentum invariant is bounded above by the central charges in 4dE, while in 4dM the central charges bound the momentum invariant from below. Dimensional reduction of the N=1 SUSY algebra in six-dimensional Minkowski space (6dM) to 4dE reproduces our SUSY algebra in 4dE. This dimensional reduction can be used to introduce additional generators into the SUSY algebra in 4dE. Well known interpolating maps are used to relate the N=2 SUSY algebra in 4dE derived in this paper to the N=2 SUSY algebra in 4dM. The nature of the spinors in 4dE allows us to write an axially gauge invariant model which is shown to be both Hermitian and anomaly-free. No equivalent model exists in 4dM. Useful formulae in 4dE are collected together in two appendixes

Non-Euclidean Geometry and Gravitation

Directory of Open Access Journals (Sweden)

Stavroulakis N.

2006-04-01

Full Text Available A great deal of misunderstandings and mathematical errors are involved in the currently accepted theory of the gravitational field generated by an isotropic spherical mass. The purpose of the present paper is to provide a short account of the rigorous mathematical theory and exhibit a new formulation of the problem. The solution of the corresponding equations of gravitation points out several new and unusual features of the stationary gravitational field which are related to the non-Euclidean structure of the space. Moreover it precludes the black hole from being a mathematical and physical notion.

Multiplicative Structure and Hecke Rings of Generator Matrices for Codes over Quotient Rings of Euclidean Domains

Directory of Open Access Journals (Sweden)

Hajime Matsui

2017-12-01

Full Text Available In this study, we consider codes over Euclidean domains modulo their ideals. In the first half of the study, we deal with arbitrary Euclidean domains. We show that the product of generator matrices of codes over the rings mod a and mod b produces generator matrices of all codes over the ring mod a b , i.e., this correspondence is onto. Moreover, we show that if a and b are coprime, then this correspondence is one-to-one, i.e., there exist unique codes over the rings mod a and mod b that produce any given code over the ring mod a b through the product of their generator matrices. In the second half of the study, we focus on the typical Euclidean domains such as the rational integer ring, one-variable polynomial rings, rings of Gaussian and Eisenstein integers, p-adic integer rings and rings of one-variable formal power series. We define the reduced generator matrices of codes over Euclidean domains modulo their ideals and show their uniqueness. Finally, we apply our theory of reduced generator matrices to the Hecke rings of matrices over these Euclidean domains.

Superconvergent perturbation theory for euclidean scalar field theories

International Nuclear Information System (INIS)

Ushveridze, A.G.

1984-01-01

It is shown that the bare (unrenormalized) correlation functions in the euclidean scalar field theories can be expanded in a series whose terms, being computable in a relatively simple way, are free from ultraviolet and infrared divergencies. This series is convergent (divergent) for finite (infinite) values of the correlation functions. (orig.)

Algebraic Methods for Counting Euclidean Embeddings of Rigid Graphs

NARCIS (Netherlands)

I.Z. Emiris; E.P. Tsigaridas; A. Varvitsiotis (Antonios); E.R. Gasner

2009-01-01

textabstract The study of (minimally) rigid graphs is motivated by numerous applications, mostly in robotics and bioinformatics. A major open problem concerns the number of embeddings of such graphs, up to rigid motions, in Euclidean space. We capture embeddability by polynomial systems

Euclidean Primes Have the Minimum Number of Primitive Roots

Czech Academy of Sciences Publication Activity Database

Křížek, Michal; Somer, L.

2008-01-01

Roč. 12, č. 1 (2008), s. 121-127 ISSN 0972-5555 R&D Projects: GA AV ČR(CZ) IAA100190803 Institutional research plan: CEZ:AV0Z10190503 Keywords : Euclidean primes * Fermat primes * Sophie Germain primes Subject RIV: BA - General Mathematics

Euclidean approach to the inflationary universe

International Nuclear Information System (INIS)

Hawking, S.W.

1983-01-01

The aim of this article is to show how the Euclidean approach can be used to study the inflationary universe. Although this formulation may appear counterintuitive in some respects, it has the advantage that it defines a definite quantum state and provides a framework for calculating quantities of interest such as correlation functions or tunnelling probabilities. By contrast, in the more usual approach in real Lorentzian spacetime, it is not so clear what the quantum state should be or how to evaluate such quantities. (author)

Non-Euclidean spacetime structure and the two-slit experiment

International Nuclear Information System (INIS)

El Naschie, M.S.

2005-01-01

A simple mathematical model for the two-slit experiment is given to account for the wave-particle duality. Subsequently, the various solutions are interpreted via the experimental evidence as a property of the underlying non-Euclidean spacetime topology and geometry at the quantum level

$O(N)$ model in Euclidean de Sitter space: beyond the leading infrared approximation

CERN Document Server

Nacir, Diana López; Trombetta, Leonardo G

2016-01-01

We consider an $O(N)$ scalar field model with quartic interaction in $d$-dimensional Euclidean de Sitter space. In order to avoid the problems of the standard perturbative calculations for light and massless fields, we generalize to the $O(N)$ theory a systematic method introduced previously for a single field, which treats the zero modes exactly and the nonzero modes perturbatively. We compute the two-point functions taking into account not only the leading infrared contribution, coming from the self-interaction of the zero modes, but also corrections due to the interaction of the ultraviolet modes. For the model defined in the corresponding Lorentzian de Sitter spacetime, we obtain the two-point functions by analytical continuation. We point out that a partial resummation of the leading secular terms (which necessarily involves nonzero modes) is required to obtain a decay at large distances for massless fields. We implement this resummation along with a systematic double expansion in an effective coupling c...

Spatial generalised linear mixed models based on distances.

Science.gov (United States)

Melo, Oscar O; Mateu, Jorge; Melo, Carlos E

2016-10-01

Risk models derived from environmental data have been widely shown to be effective in delineating geographical areas of risk because they are intuitively easy to understand. We present a new method based on distances, which allows the modelling of continuous and non-continuous random variables through distance-based spatial generalised linear mixed models. The parameters are estimated using Markov chain Monte Carlo maximum likelihood, which is a feasible and a useful technique. The proposed method depends on a detrending step built from continuous or categorical explanatory variables, or a mixture among them, by using an appropriate Euclidean distance. The method is illustrated through the analysis of the variation in the prevalence of Loa loa among a sample of village residents in Cameroon, where the explanatory variables included elevation, together with maximum normalised-difference vegetation index and the standard deviation of normalised-difference vegetation index calculated from repeated satellite scans over time. © The Author(s) 2013.

Scalar Green's functions in an Euclidean space with a conical-type line singularity

International Nuclear Information System (INIS)

Guimaraes, M.E.X.; Linet, B.

1994-01-01

In an Euclidean space with a conical-type line singularity, we determine the Green's function for a charged massive scalar field interacting with a magnetic flux running through the line singularity. We give an integral expression of the Green's function and a local form in the neighbourhood of the point source, where it is the sum of the usual Green's function in Euclidean space and a regular term. As an application, we derive the vacuum energy-momentum tensor in the massless case for an arbitrary magnetic flux. (orig.)

Higher order BLG supersymmetry transformations from 10-dimensional super Yang Mills

Energy Technology Data Exchange (ETDEWEB)

Hall, John [Alumnus of Physics Department, Imperial College,South Kensington, London, SW7 2AZ (United Kingdom); Low, Andrew [Physics Department, Wimbledon High School,Mansel Road, London, SW19 4AB (United Kingdom)

2014-06-26

We study a Simple Route for constructing the higher order Bagger-Lambert-Gustavsson theory - both supersymmetry transformations and Lagrangian - starting from knowledge of only the 10-dimensional Super Yang Mills Fermion Supersymmetry transformation. We are able to uniquely determine the four-derivative order corrected supersymmetry transformations, to lowest non-trivial order in Fermions, for the most general three-algebra theory. For the special case of Euclidean three-algbera, we reproduce the result presented in arXiv:1207.1208, with significantly less labour. In addition, we apply our method to calculate the quadratic fermion terms in the higher order BLG fermion supersymmetry transformation.

Video surveillance using distance maps

Science.gov (United States)

Schouten, Theo E.; Kuppens, Harco C.; van den Broek, Egon L.

2006-02-01

Human vigilance is limited; hence, automatic motion and distance detection is one of the central issues in video surveillance. Hereby, many aspects are of importance, this paper specially addresses: efficiency, achieving real-time performance, accuracy, and robustness against various noise factors. To obtain fully controlled test environments, an artificial development center for robot navigation is introduced in which several parameters can be set (e.g., number of objects, trajectories and type and amount of noise). In the videos, for each following frame, movement of stationary objects is detected and pixels of moving objects are located from which moving objects are identified in a robust way. An Exact Euclidean Distance Map (E2DM) is utilized to determine accurately the distances between moving and stationary objects. Together with the determined distances between moving objects and the detected movement of stationary objects, this provides the input for detecting unwanted situations in the scene. Further, each intelligent object (e.g., a robot), is provided with its E2DM, allowing the object to plan its course of action. Timing results are specified for each program block of the processing chain for 20 different setups. So, the current paper presents extensive, experimentally controlled research on real-time, accurate, and robust motion detection for video surveillance, using E2DMs, which makes it a unique approach.

Mixed Volume and Distance Geometry Techniques for Counting Euclidean Embeddings of Rigid Graphs

NARCIS (Netherlands)

I.Z. Emiris; E.P. Tsigaridas; A. Varvitsiotis (Antonios); A. Mucherino (Antonio); C. Lavor; L. Liberti; N. Maculan

2013-01-01

htmlabstractA graph G is called generically minimally rigid in Rd if, for any choice of sufficiently generic edge lengths, it can be embedded in Rd in a finite number of distinct ways, modulo rigid transformations. Here, we deal with the problem of determining tight bounds on the number of such

Physical interpretation and geometrical representation of constant curvature surfaces in Euclidean and pseudo-Euclidean spaces

International Nuclear Information System (INIS)

Catoni, Francesco; Cannata, Roberto; Zampetti, Paolo

2005-08-01

The Riemann and Lorentz constant curvature surfaces are investigated from an Euclidean point of view. The four surfaces (constant positive and constant negative curvatures with definite and non-definite fine elements) are represented as surfaces in a Riemannian or in a particular semi-Riemannian flat space and it is shown that the complex and the hyperbolic numbers allow to obtain the same equations for the corresponding Riemann and Lorentz surfaces, respectively. Moreover it is shown that the geodesics on the Lorentz surfaces states, from a physical point of view, a link between curvature and fields. This result is obtained just as a consequence of the space-time geometrical symmetry, without invoking the famous Einstein general relativity postulate [it

On Euclidean connections for su(1,1), suq(1,1) and the algebraic approach to scattering

International Nuclear Information System (INIS)

Ionescu, R.A.

1994-11-01

We obtain a general Euclidean connection for su(1,1) and suq(1,1) algebras. Our Euclidean connection allows an algebraic derivation for the S matrix. These algebraic S matrices reduce to the known ones in suitable circumstances. Also, we obtain a map between su(1,1) and su q (1,1) representations. (author). 8 refs

The Role of Structure in Learning Non-Euclidean Geometry

Science.gov (United States)

Asmuth, Jennifer A.

2009-01-01

How do people learn novel mathematical information that contradicts prior knowledge? The focus of this thesis is the role of structure in the acquisition of knowledge about hyperbolic geometry, a non-Euclidean geometry. In a series of three experiments, I contrast a more holistic structure--training based on closed figures--with a mathematically…

Exploring Concepts of Geometry not Euclidean

Directory of Open Access Journals (Sweden)

Luiz Ambrozi

2016-02-01

Full Text Available With this article we intend to propose different situations of teaching and learning, how they can be applied in schools, mediated by the use of concrete materials and Geogebra software, emphasizing the use of technology in the classroom, that this proposal has the role of assisting in the conceptualization and identification of elements of non-Euclidean geometry. In addition, this short course is designed to be a time of current and continuing education for teachers, with activities to be developed with dynamic geometry and based on the theory of Conceptual Fields of Vergnaud.

Bochner-Riesz means on Euclidean spaces

CERN Document Server

Lu, Shanzhen

2013-01-01

This book mainly deals with the Bochner-Riesz means of multiple Fourier integral and series on Euclidean spaces. It aims to give a systematical introduction to the fundamental theories of the Bochner-Riesz means and important achievements attained in the last 50 years. For the Bochner-Riesz means of multiple Fourier integral, it includes the Fefferman theorem which negates the Disc multiplier conjecture, the famous Carleson-Sjölin theorem, and Carbery-Rubio de Francia-Vega's work on almost everywhere convergence of the Bochner-Riesz means below the critical index. For the Bochner-Riesz means o

Perturbative renormalization of composite operators via flow equations. Pt. 2. Short distance expansion

Energy Technology Data Exchange (ETDEWEB)

Keller, G. (Max-Planck-Institut fuer Physik, Muenchen (Germany). Werner-Heisenberg-Institut); Kopper, C. (Goettingen Univ. (Germany). Inst. fuer Theoretische Physik)

1993-04-01

We give a rigorous and very detailed derivation of the short distance expansion for a product of two arbitrary composite operators in the framework of the perturbative Euclidean massive [Phi][sub 4][sup 4]. The technically almost trivial proof rests on an extension of the differential flow equation method to Green functions with bilocal insertions, for which we also establish a set of generalized Zimmermann identities and Lowenstein rules. (orig.).

Application of affinity propagation algorithm based on manifold distance for transformer PD pattern recognition

Science.gov (United States)

Wei, B. G.; Huo, K. X.; Yao, Z. F.; Lou, J.; Li, X. Y.

2018-03-01

It is one of the difficult problems encountered in the research of condition maintenance technology of transformers to recognize partial discharge (PD) pattern. According to the main physical characteristics of PD, three models of oil-paper insulation defects were set up in laboratory to study the PD of transformers, and phase resolved partial discharge (PRPD) was constructed. By using least square method, the grey-scale images of PRPD were constructed and features of each grey-scale image were 28 box dimensions and 28 information dimensions. Affinity propagation algorithm based on manifold distance (AP-MD) for transformers PD pattern recognition was established, and the data of box dimension and information dimension were clustered based on AP-MD. Study shows that clustering result of AP-MD is better than the results of affinity propagation (AP), k-means and fuzzy c-means algorithm (FCM). By choosing different k values of k-nearest neighbor, we find clustering accuracy of AP-MD falls when k value is larger or smaller, and the optimal k value depends on sample size.

Pearson's Correlation between Three Variables; Using Students' Basic Knowledge of Geometry for an Exercise in Mathematical Statistics

Science.gov (United States)

Vos, Pauline

2009-01-01

When studying correlations, how do the three bivariate correlation coefficients between three variables relate? After transforming Pearson's correlation coefficient r into a Euclidean distance, undergraduate students can tackle this problem using their secondary school knowledge of geometry (Pythagoras' theorem and similarity of triangles).…

What does the Euclidean pseudoparticle do in Minkowski space

International Nuclear Information System (INIS)

Ju, I.

1978-08-01

Self dual pseudoparticle solutions for the classical Yang--Mills field equation with finite action have been constructed in Minkowski space. It is shown that the topological structures apparent in Euclidean space are no longer present in Minkowski space. Topological charges become fractional leading to the unquantized axial charge violation in the process involving fermions. 17 references

Fast Transform Decoding Of Nonsystematic Reed-Solomon Codes

Science.gov (United States)

Truong, Trieu-Kie; Cheung, Kar-Ming; Shiozaki, A.; Reed, Irving S.

1992-01-01

Fast, efficient Fermat number transform used to compute F'(x) analogous to computation of syndrome in conventional decoding scheme. Eliminates polynomial multiplications and reduces number of multiplications in reconstruction of F'(x) to n log (n). Euclidean algorithm used to evaluate F(x) directly, without going through intermediate steps of solving error-locator and error-evaluator polynomials. Algorithm suitable for implementation in very-large-scale integrated circuits.

Non-Euclidean geometry and curvature two-dimensional spaces, volume 3

CERN Document Server

Cannon, James W

2017-01-01

This is the final volume of a three volume collection devoted to the geometry, topology, and curvature of 2-dimensional spaces. The collection provides a guided tour through a wide range of topics by one of the twentieth century's masters of geometric topology. The books are accessible to college and graduate students and provide perspective and insight to mathematicians at all levels who are interested in geometry and topology. Einstein showed how to interpret gravity as the dynamic response to the curvature of space-time. Bill Thurston showed us that non-Euclidean geometries and curvature are essential to the understanding of low-dimensional spaces. This third and final volume aims to give the reader a firm intuitive understanding of these concepts in dimension 2. The volume first demonstrates a number of the most important properties of non-Euclidean geometry by means of simple infinite graphs that approximate that geometry. This is followed by a long chapter taken from lectures the author gave at MSRI, wh...

From Euclidean to Minkowski space with the Cauchy-Riemann equations

International Nuclear Information System (INIS)

Gimeno-Segovia, Mercedes; Llanes-Estrada, Felipe J.

2008-01-01

We present an elementary method to obtain Green's functions in non-perturbative quantum field theory in Minkowski space from Green's functions calculated in Euclidean space. Since in non-perturbative field theory the analytical structure of amplitudes often is unknown, especially in the presence of confined fields, dispersive representations suffer from systematic uncertainties. Therefore, we suggest to use the Cauchy-Riemann equations, which perform the analytical continuation without assuming global information on the function in the entire complex plane, but only in the region through which the equations are solved. We use as example the quark propagator in Landau gauge quantum chromodynamics, which is known from lattice and Dyson-Schwinger studies in Euclidean space. The drawback of the method is the instability of the Cauchy-Riemann equations against high-frequency noise,which makes it difficult to achieve good accuracy. We also point out a few curious details related to the Wick rotation. (orig.)

Micrononcasual Euclidean wave functions

International Nuclear Information System (INIS)

Enatsu, H.; Takenaka, A.; Okazaki, M.

1978-01-01

A theory which describes the internal attributes of hadrons in terms of space-time wave functions is presented. In order to develop the theory on the basis of a rather realistic model, covariant wave equations are first derived for the deuteron, in which the co-ordinates of the centre of mass of two nucleons can be defined unambiguously. Then the micro-noncasual behaviour of virtual mesons mediating between the two nucleons is expressed by means of wave functions depending only on the relative Euclidean co-ordinates with respect to the centre of mass of the two nucleons; the wave functions are assumed to obey the 0 4 and SU 2 x SU 2 groups. The properties of the wave functions under space inversion, time reversal and particle-antiparticle conjugation are investigated. It is found that the internal attributes of the mesons, such as spin, isospin, strangeness, intrinsic parity, charge parity and G-parity are explained consistently. The theory is applicable also to the case of baryons

The toroidal Hausdorff dimension of 2d Euclidean quantum gravity

DEFF Research Database (Denmark)

Ambjorn, Jan; Budd, Timothy George

2013-01-01

The lengths of shortest non-contractible loops are studied numerically in 2d Euclidean quantum gravity on a torus coupled to conformal field theories with central charge less than one. We find that the distribution of these geodesic lengths displays a scaling in agreement with a Hausdorff dimension...

A Low-Complexity Euclidean Orthogonal LDPC Architecture for Low Power Applications.

Science.gov (United States)

Revathy, M; Saravanan, R

2015-01-01

Low-density parity-check (LDPC) codes have been implemented in latest digital video broadcasting, broadband wireless access (WiMax), and fourth generation of wireless standards. In this paper, we have proposed a high efficient low-density parity-check code (LDPC) decoder architecture for low power applications. This study also considers the design and analysis of check node and variable node units and Euclidean orthogonal generator in LDPC decoder architecture. The Euclidean orthogonal generator is used to reduce the error rate of the proposed LDPC architecture, which can be incorporated between check and variable node architecture. This proposed decoder design is synthesized on Xilinx 9.2i platform and simulated using Modelsim, which is targeted to 45 nm devices. Synthesis report proves that the proposed architecture greatly reduces the power consumption and hardware utilizations on comparing with different conventional architectures.

A Low-Complexity Euclidean Orthogonal LDPC Architecture for Low Power Applications

Directory of Open Access Journals (Sweden)

M. Revathy

2015-01-01

Full Text Available Low-density parity-check (LDPC codes have been implemented in latest digital video broadcasting, broadband wireless access (WiMax, and fourth generation of wireless standards. In this paper, we have proposed a high efficient low-density parity-check code (LDPC decoder architecture for low power applications. This study also considers the design and analysis of check node and variable node units and Euclidean orthogonal generator in LDPC decoder architecture. The Euclidean orthogonal generator is used to reduce the error rate of the proposed LDPC architecture, which can be incorporated between check and variable node architecture. This proposed decoder design is synthesized on Xilinx 9.2i platform and simulated using Modelsim, which is targeted to 45 nm devices. Synthesis report proves that the proposed architecture greatly reduces the power consumption and hardware utilizations on comparing with different conventional architectures.

Membrane paradigm and entropy of black holes in the Euclidean action approach

International Nuclear Information System (INIS)

Lemos, Jose P. S.; Zaslavskii, Oleg B.

2011-01-01

The membrane paradigm approach to black holes fixes in the vicinity of the event horizon a fictitious surface, the stretched horizon, so that the spacetime outside remains unchanged and the spacetime inside is vacuum. Using this powerful method, several black hole properties have been found and settled, such as the horizon's viscosity, electrical conductivity, resistivity, as well as other properties. On the other hand, the Euclidean action approach to black hole spacetimes has been very fruitful in understanding black hole entropy. Combining both the Euclidean action and membrane paradigm approaches, a direct derivation of the black hole entropy is given. In the derivation, it is considered that the only fields present are the gravitational and matter fields, with no electric field.

Gender Differences in Knee Joint Congruity Quantified from MRI

DEFF Research Database (Denmark)

Tummala, Sudhakar; Schiphof, Dieuwke; Byrjalsen, Inger

2018-01-01

was located and quantified using Euclidean distance transform. Furthermore, the CI was quantified over the contact area by assessing agreement of the first- and second-order general surface features. Then, the gender differences between CA and CI values were evaluated at different stages of radiographic OA...

Pythagoras's theorem on a two-dimensional lattice from a 'natural' Dirac operator and Connes's distance formula

Energy Technology Data Exchange (ETDEWEB)

Dai Jian [Theory Group, Department of Physics, Peking University, Beijing (China)]. E-mail: jdai@mail.phy.pku.edu.cn; Song Xingchang [Theory Group, Department of Physics, Peking University, Beijing (China)]. E-mail: songxc@ibm320h.phy.pku.edu.cn

2001-07-13

One of the key ingredients of Connes's noncommutative geometry is a generalized Dirac operator which induces a metric (Connes's distance) on the pure state space. We generalize such a Dirac operator devised by Dimakis et al, whose Connes distance recovers the linear distance on an one-dimensional lattice, to the two-dimensional case. This Dirac operator has the local eigenvalue property and induces a Euclidean distance on this two-dimensional lattice, which is referred to as 'natural'. This kind of Dirac operator can be easily generalized into any higher-dimensional lattices. (author)

Distance-Based Phylogenetic Methods Around a Polytomy.

Science.gov (United States)

Davidson, Ruth; Sullivant, Seth

2014-01-01

Distance-based phylogenetic algorithms attempt to solve the NP-hard least-squares phylogeny problem by mapping an arbitrary dissimilarity map representing biological data to a tree metric. The set of all dissimilarity maps is a Euclidean space properly containing the space of all tree metrics as a polyhedral fan. Outputs of distance-based tree reconstruction algorithms such as UPGMA and neighbor-joining are points in the maximal cones in the fan. Tree metrics with polytomies lie at the intersections of maximal cones. A phylogenetic algorithm divides the space of all dissimilarity maps into regions based upon which combinatorial tree is reconstructed by the algorithm. Comparison of phylogenetic methods can be done by comparing the geometry of these regions. We use polyhedral geometry to compare the local nature of the subdivisions induced by least-squares phylogeny, UPGMA, and neighbor-joining when the true tree has a single polytomy with exactly four neighbors. Our results suggest that in some circumstances, UPGMA and neighbor-joining poorly match least-squares phylogeny.

Evaluation of gene-expression clustering via mutual information distance measure

Directory of Open Access Journals (Sweden)

Maimon Oded

2007-03-01

Full Text Available Abstract Background The definition of a distance measure plays a key role in the evaluation of different clustering solutions of gene expression profiles. In this empirical study we compare different clustering solutions when using the Mutual Information (MI measure versus the use of the well known Euclidean distance and Pearson correlation coefficient. Results Relying on several public gene expression datasets, we evaluate the homogeneity and separation scores of different clustering solutions. It was found that the use of the MI measure yields a more significant differentiation among erroneous clustering solutions. The proposed measure was also used to analyze the performance of several known clustering algorithms. A comparative study of these algorithms reveals that their "best solutions" are ranked almost oppositely when using different distance measures, despite the found correspondence between these measures when analysing the averaged scores of groups of solutions. Conclusion In view of the results, further attention should be paid to the selection of a proper distance measure for analyzing the clustering of gene expression data.

A Framework for Generalising the Newton Method and Other Iterative Methods from Euclidean Space to Manifolds

OpenAIRE

Manton, Jonathan H.

2012-01-01

The Newton iteration is a popular method for minimising a cost function on Euclidean space. Various generalisations to cost functions defined on manifolds appear in the literature. In each case, the convergence rate of the generalised Newton iteration needed establishing from first principles. The present paper presents a framework for generalising iterative methods from Euclidean space to manifolds that ensures local convergence rates are preserved. It applies to any (memoryless) iterative m...

On the Convergence and Law of Large Numbers for the Non-Euclidean Lp -Means

Directory of Open Access Journals (Sweden)

George Livadiotis

2017-05-01

Full Text Available This paper describes and proves two important theorems that compose the Law of Large Numbers for the non-Euclidean L p -means, known to be true for the Euclidean L 2 -means: Let the L p -mean estimator, which constitutes the specific functional that estimates the L p -mean of N independent and identically distributed random variables; then, (i the expectation value of the L p -mean estimator equals the mean of the distributions of the random variables; and (ii the limit N → ∞ of the L p -mean estimator also equals the mean of the distributions.

Singular Minkowski and Euclidean solutions for SU(2) Yang-Mills theory

International Nuclear Information System (INIS)

Singleton, D.

1996-01-01

In this paper it is examined a solution to the SU(2) Yang-Mills-Higgs system, which is a trivial mathematical extension of recently discovered Schwarzschild- like solutions (Singleton D., Phys. Rev. D, 51 (1955) 5911). Physically, however, this new solution has drastically different properties from the Schwarzschild-like solutions. It is also studied a new classical solution for Euclidean SU(2) Yang-Mills theory. Again this new solution is a mathematically trivial extension of the Belavin-Polyakov-Schwartz-Tyupkin (BPST) (Belavin A. A. et al., Phys. Lett. B, 59 (1975) 85) instanton, but is physically very different. Unlike the usual instanton solution, the present solution is singular on a sphere of arbitrary radius in Euclidean space. Both of these solutions are infinite-energy solutions, so their practical value is somewhat unclear. However, they may be useful in exploring some of the mathematical aspects of classical Yang-Mills theory

A fixed point approach to the Green's functions of PHI42: Local exsistence of the Borel transforms

International Nuclear Information System (INIS)

Bros, J.; Iagolnitzer, D.

1981-01-01

We prove the existence at small μ of a unique solution of the system B = M(B) to be satisfied by the set of Borel transformed euclidean Green's functions of a PHI 4 2 theory, μ being the Borel conjugate variable of the coupling lambda. As a byproduct, a new proof of convergence of the Borel transformed perturbative series is obtained. (orig.)

Euclidean supergravity and multi-centered solutions

Directory of Open Access Journals (Sweden)

W.A. Sabra

2017-04-01

Full Text Available In ungauged supergravity theories, the no-force condition for BPS states implies the existence of stable static multi-centered solutions. The first solutions to Einstein–Maxwell theory with a positive cosmological constant describing an arbitrary number of charged black holes were found by Kastor and Traschen. Generalisations to five and higher dimensional theories were obtained by London. Multi-centered solutions in gauged supergravity, even with time-dependence allowed, have yet to be constructed. In this letter we construct supersymmetry-preserving multi-centered solutions for the case of D=5, N=2 Euclidean gauged supergravity coupled to an arbitrary number of vector multiplets. Higher dimensional Einstein–Maxwell multi-centered solutions are also presented.

The imaginary-time path integral and non-time-reversal-invariant saddle points of the Euclidean action

International Nuclear Information System (INIS)

Dasgupta, I.

1998-01-01

We discuss new bounce-like (but non-time-reversal-invariant) solutions to Euclidean equations of motion, which we dub boomerons. In the Euclidean path integral approach to quantum theories, boomerons make an imaginary contribution to the vacuum energy. The fake vacuum instability can be removed by cancelling boomeron contributions against contributions from time reversed boomerons (anti-boomerons). The cancellation rests on a sign choice whose significance is not completely understood in the path integral method. (orig.)

Euclidean scalar field theory in the bilocal approximation

Science.gov (United States)

Nagy, S.; Polonyi, J.; Steib, I.

2018-04-01

The blocking step of the renormalization group method is usually carried out by restricting it to fluctuations and to local blocked action. The tree-level, bilocal saddle point contribution to the blocking, defined by the infinitesimal decrease of the sharp cutoff in momentum space, is followed within the three dimensional Euclidean ϕ6 model in this work. The phase structure is changed, new phases and relevant operators are found, and certain universality classes are restricted by the bilocal saddle point.

Bayesian Maximum Entropy space/time estimation of surface water chloride in Maryland using river distances.

Science.gov (United States)

Jat, Prahlad; Serre, Marc L

2016-12-01

Widespread contamination of surface water chloride is an emerging environmental concern. Consequently accurate and cost-effective methods are needed to estimate chloride along all river miles of potentially contaminated watersheds. Here we introduce a Bayesian Maximum Entropy (BME) space/time geostatistical estimation framework that uses river distances, and we compare it with Euclidean BME to estimate surface water chloride from 2005 to 2014 in the Gunpowder-Patapsco, Severn, and Patuxent subbasins in Maryland. River BME improves the cross-validation R 2 by 23.67% over Euclidean BME, and river BME maps are significantly different than Euclidean BME maps, indicating that it is important to use river BME maps to assess water quality impairment. The river BME maps of chloride concentration show wide contamination throughout Baltimore and Columbia-Ellicott cities, the disappearance of a clean buffer separating these two large urban areas, and the emergence of multiple localized pockets of contamination in surrounding areas. The number of impaired river miles increased by 0.55% per year in 2005-2009 and by 1.23% per year in 2011-2014, corresponding to a marked acceleration of the rate of impairment. Our results support the need for control measures and increased monitoring of unassessed river miles. Copyright © 2016. Published by Elsevier Ltd.

An Initialization Method Based on Hybrid Distance for k-Means Algorithm.

Science.gov (United States)

Yang, Jie; Ma, Yan; Zhang, Xiangfen; Li, Shunbao; Zhang, Yuping

2017-11-01

The traditional [Formula: see text]-means algorithm has been widely used as a simple and efficient clustering method. However, the performance of this algorithm is highly dependent on the selection of initial cluster centers. Therefore, the method adopted for choosing initial cluster centers is extremely important. In this letter, we redefine the density of points according to the number of its neighbors, as well as the distance between points and their neighbors. In addition, we define a new distance measure that considers both Euclidean distance and density. Based on that, we propose an algorithm for selecting initial cluster centers that can dynamically adjust the weighting parameter. Furthermore, we propose a new internal clustering validation measure, the clustering validation index based on the neighbors (CVN), which can be exploited to select the optimal result among multiple clustering results. Experimental results show that the proposed algorithm outperforms existing initialization methods on real-world data sets and demonstrates the adaptability of the proposed algorithm to data sets with various characteristics.

The non-Euclidean revolution with an introduction by H.S.M. Coxeter

CERN Document Server

Trudeau, Richard J

2001-01-01

How unique and definitive is Euclidean geometry in describing the "real" space in which we live? Richard Trudeau confronts the fundamental question of truth and its representation through mathematical models in The Non-Euclidean Revolution. First, the author analyzes geometry in its historical and philosophical setting; second, he examines a revolution every bit as significant as the Copernican revolution in astronomy and the Darwinian revolution in biology; third, on the most speculative level, he questions the possibility of absolute knowledge of the world. Trudeau writes in a lively, entertaining, and highly accessible style. His book provides one of the most stimulating and personal presentations of a struggle with the nature of truth in mathematics and the physical world. A portion of the book won the Pólya Prize, a distinguished award from the Mathematical Association of America.

Convergent perturbation expansions for Euclidean quantum field theory

International Nuclear Information System (INIS)

Mack, G.; Pordt, A.

1984-09-01

Mayer perturbation theory is designed to provide computable convergent expansions which permit calculation of Greens functions in Euclidean Quantum Field Theory to arbitrary accuracy, including 'nonperturbative' contributions from large field fluctuations. Here we describe the expansions at the example of 3-dimensional lambdaphi 4 -theory (in continuous space). They are not essentially more complicated than standard perturbation theory. The n-th order term is expressed in terms of 0(n)-dimensional integrals, and is of order lambda 4 if 4k-3<=n<=4k. (orig.)

ILUCG algorithm which minimizes in the Euclidean norm

International Nuclear Information System (INIS)

Petravic, M.; Kuo-Petravic, G.

1978-07-01

An algroithm is presented which solves sparse systems of linear equations of the form Ax = Y, where A is non-symmetric, by the Incomplete LU Decomposition-Conjugate Gradient (ILUCG) method. The algorithm minimizes the error in the Euclidean norm vertical bar x/sub i/ - x vertical bar 2 , where x/sub i/ is the solution vector after the i/sup th/ iteration and x the exact solution vector. The results of a test on one real problem indicate that the algorithm is likely to be competitive with the best existing algorithms of its type

A strong coupling simulation of Euclidean quantum gravity

International Nuclear Information System (INIS)

Berg, B.; Hamburg Univ.

1984-12-01

Relying on Regge calculus a systematic numerical investigation of models of 4d Euclidean gravity is proposed. The scale a = 1 0 is set by fixing the expectation value of a length. Possible universality of such models is discussed. The strong coupling limit is defined by taking Planck mass msub(p) -> 0 (in units of 1 0 -1 ). The zero order approximation msub(p) = 0 is called 'fluctuating space' and investigated numerically in two 4d models. Canonical dimensions are realized and both models give a negative expectation value for the scalar curvature density. (orig.)

Structure functions at small xBj in a Euclidean field theory approach

International Nuclear Information System (INIS)

Hebecker, A.; Meggiolaro, E.; Nachtmann, O.

2000-01-01

The small-x Bj limit of deep inelastic scattering is related to the high-energy limit of the forward Compton amplitude in a familiar way. We show that the analytic continuation of this amplitude in the energy variable is calculable from a matrix element in Euclidean field theory. This matrix element can be written as a Euclidean functional integral in an effective field theory. Its effective Lagrangian has a simple expression in terms of the original Lagrangian. The functional integral expression obtained can, at least in principle, be evaluated using genuinely non-perturbative methods, e.g., on the lattice. Thus, a fundamentally new approach to the long-standing problem of structure functions at very small x Bj seems possible. We give arguments that the limit x Bj →0 corresponds to a critical point of the effective field theory where the correlation length becomes infinite in one direction

The data singular and the data isotropic loci for affine cones

NARCIS (Netherlands)

Horobet, E.

2015-01-01

The generic number of critical points of the Euclidean distance function from a data point to a variety is called the Euclidean distance degree. The two special loci of the data points where the number of critical points is smaller then the ED degree are called the Euclidean Distance Data Singular

Visual Analytics for Exploration of a High-Dimensional Structure

Science.gov (United States)

2013-04-01

5 Figure 3. Comparison of Euclidean vs. geodesic distance. LDRs use ...manifold, whereas an LDR fails. ...........................6 Figure 4. WEKA GUI for data mining HDD using FRFS-ACO...of Euclidean vs. geodesic distance. LDRs use metrics based on the Euclidean distance between two points, while the NLDRs are based on geodesic

Usability Evaluation of an Augmented Reality System for Teaching Euclidean Vectors

Science.gov (United States)

Martin-Gonzalez, Anabel; Chi-Poot, Angel; Uc-Cetina, Victor

2016-01-01

Augmented reality (AR) is one of the emerging technologies that has demonstrated to be an efficient technological tool to enhance learning techniques. In this paper, we describe the development and evaluation of an AR system for teaching Euclidean vectors in physics and mathematics. The goal of this pedagogical tool is to facilitate user's…

Loci of points in the Euclidean plane are deter- mined from ...

