WorldWideScience

Sample records for two-dimensional pattern recognition

  1. REMOVAL OF SPECTRO-POLARIMETRIC FRINGES BY TWO-DIMENSIONAL PATTERN RECOGNITION

    Energy Technology Data Exchange (ETDEWEB)

    Casini, R.; Judge, P. G. [High Altitude Observatory, NCAR P.O. Box 3000, Boulder, CO 80307-3000 (United States); Schad, T. A. [Lunar and Planetary Laboratory, University of Arizona, Tucson, AZ 85721 (United States)

    2012-09-10

    We present a pattern-recognition-based approach to the problem of the removal of polarized fringes from spectro-polarimetric data. We demonstrate that two-dimensional principal component analysis can be trained on a given spectro-polarimetric map in order to identify and isolate fringe structures from the spectra. This allows us, in principle, to reconstruct the data without the fringe component, providing an effective and clean solution to the problem. The results presented in this paper point in the direction of revising the way that science and calibration data should be planned for a typical spectro-polarimetric observing run.

  2. Testing of hypothesis of two-dimensional random variables independence on the basis of algorithm of pattern recognition

    Science.gov (United States)

    Lapko, A. V.; Lapko, V. A.; Yuronen, E. A.

    2016-11-01

    The new technique of testing of hypothesis of random variables independence is offered. Its basis is made by nonparametric algorithm of pattern recognition. The considered technique doesn't demand sampling of area of values of random variables.

  3. FACE RECOGNITION USING TWO DIMENSIONAL LAPLACIAN EIGENMAP

    Institute of Scientific and Technical Information of China (English)

    Chen Jiangfeng; Yuan Baozong; Pei Bingnan

    2008-01-01

    Recently,some research efforts have shown that face images possibly reside on a nonlinear sub-manifold. Though Laplacianfaces method considered the manifold structures of the face images,it has limits to solve face recognition problem. This paper proposes a new feature extraction method,Two Dimensional Laplacian EigenMap (2DLEM),which especially considers the manifold structures of the face images,and extracts the proper features from face image matrix directly by using a linear transformation. As opposed to Laplacianfaces,2DLEM extracts features directly from 2D images without a vectorization preprocessing. To test 2DLEM and evaluate its performance,a series of ex-periments are performed on the ORL database and the Yale database. Moreover,several experiments are performed to compare the performance of three 2D methods. The experiments show that 2DLEM achieves the best performance.

  4. Two dimensional convolute integers for machine vision and image recognition

    Science.gov (United States)

    Edwards, Thomas R.

    1988-01-01

    Machine vision and image recognition require sophisticated image processing prior to the application of Artificial Intelligence. Two Dimensional Convolute Integer Technology is an innovative mathematical approach for addressing machine vision and image recognition. This new technology generates a family of digital operators for addressing optical images and related two dimensional data sets. The operators are regression generated, integer valued, zero phase shifting, convoluting, frequency sensitive, two dimensional low pass, high pass and band pass filters that are mathematically equivalent to surface fitted partial derivatives. These operators are applied non-recursively either as classical convolutions (replacement point values), interstitial point generators (bandwidth broadening or resolution enhancement), or as missing value calculators (compensation for dead array element values). These operators show frequency sensitive feature selection scale invariant properties. Such tasks as boundary/edge enhancement and noise or small size pixel disturbance removal can readily be accomplished. For feature selection tight band pass operators are essential. Results from test cases are given.

  5. Real-time comparison of conventional direct control and pattern recognition myoelectric control in a two-dimensional Fitts' law style test.

    Science.gov (United States)

    Wurth, Sophie M; Hargrove, Levi J

    2013-01-01

    Few studies have directly compared real-time control performance of pattern recognition to direct control for the next generation of myoelectric controlled upper limb prostheses. Many different implementations of pattern recognition control have been proposed, with minor differentiations in the feature sets and classifiers. An objective and generalizable evaluation tool quantifying the control performance, other than classification accuracy, is needed. This paper used the implementation of such a tool through the design of a target acquisition test, similar to a Fitts' law test, relating movement time of the target acquisition to the difficulty of the target, for a given control strategy. Performance metrics such as throughput (bits/sec), completion rate (%) and path efficiency (%) allow for a complete evaluation of the described strategies. We compared direct control and pattern recognition control with the proposed test and found that 1) the test was valid for control system evaluation by following Fitts' law with high coefficients of determination for both types of control and 2) that pattern recognition significantly outperformed direct control in throughput with similar completion rates and path efficiencies. In this framework, the present pilot study supports pattern recognition as a promising strategy and forms a basis for the development of a general and objective tool for the performance evaluation of upper limb control strategies.

  6. Gesture Recognition Using Character Recognition Techniques on Two-dimensional Eigenspace

    OpenAIRE

    大野, 宏; 山本, 正信; Ohno, Hiroshi; Yamamoto, Masanobu

    1999-01-01

    This paper describes a novel method for gesture recognition using character recognition techniques on two-dimensional eigenspace. An image-based approach can capture human body poses in 3D motion from multiple image sequences. The sequence of poses can be reduced into a trajectory on the two-dimensional eigenspace with preserving the main features in gesture, so that the gesture recognition equals the character recognition. Experiments for the gesture recognition using some character recognit...

  7. Two dimensional discriminant neighborhood preserving embedding in face recognition

    Science.gov (United States)

    Pang, Meng; Jiang, Jifeng; Lin, Chuang; Wang, Binghui

    2015-03-01

    One of the key issues of face recognition is to extract the features of face images. In this paper, we propose a novel method, named two-dimensional discriminant neighborhood preserving embedding (2DDNPE), for image feature extraction and face recognition. 2DDNPE benefits from four techniques, i.e., neighborhood preserving embedding (NPE), locality preserving projection (LPP), image based projection and Fisher criterion. Firstly, NPE and LPP are two popular manifold learning techniques which can optimally preserve the local geometry structures of the original samples from different angles. Secondly, image based projection enables us to directly extract the optimal projection vectors from twodimensional image matrices rather than vectors, which avoids the small sample size problem as well as reserves useful structural information embedded in the original images. Finally, the Fisher criterion applied in 2DDNPE can boost face recognition rates by minimizing the within-class distance, while maximizing the between-class distance. To evaluate the performance of 2DDNPE, several experiments are conducted on the ORL and Yale face datasets. The results corroborate that 2DDNPE outperforms the existing 1D feature extraction methods, such as NPE, LPP, LDA and PCA across all experiments with respect to recognition rate and training time. 2DDNPE also delivers consistently promising results compared with other competing 2D methods such as 2DNPP, 2DLPP, 2DLDA and 2DPCA.

  8. Pattern recognition

    CERN Document Server

    Theodoridis, Sergios

    2003-01-01

    Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. Patter Recognition, 2e covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to ""learn"" -and enhances student motivation by approaching pattern recognition from the designer's point of view. A direct result of more than 10

  9. RESEARCH ON TWO-DIMENSIONAL LDA FOR FACE RECOGNITION

    Institute of Scientific and Technical Information of China (English)

    Han Ke; Zhu Xiuchang

    2006-01-01

    The letter presents an improved two-dimensional linear discriminant analysis method for feature extraction. Compared with the current two-dimensional methods for feature extraction, the improved two-dimensional linear discriminant analysis method makes full use of not only the row and the column direction information of face images but also the discriminant information among different classes. The method is evaluated using the Nanjing University of Science and Technology (NUST) 603 face database and the Aleix Martinez and Robert Benavente (AR) face database. Experimental results show that the method in the letter is feasible and effective.

  10. Use of Comprehensive Two-Dimensional Gas Chromatography with Time-of-Flight Mass Spectrometric Detection and Random Forest Pattern Recognition Techniques for Classifying Chemical Threat Agents and Detecting Chemical Attribution Signatures.

    Science.gov (United States)

    Strozier, Erich D; Mooney, Douglas D; Friedenberg, David A; Klupinski, Theodore P; Triplett, Cheryl A

    2016-07-19

    In this proof of concept study, chemical threat agent (CTA) samples were classified to their sources with accuracies of 87-100% by applying a random forest statistical pattern recognition technique to analytical data acquired by comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometric detection (GC × GC-TOFMS). Three organophosphate pesticides, chlorpyrifos, dichlorvos, and dicrotophos, were used as the model CTAs, with data collected for 4-6 sources per CTA and 7-10 replicate analyses per source. The analytical data were also evaluated to determine tentatively identified chemical attribution signatures for the CTAs by comparing samples from different sources according to either the presence/absence of peaks or the relative responses of peaks. These results demonstrate that GC × GC-TOFMS analysis in combination with a random forest technique can be useful in sample classification and signature identification for pesticides. Furthermore, the results suggest that this combination of analytical chemistry and statistical approaches can be applied to forensic analysis of other chemicals for similar purposes.

  11. Two-dimensional spatial patterning in developmental systems.

    Science.gov (United States)

    Torii, Keiko U

    2012-08-01

    Multicellular organisms produce complex tissues with specialized cell types. During animal development, numerous cell-cell interactions shape tissue patterning through mechanisms involving contact-dependent cell migration and ligand-receptor-mediated lateral inhibition. Owing to the presence of cell walls, plant cells neither migrate nor undergo apoptosis as a means to correct for mis-specified cells. How can plants generate functional tissue patterns? This review aims to deduce fundamental principles of pattern formation through examining two-dimensional (2-D) spatial tissue patterning in plants and animals. Turing's mathematical framework will be introduced and applied to classic examples of de novo 2-D patterning in both animal and plant systems. By comparing their regulatory circuits, new insights into the similarities and differences of the basic principles governing tissue patterning will be discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.

  12. Quantifying leaf venation patterns: two-dimensional maps.

    Science.gov (United States)

    Rolland-Lagan, Anne-Gaëlle; Amin, Mira; Pakulska, Malgosia

    2009-01-01

    The leaf vasculature plays crucial roles in transport and mechanical support. Understanding how vein patterns develop and what underlies pattern variation between species has many implications from both physiological and evolutionary perspectives. We developed a method for extracting spatial vein pattern data from leaf images, such as vein densities and also the sizes and shapes of the vein reticulations. We used this method to quantify leaf venation patterns of the first rosette leaf of Arabidopsis thaliana throughout a series of developmental stages. In particular, we characterized the size and shape of vein network areoles (loops), which enlarge and are split by new veins as a leaf develops. Pattern parameters varied in time and space. In particular, we observed a distal to proximal gradient in loop shape (length/width ratio) which varied over time, and a margin-to-center gradient in loop sizes. Quantitative analyses of vein patterns at the tissue level provide a two-way link between theoretical models of patterning and molecular experimental work to further explore patterning mechanisms during development. Such analyses could also be used to investigate the effect of environmental factors on vein patterns, or to compare venation patterns from different species for evolutionary studies. The method also provides a framework for gathering and overlaying two-dimensional maps of point, line and surface morphological data.

  13. Pattern Coarsening in a Two Dimensional Hexagonal System

    Science.gov (United States)

    Chaikin, Paul

    2008-03-01

    We have been studying the ordering, annealing, coarsening and alignment of two dimensional periodically ordered structures in thin films of diblock copolymers*. Coarsening by dislocation and disclination annihilation is clearly observed in AFM studies of monolayer films of cylindrical patterns with a time dependence given by t^α, with α about 1/4. However in hexagonal structures the mechanism is less well defined and appears to involve the collapse of small grains entrained in the grain boundaries of larger domains. Remarkably the exponent of α about 1/4 remains. We also report on shear aligned samples and samples quenched in a gradient after alignment. * Harrison C, Angelescu DE, Trawick M, Cheng ZD, Huse DA, Chaikin PM, Vega DA, Sebastian JM, Register RA, Adamson DH, EUROPHYSICS LETTERS 67 800-806 (2004)

  14. Wetting of two-dimensional physically patterned surfaces

    Science.gov (United States)

    Bell, Michael Scott

    An understanding of wetting phenomena is important, in part, due to the many practical applications of controlled wetting. Some of the most exciting applications involve superhydrophobic surfaces, on which water droplets exhibit contact angles larger than 150° and contact angle hysteresis less than 10°. These surfaces are notable for their low-drag, antifouling, and self-cleaning properties, among others. Wetting is known to be affected by both the chemistry and the physical patterning of a surface, with the chemistry affecting what is called the intrinsic contact angle, which is the contact angle displayed by a droplet on a smooth flat surface made of the given material. To date, the largest intrinsic contact angle observed for any material is only about 120°, which does not confer superhydrophobicity. Thus, physical patterning is a crucial component of any superhydrophobic surface. Interestingly, many natural examples of superhydrophobic surfaces exist, with one of the most notable being the lotus leaf. In designing such surfaces, scientists have turned to the natural examples for inspiration, and have found that most natural examples have multiple (usually two) scales of roughness, commonly referred to as hierarchical roughness. Though hierarchical roughness is ubiquitous in the superhydrophobic surfaces of the natural world, its precise role in conferring superhydrophobicity has so far remained elusive. In this work, we develop a thermodynamic model to study the wetting of two-dimensional physically patterned surfaces. Past models that have been developed for this purpose often make several assumptions: the drop must be much larger than the surface features while simultaneously being small enough that the effects of gravity are negligible. Many of these models ultimately rely on the older Cassie and Wenzel models, which themselves make assumptions about the drop size relative to the surface features--namely that the drop is again much larger than the surface

  15. Jamming patterns in a two-dimensional hopper

    Indian Academy of Sciences (India)

    Kiwing To

    2005-06-01

    We report experimental studies of jamming phenomenon of monodisperse metal disks falling through a two-dimensional hopper when the hopper opening is larger than three times the size of the disks. For each jamming event, the configuration of the arch formed at the hopper opening is studied. The cumulative distribution functions () for hoppers of opening size d are measured. (Here is the horizontal component of the arch vector, which is defined as the displacement vector from the center of the first disk to the center of the last disk in the arch.) We found that the distribution of () can be collasped into a master curve () = ()() that decays exponentially for > 4. The scaling factor () is a decreasing function of d and is approximately proportional to the jamming probability.

  16. Fabrication of two-dimensional micro patterns for adaptive optics by using laser interference lithography

    Science.gov (United States)

    Li, Xinghui; Cai, Yindi; Aihara, Ryo; Shimizu, Yuki; Ito, So; Gao, Wei

    2015-07-01

    This paper presents a fabrication method of two-dimensional micro patterns for adaptive optics with a micrometric or sub-micrometric period to be used for fabrication of micro lens array or two-dimensional diffraction gratings. A multibeam two-axis Lloyd's mirror interferometer is employed to carry out laser interference lithography for the fabrication of two-dimensional grating structures. In the proposed instrument, the optical setup consists of a light source providing a laser beam, a multi-beam generator, two plane mirrors to generate a two-dimensional XY interference pattern and a substrate on which the XY interference pattern is to be exposed. In this paper, pattern exposure tests are carried out by the developed optical configuration optimized by computer simulations. Some experimental results of the XY pattern fabrication will be reported.

  17. Two-dimensional maximum local variation based on image euclidean distance for face recognition.

    Science.gov (United States)

    Gao, Quanxue; Gao, Feifei; Zhang, Hailin; Hao, Xiu-Juan; Wang, Xiaogang

    2013-10-01

    Manifold learning concerns the local manifold structure of high dimensional data, and many related algorithms are developed to improve image classification performance. None of them, however, consider both the relationships among pixels in images and the geometrical properties of various images during learning the reduced space. In this paper, we propose a linear approach, called two-dimensional maximum local variation (2DMLV), for face recognition. In 2DMLV, we encode the relationships among pixels in images using the image Euclidean distance instead of conventional Euclidean distance in estimating the variation of values of images, and then incorporate the local variation, which characterizes the diversity of images and discriminating information, into the objective function of dimensionality reduction. Extensive experiments demonstrate the effectiveness of our approach.

  18. Patterning two-dimensional free-standing surfaces with mesoporous conducting polymers

    NARCIS (Netherlands)

    Liu, Shaohua; Gordiichuk, Pavlo; Wu, Zhong-Shuai; Liu, Zhaoyang; Wei, Wei; Wagner, Manfred; Mohamed-Noriega, Nasser; Wu, Dongqing; Mai, Yiyong; Herrmann, Andreas; Müllen, Klaus; Feng, Xinliang

    2015-01-01

    The ability to pattern functional moieties with well-defined architectures is highly important in material science, nanotechnology and bioengineering. Although two-dimensional surfaces can serve as attractive platforms, direct patterning them in solution with regular arrays remains a major challenge

  19. Applications of Barcode Images by Enhancing the Two-Dimensional Recognition Rate

    Directory of Open Access Journals (Sweden)

    Kun-Hsien Lin

    2012-07-01

    Full Text Available The paper not only proposed the latest Two-Dimensional Barcodes Image-processing Module, but also captured the smallest camera screens (320 240 with different focal distances and tried to find out “Finder Pattern” for positioning images. Further, use CROBU (Conversion Ratio of Basic Unit the thesis proposed to convert 2-D barcodes into 1-pixel ratio to match images before judging recognition rate of 2-D barcodes through matching. Normally speaking, 2-D barcodes are deciphered and recognized by software while the thesis recognizes 2-D barcodes and enhances implementation speed up to 10-cm accurate max. using image matching. The 2-D barcodes image-processing module the thesis proposed does capture and standardize image with complicated background or raw edge, which enhances 2-D barcodes recognition rate. The main point of this study is to construct a platform to manage or suggest nutrients human body needs. The Quick Response Code image of 2-D barcodes represents vitamin and calories information. 2-D barcodes taken instantly by MATLAB and CCD camera can be used to list nutrients from foods you eat recently and suggest what else you should eat for the purpose of health management.

  20. A pattern-matching algorithm for two-dimensional coordinate lists. [for stellar positions

    Science.gov (United States)

    Groth, E. J.

    1986-01-01

    A pattern-matching algorithm for two-dimensional coordinate lists is described. The algorithm matches pairs of coordinates in two lists based on the triangles that can be formed from triplets of points in each list. The algorithm is insensitive to coordinate translation, rotation, magnification, or inversion and can tolerate random errors or distortions.

  1. Pattern recognition & machine learning

    CERN Document Server

    Anzai, Y

    1992-01-01

    This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.