Indian Academy of Sciences (India)

Loci of points in the Euclidean plane are deter- mined from prescribed relations of the points with given points, and/or, lines. The depen- dence of these relations on parameters lead to the differential equations representing the fam- ily of loci under concern. Incidentally most of the differential equations thus obtained are non ...

The data singular and the data isotropic loci for affine cones

NARCIS (Netherlands)

Horobet, E.

2017-01-01

The generic number of critical points of the Euclidean distance function from a data point to a variety is called the Euclidean distance degree (or ED degree). The two special loci of the data points where the number of critical points is smaller than the ED degree are called the Euclidean distance

Euclidean mirrors. Enhanced vacuum decay from reflected instantons

Energy Technology Data Exchange (ETDEWEB)

Akal, Ibrahim [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany). Theory Group; Moortgat-Pick, Gudrid [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik

2017-06-15

We study the tunneling of virtual matter-antimatter pairs from the quantum vacuum in the presence of a spatially uniform temporal electric background composed of of a strong slow field superimposed with a weak rapid field. After analytic continuation to Euclidean spacetime we obtain from the instanton equations two critical points. While one of them is the closing point of the instanton path, the other serves as an Euclidean mirror which reflects and squeezes the instanton. It is this reflection and shrinking which is responsible for an enormous enhancement of the vacuum pair production rate. We discuss how important features of this mechanism can be analysed and understood via such a rotation in the complex plane. Consistent with previous studies, we consider certain examples where we apply weak fields with a distinct pole structure in order to show that the reflection takes place exactly at the poles. We also discuss the effect of possible sub-cycle structures. We extend this reflection picture to fields which have no poles present and illustrate the effective reflections with explicit examples. An additional field strength dependence for the rate occurs in such cases. We analytically compute the characteristic threshold for this mechanism given by the critical combined Keldysh parameter. We discuss significant differences between these two types of fields. For various backgrounds, we present the contributing instantons and perform analytical computations for the corresponding rates treating both fields nonperturbatively. The validity of the results is confirmed by numerical computations. Considering different profiles for the strong field, we also discuss its impact on the critical combined Keldysh parameter.

The G_Newton --> 0 Limit of Euclidean Quantum Gravity

OpenAIRE

Smolin, Lee

1992-01-01

Using the Ashtekar formulation, it is shown that the G_{Newton} --> 0 limit of Euclidean or complexified general relativity is not a free field theory, but is a theory that describes a linearized self-dual connection propagating on an arbitrary anti-self-dual background. This theory is quantized in the loop representation and, as in the full theory, an infinite dimnensional space of exact solutions to the constraint is found. An inner product is also proposed. The path integral is constructed...

Euclidean Monte Carlo simulation of nuclear interactions

International Nuclear Information System (INIS)

Montvay, Istvan; Bonn Univ.; Urbach, Carsten

2011-05-01

We present an exploratory study of chiral effective theories of nuclei with methods adopted from lattice quantum chromodynamics (QCD). We show that the simulations in the Euclidean path integral approach are feasible and that we can determine the energy of the two nucleon state. By varying the parameters and the simulated volumes phase shifts can be determined in principle and hopefully tuned to their physical values in the future. The physical cut-off of the theory is realised by blocking of the lattice fields. By keeping this physical cut-off fixed in physical units the lattice cut-off can be changed and in this way the lattice artefacts can be eliminated. (orig.)

Faster exact algorithms for computing Steiner trees in higher dimensional Euclidean spaces

DEFF Research Database (Denmark)

Fonseca, Rasmus; Brazil, Marcus; Winter, Pawel

The Euclidean Steiner tree problem asks for a network of minimum total length interconnecting a finite set of points in d-dimensional space. For d ≥ 3, only one practical algorithmic approach exists for this problem --- proposed by Smith in 1992. A number of refinements of Smith's algorithm have...

Variational estimates for the mass gap of SU(2) Euclidean lattice gauge theory

International Nuclear Information System (INIS)

Hari Dass, N.D.

1984-10-01

The purpose of this letter is to report on the progress made in our understanding of series expansions for the masses in lattice gauge theories by the application of variational techniques to the Euclidean SU(2) lattice gauge theory. (Auth.)

Landscape features influence gene flow as measured by cost-distance and genetic analyses: a case study for giant pandas in the Daxiangling and Xiaoxiangling Mountains

Directory of Open Access Journals (Sweden)

Wei Fuwen

2010-07-01

Full Text Available Abstract Background Gene flow maintains genetic diversity within a species and is influenced by individual behavior and the geographical features of the species' habitat. Here, we have characterized the geographical distribution of genetic patterns in giant pandas (Ailuropoda melanoleuca living in four isolated patches of the Xiaoxiangling and Daxiangling Mountains. Three geographic distance definitions were used with the "isolation by distance theory": Euclidean distance (EUD, least-cost path distance (LCD defined by food resources, and LCD defined by habitat suitability. Results A total of 136 genotypes were obtained from 192 fecal samples and one blood sample, corresponding to 53 unique genotypes. Geographical maps plotted at high resolution using smaller neighborhood radius definitions produced large cost distances, because smaller radii include a finer level of detail in considering each pixel. Mantel tests showed that most correlation indices, particularly bamboo resources defined for different sizes of raster cell, were slightly larger than the correlations calculated for the Euclidean distance, with the exception of Patch C. We found that natural barriers might have decreased gene flow between the Xiaoxiangling and Daxiangling regions. Conclusions Landscape features were found to partially influence gene flow in the giant panda population. This result is closely linked to the biological character and behavior of giant pandas because, as bamboo feeders, individuals spend most of their lives eating bamboo or moving within the bamboo forest. Landscape-based genetic analysis suggests that gene flow will be enhanced if the connectivity between currently fragmented bamboo forests is increased.

General Nth order integrals of motion in the Euclidean plane

International Nuclear Information System (INIS)

Post, S; Winternitz, P

2015-01-01

The general form of an integral of motion that is a polynomial of order N in the momenta is presented for a Hamiltonian system in two-dimensional Euclidean space. The classical and the quantum cases are treated separately, emphasizing both the similarities and the differences between the two. The main application will be to study Nth order superintegrable systems that allow separation of variables in the Hamilton–Jacobi and Schrödinger equations, respectively. (paper)

A Class of Weingarten Surfaces in Euclidean 3-Space

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Yu Fu

2013-01-01

Full Text Available The class of biconservative surfaces in Euclidean 3-space 3 are defined in (Caddeo et al., 2012 by the equation A(grad H=-H grad H for the mean curvature function H and the Weingarten operator A. In this paper, we consider the more general case that surfaces in 3 satisfying A(grad H=kH grad H for some constant k are called generalized bi-conservative surfaces. We show that this class of surfaces are linear Weingarten surfaces. We also give a complete classification of generalized bi-conservative surfaces in 3.

Multi-stability in folded shells: non-Euclidean origami

Science.gov (United States)

Evans, Arthur

2015-03-01

Both natural and man-made structures benefit from having multiple mechanically stable states, from the quick snapping motion of hummingbird beaks to micro-textured surfaces with tunable roughness. Rather than discuss special fabrication techniques for creating bi-stability through material anisotropy, in this talk I will present several examples of how folding a structure can modify the energy landscape and thus lead to multiple stable states. Using ideas from origami and differential geometry, I will discuss how deforming a non-Euclidean surface can be done either continuously or discontinuously, and explore the effects that global constraints have on the ultimate stability of the surface.

Euclidean D-branes and higher-dimensional gauge theory

International Nuclear Information System (INIS)

Acharya, B.S.; Figueroa-O'Farrill, J.M.; Spence, B.; O'Loughlin, M.

1997-07-01

We consider euclidean D-branes wrapping around manifolds of exceptional holonomy in dimensions seven and eight. The resulting theory on the D-brane-that is, the dimensional reduction of 10-dimensional supersymmetric Yang-Mills theory-is a cohomological field theory which describes the topology of the moduli space of instantons. The 7-dimensional theory is an N T =2 (or balanced) cohomological theory given by an action potential of Chern-Simons type. As a by-product of this method, we construct a related cohomological field theory which describes the monopole moduli space on a 7-manifold of G 2 holonomy. (author). 22 refs, 3 tabs

The Euclidean three-point function in loop and perturbative gravity

International Nuclear Information System (INIS)

Rovelli, Carlo; Zhang Mingyi

2011-01-01

We compute the leading order of the three-point function in loop quantum gravity, using the vertex expansion of the Euclidean version of the new spin foam dynamics, in the region of γ < 1. We find results consistent with Regge calculus in the limit γ → 0, j → ∞. We also compute the tree-level three-point function of perturbative quantum general relativity in position space and discuss the possibility of directly comparing the two results.

On the Schroedinger representation of the Euclidean quantum field theory

International Nuclear Information System (INIS)

Semmler, U.

1987-04-01

The theme of the present thesis is the Schroedinger representation of the Euclidean quantum field theory: We define the time development of the quantum field states as functional integral in a novel, mathematically precise way. In the following we discuss the consequences which result from this approach to the Euclidean quantum field theory. Chapter 1 introduces the theory of abstract Wiener spaces which is here proved as suitable mathematical tool for the treatment of the physical problems. In chapter 2 the diffusion theory is formulated in the framework of abstract Wiener spaces. In chapter 3 we define the field functional ψ 5 u, t 7 as functional integral, determine the functional differential equation which ψ satisfies (Schroedinger equation), and summarize the consequences resulting from this. Chapter 4 is dedicated to the attempt to determine the kernel of the time-development operator, by the knowledge of which the time development of each initial state is fixed. In chapter 5 the consequences of the theory presented in chapter 3 and 4 are discussed by means of simple examples. In chapter 6 the renormalization which results for the φ 4 potential from the definition of the functional integral in chapter 3 is calculated up to the first-order perturbation theory, and it is shown that the problems in the Symanzik renormalization procedure can be removed. (orig./HSI) [de

Euclidean mirrors: enhanced vacuum decay from reflected instantons

Science.gov (United States)

Akal, Ibrahim; Moortgat-Pick, Gudrid

2018-05-01

We study the tunnelling of virtual matter–antimatter pairs from the quantum vacuum in the presence of a spatially uniform, time-dependent electric background composed of a strong, slow field superimposed with a weak, rapid field. After analytic continuation to Euclidean spacetime, we obtain from the instanton equations two critical points. While one of them is the closing point of the instanton path, the other serves as an Euclidean mirror which reflects and squeezes the instanton. It is this reflection and shrinking which is responsible for an enormous enhancement of the vacuum pair production rate. We discuss how important features of two different mechanisms can be analysed and understood via such a rotation in the complex plane. (a) Consistent with previous studies, we first discuss the standard assisted mechanism with a static strong field and certain weak fields with a distinct pole structure in order to show that the reflection takes place exactly at the poles. We also discuss the effect of possible sub-cycle structures. We extend this reflection picture then to weak fields which have no poles present and illustrate the effective reflections with explicit examples. An additional field strength dependence for the rate occurs in such cases. We analytically compute the characteristic threshold for the assisted mechanism given by the critical combined Keldysh parameter. We discuss significant differences between these two types of fields. For various backgrounds, we present the contributing instantons and perform analytical computations for the corresponding rates treating both fields nonperturbatively. (b) In addition, we also study the case with a nonstatic strong field which gives rise to the assisted dynamical mechanism. For different strong field profiles we investigate the impact on the critical combined Keldysh parameter. As an explicit example, we analytically compute the rate by employing the exact reflection points. The validity of the predictions

Fault Diagnosis of Supervision and Homogenization Distance Based on Local Linear Embedding Algorithm

Directory of Open Access Journals (Sweden)

Guangbin Wang

2015-01-01

Full Text Available In view of the problems of uneven distribution of reality fault samples and dimension reduction effect of locally linear embedding (LLE algorithm which is easily affected by neighboring points, an improved local linear embedding algorithm of homogenization distance (HLLE is developed. The method makes the overall distribution of sample points tend to be homogenization and reduces the influence of neighboring points using homogenization distance instead of the traditional Euclidean distance. It is helpful to choose effective neighboring points to construct weight matrix for dimension reduction. Because the fault recognition performance improvement of HLLE is limited and unstable, the paper further proposes a new local linear embedding algorithm of supervision and homogenization distance (SHLLE by adding the supervised learning mechanism. On the basis of homogenization distance, supervised learning increases the category information of sample points so that the same category of sample points will be gathered and the heterogeneous category of sample points will be scattered. It effectively improves the performance of fault diagnosis and maintains stability at the same time. A comparison of the methods mentioned above was made by simulation experiment with rotor system fault diagnosis, and the results show that SHLLE algorithm has superior fault recognition performance.

Water quality assessment with hierarchical cluster analysis based on Mahalanobis distance.

Science.gov (United States)

Du, Xiangjun; Shao, Fengjing; Wu, Shunyao; Zhang, Hanlin; Xu, Si

2017-07-01

Water quality assessment is crucial for assessment of marine eutrophication, prediction of harmful algal blooms, and environment protection. Previous studies have developed many numeric modeling methods and data driven approaches for water quality assessment. The cluster analysis, an approach widely used for grouping data, has also been employed. However, there are complex correlations between water quality variables, which play important roles in water quality assessment but have always been overlooked. In this paper, we analyze correlations between water quality variables and propose an alternative method for water quality assessment with hierarchical cluster analysis based on Mahalanobis distance. Further, we cluster water quality data collected form coastal water of Bohai Sea and North Yellow Sea of China, and apply clustering results to evaluate its water quality. To evaluate the validity, we also cluster the water quality data with cluster analysis based on Euclidean distance, which are widely adopted by previous studies. The results show that our method is more suitable for water quality assessment with many correlated water quality variables. To our knowledge, it is the first attempt to apply Mahalanobis distance for coastal water quality assessment.

Improved target detection algorithm using Fukunaga-Koontz transform and distance classifier correlation filter

Science.gov (United States)

Bal, A.; Alam, M. S.; Aslan, M. S.

2006-05-01

Often sensor ego-motion or fast target movement causes the target to temporarily go out of the field-of-view leading to reappearing target detection problem in target tracking applications. Since the target goes out of the current frame and reenters at a later frame, the reentering location and variations in rotation, scale, and other 3D orientations of the target are not known thus complicating the detection algorithm has been developed using Fukunaga-Koontz Transform (FKT) and distance classifier correlation filter (DCCF). The detection algorithm uses target and background information, extracted from training samples, to detect possible candidate target images. The detected candidate target images are then introduced into the second algorithm, DCCF, called clutter rejection module, to determine the target coordinates are detected and tracking algorithm is initiated. The performance of the proposed FKT-DCCF based target detection algorithm has been tested using real-world forward looking infrared (FLIR) video sequences.

On infinitesimal increase of volumes of morphological transforms

DEFF Research Database (Denmark)

Kiderlen, Markus; Rataj, Jan

2007-01-01

Let B (“black”) and W (“white”) be disjoint compact test sets in the d-dimensional Euclidean space and consider the volume of all its simultaneous shifts keeping B inside and W outside a compact set A. If the union of B and W is rescaled by a factor tending to zero, then the rescaled volume...... for the hit-or-miss function. Secondly, in a design based setting, different random digitizations of a deterministic set A are treated. It is shown how the number of configurations in such a digitization is related to the surface area measure of A as the lattice distance converges to zero....

Exploring Cloud Computing for Distance Learning

Science.gov (United States)

He, Wu; Cernusca, Dan; Abdous, M'hammed

2011-01-01

The use of distance courses in learning is growing exponentially. To better support faculty and students for teaching and learning, distance learning programs need to constantly innovate and optimize their IT infrastructures. The new IT paradigm called "cloud computing" has the potential to transform the way that IT resources are utilized and…

Curvature-driven morphing of non-Euclidean shells

Science.gov (United States)

Pezzulla, Matteo; Stoop, Norbert; Jiang, Xin; Holmes, D. P.

2017-05-01

We investigate how thin structures change their shape in response to non-mechanical stimuli that can be interpreted as variations in the structure's natural curvature. Starting from the theory of non-Euclidean plates and shells, we derive an effective model that reduces a three-dimensional stimulus to the natural fundamental forms of the mid-surface of the structure, incorporating expansion, or growth, in the thickness. Then, we apply the model to a variety of thin bodies, from flat plates to spherical shells, obtaining excellent agreement between theory and numerics. We show how cylinders and cones can either bend more or unroll, and eventually snap and rotate. We also study the nearly isometric deformations of a spherical shell and describe how this shape change is ruled by the geometry of a spindle. As the derived results stem from a purely geometrical model, they are general and scalable.

Surface Design Based on Discrete Conformal Transformations

Science.gov (United States)

Duque, Carlos; Santangelo, Christian; Vouga, Etienne

Conformal transformations are angle-preserving maps from one domain to another. Although angles are preserved, the lengths between arbitrary points are not generally conserved. As a consequence there is always a given amount of distortion associated to any conformal map. Different uses of such transformations can be found in various fields, but have been used by us to program non-uniformly swellable gel sheets to buckle into prescribed three dimensional shapes. In this work we apply circle packings as a kind of discrete conformal map in order to find conformal maps from the sphere to the plane that can be used as nearly uniform swelling patterns to program non-Euclidean sheets to buckle into spheres. We explore the possibility of tuning the area distortion to fit the experimental range of minimum and maximum swelling by modifying the boundary of the planar domain through the introduction of different cutting schemes.

Transformation of Correspondence Education into Distance Education

Directory of Open Access Journals (Sweden)

Marjan Velej

1997-12-01

Full Text Available Since 1957 the Correspondence-Education Centre Univerzum has been involved in correspondence education, which - as a matter of principle - uses the written word as a basic and predorninam medium of instruction, ensuring a two­ directional communication between the teacher and the student. Following the world-wide trends in adult education, the institution has gradually updated its teaching methods by incorporating correspondence-consulting and correspondence-seminar methods. As a result of the forceful development of new technologies and media the written word has become only one among many media of instruction, replacing the concept of correspon­ dence education with that of distance education. Although the latter hasa num­ ber of advantages, it is rather difficult to implement. ln view of its role and in the interese of its own development, the Correspondence-Education Centre Univerzum is forced to effect the transition to distance education. In order to be able to effectively adopt new methods, extensive training has been organised for the teaching staff, the results of which are encouraging. They enable us to plan further changes and improvements of our methods of instruction.

Mayer expansions for Euclidean lattice field theory: Convergence properties and relation with perturbation theory

International Nuclear Information System (INIS)

Pordt, A.

1985-10-01

The author describes the Mayer expansion in Euclidean lattice field theory by comparing it with the statistical mechanics of polymer systems. In this connection he discusses the Borel summability and the analyticity of the activities on the lattice. Furthermore the relations between renormalization and the Mayer expansion are considered. (HSI)

Metric distances derived from cosine similarity and Pearson and Spearman correlations

OpenAIRE

van Dongen, Stijn; Enright, Anton J.

2012-01-01

We investigate two classes of transformations of cosine similarity and Pearson and Spearman correlations into metric distances, utilising the simple tool of metric-preserving functions. The first class puts anti-correlated objects maximally far apart. Previously known transforms fall within this class. The second class collates correlated and anti-correlated objects. An example of such a transformation that yields a metric distance is the sine function when applied to centered data.

Distance breached or distance transformed? Dilemmas of simulated and banal closeness in humanitarian communication

DEFF Research Database (Denmark)

Bajde, Domen; Knudsen, Gry Høngsmark

Social media have been argued to have transformed humanitarian communication and those involved in it. Networked humanitarian organizations are supposedly more open and transparent (Kanter and Fine 2010) and their “audiences” too are networked and "cause-wired" (Watson 2009), implying an unpreced......Social media have been argued to have transformed humanitarian communication and those involved in it. Networked humanitarian organizations are supposedly more open and transparent (Kanter and Fine 2010) and their “audiences” too are networked and "cause-wired" (Watson 2009), implying...

Forward looking anomaly detection via fusion of infrared and color imagery

Science.gov (United States)

Stone, K.; Keller, J. M.; Popescu, M.; Havens, T. C.; Ho, K. C.

2010-04-01

This paper develops algorithms for the detection of interesting and abnormal objects in color and infrared imagery taken from cameras mounted on a moving vehicle, observing a fixed scene. The primary purpose of detection is to cue a human-in-the-loop detection system. Algorithms for direct detection and change detection are investigated, as well as fusion of the two. Both methods use temporal information to reduce the number of false alarms. The direct detection algorithm uses image self-similarity computed between local neighborhoods to determine interesting, or unique, parts of an image. Neighborhood similarity is computed using Euclidean distance in CIELAB color space for the color imagery, and Euclidean distance between grey levels in the infrared imagery. The change detection algorithm uses the affine scale-invariant feature transform (ASIFT) to transform multiple background frames into the current image space. Each transformed image is then compared to the current image, and the multiple outputs are fused to produce a single difference image. Changes in lighting and contrast between the background run and the current run are adjusted for in both color and infrared imagery. Frame-to-frame motion is modeled using a perspective transformation, the parameters of which are computed using scale-invariant feature transform (SIFT) keypoint correspondences. This information is used to perform temporal accumulation of single frame detections for both the direct detection and change detection algorithms. Performance of the proposed algorithms is evaluated on multiple lanes from a data collection at a US Army test site.

Clifford coherent state transforms on spheres

Science.gov (United States)

Dang, Pei; Mourão, José; Nunes, João P.; Qian, Tao

2018-01-01

We introduce a one-parameter family of transforms, U(m)t,t > 0, from the Hilbert space of Clifford algebra valued square integrable functions on the m-dimensional sphere, L2(Sm , dσm) ⊗Cm+1, to the Hilbert spaces, ML2(R m + 1 ∖ { 0 } , dμt) , of solutions of the Euclidean Dirac equation on R m + 1 ∖ { 0 } which are square integrable with respect to appropriate measures, dμt. We prove that these transforms are unitary isomorphisms of the Hilbert spaces and are extensions of the Segal-Bargman coherent state transform, U(1) :L2(S1 , dσ1) ⟶ HL2(C ∖ { 0 } , dμ) , to higher dimensional spheres in the context of Clifford analysis. In Clifford analysis it is natural to replace the analytic continuation from Sm to SCm as in (Hall, 1994; Stenzel, 1999; Hall and Mitchell, 2002) by the Cauchy-Kowalewski extension from Sm to R m + 1 ∖ { 0 } . One then obtains a unitary isomorphism from an L2-Hilbert space to a Hilbert space of solutions of the Dirac equation, that is to a Hilbert space of monogenic functions.

Double peak-induced distance error in short-time-Fourier-transform-Brillouin optical time domain reflectometers event detection and the recovery method.

Science.gov (United States)

Yu, Yifei; Luo, Linqing; Li, Bo; Guo, Linfeng; Yan, Jize; Soga, Kenichi

2015-10-01

The measured distance error caused by double peaks in the BOTDRs (Brillouin optical time domain reflectometers) system is a kind of Brillouin scattering spectrum (BSS) deformation, discussed and simulated for the first time in the paper, to the best of the authors' knowledge. Double peak, as a kind of Brillouin spectrum deformation, is important in the enhancement of spatial resolution, measurement accuracy, and crack detection. Due to the variances of the peak powers of the BSS along the fiber, the measured starting point of a step-shape frequency transition region is shifted and results in distance errors. Zero-padded short-time-Fourier-transform (STFT) can restore the transition-induced double peaks in the asymmetric and deformed BSS, thus offering more accurate and quicker measurements than the conventional Lorentz-fitting method. The recovering method based on the double-peak detection and corresponding BSS deformation can be applied to calculate the real starting point, which can improve the distance accuracy of the STFT-based BOTDR system.

Surface-to-surface registration using level sets

DEFF Research Database (Denmark)

Hansen, Mads Fogtmann; Erbou, Søren G.; Vester-Christensen, Martin

2007-01-01

This paper presents a general approach for surface-to-surface registration (S2SR) with the Euclidean metric using signed distance maps. In addition, the method is symmetric such that the registration of a shape A to a shape B is identical to the registration of the shape B to the shape A. The S2SR...... problem can be approximated by the image registration (IR) problem of the signed distance maps (SDMs) of the surfaces confined to some narrow band. By shrinking the narrow bands around the zero level sets the solution to the IR problem converges towards the S2SR problem. It is our hypothesis...... that this approach is more robust and less prone to fall into local minima than ordinary surface-to-surface registration. The IR problem is solved using the inverse compositional algorithm. In this paper, a set of 40 pelvic bones of Duroc pigs are registered to each other w.r.t. the Euclidean transformation...

Exact Boson-Fermion Duality on a 3D Euclidean Lattice

Science.gov (United States)

Chen, Jing-Yuan; Son, Jun Ho; Wang, Chao; Raghu, S.

2018-01-01

The idea of statistical transmutation plays a crucial role in descriptions of the fractional quantum Hall effect. However, a recently conjectured duality between a critical boson and a massless two-component Dirac fermion extends this notion to gapless systems. This duality sheds light on highly nontrivial problems such as the half-filled Landau level, the superconductor-insulator transition, and surface states of strongly coupled topological insulators. Although this boson-fermion duality has undergone many consistency checks, it has remained unproven. We describe the duality in a nonperturbative fashion using an exact UV mapping of partition functions on a 3D Euclidean lattice.

The Bregman Variational Dual-Tree Framework

DEFF Research Database (Denmark)

Amizadeh, Saeed; Thiesson, Bo; Hauskrecht, Milos

2013-01-01

where the Euclidean distance quantifies the similarity. In this paper, we extend the VDT framework beyond the Euclidean distance to more general Bregman divergences that include the Euclidean distance as a special case. By exploiting the properties of the general Bregman divergence, we show how the new....... A significant effort to find more efficient solutions to the problem has been made in the literature. One of the state-of-the-art methods that has been recently introduced is the Variational Dual-Tree (VDT) framework. Despite some of its unique features, VDT is currently restricted only to Euclidean spaces...... framework can maintain all the pivotal features of the VDT framework and yet significantly improve its performance in non-Euclidean domains. We apply the proposed framework to different text categorization problems and demonstrate its benefits over the original VDT....

Simple Motion Pursuit and Evasion Differential Games with Many Pursuers on Manifolds with Euclidean Metric

Directory of Open Access Journals (Sweden)

Atamurat Kuchkarov

2016-01-01

Full Text Available We consider pursuit and evasion differential games of a group of m pursuers and one evader on manifolds with Euclidean metric. The motions of all players are simple, and maximal speeds of all players are equal. If the state of a pursuer coincides with that of the evader at some time, we say that pursuit is completed. We establish that each of the differential games (pursuit or evasion is equivalent to a differential game of m groups of countably many pursuers and one group of countably many evaders in Euclidean space. All the players in any of these groups are controlled by one controlled parameter. We find a condition under which pursuit can be completed, and if this condition is not satisfied, then evasion is possible. We construct strategies for the pursuers in pursuit game which ensure completion the game for a finite time and give a formula for this time. In the case of evasion game, we construct a strategy for the evader.

Hoelder continuity properties of Euclidean fields in some models of Markovian and non-Markovian field theory

International Nuclear Information System (INIS)

Haba, Z.

1981-01-01

In the usual models of Euclidean field theory the Schwinger functions are moments of a positive measure. In this paper the author discusses the basic properties of the measure μ, i.e. properties of the sample paths of the random field. (Auth.)

Evaluation of uterine ultrasound imaging in cervical radiotherapy; a comparison of autoscan and conventional probe

DEFF Research Database (Denmark)

Baker, Mariwan; Cooper, David T.; Behrens, Claus F.

2016-01-01

.001). The median of the interobserver COM distance (Euclidean distance for 36 scans) was reduced from 8.5 (C-US) to 6.0mm (A-US). An F-test on the 36 scans showed strong significant differences (p Euclidean interobserver distance when comparing the C-US with the A-US scans. The average...

Quantitative Comparison of Tolerance-Based Feature Transforms

OpenAIRE

Reniers, Dennie; Telea, Alexandru

2006-01-01

Tolerance-based feature transforms (TFTs) assign to each pixel in an image not only the nearest feature pixels on the boundary (origins), but all origins from the minimum distance up to a user-defined tolerance. In this paper, we compare four simple-to-implement methods for computing TFTs for binary images. Of these, two are novel methods and two extend existing distance transform algorithms. We quantitatively and qualitatively compare all algorithms on speed and accuracy of both distance and...

Convex hull and tour crossings in the Euclidean traveling salesperson problem : implications for human performance studies

NARCIS (Netherlands)

Rooij, van I.; Stege, U.; Schactman, A.

2003-01-01

Recently there has been growing interest among psychologists in human performance on the Euclidean traveling salesperson problem (E-TSP). A debate has been initiated on what strategy people use in solving visually presented E-TSP instances. The most prominent hypothesis is the convex-hull

Characterizations of Space Curves According to Bishop Darboux Vector in Euclidean 3-Space E3

OpenAIRE

Huseyin KOCAYIGIT; Ali OZDEMIR

2014-01-01

In this paper, we obtained some characterizations of space curves according to Bihop frame in Euclidean 3-space E3 by using Laplacian operator and Levi-Civita connection. Furthermore, we gave the general differential equations which characterize the space curves according to the Bishop Darboux vector and the normal Bishop Darboux vector.

A New Form of the Spherical Expansion of Zonal Functions and Fourier Transforms of SO(d-Finite Functions

Directory of Open Access Journals (Sweden)

Agata Bezubik

2006-03-01

Full Text Available This paper presents recent results obtained by the authors (partly in collaboration with A. Dabrowska concerning expansions of zonal functions on Euclidean spheres into spherical harmonics and some applications of such expansions for problems involving Fourier transforms of functions with rotational symmetry. The method used to derive the expansion formula is based entirely on differential methods and completely avoids the use of various integral identities commonly used in this context. Some new identities for the Fourier transform are derived and as a byproduct seemingly new recurrence relations for the classical Bessel functions are obtained.

Effect of Image Linearization on Normalized Compression Distance

Science.gov (United States)

Mortensen, Jonathan; Wu, Jia Jie; Furst, Jacob; Rogers, John; Raicu, Daniela

Normalized Information Distance, based on Kolmogorov complexity, is an emerging metric for image similarity. It is approximated by the Normalized Compression Distance (NCD) which generates the relative distance between two strings by using standard compression algorithms to compare linear strings of information. This relative distance quantifies the degree of similarity between the two objects. NCD has been shown to measure similarity effectively on information which is already a string: genomic string comparisons have created accurate phylogeny trees and NCD has also been used to classify music. Currently, to find a similarity measure using NCD for images, the images must first be linearized into a string, and then compared. To understand how linearization of a 2D image affects the similarity measure, we perform four types of linearization on a subset of the Corel image database and compare each for a variety of image transformations. Our experiment shows that different linearization techniques produce statistically significant differences in NCD for identical spatial transformations.

The challenge of global water access monitoring: evaluating straight-line distance versus self-reported travel time among rural households in Mozambique.

Science.gov (United States)

Ho, Jeff C; Russel, Kory C; Davis, Jennifer

2014-03-01

Support is growing for the incorporation of fetching time and/or distance considerations in the definition of access to improved water supply used for global monitoring. Current efforts typically rely on self-reported distance and/or travel time data that have been shown to be unreliable. To date, however, there has been no head-to-head comparison of such indicators with other possible distance/time metrics. This study provides such a comparison. We examine the association between both straight-line distance and self-reported one-way travel time with measured route distances to water sources for 1,103 households in Nampula province, Mozambique. We find straight-line, or Euclidean, distance to be a good proxy for route distance (R(2) = 0.98), while self-reported travel time is a poor proxy (R(2) = 0.12). We also apply a variety of time- and distance-based indicators proposed in the literature to our sample data, finding that the share of households classified as having versus lacking access would differ by more than 70 percentage points depending on the particular indicator employed. This work highlights the importance of the ongoing debate regarding valid, reliable, and feasible strategies for monitoring progress in the provision of improved water supply services.

Dual transformations of the non-abelian fields in Minkowsky, Euclid, and Galilei-Newton spaces

International Nuclear Information System (INIS)

Tolkaehev, E.A.; Kurochkin, Y.A.; Trequbovich, A.Y.

1991-01-01

In this paper it is shown that the generalization of the Yang-Mills equations in Minkowsky space to the case of the biquaternions over dual and double numbers enables one to define the corresponding representations of the Galilei and SO(4) groups in a rather natural way. it makes construction of the non-Abelian field equations in Euclidean and Galilei-Newton spaces possible and proves their invariance under generalized dual transformations by use of the analogy with the Abelian gauge

Biolistic transformation of Scoparia dulcis L.

Science.gov (United States)

Srinivas, Kota; Muralikrishna, Narra; Kumar, Kalva Bharath; Raghu, Ellendula; Mahender, Aileni; Kiranmayee, Kasula; Yashodahara, Velivela; Sadanandam, Abbagani

2016-01-01

Here, we report for the first time, the optimized conditions for microprojectile bombardment-mediated genetic transformation in Vassourinha (Scoparia dulcis L.), a Plantaginaceae medicinal plant species. Transformation was achieved by bombardment of axenic leaf segments with Binary vector pBI121 harbouring β-glucuronidase gene (GUS) as a reporter and neomycin phosphotransferase II gene (npt II) as a selectable marker. The influence of physical parameters viz., acceleration pressure, flight distance, gap width & macroprojectile travel distance of particle gun on frequency of transient GUS and stable (survival of putative transformants) expressions have been investigated. Biolistic delivery of the pBI121 yielded the best (80.0 %) transient expression of GUS gene bombarded at a flight distance of 6 cm and rupture disc pressure/acceleration pressure of 650 psi. Highest stable expression of 52.0 % was noticed in putative transformants on RMBI-K medium. Integration of GUS and npt II genes in the nuclear genome was confirmed through primer specific PCR. DNA blot analysis showed more than one transgene copy in the transformed plantlet genomes. The present study may be used for metabolic engineering and production of biopharmaceuticals by transplastomic technology in this valuable medicinal plant.

A latent class distance association model for cross-classified data with a categorical response variable.

Science.gov (United States)

Vera, José Fernando; de Rooij, Mark; Heiser, Willem J

2014-11-01

In this paper we propose a latent class distance association model for clustering in the predictor space of large contingency tables with a categorical response variable. The rows of such a table are characterized as profiles of a set of explanatory variables, while the columns represent a single outcome variable. In many cases such tables are sparse, with many zero entries, which makes traditional models problematic. By clustering the row profiles into a few specific classes and representing these together with the categories of the response variable in a low-dimensional Euclidean space using a distance association model, a parsimonious prediction model can be obtained. A generalized EM algorithm is proposed to estimate the model parameters and the adjusted Bayesian information criterion statistic is employed to test the number of mixture components and the dimensionality of the representation. An empirical example highlighting the advantages of the new approach and comparing it with traditional approaches is presented. © 2014 The British Psychological Society.

A Novel Parallel Algorithm for Edit Distance Computation

Directory of Open Access Journals (Sweden)

Muhammad Murtaza Yousaf

2018-01-01

Full Text Available The edit distance between two sequences is the minimum number of weighted transformation-operations that are required to transform one string into the other. The weighted transformation-operations are insert, remove, and substitute. Dynamic programming solution to find edit distance exists but it becomes computationally intensive when the lengths of strings become very large. This work presents a novel parallel algorithm to solve edit distance problem of string matching. The algorithm is based on resolving dependencies in the dynamic programming solution of the problem and it is able to compute each row of edit distance table in parallel. In this way, it becomes possible to compute the complete table in min(m,n iterations for strings of size m and n whereas state-of-the-art parallel algorithm solves the problem in max(m,n iterations. The proposed algorithm also increases the amount of parallelism in each of its iteration. The algorithm is also capable of exploiting spatial locality while its implementation. Additionally, the algorithm works in a load balanced way that further improves its performance. The algorithm is implemented for multicore systems having shared memory. Implementation of the algorithm in OpenMP shows linear speedup and better execution time as compared to state-of-the-art parallel approach. Efficiency of the algorithm is also proven better in comparison to its competitor.

Using BMDP and SPSS for a Q factor analysis.

Science.gov (United States)

Tanner, B A; Koning, S M

1980-12-01

While Euclidean distances and Q factor analysis may sometimes be preferred to correlation coefficients and cluster analysis for developing a typology, commercially available software does not always facilitate their use. Commands are provided for using BMDP and SPSS in a Q factor analysis with Euclidean distances.

Geometry through history Euclidean, hyperbolic, and projective geometries

CERN Document Server

Dillon, Meighan I

2018-01-01

Presented as an engaging discourse, this textbook invites readers to delve into the historical origins and uses of geometry. The narrative traces the influence of Euclid’s system of geometry, as developed in his classic text The Elements, through the Arabic period, the modern era in the West, and up to twentieth century mathematics. Axioms and proof methods used by mathematicians from those periods are explored alongside the problems in Euclidean geometry that lead to their work. Students cultivate skills applicable to much of modern mathematics through sections that integrate concepts like projective and hyperbolic geometry with representative proof-based exercises. For its sophisticated account of ancient to modern geometries, this text assumes only a year of college mathematics as it builds towards its conclusion with algebraic curves and quaternions. Euclid’s work has affected geometry for thousands of years, so this text has something to offer to anyone who wants to broaden their appreciation for the...

Defects and boundary layers in non-Euclidean plates

International Nuclear Information System (INIS)

Gemmer, J A; Venkataramani, S C

2012-01-01

We investigate the behaviour of non-Euclidean plates with constant negative Gaussian curvature using the Föppl–von Kármán reduced theory of elasticity. Motivated by recent experimental results, we focus on annuli with a periodic profile. We prove rigorous upper and lower bounds for the elastic energy that scales like the thickness squared. In particular we show that are only two types of global minimizers—deformations that remain flat and saddle shaped deformations with isolated regions of stretching near the edge of the annulus. We also show that there exist local minimizers with a periodic profile that have additional boundary layers near their lines of inflection. These additional boundary layers are a new phenomenon in thin elastic sheets and are necessary to regularize jump discontinuities in the azimuthal curvature across lines of inflection. We rigorously derive scaling laws for the width of these boundary layers as a function of the thickness of the sheet. (paper)

Logical and Geometrical Distance in Polyhedral Aristotelian Diagrams in Knowledge Representation

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Lorenz Demey

2017-09-01

Full Text Available Aristotelian diagrams visualize the logical relations among a finite set of objects. These diagrams originated in philosophy, but recently, they have also been used extensively in artificial intelligence, in order to study (connections between various knowledge representation formalisms. In this paper, we develop the idea that Aristotelian diagrams can be fruitfully studied as geometrical entities. In particular, we focus on four polyhedral Aristotelian diagrams for the Boolean algebra B 4 , viz. the rhombic dodecahedron, the tetrakis hexahedron, the tetraicosahedron and the nested tetrahedron. After an in-depth investigation of the geometrical properties and interrelationships of these polyhedral diagrams, we analyze the correlation (or lack thereof between logical (Hamming and geometrical (Euclidean distance in each of these diagrams. The outcome of this analysis is that the Aristotelian rhombic dodecahedron and tetrakis hexahedron exhibit the strongest degree of correlation between logical and geometrical distance; the tetraicosahedron performs worse; and the nested tetrahedron has the lowest degree of correlation. Finally, these results are used to shed new light on the relative strengths and weaknesses of these polyhedral Aristotelian diagrams, by appealing to the congruence principle from cognitive research on diagram design.

An improved model for whole genome phylogenetic analysis by Fourier transform.

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Yin, Changchuan; Yau, Stephen S-T

2015-10-07

DNA sequence similarity comparison is one of the major steps in computational phylogenetic studies. The sequence comparison of closely related DNA sequences and genomes is usually performed by multiple sequence alignments (MSA). While the MSA method is accurate for some types of sequences, it may produce incorrect results when DNA sequences undergone rearrangements as in many bacterial and viral genomes. It is also limited by its computational complexity for comparing large volumes of data. Previously, we proposed an alignment-free method that exploits the full information contents of DNA sequences by Discrete Fourier Transform (DFT), but still with some limitations. Here, we present a significantly improved method for the similarity comparison of DNA sequences by DFT. In this method, we map DNA sequences into 2-dimensional (2D) numerical sequences and then apply DFT to transform the 2D numerical sequences into frequency domain. In the 2D mapping, the nucleotide composition of a DNA sequence is a determinant factor and the 2D mapping reduces the nucleotide composition bias in distance measure, and thus improving the similarity measure of DNA sequences. To compare the DFT power spectra of DNA sequences with different lengths, we propose an improved even scaling algorithm to extend shorter DFT power spectra to the longest length of the underlying sequences. After the DFT power spectra are evenly scaled, the spectra are in the same dimensionality of the Fourier frequency space, then the Euclidean distances of full Fourier power spectra of the DNA sequences are used as the dissimilarity metrics. The improved DFT method, with increased computational performance by 2D numerical representation, can be applicable to any DNA sequences of different length ranges. We assess the accuracy of the improved DFT similarity measure in hierarchical clustering of different DNA sequences including simulated and real datasets. The method yields accurate and reliable phylogenetic trees

Hadronic vacuum polarization in QCD and its evaluation in Euclidean spacetime

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de Rafael, Eduardo

2017-07-01

We discuss a new technique to evaluate integrals of QCD Green's functions in the Euclidean based on their Mellin-Barnes representation. We present as a first application the evaluation of the lowest order hadronic vacuum polarization (HVP) contribution to the anomalous magnetic moment of the muon 1/2 (gμ-2 )HVP≡aμHVP . It is shown that with a precise determination of the slope and curvature of the HVP function at the origin from lattice QCD (LQCD), one can already obtain a result for aμHVP which may serve as a test of the determinations based on experimental measurements of the e+e- annihilation cross section into hadrons.

Supersymmetry on a euclidean spacetime lattice 1. A target theory with four supercharges

International Nuclear Information System (INIS)

Cohen, Andrew G.; Kaplan, David B.; Katz, Emanuel; Uensal, Mithat

2003-01-01

We formulate a euclidean spacetime lattice whose continuum limit is (2,2) supersymmetric Yang-Mills theory in two dimensions, a theory which possesses four supercharges and an anomalous global chiral symmetry. The lattice action respects one exact supersymmetry, which allows the target theory to emerge in the continuum limit without fine-tuning. Our method exploits an orbifold construction described previously for spatial lattices in Minkowski space, and can be generalized to more complicated theories with additional supersymmetry and more spacetime dimensions. (author)

Equivalence Testing of Complex Particle Size Distribution Profiles Based on Earth Mover's Distance.

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Hu, Meng; Jiang, Xiaohui; Absar, Mohammad; Choi, Stephanie; Kozak, Darby; Shen, Meiyu; Weng, Yu-Ting; Zhao, Liang; Lionberger, Robert

2018-04-12

Particle size distribution (PSD) is an important property of particulates in drug products. In the evaluation of generic drug products formulated as suspensions, emulsions, and liposomes, the PSD comparisons between a test product and the branded product can provide useful information regarding in vitro and in vivo performance. Historically, the FDA has recommended the population bioequivalence (PBE) statistical approach to compare the PSD descriptors D50 and SPAN from test and reference products to support product equivalence. In this study, the earth mover's distance (EMD) is proposed as a new metric for comparing PSD particularly when the PSD profile exhibits complex distribution (e.g., multiple peaks) that is not accurately described by the D50 and SPAN descriptor. EMD is a statistical metric that measures the discrepancy (distance) between size distribution profiles without a prior assumption of the distribution. PBE is then adopted to perform statistical test to establish equivalence based on the calculated EMD distances. Simulations show that proposed EMD-based approach is effective in comparing test and reference profiles for equivalence testing and is superior compared to commonly used distance measures, e.g., Euclidean and Kolmogorov-Smirnov distances. The proposed approach was demonstrated by evaluating equivalence of cyclosporine ophthalmic emulsion PSDs that were manufactured under different conditions. Our results show that proposed approach can effectively pass an equivalent product (e.g., reference product against itself) and reject an inequivalent product (e.g., reference product against negative control), thus suggesting its usefulness in supporting bioequivalence determination of a test product to the reference product which both possess multimodal PSDs.

On the theory of high-velocity particles

International Nuclear Information System (INIS)

Gordeyev, G.V.

1979-01-01

The equations of mechanics and electrodynamics are presented in a form which is covariant for Galileo transformations in Euclidean space. The author shows that Galileo transformations in the Euclidean space are valid for particles with velocities approaching that of light. (author)

Green's functions in Bianchi type-I spaces. Relation between Minkowski and Euclidean approaches

International Nuclear Information System (INIS)

Bukhbinder, I.L.; Kirillova, E.N.

1988-01-01

A theory is considered for a free scalar field with a conformal connection in a curved space-time with a Bianchi type-I metric. A representation is obtained for the Green's function G∼ in in in the form of an integral of a Schwinger-DeWitt kernel along a contour in a plane of complex-valued proper time. It is shown how as transition may be accomplished from Green's functions in space with the Euclidean signature to Green's functions in space with Minkowski signature and vice versa

Diffusionless phase transformations

International Nuclear Information System (INIS)

Vejman, K.M.

1987-01-01

Diffusionless phase transformations in metals and alloys in the process of which atomic displacements occur at the distances lower than interatomic ones and relative correspondence of neighbour atoms is preserved, are considered. Special attention is paid to the mechanism of martensitic transformations. Phenomenologic crystallographical theory of martensitic transformations are presented. Two types of martensitic transformations different from the energy viewpoint are pointed out - thermoelastic and non-thermoelastic ones - which are characterized by transformation hysteresis and ways of martensite - initial phase reverse transformation realization. Mechanical effect in the martensitic transformations have been analyzed. The problem of diffusionless formation of ω-phases and the effect of impurities and vacancies on the process are briefly discussed. The role of charge density waves in phase transformations of the second type (transition of initial phase into noncommensurate one) and of the first type (transition of noncommensurate phase into commensurate one) is considered

Using P-Stat, BMDP and SPSS for a cross-products factor analysis.

Science.gov (United States)

Tanner, B A; Leiman, J M

1983-06-01

The major disadvantage of the Q factor analysis with Euclidean distances described by Tanner and Koning [Comput. Progr. Biomed. 12 (1980) 201-202] is the considerable editing required. An alternative procedure with commercially distributed software, and with cross-products in place of Euclidean distances is described. This procedure does not require any editing.

Constraint algebra in Smolin's G →0 limit of 4D Euclidean gravity

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Varadarajan, Madhavan

2018-05-01

Smolin's generally covariant GNewton→0 limit of 4d Euclidean gravity is a useful toy model for the study of the constraint algebra in loop quantum gravity (LQG). In particular, the commutator between its Hamiltonian constraints has a metric dependent structure function. While a prior LQG-like construction of nontrivial anomaly free constraint commutators for the model exists, that work suffers from two defects. First, Smolin's remarks on the inability of the quantum dynamics to generate propagation effects apply. Second, the construction only yields the action of a single Hamiltonian constraint together with the action of its commutator through a continuum limit of corresponding discrete approximants; the continuum limit of a product of two or more constraints does not exist. Here, we incorporate changes in the quantum dynamics through structural modifications in the choice of discrete approximants to the quantum Hamiltonian constraint. The new structure is motivated by that responsible for propagation in an LQG-like quantization of paramatrized field theory and significantly alters the space of physical states. We study the off shell constraint algebra of the model in the context of these structural changes and show that the continuum limit action of multiple products of Hamiltonian constraints is (a) supported on an appropriate domain of states, (b) yields anomaly free commutators between pairs of Hamiltonian constraints, and (c) is diffeomorphism covariant. Many of our considerations seem robust enough to be applied to the setting of 4d Euclidean gravity.

THE FLUENCE AND DISTANCE DISTRIBUTIONS OF FAST RADIO BURSTS

International Nuclear Information System (INIS)

Vedantham, H. K.; Ravi, V.; Hallinan, G.; Shannon, R. M.

2016-01-01

Fast radio bursts (FRB) are millisecond-duration radio pulses with apparent extragalactic origins. All but two of the FRBs have been discovered using the Parkes dish, which employs multiple beams formed by an array of feed horns on its focal plane. In this paper, we show that (i) the preponderance of multiple-beam detections and (ii) the detection rates for varying dish diameters can be used to infer the index α of the cumulative fluence distribution function (the log N –log F function: α = 1.5 for a non-evolving population in a Euclidean universe). If all detected FRBs arise from a single progenitor population, multiple-beam FRB detection rates from the Parkes telescope yield the constraint 0.52 < α < 1.0 with 90% confidence. Searches at other facilities with different dish sizes refine the constraint to 0.5 < α < 0.9. Our results favor FRB searches with smaller dishes, because for α < 1 the gain in field of view for a smaller dish is more important than the reduction in sensitivity. Further, our results suggest that (i) FRBs are not standard candles, and (ii) the distribution of distances to the detected FRBs is weighted toward larger distances. If FRBs are extragalactic, these results are consistent with a cosmological population, which would make FRBs excellent probes of the baryonic content and geometry of the universe.

Constant curvature black holes in Einstein AdS gravity: Euclidean action and thermodynamics

Science.gov (United States)

Guilleminot, Pablo; Olea, Rodrigo; Petrov, Alexander N.

2018-03-01

We compute the Euclidean action for constant curvature black holes (CCBHs), as an attempt to associate thermodynamic quantities to these solutions of Einstein anti-de Sitter (AdS) gravity. CCBHs are gravitational configurations obtained by identifications along isometries of a D -dimensional globally AdS space, such that the Riemann tensor remains constant. Here, these solutions are interpreted as extended objects, which contain a (D -2 )-dimensional de-Sitter brane as a subspace. Nevertheless, the computation of the free energy for these solutions shows that they do not obey standard thermodynamic relations.

Euclidean quantum field theory and the Hawking effect

International Nuclear Information System (INIS)

Lapedes, A.S.

1978-01-01

Complex analytic continuation in a time variable in order to define a Feynman propagator is investigated in a general relativistic context. When external electric fields are present a complex analytic continuation in the electric charge is also introduced. The new Euclidean formalism is checked by reproducing Schwinger's special relativistic result for pair creation by an external, homogenous, electric field, and then applied to the Robinson-Bertotti universe. The Robinson-Bertotti universe, although unphysical, provides an interesting theoretical laboratory in which to investigate quantum effects, much as the unphysical Taub-NUT (Newman-Unti-Tamburino) universe does for purely classical general relativity. A conformally related problem of pair creation by a supercritically charged nucleus is also considered, and a sensible resolution is obtained to this classic problem. The essential mathematical point throughout is the use of the Feynman path-integral form of the propagator to motivate replacing hyperbolic equations by elliptic equations. The unique, bounded solution for the elliptic Green's function is then analytically continued back to physical values to define the Feynman Green's function

Mining spatial information to investigate the evolution of karst rocky desertification and its human driving forces in Changshun, China.

Science.gov (United States)

Xu, Erqi; Zhang, Hongqi; Li, Mengxian

2013-08-01

The processes of karst rocky desertification (KRD) have been found to cause the most severe environmental degradation in southwestern China. Understanding the driving forces that cause KRD is essential for managing and restoring the areas that it impacts. Studies of the human driving forces of KRD are limited to the county level, a specific administrative unit in China; census data are acquired at this scale, which can lead to scale biases. Changshun County is studied here as a representative area and anthropogenic influences in the county are accounted for by using Euclidean distances for the proximity to roads and settlements. We propose a standard coefficient of human influence (SOI) that standardizes the Euclidean distances for different KRD transformations to compare the effects of human activities in different areas. In Changshun County, the individual influences of roads and settlements share similar characteristics. The SOIs of improved KRD transformation types are almost negative, but the SOIs of deteriorated types are nearly positive except for one form of KRD turning to the extremely severe KRD. The results indicated that the distribution and evolution of the KRD areas from 2000 to 2010 in Changshun were affected positively by human activities (e.g., KRD restoration projects) and also negatively (e.g., by intense and irrational land use). Our results demonstrate that the spatial techniques and SOI used in this study can effectively incorporate information concerning human influences and internal KRD transformations. This provides a suitable approach for studying the relationships between human activities and KRD processes at fine scales. Copyright © 2013 Elsevier B.V. All rights reserved.

Two-stage sparse coding of region covariance via Log-Euclidean kernels to detect saliency.

Science.gov (United States)

Zhang, Ying-Ying; Yang, Cai; Zhang, Ping

2017-05-01

In this paper, we present a novel bottom-up saliency detection algorithm from the perspective of covariance matrices on a Riemannian manifold. Each superpixel is described by a region covariance matrix on Riemannian Manifolds. We carry out a two-stage sparse coding scheme via Log-Euclidean kernels to extract salient objects efficiently. In the first stage, given background dictionary on image borders, sparse coding of each region covariance via Log-Euclidean kernels is performed. The reconstruction error on the background dictionary is regarded as the initial saliency of each superpixel. In the second stage, an improvement of the initial result is achieved by calculating reconstruction errors of the superpixels on foreground dictionary, which is extracted from the first stage saliency map. The sparse coding in the second stage is similar to the first stage, but is able to effectively highlight the salient objects uniformly from the background. Finally, three post-processing methods-highlight-inhibition function, context-based saliency weighting, and the graph cut-are adopted to further refine the saliency map. Experiments on four public benchmark datasets show that the proposed algorithm outperforms the state-of-the-art methods in terms of precision, recall and mean absolute error, and demonstrate the robustness and efficiency of the proposed method. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Perspective Structure of Visual Space

Science.gov (United States)

2015-01-01

Luneburg’s model has been the reference for experimental studies of visual space for almost seventy years. His claim for a curved visual space has been a source of inspiration for visual scientists as well as philosophers. The conclusion of many experimental studies has been that Luneburg’s model does not describe visual space in various tasks and conditions. Remarkably, no alternative model has been suggested. The current study explores perspective transformations of Euclidean space as a model for visual space. Computations show that the geometry of perspective spaces is considerably different from that of Euclidean space. Collinearity but not parallelism is preserved in perspective space and angles are not invariant under translation and rotation. Similar relationships have shown to be properties of visual space. Alley experiments performed early in the nineteenth century have been instrumental in hypothesizing curved visual spaces. Alleys were computed in perspective space and compared with reconstructed alleys of Blumenfeld. Parallel alleys were accurately described by perspective geometry. Accurate distance alleys were derived from parallel alleys by adjusting the interstimulus distances according to the size-distance invariance hypothesis. Agreement between computed and experimental alleys and accommodation of experimental results that rejected Luneburg’s model show that perspective space is an appropriate model for how we perceive orientations and angles. The model is also appropriate for perceived distance ratios between stimuli but fails to predict perceived distances. PMID:27648222

Computational Analysis of Distance Operators for the Iterative Closest Point Algorithm.

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Higinio Mora

Full Text Available The Iterative Closest Point (ICP algorithm is currently one of the most popular methods for rigid registration so that it has become the standard in the Robotics and Computer Vision communities. Many applications take advantage of it to align 2D/3D surfaces due to its popularity and simplicity. Nevertheless, some of its phases present a high computational cost thus rendering impossible some of its applications. In this work, it is proposed an efficient approach for the matching phase of the Iterative Closest Point algorithm. This stage is the main bottleneck of that method so that any efficiency improvement has a great positive impact on the performance of the algorithm. The proposal consists in using low computational cost point-to-point distance metrics instead of classic Euclidean one. The candidates analysed are the Chebyshev and Manhattan distance metrics due to their simpler formulation. The experiments carried out have validated the performance, robustness and quality of the proposal. Different experimental cases and configurations have been set up including a heterogeneous set of 3D figures, several scenarios with partial data and random noise. The results prove that an average speed up of 14% can be obtained while preserving the convergence properties of the algorithm and the quality of the final results.

SLE as a Mating of Trees in Euclidean Geometry

Science.gov (United States)

Holden, Nina; Sun, Xin

2018-05-01

The mating of trees approach to Schramm-Loewner evolution (SLE) in the random geometry of Liouville quantum gravity (LQG) has been recently developed by Duplantier et al. (Liouville quantum gravity as a mating of trees, 2014. arXiv:1409.7055). In this paper we consider the mating of trees approach to SLE in Euclidean geometry. Let {η} be a whole-plane space-filling SLE with parameter {κ > 4} , parameterized by Lebesgue measure. The main observable in the mating of trees approach is the contour function, a two-dimensional continuous process describing the evolution of the Minkowski content of the left and right frontier of {η} . We prove regularity properties of the contour function and show that (as in the LQG case) it encodes all the information about the curve {η} . We also prove that the uniform spanning tree on {Z^2} converges to SLE8 in the natural topology associated with the mating of trees approach.

Non-Euclidean Geometry, Nontrivial Topology and Quantum Vacuum Effects

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Yurii A. Sitenko

2018-01-01

Full Text Available Space out of a topological defect of the Abrikosov–Nielsen–Olesen (ANO vortex type is locally flat but non-Euclidean. If a spinor field is quantized in such a space, then a variety of quantum effects are induced in the vacuum. On the basis of the continuum model for long-wavelength electronic excitations originating in the tight-binding approximation for the nearest-neighbor interaction of atoms in the crystal lattice, we consider quantum ground-state effects in Dirac materials with two-dimensional monolayer structures warped into nanocones by a disclination; the nonzero size of the disclination is taken into account, and a boundary condition at the edge of the disclination is chosen to ensure self-adjointness of the Dirac–Weyl Hamiltonian operator. We show that the quantum ground-state effects are independent of the disclination size, and we find circumstances in which they are independent of parameters of the boundary condition.

Buckling transition and boundary layer in non-Euclidean plates.

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Efrati, Efi; Sharon, Eran; Kupferman, Raz

2009-07-01

Non-Euclidean plates are thin elastic bodies having no stress-free configuration, hence exhibiting residual stresses in the absence of external constraints. These bodies are endowed with a three-dimensional reference metric, which may not necessarily be immersible in physical space. Here, based on a recently developed theory for such bodies, we characterize the transition from flat to buckled equilibrium configurations at a critical value of the plate thickness. Depending on the reference metric, the buckling transition may be either continuous or discontinuous. In the infinitely thin plate limit, under the assumption that a limiting configuration exists, we show that the limit is a configuration that minimizes the bending content, among all configurations with zero stretching content (isometric immersions of the midsurface). For small but finite plate thickness, we show the formation of a boundary layer, whose size scales with the square root of the plate thickness and whose shape is determined by a balance between stretching and bending energies.

Hyperbolic Cosines and Sines Theorems for the Triangle Formed by Arcs of Intersecting Semicircles on Euclidean Plane

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Robert M. Yamaleev

2013-01-01

Full Text Available The hyperbolic cosines and sines theorems for the curvilinear triangle bounded by circular arcs of three intersecting circles are formulated and proved by using the general complex calculus. The method is based on a key formula establishing a relationship between exponential function and the cross-ratio. The proofs are carried out on Euclidean plane.

Phenotypic distance among assai palm’s mother plants (Euterpe oleracea Mart. from Eastern Amazon

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Rosemiro Santos Galate

2014-09-01

Full Text Available The açai palm tree (Euterpe oleracea Mart. is native to the Amazonian estuary. Media revelation of the nutraceutical properties of açai palm has resulted in its introduction in the national and international markets, consequently increasing the açai palm crop area in the Amazon. Nevertheless, açai palm cultivation is performed in a rational manner, because of limited product extraction from the native açai palm varieties. The study aimed to conduct a preliminary estimate of genetic variability, parameters, and phenotypic divergence of parent açai palms. Data from 129 parent plants from northeast Pará was collected. Analysis of variance (ANOVA of 22 morphoagronomic traits was performed to estimate the genetic parameters. Divergence was estimated using standardized average euclidean distance by using unweighted pair group method with arithmetic mean (UPGMA and Tocher clustering methods. Significant variance was noted in 77.3% traits (ANOVA, p<0.01 and p<0.05; CVg/CVe ratio indicated that 72.3% traits may present genetic variability for use in breeding programs. The euclidean distance showed EO-070 and EO-072 parent plants (Combu Island as the least divergent, and EO-010 (Belém and EO-018 (Salinópolis as the most divergent. The clustering methods determined ten (Tocher and nine (UPGMA similar groups. The most dissimilar parent plants were EO-035 (Capitão Poço, EO- 109 (Combu Island, EO-019 (Salinópolis, and EO-010 (Belém (Tocher method, whereas even the EO-010 (Belém; EO-011 (São João de Pirabas; EO-017, EO-018, and EO-019 (Salinópolis; EO-062 and EO-109 (Combu Island plants showed dissimilarity. We concluded that the 129 mother plants have high phenotypic variability, indicating the possibility of their use in genetic breeding programs. Further, the divergent parent plants can be used in the production of genotypes with favorable characteristics.

Single-Image Distance Measurement by a Smart Mobile Device.

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Chen, Shangwen; Fang, Xianyong; Shen, Jianbing; Wang, Linbo; Shao, Ling

2017-12-01

Existing distance measurement methods either require multiple images and special photographing poses or only measure the height with a special view configuration. We propose a novel image-based method that can measure various types of distance from single image captured by a smart mobile device. The embedded accelerometer is used to determine the view orientation of the device. Consequently, pixels can be back-projected to the ground, thanks to the efficient calibration method using two known distances. Then the distance in pixel is transformed to a real distance in centimeter with a linear model parameterized by the magnification ratio. Various types of distance specified in the image can be computed accordingly. Experimental results demonstrate the effectiveness of the proposed method.

Superintegrability in two-dimensional Euclidean space and associated polynomial solutions

International Nuclear Information System (INIS)

Kalnins, E.G.; Miller, W. Jr; Pogosyan, G.S.

1996-01-01

In this work we examine the basis functions for those classical and quantum mechanical systems in two dimensions which admit separation of variables in at least two coordinate systems. We do this for the corresponding systems defined in Euclidean space and on the two dimensional sphere. We present all of these cases from a unified point of view. In particular, all of the spectral functions that arise via variable separation have their essential features expressed in terms of their zeros. The principal new results are the details of the polynomial base for each of the nonsubgroup base, not just the subgroup cartesian and polar coordinate case, and the details of the structure of the quadratic algebras. We also study the polynomial eigenfunctions in elliptic coordinates of the N-dimensional isotropic quantum oscillator. 28 refs., 1 tab

Non-perturbative BRST quantization of Euclidean Yang-Mills theories in Curci-Ferrari gauges

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Pereira, A. D.; Sobreiro, R. F.; Sorella, S. P.

2016-10-01

In this paper we address the issue of the non-perturbative quantization of Euclidean Yang-Mills theories in the Curci-Ferrari gauge. In particular, we construct a refined Gribov-Zwanziger action for this gauge, which takes into account the presence of gauge copies as well as the dynamical formation of dimension-two condensates. This action enjoys a non-perturbative BRST symmetry recently proposed in Capri et al. (Phys. Rev. D 92(4), 045039. doi: 10.1103/PhysRevD.92.045039 arXiv:1506.06995 [hep-th], 2015). Finally, we pay attention to the gluon propagator in different space-time dimensions.

Non-perturbative BRST quantization of Euclidean Yang-Mills theories in Curci-Ferrari gauges

International Nuclear Information System (INIS)

Pereira, A.D.; Sobreiro, R.F.; Sorella, S.P.

2016-01-01

In this paper we address the issue of the non-perturbative quantization of Euclidean Yang-Mills theories in the Curci-Ferrari gauge. In particular, we construct a refined Gribov-Zwanziger action for this gauge, which takes into account the presence of gauge copies as well as the dynamical formation of dimension-two condensates. This action enjoys a non-perturbative BRST symmetry recently proposed in Capri et al. (Phys. Rev. D 92(4), 045039. doi:10.1103/PhysRevD.92.045039. arXiv:1506.06995 [hepth], 2015). Finally, we pay attention to the gluon propagator in different space-time dimensions. (orig.)

Non-perturbative BRST quantization of Euclidean Yang-Mills theories in Curci-Ferrari gauges

Energy Technology Data Exchange (ETDEWEB)

Pereira, A.D. [UFF, Universidade Federal Fluminense, Instituto de Fisica, Campus da Praia Vermelha, Niteroi, RJ (Brazil); Max Planck Institute for Gravitational Physics, Albert Einstein Institute, Potsdam (Germany); UERJ, Universidade do Estado do Rio de Janeiro, Departamento de Fisica Teorica, Rio de Janeiro (Brazil); Sobreiro, R.F. [UFF, Universidade Federal Fluminense, Instituto de Fisica, Campus da Praia Vermelha, Niteroi, RJ (Brazil); Sorella, S.P. [UERJ, Universidade do Estado do Rio de Janeiro, Departamento de Fisica Teorica, Rio de Janeiro (Brazil)

2016-10-15

In this paper we address the issue of the non-perturbative quantization of Euclidean Yang-Mills theories in the Curci-Ferrari gauge. In particular, we construct a refined Gribov-Zwanziger action for this gauge, which takes into account the presence of gauge copies as well as the dynamical formation of dimension-two condensates. This action enjoys a non-perturbative BRST symmetry recently proposed in Capri et al. (Phys. Rev. D 92(4), 045039. doi:10.1103/PhysRevD.92.045039. arXiv:1506.06995 [hepth], 2015). Finally, we pay attention to the gluon propagator in different space-time dimensions. (orig.)

Absence of even-integer ζ-function values in Euclidean physical quantities in QCD

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Jamin, Matthias; Miravitllas, Ramon

2018-04-01

At order αs4 in perturbative quantum chromodynamics, even-integer ζ-function values are present in Euclidean physical correlation functions like the scalar quark correlation function or the scalar gluonium correlator. We demonstrate that these contributions cancel when the perturbative expansion is expressed in terms of the so-called C-scheme coupling αˆs which has recently been introduced in Ref. [1]. It is furthermore conjectured that a ζ4 term should arise in the Adler function at order αs5 in the MS ‾-scheme, and that this term is expected to disappear in the C-scheme as well.

Case-Based Reasoning untuk Diagnosis Penyakit Jantung

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Eka Wahyudi

2017-01-01

            The test results using medical records data validated by expert indicate that the system is able to recognize diseases heart using nearest neighbor similarity method, minskowski distance similarity and euclidean distance similarity correctly respectively of 100%. Using nearest neighbor get accuracy of 86.21%, minkowski 100%, and euclidean 94.83%

A Monte Carlo Study on Multiple Output Stochastic Frontiers: Comparison of Two Approaches

DEFF Research Database (Denmark)

Henningsen, Geraldine; Henningsen, Arne; Jensen, Uwe

, dividing all other output quantities by the selected output quantity, and using these ratios as regressors (OD). Another approach is the stochastic ray production frontier (SR) which transforms the output quantities into their Euclidean distance as the dependent variable and their polar coordinates......In the estimation of multiple output technologies in a primal approach, the main question is how to handle the multiple outputs. Often an output distance function is used, where the classical approach is to exploit its homogeneity property by selecting one output quantity as the dependent variable...... of both specifications for the case of a Translog output distance function with respect to different common statistical problems as well as problems arising as a consequence of zero values in the output quantities. Although, our results partly show clear reactions to statistical misspecifications...

A Monte Carlo Study on Multiple Output Stochastic Frontiers

DEFF Research Database (Denmark)

Henningsen, Géraldine; Henningsen, Arne; Jensen, Uwe

, dividing all other output quantities by the selected output quantity, and using these ratios as regressors (OD). Another approach is the stochastic ray production frontier (SR) which transforms the output quantities into their Euclidean distance as the dependent variable and their polar coordinates......In the estimation of multiple output technologies in a primal approach, the main question is how to handle the multiple outputs. Often an output distance function is used, where the classical approach is to exploit its homogeneity property by selecting one output quantity as the dependent variable...... of both specifications for the case of a Translog output distance function with respect to different common statistical problems as well as problems arising as a consequence of zero values in the output quantities. Although, our results partly show clear reactions to statistical misspecifications...

Geometric characterization of separability and entanglement in pure Gaussian states by single-mode unitary operations

Science.gov (United States)

Adesso, Gerardo; Giampaolo, Salvatore M.; Illuminati, Fabrizio

2007-10-01

We present a geometric approach to the characterization of separability and entanglement in pure Gaussian states of an arbitrary number of modes. The analysis is performed adapting to continuous variables a formalism based on single subsystem unitary transformations that has been recently introduced to characterize separability and entanglement in pure states of qubits and qutrits [S. M. Giampaolo and F. Illuminati, Phys. Rev. A 76, 042301 (2007)]. In analogy with the finite-dimensional case, we demonstrate that the 1×M bipartite entanglement of a multimode pure Gaussian state can be quantified by the minimum squared Euclidean distance between the state itself and the set of states obtained by transforming it via suitable local symplectic (unitary) operations. This minimum distance, corresponding to a , uniquely determined, extremal local operation, defines an entanglement monotone equivalent to the entropy of entanglement, and amenable to direct experimental measurement with linear optical schemes.

Geometric characterization of separability and entanglement in pure Gaussian states by single-mode unitary operations

International Nuclear Information System (INIS)

Adesso, Gerardo; Giampaolo, Salvatore M.; Illuminati, Fabrizio

2007-01-01

We present a geometric approach to the characterization of separability and entanglement in pure Gaussian states of an arbitrary number of modes. The analysis is performed adapting to continuous variables a formalism based on single subsystem unitary transformations that has been recently introduced to characterize separability and entanglement in pure states of qubits and qutrits [S. M. Giampaolo and F. Illuminati, Phys. Rev. A 76, 042301 (2007)]. In analogy with the finite-dimensional case, we demonstrate that the 1xM bipartite entanglement of a multimode pure Gaussian state can be quantified by the minimum squared Euclidean distance between the state itself and the set of states obtained by transforming it via suitable local symplectic (unitary) operations. This minimum distance, corresponding to a, uniquely determined, extremal local operation, defines an entanglement monotone equivalent to the entropy of entanglement, and amenable to direct experimental measurement with linear optical schemes

A relationship between scalar Green functions on hyperbolic and Euclidean Rindler spaces

International Nuclear Information System (INIS)

Haba, Z

2007-01-01

We derive a formula connecting in any dimension the Green function on the (D + 1)-dimensional Euclidean Rindler space and the one for a minimally coupled scalar field with a mass m in the D-dimensional hyperbolic space. The relation takes a simple form in the momentum space where the Green functions are equal at the momenta (p 0 , p) for Rindler and (m,p-hat) for hyperbolic space with a simple additive relation between the squares of the mass and the momenta. The formula has applications to finite temperature Green functions, Green functions on the cone and on the (compactified) Milne spacetime. Analytic continuations and interacting quantum fields are briefly discussed

ХL

Indian Academy of Sciences (India)

time-reversal invariance. A Euclidean space-time version of this invariance also exists. This is necessary in setting up the Euclidean functional integral. A mea- sure for quark functional integration can be constructed to be invariant under this. Euclidean transformation in addition to strong and electromagnetic gauge transfor-.

Anisotropic, Mixed-Norm Lizorkin-Triebel Spaces and Diffeomorphic Maps

DEFF Research Database (Denmark)

Johnsen, Jon; Hansen, Sabrina Munch; Sickel, Winfried

2014-01-01

This paper gives general results on invariance of anisotropic Lizorkin-Triebel spaces with mixed norms under coordinate transformations on Euclidean space, open sets, and cylindrical domains.......This paper gives general results on invariance of anisotropic Lizorkin-Triebel spaces with mixed norms under coordinate transformations on Euclidean space, open sets, and cylindrical domains....