  2. Statistical Pattern Recognition

    CERN Document Server

    Webb, Andrew R

    2011-01-01

    Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions.  It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields,

  3. Fractal characteristics of far-field diffraction patterns for two-dimensional Thue-Morse quasicrystals

    Institute of Scientific and Technical Information of China (English)

    YANG Ming-yang; ZHOU Jun; L Petti; S De Nicola; P Mormile

    2011-01-01

    We report a numerical method to analyze the fractal characteristics of far-field diffraction patterns for two-dimensional Thue-Morse(2-D TM) structures.The far-field diffraction patterns of the 2-D TM structures can be obtained by the numerical method,and they have a good agreement with the experimental ones.The analysis shows that the fractal characteristics of far-field diffraction patterns for the 2-D TM structures are determined by the inflation rule,which have potential applications in the design of optical diffraction devices.

  4. Three-dimensional volume containing multiple two-dimensional information patterns

    Science.gov (United States)

    Nakayama, Hirotaka; Shiraki, Atsushi; Hirayama, Ryuji; Masuda, Nobuyuki; Shimobaba, Tomoyoshi; Ito, Tomoyoshi

    2013-06-01

    We have developed an algorithm for recording multiple gradated two-dimensional projection patterns in a single three-dimensional object. When a single pattern is observed, information from the other patterns can be treated as background noise. The proposed algorithm has two important features: the number of patterns that can be recorded is theoretically infinite and no meaningful information can be seen outside of the projection directions. We confirmed the effectiveness of the proposed algorithm by performing numerical simulations of two laser crystals: an octagonal prism that contained four patterns in four projection directions and a dodecahedron that contained six patterns in six directions. We also fabricated and demonstrated an actual prototype laser crystal from a glass cube engraved by a laser beam. This algorithm has applications in various fields, including media art, digital signage, and encryption technology.

  5. Smart templates for peak pattern matching with comprehensive two-dimensional liquid chromatography.

    Science.gov (United States)

    Reichenbach, Stephen E; Carr, Peter W; Stoll, Dwight R; Tao, Qingping

    2009-04-17

    Comprehensive two-dimensional liquid chromatography (LCxLC) generates information-rich but complex peak patterns that require automated processing for rapid chemical identification and classification. This paper describes a powerful approach and specific methods for peak pattern matching to identify and classify constituent peaks in data from LCxLC and other multidimensional chemical separations. The approach records a prototypical pattern of peaks with retention times and associated metadata, such as chemical identities and classes, in a template. Then, the template pattern is matched to the detected peaks in subsequent data and the metadata are copied from the template to identify and classify the matched peaks. Smart Templates employ rule-based constraints (e.g., multispectral matching) to increase matching accuracy. Experimental results demonstrate Smart Templates, with the combination of retention-time pattern matching and multispectral constraints, are accurate and robust with respect to changes in peak patterns associated with variable chromatographic conditions.

  6. Dynamic patterns in a two-dimensional neural field with refractoriness.

    Science.gov (United States)

    Qi, Yang; Gong, Pulin

    2015-08-01

    The formation of dynamic patterns such as localized propagating waves is a fascinating self-organizing phenomenon that happens in a wide range of spatially extended systems including neural systems, in which they might play important functional roles. Here we derive a type of two-dimensional neural-field model with refractoriness to study the formation mechanism of localized waves. After comparing this model with existing neural-field models, we show that it is able to generate a variety of localized patterns, including stationary bumps, localized waves rotating along a circular path, and localized waves with longer-range propagation. We construct explicit bump solutions for the two-dimensional neural field and conduct a linear stability analysis on how a stationary bump transitions to a propagating wave under different spatial eigenmode perturbations. The neural-field model is then partially solved in a comoving frame to obtain localized wave solutions, whose spatial profiles are in good agreement with those obtained from simulations. We demonstrate that when there are multiple such propagating waves, they exhibit rich propagation dynamics, including propagation along periodically oscillating and irregular trajectories; these propagation dynamics are quantitatively characterized. In addition, we show that these waves can have repulsive or merging collisions, depending on their collision angles and the refractoriness parameter. Due to its analytical tractability, the two-dimensional neural-field model provides a modeling framework for studying localized propagating waves and their interactions.

  7. Steering light into logic patterns with two-dimensional cascaded multimode waveguide

    Institute of Scientific and Technical Information of China (English)

    Zhou Hai-Feng; Yang Jian-Yi; Wang Ming-Hua; Jiang Xiao-Qing

    2007-01-01

    Steering light into logic patterns with two-dimensional cascaded multimode waveguide is demonstrated.By employing the imaging properties of 2D multimode interference (MMI) and partial phase modulation method,the design ideas and the implementing methods of the 2(2×2) bits type spatial logic steering are discussed;therefore the structure of logical pattern is proposed.Numerical simulation is carried out to verify the design in detail by using the beam propagation method.It is expected to realize logic coders by using the integrated optical methods and exploit their potential applications in the field of optical logic.

  8. Intrinsically patterned two-dimensional materials for selective adsorption of molecules and nanoclusters

    Science.gov (United States)

    Lin, X.; Lu, J. C.; Shao, Y.; Zhang, Y. Y.; Wu, X.; Pan, J. B.; Gao, L.; Zhu, S. Y.; Qian, K.; Zhang, Y. F.; Bao, D. L.; Li, L. F.; Wang, Y. Q.; Liu, Z. L.; Sun, J. T.; Lei, T.; Liu, C.; Wang, J. O.; Ibrahim, K.; Leonard, D. N.; Zhou, W.; Guo, H. M.; Wang, Y. L.; Du, S. X.; Pantelides, S. T.; Gao, H.-J.

    2017-07-01

    Two-dimensional (2D) materials have been studied extensively as monolayers, vertical or lateral heterostructures. To achieve functionalization, monolayers are often patterned using soft lithography and selectively decorated with molecules. Here we demonstrate the growth of a family of 2D materials that are intrinsically patterned. We demonstrate that a monolayer of PtSe2 can be grown on a Pt substrate in the form of a triangular pattern of alternating 1T and 1H phases. Moreover, we show that, in a monolayer of CuSe grown on a Cu substrate, strain relaxation leads to periodic patterns of triangular nanopores with uniform size. Adsorption of different species at preferred pattern sites is also achieved, demonstrating that these materials can serve as templates for selective self-assembly of molecules or nanoclusters, as well as for the functionalization of the same substrate with two different species.

  9. Two-dimensional Morlet wavelet transform and its application to wave recognition methodology of automatically extracting two-dimensional wave packets from lidar observations in Antarctica

    Science.gov (United States)

    Chen, Cao; Chu, Xinzhao

    2017-09-01

    Waves in the atmosphere and ocean are inherently intermittent, with amplitudes, frequencies, or wavelengths varying in time and space. Most waves exhibit wave packet-like properties, propagate at oblique angles, and are often observed in two-dimensional (2-D) datasets. These features make the wavelet transforms, especially the 2-D wavelet approach, more appealing than the traditional windowed Fourier analysis, because the former allows adaptive time-frequency window width (i.e., automatically narrowing window size at high frequencies and widening at low frequencies), while the latter uses a fixed envelope function. This study establishes the mathematical formalism of modified 1-D and 2-D Morlet wavelet transforms, ensuring that the power of the wavelet transform in the frequency/wavenumber domain is equivalent to the mean power of its counterpart in the time/space domain. Consequently, the modified wavelet transforms eliminate the bias against high-frequency/small-scale waves in the conventional wavelet methods and many existing codes. Based on the modified 2-D Morlet wavelet transform, we put forward a wave recognition methodology that automatically identifies and extracts 2-D quasi-monochromatic wave packets and then derives their wave properties including wave periods, wavelengths, phase speeds, and time/space spans. A step-by-step demonstration of this methodology is given on analyzing the lidar data taken during 28-30 June 2014 at McMurdo, Antarctica. The newly developed wave recognition methodology is then applied to two more lidar observations in May and July 2014, to analyze the recently discovered persistent gravity waves in Antarctica. The decomposed inertia-gravity wave characteristics are consistent with the conclusion in Chen et al. (2016a) that the 3-10 h waves are persistent and dominant, and exhibit lifetimes of multiple days. They have vertical wavelengths of 20-30 km, vertical phase speeds of 0.5-2 m/s, and horizontal wavelengths up to several

  10. Optical gaps, mode patterns and dipole radiation in two-dimensional aperiodic photonic structures

    Science.gov (United States)

    Boriskina, Svetlana V.; Gopinath, Ashwin; Negro, Luca Dal

    2009-05-01

    Based on the rigorous generalized Mie theory solution of Maxwell's equations for dielectric cylinders we theoretically investigate the optical properties of two-dimensional deterministic structures based on the Fibonacci, Thue-Morse and Rudin-Shapiro aperiodic sequences. In particular, we investigate bandgap formation and mode localization properties in aperiodic photonic structures based on the accurate calculation of their local density of states (LDOS). In addition, we explore the potential of photonic structures based on aperiodic order for the engineering of radiative rates and emission patterns in erbium-doped silicon-rich nitride photonic structures.

  11. Structural information in two-dimensional patterns: entropy convergence and excess entropy.

    Science.gov (United States)

    Feldman, David P; Crutchfield, James P

    2003-05-01

    We develop information-theoretic measures of spatial structure and pattern in more than one dimension. As is well known, the entropy density of a two-dimensional configuration can be efficiently and accurately estimated via a converging sequence of conditional entropies. We show that the manner in which these conditional entropies converge to their asymptotic value serves as a measure of global correlation and structure for spatial systems in any dimension. We compare and contrast entropy convergence with mutual-information and structure-factor techniques for quantifying and detecting spatial structure.

  12. Dislocation patterning in a two-dimensional continuum theory of dislocations

    Science.gov (United States)

    Groma, István; Zaiser, Michael; Ispánovity, Péter Dusán

    2016-06-01

    Understanding the spontaneous emergence of dislocation patterns during plastic deformation is a long standing challenge in dislocation theory. During the past decades several phenomenological continuum models of dislocation patterning were proposed, but few of them (if any) are derived from microscopic considerations through systematic and controlled averaging procedures. In this paper we present a two-dimensional continuum theory that is obtained by systematic averaging of the equations of motion of discrete dislocations. It is shown that in the evolution equations of the dislocation densities diffusionlike terms neglected in earlier considerations play a crucial role in the length scale selection of the dislocation density fluctuations. It is also shown that the formulated continuum theory can be derived from an averaged energy functional using the framework of phase field theories. However, in order to account for the flow stress one has in that case to introduce a nontrivial dislocation mobility function, which proves to be crucial for the instability leading to patterning.

  13. New algorithmic approaches to protein spot detection and pattern matching in two-dimensional electrophoresis gel databases.

    Science.gov (United States)

    Pleissner, K P; Hoffmann, F; Kriegel, K; Wenk, C; Wegner, S; Sahlström, A; Oswald, H; Alt, H; Fleck, E

    1999-01-01

    Protein spot identification in two-dimensional electrophoresis gels can be supported by the comparison of gel images accessible in different World Wide Web two-dimensional electrophoresis (2-DE) gel protein databases. The comparison may be performed either by visual cross-matching between gel images or by automatic recognition of similar protein spot patterns. A prerequisite for the automatic point pattern matching approach is the detection of protein spots yielding the x(s),y(s) coordinates and integrated spot intensities i(s). For this purpose an algorithm is developed based on a combination of hierarchical watershed transformation and feature extraction methods. This approach reduces the strong over-segmentation of spot regions normally produced by watershed transformation. Measures for the ellipticity and curvature are determined as features of spot regions. The resulting spot lists containing x(s),y(s),i(s)-triplets are calculated for a source as well as for a target gel image accessible in 2-DE gel protein databases. After spot detection a matching procedure is applied. Both the matching of a local pattern vs. a full 2-DE gel image and the global matching between full images are discussed. Preset slope and length tolerances of pattern edges serve as matching criteria. The local matching algorithm relies on a data structure derived from the incremental Delaunay triangulation of a point set and a two-step hashing technique. For the incremental construction of triangles the spot intensities are considered in decreasing order. The algorithm needs neither landmarks nor an a priori image alignment. A graphical user interface for spot detection and gel matching is written in the Java programming language for the Internet. The software package called CAROL (http://gelmatching.inf.fu-berlin.de) is realized in a client-server architecture.

  14. Retrieving the size of particles with rough and complex surfaces from two-dimensional scattering patterns

    Science.gov (United States)

    Ulanowski, Z.; Hirst, E.; Kaye, P. H.; Greenaway, R.

    2012-12-01

    Scattered intensity measurement is a commonly used method for determining the size of small particles. However, it requires calibration and is subject to errors due to changes in incident irradiance or detector sensitivity. Analysis of two-dimensional scattering patterns offers an alternative approach. We test morphological image processing operations on patterns from a diverse range of particles with rough surfaces and/or complex structure, including mineral dust, spores, pollen, ice analogs and sphere clusters from 4 to 88 μm in size. It is found that the median surface area of intensity peaks is the most robust measure, and it is inversely proportional to particle size. The trend holds well for most particle types, as long as substantial roughness or complexity is present. One important application of this technique is the sizing of atmospheric particles, such as ice crystals.

  15. Two-dimensional surface river flow patterns measured with paired RiverSondes

    Science.gov (United States)

    Teague, C.C.; Barrick, D.E.; Lilleboe, P.M.; Cheng, R.T.

    2008-01-01

    Two RiverSondes were operated simultaneously in close proximity in order to provide a two-dimensional map of river surface velocity. The initial test was carried out at Threemile Slough in central California. The two radars were installed about 135 m apart on the same bank of the channel. Each radar used a 3-yagi antenna array and determined signal directions using direction finding. The slough is approximately 200 m wide, and each radar processed data out to about 300 m, with a range resolution of 15 m and an angular resolution of 1 degree. Overlapping radial vector data from the two radars were combined to produce total current vectors at a grid spacing of 10 m, with updates every 5 minutes. The river flow in the region, which has a maximum velocity of about 0.8 m/s, is tidally driven with flow reversals every 6 hours, and complex flow patterns were seen during flow reversal. The system performed well with minimal mutual interference. The ability to provide continuous, non-contact two-dimensional river surface flow measurements will be useful in several unique settings, such as studies of flow at river junctions where impacts to juvenile fish migration are significant. Additional field experiments are planned this year on the Sacramento River. ?? 2007 IEEE.

  16. Frequency-domain nonlinear optics in two-dimensionally patterned quasi-phase-matching media

    CERN Document Server

    Phillips, C R; Gallmann, L; Keller, U

    2015-01-01

    Advances in the amplification and manipulation of ultrashort laser pulses has led to revolutions in several areas. Examples include chirped pulse amplification for generating high peak-power lasers, power-scalable amplification techniques, pulse shaping via modulation of spatially-dispersed laser pulses, and efficient frequency-mixing in quasi-phase-matched nonlinear crystals to access new spectral regions. In this work, we introduce and demonstrate a new platform for nonlinear optics which has the potential to combine all of these separate functionalities (pulse amplification, frequency transfer, and pulse shaping) into a single monolithic device. Moreover, our approach simultaneously offers solutions to the performance-limiting issues in the conventionally-used techniques, and supports scaling in power and bandwidth of the laser source. The approach is based on two-dimensional patterning of quasi-phase-matching gratings combined with optical parametric interactions involving spatially dispersed laser pulses...

  17. Two-Dimensional River Flow Patterns Observed with a Pair of UHF Radar System

    Directory of Open Access Journals (Sweden)

    Yidong Hou

    2017-01-01

    Full Text Available A pair of ultrahigh-frequency (UHF radars system for measuring the two-dimensional river flow patterns is presented. The system consists of two all-digital UHF radars with exactly the same hardware structure, operating separately at 329–339 MHz and 341–351 MHz. The adoption of direct radio frequency (RF sampling technique and digital pulse compression simplifies the structure of radar system and eliminates the distortion introduced by the analog mixer, which improves the SNR and dynamic range of the radar. The field experiment was conducted at Hanjiang River, Hubei province, China. Over a period of several weeks, the radar-derived surface velocity has been very highly correlated with the measurements of EKZ-I, with a correlation coefficient of 0.958 and a mean square error of 0.084 m/s.

  18. Pattern recognition in bioinformatics.

    Science.gov (United States)

    de Ridder, Dick; de Ridder, Jeroen; Reinders, Marcel J T

    2013-09-01

    Pattern recognition is concerned with the development of systems that learn to solve a given problem using a set of example instances, each represented by a number of features. These problems include clustering, the grouping of similar instances; classification, the task of assigning a discrete label to a given instance; and dimensionality reduction, combining or selecting features to arrive at a more useful representation. The use of statistical pattern recognition algorithms in bioinformatics is pervasive. Classification and clustering are often applied to high-throughput measurement data arising from microarray, mass spectrometry and next-generation sequencing experiments for selecting markers, predicting phenotype and grouping objects or genes. Less explicitly, classification is at the core of a wide range of tools such as predictors of genes, protein function, functional or genetic interactions, etc., and used extensively in systems biology. A course on pattern recognition (or machine learning) should therefore be at the core of any bioinformatics education program. In this review, we discuss the main elements of a pattern recognition course, based on material developed for courses taught at the BSc, MSc and PhD levels to an audience of bioinformaticians, computer scientists and life scientists. We pay attention to common problems and pitfalls encountered in applications and in interpretation of the results obtained.

  19. Feminist Politics in the Age of Recognition: A Two-Dimensional Approach to Gender Justice

    Directory of Open Access Journals (Sweden)

    Nancy Fraser

    2007-03-01

    Full Text Available In the course of the last thirty years, feminist theories of gender have shifted from quasi-Marxist, labor-centered conceptions to putatively “post-Marxist”culture- and identity-based conceptions. Reflecting a broader political move from redistribution to recognition, this shift has been double-edged. On the one hand, it has broadened feminist politics to encompass legitimate issues of representation, identity, and difference. Yet, in the context of an ascendant neoliberalism, feminist struggles for recognition may be serving to less to enrich struggles for redistribution than to displace the latter. I aim to resist that trend. In this essay, I propose an analysis of gender that is broad enough to house the full range of feminist concerns, those central to the old socialist-feminism as well as those rooted in the cultural turn. I also propose a correspondingly broad conception of justice, capable of encompassing both distribution and recognition, and a non-identitarian account of recognition, capable of synergizing with redistribution. I conclude by examining some practical problems that arise when we try to envision institutional reforms that could redress gender maldistribution and gender misrecognition simultaneously.