Predicting pathologic tumor response to chemoradiotherapy with histogram distances characterizing longitudinal changes in 18F-FDG uptake patterns

Science.gov (United States)

Tan, Shan; Zhang, Hao; Zhang, Yongxue; Chen, Wengen; D’Souza, Warren D.; Lu, Wei

2013-01-01

Purpose: A family of fluorine-18 (18F)-fluorodeoxyglucose (18F-FDG) positron-emission tomography (PET) features based on histogram distances is proposed for predicting pathologic tumor response to neoadjuvant chemoradiotherapy (CRT). These features describe the longitudinal change of FDG uptake distribution within a tumor. Methods: Twenty patients with esophageal cancer treated with CRT plus surgery were included in this study. All patients underwent PET/CT scans before (pre-) and after (post-) CRT. The two scans were first rigidly registered, and the original tumor sites were then manually delineated on the pre-PET/CT by an experienced nuclear medicine physician. Two histograms representing the FDG uptake distribution were extracted from the pre- and the registered post-PET images, respectively, both within the delineated tumor. Distances between the two histograms quantify longitudinal changes in FDG uptake distribution resulting from CRT, and thus are potential predictors of tumor response. A total of 19 histogram distances were examined and compared to both traditional PET response measures and Haralick texture features. Receiver operating characteristic analyses and Mann-Whitney U test were performed to assess their predictive ability. Results: Among all tested histogram distances, seven bin-to-bin and seven crossbin distances outperformed traditional PET response measures using maximum standardized uptake value (AUC = 0.70) or total lesion glycolysis (AUC = 0.80). The seven bin-to-bin distances were: L2 distance (AUC = 0.84), χ2 distance (AUC = 0.83), intersection distance (AUC = 0.82), cosine distance (AUC = 0.83), squared Euclidean distance (AUC = 0.83), L1 distance (AUC = 0.82), and Jeffrey distance (AUC = 0.82). The seven crossbin distances were: quadratic-chi distance (AUC = 0.89), earth mover distance (AUC = 0.86), fast earth mover distance (AUC = 0.86), diffusion distance (AUC = 0.88), Kolmogorov-Smirnov distance (AUC = 0.88), quadratic form distance

Searching for patterns in TJ-II time evolution signals

International Nuclear Information System (INIS)

Farias, G.; Dormido-Canto, S.; Vega, J.; Sanchez, J.; Duro, N.; Dormido, R.; Ochando, M.; Santos, M.; Pajares, G.

2006-01-01

Since fusion plasma experiments generate hundreds of signals, it is important for their analysis to have automatic mechanisms for searching for similarities and retrieving specific data from the signal database. This paper describes a technique for searching in the TJ-II database that combines support vector machines and similarity query methods. Firstly, plasma signals are pre-processed by wavelet transform or discrete Fourier transform to reduce the dimensionality of the problem and to extract their main features. Secondly, support vector machines are used to classify a set of signals by reference to an input signal. Finally, similarity query methods (Euclidean distance and bounding envelope) are used to search the set of signals that best matches the input signal

Directional sound radiation from substation transformers

International Nuclear Information System (INIS)

Maybee, N.

2009-01-01

This paper presented the results of a study in which acoustical measurements at two substations were analyzed to investigate the directional behaviour of typical arrays having 2 or 3 transformers. Substation transformers produce a characteristic humming sound that is caused primarily by vibration of the core at twice the frequency of the power supply. The humming noise radiates predominantly from the tank enclosing the core. The main components of the sound are harmonics of 120 Hz. Sound pressure level data were obtained for various directions and distances from the arrays, ranging from 0.5 m to over 100 m. The measured sound pressure levels of the transformer tones displayed substantial positive and negative excursions from the calculated average values for many distances and directions. The results support the concept that the directional effects are associated with constructive and destructive interference of tonal sound waves emanating from different parts of the array. Significant variations in the directional sound pattern can occur in the near field of a single transformer or an array, and the extent of the near field is significantly larger than the scale of the array. Based on typical dimensions for substation sites, the distance to the far field may be much beyond the substation boundary and beyond typical setbacks to the closest dwellings. As such, the directional sound radiation produced by transformer arrays introduces additional uncertainty in the prediction of substation sound levels at dwellings within a few hundred meters of a substation site. 4 refs., 4 figs.

Entropy, extremality, euclidean variations, and the equations of motion

Science.gov (United States)

Dong, Xi; Lewkowycz, Aitor

2018-01-01

We study the Euclidean gravitational path integral computing the Rényi entropy and analyze its behavior under small variations. We argue that, in Einstein gravity, the extremality condition can be understood from the variational principle at the level of the action, without having to solve explicitly the equations of motion. This set-up is then generalized to arbitrary theories of gravity, where we show that the respective entanglement entropy functional needs to be extremized. We also extend this result to all orders in Newton's constant G N , providing a derivation of quantum extremality. Understanding quantum extremality for mixtures of states provides a generalization of the dual of the boundary modular Hamiltonian which is given by the bulk modular Hamiltonian plus the area operator, evaluated on the so-called modular extremal surface. This gives a bulk prescription for computing the relative entropies to all orders in G N . We also comment on how these ideas can be used to derive an integrated version of the equations of motion, linearized around arbitrary states.

Euclidean supersymmetric solutions with the self-dual Weyl tensor

Directory of Open Access Journals (Sweden)

Masato Nozawa

2017-07-01

Full Text Available We explore the Euclidean supersymmetric solutions admitting the self-dual gauge field in the framework of N=2 minimal gauged supergravity in four dimensions. According to the classification scheme utilizing the spinorial geometry or the bilinears of Killing spinors, the general solution preserves one quarter of supersymmetry and is described by the Przanowski–Tod class with the self-dual Weyl tensor. We demonstrate that there exists an additional Killing spinor, provided the Przanowski–Tod metric admits a Killing vector that commutes with the principal one. The proof proceeds by recasting the metric into another Przanowski–Tod form. This formalism enables us to show that the self-dual Reissner–Nordström–Taub–NUT–AdS metric possesses a second Killing spinor, which has been missed over many years. We also address the supersymmetry when the Przanowski–Tod space is conformal to each of the self-dual ambi-toric Kähler metrics. It turns out that three classes of solutions are all reduced to the self-dual Carter family, by virtue of the nondegenerate Killing–Yano tensor.

The system-dynamic and evolutionary non-Euclidean approach and the 'Lobachevsky-Poincare programme' idea for its successive realization in high energy physics

International Nuclear Information System (INIS)

Bubelev, E.G.; Kuchin, I.A.

1998-01-01

The necessity of creating mesophysics is motivated on the basis of a general likeness of the description of many phenomena and processes in micro- and macroworld. For a general and detailed investigation of the former in modern high energy physics (HEP), the Absolute (arising from Minkovsky and irrespective of any reference system) universal approach is used. Its two conceptually new branches are non-linear system-dynamic and non-Euclidean evolutionary ones. They are complementary ones and completely adequate to an extreme complexity of directly unobservable HEP objects. Some primary problems of them are briefly made clear on the basis of synergetics principles and HEP's internal Lobachevsky-Euclidean geometry. They are noted as the primary content of the Lobachevsky-Poincare Programme (LPP) the idea of which has been proposed recently for their successive solution

The mean distance to the nth neighbour in a uniform distribution of random points: an application of probability theory

International Nuclear Information System (INIS)

Bhattacharyya, Pratip; Chakrabarti, Bikas K

2008-01-01

We study different ways of determining the mean distance (r n ) between a reference point and its nth neighbour among random points distributed with uniform density in a D-dimensional Euclidean space. First, we present a heuristic method; though this method provides only a crude mathematical result, it shows a simple way of estimating (r n ). Next, we describe two alternative means of deriving the exact expression of (r n ): we review the method using absolute probability and develop an alternative method using conditional probability. Finally, we obtain an approximation to (r n ) from the mean volume between the reference point and its nth neighbour and compare it with the heuristic and exact results

Project-based Collaborative learning in distance education

DEFF Research Database (Denmark)

Knudsen, Morten; Bajard, Christine; Helbo, Jan

2004-01-01

) programme indicates, however, that adjustments are required in transforming the on-campus model to distance education. The main problem is that while project work is an excellent regulator of the learning process for on-campus students, this does not seem to be the case for off-campus students. Consequently......This article describes the experiences drawn from an experiment in transferring positive experience with a project-organised on-campus engineering programme to a technology supported distance education programme. Three years of experience with the Master of Industrial Information Technology (MII......, didactic adjustments have been made based on feedback, in particular from evaluation questionnaires. This process has been very constructive in approaching the goal: a successful model for project organized learning in distance education....

Euler numbers of four-dimensional rotating black holes with the Euclidean signature

International Nuclear Information System (INIS)

Ma Zhengze

2003-01-01

For a black hole's spacetime manifold in the Euclidean signature, its metric is positive definite and therefore a Riemannian manifold. It can be regarded as a gravitational instanton and a topological characteristic which is the Euler number to which it is associated. In this paper we derive a formula for the Euler numbers of four-dimensional rotating black holes by the integral of the Euler density on the spacetime manifolds of black holes. Using this formula, we obtain that the Euler numbers of Kerr and Kerr-Newman black holes are 2. We also obtain that the Euler number of the Kerr-Sen metric in the heterotic string theory with one boost angle nonzero is 2, which is in accordance with its topology

The stochastic versus the Euclidean approach to quantum fields on a static space-time

International Nuclear Information System (INIS)

De Angelis, G.F.; de Falco, D.

1986-01-01

Equations are presented which modify the definition of the Gaussian field in the Rindler chart in order to make contact with the Wightman state, the Hartle-Hawking state, and the Euclidean field. By taking Ornstein-Uhlenbeck processes the authors have chosen, in the sense of stochastic mechanics, to place precisely the Fulling modes in their harmonic oscillator ground state. In this respect, together with the periodicity of Minkowski space-time, the authors observe that the covariance of the Ornstein-Uhlenbeck process can be obtained by analytical continuation of the Wightman function of the harmonic oscillator at zero temperature

Does apartment's distance to an in-built transformer room predict magnetic field exposure levels?

Science.gov (United States)

Huss, Anke; Goris, Kelly; Vermeulen, Roel; Kromhout, Hans

2013-01-01

It has been shown that magnetic field exposure in apartments located directly on top or adjacent to transformer rooms is higher compared with exposure in apartments located further away from the transformer rooms. It is unclear whether this also translates into exposure contrast among individuals living in these apartments. We performed spot measurements of magnetic fields in 35 apartments in 14 apartment buildings with an in-built transformer and additionally performed 24-h personal measurements in a subsample of 24 individuals. Apartments placed directly on top of or adjacent to a transformer room had on average exposures of 0.42 μT, apartments on the second floor on top of a transformer room, or sharing a corner or edge with the transformer room had 0.11 μT, and apartments located further away from the transformer room had levels of 0.06 μT. Personal exposure levels were approximately a factor 2 lower compared with apartment averages, but still showed exposure contrasts, but only for those individuals who live in the apartments directly on top or adjacent to a transformer room compared with those living further away, with 0.23 versus 0.06 μT for personal exposure when indoors, respectively. A classification of individuals into 'high' and 'low' exposed based on the location of their apartment within a building with an in-built transformer is possible and could be applied in future epidemiological studies.

The distance-decay function of geographical gravity model: Power law or exponential law?

International Nuclear Information System (INIS)

Chen, Yanguang

2015-01-01

Highlights: •The distance-decay exponent of the gravity model is a fractal dimension. •Entropy maximization accounts for the gravity model based on power law decay. •Allometric scaling relations relate gravity models with spatial interaction models. •The four-parameter gravity models have dual mathematical expressions. •The inverse power law is the most probable distance-decay function. -- Abstract: The distance-decay function of the geographical gravity model is originally an inverse power law, which suggests a scaling process in spatial interaction. However, the distance exponent of the model cannot be reasonably explained with the ideas from Euclidean geometry. This results in a dimension dilemma in geographical analysis. Consequently, a negative exponential function was used to replace the inverse power function to serve for a distance-decay function. But a new puzzle arose that the exponential-based gravity model goes against the first law of geography. This paper is devoted for solving these kinds of problems by mathematical reasoning and empirical analysis. New findings are as follows. First, the distance exponent of the gravity model is demonstrated to be a fractal dimension using the geometric measure relation. Second, the similarities and differences between the gravity models and spatial interaction models are revealed using allometric relations. Third, a four-parameter gravity model possesses a symmetrical expression, and we need dual gravity models to describe spatial flows. The observational data of China's cities and regions (29 elements indicative of 841 data points) in 2010 are employed to verify the theoretical inferences. A conclusion can be reached that the geographical gravity model based on power-law decay is more suitable for analyzing large, complex, and scale-free regional and urban systems. This study lends further support to the suggestion that the underlying rationale of fractal structure is entropy maximization. Moreover

Reprint of "Two-stage sparse coding of region covariance via Log-Euclidean kernels to detect saliency".

Science.gov (United States)

Zhang, Ying-Ying; Yang, Cai; Zhang, Ping

2017-08-01

In this paper, we present a novel bottom-up saliency detection algorithm from the perspective of covariance matrices on a Riemannian manifold. Each superpixel is described by a region covariance matrix on Riemannian Manifolds. We carry out a two-stage sparse coding scheme via Log-Euclidean kernels to extract salient objects efficiently. In the first stage, given background dictionary on image borders, sparse coding of each region covariance via Log-Euclidean kernels is performed. The reconstruction error on the background dictionary is regarded as the initial saliency of each superpixel. In the second stage, an improvement of the initial result is achieved by calculating reconstruction errors of the superpixels on foreground dictionary, which is extracted from the first stage saliency map. The sparse coding in the second stage is similar to the first stage, but is able to effectively highlight the salient objects uniformly from the background. Finally, three post-processing methods-highlight-inhibition function, context-based saliency weighting, and the graph cut-are adopted to further refine the saliency map. Experiments on four public benchmark datasets show that the proposed algorithm outperforms the state-of-the-art methods in terms of precision, recall and mean absolute error, and demonstrate the robustness and efficiency of the proposed method. Copyright © 2017 Elsevier Ltd. All rights reserved.

Determining the Number of Instars in Simulium quinquestriatum (Diptera: Simuliidae) Using k-Means Clustering via the Canberra Distance.

Science.gov (United States)

Yang, Yao Ming; Jia, Ruo; Xun, Hui; Yang, Jie; Chen, Qiang; Zeng, Xiang Guang; Yang, Ming

2018-02-21

Simulium quinquestriatum Shiraki (Diptera: Simuliidae), a human-biting fly that is distributed widely across Asia, is a vector for multiple pathogens. However, the larval development of this species is poorly understood. In this study, we determined the number of instars in this pest using three batches of field-collected larvae from Guiyang, Guizhou, China. The postgenal length, head capsule width, mandibular phragma length, and body length of 773 individuals were measured, and k-means clustering was used for instar grouping. Four distance measures-Manhattan, Euclidean, Chebyshev, and Canberra-were determined. The reported instar numbers, ranging from 4 to 11, were set as initial cluster centers for k-means clustering. The Canberra distance yielded reliable instar grouping, which was consistent with the first instar, as characterized by egg bursters and prepupae with dark histoblasts. Females and males of the last cluster of larvae were identified using Feulgen-stained gonads. Morphometric differences between the two sexes were not significant. Validation was performed using the Brooks-Dyar and Crosby rules, revealing that the larval stage of S. quinquestriatum is composed of eight instars.

Electromagnetic potentials without gauge transformations

International Nuclear Information System (INIS)

Chubykalo, A; Espinoza, A; Alvarado Flores, R

2011-01-01

In this paper, we show that the use of the Helmholtz theorem enables the derivation of uniquely determined electromagnetic potentials without the necessity of using gauge transformation. We show that the electromagnetic field comprises two components, one of which is characterized by instantaneous action at a distance, whereas the other propagates in retarded form with the velocity of light. In our attempt to show the superiority of the new proposed method to the standard one, we argue that the action-at-a-distance components cannot be considered as a drawback of our method, because the recommended procedure for eliminating the action at a distance in the Coulomb gauge leads to theoretical subtleties that allow us to say that the needed gauge transformation is not guaranteed. One of the theoretical consequences of this new definition is that, in addition to the electric E and magnetic B fields, the electromagnetic potentials are real physical quantities. We show that this property of the electromagnetic potentials in quantum mechanics is also a property of the electromagnetic potentials in classical electrodynamics.

Optimal placement of range-only beacons for mobile robot localisation

CSIR Research Space (South Africa)

Burke, Michael G

2011-11-01

Full Text Available of the Euclidean distance between the position estimate (x; y; z) and the largest orthogo- nal standard deviations in 3D space, and is an improvement on the GDOP metric as it considers both off-diagonal covariance terms and individual beacon noise. The beacon... is the Euclidean distance between an accessed node and a goal. This results in the shortest route to a goal being determined. The cost of traversing to a node is typically the distance between nodes. However, by replacing this cost with the uncertainty metric...

Clear evidence of a continuum theory of 4D Euclidean simplicial quantum gravity

International Nuclear Information System (INIS)

Egawa, H.S.; Horata, S.; Yukawa, T.

2002-01-01

Four-dimensional (4D) simplicial quantum gravity coupled to both scalar fields (N X ) and gauge fields (N A ) has been studied using Monte-Carlo simulations. The matter dependence of the string susceptibility exponent γ (4) is estimated. Furthermore, we compare our numerical results with Background-Metric-Independent (BMI) formulation conjectured to describe the quantum field theory of gravity in 4D. The numerical results suggest that the 4D simplicial quantum gravity is related to the conformal gravity in 4D. Therefore, we propose a phase structure in detail with adding both scalar and gauge fields and discuss the possibility and the property of a continuum theory of 4D Euclidean simplicial quantum gravity

Project-Based Collaborative Learning in Distance Education

DEFF Research Database (Denmark)

Knudsen, Morten; Bajard, C.; Helbo, Jan

2003-01-01

This article describes the experiences drawn from an experiment in transferring positive experience with a project-organised on-campus engineering programme to a technology supported distance education programme. Three years of experience with the Master of Industrial Information Technology (MII)......, didactic adjustments have been made based on feedback, in particular from evaluation questionnaires. This process has been very constructive in approaching the goal: a successful model for project organized learning in distance education.......) programme indicates, however, that adjustments are required in transforming the on-campus model to distance education. The main problem is that while project work is an excellent regulator of the learning process for on-campus students, this does not seem to be the case for off-campus students. Consequently......This article describes the experiences drawn from an experiment in transferring positive experience with a project-organised on-campus engineering programme to a technology supported distance education programme. Three years of experience with the Master of Industrial Information Technology (MII...

On application of analytical transformation system using a computer for Feynman intearal calculation

International Nuclear Information System (INIS)

Gerdt, V.P.

1978-01-01

Various systems of analytic transformations for the calculation of Feynman integrals using computers are discussed. The hyperspheric technique Which is used to calculate Feynman integrals enables to perform angular integration for a set of diagrams, thus reducing the multiplicity of integral. All calculations based on this method are made with the ASHMEDAL program. Feynman integrals are calculated in Euclidean space using integration by parts and some differential identities. Analytic calculation of Feynman integral is performed by the MACSYMA system. Dispersion method of integral calculation is implemented in the SCHOONSCHIP system, calculations based on features of Nielsen function are made using efficient SINAC and RSIN programs. A tube of basic Feynman integral parameters calculated using the above techniques is given

Biased discriminant euclidean embedding for content-based image retrieval.

Science.gov (United States)

Bian, Wei; Tao, Dacheng

2010-02-01

With many potential multimedia applications, content-based image retrieval (CBIR) has recently gained more attention for image management and web search. A wide variety of relevance feedback (RF) algorithms have been developed in recent years to improve the performance of CBIR systems. These RF algorithms capture user's preferences and bridge the semantic gap. However, there is still a big room to further the RF performance, because the popular RF algorithms ignore the manifold structure of image low-level visual features. In this paper, we propose the biased discriminative Euclidean embedding (BDEE) which parameterises samples in the original high-dimensional ambient space to discover the intrinsic coordinate of image low-level visual features. BDEE precisely models both the intraclass geometry and interclass discrimination and never meets the undersampled problem. To consider unlabelled samples, a manifold regularization-based item is introduced and combined with BDEE to form the semi-supervised BDEE, or semi-BDEE for short. To justify the effectiveness of the proposed BDEE and semi-BDEE, we compare them against the conventional RF algorithms and show a significant improvement in terms of accuracy and stability based on a subset of the Corel image gallery.

Numerical evaluation of tensor Feynman integrals in Euclidean kinematics

Energy Technology Data Exchange (ETDEWEB)

Gluza, J.; Kajda [Silesia Univ., Katowice (Poland). Inst. of Physics; Riemann, T.; Yundin, V. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany)

2010-10-15

For the investigation of higher order Feynman integrals, potentially with tensor structure, it is highly desirable to have numerical methods and automated tools for dedicated, but sufficiently 'simple' numerical approaches. We elaborate two algorithms for this purpose which may be applied in the Euclidean kinematical region and in d=4-2{epsilon} dimensions. One method uses Mellin-Barnes representations for the Feynman parameter representation of multi-loop Feynman integrals with arbitrary tensor rank. Our Mathematica package AMBRE has been extended for that purpose, and together with the packages MB (M. Czakon) or MBresolve (A. V. Smirnov and V. A. Smirnov) one may perform automatically a numerical evaluation of planar tensor Feynman integrals. Alternatively, one may apply sector decomposition to planar and non-planar multi-loop {epsilon}-expanded Feynman integrals with arbitrary tensor rank. We automatized the preparations of Feynman integrals for an immediate application of the package sectordecomposition (C. Bogner and S. Weinzierl) so that one has to give only a proper definition of propagators and numerators. The efficiency of the two implementations, based on Mellin-Barnes representations and sector decompositions, is compared. The computational packages are publicly available. (orig.)

Modified fuzzy c-means applied to a Bragg grating-based spectral imager for material clustering

Science.gov (United States)

Rodríguez, Aida; Nieves, Juan Luis; Valero, Eva; Garrote, Estíbaliz; Hernández-Andrés, Javier; Romero, Javier

2012-01-01

We have modified the Fuzzy C-Means algorithm for an application related to segmentation of hyperspectral images. Classical fuzzy c-means algorithm uses Euclidean distance for computing sample membership to each cluster. We have introduced a different distance metric, Spectral Similarity Value (SSV), in order to have a more convenient similarity measure for reflectance information. SSV distance metric considers both magnitude difference (by the use of Euclidean distance) and spectral shape (by the use of Pearson correlation). Experiments confirmed that the introduction of this metric improves the quality of hyperspectral image segmentation, creating spectrally more dense clusters and increasing the number of correctly classified pixels.

Representing distance, consuming distance

DEFF Research Database (Denmark)

Larsen, Gunvor Riber

Title: Representing Distance, Consuming Distance Abstract: Distance is a condition for corporeal and virtual mobilities, for desired and actual travel, but yet it has received relatively little attention as a theoretical entity in its own right. Understandings of and assumptions about distance...... are being consumed in the contemporary society, in the same way as places, media, cultures and status are being consumed (Urry 1995, Featherstone 2007). An exploration of distance and its representations through contemporary consumption theory could expose what role distance plays in forming...

Revolution in Communication Technologies: Impact on Distance Education

Science.gov (United States)

Rajesh, M.

2015-01-01

Information and Communication Technologies have transformed the way the world lives and thinks. Education, especially, Distance Education is no different. While the technologies per se are an important factor, the social milieus in which these technologies are implemented are equally important. Technological convergence in the Indian context…

Comparing alternative approaches to measuring the geographical accessibility of urban health services: Distance types and aggregation-error issues

Directory of Open Access Journals (Sweden)

Riva Mylène

2008-02-01

Full Text Available Abstract Background Over the past two decades, geographical accessibility of urban resources for population living in residential areas has received an increased focus in urban health studies. Operationalising and computing geographical accessibility measures depend on a set of four parameters, namely definition of residential areas, a method of aggregation, a measure of accessibility, and a type of distance. Yet, the choice of these parameters may potentially generate different results leading to significant measurement errors. The aim of this paper is to compare discrepancies in results for geographical accessibility of selected health care services for residential areas (i.e. census tracts computed using different distance types and aggregation methods. Results First, the comparison of distance types demonstrates that Cartesian distances (Euclidean and Manhattan distances are strongly correlated with more accurate network distances (shortest network and shortest network time distances across the metropolitan area (Pearson correlation greater than 0.95. However, important local variations in correlation between Cartesian and network distances were observed notably in suburban areas where Cartesian distances were less precise. Second, the choice of the aggregation method is also important: in comparison to the most accurate aggregation method (population-weighted mean of the accessibility measure for census blocks within census tracts, accessibility measures computed from census tract centroids, though not inaccurate, yield important measurement errors for 5% to 10% of census tracts. Conclusion Although errors associated to the choice of distance types and aggregation method are only important for about 10% of census tracts located mainly in suburban areas, we should not avoid using the best estimation method possible for evaluating geographical accessibility. This is especially so if these measures are to be included as a dimension of the

Multiscale Distance Coherence Vector Algorithm for Content-Based Image Retrieval

Science.gov (United States)

Jiexian, Zeng; Xiupeng, Liu

2014-01-01

Multiscale distance coherence vector algorithm for content-based image retrieval (CBIR) is proposed due to the same descriptor with different shapes and the shortcomings of antinoise performance of the distance coherence vector algorithm. By this algorithm, the image contour curve is evolved by Gaussian function first, and then the distance coherence vector is, respectively, extracted from the contour of the original image and evolved images. Multiscale distance coherence vector was obtained by reasonable weight distribution of the distance coherence vectors of evolved images contour. This algorithm not only is invariable to translation, rotation, and scaling transformation but also has good performance of antinoise. The experiment results show us that the algorithm has a higher recall rate and precision rate for the retrieval of images polluted by noise. PMID:24883416

Unstable spiral waves and local Euclidean symmetry in a model of cardiac tissue

International Nuclear Information System (INIS)

Marcotte, Christopher D.; Grigoriev, Roman O.

2015-01-01

This paper investigates the properties of unstable single-spiral wave solutions arising in the Karma model of two-dimensional cardiac tissue. In particular, we discuss how such solutions can be computed numerically on domains of arbitrary shape and study how their stability, rotational frequency, and spatial drift depend on the size of the domain as well as the position of the spiral core with respect to the boundaries. We also discuss how the breaking of local Euclidean symmetry due to finite size effects as well as the spatial discretization of the model is reflected in the structure and dynamics of spiral waves. This analysis allows identification of a self-sustaining process responsible for maintaining the state of spiral chaos featuring multiple interacting spirals

Unstable spiral waves and local Euclidean symmetry in a model of cardiac tissue.

Science.gov (United States)

Marcotte, Christopher D; Grigoriev, Roman O

2015-06-01

This paper investigates the properties of unstable single-spiral wave solutions arising in the Karma model of two-dimensional cardiac tissue. In particular, we discuss how such solutions can be computed numerically on domains of arbitrary shape and study how their stability, rotational frequency, and spatial drift depend on the size of the domain as well as the position of the spiral core with respect to the boundaries. We also discuss how the breaking of local Euclidean symmetry due to finite size effects as well as the spatial discretization of the model is reflected in the structure and dynamics of spiral waves. This analysis allows identification of a self-sustaining process responsible for maintaining the state of spiral chaos featuring multiple interacting spirals.

Fractal and Euclidean geometric diagnostic methodology of uterine cervix cells = Metodología diagnóstica geométrica fractal y euclidiana de células del cuello uterino

Directory of Open Access Journals (Sweden)

Rodríguez Velásquez, Javier Oswaldo

2014-01-01

Full Text Available Background: Pathological interpretation of cellular form in cervical cytology is very important for preven- tion of cervical cancer. The methods most frequently used for assessment of this test have reproducibility and inter-observer variability problems. Objective: To make fractal and Euclidean measure- ments to mathematically diagnose normal and pre- malignant cells of cervical squamous epithelium. Methodology: 21 cells with normal, ASCUS or LSIL diagnosis according to the Bethesda system were assessed. Fractal and Euclidean geometric measures of three mathematical objects were calculated: cyto- plasm, nucleus and whole cell. Mathematical propor- tions between these measurements were calculated in order to compare them with conventional classification methods. Results: It was found that the nuclear border measures calculated with the 2-pixel grill and the surface measures could mathematically and objectively differentiate normal cells from the pre-malignant ones (ASCUS and LSIL. Conclusions: An objective and reproducible diagnos- tic method was developed; it allows to identify the evolution towards malignant cellular states based on simultaneous fractal and Euclidean measures, estab- lishing the severity level of ASCUS and LSIL cells.

Toward Optimal Manifold Hashing via Discrete Locally Linear Embedding.

Science.gov (United States)

Rongrong Ji; Hong Liu; Liujuan Cao; Di Liu; Yongjian Wu; Feiyue Huang

2017-11-01

Binary code learning, also known as hashing, has received increasing attention in large-scale visual search. By transforming high-dimensional features to binary codes, the original Euclidean distance is approximated via Hamming distance. More recently, it is advocated that it is the manifold distance, rather than the Euclidean distance, that should be preserved in the Hamming space. However, it retains as an open problem to directly preserve the manifold structure by hashing. In particular, it first needs to build the local linear embedding in the original feature space, and then quantize such embedding to binary codes. Such a two-step coding is problematic and less optimized. Besides, the off-line learning is extremely time and memory consuming, which needs to calculate the similarity matrix of the original data. In this paper, we propose a novel hashing algorithm, termed discrete locality linear embedding hashing (DLLH), which well addresses the above challenges. The DLLH directly reconstructs the manifold structure in the Hamming space, which learns optimal hash codes to maintain the local linear relationship of data points. To learn discrete locally linear embeddingcodes, we further propose a discrete optimization algorithm with an iterative parameters updating scheme. Moreover, an anchor-based acceleration scheme, termed Anchor-DLLH, is further introduced, which approximates the large similarity matrix by the product of two low-rank matrices. Experimental results on three widely used benchmark data sets, i.e., CIFAR10, NUS-WIDE, and YouTube Face, have shown superior performance of the proposed DLLH over the state-of-the-art approaches.

Bayesian Approach to Spectral Function Reconstruction for Euclidean Quantum Field Theories

Science.gov (United States)

Burnier, Yannis; Rothkopf, Alexander

2013-11-01

We present a novel approach to the inference of spectral functions from Euclidean time correlator data that makes close contact with modern Bayesian concepts. Our method differs significantly from the maximum entropy method (MEM). A new set of axioms is postulated for the prior probability, leading to an improved expression, which is devoid of the asymptotically flat directions present in the Shanon-Jaynes entropy. Hyperparameters are integrated out explicitly, liberating us from the Gaussian approximations underlying the evidence approach of the maximum entropy method. We present a realistic test of our method in the context of the nonperturbative extraction of the heavy quark potential. Based on hard-thermal-loop correlator mock data, we establish firm requirements in the number of data points and their accuracy for a successful extraction of the potential from lattice QCD. Finally we reinvestigate quenched lattice QCD correlators from a previous study and provide an improved potential estimation at T=2.33TC.

New results on embeddings of polyhedra and manifolds in Euclidean spaces

International Nuclear Information System (INIS)

Repovs, D; Skopenkov, A B

1999-01-01

The aim of this survey is to present several classical results on embeddings and isotopies of polyhedra and manifolds in R m . We also describe the revival of interest in this beautiful branch of topology and give an account of new results, including an improvement of the Haefliger-Weber theorem on the completeness of the deleted product obstruction to embeddability and isotopy of highly connected manifolds in R m (Skopenkov) as well as the unimprovability of this theorem for polyhedra (Freedman, Krushkal, Teichner, Segal, Skopenkov, and Spiez) and for manifolds without the necessary connectedness assumption (Skopenkov). We show how algebraic obstructions (in terms of cohomology, characteristic classes, and equivariant maps) arise from geometric problems of embeddability in Euclidean spaces. Several classical and modern results on completeness or incompleteness of these obstructions are stated and proved. By these proofs we illustrate classical and modern tools of geometric topology (engulfing, the Whitney trick, van Kampen and Casson finger moves, and their generalizations)

Medical image compression by using three-dimensional wavelet transformation

International Nuclear Information System (INIS)

Wang, J.; Huang, H.K.

1996-01-01

This paper proposes a three-dimensional (3-D) medical image compression method for computed tomography (CT) and magnetic resonance (MR) that uses a separable nonuniform 3-D wavelet transform. The separable wavelet transform employs one filter bank within two-dimensional (2-D) slices and then a second filter bank on the slice direction. CT and MR image sets normally have different resolutions within a slice and between slices. The pixel distances within a slice are normally less than 1 mm and the distance between slices can vary from 1 mm to 10 mm. To find the best filter bank in the slice direction, the authors use the various filter banks in the slice direction and compare the compression results. The results from the 12 selected MR and CT image sets at various slice thickness show that the Haar transform in the slice direction gives the optimum performance for most image sets, except for a CT image set which has 1 mm slice distance. Compared with 2-D wavelet compression, compression ratios of the 3-D method are about 70% higher for CT and 35% higher for MR image sets at a peak signal to noise ratio (PSNR) of 50 dB. In general, the smaller the slice distance, the better the 3-D compression performance

Linear embeddings of finite-dimensional subsets of Banach spaces into Euclidean spaces

International Nuclear Information System (INIS)

Robinson, James C

2009-01-01

This paper treats the embedding of finite-dimensional subsets of a Banach space B into finite-dimensional Euclidean spaces. When the Hausdorff dimension of X − X is finite, d H (X − X) k are injective on X. The proof motivates the definition of the 'dual thickness exponent', which is the key to proving that a prevalent set of such linear maps have Hölder continuous inverse when the box-counting dimension of X is finite and k > 2d B (X). A related argument shows that if the Assouad dimension of X − X is finite and k > d A (X − X), a prevalent set of such maps are bi-Lipschitz with logarithmic corrections. This provides a new result for compact homogeneous metric spaces via the Kuratowksi embedding of (X, d) into L ∞ (X)

L 1 Generalized Procrustes 2D Shape Alignment

DEFF Research Database (Denmark)

Larsen, Rasmus

2008-01-01

on the orientation of the coordinate system, i.e. it is not rotationally invariant. However, by simultaneously minimizing the city block distances in a series of rotated coordinate systems we are able to approximate the circular equidistance curves of Euclidean distances with a regular polygonal equidistance curve...... to the precision needed. Using 3 coordinate systems rotated 30 degrees we get a 12 sided regular polygon, with which we achieve deviations from Euclidean distances less than 2 % over all directions. This new formulation allows for minimization in the L1-norm using LP. We demonstrate that the use of the L1-norm...

Non-Euclidean phasor analysis for quantification of oxidative stress in ex vivo human skin exposed to sun filters using fluorescence lifetime imaging microscopy

Science.gov (United States)

Osseiran, Sam; Roider, Elisabeth M.; Wang, Hequn; Suita, Yusuke; Murphy, Michael; Fisher, David E.; Evans, Conor L.

2017-12-01

Chemical sun filters are commonly used as active ingredients in sunscreens due to their efficient absorption of ultraviolet (UV) radiation. Yet, it is known that these compounds can photochemically react with UV light and generate reactive oxygen species and oxidative stress in vitro, though this has yet to be validated in vivo. One label-free approach to probe oxidative stress is to measure and compare the relative endogenous fluorescence generated by cellular coenzymes nicotinamide adenine dinucleotides and flavin adenine dinucleotides. However, chemical sun filters are fluorescent, with emissive properties that contaminate endogenous fluorescent signals. To accurately distinguish the source of fluorescence in ex vivo skin samples treated with chemical sun filters, fluorescence lifetime imaging microscopy data were processed on a pixel-by-pixel basis using a non-Euclidean separation algorithm based on Mahalanobis distance and validated on simulated data. Applying this method, ex vivo samples exhibited a small oxidative shift when exposed to sun filters alone, though this shift was much smaller than that imparted by UV irradiation. Given the need for investigative tools to further study the clinical impact of chemical sun filters in patients, the reported methodology may be applied to visualize chemical sun filters and measure oxidative stress in patients' skin.

Tolerance-Based Feature Transforms

NARCIS (Netherlands)

Reniers, Dennie; Telea, Alexandru

2007-01-01

Tolerance-based feature transforms (TFTs) assign to each pixel in an image not only the nearest feature pixels on the boundary (origins), but all origins from the minimum distance up to a user-defined tolerance. In this paper, we compare four simple-to-implement methods for computing TFTs on binary

Spherical stochastic neighbor embedding of hyperspectral data

CSIR Research Space (South Africa)

Lunga, D

2012-07-01

Full Text Available and manifold learning in Euclidean spaces, very few attempts have focused on non-Euclidean spaces. Here, we propose a novel approach that embeds hyperspectral data, transformed into bilateral probability similarities, onto a nonlinear unit norm coordinate...

A Simple but Powerful Heuristic Method for Accelerating k-Means Clustering of Large-Scale Data in Life Science.