  20. Evolution of self-organized two-dimensional patterns of nanoclusters through demixing

    Science.gov (United States)

    Choudhuri, Madhumita; Iyengar, A. N. Sekar; Datta, Alokmay; Janaki, M. S.

    2015-09-01

    A mixture of dodecanethiol-capped Au nanoparticles (AuNPs) and the amphiphilic fatty acid, stearic acid, spread as a monomolecular layer on water surface, is observed with Brewster angle microscopy (BAM) to form a two-dimensional network of AuNP clusters through demixing, at concentration of AuNPs by weight (ρ ¯)>10 % and the surface pressure (π )≥10 mN m-1 . For π =15 mN m-1 , the number of nodes (n ) remains unchanged till ˜2 hours and then changes over to a lower n state, where the pattern consists of almost perfect circles with greater in-plane thickness of the AuNP lamellae. For the higher n state the mean-square fluctuation of BAM intensity remains flat and then decays as f (ξ ) =ξ2 α with α ˜0.6 (correlated fluctuations) over the length scales of 400 μ m -6 μ m and below 6 μ m , respectively. For the lower n state the fluctuation decays almost over the entire length scale with α =0.3 , indicating emergence of aperiodicity from quasiperiodicity and a changeover to anticorrelated fluctuations. These patterns can be looked at as two distinct chaotic trajectories in the I -I' phase space of the system (I being the scattered light intensity at any position of the pattern and I' its gradient) with characteristic Lyapunov exponents.

  1. Two-dimensional pattern formation in ionic liquids confined between graphene walls.

    Science.gov (United States)

    Montes-Campos, Hadrián; Otero-Mato, José Manuel; Méndez-Morales, Trinidad; Cabeza, Oscar; Gallego, Luis J; Ciach, Alina; Varela, Luis M

    2017-09-20

    We perform molecular dynamics simulations of ionic liquids confined between graphene walls under a large variety of conditions (pure ionic liquids, mixtures with water and alcohols, mixtures with lithium salts and defective graphene walls). Our results show that the formation of striped and hexagonal patterns in the Stern layer can be considered as a general feature of ionic liquids at electrochemical interfaces, the transition between patterns being controlled by the net balance of charge in the innermost layer of adsorbed molecules. This explains previously reported experimental and computational results and, for the first time, why these pattern changes are triggered by any perturbation of the charge density at the innermost layer of the electric double layer (voltage and composition changes, and vacancies at the electrode walls, among others), which may help tuning electrode-ionic liquid interfaces. Using Monte Carlo simulations we show that such structures can be reproduced by a simple two-dimensional lattice model with only nearest-neighbour interactions, governed by highly screened ionic interactions and short-range and excluded volume interactions. We also show that the results of our simulations are consistent with those inferred from the Landau-Brazovskii theory of pattern formation in self-assembling systems. The presence of these patterns at the ionic liquid graphene-electrode interfaces may have a strong impact on the process of ionic transfer from the bulk mixtures to the electrodes, on the differential capacitance of the electrode-electrolyte double layer or on the rates of redox reactions at the electrodes, among other physicochemical properties, and is therefore an effect of great technological interest.

  2. KP solitons and the Grassmannians combinatorics and geometry of two-dimensional wave patterns

    CERN Document Server

    Kodama, Yuji

    2017-01-01

    This is the first book to treat combinatorial and geometric aspects of two-dimensional solitons. Based on recent research by the author and his collaborators, the book presents new developments focused on an interplay between the theory of solitons and the combinatorics of finite-dimensional Grassmannians, in particular, the totally nonnegative (TNN) parts of the Grassmannians. The book begins with a brief introduction to the theory of the Kadomtsev–Petviashvili (KP) equation and its soliton solutions, called the KP solitons. Owing to the nonlinearity in the KP equation, the KP solitons form very complex but interesting web-like patterns in two dimensions. These patterns are referred to as soliton graphs. The main aim of the book is to investigate the detailed structure of the soliton graphs and to classify these graphs. It turns out that the problem has an intimate connection with the study of the TNN part of the Grassmannians. The book also provides an elementary introduction to the recent development of ...

  3. Pattern Recognition Control Design

    Science.gov (United States)

    Gambone, Elisabeth A.

    2018-01-01

    Spacecraft control algorithms must know the expected vehicle response to any command to the available control effectors, such as reaction thrusters or torque devices. Spacecraft control system design approaches have traditionally relied on the estimated vehicle mass properties to determine the desired force and moment, as well as knowledge of the effector performance to efficiently control the spacecraft. A pattern recognition approach was used to investigate the relationship between the control effector commands and spacecraft responses. Instead of supplying the approximated vehicle properties and the thruster performance characteristics, a database of information relating the thruster ring commands and the desired vehicle response was used for closed-loop control. A Monte Carlo simulation data set of the spacecraft dynamic response to effector commands was analyzed to establish the influence a command has on the behavior of the spacecraft. A tool developed at NASA Johnson Space Center to analyze flight dynamics Monte Carlo data sets through pattern recognition methods was used to perform this analysis. Once a comprehensive data set relating spacecraft responses with commands was established, it was used in place of traditional control methods and gains set. This pattern recognition approach was compared with traditional control algorithms to determine the potential benefits and uses.

  4. Dual-RiverSonde measurements of two-dimensional river flow patterns

    Science.gov (United States)

    Teague, C.C.; Barrick, D.E.; Lilleboe, P.M.; Cheng, R.T.; Stumpner, P.; Burau, J.R.

    2008-01-01

    Two-dimensional river flow patterns have been measured using a pair of RiverSondes in two experiments in the Sacramento-San Joaquin River Delta system of central California during April and October 2007. An experiment was conducted at Walnut Grove, California in order to explore the use of dual RiverSondes to measure flow patterns at a location which is important in the study of juvenile fish migration. The data available during the first experiment were limited by low wind, so a second experiment was conducted at Threemile Slough where wind conditions and surface turbulence historically have resulted in abundant data. Both experiments included ADCP near-surface velocity measurements from either manned or unmanned boats. Both experiments showed good comparisons between the RiverSonde and ADCP measurements. The flow conditions at both locations are dominated by tidal effects, with partial flow reversal at Walnut Grove and complete flow reversal at Threemile Slough. Both systems showed complex flow patterns during the flow reversals. Quantitative comparisons between the RiverSondes and an ADCP on a manned boat at Walnut Grove showed mean differences of 4.5 cm/s in the u (eastward) and 7.6 cm/s in the v (northward) components, and RMS differences of 14.7 cm/s in the u component and 21.0 cm/s in the v component. Quantitative comparisons between the RiverSondes and ADCPs on autonomous survey vessels at Threemile Slough showed mean differences of 0.007 cm/s in the u component and 0.5 cm/s in the v component, and RMS differences of 7.9 cm/s in the u component and 13.5 cm/s in the v component after obvious outliers were removed. ?? 2008 IEEE.

  5. Symmetrical Two-Dimensional PCA with Image Measures in Face Recognition

    Directory of Open Access Journals (Sweden)

    Jicheng Meng

    2012-12-01

    Full Text Available In this paper, weextensively investigate symmetrical two‐dimensional principal component analysis (S2DPCA and introduce two image measures for S2DPCA‐based face recognition, volume measure (VM and subspace distance measure (SM. Although symmetrical features are an obviously but not absolutely facial characteristic, they have been successfully applied to PCA and 2DPCA. The paper gives detailed evidence that even and odd subspaces in S2DPCA are mutually orthogonal, and particularly that S2DPCA can be constructed using a quarter of the conventional S2DPCA even/odd covariance matrix. Based on these theories, we investigate the time and memory complexities of S2PDCA further, and find that S2DPCA can in fact be computed using a quarter of the time and memory compared to conventional S2DPCA. Finally, VM and SM are introduced to S2DPCA for final classification. Our experiments compare S2DPCA with 2DPCA on YALE, AR and FERET face databases, and the results indicate that S2DPCA+VM generally outperforms other algorithms.

  6. Grip-pattern recognition: Applied to a smart gun

    NARCIS (Netherlands)

    Shang, X.

    2008-01-01

    In our work the verification performance of a biometric recognition system based on grip patterns, as part of a smart gun for use by the police ocers, has been investigated. The biometric features are extracted from a two-dimensional pattern of the pressure, exerted on the grip of a gun by the hand

  7. Pattern formation and coarse-graining in two-dimensional colloids driven by multiaxial magnetic fields.

    Science.gov (United States)

    Müller, Kathrin; Osterman, Natan; Babič, Dušan; Likos, Christos N; Dobnikar, Jure; Nikoubashman, Arash

    2014-05-13

    We study the pattern formation in a two-dimensional system of superparamagnetic colloids interacting via spatially coherent induced interactions driven by an external precessing magnetic field. On the pair level, upon changing the opening angle of the external field, the interactions smoothly vary from purely repulsive (opening angle equal to zero) to purely attractive (time-averaged pair interactions at an opening angle of 90°). In the experiments, we observed ordered hexagonal crystals at the repulsive end and coarsening frothlike structures for purely attractive interactions. In both of these limiting cases, the dense colloidal systems can be sufficiently accurately described by assuming pairwise additivity of the interaction potentials. However, for a range of intermediate angles, pronounced many-body depolarization effects compete with the direct induced interactions, resulting in inherently anisotropic effective interactions. Under such conditions, we observed the decay of hexagonal order with the concomitant formation of short chains and percolated networks of chains coexisting with free colloids. In order to describe and investigate these systems theoretically, we developed a coarse-grained model of a binary mixture of patchy and nonpatchy particles with the ratio of patchy and nonpatchy colloids as the order parameter. Combining genetic algorithms with Monte Carlo simulations, we optimized the model parameters and quantitatively reproduced the experimentally observed sequence of colloidal structures. The results offer new insight into the anisotropy induced by the many-body effects. At the same time, they allow for a very efficient description of the system by means of a pairwise-additive Hamiltonian, whereupon the original, one-component system features a two-component mixture of isotropic and patchy colloids.

  8. Pattern transition, microstructure, and dynamics in a two-dimensional vibrofluidized granular bed

    Science.gov (United States)

    Ansari, Istafaul H.; Alam, Meheboob

    2016-05-01

    Experiments are conducted in a two-dimensional monolayer vibrofluidized bed of glass beads, with a goal to understand the transition scenario and the underlying microstructure and dynamics in different patterned states. At small shaking accelerations (Γ =A ω2/g convection" to "1-roll convection" and finally to a gas-like state. For a given length of the container, the coarsening of multiple convection rolls leading to the genesis of a "single-roll" structure (dubbed the multiroll transition) and its subsequent transition to a granular gas are two findings of this work. We show that the critical shaking intensity (ΓBBLS) for the BB→LS transition has a power-law dependence on the particle loading (F =h0/d , where h0 is the number of particle layers at rest and d is the particle diameter) and the shaking amplitude (A /d ). The characteristics of BB and LS states are studied by calculating (i) the coarse-grained density and temperature profiles and (ii) the pair correlation function. It is shown that while the contact network of particles in the BB state represents a hexagonal-packed structure, the contact network within the "floating cluster" of the LS resembles a liquid-like state. An unsteadiness of the Leidenfrost state has been uncovered wherein the interface (between the floating cluster and the dilute collisional layer underneath) and the top of the bed are found to oscillate sinusoidally, with the oscillation frequency closely matching the frequency of external shaking. Therefore, the granular Leidenfrost state is a period-1 wave as is the case for the BB state.

  9. PDF417码识别算法研究%Study on the Recognition Algorithms for Two-Dimensional Barcode

    Institute of Scientific and Technical Information of China (English)

    陈俊梅

    2015-01-01

    Along with the vigorous development of computer technology and signal processing technology,barcode,especially the two-dimensional barcode,is used more and more widely,in order to ensure the accuracy of the recognition of two-dimensional barcode,the recognition algorithms should be learned.Using an ordinary camera equipment, a PDF417 barcode image can be got with a lot of noise points,through the image processing which is realized by the MATLAB, the source code of the image can be got.During the process,different algorithms such as filtering , stratifing can be reduced to ensure the accuracy of the image decoding,and a series of problems which are caused by external disturbance such as image distortion,noise,motion artifacts can be reduced too.%随着计算机技术和信号处理技术的蓬勃发展,条形码尤其是二维条码在各个领域中的使用范围越来越广,为了保证对二维条码中所含信息识别的准确性,需要对条码的识别算法加以研究。本文以PDF417码为例,在普通的摄入环境下采集到干扰比较大的图像,利用MATLAB通过滤波、分层等算法对这样得到图像进行的一系列处理,最终得到图像的源代码。在处理过程中,保证了图像解码的准确性,减少了在普通摄入环境下可能产生的图像畸变、噪声干扰、运动伪影等干扰对条码识别的影响。

  10. Flow pattern transition accompanied with sudden growth of flow resistance in two-dimensional curvilinear viscoelastic flows

    OpenAIRE

    Yatou, Hiroki

    2010-01-01

    We find three types of steady solutions and remarkable flow pattern transitions between them in a two-dimensional wavy-walled channel for low to moderate Reynolds (Re) and Weissenberg (Wi) numbers using direct numerical simulations with spectral element method. The solutions are called "convective", "transition", and "elastic" in ascending order of Wi. In the convective region in the Re-Wi parameter space, the convective effect and the pressure gradient balance on average. As Wi increases, th...

  11. Pattern Recognition Theory of Mind

    OpenAIRE

    2009-01-01

    I propose that pattern recognition, memorization and processing are key concepts that can be a principle set for the theoretical modeling of the mind function. Most of the questions about the mind functioning can be answered by a descriptive modeling and definitions from these principles. An understandable consciousness definition can be drawn based on the assumption that a pattern recognition system can recognize its own patterns of activity. The principles, descriptive modeling and definiti...

  12. Two-dimensional patterning of thin coatings for the control of tissue outgrowth

    DEFF Research Database (Denmark)

    Thissen, H.; Johnson, G.; Hartley, P.G.

    2006-01-01

    were used to provide evidence of successful surface modifications. Adsorption of the extracellular matrix protein collagen I followed by tissue outgrowth experiments with bovine corneal epithelial tissue for up to 21 days showed that two-dimensional control over tissue outgrowth is achievable with our......Control of the precise location and extent of cellular attachment and proliferation, and of tissue outgrowth is important in a number of biomedical applications, including biomaterials and tissue engineered medical devices. Here we describe a method to control and direct the location and define...... boundaries of tissue growth on surfaces in two dimensions. The method relies on the generation of a spatially defined surface chemistry comprising protein adsorbing and non-adsorbing areas that allow control over the adsorption of cell-adhesive glycoproteins. Surface modification was carried out...

  13. Pattern Recognition by Combined Invariants

    Institute of Scientific and Technical Information of China (English)

    WANG Xiaohong; ZHAO Rongchun

    2001-01-01

    A feature-based recognition of objectsor patterns independent of their position, size, orien-tation and other variations has been the goal of muchrecent research. The existing approaches to invarianttwo-dimensional pattern recognition are useless whenpattern is blurred. In this paper, we present a novelpattern recognition system which can solve the prob-lem by using combined invariants as image features.The classification technique we choose for our systemis weighted normalized cross correlation. The mean ofthe intraclass standard deviations of the kth featureover the total number of prototypes for each class isused as a weighting factor during the classification pro-cess to improve recognition accuracy. The feasibilityof our pattern recognition system and the invarianceof the combined features with respect to translation,scaling, rotation and blurring are approved by numer-ical experiments on head images.

  14. Aerosol assisted fabrication of two dimensional ZnO island arrays and honeycomb patterns with identical lattice structures

    Directory of Open Access Journals (Sweden)

    Mitsuhiro Numata

    2010-11-01

    Full Text Available Two dimensional island arrays and honeycomb patterns consisting of ZnO nanocrystal clusters were fabricated on predefined TiO2 seed patterns prepared by vacuum free, aerosol assisted wet-chemical synthesis. The TiO2 seed patterns were prepared by applying an aerosol of a water soluble titanium complex on hexagonally close-packed polystyrene bead arrays for different lengths of time. Scanning electron microscopy revealed that a dot array grows into a honeycomb shape as increasing amounts of the precursor were deposited. ZnO nucleation on substrates with a dot array and honeycomb patterns resulted in the formation of two discrete patterns with contrasting fill fractions of the materials.

  15. Spontaneous assembly of chemically encoded two-dimensional coacervate droplet arrays by acoustic wave patterning

    Science.gov (United States)

    Tian, Liangfei; Martin, Nicolas; Bassindale, Philip G.; Patil, Avinash J.; Li, Mei; Barnes, Adrian; Drinkwater, Bruce W.; Mann, Stephen

    2016-10-01

    The spontaneous assembly of chemically encoded, molecularly crowded, water-rich micro-droplets into periodic defect-free two-dimensional arrays is achieved in aqueous media by a combination of an acoustic standing wave pressure field and in situ complex coacervation. Acoustically mediated coalescence of primary droplets generates single-droplet per node micro-arrays that exhibit variable surface-attachment properties, spontaneously uptake dyes, enzymes and particles, and display spatial and time-dependent fluorescence outputs when exposed to a reactant diffusion gradient. In addition, coacervate droplet arrays exhibiting dynamical behaviour and exchange of matter are prepared by inhibiting coalescence to produce acoustically trapped lattices of droplet clusters that display fast and reversible changes in shape and spatial configuration in direct response to modulations in the acoustic frequencies and fields. Our results offer a novel route to the design and construction of `water-in-water' micro-droplet arrays with controllable spatial organization, programmable signalling pathways and higher order collective behaviour.

  16. Probing of two-dimensional grid patterns by means of camera-based image processing

    Science.gov (United States)

    Schroeck, Martin; Doiron, Theodore D.

    2000-03-01

    Camera based probes and machine vision have found increased use in coordinate measuring machines over the past years and the calibration of artifacts for these probes has become an important task for NIST. Until recently these artifacts have been calibrated using one or two dimensional measuring machines with electro-optic microscopes or scanning devices as probes. These sensors evaluate only a small section of the edge of a grid mark, and irregularities in this particular spot from local deformations or contamination influence the measurement result. Since these measurements result in a single number based on the entire field of view, the influence of small irregularities are not easily detected. Since different probes scan different parts of the grid mark edge they may give systematically different positions of the mark. The conversion to video based sensors has allowed more flexibility it edge detection, although most instruments still use least squares fits as the substitute geometry of straight edges. This method is very susceptible to noise and edge irregularities. We present some experiments for finding the sub-pixel edge point locations and fitting the set of edge points to a line using a fairly simple least sum of absolute deviations fit. Data from a high accuracy 2D measuring machine is used to show the strengths of the algorithms.

  17. Pattern recognition and string matching

    CERN Document Server

    Cheng, Xiuzhen

    2002-01-01

    The research and development of pattern recognition have proven to be of importance in science, technology, and human activity. Many useful concepts and tools from different disciplines have been employed in pattern recognition. Among them is string matching, which receives much theoretical and practical attention. String matching is also an important topic in combinatorial optimization. This book is devoted to recent advances in pattern recognition and string matching. It consists of twenty eight chapters written by different authors, addressing a broad range of topics such as those from classifica­ tion, matching, mining, feature selection, and applications. Each chapter is self-contained, and presents either novel methodological approaches or applications of existing theories and techniques. The aim, intent, and motivation for publishing this book is to pro­ vide a reference tool for the increasing number of readers who depend upon pattern recognition or string matching in some way. This includes student...

  18. Pattern formation by kicked solitons in the two-dimensional Ginzburg-Landau medium with a transverse grating.

    Science.gov (United States)

    Besse, Valentin; Leblond, Hervé; Mihalache, Dumitru; Malomed, Boris A

    2013-01-01

    We consider the kick- (tilt-) induced mobility of two-dimensional (2D) fundamental dissipative solitons in models of bulk lasing media based on the 2D complex Ginzburg-Landau equation including a spatially periodic potential (transverse grating). The depinning threshold, which depends on the orientation of the kick, is identified by means of systematic simulations and estimated by means of an analytical approximation. Various pattern-formation scenarios are found above the threshold. Most typically, the soliton, hopping between potential cells, leaves arrayed patterns of different sizes in its wake. In the single-pass-amplifier setup, this effect may be used as a mechanism for the selective pattern formation controlled by the tilt of the input beam. Freely moving solitons feature two distinct values of the established velocity. Elastic and inelastic collisions between free solitons and pinned arrayed patterns are studied too.

  19. Simultaneous two-color, two-dimensional angular optical scattering patterns from airborne particulates: Scattering results and exploratory analysis

    Science.gov (United States)

    Holler, Stephen; Fuerstenau, Stephen D.; Skelsey, Charles R.

    2016-07-01

    Light scattering from non-spherical particles and aggregates exhibits complex structure that is revealed only when observed in two angular dimensions (θ, ϕ). However, due to variations in shape, packing, and orientation of such aerosols, the structure of two-dimensional angular optical scattering (TAOS) patterns varies among particles. The spectral dependence of scattering contributes further to the observed complexity, but offers another facet to consider. By leveraging multispectral TAOS data from flowing aerosols, we have identified novel morphological descriptors that may be employed in multivariate statistical algorithms for "unknown" particle classification.

  20. Automated classification of single airborne particles from two-dimensional angle-resolved optical scattering (TAOS) patterns by non-linear filtering

    Science.gov (United States)

    Crosta, Giovanni Franco; Pan, Yong-Le; Aptowicz, Kevin B.; Casati, Caterina; Pinnick, Ronald G.; Chang, Richard K.; Videen, Gorden W.

    2013-12-01

    Measurement of two-dimensional angle-resolved optical scattering (TAOS) patterns is an attractive technique for detecting and characterizing micron-sized airborne particles. In general, the interpretation of these patterns and the retrieval of the particle refractive index, shape or size alone, are difficult problems. By reformulating the problem in statistical learning terms, a solution is proposed herewith: rather than identifying airborne particles from their scattering patterns, TAOS patterns themselves are classified through a learning machine, where feature extraction interacts with multivariate statistical analysis. Feature extraction relies on spectrum enhancement, which includes the discrete cosine FOURIER transform and non-linear operations. Multivariate statistical analysis includes computation of the principal components and supervised training, based on the maximization of a suitable figure of merit. All algorithms have been combined together to analyze TAOS patterns, organize feature vectors, design classification experiments, carry out supervised training, assign unknown patterns to classes, and fuse information from different training and recognition experiments. The algorithms have been tested on a data set with more than 3000 TAOS patterns. The parameters that control the algorithms at different stages have been allowed to vary within suitable bounds and are optimized to some extent. Classification has been targeted at discriminating aerosolized Bacillus subtilis particles, a simulant of anthrax, from atmospheric aerosol particles and interfering particles, like diesel soot. By assuming that all training and recognition patterns come from the respective reference materials only, the most satisfactory classification result corresponds to 20% false negatives from B. subtilis particles and classification method may be adapted into a real-time operation technique, capable of detecting and characterizing micron-sized airborne particles.

  1. Development of Two-dimensional Analytical Model According to Polarizing Characteristics of the Raman Ranges at Recognition of Nanoparticles of Silver on Polyester Fibers

    Directory of Open Access Journals (Sweden)

    V.M. Emelyanov

    2015-12-01

    Full Text Available Parameters of two-dimensional analytical model of an assessment of crossing of ellipses of distribution at recognition of nanoparticles of colloidal silver are given in polyair fibers on multidimensional correlation components of the Raman ranges with control according to polarizing characteristics. Reliability of recognition of nanoparticles increased more than by 1000 times and was estimated on joint probability of normal distributions of intensivnost of the Raman spectrograms of nanoparticles of silver on polyair fibers depending on longitudinal and cross polarization of laser radiation on all range of a range with the analysis of 9 main peaks.

  2. Pattern Recognition Theory of Mind

    CERN Document Server

    de Paiva, Gilberto

    2009-01-01

    I propose that pattern recognition, memorization and processing are key concepts that can be a principle set for the theoretical modeling of the mind function. Most of the questions about the mind functioning can be answered by a descriptive modeling and definitions from these principles. An understandable consciousness definition can be drawn based on the assumption that a pattern recognition system can recognize its own patterns of activity. The principles, descriptive modeling and definitions can be a basis for theoretical and applied research on cognitive sciences, particularly at artificial intelligence studies.

  3. Application of approximate pattern matching in two dimensional spaces to grid layout for biochemical network maps.

    Directory of Open Access Journals (Sweden)

    Kentaro Inoue

    Full Text Available BACKGROUND: For visualizing large-scale biochemical network maps, it is important to calculate the coordinates of molecular nodes quickly and to enhance the understanding or traceability of them. The grid layout is effective in drawing compact, orderly, balanced network maps with node label spaces, but existing grid layout algorithms often require a high computational cost because they have to consider complicated positional constraints through the entire optimization process. RESULTS: We propose a hybrid grid layout algorithm that consists of a non-grid, fast layout (preprocessor algorithm and an approximate pattern matching algorithm that distributes the resultant preprocessed nodes on square grid points. To demonstrate the feasibility of the hybrid layout algorithm, it is characterized in terms of the calculation time, numbers of edge-edge and node-edge crossings, relative edge lengths, and F-measures. The proposed algorithm achieves outstanding performances compared with other existing grid layouts. CONCLUSIONS: Use of an approximate pattern matching algorithm quickly redistributes the laid-out nodes by fast, non-grid algorithms on the square grid points, while preserving the topological relationships among the nodes. The proposed algorithm is a novel use of the pattern matching, thereby providing a breakthrough for grid layout. This application program can be freely downloaded from http://www.cadlive.jp/hybridlayout/hybridlayout.html.

  4. Two-Dimensional Time-Domain Antenna Arrays for Optimum Steerable Energy Pattern with Low Side Lobes

    Directory of Open Access Journals (Sweden)

    Alberto Reyna

    2014-01-01

    Full Text Available This document presents the synthesis of different two-dimensional time-domain antenna arrays for steerable energy patterns with side lobe levels. The research is focused on the uniform and nonuniform distributions of true-time exciting delays and positions of antenna elements. The uniform square array, random array, uniform concentric ring array, and rotated nonuniform concentric ring array geometries are particularly studied. These geometries are synthesized by using the well-known sequential quadratic programming. The synthesis regards the optimal true-time exciting delays and optimal positions of pulsed antenna elements. The results show the capabilities of the different antenna arrays to steer the beam in their energy pattern in time domain and how their performance is in frequency domain after the synthesis in time domain.

  5. Multivariate data analysis of two-dimensional gel electrophoresis protein patterns from few samples

    DEFF Research Database (Denmark)

    Jensen, Kristina Nedenskov; Jessen, Flemming; Jørgensen, Bo

    2008-01-01

    One application of 2D gel electrophoresis is to reveal differences in protein pattern between two or more groups of individuals, attributable to their group membership. Multivariate data analytical methods are useful in pinpointing the spots relevant for discrimination by focusing not only...... on single spot differences, but on the covariance structure between proteins. However, their outcome is dependent on data scaling, and they may fail in producing valid multivariate models due to the much higher number of "irrelevant" spots present in the gels. The case where only few gels are available...

  6. Two-dimensional phase unwrapping algorithms for fringe pattern analysis: a comparison study

    Science.gov (United States)

    Yang, Fang; Wang, Zhaomin; Wen, Yongfu; Qu, Weijuan

    2015-03-01

    Phase unwrapping is a process to reconstruct the absolute phase from a wrapped phase map whose range is (-π, π]. As the absolute phase cannot be directly extracted from the fringe pattern, phase unwrapping is therefore required by phasemeasure techniques. Currently, many phase unwrapping algorithms have been proposed. In this paper, four popular phase unwrapping algorithms, including the Goldstein's branch cut method, the quality-guided method, the Phase Unwrapping via Max Flow (PUMA) method, and the phase estimation using adaptive regularization based on local smoothing method (PERALS), are reviewed and discussed. Detailed accuracy comparisons of these methods are provided as well.

  7. Two-dimensional intraventricular flow pattern visualization using the image-based computational fluid dynamics.

    Science.gov (United States)

    Doost, Siamak N; Zhong, Liang; Su, Boyang; Morsi, Yosry S

    2016-10-31

    The image-based computational fluid dynamics (IB-CFD) technique, as the combination of medical images and the CFD method, is utilized in this research to analyze the left ventricle (LV) hemodynamics. The research primarily aims to propose a semi-automated technique utilizing some freely available and commercial software packages in order to simulate the LV hemodynamics using the IB-CFD technique. In this research, moreover, two different physiological time-resolved 2D models of a patient-specific LV with two different types of aortic and mitral valves, including the orifice-type valves and integrated with rigid leaflets, are adopted to visualize the process of developing intraventricular vortex formation and propagation. The blood flow pattern over the whole cardiac cycle of two models is also compared to investigate the effect of utilizing different valve types in the process of the intraventricular vortex formation. Numerical findings indicate that the model with integrated valves can predict more complex intraventricular flow that can match better the physiological flow pattern in comparison to the orifice-type model.

  8. Feasibility and diagnostic accuracy of ischemic stroke territory recognition based on two-dimensional projections of three-dimensional diffusion MRI data

    Directory of Open Access Journals (Sweden)

    Jana Katharina Wrosch

    2015-11-01

    Full Text Available This study was conducted to assess the feasibility and diagnostic accuracy of brain artery territory recognition based on geoprojected two-dimensional maps of diffusion MRI data in stroke patients. In this retrospective study, multiplanar diffusion MRI data of ischemic stroke patients was used to create a two-dimensional map of the entire brain. To guarantee correct representation of the stroke, a computer-aided brain artery territory diagnosis was developed and tested for its diagnostic accuracy. The test recognized the stroke affected brain artery territory based on the position of the stroke in the map. The performance of the test was evaluated by comparing it to the reference standard of each patient’s diagnosed stroke territory on record. This study was designed and conducted according to Standards for Reporting of Diagnostic Accuracy (STARD. The statistical analysis included diagnostic accuracy parameters, cross-validation and Youden-Index optimization. After cross-validation on a cohort of 91 patients, the sensitivity of this territory diagnosis was 78% with a specificity of 71%. With this, the projection of strokes onto a two-dimensional map is accurate for representing the affected stroke territory and can be used to provide a static and printable overview of the diffusion MRI data. The projected map is compatible with other two-dimensional data such as EEG and will serve as a useful visualization tool.

  9. Feasibility and Diagnostic Accuracy of Ischemic Stroke Territory Recognition Based on Two-Dimensional Projections of Three-Dimensional Diffusion MRI Data.

    Science.gov (United States)

    Wrosch, Jana Katharina; Volbers, Bastian; Gölitz, Philipp; Gilbert, Daniel Frederic; Schwab, Stefan; Dörfler, Arnd; Kornhuber, Johannes; Groemer, Teja Wolfgang

    2015-01-01

    This study was conducted to assess the feasibility and diagnostic accuracy of brain artery territory recognition based on geoprojected two-dimensional maps of diffusion MRI data in stroke patients. In this retrospective study, multiplanar diffusion MRI data of ischemic stroke patients was used to create a two-dimensional map of the entire brain. To guarantee correct representation of the stroke, a computer-aided brain artery territory diagnosis was developed and tested for its diagnostic accuracy. The test recognized the stroke-affected brain artery territory based on the position of the stroke in the map. The performance of the test was evaluated by comparing it to the reference standard of each patient's diagnosed stroke territory on record. This study was designed and conducted according to Standards for Reporting of Diagnostic Accuracy (STARD). The statistical analysis included diagnostic accuracy parameters, cross-validation, and Youden Index optimization. After cross-validation on a cohort of 91 patients, the sensitivity of this territory diagnosis was 81% with a specificity of 87%. With this, the projection of strokes onto a two-dimensional map is accurate for representing the affected stroke territory and can be used to provide a static and printable overview of the diffusion MRI data. The projected map is compatible with other two-dimensional data such as EEG and will serve as a useful visualization tool.

  10. Topological patterns in two-dimensional gel electrophoresis of DNA knots.

    Science.gov (United States)

    Michieletto, Davide; Marenduzzo, Davide; Orlandini, Enzo

    2015-10-06

    Gel electrophoresis is a powerful experimental method to probe the topology of DNA and other biopolymers. Although there is a large body of experimental work that allows us to accurately separate different topoisomers of a molecule, a full theoretical understanding of these experiments has not yet been achieved. Here we show that the mobility of DNA knots depends crucially and subtly on the physical properties of the gel and, in particular, on the presence of dangling ends. The topological interactions between these and DNA molecules can be described in terms of an "entanglement number" and yield a nonmonotonic mobility at moderate fields. Consequently, in 2D electrophoresis, gel bands display a characteristic arc pattern; this turns into a straight line when the density of dangling ends vanishes. We also provide a novel framework to accurately predict the shape of such arcs as a function of molecule length and topological complexity, which may be used to inform future experiments.

  11. Two-dimensional WS2 nanoribbon deposition by conversion of pre-patterned amorphous silicon

    Science.gov (United States)

    Heyne, Markus H.; de Marneffe, Jean-François; Delabie, Annelies; Caymax, Matty; Neyts, Erik C.; Radu, Iuliana; Huyghebaert, Cedric; De Gendt, Stefan

    2017-01-01

    We present a method for area selective deposition of 2D WS2 nanoribbons with tunable thickness on a dielectric substrate. The process is based on a complete conversion of a pre-patterned, H-terminated Si layer to metallic W by WF6, followed by in situ sulfidation by H2S. The reaction process, performed at 450 °C, yields nanoribbons with lateral dimension down to 20 nm and with random basal plane orientation. The thickness of the nanoribbons is accurately controlled by the thickness of the pre-deposited Si layer. Upon rapid thermal annealing at 900 °C under inert gas, the WS2 basal planes align parallel to the substrate.

  12. Flow pattern transition accompanied with sudden growth of flow resistance in two-dimensional curvilinear viscoelastic flows

    CERN Document Server

    Yatou, Hiroki

    2010-01-01

    We find three types of steady solutions and remarkable flow pattern transitions between them in a two-dimensional wavy-walled channel for low to moderate Reynolds (Re) and Weissenberg (Wi) numbers using direct numerical simulations with spectral element method. The solutions are called "convective", "transition", and "elastic" in ascending order of Wi. In the convective region in the Re-Wi parameter space, the convective effect and the pressure gradient balance on average. As Wi increases, the elastic effect becomes suddenly comparable and the first transition sets in. Through the transition, a separation vortex disappears and a jet flow induced close to the wall by the viscoelasticity moves into the bulk; The viscous drag significantly drops and the elastic wall friction rises sharply. This transition is caused by an elastic force in the streamwise direction due to the competition of the convective and elastic effects. In the transition region, the convective and elastic effects balance. When the elastic eff...

  13. Transfer of Two-Dimensional Oligonucleotide Patterns onto Stereocontrolled Plasmonic Nanostructures through DNA-Origami-Based Nanoimprinting Lithography.

    Science.gov (United States)

    Zhang, Yinan; Chao, Jie; Liu, Huajie; Wang, Fei; Su, Shao; Liu, Bing; Zhang, Lan; Shi, Jiye; Wang, Lihua; Huang, Wei; Wang, Lianhui; Fan, Chunhai

    2016-07-04

    The precise functionalization of self-assembled nanostructures with spatial and stereocontrol is a major objective of nanotechnology and holds great promise for many applications. Herein, the nanoscale addressability of DNA origami was exploited to develop a precise copy-machine-like platform that can transfer two-dimensional oligonucleotide patterns onto the surface of gold nanoparticles (AuNPs) through a deliberately designed toehold-initiated DNA displacement reaction. This strategy of DNA-origami-based nanoimprinting lithography (DONIL) demonstrates high precision in controlling the valence and valence angles of AuNPs. These DNA-decorated AuNPs act as precursors in the construction of discrete AuNP clusters with desired chirality.

  14. Pattern Recognition Using Associative Memories

    OpenAIRE

    Burles, Nathan John

    2014-01-01

    The human brain is extremely effective at performing pattern recognition, even in the presence of noisy or distorted inputs. Artificial neural networks attempt to imitate the structure of the brain, often with a view to mimicking its success. The binary correlation matrix memory (CMM) is a particular type of neural network that is capable of learning and recalling associations extremely quickly, as well as displaying a high storage capacity and having the ability to generalise from patterns a...