Science.gov (United States)

Ichikawa, Kazuki; Morishita, Shinichi

2014-01-01

K-means clustering has been widely used to gain insight into biological systems from large-scale life science data. To quantify the similarities among biological data sets, Pearson correlation distance and standardized Euclidean distance are used most frequently; however, optimization methods have been largely unexplored. These two distance measurements are equivalent in the sense that they yield the same k-means clustering result for identical sets of k initial centroids. Thus, an efficient algorithm used for one is applicable to the other. Several optimization methods are available for the Euclidean distance and can be used for processing the standardized Euclidean distance; however, they are not customized for this context. We instead approached the problem by studying the properties of the Pearson correlation distance, and we invented a simple but powerful heuristic method for markedly pruning unnecessary computation while retaining the final solution. Tests using real biological data sets with 50-60K vectors of dimensions 10-2001 (~400 MB in size) demonstrated marked reduction in computation time for k = 10-500 in comparison with other state-of-the-art pruning methods such as Elkan's and Hamerly's algorithms. The BoostKCP software is available at http://mlab.cb.k.u-tokyo.ac.jp/~ichikawa/boostKCP/.

Pengelompokan Wilayah Madura Berdasar Indikator Pemerataan Pendidikan Menggunakan Partition Around Medoids Dan Validasi Adjusted Random Index

Directory of Open Access Journals (Sweden)

Budi Dwi Satoto

2015-04-01

Full Text Available Distribution of education in Indonesia has become government's attention for a long time. But until now, education in Indonesia is still not evenly distributed. This can be seen from the low value of Participation Rough figures and net enrollment ratio in certain areas as well as uneven educational facilities. The purpose of this research is to provide information to local authorities about the state of education in local region to produce an appropriate policy regarding development of educational infrastructure and teachers assistant distribution. Clustering is a data mining method that divides data into several groups with the same object characteristics. This research used Partition Around Medoids methods with 3 distance measure that contain Manhattan, Euclidean and Canberra distance. Adjusted Random Index used to measure the quality of clustering results. From 3 times sampling, better value of ARI Euclidean distance 0.799, Manhattan distance 0.738 and Canberra distance 0.163 while the best clustering obtained is Euclidean distance with value of ARI 0.825 and compatibility with the original label 83.33%. it is produces high equity group composed of 11 districts with equity groups are composed of 15 districts and low equity group consists of 46 sub-districts.

DISTANCES TO DARK CLOUDS: COMPARING EXTINCTION DISTANCES TO MASER PARALLAX DISTANCES

International Nuclear Information System (INIS)

Foster, Jonathan B.; Jackson, James M.; Stead, Joseph J.; Hoare, Melvin G.; Benjamin, Robert A.

2012-01-01

We test two different methods of using near-infrared extinction to estimate distances to dark clouds in the first quadrant of the Galaxy using large near-infrared (Two Micron All Sky Survey and UKIRT Infrared Deep Sky Survey) surveys. Very long baseline interferometry parallax measurements of masers around massive young stars provide the most direct and bias-free measurement of the distance to these dark clouds. We compare the extinction distance estimates to these maser parallax distances. We also compare these distances to kinematic distances, including recent re-calibrations of the Galactic rotation curve. The extinction distance methods agree with the maser parallax distances (within the errors) between 66% and 100% of the time (depending on method and input survey) and between 85% and 100% of the time outside of the crowded Galactic center. Although the sample size is small, extinction distance methods reproduce maser parallax distances better than kinematic distances; furthermore, extinction distance methods do not suffer from the kinematic distance ambiguity. This validation gives us confidence that these extinction methods may be extended to additional dark clouds where maser parallaxes are not available.

Euclidean scalar Green's functions near the black hole and black brane horizons

International Nuclear Information System (INIS)

Haba, Z

2009-01-01

We discuss approximations of the Riemannian geometry near the horizon. If a (D + 1)-dimensional manifold N has a bifurcate Killing horizon then we approximate N by a product of the two-dimensional Rindler space R 2 and a (D - 1)-dimensional Riemannian manifold M. We obtain approximate formulae for scalar Green's functions. We study the behavior of the Green's functions near the horizon and their dimensional reduction. We show that if M is compact then the Green's function near the horizon can be approximated by the Green's function of the two-dimensional quantum field theory. The correction term is exponentially small away from the horizon. We extend the results to black brane solutions of supergravity in 10 and 11 dimensions. The near-horizon geometry can be approximated by N=AdS p xS q . We discuss the Euclidean Green's functions on N and their behavior near the horizon.

Exact covariant results related to the redshift, aberration and luminosity distance for arbitrary spacetime and instantaneous observers

Energy Technology Data Exchange (ETDEWEB)

Calvao, Maurcio O.; Lago, Bruno L.; Reis, Ribamar R.R. [Universidade Federal do Rio de Janeiro (IF/UFRJ), RJ (Brazil). Inst. de Fisica

2011-07-01

Full text: We start by emphasizing the importance of formalizing the the concepts of a (classical) relativistic instantaneous observer, observer, frame of reference (as distinct from a coordinate system or tetrad) and a local Lorentz boost. Then, as a first result, we apply their concrete definitions to obtain exact covariant expressions for the redshift and aberration, as well as for the redshift transformation under local Lorentz boosts. Afterwards we revisit the notion of luminosity distance, providing some clarifications which render its definition manifestly valid in a completely general setting (not only for comoving observers in the Robertson-Walker spacetime); therefrom we see clearly that (not unexpectedly) the luminosity distance is dependent on the instantaneous observers and we derive its corresponding exact, covariant transformation law. By Etherington's reciprocity theorem, analogous transformation laws can be obtained for other relativistic distances, e.g. the angular size one. The exact covariant transformation law for the luminosity distance has a particularly relevant application for the determination of the impact of peculiar motions on type Ia supernovae observations and data analysis, which is supposed to be one of the main systematic effects plaguing that probe. The redshift and aberration results, on the other hand, might be of interest for precise redshift drift and astrometric (e.g. Gaia) measurements, respectively. We conclude by listing some open avenues for generalizations. (author)

Overlapping community detection based on link graph using distance dynamics

Science.gov (United States)

Chen, Lei; Zhang, Jing; Cai, Li-Jun

2018-01-01

The distance dynamics model was recently proposed to detect the disjoint community of a complex network. To identify the overlapping structure of a network using the distance dynamics model, an overlapping community detection algorithm, called L-Attractor, is proposed in this paper. The process of L-Attractor mainly consists of three phases. In the first phase, L-Attractor transforms the original graph to a link graph (a new edge graph) to assure that one node has multiple distances. In the second phase, using the improved distance dynamics model, a dynamic interaction process is introduced to simulate the distance dynamics (shrink or stretch). Through the dynamic interaction process, all distances converge, and the disjoint community structure of the link graph naturally manifests itself. In the third phase, a recovery method is designed to convert the disjoint community structure of the link graph to the overlapping community structure of the original graph. Extensive experiments are conducted on the LFR benchmark networks as well as real-world networks. Based on the results, our algorithm demonstrates higher accuracy and quality than other state-of-the-art algorithms.

Anthropology in the post-Euclidean State, or from textual to oral anthropology

Directory of Open Access Journals (Sweden)

Antonio Luigi Palmisano

2011-12-01

Full Text Available The actual crisis of anthropology is examined in relation to its wide public success. Anthropology has prospered and the anthropologists have proliferated becoming more specific. But the theoretical debate has come to a halt over the last decades. The article suggests that both the methodology and the form of expression of the ethnographic report have developed and then become crystallized around actual protocols. A critique of the dichotomy Subject/Object, namely the key discussion about the notion of Otherness, is here reexamined as the testimony for an immanent “non-protocolar” character of anthropology. This critique together with the end of anthropology as tekhne, i.e. as protocolar activity, will allow anthropology to go on enhancing many other social and non social sciences. The article discusses the re-definition of anthropology in the context of Daseinanalysis and, therefore the changing relation between man and power, that is between the social actor and the post-Euclidean State in the era of the tekhne.

Euclidean scalar Green function in a higher dimensional global monopole space-time

International Nuclear Information System (INIS)

Bezerra de Mello, E.R.

2002-01-01

We construct the explicit Euclidean scalar Green function associated with a massless field in a higher dimensional global monopole space-time, i.e., a (1+d)-space-time with d≥3 which presents a solid angle deficit. Our result is expressed in terms of an infinite sum of products of Legendre functions with Gegenbauer polynomials. Although this Green function cannot be expressed in a closed form, for the specific case where the solid angle deficit is very small, it is possible to develop the sum and obtain the Green function in a more workable expression. Having this expression it is possible to calculate the vacuum expectation value of some relevant operators. As an application of this formalism, we calculate the renormalized vacuum expectation value of the square of the scalar field, 2 (x)> Ren , and the energy-momentum tensor, μν (x)> Ren , for the global monopole space-time with spatial dimensions d=4 and d=5

Effects of logging on macroinvertebrates in streams with and without buffer strips

Energy Technology Data Exchange (ETDEWEB)

Newbold, J D; Erman, D C; Roby, K B

1980-01-01

The impact of logging with and without buffer strip protection on stream macroinvertebrates was examined through comparisons of community structure in commercially logged and control watersheds throughout northern California. A nonparametric test of community dissimilarities within matched blocks of two control and one or two treated stations showed significant (P < 0.05) logging effects on unprotected streams when Euclidean distance and mutual information were used as dissimilarity indices, but not when chord distance was used. Shannon diversity in unprotected streams was lower (P < 0.01) than in control (unlogged) streams; densities of total macroinvertebrate fauna and of Chironomidae, Baetis, and Nemoura were higher in unprotected streams than in controls (P <0.05). Streams with narrow buffer strips (<30 m) showed significant effects by the Euclidean distance test, but diversity varied widely and was not significantly different from that in either unprotected or control streams than in controls (P < 0.05). Macroinvertebrate communities in streams with wide buffers (greater than or equal to 30m) could not be distinguished from those of controls by either Euclidean distance or diversity; however, diversity in wide-buffered streams was significantly greater than in streams without buffer strips, indicating effective protection from logging effects.

Invisibility cloaking without superluminal propagation

Energy Technology Data Exchange (ETDEWEB)

Perczel, Janos; Leonhardt, Ulf [School of Physics and Astronomy, University of St Andrews, North Haugh, St Andrews KY16 9SS (United Kingdom); Tyc, Tomas, E-mail: jp394@st-andrews.ac.uk, E-mail: tomtyc@physics.muni.cz, E-mail: ulf@st-andrews.ac.uk [Faculty of Science, Kotlarska 2 and Faculty of Informatics, Botanicka 68a, Masaryk University, 61137 Brno (Czech Republic)

2011-08-15

Conventional cloaking based on Euclidean transformation optics requires that the speed of light should tend to infinity on the inner surface of the cloak. Non-Euclidean cloaking still needs media with superluminal propagation. Here we show by giving an example that this is no longer necessary.

Distance Adaptive Tensor Discriminative Geometry Preserving Projection for Face Recognition

Directory of Open Access Journals (Sweden)

Ziqiang Wang

2012-09-01

Full Text Available There is a growing interest in dimensionality reduction techniques for face recognition, however, the traditional dimensionality reduction algorithms often transform the input face image data into vectors before embedding. Such vectorization often ignores the underlying data structure and leads to higher computational complexity. To effectively cope with these problems, a novel dimensionality reduction algorithm termed distance adaptive tensor discriminative geometry preserving projection (DATDGPP is proposed in this paper. The key idea of DATDGPP is as follows: first, the face image data are directly encoded in high-order tensor structure so that the relationships among the face image data can be preserved; second, the data-adaptive tensor distance is adopted to model the correlation among different coordinates of tensor data; third, the transformation matrix which can preserve discrimination and local geometry information is obtained by an iteration algorithm. Experimental results on three face databases show that the proposed algorithm outperforms other representative dimensionality reduction algorithms.

Successive canonical transformation in model two-body electrodynamics

International Nuclear Information System (INIS)

Raha, S.

1978-10-01

The possibility is investigated of bypassing the no interaction theorum of Currie, Jordan and Sudarshan for direct action Lagrangians. Starting with the field theoretic description of a two-body electrodynamic problem, the field variable is solved for in terms of the particle variables, which paves the way to write an action-at-a-distance Hamiltonian for the problem. A suitable transformation is found which uncouples the field and the particle variables in the interaction up to order e 2 . It is shown that this transformation leaves the statement of Newton's 2nd law unchanged which also agrees with the standard results of electrodynamics. This allows for the identification of canonical variables for the proper action-at-a-distance problem. 19 references

Application of Technology in Project-Based Distance Learning

Directory of Open Access Journals (Sweden)

Ali Mehrabian

2008-06-01

Full Text Available Present technology and the accessibility of internet have made distance learning easier, more efficient, and more convenient for students. This technology allows instructors and students to communicate asynchronously, at times and locations of their own choosing, by exchanging printed or electronic information. The use of project-based approach is being recognized in the literature as a potential component of courses in the faculties of engineering, science, and technology. Instructors may have to restructure their course differently to accommodate and facilitate the effectiveness of distance learning. A project-based engineering course, traditionally taught in a classroom settings using live mode at the College of Engineering and Computer Sciences at the University of Central Florida (UCF has been transformed to a distance course taught using distance modes. In this case, pedagogical transitions and adjustments are required, in particular for obtaining an optimal balance between the course material and the project work. Project collaboration in groups requires communication, which is possible with extensive utilization of new information and communication technology, such as virtual meetings. This paper discusses the course transition from live to distance modes and touches on some issues as they relate to the effectiveness of this methodology and the lessons learned from its application within different context. More specifically, this discussion includes the benefit of implementing project-based work in the domain of the distance learning courses.

Distance Education at Conventional Universities in Germany

Directory of Open Access Journals (Sweden)

Hans-Henning Kappel

2002-01-01

Full Text Available Germany’s educational system has undergone a series of transformations during the last 40 years. In recent years, marked increases in enrolment have occurred. In response, admission requirements have been relaxed and new universities have been established.Academic distance education in the former Federal Republic of Germany (West Germany was ushered in by the educational radio broadcasts around the end of the 1960s. Aside from the formation of the FernUniversität (Open University in West Germany in 1975, there were significant developments in distance education occurring at the major universities in the German Democratic Republic (East Germany. After German reunification in 1990, the new unitary state launched programs to advance the development of distance education programs at conventional universities.Germany’s campus-based universities (Präsenzuniversitäten created various entities, including central units and consortia of universities to design and market distance education programs. Hybridisation provides the necessary prerequisites for dual mode delivery, such as basic and continuing education programs, as well as for the combination of distance and campus-based education (Präsenzstudium. Hybridisation also has also opened the door for the creation of new programs.Following an initial phase in which distance education research is expected to centralize a trend towards decentralisation is likely to follow. The German Association for Distance Education (AG-F offers a viable research network in distance education. Two dual mode case studies are also be surveyed: The Master of Arts degree, offered by the University of Koblenz-Landau, with Library Science as the second major, and the University of Kaiserslautern, where basic education will continue to be captured within the domain of the Präsenzstudium or campus-based education.The area in which distance education is flourishing most is within the field of academic continuing

On locating a semi-desirable facility on the continuous plane

DEFF Research Database (Denmark)

Brimberg, Jack; Juel, Henrik

1998-01-01

Euclidean distance from the facility to the closest customer. The objective is to generate the set of efficient points, from which the decision maker must choose the preferred one. Two reformulations are considered: in one, the sum of weighted distances is minimized, subject to constraints requiring...... that each customer must have a weighted Euclidean distance to the facility of at least a given parameter; varying the parameter yields the efficient set. In the other, both criteria are viewed as minimization problems and a convex combination of them is minimized. Properties of the reformulations are given......The paper considers a bicriteria model for locating a semi-desirable facility on the plane. One criterion is that of minimizing the sum of weighted distances between customers and facility, where distances are given by an arbitrary norm. The other criterion is that of maximizing the weighted...

Linear algebra

CERN Document Server

Shilov, Georgi E

1977-01-01

Covers determinants, linear spaces, systems of linear equations, linear functions of a vector argument, coordinate transformations, the canonical form of the matrix of a linear operator, bilinear and quadratic forms, Euclidean spaces, unitary spaces, quadratic forms in Euclidean and unitary spaces, finite-dimensional space. Problems with hints and answers.

Proving Continuity of Coinductive Global Bisimulation Distances: A Never Ending Story

Directory of Open Access Journals (Sweden)

David Romero-Hernández

2015-12-01

Full Text Available We have developed a notion of global bisimulation distance between processes which goes somehow beyond the notions of bisimulation distance already existing in the literature, mainly based on bisimulation games. Our proposal is based on the cost of transformations: how much we need to modify one of the compared processes to obtain the other. Our original definition only covered finite processes, but a coinductive approach allows us to extend it to cover infinite but finitary trees. After having shown many interesting properties of our distance, it was our intention to prove continuity with respect to projections, but unfortunately the issue remains open. Nonetheless, we have obtained several partial results that are presented in this paper.

A Case-Based Reasoning Method with Rank Aggregation

Science.gov (United States)

Sun, Jinhua; Du, Jiao; Hu, Jian

2018-03-01

In order to improve the accuracy of case-based reasoning (CBR), this paper addresses a new CBR framework with the basic principle of rank aggregation. First, the ranking methods are put forward in each attribute subspace of case. The ordering relation between cases on each attribute is got between cases. Then, a sorting matrix is got. Second, the similar case retrieval process from ranking matrix is transformed into a rank aggregation optimal problem, which uses the Kemeny optimal. On the basis, a rank aggregation case-based reasoning algorithm, named RA-CBR, is designed. The experiment result on UCI data sets shows that case retrieval accuracy of RA-CBR algorithm is higher than euclidean distance CBR and mahalanobis distance CBR testing.So we can get the conclusion that RA-CBR method can increase the performance and efficiency of CBR.

Principal distance constraint error diffusion algorithm for homogeneous dot distribution

Science.gov (United States)

Kang, Ki-Min; Kim, Choon-Woo

1999-12-01

The perceived quality of the halftoned image strongly depends on the spatial distribution of the binary dots. Various error diffusion algorithms have been proposed for realizing the homogeneous dot distribution in the highlight and shadow regions. However, they are computationally expensive and/or require large memory space. This paper presents a new threshold modulated error diffusion algorithm for the homogeneous dot distribution. The proposed method is applied exactly same as the Floyd-Steinberg's algorithm except the thresholding process. The threshold value is modulated based on the difference between the distance to the nearest minor pixel, `minor pixel distance', and the principal distance. To do so, calculation of the minor pixel distance is needed for every pixel. But, it is quite time consuming and requires large memory resources. In order to alleviate this problem, `the minor pixel offset array' that transforms the 2D history of minor pixels into the 1D codes is proposed. The proposed algorithm drastically reduces the computational load and memory spaces needed for calculation of the minor pixel distance.

Resistance Distances in Vertex-Face Graphs

Science.gov (United States)

Shangguan, Yingmin; Chen, Haiyan

2018-01-01

The computation of two-point resistances in networks is a classical problem in electric circuit theory and graph theory. Let G be a triangulation graph with n vertices embedded on an orientable surface. Define K(G) to be the graph obtained from G by inserting a new vertex vϕ to each face ϕ of G and adding three new edges (u, vϕ), (v, vϕ) and (w, vϕ), where u, v and w are three vertices on the boundary of ϕ. In this paper, using star-triangle transformation and resistance local-sum rules, explicit relations between resistance distances in K(G) and those in G are obtained. These relations enable us to compute resistance distance between any two points of Kk(G) recursively. As explanation examples, some resistances in several networks are computed, including the modified Apollonian network and networks constructed from tetrahedron, octahedron and icosahedron, respectively.

Penerapan Algoritma A Star (A* pada Game Petualangan Labirin Berbasis Android

Directory of Open Access Journals (Sweden)

Wahyu Widodo

2018-01-01

Full Text Available Game memiliki arti dasar permainan, permainan dalam hal ini merujuk pada pengertian kelincahan intelektual. Di dalam penerapannya, sebuah Game tentu memerlukan sebuah AI (Artificial Intelligence, dan AI yang digunakan dalam pembangunan Game petualangan labirin ini adalah algoritma A* (A Star dengan euclidean distance. Algoritma ini merupakan algoritma pencarian untuk menemukan rute terpendek dengan cost paling minimum, algoritma A* mencari rute terpendek dengan menjumlahkan jarak sebenarnya dengan jarak perkiraan sehingga membuatnya optimum dan complete. Petualangan labirin merupakan Game yang menceritakan mengenai petualangan kelinci melewati sebuah labirin untuk mencari makanannya. Genre dari Game ini adalah adventure dan puzzle, dibangun dengan bahasa pemrograman java dengan tools Android Studio, AI yang digunakan adalah algoritma A* dengan euclidean distance yang digunakan pada bantuan untuk melakukan pencarian jalur guna menemukan makanan kelinci. Hasil uji dari Game Petualangan labirin ini adalah jika pemain dalam kesusahan menemukan jalur menuju makanan kelinci, maka pemain dapat menggunakan tombol bantuan yang akan dicarikan jalur terpendek oleh algoritma A* (A Star dengan euclidean distance untuk menuju lokasi tempat makanan kelinci berada.

Angular Distribution of GRBs

Directory of Open Access Journals (Sweden)

L. G. Balázs

2012-01-01

Full Text Available We studied the complete randomness of the angular distribution of BATSE gamma-ray bursts (GRBs. Based on their durations and peak fluxes, we divided the BATSE sample into 5 subsamples (short1, short2, intermediate, long1, long2 and studied the angular distributions separately. We used three methods to search for non-randomness in the subsamples: Voronoi tesselation, minimal spanning tree, and multifractal spectra. To study any non-randomness in the subsamples we defined 13 test-variables (9 from Voronoi tesselation, 3 from the minimal spanning tree and one from the multifractal spectrum. We made Monte Carlo simulations taking into account the BATSE’s sky-exposure function. We tested therandomness by introducing squared Euclidean distances in the parameter space of the test-variables. We recognized that the short1, short2 groups deviate significantly (99.90%, 99.98% from the fully random case in the distribution of the squared Euclidean distances but this is not true for the long samples. In the intermediate group, the squared Euclidean distances also give significant deviation (98.51%.

Gender classification in children based on speech characteristics: using fundamental and formant frequencies of Malay vowels.

Science.gov (United States)

Zourmand, Alireza; Ting, Hua-Nong; Mirhassani, Seyed Mostafa

2013-03-01

Speech is one of the prevalent communication mediums for humans. Identifying the gender of a child speaker based on his/her speech is crucial in telecommunication and speech therapy. This article investigates the use of fundamental and formant frequencies from sustained vowel phonation to distinguish the gender of Malay children aged between 7 and 12 years. The Euclidean minimum distance and multilayer perceptron were used to classify the gender of 360 Malay children based on different combinations of fundamental and formant frequencies (F0, F1, F2, and F3). The Euclidean minimum distance with normalized frequency data achieved a classification accuracy of 79.44%, which was higher than that of the nonnormalized frequency data. Age-dependent modeling was used to improve the accuracy of gender classification. The Euclidean distance method obtained 84.17% based on the optimal classification accuracy for all age groups. The accuracy was further increased to 99.81% using multilayer perceptron based on mel-frequency cepstral coefficients. Copyright © 2013 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

Green functions and dimensional reduction of quantum fields on product manifolds

International Nuclear Information System (INIS)

Haba, Z

2008-01-01

We discuss Euclidean Green functions on product manifolds P=N x M. We show that if M is compact and N is not compact then the Euclidean field on P can be approximated by its zero mode which is a Euclidean field on N. We estimate the remainder of this approximation. We show that for large distances on N the remainder is small. If P=R D-1 x S β , where S β is a circle of radius β, then the result reduces to the well-known approximation of the D-dimensional finite temperature quantum field theory by (D - 1)-dimensional one in the high-temperature limit. Analytic continuation of Euclidean fields is discussed briefly

Zernike Basis to Cartesian Transformations

Science.gov (United States)

Mathar, R. J.

2009-12-01

The radial polynomials of the 2D (circular) and 3D (spherical) Zernike functions are tabulated as powers of the radial distance. The reciprocal tabulation of powers of the radial distance in series of radial polynomials is also given, based on projections that take advantage of the orthogonality of the polynomials over the unit interval. They play a role in the expansion of products of the polynomials into sums, which is demonstrated by some examples. Multiplication of the polynomials by the angular bases (azimuth, polar angle) defines the Zernike functions, for which we derive transformations to and from the Cartesian coordinate system centered at the middle of the circle or sphere.

Non-Hermitian systems of Euclidean Lie algebraic type with real energy spectra

Science.gov (United States)

Dey, Sanjib; Fring, Andreas; Mathanaranjan, Thilagarajah

2014-07-01

We study several classes of non-Hermitian Hamiltonian systems, which can be expressed in terms of bilinear combinations of Euclidean-Lie algebraic generators. The classes are distinguished by different versions of antilinear (PT)-symmetries exhibiting various types of qualitative behaviour. On the basis of explicitly computed non-perturbative Dyson maps we construct metric operators, isospectral Hermitian counterparts for which we solve the corresponding time-independent Schrödinger equation for specific choices of the coupling constants. In these cases general analytical expressions for the solutions are obtained in the form of Mathieu functions, which we analyze numerically to obtain the corresponding energy spectra. We identify regions in the parameter space for which the corresponding spectra are entirely real and also domains where the PT symmetry is spontaneously broken and sometimes also regained at exceptional points. In some cases it is shown explicitly how the threshold region from real to complex spectra is characterized by the breakdown of the Dyson maps or the metric operator. We establish the explicit relationship to models currently under investigation in the context of beam dynamics in optical lattices.

The Metric of Colour Space

DEFF Research Database (Denmark)

Gravesen, Jens

2015-01-01

and found the MacAdam ellipses which are often interpreted as defining the metric tensor at their centres. An important question is whether it is possible to define colour coordinates such that the Euclidean distance in these coordinates correspond to human perception. Using cubic splines to represent......The space of colours is a fascinating space. It is a real vector space, but no matter what inner product you put on the space the resulting Euclidean distance does not correspond to human perception of difference between colours. In 1942 MacAdam performed the first experiments on colour matching...

Computing the Expected Value and Variance of Geometric Measures

DEFF Research Database (Denmark)

Staals, Frank; Tsirogiannis, Constantinos

2017-01-01

distance (MPD), the squared Euclidean distance from the centroid, and the diameter of the minimum enclosing disk. We also describe an efficient (1-e)-approximation algorithm for computing the mean and variance of the mean pairwise distance. We implemented three of our algorithms and we show that our...

Inversion: A Most Useful Kind of Transformation.

Science.gov (United States)

Dubrovsky, Vladimir

1992-01-01

The transformation assigning to every point its inverse with respect to a circle with given radius and center is called an inversion. Discusses inversion with respect to points, circles, angles, distances, space, and the parallel postulate. Exercises related to these topics are included. (MDH)

The Euclidean scalar Green function in the five-dimensional Kaluza-Klein magnetic monopole space-time

International Nuclear Information System (INIS)

Bezerra de Mello, E.R.

2006-01-01

In this paper we present, in a integral form, the Euclidean Green function associated with a massless scalar field in the five-dimensional Kaluza-Klein magnetic monopole superposed to a global monopole, admitting a nontrivial coupling between the field with the geometry. This Green function is expressed as the sum of two contributions: the first one related with uncharged component of the field, is similar to the Green function associated with a scalar field in a four-dimensional global monopole space-time. The second contains the information of all the other components. Using this Green function it is possible to study the vacuum polarization effects on this space-time. Explicitly we calculate the renormalized vacuum expectation value * (x)Φ(x)> Ren , which by its turn is also expressed as the sum of two contributions

Isomap transform for segmenting human body shapes.

Science.gov (United States)

Cerveri, P; Sarro, K J; Marchente, M; Barros, R M L

2011-09-01

Segmentation of the 3D human body is a very challenging problem in applications exploiting volume capture data. Direct clustering in the Euclidean space is usually complex or even unsolvable. This paper presents an original method based on the Isomap (isometric feature mapping) transform of the volume data-set. The 3D articulated posture is mapped by Isomap in the pose of Da Vinci's Vitruvian man. The limbs are unrolled from each other and separated from the trunk and pelvis, and the topology of the human body shape is recovered. In such a configuration, Hoshen-Kopelman clustering applied to concentric spherical shells is used to automatically group points into the labelled principal curves. Shepard interpolation is utilised to back-map points of the principal curves into the original volume space. The experimental results performed on many different postures have proved the validity of the proposed method. Reliability of less than 2 cm and 3° in the location of the joint centres and direction axes of rotations has been obtained, respectively, which qualifies this procedure as a potential tool for markerless motion analysis.

Zernike Basis to Cartesian Transformations

Directory of Open Access Journals (Sweden)

Mathar, R. J.

2009-12-01

Full Text Available The radial polynomials of the 2D (circular and 3D (spherical Zernike functions are tabulated as powers of the radial distance. The reciprocal tabulation of powers of the radial distance in series of radial polynomials is also given, based on projections that take advantage of the orthogonality of the polynomials over the unit interval. They play a role in the expansion of products of the polynomials into sums, which is demonstrated by some examples. Multiplication of the polynomials by the angular bases (azimuth, polar angle defines the Zernike functions, for which we derive transformations to and from the Cartesian coordinate system centered at the middle of the circle or sphere.

Zernike basis to cartesian transformations

Directory of Open Access Journals (Sweden)

Mathar R.J.

2009-01-01

Full Text Available The radial polynomials of the 2D (circular and 3D (spherical Zernike functions are tabulated as powers of the radial distance. The reciprocal tabulation of powers of the radial distance in series of radial polynomials is also given, based on projections that take advantage of the orthogonality of the polynomials over the unit interval. They play a role in the expansion of products of the polynomials into sums, which is demonstrated by some examples. Multiplication of the polynomials by the angular bases (azimuth, polar angle defines the Zernike functions, for which we derive transformations to and from the Cartesian coordinate system centered at the middle of the circle or sphere.

Real-Time Pathogen Detection in the Era of Whole-Genome Sequencing and Big Data: Comparison of k-mer and Site-Based Methods for Inferring the Genetic Distances among Tens of Thousands of Salmonella Samples.

Science.gov (United States)

Pettengill, James B; Pightling, Arthur W; Baugher, Joseph D; Rand, Hugh; Strain, Errol

2016-01-01

The adoption of whole-genome sequencing within the public health realm for molecular characterization of bacterial pathogens has been followed by an increased emphasis on real-time detection of emerging outbreaks (e.g., food-borne Salmonellosis). In turn, large databases of whole-genome sequence data are being populated. These databases currently contain tens of thousands of samples and are expected to grow to hundreds of thousands within a few years. For these databases to be of optimal use one must be able to quickly interrogate them to accurately determine the genetic distances among a set of samples. Being able to do so is challenging due to both biological (evolutionary diverse samples) and computational (petabytes of sequence data) issues. We evaluated seven measures of genetic distance, which were estimated from either k-mer profiles (Jaccard, Euclidean, Manhattan, Mash Jaccard, and Mash distances) or nucleotide sites (NUCmer and an extended multi-locus sequence typing (MLST) scheme). When analyzing empirical data (whole-genome sequence data from 18,997 Salmonella isolates) there are features (e.g., genomic, assembly, and contamination) that cause distances inferred from k-mer profiles, which treat absent data as informative, to fail to accurately capture the distance between samples when compared to distances inferred from differences in nucleotide sites. Thus, site-based distances, like NUCmer and extended MLST, are superior in performance, but accessing the computing resources necessary to perform them may be challenging when analyzing large databases.

Real-Time Pathogen Detection in the Era of Whole-Genome Sequencing and Big Data: Comparison of k-mer and Site-Based Methods for Inferring the Genetic Distances among Tens of Thousands of Salmonella Samples.

Directory of Open Access Journals (Sweden)

James B Pettengill

Full Text Available The adoption of whole-genome sequencing within the public health realm for molecular characterization of bacterial pathogens has been followed by an increased emphasis on real-time detection of emerging outbreaks (e.g., food-borne Salmonellosis. In turn, large databases of whole-genome sequence data are being populated. These databases currently contain tens of thousands of samples and are expected to grow to hundreds of thousands within a few years. For these databases to be of optimal use one must be able to quickly interrogate them to accurately determine the genetic distances among a set of samples. Being able to do so is challenging due to both biological (evolutionary diverse samples and computational (petabytes of sequence data issues. We evaluated seven measures of genetic distance, which were estimated from either k-mer profiles (Jaccard, Euclidean, Manhattan, Mash Jaccard, and Mash distances or nucleotide sites (NUCmer and an extended multi-locus sequence typing (MLST scheme. When analyzing empirical data (whole-genome sequence data from 18,997 Salmonella isolates there are features (e.g., genomic, assembly, and contamination that cause distances inferred from k-mer profiles, which treat absent data as informative, to fail to accurately capture the distance between samples when compared to distances inferred from differences in nucleotide sites. Thus, site-based distances, like NUCmer and extended MLST, are superior in performance, but accessing the computing resources necessary to perform them may be challenging when analyzing large databases.

Geometric influences of a particle confined to a curved surface embedded in three-dimensional Euclidean space

Science.gov (United States)

Wang, Yong-Long; Jiang, Hua; Zong, Hong-Shi

2017-08-01

In the spirit of the thin-layer quantization approach, we give the formula of the geometric influences of a particle confined to a curved surface embedded in three-dimensional Euclidean space. The geometric contributions can result from the reduced commutation relation between the acted function depending on normal variable and the normal derivative. According to the formula, we obtain the geometric potential, geometric momentum, geometric orbital angular momentum, geometric linear Rashba, and cubic Dresselhaus spin-orbit couplings. As an example, a truncated cone surface is considered. We find that the geometric orbital angular momentum can provide an azimuthal polarization for spin, and the sign of the geometric Dresselhaus spin-orbit coupling can be flipped through the inclination angle of generatrix.

Biometric identification of cardiosynchronous waveforms utilizing person specific continuous and discrete wavelet transform features.

Science.gov (United States)

Bhagavatula, Chandrasekhar; Venugopalan, Shreyas; Blue, Rebecca; Friedman, Robert; Griofa, Marc O; Savvides, Marios; Kumar, B V K Vijaya

2012-01-01

In this paper we explore how a Radio Frequency Impedance Interrogation (RFII) signal may be used as a biometric feature. This could allow the identification of subjects in operational and potentially hostile environments. Features extracted from the continuous and discrete wavelet decompositions of the signal are investigated for biometric identification. In the former case, the most discriminative features in the wavelet space were extracted using a Fisher ratio metric. Comparisons in the wavelet space were done using the Euclidean distance measure. In the latter case, the signal was decomposed at various levels using different wavelet bases, in order to extract both low frequency and high frequency components. Comparisons at each decomposition level were performed using the same distance measure as before. The data set used consists of four subjects, each with a 15 minute RFII recording. The various data samples for our experiments, corresponding to a single heart beat duration, were extracted from these recordings. We achieve identification rates of up to 99% using the CWT approach and rates of up to 100% using the DWT approach. While the small size of the dataset limits the interpretation of these results, further work with larger datasets is expected to develop better algorithms for subject identification.

Full-Angle Quaternions for Robustly Matching Vectors of 3D Rotations

NARCIS (Netherlands)

Liwicki, Stephan; Pham, Minh-Tri; Zafeiriou, Stefanos; Pantic, Maja; Stenger, Björn

In this paper we introduce a new distance for robustly matching vectors of 3D rotations. A special representation of 3D rotations, which we coin full-angle quaternion (FAQ), allows us to express this distance as Euclidean. We apply the distance to the problems of 3D shape recognition from point

Iris recognition using image moments and k-means algorithm.

Science.gov (United States)

Khan, Yaser Daanial; Khan, Sher Afzal; Ahmad, Farooq; Islam, Saeed

2014-01-01

This paper presents a biometric technique for identification of a person using the iris image. The iris is first segmented from the acquired image of an eye using an edge detection algorithm. The disk shaped area of the iris is transformed into a rectangular form. Described moments are extracted from the grayscale image which yields a feature vector containing scale, rotation, and translation invariant moments. Images are clustered using the k-means algorithm and centroids for each cluster are computed. An arbitrary image is assumed to belong to the cluster whose centroid is the nearest to the feature vector in terms of Euclidean distance computed. The described model exhibits an accuracy of 98.5%.

[Mahalanobis distance based hyperspectral characteristic discrimination of leaves of different desert tree species].

Science.gov (United States)

Lin, Hai-jun; Zhang, Hui-fang; Gao, Ya-qi; Li, Xia; Yang, Fan; Zhou, Yan-fei

2014-12-01

The hyperspectral reflectance of Populus euphratica, Tamarix hispida, Haloxylon ammodendron and Calligonum mongolicum in the lower reaches of Tarim River and Turpan Desert Botanical Garden was measured by using the HR-768 field-portable spectroradiometer. The method of continuum removal, first derivative reflectance and second derivative reflectance were used to deal with the original spectral data of four tree species. The method of Mahalanobis Distance was used to select the bands with significant differences in the original spectral data and transform spectral data to identify the different tree species. The progressive discrimination analyses were used to test the selective bands used to identify different tree species. The results showed that The Mahalanobis Distance method was an effective method in feature band extraction. The bands for identifying different tree species were most near-infrared bands. The recognition accuracy of four methods was 85%, 93.8%, 92.4% and 95.5% respectively. Spectrum transform could improve the recognition accuracy. The recognition accuracy of different research objects and different spectrum transform methods were different. The research provided evidence for desert tree species classification, monitoring biodiversity and the analysis of area in desert by using large scale remote sensing method.

Renormalized G-convolution of n-point functions in quantum field theory. I. The Euclidean case

International Nuclear Information System (INIS)

Bros, Jacques; Manolessou-Grammaticou, Marietta.

1977-01-01

The notion of Feynman amplitude associated with a graph G in perturbative quantum field theory admits a generalized version in which each vertex v of G is associated with a general (non-perturbative) nsub(v)-point function Hsup(nsub(v)), nsub(v) denoting the number of lines which are incident to v in G. In the case where no ultraviolet divergence occurs, this has been performed directly in complex momentum space through Bros-Lassalle's G-convolution procedure. The authors propose a generalization of G-convolution which includes the case when the functions Hsup(nsub(v)) are not integrable at infinity but belong to a suitable class of slowly increasing functions. A finite part of the G-convolution integral is then defined through an algorithm which closely follows Zimmermann's renormalization scheme. The case of Euclidean four-momentum configurations is only treated

Polymer deposition morphology by electrospray deposition - Modifications through distance variation

International Nuclear Information System (INIS)

Altmann, K.; Schulze, R.-D.; Friedrich, J.

2014-01-01

Electrospray deposition (ESD) of highly diluted polymers was examined with regard to the deposited surface structure. Only the flight distance (flight time) onto the resulting deposited surface was varied from 20 to 200 mm. An apparatus without any additional heating or gas flows was used. Polyacrylic acid (PAA) and polyallylamine (PAAm) in methanol were deposited on Si wafers. The polymer layers were characterized by scanning electron microscopy, X-ray photoelectron spectroscopy, derivatization reactions and Fourier transform infrared spectroscopy using a grazing incidence unit. SEM images illustrated the changing structures of PAA and PAAm. For PAA the deposited structure changed from a smooth film (20 mm) to a film with individual droplets on the coated surface (100 mm and 200 mm), while for PAAm individual droplets can be seen at all distances. The ESD process with cascades of splitting droplets slows down for PAA after distances greater than 40 mm. In contrast, the ESD process for PAAm is nearly stopped within the first flight distance of 20 mm. Residual solvent analysis showed that most of the solvent evaporated within the first 20 mm capillary-sample distance. - Highlights: • We deposited polyacrylic acid and polyallylamine by electrospray ionization (ESI). • The morphology in dependence of flight distance (20 mm to 200 mm) was analyzed. • The amount of residual solvent after deposition was determined. • ESI-process slows down for polyacrylic acid after 40 mm flight distance. • ESI-Process is complete for polyallylamine within the first 20 mm

Quantitative Comparison of Tolerance-Based Feature Transforms

NARCIS (Netherlands)

Reniers, Dennie; Telea, Alexandru

2006-01-01

Tolerance-based feature transforms (TFTs) assign to each pixel in an image not only the nearest feature pixels on the boundary (origins), but all origins from the minimum distance up to a user-defined tolerance. In this paper, we compare four simple-to-implement methods for computing TFTs for binary

Steiner trees in industry

CERN Document Server

Du, Ding-Zhu

2001-01-01

This book is a collection of articles studying various Steiner tree prob­ lems with applications in industries, such as the design of electronic cir­ cuits, computer networking, telecommunication, and perfect phylogeny. The Steiner tree problem was initiated in the Euclidean plane. Given a set of points in the Euclidean plane, the shortest network interconnect­ ing the points in the set is called the Steiner minimum tree. The Steiner minimum tree may contain some vertices which are not the given points. Those vertices are called Steiner points while the given points are called terminals. The shortest network for three terminals was first studied by Fermat (1601-1665). Fermat proposed the problem of finding a point to minimize the total distance from it to three terminals in the Euclidean plane. The direct generalization is to find a point to minimize the total distance from it to n terminals, which is still called the Fermat problem today. The Steiner minimum tree problem is an indirect generalization. Sch...

Transforming Exploratory Creativity with DeLeNoX

DEFF Research Database (Denmark)

Liapis, Antonios; Martínez, Héctor Pérez; Togelius, Julian

2013-01-01

We introduce DeLeNoX (Deep Learning Novelty Explorer), a system that autonomously creates artifacts in constrained spaces according to its own evolving interestingness criterion. DeLeNoX proceeds in alternating phases of exploration and transformation. In the exploration phases, a version...... of novelty search augmented with constraint handling searches for maximally diverse artifacts using a given distance function. In the transformation phases, a deep learning autoencoder learns to compress the variation between the found artifacts into a lower-dimensional space. The newly trained encoder...

Modeling of Electric Field Around 100 MVA 150/20 kV Power Transformator using Charge Simulation Method

Directory of Open Access Journals (Sweden)

Noviadi Arief Rachman

2013-07-01

Full Text Available Charge Simulation Method is one of the field theory that can be used as an approach to calculate the electromagnetic distribution on the electrical conductor. This paper discussed electric field modeling around power transformator by using Matlab to find the safety distance. The safe distance threshold of the electric field to human health refers to WHO and SNI was 5 kV/m. The specification of the power transformator was three phases, 150/20 kV, and 100 MVA. The basic concept is to change the distribution charge on the conductor or dielectric polarization charge with a set of discrete fictitious charge. The value of discrete fictitious charge was equivalent to the potential value of the conductor, and became a reference to calculate the electric field around the surface contour of the selected power transformator. The measurement distance was 5 meter on each side of the transformator surface. The results showed that the magnitude of the electric field at the front side was 5541 V/m, exceeding the safety limits.

Towards an intelligent environment for distance learning

Directory of Open Access Journals (Sweden)

Rafael Morales

2009-12-01

Full Text Available Mainstream distance learning nowadays is heavily influenced by traditional educational approaches that produceshomogenised learning scenarios for all learners through learning management systems. Any differentiation betweenlearners and personalisation of their learning scenarios is left to the teacher, who gets minimum support from the system inthis respect. This way, the truly digital native, the computer, is left out of the move, unable to better support the teachinglearning processes because it is not provided with the means to transform into knowledge all the information that it storesand manages. I believe learning management systems should care for supporting adaptation and personalisation of bothindividual learning and the formation of communities of learning. Open learner modelling and intelligent collaborativelearning environments are proposed as a means to care. The proposal is complemented with a general architecture for anintelligent environment for distance learning and an educational model based on the principles of self-management,creativity, significance and participation.

Spontaneous cluster activity in the inferior olivary nucleus in brainstem slices from postnatal mice

DEFF Research Database (Denmark)

Rekling, Jens C; Reveles Jensen, Kristian; Jahnsen, Henrik

2012-01-01

-active with separate clusters at different times. The coherence between calcium transients in IO neurons decreased with Euclidean distance between the cells reaching low values at 100-200 µm distances. Intracellular recordings from IO neurons during cluster formation revealed the presence of spikelet-like potentials...

Paradigm Shift in Distance Education in the 21st Century

Directory of Open Access Journals (Sweden)

Mehmet FIRAT

2016-10-01

Full Text Available Information and communication technologies have been one of a driving force which enables higher education expansion and gives a dynamic structure to the science in the twenty-first century. One of the most effective users of this driving force in higher education is distance education. Previously, distance education was considered to be as a method to ensure equality of opportunity in education, and partly to meet the educational needs of citizens in limited circumstances; today it has undergone an incontrovertible paradigm shift by transforming into an interdisciplinary science field with its functional flexibility, strong technology infrastructure, diversity of programs, innovative teaching approaches and rapidly increasing student numbers. In this study, it is aimed to reveal this paradigm shift with a historical point of view, and the information technology supported rise and paradigm shift of distance education is evaluated by a holistic perspective from different point of views of different perspectives from the studies in literature to the current research topics.

DOCUMENT IMAGE REGISTRATION FOR IMPOSED LAYER EXTRACTION

Directory of Open Access Journals (Sweden)

Surabhi Narayan

2017-02-01

Full Text Available Extraction of filled-in information from document images in the presence of template poses challenges due to geometrical distortion. Filled-in document image consists of null background, general information foreground and vital information imposed layer. Template document image consists of null background and general information foreground layer. In this paper a novel document image registration technique has been proposed to extract imposed layer from input document image. A convex polygon is constructed around the content of the input and the template image using convex hull. The vertices of the convex polygons of input and template are paired based on minimum Euclidean distance. Each vertex of the input convex polygon is subjected to transformation for the permutable combinations of rotation and scaling. Translation is handled by tight crop. For every transformation of the input vertices, Minimum Hausdorff distance (MHD is computed. Minimum Hausdorff distance identifies the rotation and scaling values by which the input image should be transformed to align it to the template. Since transformation is an estimation process, the components in the input image do not overlay exactly on the components in the template, therefore connected component technique is applied to extract contour boxes at word level to identify partially overlapping components. Geometrical features such as density, area and degree of overlapping are extracted and compared between partially overlapping components to identify and eliminate components common to input image and template image. The residue constitutes imposed layer. Experimental results indicate the efficacy of the proposed model with computational complexity. Experiment has been conducted on variety of filled-in forms, applications and bank cheques. Data sets have been generated as test sets for comparative analysis.

The Challenges for Marketing Distance Education in Online Environment: An Intergrated Approach

Science.gov (United States)

Demiray, Ugur, Ed.; Sever, N. Serdar, Ed.

2009-01-01

The education system of our times has transformed greatly due to enormous developments in the IT field, ease in access to online resources by the individuals and the teachers adopting new technologies in their instructional strategies, be it for course design, development or delivery. The field of Distance and Online Education is experiencing…

On Finding the Shortest Distance of a Point From a Line: Which ...

Indian Academy of Sciences (India)

One more application is in disaster management in the vicinity of high ... A proper safety dis- .... of a point in the n-dimensional Euclidean space Rn from a hyper- plane. Let the ... Let the coordinates in the new system be represented by. (x ,y ).

Early detection of rogue waves by the wavelet transforms

International Nuclear Information System (INIS)

Bayındır, Cihan

2016-01-01

Highlights: • The advantages of wavelet analysis over the Fourier analysis for the early detection of rogue waves are discussed. • The triangular wavelet spectra can be detected at early stages of the development of rogue waves. • The wavelet analysis is capable of detecting not only the emergence but also the location of a rogue wave. • Wavelet analysis is also capable of predicting the characteristic distances between successive rogue waves. - Abstract: We discuss the possible advantages of using the wavelet transform over the Fourier transform for the early detection of rogue waves. We show that the triangular wavelet spectra of the rogue waves can be detected at early stages of the development of rogue waves in a chaotic wave field. Compared to the Fourier spectra, the wavelet spectra are capable of detecting not only the emergence of a rogue wave but also its possible spatial (or temporal) location. Due to this fact, wavelet transform is also capable of predicting the characteristic distances between successive rogue waves. Therefore multiple simultaneous breaking of the successive rogue waves on ships or on the offshore structures can be predicted and avoided by smart designs and operations.

Early detection of rogue waves by the wavelet transforms

Energy Technology Data Exchange (ETDEWEB)

Bayındır, Cihan, E-mail: cihan.bayindir@isikun.edu.tr

2016-01-08

Highlights: • The advantages of wavelet analysis over the Fourier analysis for the early detection of rogue waves are discussed. • The triangular wavelet spectra can be detected at early stages of the development of rogue waves. • The wavelet analysis is capable of detecting not only the emergence but also the location of a rogue wave. • Wavelet analysis is also capable of predicting the characteristic distances between successive rogue waves. - Abstract: We discuss the possible advantages of using the wavelet transform over the Fourier transform for the early detection of rogue waves. We show that the triangular wavelet spectra of the rogue waves can be detected at early stages of the development of rogue waves in a chaotic wave field. Compared to the Fourier spectra, the wavelet spectra are capable of detecting not only the emergence of a rogue wave but also its possible spatial (or temporal) location. Due to this fact, wavelet transform is also capable of predicting the characteristic distances between successive rogue waves. Therefore multiple simultaneous breaking of the successive rogue waves on ships or on the offshore structures can be predicted and avoided by smart designs and operations.

Modeling of Electric Field Around 100 MVA 150/20 KV Power Transformator Using Charge Simulation Method

OpenAIRE

Rachman, Noviadi Arief; Risdiyanto, Agus; Ramdan, Ade

2013-01-01

Charge Simulation Method is one of the field theory that can be used as an approach to calculate the electromagnetic distribution on the electrical conductor. This paper discussed electric field modeling around power transformator by using Matlab to find the safety distance. The safe distance threshold of the electric field to human health refers to WHO and SNI was 5 kV/m. The specification of the power transformator was three phases, 150/20 kV, and 100 MVA. The basic concept is to change the...

Classification in medical image analysis using adaptive metric k-NN

DEFF Research Database (Denmark)

Chen, Chen; Chernoff, Konstantin; Karemore, Gopal

2010-01-01

The performance of the k-nearest neighborhoods (k-NN) classifier is highly dependent on the distance metric used to identify the k nearest neighbors of the query points. The standard Euclidean distance is commonly used in practice. This paper investigates the performance of k-NN classifier...

Estimating the relationship between abundance and distribution

DEFF Research Database (Denmark)

Rindorf, Anna; Lewy, Peter

2012-01-01

based on Euclidean distance to the centre of gravity of the spatial distribution. Only the proportion of structurally empty areas, Lloyds index, and indices of the distance to the centre of gravity of the spatial distribution are unbiased at all levels of abundance. The remaining indices generate...

Efficient Proximity Detection among Mobile Users via SelfTuning Policies

DEFF Research Database (Denmark)

Yiu, Man Lung; Hou U, Leong; Saltenis, Simonas

2010-01-01

Given a set of users, their friend relationships, and a distance threshold per friend pair, the proximity detection problem is to find each pair of friends such that the Euclidean distance between them is within the given threshold. This problem plays an essential role in friend...

Geometry-based populated chessboard recognition

Science.gov (United States)

Xie, Youye; Tang, Gongguo; Hoff, William

2018-04-01

Chessboards are commonly used to calibrate cameras, and many robust methods have been developed to recognize the unoccupied boards. However, when the chessboard is populated with chess pieces, such as during an actual game, the problem of recognizing the board is much harder. Challenges include occlusion caused by the chess pieces, the presence of outlier lines and low viewing angles of the chessboard. In this paper, we present a novel approach to address the above challenges and recognize the chessboard. The Canny edge detector and Hough transform are used to capture all possible lines in the scene. The k-means clustering and a k-nearest-neighbors inspired algorithm are applied to cluster and reject the outlier lines based on their Euclidean distances to the nearest neighbors in a scaled Hough transform space. Finally, based on prior knowledge of the chessboard structure, a geometric constraint is used to find the correspondences between image lines and the lines on the chessboard through the homography transformation. The proposed algorithm works for a wide range of the operating angles and achieves high accuracy in experiments.

Euclidean action for vacuum decay in a de Sitter universe

International Nuclear Information System (INIS)

Balek, V.; Demetrian, M.

2005-01-01

The behavior of the action of the instantons describing vacuum decay in a de Sitter is investigated. For a near-to-limit instanton (a Coleman-de Luccia instanton close to some Hawking-Moss instanton) we find approximate formulas for the Euclidean action by expanding the scalar field and the metric of the instanton in the powers of the scalar field amplitude. The order of the magnitude of the correction to the Hawking-Moss action depends on the order of the instanton (the number of crossings of the barrier by the scalar field): for instantons of odd and even orders the correction is of the fourth and third order in the scalar field amplitude, respectively. If a near-to-limit instanton of the first order exists in a potential with the curvature at the top of the barrier greater than 4x(Hubble constant) 2 , which is the case if the fourth derivative of the potential at the top of the barrier is greater than some negative limit value, the action of the instanton is less than the Hawking-Moss action and, consequently, the instanton determines the outcome of the vacuum decay if no other Coleman-de Luccia instanton is admitted by the potential. A numerical study shows that for the quartic potential the physical mode of the vacuum decay is given by the Coleman-de Luccia instanton of the first order also in the region of parameters in which the potential admits two instantons of the second order

OPEN AND DISTANCE LEARNING: An Emerging System for Alternative Higher Education in Nigeria

Directory of Open Access Journals (Sweden)

Emmanuel Chisa IBARA

2008-01-01

Full Text Available ABSTRACT Nigeria no doubt is at the threshold of transformation in information and communication technology (ICT, a development that should be utilized to meet the demand of time, especially in the education sector. One area in which ICT has made enormous impact is in open and distance learning. Undoubtedly, the demand on the conventional higher education delivery system in the country is high and ever increasing that the system at the moment is unable to accommodate the number of candidates seeking admission. This paper, therefore, attempts some definition of open and distance learning as well as its practices with a view to advancing the prospects of open and distance as alternative system of higher education in Nigeria. Furthermore, it concludes that considering the level of infrastructural decay in the conventional higher education system, open and distance learning as an alternative system of education has become imperative for the realization of the primary objectives of higher education in Nigeria. Recommendations that will enhance the prospects of open and distance learning as viable alternative system of higher education were proffered.

Automated segmentation and isolation of touching cell nuclei in cytopathology smear images of pleural effusion using distance transform watershed method

Science.gov (United States)

Win, Khin Yadanar; Choomchuay, Somsak; Hamamoto, Kazuhiko

2017-06-01

The automated segmentation of cell nuclei is an essential stage in the quantitative image analysis of cell nuclei extracted from smear cytology images of pleural fluid. Cell nuclei can indicate cancer as the characteristics of cell nuclei are associated with cells proliferation and malignancy in term of size, shape and the stained color. Nevertheless, automatic nuclei segmentation has remained challenging due to the artifacts caused by slide preparation, nuclei heterogeneity such as the poor contrast, inconsistent stained color, the cells variation, and cells overlapping. In this paper, we proposed a watershed-based method that is capable to segment the nuclei of the variety of cells from cytology pleural fluid smear images. Firstly, the original image is preprocessed by converting into the grayscale image and enhancing by adjusting and equalizing the intensity using histogram equalization. Next, the cell nuclei are segmented using OTSU thresholding as the binary image. The undesirable artifacts are eliminated using morphological operations. Finally, the distance transform based watershed method is applied to isolate the touching and overlapping cell nuclei. The proposed method is tested with 25 Papanicolaou (Pap) stained pleural fluid images. The accuracy of our proposed method is 92%. The method is relatively simple, and the results are very promising.

Properties of 3-dimensional line location models

DEFF Research Database (Denmark)

Brimberg, Jack; Juel, Henrik; Schöbel, Anita

2002-01-01

We consider the problem of locating a line with respect to some existing facilities in 3-dimensional space, such that the sum of weighted distances between the line and the facilities is minimized. Measuring distance using the l\\_p norm is discussed, along with the special cases of Euclidean...

The Edit Distance as a Measure of Perceived Rhythmic Similarity

Directory of Open Access Journals (Sweden)

Olaf Post

2012-07-01

Full Text Available The ‘edit distance’ (or ‘Levenshtein distance’ measure of distance between two data sets is defined as the minimum number of editing operations – insertions, deletions, and substitutions – that are required to transform one data set to the other (Orpen and Huron, 1992. This measure of distance has been applied frequently and successfully in music information retrieval, but rarely in predicting human perception of distance. In this study, we investigate the effectiveness of the edit distance as a predictor of perceived rhythmic dissimilarity under simple rhythmic alterations. Approaching rhythms as a set of pulses that are either onsets or silences, we study two types of alterations. The first experiment is designed to test the model’s accuracy for rhythms that are relatively similar; whether rhythmic variations with the same edit distance to a source rhythm are also perceived as relatively similar by human subjects. In addition, we observe whether the salience of an edit operation is affected by its metric placement in the rhythm. Instead of using a rhythm that regularly subdivides a 4/4 meter, our source rhythm is a syncopated 16-pulse rhythm, the son. Results show a high correlation between the predictions by the edit distance model and human similarity judgments (r = 0.87; a higher correlation than for the well-known generative theory of tonal music (r = 0.64. In the second experiment, we seek to assess the accuracy of the edit distance model in predicting relatively dissimilar rhythms. The stimuli used are random permutations of the son’s inter-onset intervals: 3-3-4-2-4. The results again indicate that the edit distance correlates well with the perceived rhythmic dissimilarity judgments of the subjects (r = 0.76. To gain insight in the relationships between the individual rhythms, the results are also presented by means of graphic phylogenetic trees.

Hyperspectral Image-Based Night-Time Vehicle Light Detection Using Spectral Normalization and Distance Mapper for Intelligent Headlight Control

Directory of Open Access Journals (Sweden)

Heekang Kim

2016-07-01

Full Text Available This paper proposes a vehicle light detection method using a hyperspectral camera instead of a Charge-Coupled Device (CCD or Complementary metal-Oxide-Semiconductor (CMOS camera for adaptive car headlamp control. To apply Intelligent Headlight Control (IHC, the vehicle headlights need to be detected. Headlights are comprised from a variety of lighting sources, such as Light Emitting Diodes (LEDs, High-intensity discharge (HID, and halogen lamps. In addition, rear lamps are made of LED and halogen lamp. This paper refers to the recent research in IHC. Some problems exist in the detection of headlights, such as erroneous detection of street lights or sign lights and the reflection plate of ego-car from CCD or CMOS images. To solve these problems, this study uses hyperspectral images because they have hundreds of bands and provide more information than a CCD or CMOS camera. Recent methods to detect headlights used the Spectral Angle Mapper (SAM, Spectral Correlation Mapper (SCM, and Euclidean Distance Mapper (EDM. The experimental results highlight the feasibility of the proposed method in three types of lights (LED, HID, and halogen.

X-ray tube transformer

International Nuclear Information System (INIS)

1980-01-01

An X-ray generator is described which comprises a transmission line transformer including an electrical conductor with a cavity and a second electrical conductor including helical windings disposed along a longitudinal axis within the cavity of the first conductor. The windings have a pitch which varies per unit length along the axis. There is dielectric material in the cavity for insulation and to couple electromagnetically the two conductors in response to an electric current flowing through the conductors, which have an impedance between them; this varies with distance along the axis of the helix of the second conductor. An X-ray tube is disposed along the longitudinal axis within the cavity, for radiating X-rays. The invention increases the voltage of applied voltage pulses at the remote tube-head with a transformer formed by using a spiral delay line geometry to give a tapered-impedance coaxial high voltage multiplier for pulse voltage operation. This transformer is smaller and lighter than previous designs for the same high peak voltage and power ratings. This is important because the penetration capabilities of Flash X-ray equipment increase with voltage, particularly in heavy materials such as steel. (U.K.)

Weyl-Euler-Lagrange Equations of Motion on Flat Manifold

Directory of Open Access Journals (Sweden)

Zeki Kasap

2015-01-01

Full Text Available This paper deals with Weyl-Euler-Lagrange equations of motion on flat manifold. It is well known that a Riemannian manifold is said to be flat if its curvature is everywhere zero. Furthermore, a flat manifold is one Euclidean space in terms of distances. Weyl introduced a metric with a conformal transformation for unified theory in 1918. Classical mechanics is one of the major subfields of mechanics. Also, one way of solving problems in classical mechanics occurs with the help of the Euler-Lagrange equations. In this study, partial differential equations have been obtained for movement of objects in space and solutions of these equations have been generated by using the symbolic Algebra software. Additionally, the improvements, obtained in this study, will be presented.

Numerical calculation of the Fresnel transform.

Science.gov (United States)

Kelly, Damien P

2014-04-01

In this paper, we address the problem of calculating Fresnel diffraction integrals using a finite number of uniformly spaced samples. General and simple sampling rules of thumb are derived that allow the user to calculate the distribution for any propagation distance. It is shown how these rules can be extended to fast-Fourier-transform-based algorithms to increase calculation efficiency. A comparison with other theoretical approaches is made.

Encyclopedia of distances

CERN Document Server

Deza, Michel Marie

2016-01-01

This 4th edition of the leading reference volume on distance metrics is characterized by updated and rewritten sections on some items suggested by experts and readers, as well a general streamlining of content and the addition of essential new topics. Though the structure remains unchanged, the new edition also explores recent advances in the use of distances and metrics for e.g. generalized distances, probability theory, graph theory, coding theory, data analysis. New topics in the purely mathematical sections include e.g. the Vitanyi multiset-metric, algebraic point-conic distance, triangular ratio metric, Rossi-Hamming metric, Taneja distance, spectral semimetric between graphs, channel metrization, and Maryland bridge distance. The multidisciplinary sections have also been supplemented with new topics, including: dynamic time wrapping distance, memory distance, allometry, atmospheric depth, elliptic orbit distance, VLBI distance measurements, the astronomical system of units, and walkability distance. Lea...

Geographic Location of a Computer Node Examining a Time-to-Location Algorithm and Multiple Autonomous System Networks

National Research Council Canada - National Science Library

Sorgaard, Duane

2004-01-01

.... A time-to-location algorithm can successfully resolve a geographic location of a computer node using only latency information from known sites and mathematically calculating the Euclidean distance...

Distance Learning

National Research Council Canada - National Science Library

Braddock, Joseph

1997-01-01

A study reviewing the existing Army Distance Learning Plan (ADLP) and current Distance Learning practices, with a focus on the Army's training and educational challenges and the benefits of applying Distance Learning techniques...

Adaptive geodesic transform for segmentation of vertebrae on CT images

Science.gov (United States)

Gaonkar, Bilwaj; Shu, Liao; Hermosillo, Gerardo; Zhan, Yiqiang

2014-03-01

Vertebral segmentation is a critical first step in any quantitative evaluation of vertebral pathology using CT images. This is especially challenging because bone marrow tissue has the same intensity profile as the muscle surrounding the bone. Thus simple methods such as thresholding or adaptive k-means fail to accurately segment vertebrae. While several other algorithms such as level sets may be used for segmentation any algorithm that is clinically deployable has to work in under a few seconds. To address these dual challenges we present here, a new algorithm based on the geodesic distance transform that is capable of segmenting the spinal vertebrae in under one second. To achieve this we extend the theory of the geodesic distance transforms proposed in1 to incorporate high level anatomical knowledge through adaptive weighting of image gradients. Such knowledge may be provided by the user directly or may be automatically generated by another algorithm. We incorporate information 'learnt' using a previously published machine learning algorithm2 to segment the L1 to L5 vertebrae. While we present a particular application here, the adaptive geodesic transform is a generic concept which can be applied to segmentation of other organs as well.

A phylogenetic transform enhances analysis of compositional microbiota data.

Science.gov (United States)

Silverman, Justin D; Washburne, Alex D; Mukherjee, Sayan; David, Lawrence A

2017-02-15

Surveys of microbial communities (microbiota), typically measured as relative abundance of species, have illustrated the importance of these communities in human health and disease. Yet, statistical artifacts commonly plague the analysis of relative abundance data. Here, we introduce the PhILR transform, which incorporates microbial evolutionary models with the isometric log-ratio transform to allow off-the-shelf statistical tools to be safely applied to microbiota surveys. We demonstrate that analyses of community-level structure can be applied to PhILR transformed data with performance on benchmarks rivaling or surpassing standard tools. Additionally, by decomposing distance in the PhILR transformed space, we identified neighboring clades that may have adapted to distinct human body sites. Decomposing variance revealed that covariation of bacterial clades within human body sites increases with phylogenetic relatedness. Together, these findings illustrate how the PhILR transform combines statistical and phylogenetic models to overcome compositional data challenges and enable evolutionary insights relevant to microbial communities.

(Non-) homomorphic approaches to denoise intensity SAR images with non-local means and stochastic distances

Science.gov (United States)

Penna, Pedro A. A.; Mascarenhas, Nelson D. A.

2018-02-01

The development of new methods to denoise images still attract researchers, who seek to combat the noise with the minimal loss of resolution and details, like edges and fine structures. Many algorithms have the goal to remove additive white Gaussian noise (AWGN). However, it is not the only type of noise which interferes in the analysis and interpretation of images. Therefore, it is extremely important to expand the filters capacity to different noise models present in li-terature, for example the multiplicative noise called speckle that is present in synthetic aperture radar (SAR) images. The state-of-the-art algorithms in remote sensing area work with similarity between patches. This paper aims to develop two approaches using the non local means (NLM), developed for AWGN. In our research, we expanded its capacity for intensity SAR ima-ges speckle. The first approach is grounded on the use of stochastic distances based on the G0 distribution without transforming the data to the logarithm domain, like homomorphic transformation. It takes into account the speckle and backscatter to estimate the parameters necessary to compute the stochastic distances on NLM. The second method uses a priori NLM denoising with a homomorphic transformation and applies the inverse Gamma distribution to estimate the parameters that were used into NLM with stochastic distances. The latter method also presents a new alternative to compute the parameters for the G0 distribution. Finally, this work compares and analyzes the synthetic and real results of the proposed methods with some recent filters of the literature.

REPRESENTATIONS OF DISTANCE: DIFFERENCES IN UNDERSTANDING DISTANCE ACCORDING TO TRAVEL METHOD

Directory of Open Access Journals (Sweden)

Gunvor Riber Larsen

2017-12-01

Full Text Available This paper explores how Danish tourists represent distance in relation to their holiday mobility and how these representations of distance are a result of being aero-mobile as opposed to being land-mobile. Based on interviews with Danish tourists, whose holiday mobility ranges from the European continent to global destinations, the first part of this qualitative study identifies three categories of representations of distance that show how distance is being ‘translated’ by the tourists into non-geometric forms: distance as resources, distance as accessibility, and distance as knowledge. The representations of distance articulated by the Danish tourists show that distance is often not viewed in ‘just’ kilometres. Rather, it is understood in forms that express how transcending the physical distance through holiday mobility is dependent on individual social and economic contexts, and on whether the journey was undertaken by air or land. The analysis also shows that being aeromobile is the holiday transportation mode that removes the tourists the furthest away from physical distance, resulting in the distance travelled by air being represented in ways that have the least correlation, in the tourists’ minds, with physical distance measured in kilometres.

Quantifying the Error Associated with Alternative GIS-based Techniques to Measure Access to Health Care Services

Directory of Open Access Journals (Sweden)

Amy Mizen

2015-11-01

Full Text Available The aim of this study was to quantify the error associated with different accessibility methods commonly used by public health researchers. Network distances were calculated from each household to the nearest GP our study area in the UK. Household level network distances were assigned as the gold standard and compared to alternate widely used accessibility methods. Four spatial aggregation units, two centroid types and two distance calculation methods represent commonly used accessibility calculation methods. Spearman's rank coefficients were calculated to show the extent which distance measurements were correlated with the gold standard. We assessed the proportion of households that were incorrectly assigned to GP for each method. The distance method, level of spatial aggregation and centroid type were compared between urban and rural regions. Urban distances were less varied from the gold standard, with smaller errors, compared to rural regions. For urban regions, Euclidean distances are significantly related to network distances. Network distances assigned a larger proportion of households to the correct GP compared to Euclidean distances, for both urban and rural morphologies. Our results, stratified by urban and rural populations, explain why contradicting results have been reported in the literature. The results we present are intended to be used aide-memoire by public health researchers using geographical aggregated data in accessibility research.

Valuation of travel time for international long-distance travel - results from the Fehmarn Belt stated choice experiment

DEFF Research Database (Denmark)

Mabit, Stefan Lindhard; Rich, Jeppe; Burge, Peter

2013-01-01

of travel time savings (VTTS). The final model, which was formulated as a nested logit model and included Box–Cox transformed travel time and cost attributes, revealed several interesting findings. Firstly, we found damping effects in both cost and time – most strongly in cost. Secondly, we found...... significant interactions among travel cost and time, and journey characteristics, such as distance and duration. This had direct impact on the VTTS, which was shown to decrease with distance and duration. Thirdly, we found that air travel implies a higher average VTTS, which is to be expected but rarely......The geographical scope of travel varies from short distances in urban areas to long distances across cities and countries. While urban travel has been widely analysed in the literature, travel over longer distances and particularly across countries, has received much less attention. While this may...

Identification of Homogeneous Stations for Quality Monitoring Network of Mashhad Aquifer Based on Nitrate Pollution

Directory of Open Access Journals (Sweden)

Moslem Akbarzadeh

2017-01-01

Full Text Available Introduction: For water resources monitoring, Evaluation of groundwater quality obtained via detailed analysis of pollution data. The most fundamental analysis is to identify the exact measurement of dangerous zones and homogenous station identification in terms of pollution. In case of quality evaluation, the monitoring improvement could be achieved via identifying homogenous wells in terms of pollution. Presenting a method for clustering is essential in large amounts of quality data for aquifer monitoring and quality evaluation, including identification of homogeneous stations of monitoring network and their clustering based on pollution. In this study, with the purpose of Mashhad aquifer quality evaluation, clustering have been studied based on Euclidean distance and Entropy criteria. Cluster analysis is the task of grouping a set of objects in such a way that objects in the same group (called a cluster are more similar (in some sense or another to each other than to those in other groups (clusters. SNI as a combined entropy measure for clustering calculated from dividing mutual information of two values (pollution index values to the joint entropy. These measures apply as similar distance criteria for monitoring stations clustering. Materials and Methods: First, nitrate data (as pollution index and electrical conductivity (EC (as covariate collected from the related locational situation of 287 wells in statistical period 2002 to 2011. Having identified the outlying data and estimating non-observed points by spatial-temporal Kriging method and then standardizes them, the clustering process was carried out. A similar distance of wells calculated through a clustering process based on Euclidean distance and Entropy (SNI criteria. This difference explained by characteristics such as the location of wells (longitude & latitude and the pollution index (nitrate. Having obtained a similar distance of each well to others, the hierarchical clustering

Fourier transform infrared spectroscopy microscopic imaging classification based on spatial-spectral features

Science.gov (United States)

Liu, Lian; Yang, Xiukun; Zhong, Mingliang; Liu, Yao; Jing, Xiaojun; Yang, Qin

2018-04-01

The discrete fractional Brownian incremental random (DFBIR) field is used to describe the irregular, random, and highly complex shapes of natural objects such as coastlines and biological tissues, for which traditional Euclidean geometry cannot be used. In this paper, an anisotropic variable window (AVW) directional operator based on the DFBIR field model is proposed for extracting spatial characteristics of Fourier transform infrared spectroscopy (FTIR) microscopic imaging. Probabilistic principal component analysis first extracts spectral features, and then the spatial features of the proposed AVW directional operator are combined with the former to construct a spatial-spectral structure, which increases feature-related information and helps a support vector machine classifier to obtain more efficient distribution-related information. Compared to Haralick’s grey-level co-occurrence matrix, Gabor filters, and local binary patterns (e.g. uniform LBPs, rotation-invariant LBPs, uniform rotation-invariant LBPs), experiments on three FTIR spectroscopy microscopic imaging datasets show that the proposed AVW directional operator is more advantageous in terms of classification accuracy, particularly for low-dimensional spaces of spatial characteristics.

Maximally-localized position, Euclidean path-integral, and thermodynamics in GUP quantum mechanics

Science.gov (United States)

Bernardo, Reginald Christian S.; Esguerra, Jose Perico H.

2018-04-01

In dealing with quantum mechanics at very high energies, it is essential to adapt to a quasiposition representation using the maximally-localized states because of the generalized uncertainty principle. In this paper, we look at maximally-localized states as eigenstates of the operator ξ = X + iβP that we refer to as the maximally-localized position. We calculate the overlap between maximally-localized states and show that the identity operator can be expressed in terms of the maximally-localized states. Furthermore, we show that the maximally-localized position is diagonal in momentum-space and that the maximally-localized position and its adjoint satisfy commutation and anti-commutation relations reminiscent of the harmonic oscillator commutation and anti-commutation relations. As application, we use the maximally-localized position in developing the Euclidean path-integral and introduce the compact form of the propagator for maximal localization. The free particle momentum-space propagator and the propagator for maximal localization are analytically evaluated up to quadratic-order in β. Finally, we obtain a path-integral expression for the partition function of a thermodynamic system using the maximally-localized states. The partition function of a gas of noninteracting particles is evaluated. At temperatures exceeding the Planck energy, we obtain the gas' maximum internal energy N / 2 β and recover the zero heat capacity of an ideal gas.