  15. Data complexity in pattern recognition

    CERN Document Server

    Kam Ho Tin

    2006-01-01

    Machines capable of automatic pattern recognition have many fascinating uses. Algorithms for supervised classification, where one infers a decision boundary from a set of training examples, are at the core of this capability. This book looks at data complexity and its role in shaping the theories and techniques in different disciplines

  16. Data structures, computer graphics, and pattern recognition

    CERN Document Server

    Klinger, A; Kunii, T L

    1977-01-01

    Data Structures, Computer Graphics, and Pattern Recognition focuses on the computer graphics and pattern recognition applications of data structures methodology.This book presents design related principles and research aspects of the computer graphics, system design, data management, and pattern recognition tasks. The topics include the data structure design, concise structuring of geometric data for computer aided design, and data structures for pattern recognition algorithms. The survey of data structures for computer graphics systems, application of relational data structures in computer gr

  17. The two-dimensional optical pattern of a five inch diagonal white organic light emitting diode by rapid rotating measurement

    Science.gov (United States)

    Yang, Henglong; Cheng, Yu-Hen; Chen, Ming-Hong; Lin, Yu-Hsuan

    2016-09-01

    The feasibility of applying a five-inch diagonal white organic light-emitting diode (WOLED) as a desk lamp was experimentally investigated by quantitatively comparing its two-dimensional (2D) optical intensity profile to that of a traditional 3M desk lamp equipped with optical diffuser. The 2D optical distribution patterns as the function of vertical distances to a surface of a five-inch diagonal WOLED were obtained by using rapid rotating measurement technique consisted of a sample holder on a rotational stage and a fixed photo detector with optical power meter. The 2D optical intensity profile on a surface can be rapidly established in a relatively small space by recording the reading from the fixed photo detector as rotating the sample holder. This rapid measurement technique is suitable for practical application in quality engineering without larger space. A WOLED is a compact and thin lighting source with planar device structure without additional optical components. Its optical intensity profile on a plane is expected to be different from traditional lighting sources. The optical distribution pattern of a desk lamp requires a relatively large area on a surface with relatively uniformed intensity distribution. The quantitative analysis of the similarity between WOLED and 3M desk lamp was conducted by comparing the optimal zones defined as the area within 75% of the maximum intensity in 2D optical distribution pattern. Our preliminary result showed that the optimal zone of a five-inch diagonal WOLED at 45cm vertical distance is highly similar to that of the 3M desk lamp with optical diffuser.

  18. Flow pattern transition accompanied with sudden growth of flow resistance in two-dimensional curvilinear viscoelastic flows.

    Science.gov (United States)

    Yatou, Hiroki

    2010-09-01

    We numerically find three types of steady solutions of viscoelastic flows and flow pattern transitions between them in a two-dimensional wavy-walled channel for low to moderate Weissenberg (Wi) and Reynolds (Re) numbers using a spectral element method. The solutions are called "convective," "transition," and "elastic" in ascending order of Wi. In the convective region in the Wi-Re parameter space, convective effect and pressure gradient balance on average. As Wi increases, elastic effect becomes comparable, and the first transition sets in. Through the transition, a separation vortex disappears, and a jet flow induced close to the wall by the viscoelasticity moves into the bulk; the viscous drag significantly drops, and the elastic wall friction rises sharply. This transition is caused by an elastic force in the streamwise direction due to the competition of the convective and elastic effects. In the transition region, the convective and elastic effects balance. When the elastic effect becomes greater than the convective effect, the second transition occurs but it is relatively moderate. The second transition seems to be governed by the so-called Weissenberg effect. These transitions are not sensitive to driving forces. By a scaling analysis, it is shown that the stress component is proportional to the Reynolds number on the boundary of the first transition in the Wi-Re space. This scaling coincides well with the numerical result.

  19. Two-dimensional laser servoing for precision motion control of an ODV robotic license plate recognition system

    Science.gov (United States)

    Song, Zhen; Moore, Kevin L.; Chen, YangQuan; Bahl, Vikas

    2003-09-01

    As an outgrowth of series of projects focused on mobility of unmanned ground vehicles (UGV), an omni-directional (ODV), multi-robot, autonomous mobile parking security system has been developed. The system has two types of robots: the low-profile Omni-Directional Inspection System (ODIS), which can be used for under-vehicle inspections, and the mid-sized T4 robot, which serves as a ``marsupial mothership'' for the ODIS vehicles and performs coarse resolution inspection. A key task for the T4 robot is license plate recognition (LPR). For a successful LPR task without compromising the recognition rate, the robot must be able to identify the bumper locations of vehicles in the parking area and then precisely position the LPR camera relative to the bumper. This paper describes a 2D-laser scanner based approach to bumper identification and laser servoing for the T4 robot. The system uses a gimbal-mounted scanning laser. As the T4 robot travels down a row of parking stalls, data is collected from the laser every 100ms. For each parking stall in the range of the laser during the scan, the data is matched to a ``bumper box'' corresponding to where a car bumper is expected, resulting in a point cloud of data corresponding to a vehicle bumper for each stall. Next, recursive line-fitting algorithms are used to determine a line for the data in each stall's ``bumper box.'' The fitting technique uses Hough based transforms, which are robust against segmentation problems and fast enough for real-time line fitting. Once a bumper line is fitted with an acceptable confidence, the bumper location is passed to the T4 motion controller, which moves to position the LPR camera properly relative to the bumper. The paper includes examples and results that show the effectiveness of the technique, including its ability to work in real-time.

  20. 2D DOST based local phase pattern for face recognition

    Science.gov (United States)

    Moniruzzaman, Md.; Alam, Mohammad S.

    2017-05-01

    A new two dimensional (2-D) Discrete Orthogonal Stcokwell Transform (DOST) based Local Phase Pattern (LPP) technique has been proposed for efficient face recognition. The proposed technique uses 2-D DOST as preliminary preprocessing and local phase pattern to form robust feature signature which can effectively accommodate various 3D facial distortions and illumination variations. The S-transform, is an extension of the ideas of the continuous wavelet transform (CWT), is also known for its local spectral phase properties in time-frequency representation (TFR). It provides a frequency dependent resolution of the time-frequency space and absolutely referenced local phase information while maintaining a direct relationship with the Fourier spectrum which is unique in TFR. After utilizing 2-D Stransform as the preprocessing and build local phase pattern from extracted phase information yield fast and efficient technique for face recognition. The proposed technique shows better correlation discrimination compared to alternate pattern recognition techniques such as wavelet or Gabor based face recognition. The performance of the proposed method has been tested using the Yale and extended Yale facial database under different environments such as illumination variation and 3D changes in facial expressions. Test results show that the proposed technique yields better performance compared to alternate time-frequency representation (TFR) based face recognition techniques.

  1. Spatial distribution patterns of anorectal atresia/stenosis in China: Use of two-dimensional graph-theoretical clustering

    Institute of Scientific and Technical Information of China (English)

    Ping Yuan; Liang Qiao; Li Dai; Yan-Ping Wang; Guang-Xuan Zhou; Ying Han; Xiao-Xia Liu; Xun Zhang; Yi Cao; Juan Liang; Jun Zhu

    2009-01-01

    AIM:To investigate the spatial distribution patterns of anorectal atresia/stenosis in China.METHODS:Data were collected from the Chinese Birth Defects Monitoring Network (CBDMN),a hospitalbased congenital malformations registry system.All fetuses more than 28 wk of gestation and neonates up to 7 d of age in hospitals within the monitoring sites of the CBDMN were monitored from 2001 to 2005.Two-dimensional graph-theoretical clustering was used to divide monitoring sites of the CBDMN into different clusters according to the average incidences of anorectal atresia/stenosis in the different monitoring sites.RESULTS:The overall average incidence of anorectal atresia/stenosis in China was 3.17 per 10 000 from 2001 to 2005.The areas with the highest average incidences of anorectal atresia/stenosis were almost always focused in Eastern China.The monitoring sites were grouped into 6 clusters of areas.Cluster 1 comprised the monitoring sites in Heilongjiang Province,Jilin Province,and Liaoning Province;Cluster 2 was composed of those in Fujian Province,Guangdong Province,Hainan Province,Guangxi Zhuang Autonomous Region,south Hunan Province,and south Jiangxi Province;Cluster 3 consisted of those in Beijing Municipal City,Tianjin Municipal City,Hebei Province,Shandong Province,north Jiangsu Province,and north Anhui Province;Cluster 4 was made up of those in Zhejiang Province,Shanghai Municipal City,south Anhui Province,south Jiangsu Province,north Hunan Province,north Jiangxi Province,Hubei Province,Henan Province,Shanxi Province and Inner Mongolia Autonomous Region;Cluster 5 consisted of those in Ningxia Hui Autonomous Region,Gansu Province and Qinghai Province;and Cluster 6 included those in Shaanxi Province,Sichuan Province,Chongqing Municipal City,Yunnan Province,Guizhou Province,Xinjiang Uygur Autonomous Province and Tibet Autonomous Region.CONCLUSION:The findings in this research allow the display of the spatial distribution patterns of anorectal atresia/stenosis in

  2. Pattern recognition, machine intelligence and biometrics

    CERN Document Server

    Wang, Patrick S P

    2012-01-01

    ""Pattern Recognition, Machine Intelligence and Biometrics"" covers the most recent developments in Pattern Recognition and its applications, using artificial intelligence technologies within an increasingly critical field. It covers topics such as: image analysis and fingerprint recognition; facial expressions and emotions; handwriting and signatures; iris recognition; hand-palm gestures; and multimodal based research. The applications span many fields, from engineering, scientific studies and experiments, to biomedical and diagnostic applications, to personal identification and homeland secu

  3. Pattern recognition in speech and language processing

    CERN Document Server

    Chou, Wu

    2003-01-01

    Minimum Classification Error (MSE) Approach in Pattern Recognition, Wu ChouMinimum Bayes-Risk Methods in Automatic Speech Recognition, Vaibhava Goel and William ByrneA Decision Theoretic Formulation for Adaptive and Robust Automatic Speech Recognition, Qiang HuoSpeech Pattern Recognition Using Neural Networks, Shigeru KatagiriLarge Vocabulary Speech Recognition Based on Statistical Methods, Jean-Luc GauvainToward Spontaneous Speech Recognition and Understanding, Sadaoki FuruiSpeaker Authentication, Qi Li and Biing-Hwang JuangHMMs for Language Processing Problems, Ri

  4. MEMBRAIN NEURAL NETWORK FOR VISUAL PATTERN RECOGNITION

    Directory of Open Access Journals (Sweden)

    Artur Popko

    2013-06-01

    Full Text Available Recognition of visual patterns is one of significant applications of Artificial Neural Networks, which partially emulate human thinking in the domain of artificial intelligence. In the paper, a simplified neural approach to recognition of visual patterns is portrayed and discussed. This paper is dedicated for investigators in visual patterns recognition, Artificial Neural Networking and related disciplines. The document describes also MemBrain application environment as a powerful and easy to use neural networks’ editor and simulator supporting ANN.

  5. A Recognition Algorithm for Highly Deformed Two-Dimensional Code%高形变二维码识别算法设计与实现

    Institute of Scientific and Technical Information of China (English)

    于继明; 徐楠; 陈硕

    2014-01-01

    针对 QR(Quick Response)二维码在高偏离拍摄角度下难以识别的问题,设计一种在高偏离拍摄角度下正确识别的算法。该算法通过对图像二值化处理、形态学处理、边缘检测、Hough 变换和射影几何变换5个步骤,实现对图像的高准确率识别,使用 java 语言环境和移动终端的 android 环境下对算法进行仿真与算法验证,并实现了通过扫描或读取二维码图像来写入、查找信息等操作。%A recognition algorithm at a highly deviated shooting angle is proposed,which can solve the puzzle of identification for QR (Quick Response)two-dimensional code in case of high-angle shooting deviation from itself.The image can be recognized with high accuracy through the method with five procedures to process the image,i.e.,binarization processing, morphological processing,edge detection,Hough transformation and projective geometry trans-formation.Then the algorithm has been simulated and evaluated by using java language envi-ronment and android mobile terminal.By scanning or reading two-dimensional code image,the i-dentification function can be realized with the algorithm.

  6. Pattern recognition of quantum information based on pattern-distance

    Institute of Scientific and Technical Information of China (English)

    Dong Daoyi; Chen Zonghai; Jiang Shengxiang

    2005-01-01

    Looking upon every encoding state of quantum information systems as a quantum information pattern, A kind of pattern-distance between different patterns as a measurement of comparability of quantum information patterns is defined, and two kinds of recognition algorithms based on pattern-distance for quantum information are proposed. They can respectively recognize quantum information with known objective pattern and unknown objective pattern. In the two algorithms, the phases and occurrence probabilities of different eigenpatterns of quantum information are sufficiently considered. Two examples demonstrate the feasibility and effectiveness of the two recognition methods. These algorithms point out a new and important path for applications of quantum information and pattern recognition.

  7. The Fuzzy Sets Approach to Pattern Recognition

    Science.gov (United States)

    Wilson, T.

    1972-01-01

    The fuzzy set concept is defined and its application to pattern recognition is illustrated. An iterative procedure for learning the equi-membership surfaces and for generating a set of discriminate functions for two pattern classes is given.

  8. Acoustic Pattern Recognition on Android Devices

    DEFF Research Database (Denmark)

    Møller, Maiken Bjerg; Gaarsdal, Jesper; Steen, Kim Arild

    2013-01-01

    an Android application developed for acoustic pattern recognition of bird species. The acoustic data is recorded using a built-in microphone, and pattern recognition is performed on the device, requiring no network connection. The algorithm is implemented in C++ as a native Android module and the Open...

  9. Acoustic Pattern Recognition on Android Devices

    DEFF Research Database (Denmark)

    Møller, Maiken Bjerg; Gaarsdal, Jesper; Steen, Kim Arild

    2013-01-01

    an Android application developed for acoustic pattern recognition of bird species. The acoustic data is recorded using a built-in microphone, and pattern recognition is performed on the device, requiring no network connection. The algorithm is implemented in C++ as a native Android module and the Open...

  10. Optical pattern recognition for printed music notation

    Science.gov (United States)

    Homenda, Wladyslaw

    1995-03-01

    The paper presents problems related to automated recognition of printed music notation. Music notation recognition is a challenging problem in both fields: pattern recognition and knowledge representation. Music notation symbols, though well characterized by their features, are arranged in elaborated way in real music notation, which makes recognition task very difficult and still open for new ideas. On the other hand, the aim of the system, i.e. application of acquired printed music into further processing requires special representation of music data. Due to complexity of music nature and music notation, music representation is one of the key issue in music notation recognition and music processing. The problems of pattern recognition and knowledge representation in context or music processing are discussed in this paper. MIDISCAN, the computer system for music notation recognition and music processing, is presented.

  11. Introduction to pattern recognition a MATLAB approach

    CERN Document Server

    Theodoridis, Sergios; Koutroumbas, Konstantinos; Cavouras, Dionisis

    2010-01-01

    An accompanying manual to Theodoridis/Koutroumbas, Pattern Recognition, that includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. *Matlab code and descriptive summary of the most common methods and algorithms in Theodoridis/Koutroumbas, Pattern Recognition 4e.*Solved examples in Matlab, including real-life data sets in imaging and audio recognition*Available separately or at a special package price with the mai

  12. Two-dimensional pattern analysis on dominant species and community in subalpine meadow of Luya Mountain,Shanxi Province,China

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jintun

    2007-01-01

    The spatial pattern analysis of population and community is important to understand community structure and has become one key topic in modern plant ecology.There are many techniques for analyzing one-dimensional pattern in ecological literature.Two-dimensional pattern analysis is better than one-dimensional analysis in the study on community spatial characteristics and structure.However,it is hard to analyze these two-dimensional patterns due to poor effective methodology.The two-dimensional sampling using two transects that meet at right angles was applied to get quadrat data in this work.And then the data from the two transects were analyzed separately by one-dimensional pattern analysis method,two-term local quadrat variance.The length,width,and area of patches at different scales of pattern for populations were obtained from the analysis.For community pattern,detrended correspondence analysis (DCA)was employed to summarize the species information firstly,and then the first DCA axis scores were analyzed to check its pattern.The application of this method to the pattern analysis on dominant populations and community for subalpine meadow (Comm.Polygonum viviparum+Carex rigescens+Kobresia bellardii)in the Luya mountains showed that it could release the characteristics of spatial pattern clearly and was a very effective technique.The method is easy to use and saves time with obvious advantages,compared with the twodimensional pattern analysis methods presented in the literatures.In the study meadow,the patterns of the main dominant species,Polygonum viviparum,Carex rigescens,and Kobresia bellardii,were apparent and comparatively regular in shape with large areas of patches at the same scale compared with other species such as Festuca sp.and Thalictrum petaloideum.There were two or three scales of patterns for each plant population studied.This was related to population features,the interaction with environmental factors,and their dominant position in the community

  13. Comparison of protein patterns after two-dimensional gel electrophoresis from leaves of in vitro cultures and seedlings of Rubus chamaemorus L.

    Directory of Open Access Journals (Sweden)

    Barbara Thiem

    2014-01-01

    Full Text Available Proteins from leaves of Rubus chamaemorus propagated in vitro were subjected to miniaturized 2-D electrophoresis. The 2-DE patterns of proteins showed qualitative differences between plants propagated in vitro and control seedlings. More proteins of a high molecular weight were observed in leaves of plants from in vitro culture. A two-dimensional map of proteins from leaves provides detailed data concerning both polymorphism and protein patterns of this species. This makes it possible to start constructing a protein map of R. chamaemorus. The reasons for qualitative differences are discussed.

  14. Fuzzy Logic-Based Audio Pattern Recognition

    Science.gov (United States)

    Malcangi, M.

    2008-11-01

    Audio and audio-pattern recognition is becoming one of the most important technologies to automatically control embedded systems. Fuzzy logic may be the most important enabling methodology due to its ability to rapidly and economically model such application. An audio and audio-pattern recognition engine based on fuzzy logic has been developed for use in very low-cost and deeply embedded systems to automate human-to-machine and machine-to-machine interaction. This engine consists of simple digital signal-processing algorithms for feature extraction and normalization, and a set of pattern-recognition rules manually tuned or automatically tuned by a self-learning process.