Facial Feature Extraction Using Frequency Map Series in PCNN

Directory of Open Access Journals (Sweden)

Rencan Nie

2016-01-01

Full Text Available Pulse coupled neural network (PCNN has been widely used in image processing. The 3D binary map series (BMS generated by PCNN effectively describes image feature information such as edges and regional distribution, so BMS can be treated as the basis of extracting 1D oscillation time series (OTS for an image. However, the traditional methods using BMS did not consider the correlation of the binary sequence in BMS and the space structure for every map. By further processing for BMS, a novel facial feature extraction method is proposed. Firstly, consider the correlation among maps in BMS; a method is put forward to transform BMS into frequency map series (FMS, and the method lessens the influence of noncontinuous feature regions in binary images on OTS-BMS. Then, by computing the 2D entropy for every map in FMS, the 3D FMS is transformed into 1D OTS (OTS-FMS, which has good geometry invariance for the facial image, and contains the space structure information of the image. Finally, by analyzing the OTS-FMS, the standard Euclidean distance is used to measure the distances for OTS-FMS. Experimental results verify the effectiveness of OTS-FMS in facial recognition, and it shows better recognition performance than other feature extraction methods.

Topographic determinants of foot and mouth disease transmission in the UK 2001 epidemic

Directory of Open Access Journals (Sweden)

Keeling Matthew J

2006-01-01

Full Text Available Abstract Background A key challenge for modelling infectious disease dynamics is to understand the spatial spread of infection in real landscapes. This ideally requires a parallel record of spatial epidemic spread and a detailed map of susceptible host density along with relevant transport links and geographical features. Results Here we analyse the most detailed such data to date arising from the UK 2001 foot and mouth epidemic. We show that Euclidean distance between infectious and susceptible premises is a better predictor of transmission risk than shortest and quickest routes via road, except where major geographical features intervene. Conclusion Thus, a simple spatial transmission kernel based on Euclidean distance suffices in most regions, probably reflecting the multiplicity of transmission routes during the epidemic.

On the stretch factor of convex Delaunay graphs

Directory of Open Access Journals (Sweden)

Prosenjit Bose

2010-06-01

Full Text Available Let C be a compact and convex set in the plane that contains the origin in its interior, and let S be a finite set of points in the plane. The Delaunay graph DGC(S of S is defined to be the dual of the Voronoi diagram of S with respect to the convex distance function defined by C. We prove that DGC(S is a t-spanner for S, for some constant t that depends only on the shape of the set C. Thus, for any two points p and q in S, the graph DGC(S contains a path between p and q whose Euclidean length is at most t times the Euclidean distance between p and q.

Encyclopedia of distances

CERN Document Server

Deza, Michel Marie

2014-01-01

This updated and revised third edition of the leading reference volume on distance metrics includes new items from very active research areas in the use of distances and metrics such as geometry, graph theory, probability theory and analysis. Among the new topics included are, for example, polyhedral metric space, nearness matrix problems, distances between belief assignments, distance-related animal settings, diamond-cutting distances, natural units of length, Heidegger’s de-severance distance, and brain distances. The publication of this volume coincides with intensifying research efforts into metric spaces and especially distance design for applications. Accurate metrics have become a crucial goal in computational biology, image analysis, speech recognition and information retrieval. Leaving aside the practical questions that arise during the selection of a ‘good’ distance function, this work focuses on providing the research community with an invaluable comprehensive listing of the main available di...

Extended-Maxima Transform Watershed Segmentation Algorithm for Touching Corn Kernels

Directory of Open Access Journals (Sweden)

Yibo Qin

2013-01-01

Full Text Available Touching corn kernels are usually oversegmented by the traditional watershed algorithm. This paper proposes a modified watershed segmentation algorithm based on the extended-maxima transform. Firstly, a distance-transformed image is processed by the extended-maxima transform in the range of the optimized threshold value. Secondly, the binary image obtained by the preceding process is run through the watershed segmentation algorithm, and watershed ridge lines are superimposed on the original image, so that touching corn kernels are separated into segments. Fifty images which all contain 400 corn kernels were tested. Experimental results showed that the effect of segmentation is satisfactory by the improved algorithm, and the accuracy of segmentation is as high as 99.87%.

Interface Simulation Distances

Directory of Open Access Journals (Sweden)

Pavol Černý

2012-10-01

Full Text Available The classical (boolean notion of refinement for behavioral interfaces of system components is the alternating refinement preorder. In this paper, we define a distance for interfaces, called interface simulation distance. It makes the alternating refinement preorder quantitative by, intuitively, tolerating errors (while counting them in the alternating simulation game. We show that the interface simulation distance satisfies the triangle inequality, that the distance between two interfaces does not increase under parallel composition with a third interface, and that the distance between two interfaces can be bounded from above and below by distances between abstractions of the two interfaces. We illustrate the framework, and the properties of the distances under composition of interfaces, with two case studies.

Economics of Distance and Online Learning Theory, Practice and Research

Directory of Open Access Journals (Sweden)

reviewed by TOJDE

2009-10-01

Full Text Available Economics of Distance and Online LearningTheory, Practice and ResearchBy William Bramble & Santosh PandaPrice: $125.00ISBN: 978-0-415-96388-6, Binding: Hardback, Publishedby: Routledge, New York, Publication Date: March 2008, Pages: 312TOJDEABOUT THE BOOKThis book provides a comprehensive overview of theorganizational models of distance and online learning froman international perspective and from the point of view ofeconomic planning, costing and management decisionmaking.The book points to directions for the further research anddevelopment in this area, and will promote furtherunderstanding and critical reflection on the part ofadministrators, practitioners and researchers of distanceeducation.The experiences and perspectives in distance education inthe US are balanced with those in other areas of the world.Table of ContentsPrefaceSECTION ONE: INTRODUCTIONChapter 1: Organizational and Cost Structures for Distanceand Online Learning, William J. Bramble and Santosh PandaSECTION TWO: PLANNING AND MANAGEMENTChapter 2: Changing Distance Education andChanging Organizational Issues, D. Randy Garrison and Heather KanukaChapter 3: Online Learning and the University, Chris Curran217Chapter 4: Virtual Schooling and Basic Education, Thomas ClarkChapter 5: Historical Perspectives on Distance Education in the United States, Paul J.Edelson and Von PittmanSECTION THREE: FUNDINGChapter 6: Funding of Distance and Online Learning in the United States, Mark J. Smithand William J. BrambleChapter 7: Funding Distance Education: A Regional Perspective, Santosh Panda andAshok GabaSECTION FOUR: COST STRUCTURES AND MODELSChapter 8: Costs and Quality of Online Learning, Alistair InglisChapter 9: Costing Virtual University Education, Insung JungChapter 10: Cost-Benefit of Student Retention Policies and Practices, Ormond SimpsonSECTION FIVE: DISTANCE TRAININGChapter 11: Cost Benefit of Online Learning, Zane Berge and Charlotte DonaldsonChapter 12: Transforming Workplace

On the Use of Normalized Compression Distances for Image Similarity Detection

Directory of Open Access Journals (Sweden)

Dinu Coltuc

2018-01-01

Full Text Available This paper investigates the usefulness of the normalized compression distance (NCD for image similarity detection. Instead of the direct NCD between images, the paper considers the correlation between NCD based feature vectors extracted for each image. The vectors are derived by computing the NCD between the original image and sequences of translated (rotated versions. Feature vectors for simple transforms (circular translations on horizontal, vertical, diagonal directions and rotations around image center and several standard compressors are generated and tested in a very simple experiment of similarity detection between the original image and two filtered versions (median and moving average. The promising vector configurations (geometric transform, lossless compressor are further tested for similarity detection on the 24 images of the Kodak set subject to some common image processing. While the direct computation of NCD fails to detect image similarity even in the case of simple median and moving average filtering in 3 × 3 windows, for certain transforms and compressors, the proposed approach appears to provide robustness at similarity detection against smoothing, lossy compression, contrast enhancement, noise addition and some robustness against geometrical transforms (scaling, cropping and rotation.

Accuracy and feasibility of frameless stereotactic and robot-assisted CT-based puncture in interventional radiology. A comparative phantom study

International Nuclear Information System (INIS)

Stoffner, R.; Widmann, G.; Bale, R.; Augschoell, C.; Boehler, D.

2009-01-01

Purpose: To compare the accuracy of frameless stereotactic and robot-assisted puncture in vitro based on computed tomography (CT) imaging with a slice thickness of 1, 3, and 5 mm. Materials and Methods: 300 punctures were carried out with help of the Atlas aiming device guided by the optical navigation system Stealth Station TREONplus and 150 punctures were guided by the robotic assistance system Innomotion. Conically shaped rods were punctured with Kirschner wires. The accuracy was evaluated on the basis of control CTs by measuring the Euclidean distance between the wire tip and target and the normal distance between the target and wire. Results: With the Stealth Station a mean Euclidean distance of 1.94±0.912, 2.2±1.136, and 2.74±1.166 mm at a slice thickness of 1, 3 and 5 mm, respectively, was reached. The mean normal distance was 1.64±0.919, 1.84±1.189, and 2.48±1.196 mm, respectively. The Innomotion system resulted in a mean Euclidean distance of 1.69±0.772, 1.91±0.673, and 2.30±0.881 mm, respectively, while the mean normal distance was (1.42±0.78), 1.60±0.733, and 1.98±1.002 mm, respectively. A statistical significance between accuracies with both systems with 1 mm and 3 mm slices could not be detected (p > 0.05). At a slice thickness of 5 mm, the robot was significantly more accurate, but not as accurate as when using thinner slices (p < 0.05). The procedure time is longer for the Innomotion system (∝30 vs. ∝18 min), and the practicability is higher with the Stealth Station. (orig.)

The Earth Is Flat when Personally Significant Experiences with the Sphericity of the Earth Are Absent

Science.gov (United States)

Carbon, Claus-Christian

2010-01-01

Participants with personal and without personal experiences with the Earth as a sphere estimated large-scale distances between six cities located on different continents. Cognitive distances were submitted to a specific multidimensional scaling algorithm in the 3D Euclidean space with the constraint that all cities had to lie on the same sphere. A…

Effect of number of of projections on inverse radon transform based image reconstruction by using filtered back-projection for parallel beam transmission tomography

International Nuclear Information System (INIS)

Qureshi, S.A.; Mirza, S.M.; Arif, M.

2007-01-01

This paper present the effect of number of projections on inverse Radon transform (IRT) estimation using filtered back-projection (FBP) technique for parallel beam transmission tomography. The head phantom and the lung phantom have been used in this work. Various filters used in this study include Ram-Lak, Shepp-Logan, Cosin, Hamming and Hanning filters. The slices have been reconstructed by increasing the number of projections through parallel beam transmission tomography keeping the projections uniformly distributed. The Euclidean and Mean Squared errors and peak signal-to-noise ratio (PSNR) have been analyzed for their sensitiveness as functions of number of projections. It has found that image quality improves with the number of projections but at the cost of the computer time. The error has been minimized to get the best approximation of inverse Radon transform (IRT) as the number of projections is enhanced. The value of PSNR has been found to increase from 8.20 to 24.53 dB as the number of projections is raised from 5 to 180 for head phantom. (author)

Thyroid lesions diagnosis by Fourier transformed infrared absorption spectroscopy (FTIR)

International Nuclear Information System (INIS)

Albero, Felipe Guimaraes

2009-01-01

Thyroid nodules are a common disorder, with 4-7% of incidence in the Brazilian population. Although the fine needle aspiration (FNA) is an accurate method for thyroid tumors diagnosis, the discrimination between benign and malignant neoplasm is currently not possible in some cases with high incidence of false negative diagnosis, leading to a surgical intervention due to the risk of carcinomas. The aim of this study was to verify if the Fourier Transform infrared spectroscopy (FTIR) can contribute to the diagnosis of thyroid carcinomas and goiters, using samples of tissue and aspirates. Samples of FNA, homogenates and tissues of thyroid nodules with histopathological diagnosis were obtained and prepared for FTIR spectroscopy analysis. The FNA and homogenates samples were measured by μ-FTIR (between 950 . 1750 cm -1 ), at a nominal resolution of 4 cm -1 and 120 scans). Tissue samples were analyzed directly by ATR-FTIR technique, at a resolution 2 cm -1 , with 60 scans in the same region. All spectra were corrected by the baseline and normalized by amides area (1550-1640 cm -1 ) in order to minimize variations of sample homogeneity. Then, spectra were converted into second derivatives using the Savitzk-Golay algorithm with a 13 points window. The Ward's minimum variance algorithm and Euclidean distances among the points were used for cluster analysis. Some FNA samples showed complex spectral pattern. All samples showed some cell pellets and large amount of hormone, represented by the bands of 1545 and 1655 cm -1 . Bands in 1409, 1412, 1414, 1578 and 1579 cm -1 were also found, indicating possible presence of sugar, DNA, citric acid or metabolic products. In this study, it was obtained an excellent separation between goiter and malign lesion for the samples of tissues, with 100% of specificity in specific cluster and 67% sensibility and 50 of specificity. In homogenate and FNA samples this sensibility and specificity were lower, because among these samples, it were

Fast Implicit Methods For Elliptic Moving Interface Problems

Science.gov (United States)

2015-12-11

surfaces [30], and has recently been employed in the geometric nonuniform fast Fourier transform [12] and in the finite element method [31]. We employ...analyzed, and tested for the Fourier transform of piecewise polynomials given on d-dimensional simplices in D-dimensional Euclidean space. These transforms ...evaluation, and one to three orders of magnitude slower than the classical uniform Fast Fourier Transform . Second, bilinear quadratures ---which

Recurring Issues Encountered by Distance Educators in Developing and Emerging Nations

Directory of Open Access Journals (Sweden)

Clayton R. Wright

2009-02-01

Full Text Available This article explores a number of challenges faced by e-learning or distance educators in developing and emerging countries, provides a context for many of the challenges, and outlines some measures devised to overcome them. These educators must determine a sound rationale for employing online learning, recognize that technology is only part of the educational transformation process, address the lack of infrastructure and the cost of Internet bandwidth and equipment, counter the cultural imperialism of courseware from Western nations, deal with limited educational resources, place a greater emphasis on quality assurance systems and change negative perceptions of distance education, respond to the needs and concerns of both students and faculty, access or develop up-to-date educational resources, and consider the implementation of mobile learning. The continued growth and success of distance education in developing and emerging nations will depend on the extent to which issues covered in this article are addressed as they bear on the quality of the learning experience provided to students.

Evidence for asymptotic safety from lattice quantum gravity.

Science.gov (United States)

Laiho, J; Coumbe, D

2011-10-14

We calculate the spectral dimension for nonperturbative quantum gravity defined via Euclidean dynamical triangulations. We find that it runs from a value of ∼3/2 at short distance to ∼4 at large distance scales, similar to results from causal dynamical triangulations. We argue that the short-distance value of 3/2 for the spectral dimension may resolve the tension between asymptotic safety and the holographic principle.

Residential distance to major roadways and semen quality, sperm DNA integrity, chromosomal disomy, and serum reproductive hormones among men attending a fertility clinic.

Science.gov (United States)

Nassan, Feiby L; Chavarro, Jorge E; Mínguez-Alarcón, Lidia; Williams, Paige L; Tanrikut, Cigdem; Ford, Jennifer B; Dadd, Ramace; Perry, Melissa J; Hauser, Russ; Gaskins, Audrey J

2018-06-01

We examined associations of residential distance to major roadways, as a proxy for traffic-related air pollution exposures, with sperm characteristics and male reproductive hormones. The cohort included 797 men recruited from Massachusetts General Hospital Fertility Center between 2000 and 2015 to participate in fertility research studies. Men reported their residential addresses at enrollment and provided 1-6 semen samples and a blood sample during follow-up. We estimated the Euclidean distance to major roadways (e.g. interstates and highways: limited access highways, multi-lane highways (not limited access), other numbered routes, and major roads) using information from the Massachusetts Department of Geographic Information Systems. Semen parameters (1238 semen samples), sperm DNA integrity (389 semen samples), chromosomal disomy (101 semen samples), and serum reproductive hormones (405 serum samples) were assessed following standard procedures. Men in this cohort were primarily Caucasian (86%), not current smokers (92%), with a college or higher education (88%), and had an average age of 36 years and BMI of 27.7 kg/m 2 . The median (interquartile range) residential distance to a major roadway was 111 (37, 248) meters. Residential proximity to major roadways was not associated with semen parameters, sperm DNA integrity, chromosomal disomy, or serum reproductive hormone concentrations. The adjusted percent change (95% CI) in semen quality parameters associated with a 500 m increase in residential distance to a major roadway was -1.0% (-6.3, 4.5) for semen volume, 4.3% (-5.8, 15.7) for sperm concentration, 3.1% (-7.2, 14.5) for sperm count, 1.1% (-1.2, 3.4) for % total motile sperm, and 0.1% (-0.3, 0.5) for % morphologically normal sperm. Results were consistent when we modeled the semen parameters dichotomized according to WHO 2010 reference values. Residential distance to major roadways, as a proxy for traffic-related air pollution exposure, was not related

Audio Query by Example Using Similarity Measures between Probability Density Functions of Features

Directory of Open Access Journals (Sweden)

Marko Helén

2010-01-01

Full Text Available This paper proposes a query by example system for generic audio. We estimate the similarity of the example signal and the samples in the queried database by calculating the distance between the probability density functions (pdfs of their frame-wise acoustic features. Since the features are continuous valued, we propose to model them using Gaussian mixture models (GMMs or hidden Markov models (HMMs. The models parametrize each sample efficiently and retain sufficient information for similarity measurement. To measure the distance between the models, we apply a novel Euclidean distance, approximations of Kullback-Leibler divergence, and a cross-likelihood ratio test. The performance of the measures was tested in simulations where audio samples are automatically retrieved from a general audio database, based on the estimated similarity to a user-provided example. The simulations show that the distance between probability density functions is an accurate measure for similarity. Measures based on GMMs or HMMs are shown to produce better results than that of the existing methods based on simpler statistics or histograms of the features. A good performance with low computational cost is obtained with the proposed Euclidean distance.

Matrix Completion Optimization for Localization in Wireless Sensor Networks for Intelligent IoT

Directory of Open Access Journals (Sweden)

Thu L. N. Nguyen

2016-05-01

Full Text Available Localization in wireless sensor networks (WSNs is one of the primary functions of the intelligent Internet of Things (IoT that offers automatically discoverable services, while the localization accuracy is a key issue to evaluate the quality of those services. In this paper, we develop a framework to solve the Euclidean distance matrix completion problem, which is an important technical problem for distance-based localization in WSNs. The sensor network localization problem is described as a low-rank dimensional Euclidean distance completion problem with known nodes. The task is to find the sensor locations through recovery of missing entries of a squared distance matrix when the dimension of the data is small compared to the number of data points. We solve a relaxation optimization problem using a modification of Newton’s method, where the cost function depends on the squared distance matrix. The solution obtained in our scheme achieves a lower complexity and can perform better if we use it as an initial guess for an interactive local search of other higher precision localization scheme. Simulation results show the effectiveness of our approach.

Reducing the distance in distance-caregiving by technology innovation

Directory of Open Access Journals (Sweden)

Lazelle E Benefield

2007-07-01

Full Text Available Lazelle E Benefield1, Cornelia Beck21College of Nursing, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA; 2Pat & Willard Walker Family Memory Research Center, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USAAbstract: Family caregivers are responsible for the home care of over 34 million older adults in the United States. For many, the elder family member lives more than an hour’s distance away. Distance caregiving is a growing alternative to more familiar models where: 1 the elder and the family caregiver(s may reside in the same household; or 2 the family caregiver may live nearby but not in the same household as the elder. The distance caregiving model involves elders and their family caregivers who live at some distance, defined as more than a 60-minute commute, from one another. Evidence suggests that distance caregiving is a distinct phenomenon, differs substantially from on-site family caregiving, and requires additional assistance to support the physical, social, and contextual dimensions of the caregiving process. Technology-based assists could virtually connect the caregiver and elder and provide strong support that addresses the elder’s physical, social, cognitive, and/or sensory impairments. Therefore, in today’s era of high technology, it is surprising that so few affordable innovations are being marketed for distance caregiving. This article addresses distance caregiving, proposes the use of technology innovation to support caregiving, and suggests a research agenda to better inform policy decisions related to the unique needs of this situation.Keywords: caregiving, family, distance, technology, elders

The solution of location problems with certain existing facility structures

DEFF Research Database (Denmark)

Juel, Henrik; Love, Robert F.

1983-01-01

It is known that in the Euclidean distance case, the optimal minisum location of a new facility in relation to four existing facilities is at the intersection of the two lines joining two pairs of the facilities. The authors extend this concept to minisum problems having any even number of existing...... facilities and characterized by generalized distance norms...

Censoring distances based on labeled cortical distance maps in cortical morphometry.

Science.gov (United States)

Ceyhan, Elvan; Nishino, Tomoyuki; Alexopolous, Dimitrios; Todd, Richard D; Botteron, Kelly N; Miller, Michael I; Ratnanather, J Tilak

2013-01-01

It has been demonstrated that shape differences in cortical structures may be manifested in neuropsychiatric disorders. Such morphometric differences can be measured by labeled cortical distance mapping (LCDM) which characterizes the morphometry of the laminar cortical mantle of cortical structures. LCDM data consist of signed/labeled distances of gray matter (GM) voxels with respect to GM/white matter (WM) surface. Volumes and other summary measures for each subject and the pooled distances can help determine the morphometric differences between diagnostic groups, however they do not reveal all the morphometric information contained in LCDM distances. To extract more information from LCDM data, censoring of the pooled distances is introduced for each diagnostic group where the range of LCDM distances is partitioned at a fixed increment size; and at each censoring step, the distances not exceeding the censoring distance are kept. Censored LCDM distances inherit the advantages of the pooled distances but also provide information about the location of morphometric differences which cannot be obtained from the pooled distances. However, at each step, the censored distances aggregate, which might confound the results. The influence of data aggregation is investigated with an extensive Monte Carlo simulation analysis and it is demonstrated that this influence is negligible. As an illustrative example, GM of ventral medial prefrontal cortices (VMPFCs) of subjects with major depressive disorder (MDD), subjects at high risk (HR) of MDD, and healthy control (Ctrl) subjects are used. A significant reduction in laminar thickness of the VMPFC in MDD and HR subjects is observed compared to Ctrl subjects. Moreover, the GM LCDM distances (i.e., locations with respect to the GM/WM surface) for which these differences start to occur are determined. The methodology is also applicable to LCDM-based morphometric measures of other cortical structures affected by disease.

Censoring Distances Based on Labeled Cortical Distance Maps in Cortical Morphometry

Directory of Open Access Journals (Sweden)

Elvan eCeyhan

2013-10-01

Full Text Available It has been demonstrated that shape differences are manifested in cortical structures due to neuropsychiatric disorders. Such morphometric differences can be measured by labeled cortical distance mapping (LCDM which characterizes the morphometry of the laminar cortical mantle of cortical structures. LCDM data consist of signed/labeled distances of gray matter (GM voxels with respect to GM/white matter (WM surface. Volumes and other summary measures for each subject and the pooled distances can help determine the morphometric differences between diagnostic groups, however they do not reveal all the morphometric information con-tained in LCDM distances. To extract more information from LCDM data, censoring of the pooled distances is introduced for each diagnostic group where the range of LCDM distances is partitioned at a fixed increment size; and at each censoring step, the distances not exceeding the censoring distance are kept. Censored LCDM distances inherit the advantages of the pooled distances but also provide information about the location of morphometric differences which cannot be obtained from the pooled distances. However, at each step, the censored distances aggregate, which might confound the results. The influence of data aggregation is investigated with an extensive Monte Carlo simulation analysis and it is demonstrated that this influence is negligible. As an illustrative example, GM of ventral medial prefrontal cortices (VMPFCs of subjects with major depressive disorder (MDD, subjects at high risk (HR of MDD, and healthy control (Ctrl subjects are used. A significant reduction in laminar thickness of the VMPFC in MDD and HR subjects is observed compared to Ctrl subjects. Moreover, the GM LCDM distances (i.e., locations with respect to the GM/WM surface for which these differences start to occur are determined. The methodology is also applicable to LCDM-based morphometric measures of other cortical structures affected by disease.

Training for Distance Teaching through Distance Learning.

Science.gov (United States)

Cadorath, Jill; Harris, Simon; Encinas, Fatima

2002-01-01

Describes a mixed-mode bachelor degree course in English language teaching at the Universidad Autonoma de Puebla (Mexico) that was designed to help practicing teachers write appropriate distance education materials by giving them the experience of being distance students. Includes a course outline and results of a course evaluation. (Author/LRW)

Tourists consuming distance

DEFF Research Database (Denmark)

Larsen, Gunvor Riber

The environmental impact of tourism mobility is linked to the distances travelled in order to reach a holiday destination, and with tourists travelling more and further than previously, an understanding of how the tourists view the distance they travel across becomes relevant. Based on interviews...... contribute to an understanding of how it is possible to change tourism travel behaviour towards becoming more sustainable. How tourists 'consume distance' is discussed, from the practical level of actually driving the car or sitting in the air plane, to the symbolic consumption of distance that occurs when...... travelling on holiday becomes part of a lifestyle and a social positioning game. Further, different types of tourist distance consumers are identified, ranging from the reluctant to the deliberate and nonchalant distance consumers, who display very differing attitudes towards the distance they all travel...

Analytic processing of distance.

Science.gov (United States)

Dopkins, Stephen; Galyer, Darin

2018-01-01

How does a human observer extract from the distance between two frontal points the component corresponding to an axis of a rectangular reference frame? To find out we had participants classify pairs of small circles, varying on the horizontal and vertical axes of a computer screen, in terms of the horizontal distance between them. A response signal controlled response time. The error rate depended on the irrelevant vertical as well as the relevant horizontal distance between the test circles with the relevant distance effect being larger than the irrelevant distance effect. The results implied that the horizontal distance between the test circles was imperfectly extracted from the overall distance between them. The results supported an account, derived from the Exemplar Based Random Walk model (Nosofsky & Palmieri, 1997), under which distance classification is based on the overall distance between the test circles, with relevant distance being extracted from overall distance to the extent that the relevant and irrelevant axes are differentially weighted so as to reduce the contribution of irrelevant distance to overall distance. The results did not support an account, derived from the General Recognition Theory (Ashby & Maddox, 1994), under which distance classification is based on the relevant distance between the test circles, with the irrelevant distance effect arising because a test circle's perceived location on the relevant axis depends on its location on the irrelevant axis, and with relevant distance being extracted from overall distance to the extent that this dependency is absent. Copyright © 2017 Elsevier B.V. All rights reserved.

Medical telerehabilitation: an effective method for the long-distance functional evaluation of patients

Directory of Open Access Journals (Sweden)

DOGARU Gabriela

2014-02-01

Full Text Available Experts predicted as early as 10 years ago that starting with 2010, at least 15% of health care services worldwide would be provided from a distance, using telemedicine (1. The expansion of the fields of medicine at a distance has been possible due to the progress made in the area of communication and information technologies. These can increase the capacity of health care services, improve service provision and allow people to better take care of their health. In a society undergoing a significant transformation process at the beginning of the third millennium, the use of modern communication means for the improvement of the quality of life of disadvantaged social groups is a necessity.

Distancing, not embracing, the Distancing-Embracing model of art reception.

Science.gov (United States)

Davies, Stephen

2017-01-01

Despite denials in the target article, the Distancing-Embracing model appeals to compensatory ideas in explaining the appeal of artworks that elicit negative affect. The model also appeals to the deflationary effects of psychological distancing. Having pointed to the famous rejection in the 1960s of the view that aesthetic experience involves psychological distancing, I suggest that "distance" functions here as a weak metaphor that cannot sustain the explanatory burden the theory demands of it.

Linear algebra and analytic geometry for physical sciences

CERN Document Server

Landi, Giovanni

2018-01-01

A self-contained introduction to finite dimensional vector spaces, matrices, systems of linear equations, spectral analysis on euclidean and hermitian spaces, affine euclidean geometry, quadratic forms and conic sections. The mathematical formalism is motivated and introduced by problems from physics, notably mechanics (including celestial) and electro-magnetism, with more than two hundreds examples and solved exercises. Topics include: The group of orthogonal transformations on euclidean spaces, in particular rotations, with Euler angles and angular velocity. The rigid body with its inertia matrix. The unitary group. Lie algebras and exponential map. The Dirac’s bra-ket formalism. Spectral theory for self-adjoint endomorphisms on euclidean and hermitian spaces. The Minkowski spacetime from special relativity and the Maxwell equations. Conic sections with the use of eccentricity and Keplerian motions. An appendix collects basic algebraic notions like group, ring and field; and complex numbers and integers m...

Foundations of Distance Education. Third Edition. Routledge Studies in Distance Education.

Science.gov (United States)

Keegan, Desmond

This text gives an overview of distance education for students, administrators, and practitioners in distance education. Chapter 1 discusses the study of distance education. Chapter 2 analyzes forms of nonconventional education (open, nontraditional) that may have similarities to distance education but are not to be identified with it. Chapter 3…

modelling distances

Directory of Open Access Journals (Sweden)

Robert F. Love

2001-01-01

Full Text Available Distance predicting functions may be used in a variety of applications for estimating travel distances between points. To evaluate the accuracy of a distance predicting function and to determine its parameters, a goodness-of-fit criteria is employed. AD (Absolute Deviations, SD (Squared Deviations and NAD (Normalized Absolute Deviations are the three criteria that are mostly employed in practice. In the literature some assumptions have been made about the properties of each criterion. In this paper, we present statistical analyses performed to compare the three criteria from different perspectives. For this purpose, we employ the ℓkpθ-norm as the distance predicting function, and statistically compare the three criteria by using normalized absolute prediction error distributions in seventeen geographical regions. We find that there exist no significant differences between the criteria. However, since the criterion SD has desirable properties in terms of distance modelling procedures, we suggest its use in practice.

On approximately fair cost allocation in Euclidean TSP games

NARCIS (Netherlands)

Faigle, U.; Fekete, Sándor P.; Hochstättler, Winfried; Kern, Walter

1998-01-01

We consider the problem of allocating the cost of an optimal traveling salesman tour in a fair way among the nodes visited; in particular, we focus on the case where the distance matrix of the underlying TSP problem satisfies the triangle inequality. We thereby use the model of TSP games in the

Dimensionality Reduction of Hyperspectral Image with Graph-Based Discriminant Analysis Considering Spectral Similarity

Directory of Open Access Journals (Sweden)

Fubiao Feng

2017-03-01

Full Text Available Recently, graph embedding has drawn great attention for dimensionality reduction in hyperspectral imagery. For example, locality preserving projection (LPP utilizes typical Euclidean distance in a heat kernel to create an affinity matrix and projects the high-dimensional data into a lower-dimensional space. However, the Euclidean distance is not sufficiently correlated with intrinsic spectral variation of a material, which may result in inappropriate graph representation. In this work, a graph-based discriminant analysis with spectral similarity (denoted as GDA-SS measurement is proposed, which fully considers curves changing description among spectral bands. Experimental results based on real hyperspectral images demonstrate that the proposed method is superior to traditional methods, such as supervised LPP, and the state-of-the-art sparse graph-based discriminant analysis (SGDA.

DENBRAN: A basic program for a significance test for multivariate normality of clusters from branching patterns in dendrograms

Science.gov (United States)

Sneath, P. H. A.

A BASIC program is presented for significance tests to determine whether a dendrogram is derived from clustering of points that belong to a single multivariate normal distribution. The significance tests are based on statistics of the Kolmogorov—Smirnov type, obtained by comparing the observed cumulative graph of branch levels with a graph for the hypothesis of multivariate normality. The program also permits testing whether the dendrogram could be from a cluster of lower dimensionality due to character correlations. The program makes provision for three similarity coefficients, (1) Euclidean distances, (2) squared Euclidean distances, and (3) Simple Matching Coefficients, and for five cluster methods (1) WPGMA, (2) UPGMA, (3) Single Linkage (or Minimum Spanning Trees), (4) Complete Linkage, and (5) Ward's Increase in Sums of Squares. The program is entitled DENBRAN.

Information networks in the stock market based on the distance of the multi-attribute dimensions between listed companies

Science.gov (United States)

Liu, Qian; Li, Huajiao; Liu, Xueyong; Jiang, Meihui

2018-04-01

In the stock market, there are widespread information connections between economic agents. Listed companies can obtain mutual information about investment decisions from common shareholders, and the extent of sharing information often determines the relationships between listed companies. Because different shareholder compositions and investment shares lead to different formations of the company's governance mechanisms, we map the investment relationships between shareholders to the multi-attribute dimensional spaces of the listed companies (each shareholder investment in a company is a company dimension). Then, we construct the listed company's information network based on co-shareholder relationships. The weights for the edges in the information network are measured with the Euclidean distance between the listed companies in the multi-attribute dimension space. We define two indices to analyze the information network's features. We conduct an empirical study that analyzes Chinese listed companies' information networks. The results from the analysis show that with the diversification and decentralization of shareholder investments, almost all Chinese listed companies exchanged information through common shareholder relationships, and there is a gradual reduction in information sharing capacity between listed companies that have common shareholders. This network analysis has benefits for risk management and portfolio investments.

Protection Coordination in Electrical Substation Part-2 Unit Protections (Differential and Distance Protection)

OpenAIRE

TÜR, Mehmet Rida; Shobole, Abdulfetah; Baysal, Mustafa; Wadi, Mohammed

2018-01-01

Power systemsmust be protected against faults to ensure quality and reliable generation,transmission and distribution of power systems. Power system protection is providedby the protection relays. This paper is the second part of the ProtectionCoordination study for the Siddik Kardesler Substation. The protection fortransmission lines, transformer, bus bars and customer feeders is provided byovercurrent protection, differential and distance protection schemes. In thispaper, issues related wit...

Robust Point Matching for Non-Rigid Shapes: A Relaxation Labeling Based Approach

National Research Council Canada - National Science Library

Zheng, Yefeng; Doermann, David S

2004-01-01

.... Based on this observation, we formulate point matching as a graph matching problem. Each point is a node in the graph, and two nodes are connected by an edge if their Euclidean distance is less...

In vitro embryo rescue and plant regeneration following self ...

African Journals Online (AJOL)

EJIRO

2015-07-08

Jul 8, 2015 ... calculated using the simple matching Euclidean distance (DE) followed by cluster analysis ..... we plan to fully characterize these plantlets and to establish whether or not .... Tesis de Grado, Universidad. ICESI, Cali. Colombia.

Brownian distance covariance

OpenAIRE

Székely, Gábor J.; Rizzo, Maria L.

2010-01-01

Distance correlation is a new class of multivariate dependence coefficients applicable to random vectors of arbitrary and not necessarily equal dimension. Distance covariance and distance correlation are analogous to product-moment covariance and correlation, but generalize and extend these classical bivariate measures of dependence. Distance correlation characterizes independence: it is zero if and only if the random vectors are independent. The notion of covariance with...

The Effect of Transformational Leadership Behavior on Organizational Culture: An Application in Pharmaceutical Industry

Directory of Open Access Journals (Sweden)

Sinem Aydogdu

2011-01-01

Full Text Available In this study, conducted on 96 employees from production sector in a pharmaceutical company, the effect of transformational leadership behavior on organizational culture is investigated to determine statistically significant relations. The results of the study support the hypotheses. Transformational leadership behavior has a positive and significant correlation between the components of organizational culture such as long / short term orientation, masculinity / feminity, power distance, individualism / collectivisim and uncertainity avoidance.

Traversing psychological distance.

Science.gov (United States)

Liberman, Nira; Trope, Yaacov

2014-07-01

Traversing psychological distance involves going beyond direct experience, and includes planning, perspective taking, and contemplating counterfactuals. Consistent with this view, temporal, spatial, and social distances as well as hypotheticality are associated, affect each other, and are inferred from one another. Moreover, traversing all distances involves the use of abstraction, which we define as forming a belief about the substitutability for a specific purpose of subjectively distinct objects. Indeed, across many instances of both abstraction and psychological distancing, more abstract constructs are used for more distal objects. Here, we describe the implications of this relation for prediction, choice, communication, negotiation, and self-control. We ask whether traversing distance is a general mental ability and whether distance should replace expectancy in expected-utility theories. Copyright © 2014 Elsevier Ltd. All rights reserved.