  15. Pattern recognition and classification an introduction

    CERN Document Server

    Dougherty, Geoff

    2012-01-01

    The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. However, despite the existence of a number of notable books in the field, the subject remains very challenging, especially for the beginner. Pattern Recognition and Classification presents a comprehensive introduction to the core concepts involved in automated pattern recognition. It is designed to be accessible to newcomers from varied backgrounds, but it will also be useful to researchers and professionals in image and signal processing and analysis, and in computer visi

  16. Pattern Recognition Using Neural Networks

    Directory of Open Access Journals (Sweden)

    Santaji Ghorpade

    2010-12-01

    Full Text Available Face Recognition has been identified as one of the attracting research areas and it has drawn the attention of many researchers due to its varying applications such as security systems, medical systems,entertainment, etc. Face recognition is the preferred mode of identification by humans: it is natural,robust and non-intrusive. A wide variety of systems requires reliable personal recognition schemes to either confirm or determine the identity of an individual requesting their services. The purpose of such schemes is to ensure that the rendered services are accessed only by a legitimate user and no one else.Examples of such applications include secure access to buildings, computer systems, laptops, cellular phones, and ATMs. In the absence of robust personal recognition schemes, these systems are vulnerable to the wiles of an impostor.In this paper we have developed and illustrated a recognition system for human faces using a novel Kohonen self-organizing map (SOM or Self-Organizing Feature Map (SOFM based retrieval system.SOM has good feature extracting property due to its topological ordering. The Facial Analytics results for the 400 images of AT&T database reflects that the face recognition rate using one of the neural network algorithm SOM is 85.5% for 40 persons.

  17. Status of pattern recognition with wavelet analysis

    Institute of Scientific and Technical Information of China (English)

    Yuanyan TANG

    2008-01-01

    Pattern recognition has become one of the fastest growing research topics in the fields of computer science and electrical and electronic engineering in the recent years.Advanced research and development in pattern recognition have found numerous applications in such areas as artificial intelligence,information security,biometrics,military science and technology,finance and economics,weather forecast,image processing,communication,biomedical engineering,document processing,robot vision,transportation,and endless other areas,with many encouraging results.The achievement of pattern recognition is most likely to benefit from some new developments of theoretical mathematics including wavelet analysis.This paper aims at a brief survey of pattern recognition with the wavelet theory.It contains the following respects:analysis and detection of singularities with wavelets;wavelet descriptors for shapes of the objects;invariant representation of patterns;handwritten and printed character recognition;texture analysis and classification;image indexing and retrieval;classification and clustering;document analysis with wavelets;iris pattern recognition;face recognition using wavelet transform;hand gestures classification;character processing with B-spline wavelet transform;wavelet-based image fusion,and others.

  18. Pattern activation/recognition theory of mind.

    Science.gov (United States)

    du Castel, Bertrand

    2015-01-01

    In his 2012 book How to Create a Mind, Ray Kurzweil defines a "Pattern Recognition Theory of Mind" that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call "Pattern Activation/Recognition Theory of Mind." While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation.

  19. Pattern Activation/Recognition Theory of Mind

    Directory of Open Access Journals (Sweden)

    Bertrand edu Castel

    2015-07-01

    Full Text Available In his 2012 book How to Create a Mind, Ray Kurzweil defines a Pattern Recognition Theory of Mind that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call Pattern Activation/Recognition Theory of Mind. While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation.

  20. Patterning the two dimensional electron gas at the LaAlO3/SrTiO3 interface by structured Al capping

    Science.gov (United States)

    Zhou, Y.; Wang, P.; Luan, Z. Z.; Shi, Y. J.; Jiang, S. W.; Ding, H. F.; Wu, D.

    2017-04-01

    We demonstrate an approach for patterning a quasi-two dimensional electron gas (q-2DEG) at the interface of LaAlO3 (LAO) and SrTiO3 (STO) utilizing a structured Al capping layer. The capping of Al enables the formation of q-2DEG at the interface of 1-3 unit cells (uc) of LAO on STO, which was originally insulating before capping. The properties of the q-2DEG induced by the Al capping layer are essentially the same as those of q-2DEG without Al. Therefore, we can pattern q-2DEG by simply patterning the Al film on LAO (2 or 3 uc)/STO using a one-step liftoff process. Our approach circumvents the difficulty of direct patterning of oxide materials and provides a simple and robust patterning method for future device applications based on complex oxide interfaces.

  1. Semantic description and recognition of patterns

    Institute of Scientific and Technical Information of China (English)

    杨立; 戴汝为

    1996-01-01

    An algebraic semantic approach for the description and recognition of patterns is presented.Specifically,patterns are assumed as algebraic structures,and semantic constraints are given in the form of equational specifications.By such an idea,to recogniz a pattern is to check the validity of an equational conjecture by term rewriting.Such an approach is demonstrated through examples.

  2. Fuzzy Neural Model for Flatness Pattern Recognition

    Institute of Scientific and Technical Information of China (English)

    JIA Chun-yu; SHAN Xiu-ying; LIU Hong-min; NIU Zhao-ping

    2008-01-01

    For the problems occurring in a least square method model,a fuzzy model,and a neural network model for flatness pattern recognition,a fuzzy neural network model for flatness pattern recognition with only three-input and three-output signals was proposed with Legendre orthodoxy polynomial as basic pattern,based on fuzzy logic expert experiential knowledge and genetic-BP hybrid optimization algorithm.The model not only had definite physical meanings in its inner nodes,but also had strong self-adaptability,anti-interference ability,high recognition precision,and high velocity,thereby meeting the demand of high-precision flatness control for cold strip mill and providing a convenient,practical,and novel method for flatness pattern recognition.

  3. Visual recognition of fishmeal and meat and bone meal using temperature-dependent two-dimensional correlation near-infrared spectroscopy.

    Science.gov (United States)

    Lü, Chengxu; Chen, Longjian; Yang, Zengling; Liu, Xian; Han, Lujia

    2013-12-01

    The purpose of this study is to investigate the efficiency of two-dimensional correlation spectroscopy (2D-COS) in recognizing the authenticity and purity of fishmeal (FM) and meat and bone meal (MBM), which are both complex mixtures with high similarity. Twenty FM samples and 20 MBM samples were obtained and examined. Temperature-dependent near-infrared (NIR) spectra were obtained using a Spectrum 400 spectrometer from 20 °C to 60 °C with an interval of 10 °C. Wavelet transform (Daubechies 5 wavelet with five levels) and baseline correction were applied to the temperature-dependent spectra in the wave range of 6000-5400 cm(-1). A 2D-COS synchronous map was calculated and scaled to the range between -1 and 1. A correlation coefficient was employed to quantitatively evaluate the visual differences of synchronous maps. The results show minor differences in NIR spectral absorbency of FM and MBM, and such differences are caused by appropriate temperature perturbation and enlarged by the 2D-COS method. The sensitive wave range is found in the area of 5800-5400 cm(-1). FM and MBM have observable pattern differences in the synchronous maps. Further quantitative evaluation of synchronous maps confirms correct recognizing results. Temperature-dependent 2D-COS is capable of recognizing the authenticity and purity of highly similar FM and MBM samples.

  4. Pattern recognition using linguistic fuzzy logic predictors

    Science.gov (United States)

    Habiballa, Hashim

    2016-06-01

    The problem of pattern recognition has been solved with numerous methods in the Artificial Intelligence field. We present an unconventional method based on Lingustic Fuzzy Logic Forecaster which is primarily used for the task of time series analysis and prediction through logical deduction wtih linguistic variables. This method should be used not only to the time series prediction itself, but also for recognition of patterns in a signal with seasonal component.

  5. Word recognition using ideal word patterns

    Science.gov (United States)

    Zhao, Sheila X.; Srihari, Sargur N.

    1994-03-01

    The word shape analysis approach to text recognition is motivated by discoveries in psychological studies of the human reading process. It attempts to describe and compare the shape of the word as a whole object without trying to segment and recognize the individual characters, so it bypasses the errors committed in character segmentation and classification. However, the large number of classes and large variation and distortion expected in all patterns belonging to the same class make it difficult for conventional, accurate, pattern recognition approaches. A word shape analysis approach using ideal word patterns to overcome the difficulty and improve recognition performance is described in this paper. A special word pattern which characterizes a word class is extracted from different sample patterns of the word class and stored in memory. Recognition of a new word pattern is achieved by comparing it with the special pattern of each word class called ideal word pattern. The process of generating the ideal word pattern of each word class is proposed. The algorithm was tested on a set of machine printed gray scale word images which included a wide range of print types and qualities.

  6. Correlation of acidic and basic carrier ampholyte and immobilized pH gradient two-dimensional gel electrophoresis patterns based on mass spectrometric protein identification

    DEFF Research Database (Denmark)

    Nawrocki, A; Larsen, Martin Røssel; Podtelejnikov, A V

    1998-01-01

    Separation of proteins on either carrier ampholyte-based or immobilized pH gradient-based two-dimensional (2-D) gels gives rise to electrophoretic patterns that are difficult to compare visually. In this paper we have used matrix-assisted laser desorption/ionization mass spectrometry (MALDI......-references demonstrated that there is no obvious pattern by which the mobility of a protein in one gel system can be used to predict its mobility in the other. Thus, as laboratories adopt the immobilized pH gradient-based 2-D gel systems, the only reliable means of translating the data gained with the carrier ampholyte......-MS) to determine the identities of 335 protein spots in these two 2-D gel systems, including a substantial number of basic proteins which had never been identified before. Proteins that were identified in both gel systems allowed us to cross-reference the gel patterns. Vector analysis of these cross...

  7. Tunable exchange bias-like effect in patterned hard-soft two-dimensional lateral composites with perpendicular magnetic anisotropy

    Energy Technology Data Exchange (ETDEWEB)

    Hierro-Rodriguez, A., E-mail: ahierro@fc.up.pt; Alvarez-Prado, L. M.; Martín, J. I.; Alameda, J. M. [Departamento de Física, Universidad de Oviedo, C/Calvo Sotelo S/N, 33007 Oviedo (Spain); Centro de Investigación en Nanomateriales y Nanotecnología—CINN (CSIC—Universidad de Oviedo—Principado de Asturias), Parque Tecnológico de Asturias, 33428 Llanera (Spain); Teixeira, J. M. [IN-IFIMUP, Departamento de Física e Astronomia, Faculdade de Ciências, Universidade do Porto, Rua Campo Alegre 687, 4169-007 Porto (Portugal); Vélez, M. [Departamento de Física, Universidad de Oviedo, C/Calvo Sotelo S/N, 33007 Oviedo (Spain)

    2014-09-08

    Patterned hard-soft 2D magnetic lateral composites have been fabricated by e-beam lithography plus dry etching techniques on sputter-deposited NdCo{sub 5} thin films with perpendicular magnetic anisotropy. Their magnetic behavior is strongly thickness dependent due to the interplay between out-of-plane anisotropy and magnetostatic energy. Thus, the spatial modulation of thicknesses leads to an exchange coupled system with hard/soft magnetic regions in which rotatable anisotropy of the thicker elements provides an extra tool to design the global magnetic behavior of the patterned lateral composite. Kerr microscopy studies (domain imaging and magneto-optical Kerr effect magnetometry) reveal that the resulting hysteresis loops exhibit a tunable exchange bias-like shift that can be switched on/off by the applied magnetic field.

  8. Experiences in Pattern Recognition for Machine Olfaction

    Science.gov (United States)

    Bessant, C.

    2011-09-01

    Pattern recognition is essential for translating complex olfactory sensor responses into simple outputs that are relevant to users. Many approaches to pattern recognition have been applied in this field, including multivariate statistics (e.g. discriminant analysis), artificial neural networks (ANNs) and support vector machines (SVMs). Reviewing our experience of using these techniques with many different sensor systems reveals some useful insights. Most importantly, it is clear beyond any doubt that the quantity and selection of samples used to train and test a pattern recognition system are by far the most important factors in ensuring it performs as accurately and reliably as possible. Here we present evidence for this assertion and make suggestions for best practice based on these findings.

  9. Assessment of the spatial pattern of colorectal tumour perfusion estimated at perfusion CT using two-dimensional fractal analysis

    Energy Technology Data Exchange (ETDEWEB)

    Goh, Vicky; Sanghera, Bal [Mount Vernon Hospital, Paul Strickland Scanner Centre, Northwood, Middlesex (United Kingdom); Wellsted, David M.; Sundin, Josefin [University of Hertfordshire, Research and Development Support Unit, Hatfield (United Kingdom); Halligan, Steve [University College Hospital, Department of Academic Radiology, London (United Kingdom)

    2009-06-15

    The aim was to evaluate the feasibility of fractal analysis for assessing the spatial pattern of colorectal tumour perfusion at dynamic contrast-enhanced CT (perfusion CT). Twenty patients with colorectal adenocarcinoma underwent a 65-s perfusion CT study from which a perfusion parametric map was generated using validated commercial software. The tumour was identified by an experienced radiologist, segmented via thresholding and fractal analysis applied using in-house software: fractal dimension, abundance and lacunarity were assessed for the entire outlined tumour and for selected representative areas within the tumour of low and high perfusion. Comparison was made with ten patients with normal colons, processed in a similar manner, using two-way mixed analysis of variance with statistical significance at the 5% level. Fractal values were higher in cancer than normal colon (p {<=} 0.001): mean (SD) 1.71 (0.07) versus 1.61 (0.07) for fractal dimension and 7.82 (0.62) and 6.89 (0.47) for fractal abundance. Fractal values were lower in 'high' than 'low' perfusion areas. Lacunarity curves were shifted to the right for cancer compared with normal colon. In conclusion, colorectal cancer mapped by perfusion CT demonstrates fractal properties. Fractal analysis is feasible, potentially providing a quantitative measure of the spatial pattern of tumour perfusion. (orig.)

  10. Humoral pattern recognition and the complement system.

    Science.gov (United States)

    Degn, S E; Thiel, S

    2013-08-01

    In the context of immunity, pattern recognition is the art of discriminating friend from foe and innocuous from noxious. The basis of discrimination is the existence of evolutionarily conserved patterns on microorganisms, which are intrinsic to these microorganisms and necessary for their function and existence. Such immutable or slowly evolving patterns are ideal handles for recognition and have been targeted by early cellular immune defence mechanisms such as Toll-like receptors, NOD-like receptors, RIG-I-like receptors, C-type lectin receptors and by humoral defence mechanisms such as the complement system. Complement is a proteolytic cascade system comprising around 35 different soluble and membrane-bound proteins. It constitutes a central part of the innate immune system, mediating several major innate effector functions and modulating adaptive immune responses. The complement cascade proceeds via controlled, limited proteolysis and conformational changes of constituent proteins through three activation pathways: the classical pathway, the alternative pathway and the lectin pathway, which converge in common effector functions. Here, we review the nature of the pattern recognition molecules involved in complement activation, as well as their close relatives with no or unknown capacity for activating complement. We proceed to examine the composition of the pattern recognition complexes involved in complement activation, focusing on those of the lectin pathway, and arrive at a new model for their mechanism of operation, supported by recently emerging evidence.

  11. Combining Biometric Fractal Pattern and Particle Swarm Optimization-Based Classifier for Fingerprint Recognition

    Directory of Open Access Journals (Sweden)

    Chia-Hung Lin

    2010-01-01

    Full Text Available This paper proposes combining the biometric fractal pattern and particle swarm optimization (PSO-based classifier for fingerprint recognition. Fingerprints have arch, loop, whorl, and accidental morphologies, and embed singular points, resulting in the establishment of fingerprint individuality. An automatic fingerprint identification system consists of two stages: digital image processing (DIP and pattern recognition. DIP is used to convert to binary images, refine out noise, and locate the reference point. For binary images, Katz's algorithm is employed to estimate the fractal dimension (FD from a two-dimensional (2D image. Biometric features are extracted as fractal patterns using different FDs. Probabilistic neural network (PNN as a classifier performs to compare the fractal patterns among the small-scale database. A PSO algorithm is used to tune the optimal parameters and heighten the accuracy. For 30 subjects in the laboratory, the proposed classifier demonstrates greater efficiency and higher accuracy in fingerprint recognition.

  12. Associative Pattern Recognition In Analog VLSI Circuits

    Science.gov (United States)

    Tawel, Raoul

    1995-01-01

    Winner-take-all circuit selects best-match stored pattern. Prototype cascadable very-large-scale integrated (VLSI) circuit chips built and tested to demonstrate concept of electronic associative pattern recognition. Based on low-power, sub-threshold analog complementary oxide/semiconductor (CMOS) VLSI circuitry, each chip can store 128 sets (vectors) of 16 analog values (vector components), vectors representing known patterns as diverse as spectra, histograms, graphs, or brightnesses of pixels in images. Chips exploit parallel nature of vector quantization architecture to implement highly parallel processing in relatively simple computational cells. Through collective action, cells classify input pattern in fraction of microsecond while consuming power of few microwatts.

  13. Pattern recognition using inverse resonance filtration

    CERN Document Server

    Sofina, Olga; Kvetnyy, Roman

    2010-01-01

    An approach to textures pattern recognition based on inverse resonance filtration (IRF) is considered. A set of principal resonance harmonics of textured image signal fluctuations eigen harmonic decomposition (EHD) is used for the IRF design. It was shown that EHD is invariant to textured image linear shift. The recognition of texture is made by transfer of its signal into unstructured signal which simple statistical parameters can be used for texture pattern recognition. Anomalous variations of this signal point on foreign objects. Two methods of 2D EHD parameters estimation are considered with the account of texture signal breaks presence. The first method is based on the linear symmetry model that is not sensitive to signal phase jumps. The condition of characteristic polynomial symmetry provides the model stationarity and periodicity. Second method is based on the eigenvalues problem of matrices pencil projection into principal vectors space of singular values decomposition (SVD) of 2D correlation matrix....

  14. Algorithms for adaptive nonlinear pattern recognition

    Science.gov (United States)

    Schmalz, Mark S.; Ritter, Gerhard X.; Hayden, Eric; Key, Gary

    2011-09-01

    In Bayesian pattern recognition research, static classifiers have featured prominently in the literature. A static classifier is essentially based on a static model of input statistics, thereby assuming input ergodicity that is not realistic in practice. Classical Bayesian approaches attempt to circumvent the limitations of static classifiers, which can include brittleness and narrow coverage, by training extensively on a data set that is assumed to cover more than the subtense of expected input. Such assumptions are not realistic for more complex pattern classification tasks, for example, object detection using pattern classification applied to the output of computer vision filters. In contrast, we have developed a two step process, that can render the majority of static classifiers adaptive, such that the tracking of input nonergodicities is supported. Firstly, we developed operations that dynamically insert (or resp. delete) training patterns into (resp. from) the classifier's pattern database, without requiring that the classifier's internal representation of its training database be completely recomputed. Secondly, we developed and applied a pattern replacement algorithm that uses the aforementioned pattern insertion/deletion operations. This algorithm is designed to optimize the pattern database for a given set of performance measures, thereby supporting closed-loop, performance-directed optimization. This paper presents theory and algorithmic approaches for the efficient computation of adaptive linear and nonlinear pattern recognition operators that use our pattern insertion/deletion technology - in particular, tabular nearest-neighbor encoding (TNE) and lattice associative memories (LAMs). Of particular interest is the classification of nonergodic datastreams that have noise corruption with time-varying statistics. The TNE and LAM based classifiers discussed herein have been successfully applied to the computation of object classification in hyperspectral

  15. Grip-Pattern Recognition for Smart Guns

    NARCIS (Netherlands)

    Kauffman, J.A.; Bazen, A.M.; Gerez, S.H.; Veldhuis, R.N.J.