A transfer learning framework for traffic video using neuro-fuzzy ...

Indian Academy of Sciences (India)

P M Ashok Kumar

2017-08-04

Aug 4, 2017 ... The proposed ANFIS-LCTE transfer learning model consists of four steps. (1) Low level visual items .... algorithm clusters object trajectories based on the distance parameters like Euclidean ..... Machine Learning, pp. 113–120.

Improving the maximum transmission distance of continuous-variable quantum key distribution with noisy coherent states using a noiseless amplifier

International Nuclear Information System (INIS)

Wang, Tianyi; Yu, Song; Zhang, Yi-Chen; Gu, Wanyi; Guo, Hong

2014-01-01

By employing a nondeterministic noiseless linear amplifier, we propose to increase the maximum transmission distance of continuous-variable quantum key distribution with noisy coherent states. With the covariance matrix transformation, the expression of secret key rate under reverse reconciliation is derived against collective entangling cloner attacks. We show that the noiseless linear amplifier can compensate the detrimental effect of the preparation noise with an enhancement of the maximum transmission distance and the noise resistance. - Highlights: • Noiseless amplifier is applied in noisy coherent state quantum key distribution. • Negative effect of preparation noise is compensated by noiseless amplification. • Maximum transmission distance and noise resistance are both enhanced

Open and Distance Learning Today. Routledge Studies in Distance Education Series.

Science.gov (United States)

Lockwood, Fred, Ed.

This book contains the following papers on open and distance learning today: "Preface" (Daniel); "Big Bang Theory in Distance Education" (Hawkridge); "Practical Agenda for Theorists of Distance Education" (Perraton); "Trends, Directions and Needs: A View from Developing Countries" (Koul); "American…

The electromagnetic potentials without the gauge transformations

Energy Technology Data Exchange (ETDEWEB)

Espinoza, Augusto; Chubykalo, Andrey; Rodriguez, Alejandro Gutierrez; Hernandez, Maria de los Angeles [Universidad Autonoma de Zacatecas (Mexico). Unidad Academica de Fisica

2011-07-01

In this note we show that the use of the Helmholtz theorem lead to derivation of uniquely determined electromagnetic potentials without making use of the gauge transformation. These potentials correspond to the potentials obtained by imposing so-called Coulomb condition (gauge) in the traditional approach. We show that the electromagnetic field comprises two components, one of which is characterized by its instantaneous action at a distance, whereas another one propagates in the retarded form with the velocity of light. One of the theoretical consequences of this new definition is that the electromagnetic potentials are real physical quantities as well as the electric and magnetic fields. We show that the reality of the electromagnetic potentials in quantum-mechanics is also a property of these potentials in the classical electrodynamics. Equations for potentials obtained in our approach are already separated with respect to vector and scalar potentials, so there is no necessity in using the gauge transformations and, accordingly, in making use of either Lorentz or Coulomb condition. The vector potential and scalar potential introduced thus are uniquely defined. The scalar potential is a generator of the so called instantaneous action at a distance, whereas the solenoidal vector potential can propagate with the velocity of light and it is responsible for the retarded action of the electromagnetic field. (author)

Unrecorded Accidents Detection on Highways Based on Temporal Data Mining

Directory of Open Access Journals (Sweden)

Shi An

2014-01-01

Full Text Available Automatic traffic accident detection, especially not recorded by traffic police, is crucial to accident black spots identification and traffic safety. A new method of detecting traffic accidents is proposed based on temporal data mining, which can identify the unknown and unrecorded accidents by traffic police. Time series model was constructed using ternary numbers to reflect the state of traffic flow based on cell transmission model. In order to deal with the aftereffects of linear drift between time series and to reduce the computational cost, discrete Fourier transform was implemented to turn time series from time domain to frequency domain. The pattern of the time series when an accident happened could be recognized using the historical crash data. Then taking Euclidean distance as the similarity evaluation function, similarity data mining of the transformed time series was carried out. If the result was less than the given threshold, the two time series were similar and an accident happened probably. A numerical example was carried out and the results verified the effectiveness of the proposed method.

Probabilistic models for 2D active shape recognition using Fourier descriptors and mutual information

CSIR Research Space (South Africa)

Govender, N

2014-08-01

Full Text Available information to improve the initial shape recognition results. We propose an initial system which performs shape recognition using the euclidean distances of Fourier descriptors. To improve upon these results we build multinomial and Gaussian probabilistic...

From a distance: implications of spontaneous self-distancing for adaptive self-reflection.

Science.gov (United States)

Ayduk, Ozlem; Kross, Ethan

2010-05-01

Although recent experimental work indicates that self-distancing facilitates adaptive self-reflection, it remains unclear (a) whether spontaneous self-distancing leads to similar adaptive outcomes, (b) how spontaneous self-distancing relates to avoidance, and (c) how this strategy impacts interpersonal behavior. Three studies examined these issues demonstrating that the more participants spontaneously self-distanced while reflecting on negative memories, the less emotional (Studies 1-3) and cardiovascular (Study 2) reactivity they displayed in the short term. Spontaneous self-distancing was also associated with lower emotional reactivity and intrusive ideation over time (Study 1). The negative association between spontaneous self-distancing and emotional reactivity was mediated by how participants construed their experience (i.e., less recounting relative to reconstruing) rather than avoidance (Studies 1-2). In addition, spontaneous self-distancing was associated with more problem-solving behavior and less reciprocation of negativity during conflicts among couples in ongoing relationships (Study 3). Although spontaneous self-distancing was empirically related to trait rumination, it explained unique variance in predicting key outcomes. 2010 APA, all rights reserved

1.28 Tbaud Nyquist Signal Transmission using Time-Domain Optical Fourier Transformation based Receiver

DEFF Research Database (Denmark)

Hu, Hao; Kong, Deming; Palushani, Evarist

2013-01-01

We demonstrate transmission of a 1.28-Tbaud Nyquist-OTDM signal over a record distance of 100 km with detection by time-domain optical Fourier transformation followed by FEC decoding, resulting in error-free performance for all tributaries....

Transformation of vivianite by anaerobic nitrate-reducing iron-oxidizing bacteria.

Science.gov (United States)

Miot, J; Benzerara, K; Morin, G; Bernard, S; Beyssac, O; Larquet, E; Kappler, A; Guyot, F

2009-06-01

In phosphate-rich environments, vivianite (Fe(II)(3)(PO(4))(2), 8H(2)O) is an important sink for dissolved Fe(II) and is considered as a very stable mineral due to its low solubility at neutral pH. In the present study, we report the mineralogical transformation of vivianite in cultures of the nitrate-reducing iron-oxidizing bacterial strain BoFeN1 in the presence of dissolved Fe(II). Vivianite was first transformed into a greenish phase consisting mostly of an amorphous mixed valence Fe-phosphate. This precipitate became progressively orange and the final product of iron oxidation consisted of an amorphous Fe(III)-phosphate. The sub-micrometer analysis by scanning transmission X-ray microscopy of the iron redox state in samples collected at different stages of the culture indicated that iron was progressively oxidized at the contact of the bacteria and at a distance from the cells in extracellular minerals. Iron oxidation in the extracellular minerals was delayed by a few days compared with cell-associated Fe-minerals. This led to strong differences of Fe redox in between these two types of minerals and finally to local heterogeneities of redox within the sample. In the absence of dissolved Fe(II), vivianite was not significantly transformed by BoFeN1. Whereas Fe(II) oxidation at the cell contact is most probably directly catalyzed by the bacteria, vivianite transformation at a distance from the cells might result from oxidation by nitrite. In addition, processes leading to the export of Fe(III) from bacterial oxidation sites to extracellular minerals are discussed including some involving colloids observed by cryo-transmission electron microscopy in the culture medium.

Distance-regular graphs

NARCIS (Netherlands)

van Dam, Edwin R.; Koolen, Jack H.; Tanaka, Hajime

2016-01-01

This is a survey of distance-regular graphs. We present an introduction to distance-regular graphs for the reader who is unfamiliar with the subject, and then give an overview of some developments in the area of distance-regular graphs since the monograph 'BCN'[Brouwer, A.E., Cohen, A.M., Neumaier,

Network Kernel Density Estimation for the Analysis of Facility POI Hotspots

Directory of Open Access Journals (Sweden)

YU Wenhao

2015-12-01

Full Text Available The distribution pattern of urban facility POIs (points of interest usually forms clusters (i.e. "hotspots" in urban geographic space. To detect such type of hotspot, the methods mostly employ spatial density estimation based on Euclidean distance, ignoring the fact that the service function and interrelation of urban feasibilities is carried out on the network path distance, neither than conventional Euclidean distance. By using these methods, it is difficult to exactly and objectively delimitate the shape and the size of hotspot. Therefore, this research adopts the kernel density estimation based on the network distance to compute the density of hotspot and proposes a simple and efficient algorithm. The algorithm extends the 2D dilation operator to the 1D morphological operator, thus computing the density of network unit. Through evaluation experiment, it is suggested that the algorithm is more efficient and scalable than the existing algorithms. Based on the case study on real POI data, the range of hotspot can highlight the spatial characteristic of urban functions along traffic routes, in order to provide valuable spatial knowledge and information services for the applications of region planning, navigation and geographic information inquiring.

Why conventional detection methods fail in identifying the existence of contamination events.

Science.gov (United States)

Liu, Shuming; Li, Ruonan; Smith, Kate; Che, Han

2016-04-15

Early warning systems are widely used to safeguard water security, but their effectiveness has raised many questions. To understand why conventional detection methods fail to identify contamination events, this study evaluates the performance of three contamination detection methods using data from a real contamination accident and two artificial datasets constructed using a widely applied contamination data construction approach. Results show that the Pearson correlation Euclidean distance (PE) based detection method performs better for real contamination incidents, while the Euclidean distance method (MED) and linear prediction filter (LPF) method are more suitable for detecting sudden spike-like variation. This analysis revealed why the conventional MED and LPF methods failed to identify existence of contamination events. The analysis also revealed that the widely used contamination data construction approach is misleading. Copyright © 2016 Elsevier Ltd. All rights reserved.

Hierarchical traits distances explain grassland Fabaceae species' ecological niches distances

Science.gov (United States)

Fort, Florian; Jouany, Claire; Cruz, Pablo

2015-01-01

Fabaceae species play a key role in ecosystem functioning through their capacity to fix atmospheric nitrogen via their symbiosis with Rhizobium bacteria. To increase benefits of using Fabaceae in agricultural systems, it is necessary to find ways to evaluate species or genotypes having potential adaptations to sub-optimal growth conditions. We evaluated the relevance of phylogenetic distance, absolute trait distance and hierarchical trait distance for comparing the adaptation of 13 grassland Fabaceae species to different habitats, i.e., ecological niches. We measured a wide range of functional traits (root traits, leaf traits, and whole plant traits) in these species. Species phylogenetic and ecological distances were assessed from a species-level phylogenetic tree and species' ecological indicator values, respectively. We demonstrated that differences in ecological niches between grassland Fabaceae species were related more to their hierarchical trait distances than to their phylogenetic distances. We showed that grassland Fabaceae functional traits tend to converge among species with the same ecological requirements. Species with acquisitive root strategies (thin roots, shallow root systems) are competitive species adapted to non-stressful meadows, while conservative ones (coarse roots, deep root systems) are able to tolerate stressful continental climates. In contrast, acquisitive species appeared to be able to tolerate low soil-P availability, while conservative ones need high P availability. Finally we highlight that traits converge along the ecological gradient, providing the assumption that species with similar root-trait values are better able to coexist, regardless of their phylogenetic distance. PMID:25741353

Hierarchical traits distances explain grassland Fabaceae species’ ecological niches distances

Directory of Open Access Journals (Sweden)

Florian eFort

2015-02-01

Full Text Available Fabaceae species play a key role in ecosystem functioning through their capacity to fix atmospheric nitrogen via their symbiosis with Rhizobium bacteria. To increase benefits of using Fabaceae in agricultural systems, it is necessary to find ways to evaluate species or genotypes having potential adaptations to sub-optimal growth conditions. We evaluated the relevance of phylogenetic distance, absolute trait distance and hierarchical trait distance for comparing the adaptation of 13 grassland Fabaceae species to different habitats, i.e. ecological niches. We measured a wide range of functional traits (root traits, leaf traits and whole plant traits in these species. Species phylogenetic and ecological distances were assessed from a species-level phylogenetic tree and species’ ecological indicator values, respectively. We demonstrated that differences in ecological niches between grassland Fabaceae species were related more to their hierarchical trait distances than to their phylogenetic distances. We showed that grassland Fabaceae functional traits tend to converge among species with the same ecological requirements. Species with acquisitive root strategies (thin roots, shallow root systems are competitive species adapted to non-stressful meadows, while conservative ones (coarse roots, deep root systems are able to tolerate stressful continental climates. In contrast, acquisitive species appeared to be able to tolerate low soil-P availability, while conservative ones need high P availability. Finally we highlight that traits converge along the ecological gradient, providing the assumption that species with similar root-trait values are better able to coexist, regardless of their phylogenetic distance.

Numerical distance protection

CERN Document Server

Ziegler, Gerhard

2011-01-01

Distance protection provides the basis for network protection in transmission systems and meshed distribution systems. This book covers the fundamentals of distance protection and the special features of numerical technology. The emphasis is placed on the application of numerical distance relays in distribution and transmission systems.This book is aimed at students and engineers who wish to familiarise themselves with the subject of power system protection, as well as the experienced user, entering the area of numerical distance protection. Furthermore it serves as a reference guide for s

Optimal Formation of Multirobot Systems Based on a Recurrent Neural Network.

Science.gov (United States)

Wang, Yunpeng; Cheng, Long; Hou, Zeng-Guang; Yu, Junzhi; Tan, Min

2016-02-01

The optimal formation problem of multirobot systems is solved by a recurrent neural network in this paper. The desired formation is described by the shape theory. This theory can generate a set of feasible formations that share the same relative relation among robots. An optimal formation means that finding one formation from the feasible formation set, which has the minimum distance to the initial formation of the multirobot system. Then, the formation problem is transformed into an optimization problem. In addition, the orientation, scale, and admissible range of the formation can also be considered as the constraints in the optimization problem. Furthermore, if all robots are identical, their positions in the system are exchangeable. Then, each robot does not necessarily move to one specific position in the formation. In this case, the optimal formation problem becomes a combinational optimization problem, whose optimal solution is very hard to obtain. Inspired by the penalty method, this combinational optimization problem can be approximately transformed into a convex optimization problem. Due to the involvement of the Euclidean norm in the distance, the objective function of these optimization problems are nonsmooth. To solve these nonsmooth optimization problems efficiently, a recurrent neural network approach is employed, owing to its parallel computation ability. Finally, some simulations and experiments are given to validate the effectiveness and efficiency of the proposed optimal formation approach.

Remote Sensing Image Registration Using Multiple Image Features

Directory of Open Access Journals (Sweden)

Kun Yang

2017-06-01

Full Text Available Remote sensing image registration plays an important role in military and civilian fields, such as natural disaster damage assessment, military damage assessment and ground targets identification, etc. However, due to the ground relief variations and imaging viewpoint changes, non-rigid geometric distortion occurs between remote sensing images with different viewpoint, which further increases the difficulty of remote sensing image registration. To address the problem, we propose a multi-viewpoint remote sensing image registration method which contains the following contributions. (i A multiple features based finite mixture model is constructed for dealing with different types of image features. (ii Three features are combined and substituted into the mixture model to form a feature complementation, i.e., the Euclidean distance and shape context are used to measure the similarity of geometric structure, and the SIFT (scale-invariant feature transform distance which is endowed with the intensity information is used to measure the scale space extrema. (iii To prevent the ill-posed problem, a geometric constraint term is introduced into the L2E-based energy function for better behaving the non-rigid transformation. We evaluated the performances of the proposed method by three series of remote sensing images obtained from the unmanned aerial vehicle (UAV and Google Earth, and compared with five state-of-the-art methods where our method shows the best alignments in most cases.

Determining Distance Education Students' Readiness for Mobile Learning at University of Ghana Using the Theory of Planned Behavior

Science.gov (United States)

Tagoe, Michael Ayitey; Abakah, Ellen

2014-01-01

The use of mobile technologies in the classroom is transforming teaching and learning in higher institutions. This study investigated University of Ghana Distance Education students' perceptions toward mobile learning. The paper using the theory of planned behaviour (TPB) explained how students' beliefs influenced students' intention to adopt…

The Distance Standard Deviation

OpenAIRE

Edelmann, Dominic; Richards, Donald; Vogel, Daniel

2017-01-01

The distance standard deviation, which arises in distance correlation analysis of multivariate data, is studied as a measure of spread. New representations for the distance standard deviation are obtained in terms of Gini's mean difference and in terms of the moments of spacings of order statistics. Inequalities for the distance variance are derived, proving that the distance standard deviation is bounded above by the classical standard deviation and by Gini's mean difference. Further, it is ...

Antisymmetric Orbit Functions

Directory of Open Access Journals (Sweden)

Anatoliy Klimyk

2007-02-01

Full Text Available In the paper, properties of antisymmetric orbit functions are reviewed and further developed. Antisymmetric orbit functions on the Euclidean space $E_n$ are antisymmetrized exponential functions. Antisymmetrization is fulfilled by a Weyl group, corresponding to a Coxeter-Dynkin diagram. Properties of such functions are described. These functions are closely related to irreducible characters of a compact semisimple Lie group $G$ of rank $n$. Up to a sign, values of antisymmetric orbit functions are repeated on copies of the fundamental domain $F$ of the affine Weyl group (determined by the initial Weyl group in the entire Euclidean space $E_n$. Antisymmetric orbit functions are solutions of the corresponding Laplace equation in $E_n$, vanishing on the boundary of the fundamental domain $F$. Antisymmetric orbit functions determine a so-called antisymmetrized Fourier transform which is closely related to expansions of central functions in characters of irreducible representations of the group $G$. They also determine a transform on a finite set of points of $F$ (the discrete antisymmetric orbit function transform. Symmetric and antisymmetric multivariate exponential, sine and cosine discrete transforms are given.

Multivariate correlation analysis technique based on euclidean distance map for network traffic characterization

NARCIS (Netherlands)

Tan, Zhiyuan; Jamdagni, Aruna; He, Xiangjian; Nanda, Priyadarsi; Liu, Ren Ping; Qing, Sihan; Susilo, Willy; Wang, Guilin; Liu, Dongmei

2011-01-01

The quality of feature has significant impact on the performance of detection techniques used for Denial-of-Service (DoS) attack. The features that fail to provide accurate characterization for network traffic records make the techniques suffer from low accuracy in detection. Although researches

Distance Education in Turkey

Directory of Open Access Journals (Sweden)

Dr. Nursel Selver RUZGAR,

2004-04-01

Full Text Available Distance Education in Turkey Assistant Professor Dr. Nursel Selver RUZGAR Technical Education Faculty Marmara University, TURKEY ABSTRACT Many countries of the world are using distance education with various ways, by internet, by post and by TV. In this work, development of distance education in Turkey has been presented from the beginning. After discussing types and applications for different levels of distance education in Turkey, the distance education was given in the cultural aspect of the view. Then, in order to create the tendencies and thoughts of graduates of Higher Education Institutions and Distance Education Institutions about being competitors in job markets, sufficiency of education level, advantages for education system, continuing education in different Institutions, a face-to-face survey was applied to 1284 graduates, 958 from Higher Education Institutions and 326 from Distance Education Institutions. The results were evaluated and discussed. In the last part of this work, suggestions to become widespread and improve the distance education in the country were made.

A New Trajectory Similarity Measure for GPS Data

KAUST Repository

Ismail, Anas; Vigneron, Antoine E.

2016-01-01

We present a new algorithm for measuring the similarity between trajectories, and in particular between GPS traces. We call this new similarity measure the Merge Distance (MD). Our approach is robust against subsampling and supersampling. We perform experiments to compare this new similarity measure with the two main approaches that have been used so far: Dynamic Time Warping (DTW) and the Euclidean distance. © 2015 ACM.

A New Trajectory Similarity Measure for GPS Data

KAUST Repository

Ismail, Anas

2016-08-08

We present a new algorithm for measuring the similarity between trajectories, and in particular between GPS traces. We call this new similarity measure the Merge Distance (MD). Our approach is robust against subsampling and supersampling. We perform experiments to compare this new similarity measure with the two main approaches that have been used so far: Dynamic Time Warping (DTW) and the Euclidean distance. © 2015 ACM.

The algorithm of fast image stitching based on multi-feature extraction

Science.gov (United States)

Yang, Chunde; Wu, Ge; Shi, Jing

2018-05-01

This paper proposed an improved image registration method combining Hu-based invariant moment contour information and feature points detection, aiming to solve the problems in traditional image stitching algorithm, such as time-consuming feature points extraction process, redundant invalid information overload and inefficiency. First, use the neighborhood of pixels to extract the contour information, employing the Hu invariant moment as similarity measure to extract SIFT feature points in those similar regions. Then replace the Euclidean distance with Hellinger kernel function to improve the initial matching efficiency and get less mismatching points, further, estimate affine transformation matrix between the images. Finally, local color mapping method is adopted to solve uneven exposure, using the improved multiresolution fusion algorithm to fuse the mosaic images and realize seamless stitching. Experimental results confirm high accuracy and efficiency of method proposed in this paper.

On Lattice Sequential Decoding for The Unconstrained AWGN Channel

KAUST Repository

Abediseid, Walid; Alouini, Mohamed-Slim

2013-01-01

channel has been studied only under the use of the minimum Euclidean distance decoder that is commonly referred to as the \\textit{lattice decoder}. Lattice decoders based on solutions to the NP-hard closest vector problem are very complex to implement

Performance-complexity tradeoff in sequential decoding for the unconstrained AWGN channel

KAUST Repository

Abediseid, Walid; Alouini, Mohamed-Slim

2013-01-01

channel has been studied only under the use of the minimum Euclidean distance decoder that is commonly referred to as the lattice decoder. Lattice decoders based on solutions to the NP-hard closest vector problem are very complex to implement

Haptic Discrimination of Distance

Science.gov (United States)

van Beek, Femke E.; Bergmann Tiest, Wouter M.; Kappers, Astrid M. L.

2014-01-01

While quite some research has focussed on the accuracy of haptic perception of distance, information on the precision of haptic perception of distance is still scarce, particularly regarding distances perceived by making arm movements. In this study, eight conditions were measured to answer four main questions, which are: what is the influence of reference distance, movement axis, perceptual mode (active or passive) and stimulus type on the precision of this kind of distance perception? A discrimination experiment was performed with twelve participants. The participants were presented with two distances, using either a haptic device or a real stimulus. Participants compared the distances by moving their hand from a start to an end position. They were then asked to judge which of the distances was the longer, from which the discrimination threshold was determined for each participant and condition. The precision was influenced by reference distance. No effect of movement axis was found. The precision was higher for active than for passive movements and it was a bit lower for real stimuli than for rendered stimuli, but it was not affected by adding cutaneous information. Overall, the Weber fraction for the active perception of a distance of 25 or 35 cm was about 11% for all cardinal axes. The recorded position data suggest that participants, in order to be able to judge which distance was the longer, tried to produce similar speed profiles in both movements. This knowledge could be useful in the design of haptic devices. PMID:25116638

Haptic discrimination of distance.

Directory of Open Access Journals (Sweden)

Femke E van Beek

Full Text Available While quite some research has focussed on the accuracy of haptic perception of distance, information on the precision of haptic perception of distance is still scarce, particularly regarding distances perceived by making arm movements. In this study, eight conditions were measured to answer four main questions, which are: what is the influence of reference distance, movement axis, perceptual mode (active or passive and stimulus type on the precision of this kind of distance perception? A discrimination experiment was performed with twelve participants. The participants were presented with two distances, using either a haptic device or a real stimulus. Participants compared the distances by moving their hand from a start to an end position. They were then asked to judge which of the distances was the longer, from which the discrimination threshold was determined for each participant and condition. The precision was influenced by reference distance. No effect of movement axis was found. The precision was higher for active than for passive movements and it was a bit lower for real stimuli than for rendered stimuli, but it was not affected by adding cutaneous information. Overall, the Weber fraction for the active perception of a distance of 25 or 35 cm was about 11% for all cardinal axes. The recorded position data suggest that participants, in order to be able to judge which distance was the longer, tried to produce similar speed profiles in both movements. This knowledge could be useful in the design of haptic devices.

Introduction to instantons in Yang-Mills theory

International Nuclear Information System (INIS)

Pak, N.K.

1980-02-01

The Yang-Mills theory is outlined; the classical formalism is discussed first, and then the difficulties related to gauge invariance in the canonical quantization of the theory are taken up. Next, the task of finding and studying Euclidean gauge field configurations of finite action as solutions to the equation of motion is addressed. It is found that configurations which contribute the most in the semi-classical approximation are those which minimize the action. The question of a lower bound for the Euclidean action is considered. Properties of topological charge and the behavior of topological charge under gauge transformation are discussed. Then instanton solutions to the field equations are produced. Finally, the physical interpretation of the instanton is considered. It is found that the instanton, the Euclidean gauge field configuration which minimizes the action, induces tunneling among the infinitely degenerate vacua of the Yang-Mills theory by lifting the degeneracy and creating new distinct inequivalent (invariant under topologically nontrivial gauge transformations) vacua labelled by a superselection index theta. The angle theta is shown not to be a gauge artifact. In conclusion, the tunneling Hamiltonian and effective Lagrangian for the Yang-Mills theory are discussed

Estimation of cylinder orientation in three-dimensional point cloud using angular distance-based optimization

Science.gov (United States)

Su, Yun-Ting; Hu, Shuowen; Bethel, James S.

2017-05-01

Light detection and ranging (LIDAR) has become a widely used tool in remote sensing for mapping, surveying, modeling, and a host of other applications. The motivation behind this work is the modeling of piping systems in industrial sites, where cylinders are the most common primitive or shape. We focus on cylinder parameter estimation in three-dimensional point clouds, proposing a mathematical formulation based on angular distance to determine the cylinder orientation. We demonstrate the accuracy and robustness of the technique on synthetically generated cylinder point clouds (where the true axis orientation is known) as well as on real LIDAR data of piping systems. The proposed algorithm is compared with a discrete space Hough transform-based approach as well as a continuous space inlier approach, which iteratively discards outlier points to refine the cylinder parameter estimates. Results show that the proposed method is more computationally efficient than the Hough transform approach and is more accurate than both the Hough transform approach and the inlier method.

A note on fixed point optimality criteria for the location problem with arbitrary norms: Reply

DEFF Research Database (Denmark)

Juel, Henrik; Love, Robert F.

1983-01-01

The single-facility location problem in continuous space is considered, with distances given by arbitrary norms. When distances are Euclidean, for many practical problems the optimal location of the new facility coincides with one of the existing facilities. This property carries over to problems...... with generalized distances. In this paper a necessary and sufficient condition for the location of an existing facility to be the optimal location of the new facility is developed. Some computational examples using the condition are given....

A measure of association between vectors based on "similarity covariance"

OpenAIRE

Pascual-Marqui, Roberto D.; Lehmann, Dietrich; Kochi, Kieko; Kinoshita, Toshihiko; Yamada, Naoto

2013-01-01

The "maximum similarity correlation" definition introduced in this study is motivated by the seminal work of Szekely et al on "distance covariance" (Ann. Statist. 2007, 35: 2769-2794; Ann. Appl. Stat. 2009, 3: 1236-1265). Instead of using Euclidean distances "d" as in Szekely et al, we use "similarity", which can be defined as "exp(-d/s)", where the scaling parameter s>0 controls how rapidly the similarity falls off with distance. Scale parameters are chosen by maximizing the similarity corre...

Land cover and topography affect the land transformation caused by wind facilities.

Directory of Open Access Journals (Sweden)

Jay E Diffendorfer

Full Text Available Land transformation (ha of surface disturbance/MW associated with wind facilities shows wide variation in its reported values. In addition, no studies have attempted to explain the variation across facilities. We digitized land transformation at 39 wind facilities using high resolution aerial imagery. We then modeled the effects of turbine size, configuration, land cover, and topography on the levels of land transformation at three spatial scales. The scales included strings (turbines with intervening roads only, sites (strings with roads connecting them, buried cables and other infrastructure, and entire facilities (sites and the roads or transmission lines connecting them to existing infrastructure. An information theoretic modeling approach indicated land cover and topography were well-supported variables affecting land transformation, but not turbine size or configuration. Tilled landscapes, despite larger distances between turbines, had lower average land transformation, while facilities in forested landscapes generally had the highest land transformation. At site and string scales, flat topographies had the lowest land transformation, while facilities on mesas had the largest. The results indicate the landscape in which the facilities are placed affects the levels of land transformation associated with wind energy. This creates opportunities for optimizing wind energy production while minimizing land cover change. In addition, the results indicate forecasting the impacts of wind energy on land transformation should include the geographic variables affecting land transformation reported here.

The influence of habitat structure on genetic differentiation in red fox populations in north-eastern Poland.

Science.gov (United States)

Mullins, Jacinta; McDevitt, Allan D; Kowalczyk, Rafał; Ruczyńska, Iwona; Górny, Marcin; Wójcik, Jan M

2014-01-01

The red fox ( Vulpes vulpes ) has the widest global distribution among terrestrial carnivore species, occupying most of the Northern Hemisphere in its native range. Because it carries diseases that can be transmitted to humans and domestic animals, it is important to gather information about their movements and dispersal in their natural habitat but it is difficult to do so at a broad scale with trapping and telemetry. In this study, we have described the genetic diversity and structure of red fox populations in six areas of north-eastern Poland, based on samples collected from 2002-2003. We tested 22 microsatellite loci isolated from the dog and the red fox genome to select a panel of nine polymorphic loci suitable for this study. Genetic differentiation between the six studied populations was low to moderate and analysis in Structure revealed a panmictic population in the region. Spatial autocorrelation among all individuals showed a pattern of decreasing relatedness with increasing distance and this was not significantly negative until 93 km, indicating a pattern of isolation-by-distance over a large area. However, there was no correlation between genetic distance and either Euclidean distance or least-cost path distance at the population level. There was a significant relationship between genetic distance and the proportion of large forests and water along the Euclidean distances. These types of habitats may influence dispersal paths taken by red foxes, which is useful information in terms of wildlife disease management.

Using the Bootstrap Method for a Statistical Significance Test of Differences between Summary Histograms

Science.gov (United States)

Xu, Kuan-Man

2006-01-01

A new method is proposed to compare statistical differences between summary histograms, which are the histograms summed over a large ensemble of individual histograms. It consists of choosing a distance statistic for measuring the difference between summary histograms and using a bootstrap procedure to calculate the statistical significance level. Bootstrapping is an approach to statistical inference that makes few assumptions about the underlying probability distribution that describes the data. Three distance statistics are compared in this study. They are the Euclidean distance, the Jeffries-Matusita distance and the Kuiper distance. The data used in testing the bootstrap method are satellite measurements of cloud systems called cloud objects. Each cloud object is defined as a contiguous region/patch composed of individual footprints or fields of view. A histogram of measured values over footprints is generated for each parameter of each cloud object and then summary histograms are accumulated over all individual histograms in a given cloud-object size category. The results of statistical hypothesis tests using all three distances as test statistics are generally similar, indicating the validity of the proposed method. The Euclidean distance is determined to be most suitable after comparing the statistical tests of several parameters with distinct probability distributions among three cloud-object size categories. Impacts on the statistical significance levels resulting from differences in the total lengths of satellite footprint data between two size categories are also discussed.

The effect of the distance between acidic site and basic site immobilized on mesoporous solid on the activity in catalyzing aldol condensation

Science.gov (United States)

Yu, Xiaofang; Yu, Xiaobo; Wu, Shujie; Liu, Bo; Liu, Heng; Guan, Jingqi; Kan, Qiubin

2011-02-01

Acid-base bifunctional heterogeneous catalysts containing carboxylic and amine groups, which were immobilized at defined distance from one another on the mesoporous solid were synthesized by immobilizing lysine onto carboxyl-SBA-15. The obtained materials were characterized by X-ray diffraction (XRD), N 2 adsorption, Fourier-transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), scanning electron micrographs (SEM), transmission electron micrographs (TEM), elemental analysis, and back titration. Proximal-C-A-SBA-15 with a proximal acid-base distance was more active than maximum-C-A-SBA-15 with a maximum acid-base distance in aldol condensation reaction between acetone and various aldehydes. It appears that the distance between acidic site and basic site immobilized on mesoporous solid should be an essential factor for catalysis optimization.

Numerical analysis of DNA microarray data of Campylobacter jejuni strains correlated with survival, cytolethal distending toxin and haemolysin analyses

DEFF Research Database (Denmark)

On, Stephen L.W.; Dorrell, N.; Petersen, L.

2006-01-01

. Among the strains examined, 439 genes were polymorphic. Numerical analysis of these data by use of the squared Euclidean distance coefficient and Ward's clustering method clearly delineated strains into two clusters. CDT and haemolysin activities of cluster 1 strains were not statistically significantly...

Incorporating landscape elements into a connectivity measure: a case study for the speckled wood butterfly (Pararge aegeria L.)

NARCIS (Netherlands)

Chardon, J.P.; Adriaensen, F.; Matthysen, E.

2003-01-01

In spatial studies of populations, Euclidean distance is commonly used to measure the structural connectivity between habitat patches. The role of the matrix on patch connectivity is thereby ignored. However, the importance of the matrix for (dispersal) movement is increasingly being acknowledged.

Do seasonal profiles of foliar pigments improve species discrimination of evergreen coastal tree species in KwaZulu- Natal, South Africa?

CSIR Research Space (South Africa)

Van Deventer, Heidi

2013-04-01

Full Text Available of seven evergreen tree species in a sub-tropical region of South Africa, over four seasons during 2011-12. Parametric ANOVA classification was compared to similarity measures of shape (spectral angle mapper; SAM) and magnitude (sum of Euclidean Distance...

Hierarchical clustering using correlation metric and spatial continuity constraint

Science.gov (United States)

Stork, Christopher L.; Brewer, Luke N.

2012-10-02

Large data sets are analyzed by hierarchical clustering using correlation as a similarity measure. This provides results that are superior to those obtained using a Euclidean distance similarity measure. A spatial continuity constraint may be applied in hierarchical clustering analysis of images.

Portfolio Evaluation Based on Efficient Frontier Superiority Using Center of Gravity

Directory of Open Access Journals (Sweden)

Omar Samat

2010-01-01

Full Text Available Investing in portfolio of assets is the best way to reduce the investment risk. The most desired portfolio can be obtained when investors chose to invest in the portfolios that lay on the portfolio’s efficient frontier. However, the superiorities of the portfolios are difficult to differentiate especially when the efficient frontier curves are overlapping. This paper proposed the portfolio’s efficient frontier center of gravity (CoG and Euclidean distance to identify its superiority. A sample of 49 stocks of large-cap and small-cap were used to construct two hypothetical portfolios and its efficient frontiers. The Euclidean distance showed that the large-cap portfolio is superior and having wider feasible solutions compared to the small-cap portfolio. The results of new tool introduced are consistent with the conventional methods. Here the theoretical and practical implications are provided in light of the findings.

Distancing from experienced self: how global-versus-local perception affects estimation of psychological distance.

Science.gov (United States)

Liberman, Nira; Förster, Jens

2009-08-01

In 4 studies, the authors examined the prediction derived from construal level theory (CLT) that higher level of perceptual construal would enhance estimated egocentric psychological distance. The authors primed participants with global perception, local perception, or both (the control condition). Relative to the control condition, global processing made participants estimate larger psychological distances in time (Study 1), space (Study 2), social distance (Study 3), and hypotheticality (Study 4). Local processing had the opposite effect. Consistent with CLT, all studies show that the effect of global-versus-local processing did emerge when participants estimated egocentric distances, which are distances from the experienced self in the here and now, but did not emerge with temporal distances not from now (Study 1), spatial distances not from here (Study 2), social distances not from the self (Study 3), or hypothetical events that did not involve altering an experienced reality (Study 4).