    2003-01-01

    This paper describes the design, implementation and evaluation of a user-verification system for a smart gun, which is based on grip-pattern recognition. An existing pressure sensor consisting of an array of 44 x 44 piezoresistive elements has been used. An interface has been developed to acquire pr

  16. Pattern Recognition by Retina-Like Devices.

    Science.gov (United States)

    Weiman, Carl F. R.; Rothstein, Jerome

    This study has investigated some pattern recognition capabilities of devices consisting of arrays of cooperating elements acting in parallel. The problem of recognizing straight lines in general position on the quadratic lattice has been completely solved by applying parallel acting algorithms to a special code for lines on the lattice. The…

  17. Conformal Predictions in Multimedia Pattern Recognition

    Science.gov (United States)

    Nallure Balasubramanian, Vineeth

    2010-01-01

    The fields of pattern recognition and machine learning are on a fundamental quest to design systems that can learn the way humans do. One important aspect of human intelligence that has so far not been given sufficient attention is the capability of humans to express when they are certain about a decision, or when they are not. Machine learning…

  18. Pattern Recognition in Pharmacokinetic Data Analysis.

    Science.gov (United States)

    Gabrielsson, Johan; Meibohm, Bernd; Weiner, Daniel

    2016-01-01

    Pattern recognition is a key element in pharmacokinetic data analyses when first selecting a model to be regressed to data. We call this process going from data to insight and it is an important aspect of exploratory data analysis (EDA). But there are very few formal ways or strategies that scientists typically use when the experiment has been done and data collected. This report deals with identifying the properties of a kinetic model by dissecting the pattern that concentration-time data reveal. Pattern recognition is a pivotal activity when modeling kinetic data, because a rigorous strategy is essential for dissecting the determinants behind concentration-time courses. First, we extend a commonly used relationship for calculation of the number of potential model parameters by simultaneously utilizing all concentration-time courses. Then, a set of points to consider are proposed that specifically addresses exploratory data analyses, number of phases in the concentration-time course, baseline behavior, time delays, peak shifts with increasing doses, flip-flop phenomena, saturation, and other potential nonlinearities that an experienced eye catches in the data. Finally, we set up a series of equations related to the patterns. In other words, we look at what causes the shapes that make up the concentration-time course and propose a strategy to construct a model. By practicing pattern recognition, one can significantly improve the quality and timeliness of data analysis and model building. A consequence of this is a better understanding of the complete concentration-time profile.

  19. Applications of chaotic neurodynamics in pattern recognition

    Science.gov (United States)

    Baird, Bill; Freeman, Walter J.; Eeckman, Frank H.; Yao, Yong

    1991-08-01

    Network algorithms and architectures for pattern recognition derived from neural models of the olfactory system are reviewed. These span a range from highly abstract to physiologically detailed, and employ the kind of dynamical complexity observed in olfactory cortex, ranging from oscillation to chaos. A simple architecture and algorithm for analytically guaranteed associative memory storage of analog patterns, continuous sequences, and chaotic attractors in the same network is described. A matrix inversion determines network weights, given prototype patterns to be stored. There are N units of capacity in an N node network with 3N2 weights. It costs one unit per static attractor, two per Fourier component of each sequence, and three to four per chaotic attractor. There are no spurious attractors, and for sequences there is a Liapunov function in a special coordinate system which governs the approach of transient states to stored trajectories. Unsupervised or supervised incremental learning algorithms for pattern classification, such as competitive learning or bootstrap Widrow-Hoff can easily be implemented. The architecture can be ''folded'' into a recurrent network with higher order weights that can be used as a model of cortex that stores oscillatory and chaotic attractors by a Hebb rule. Network performance is demonstrated by application to the problem of real-time handwritten digit recognition. An effective system with on-line learning has been written by Eeckman and Baird for the Macintosh. It utilizes static, oscillatory, and/or chaotic attractors of two kinds--Lorenze attractors, or attractors resulting from chaotically interacting oscillatory modes. The successful application to an industrial pattern recognition problem of a network architecture of considerable physiological and dynamical complexity, developed by Freeman and Yao, is described. The data sets of the problem come in three classes of difficulty, and performance of the biological network is

  20. 浅谈设计型二维码在品牌识别系统中的应用%Application of Design Two-dimensional Code in Brand Recognition System

    Institute of Scientific and Technical Information of China (English)

    高立伟

    2013-01-01

    With the continuous development of image recognition technology and wireless communication technology, two-dimensional code technology has a wide range of application in the new media such as mobile phone. Creative two-dimensional code with high reorganization is significant to the improvement of enterprise's brand image the increase of consumer's attention and fancy to brand for brand design and communication. The current design of two-dimensional code in our country is made of the simple black and white squares, and it is more and more difficult to meet the increasing demand of consumer, and is difficult to make the brand stand out form the general two-dimensional code design. The paper puts forward that the new design philosophy that changing line and color, adding drawing and graphics elements for increasing the design sense of two-dimensional code and improving its reorganization and affinity, and states the necessity of the two-dimensional code with design sense and its development trend in order to promote the progress of two-dimensional code design.%随着无线通信技术、图像识别技术的不断发展,二维码技术在手机等新媒体上的应用也更为广泛,在品牌设计与传播中,充满创意、辨识度较高的二维码对提升企业品牌形象,增加消费者对于品牌的关注和喜爱具有重要意义。然而当前我国的二维码设计大多还停留在在简单的黑白格子上,越来越难以满足消费者日益增大的求新求异需求,难以让品牌在同一的二维码设计中脱颖而出,因此本文提出在传统二维码中改变线条、颜色,加入手绘、图形等元素,增加二维码的设计感,提升其辨别度和亲和度,并对发展这种有设计感的二维码的必要性及其未来发展趋势做了阐述,以期促进我国二维码设计的进步。

  1. Pattern recognition receptors in antifungal immunity.

    Science.gov (United States)

    Plato, Anthony; Hardison, Sarah E; Brown, Gordon D

    2015-03-01

    Receptors of the innate immune system are the first line of defence against infection, being able to recognise and initiate an inflammatory response to invading microorganisms. The Toll-like (TLR), NOD-like (NLR), RIG-I-like (RLR) and C-type lectin-like receptors (CLR) are four receptor families that contribute to the recognition of a vast range of species, including fungi. Many of these pattern recognition receptors (PRRs) are able to initiate innate immunity and polarise adaptive responses upon the recognition of fungal cell wall components and other conserved molecular patterns, including fungal nucleic acids. These receptors induce effective mechanisms of fungal clearance in normal hosts, but medical interventions, immunosuppression or genetic predisposition can lead to susceptibility to fungal infections. In this review, we highlight the importance of PRRs in fungal infection, specifically CLRs, which are the major PRR involved. We will describe specific PRRs in detail, the importance of receptor collaboration in fungal recognition and clearance, and describe how genetic aberrations in PRRs can contribute to disease pathology.

  2. DNA pattern recognition using canonical correlation algorithm

    Indian Academy of Sciences (India)

    B K Sarkar; Chiranjib Chakraborty

    2015-10-01

    We performed canonical correlation analysis as an unsupervised statistical tool to describe related views of the same semantic object for identifying patterns. A pattern recognition technique based on canonical correlation analysis (CCA) was proposed for finding required genetic code in the DNA sequence. Two related but different objects were considered: one was a particular pattern, and other was test DNA sequence. CCA found correlations between two observations of the same semantic pattern and test sequence. It is concluded that the relationship possesses maximum value in the position where the pattern exists. As a case study, the potential of CCA was demonstrated on the sequence found from HIV-1 preferred integration sites. The subsequences on the left and right flanking from the integration site were considered as the two views, and statistically significant relationships were established between these two views to elucidate the viral preference as an important factor for the correlation.

  3. Molecular characterization, expression patterns, and polymorphism of a differentially expressed porcine gene (PYGM) isolated by suppression subtractive hybridization and two-dimensional gel electrophoresis analysis.

    Science.gov (United States)

    Xu, Yongjie; Yu, Wenmin; Feng, Xiaoting; Xie, Hongtao; Xiong, Yuanzhu

    2012-01-01

    Suppression subtractive hybridization was performed to detect the differences in gene expression of porcine longissimus dorsi muscles between Large White and Chinese Meishan pigs. An upregulated gene in Large White that shared high homology with human muscle glycogen phosphorylase (PYGM) was identified. The porcine PYGM gene contains an open reading frame encoding 842 amino acid residues with 26 and 283 nucleotides in the 5' and 3' untranslated regions, respectively. Tissue distribution analysis indicated that porcine PYGM mRNAs are highly expressed in all tissues. Expression pattern of PYGM was similar in the two breeds. Both breeds had the highest expression levels when 120 days old (p<0.01), and PYGM was upregulated during skeletal muscle development. A similar expression pattern of PYGM in protein level was also observed by differential proteome analysis of skeletal muscle development using two-dimensional gel electrophoresis and mass spectroscopy. The mRNA abundance of PYGM in Large White was higher than Meishan at all four stages (p<0.05). Moreover, a G/T mutation in exon 8 was identified and association analysis with meat quality traits showed that it was significantly associated with lean meat percentage (p<0.05). Our data may provide further insight into the molecular mechanisms responsible for breed-specific differences in porcine growth and meat quality.

  4. Granular neural networks, pattern recognition and bioinformatics

    CERN Document Server

    Pal, Sankar K; Ganivada, Avatharam

    2017-01-01

    This book provides a uniform framework describing how fuzzy rough granular neural network technologies can be formulated and used in building efficient pattern recognition and mining models. It also discusses the formation of granules in the notion of both fuzzy and rough sets. Judicious integration in forming fuzzy-rough information granules based on lower approximate regions enables the network to determine the exactness in class shape as well as to handle the uncertainties arising from overlapping regions, resulting in efficient and speedy learning with enhanced performance. Layered network and self-organizing analysis maps, which have a strong potential in big data, are considered as basic modules,. The book is structured according to the major phases of a pattern recognition system (e.g., classification, clustering, and feature selection) with a balanced mixture of theory, algorithm, and application. It covers the latest findings as well as directions for future research, particularly highlighting bioinf...

  5. Optical Pattern Recognition for Missile Guidance.

    Science.gov (United States)

    1982-11-15

    Cutrona et al., IRE Trans. Inform. Theory, vol. IT-6, p. 386,1960, diodes whose outputs are the elements of W. Each LED is and D. Hecht , Proc. Soc...34, Acta optica Sinica, 1, 401-410, September 1981 (Casasent et al). 35. "Eigenvector Determination by Iterative Optical Methods", Applied optics, 20...Elements and Architectures" (Master’s expected in 1983). 10. Eugene Pochapsky, "Digital Preprocessing and Simulation for Optical Pattern Recognition

  6. VLSI Microsystem for Rapid Bioinformatic Pattern Recognition

    Science.gov (United States)

    Fang, Wai-Chi; Lue, Jaw-Chyng

    2009-01-01

    A system comprising very-large-scale integrated (VLSI) circuits is being developed as a means of bioinformatics-oriented analysis and recognition of patterns of fluorescence generated in a microarray in an advanced, highly miniaturized, portable genetic-expression-assay instrument. Such an instrument implements an on-chip combination of polymerase chain reactions and electrochemical transduction for amplification and detection of deoxyribonucleic acid (DNA).

  7. Pattern recognition and massively distributed computing.

    Science.gov (United States)

    Davies, E Keith; Glick, Meir; Harrison, Karl N; Richards, W Graham

    2002-12-01

    A feature of Peter Kollman's research was his exploitation of the latest computational techniques to devise novel applications of the free energy perturbation method. He would certainly have seized upon the opportunities offered by massively distributed computing. Here we describe the use of over a million personal computers to perform virtual screening of 3.5 billion druglike molecules against protein targets by pharmacophore pattern matching, together with other applications of pattern recognition such as docking ligands without any a priori knowledge about the binding site location.

  8. Classifying and assembling two-dimensional X-ray laser diffraction patterns of a single particle to reconstruct the three-dimensional diffraction intensity function: resolution limit due to the quantum noise

    Science.gov (United States)

    Tokuhisa, Atsushi; Taka, Junichiro; Kono, Hidetoshi; Go, Nobuhiro

    2012-01-01

    A new two-step algorithm is developed for reconstructing the three-dimensional diffraction intensity of a globular biological macromolecule from many experimentally measured quantum-noise-limited two-dimensional X-ray laser diffraction patterns, each for an unknown orientation. The first step is classification of the two-dimensional patterns into groups according to the similarity of direction of the incident X-rays with respect to the molecule and an averaging within each group to reduce the noise. The second step is detection of common intersecting circles between the signal-enhanced two-dimensional patterns to identify their mutual location in the three-dimensional wavenumber space. The newly developed algorithm enables one to detect a signal for classification in noisy experimental photon-count data with as low as ∼0.1 photons per effective pixel. The wavenumber of such a limiting pixel determines the attainable structural resolution. From this fact, the resolution limit due to the quantum noise attainable by this new method of analysis as well as two important experimental parameters, the number of two-dimensional patterns to be measured (the load for the detector) and the number of pairs of two-dimensional patterns to be analysed (the load for the computer), are derived as a function of the incident X-ray intensity and quantities characterizing the target molecule. PMID:22514069

  9. Statistical pattern recognition for rock joint images

    Science.gov (United States)

    Wang, Weixing; Bin, Cui

    2005-10-01

    As a cooperation project between Sweden and China, we sampled a number of rock specimens for analyze rock fracture network by optical image technique. The samples are resin injected, in which way; opened fractures can be seen clearly by means of UV (Ultraviolet) light illumination. In the study period, Recognition of rock fractures is crucial in many rock engineering applications. In order to successfully applying automatic image processing techniques for the problem of automatic (or semi-automatic) rock fracture detection and description, the key (and hardest task) is the automatic detection of fractures robustly in images. When statistical pattern recognition is used to segment a rock joint color image, features of different samples can be learned first, then, each pixel of the image is classified by these features. As the testing result showing, an attribute rock fracture image is segmented satisfactorily by using this way. The method can be widely used for other complicated images too. In this paper, Kernel Fisher discrimination (KFD) is employed to construct a statistical pattern recognition classifier. KFD can transform nonlinear discrimination in an attribute space with high dimension, into linear discrimination in a feature space with low dimension. While one needs not know the detailed mapping form from attribute space to feature space in the process of transformation. It is proved that this method performs well by segmenting complicated rock joint color images.

  10. Chaotic Neural Network for Biometric Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Kushan Ahmadian

    2012-01-01

    Full Text Available Biometric pattern recognition emerged as one of the predominant research directions in modern security systems. It plays a crucial role in authentication of both real-world and virtual reality entities to allow system to make an informed decision on granting access privileges or providing specialized services. The major issues tackled by the researchers are arising from the ever-growing demands on precision and performance of security systems and at the same time increasing complexity of data and/or behavioral patterns to be recognized. In this paper, we propose to deal with both issues by introducing the new approach to biometric pattern recognition, based on chaotic neural network (CNN. The proposed method allows learning the complex data patterns easily while concentrating on the most important for correct authentication features and employs a unique method to train different classifiers based on each feature set. The aggregation result depicts the final decision over the recognized identity. In order to train accurate set of classifiers, the subspace clustering method has been used to overcome the problem of high dimensionality of the feature space. The experimental results show the superior performance of the proposed method.

  11. Pattern recognition with "materials that compute".

    Science.gov (United States)

    Fang, Yan; Yashin, Victor V; Levitan, Steven P; Balazs, Anna C

    2016-09-01

    Driven by advances in materials and computer science, researchers are attempting to design systems where the computer and material are one and the same entity. Using theoretical and computational modeling, we design a hybrid material system that can autonomously transduce chemical, mechanical, and electrical energy to perform a computational task in a self-organized manner, without the need for external electrical power sources. Each unit in this system integrates a self-oscillating gel, which undergoes the Belousov-Zhabotinsky (BZ) reaction, with an overlaying piezoelectric (PZ) cantilever. The chemomechanical oscillations of the BZ gels deflect the PZ layer, which consequently generates a voltage across the material. When these BZ-PZ units are connected in series by electrical wires, the oscillations of these units become synchronized across the network, where the mode of synchronization depends on the polarity of the PZ. We show that the network of coupled, synchronizing BZ-PZ oscillators can perform pattern recognition. The "stored" patterns are set of polarities of the individual BZ-PZ units, and the "input" patterns are coded through the initial phase of the oscillations imposed on these units. The results of the modeling show that the input pattern closest to the stored pattern exhibits the fastest convergence time to stable synchronization behavior. In this way, networks of coupled BZ-PZ oscillators achieve pattern recognition. Further, we show that the convergence time to stable synchronization provides a robust measure of the degree of match between the input and stored patterns. Through these studies, we establish experimentally realizable design rules for creating "materials that compute."

  12. Two-dimensional calculus

    CERN Document Server

    Osserman, Robert

    2011-01-01

    The basic component of several-variable calculus, two-dimensional calculus is vital to mastery of the broader field. This extensive treatment of the subject offers the advantage of a thorough integration of linear algebra and materials, which aids readers in the development of geometric intuition. An introductory chapter presents background information on vectors in the plane, plane curves, and functions of two variables. Subsequent chapters address differentiation, transformations, and integration. Each chapter concludes with problem sets, and answers to selected exercises appear at the end o

  13. Two dimensional vernier

    Science.gov (United States)

    Juday, Richard D. (Inventor)

    1992-01-01

    A two-dimensional vernier scale is disclosed utilizing a cartesian grid on one plate member with a polar grid on an overlying transparent plate member. The polar grid has multiple concentric circles at a fractional spacing of the spacing of the cartesian grid lines. By locating the center of the polar grid on a location on the cartesian grid, interpolation can be made of both the X and Y fractional relationship to the cartesian grid by noting which circles coincide with a cartesian grid line for the X and Y direction.

  14. Artificial intelligence tools for pattern recognition

    Science.gov (United States)

    Acevedo, Elena; Acevedo, Antonio; Felipe, Federico; Avilés, Pedro

    2017-06-01

    In this work, we present a system for pattern recognition that combines the power of genetic algorithms for solving problems and the efficiency of the morphological associative memories. We use a set of 48 tire prints divided into 8 brands of tires. The images have dimensions of 200 x 200 pixels. We applied Hough transform to obtain lines as main features. The number of lines obtained is 449. The genetic algorithm reduces the number of features to ten suitable lines that give thus the 100% of recognition. Morphological associative memories were used as evaluation function. The selection algorithms were Tournament and Roulette wheel. For reproduction, we applied one-point, two-point and uniform crossover.

  15. Framework of Pattern Recognition Model Based on the Cognitive Psychology

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    According to the fundamental theory of visual cognition mechanism and cognitive psychology,the visual pattern recognition model is introduced briefly.Three pattern recognition models,i.e.template-based matching model,prototype-based matching model and feature-based matching model are built and discussed separately.In addition,the influence of object background information and visual focus point to the result of pattern recognition is also discussed with the example of recognition for fuzzy letters and figures.

  16. Pigment Melanin: Pattern for Iris Recognition

    CERN Document Server

    Hosseini, Mahdi S; Soltanian-Zadeh, Hamid

    2009-01-01

    Recognition of iris based on Visible Light (VL) imaging is a difficult problem because of the light reflection from the cornea. Nonetheless, pigment melanin provides a rich feature source in VL, unavailable in Near-Infrared (NIR) imaging. This is due to biological spectroscopy of eumelanin, a chemical not stimulated in NIR. In this case, a plausible solution to observe such patterns may be provided by an adaptive procedure using a variational technique on the image histogram. To describe the patterns, a shape analysis method is used to derive feature-code for each subject. An important question is how much the melanin patterns, extracted from VL, are independent of iris texture in NIR. With this question in mind, the present investigation proposes fusion of features extracted from NIR and VL to boost the recognition performance. We have collected our own database (UTIRIS) consisting of both NIR and VL images of 158 eyes of 79 individuals. This investigation demonstrates that the proposed algorithm is highly s...

  17. Similarity-based pattern analysis and recognition

    CERN Document Server

    Pelillo, Marcello

    2013-01-01

    This accessible text/reference presents a coherent overview of the emerging field of non-Euclidean similarity learning. The book presents a broad range of perspectives on similarity-based pattern analysis and recognition methods, from purely theoretical challenges to practical, real-world applications. The coverage includes both supervised and unsupervised learning paradigms, as well as generative and discriminative models. Topics and features: explores the origination and causes of non-Euclidean (dis)similarity measures, and how they influence the performance of traditional classification alg

  18. FEM enhanced signal processing approach for pattern recognition in the SQUID based NDE system

    Energy Technology Data Exchange (ETDEWEB)

    Sarreshtedari, F; Jahed, N M S; Hosseni, N; Pourhashemi, A; Fardmanesh, M [Department of Electrical Engineering, Sharif University of Technology, Tehran (Iran, Islamic Republic of); Banzet, Marko; Schubert, Juergen, E-mail: fardmanesh@sharif.ed [Forschungszentrum Juelich, Institute of Bio and Nanosystems, 52425 Juelich (Germany)

    2010-06-01

    An efficient Non-Destructive Evaluation algorithm has been developed in order to extract the required information for pattern recognition of defects in the conductive samples. Using high-Tc gradiometer RF-SQUIDs in unshielded environments and incorporating an automated two dimensional non-magnetic scanning robot, samples with different intentional defects have been tested. We have used a developed noise cancellation approach for the improvement of the effectiveness of the used inverse-problem technique. In this approach we have used a well examined Finite Element Method (FEM) to apply a noise reduction filtering on the obtained raw magnetic image data before incorporating the signal processing analysis. By applying this noise cancellation filter and incorporating three different signal processing algorithms and comparing the results of the predicted images by the pattern of the intentionally made defects, we have investigated the ability of these methods for pattern recognition of unknown defects.

  19. Spectral ’Fingerprinting’ of Phytoplankton Populations by Two-Dimensional Fluorescence and Fourier-Transform-Based Pattern Recognition.

    Science.gov (United States)

    2014-09-26

    Marine Research. IS. K3LXOROS (Centinue en reveree side it necessa.yad Identlfy by blek nmer) ’-"luorescence Malysis J) Chlorophyll Auorescencej Marine... chlorophylls , carotenoids, and phycobilins. Chlorophyll a provides the universal link between these three groups since it is the only pigment present in...accessory pigments ( chlorophylls b and c, carotenoids, and phycobilins) and channels it into the photosynthetic process. This allows photosynthesis to

  20. Applications of Pattern Recognition Algorithms in Agriculture: A Review

    Directory of Open Access Journals (Sweden)

    M. P. Raj

    2015-03-01

    Full Text Available Pattern recognition has its roots in artificial intelligence and is a branch of machine learning that focuses on the recognition of patterns and regularities in data. Data can be in the form of image, text, video or any other format. Under normal scenario, pattern recognition is implemented by first formalizing a problem, explain and at last visualize the pattern. In contrast to pattern matching, pattern recognition algorithms generally provide a fair result for all possible inputs by considering statistical variations. Probabilistic classifiers have supported Agricultural statistical inference for decades. Potential applications of this technique in agriculture are numerous like pattern recognition from satellite imagery, identifying the type of disease from leaf image, weed detection etc. This paper explores employment of pattern recognition in an agricultural domain.

  1. Inverse Scattering Approach to Improving Pattern Recognition

    Energy Technology Data Exchange (ETDEWEB)

    Chapline, G; Fu, C

    2005-02-15

    The Helmholtz machine provides what may be the best existing model for how the mammalian brain recognizes patterns. Based on the observation that the ''wake-sleep'' algorithm for training a Helmholtz machine is similar to the problem of finding the potential for a multi-channel Schrodinger equation, we propose that the construction of a Schrodinger potential using inverse scattering methods can serve as a model for how the mammalian brain learns to extract essential information from sensory data. In particular, inverse scattering theory provides a conceptual framework for imagining how one might use EEG and MEG observations of brain-waves together with sensory feedback to improve human learning and pattern recognition. Longer term, implementation of inverse scattering algorithms on a digital or optical computer could be a step towards mimicking the seamless information fusion of the mammalian brain.

  2. Intrusion detection using pattern recognition methods

    Science.gov (United States)

    Jiang, Nan; Yu, Li

    2007-09-01

    Today, cyber attacks such as worms, scanning, active attackers are pervasive in Internet. A number of security approaches are proposed to address this problem, among which the intrusion detection system (IDS) appears to be one of the major and most effective solutions for defending against malicious users. Essentially, intrusion detection problem can be generalized as a classification problem, whose goal is to distinguish normal behaviors and anomalies. There are many well-known pattern recognition algorithms for classification purpose. In this paper we describe the details of applying pattern recognition methods to the intrusion detection research field. Experimenting on the KDDCUP 99 data set, we first use information gain metric to reduce the dimensionality of the original feature space. Two supervised methods, the support vector machine as well as the multi-layer neural network have been tested and the results display high detection rate and low false alarm rate, which is promising for real world applications. In addition, three unsupervised methods, Single-Linkage, K-Means, and CLIQUE, are also implemented and evaluated in the paper. The low computational complexity reveals their application in initial data reduction process.

  3. Pattern recognition receptors in microbial keratitis.

    Science.gov (United States)

    Taube, M-A; del Mar Cendra, M; Elsahn, A; Christodoulides, M; Hossain, P

    2015-11-01

    Microbial keratitis is a significant cause of global visual impairment and blindness. Corneal infection can be caused by a wide variety of pathogens, each of which exhibits a range of mechanisms by which the immune system is activated. The complexity of the immune response to corneal infection is only now beginning to be elucidated. Crucial to the cornea's defences are the pattern-recognition receptors: Toll-like and Nod-like receptors and the subsequent activation of inflammatory pathways. These inflammatory pathways include the inflammasome and can lead to significant tissue destruction and corneal damage, with the potential for resultant blindness. Understanding the immune mechanisms behind this tissue destruction may enable improved identification of therapeutic targets to aid development of more specific therapies for reducing corneal damage in infectious keratitis. This review summarises current knowledge of pattern-recognition receptors and their downstream pathways in response to the major keratitis-causing organisms and alludes to potential therapeutic approaches that could alleviate corneal blindness.

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

    Science.gov (United States)

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

    2010-11-01

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

  5. Gender recognition using local binary pattern and Naive Bayes ...

    African Journals Online (AJOL)

    Gender recognition using local binary pattern and Naive Bayes Classifier. ... identity authentication, access control and human-computer interaction amongst others. Gender recognition is a fundamental task for human beings, as many social ...

  6. Two-dimensional optical spectroscopy

    CERN Document Server

    Cho, Minhaeng

    2009-01-01

    Discusses the principles and applications of two-dimensional vibrational and optical spectroscopy techniques. This book provides an account of basic theory required for an understanding of two-dimensional vibrational and electronic spectroscopy.

  7. Viral recognition by the innate immune system: the role of pattern recognition receptors

    OpenAIRE

    Silvia Torres Pedraza; Juan Guillermo Betancur; Silvio Urcuqui-Inchima

    2011-01-01

    Pattern recognition receptors are the main sensors of the innate immune response. Their function is to recognize pathogen-associated molecular patterns, which are molecules essential for the survival of microbial pathogens, but are not produced by the host. The recognition of pathogen-associated molecular patterns by pattern recognition receptors leads to the expression of cytokines, chemokines, and co-stimulatory molecules that eliminate pathogens, such as viruses, for the activation of anti...

  8. Two-dimensional gel electrophoresis pattern (pH 6-11) and identification of water-soluble barley seed and malt proteins by mass spectrometry

    DEFF Research Database (Denmark)

    Bak-Jensen, K.S.; Laugesen, S.; Roepstorff, P.

    2004-01-01

    A protocol was established for two-dimensional gel electrophoresis (2-DE) of barley seed and malt proteins in the pH range of 6-11. Proteins extracted from flour in a low-salt buffer were focused after cup-loading onto IPG strips. Successful separation in the second dimension was achieved using...

  9. KEYSTROKE PATTERN RECOGNITION PREVENTING ONLINE FRAUD

    Directory of Open Access Journals (Sweden)

    DANISH JAMIL,

    2011-03-01

    Full Text Available In the past years, global access to information has become available at all time through different network architectures and computers for an ever-changing target of employees, suppliers, and clients. In thissense, Internet has been defining the latest trends for the online companies and their customers. Together with the growth of the role that Internet plays in the continuous extending of the online environment as a potential for business, also increased the chances of online malicious attacks and intrusions. They all have at their basis the stealing of user’s identity. User names and passwords areweak and can always be cracked with a little effort from the attacker's side. Users credentials can be phished, stolen, discovered and hacked in multiple ways. In order to contra-attack the new growingthreats, efficient, rapid and reliable means for an automatic recognition of the identity of online users are being developed. Biometric security systems enable more secure authentication methods to access a computer's resources. This paper basically presents a developing biometric access control measure: computer access via keystroke pattern recognition and discusses its direct connection to preventing electronic identity thefts.

  10. A Neural Network Recognition Method of Shape Pattern

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    A new pattern recognition method of shape was presented based onartificial neural network theory. The method avoids the defects of shape pattern recognition with polynomials and it has strong disturbance resistance. It has been proved to be superior in recognizing different shape patterns by identifying many sorts of working sample books which the results are known.

  11. Searching for pulsars using image pattern recognition

    CERN Document Server

    Zhu, W W; Madsen, E C; Tan, M; Stairs, I H; Brazier, A; Lazarus, P; Lynch, R; Scholz, P; Stovall, K; Random, S M; Banaszak, S; Biwer, C M; Cohen, S; Dartez, L P; Flanigan, J; Lunsford, G; Matinez, J G; Mata, A; Rohr, M; Walker, A; Allen, B; Bhat, N D R; Bogdanov, S; Camilo, F; Chatterjee, S; Cordes, J M; Crawford, F; Deneva, J S; Desvignes, G; Ferdman, R D; Hessels, J W T; Jenet, F A; Kaplan, D; Kaspi, V M; Knispel, B; Lee, K J; van Leeuwen, J; Lyne, A G; McLaughlin, M A; Spitler, L G

    2014-01-01

    In this paper, we present a novel artificial intelligence (AI) program that identifies pulsars from recent surv eys using image pattern recognition with deep neural nets---the PICS(Pulsar Image-based Classification System) AI. The AI mimics human experts and distinguishes pulsars from noise and interferences by looking for patterns from candidate. The information from each pulsar candidate is synthesized in four diagnostic plots, which consist of up to thousands pixel of image data. The AI takes these data from each candidate as its input and uses thousands of such candidates to train its $\\sim$9000 neurons. Different from other pulsar selection programs which use pre-designed patterns, the PICS AI teaches itself the salient features of different pulsars from a set of human-labeled candidates through machine learning. The deep neural networks in this AI system grant it superior ability in recognizing various types of pulsars as well as their harmonic signals. The trained AI's performance has been validated wi...

  12. Applications of Pattern Recognition in Drug Discovery

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    This is a brief account of the plenary talk given to the meeting of the Chinese Society of Chemical Science and Technology held in Oxford on 6 October 2001. The talk covered the application of pattern recognition techniques to discover molecules which will bind to the binding sites of proteins. Three situations were considered: the structure of the protein being unknown; the structure known but the binding site unknown; and finally, and this is the most important case for the future, both the structure and nature of the target site available in atomic detail. For this case we have developed a massively distributed computer program using a screensaver which now involves over one million personal computers, including over a thousand in China. The project will involve the screening of 3.5 billion small molecules against 16 protein targets, all of which are implicated in the process of cancer.

  13. Fabric Wrinkle Grade Assessment Based on Fuzzy Pattern Recognition

    Institute of Scientific and Technical Information of China (English)

    YANG Xiao-bo

    2006-01-01

    The basic principle of fuzzy pattern recognition is brief introduced firstly in this paper, which mainly includes fuzzy rules and fuzzy inference system. Then, the algorithm procedure of fuzzy pattern recognition is proposed. Finally,the application of Mamdani fuzzy model is introduced to evaluate fabric wrinkle grade in detail, and used the correlation coefficient between subject and object evaluation to verify the reliability of fuzzy pattern recognition. It shows the method of fuzzy pattern recognition needs not a large number of testing data and the accuracy of evaluation is up to 97.38%.

  14. Pattern recognition with magnonic holographic memory device

    Energy Technology Data Exchange (ETDEWEB)

    Kozhevnikov, A.; Dudko, G.; Filimonov, Y. [Kotel' nikov Institute of Radioengineering and Electronics of Russian Academy of Sciences, Saratov Branch, Saratov 410019 (Russian Federation); Gertz, F.; Khitun, A. [Electrical Engineering Department, University of California - Riverside, Riverside, California 92521 (United States)

    2015-04-06

    In this work, we present experimental data demonstrating the possibility of using magnonic holographic devices for pattern recognition. The prototype eight-terminal device consists of a magnetic matrix with micro-antennas placed on the periphery of the matrix to excite and detect spin waves. The principle of operation is based on the effect of spin wave interference, which is similar to the operation of optical holographic devices. Input information is encoded in the phases of the spin waves generated on the edges of the magnonic matrix, while the output corresponds to the amplitude of the inductive voltage produced by the interfering spin waves on the other side of the matrix. The level of the output voltage depends on the combination of the input phases as well as on the internal structure of the magnonic matrix. Experimental data collected for several magnonic matrixes show the unique output signatures in which maxima and minima correspond to specific input phase patterns. Potentially, magnonic holographic devices may provide a higher storage density compare to optical counterparts due to a shorter wavelength and compatibility with conventional electronic devices. The challenges and shortcoming of the magnonic holographic devices are also discussed.

  15. Proteins pattern alteration in AZT-treated K562 cells detected by two-dimensional gel electrophoresis and peptide mass fingerprinting

    Directory of Open Access Journals (Sweden)

    Mignogna Giuseppina

    2006-03-01

    Full Text Available Abstract In this study we report the effect of AZT on the whole protein expression profile both in the control and the AZT-treated K562 cells, evidenced by two-dimensional gel electrophoresis and peptide mass fingerprinting analysis. Two-dimensional gels computer digital image analysis showed two spots that appeared up-regulated in AZT-treated cells and one spot present only in the drug exposed samples. Upon extraction and analysis by peptide mass fingerprinting, the first two spots were identified as PDI-A3 and stathmin, while the third one was proved to be NDPK-A. Conversely, two protein spots were present only in the untreated K562 cells, and were identified as SOD1 and HSP-60, respectively.

  16. Pattern recognition with discrete and mixed data : theory and practice

    NARCIS (Netherlands)

    C.E.A. Queiros (Carlos)

    1988-01-01

    textabstractThis thesis is devoted to aspects related to the analysis of medical data bases in the context of pattern recognition. It contains both theoretical aspects and practical applications and its scope includes questions and problems that arise when applying pattern recognition methods and te

  17. Pattern Recognition Based Detection Recognition of Traffic Sign Using SVM

    Directory of Open Access Journals (Sweden)

    S. Sathiya

    2014-05-01

    Full Text Available The objective of this work describes a method for Traffic sign detection and recognition from the traffic panel board(signage. It detect the traffic signs especially for Indian conditions. Images are acquired through the camera and it is invariant to size then it is scaled. It consist of the following steps, first, it detect the traffic sign, if it has sufficient contrast from the background then we use sobel edge detection technique and morphological dilation. Second, extract the detected traffic sign from the board using row count and column count. Third, to extract the feature using DCT, DWT and Hybrid DWT-DCT. In training phase, DCT 20 highest energy coefficients are extracted, In DWT 300 features extracted from each traffic sign and in Hybrid DWT-DCT 20 features are extracted. Finally recognition are performed through SVM. The application is to improve the efficiency of transportation networks through applications of communication visually impaired person wear the camera to identify the traffic destination board. Experimental results show that state-of-the-art algorithms obtains highly competitive performance and is especially efficient to different levels of corruptions. The performance of Traffic Sign recognition is evaluated for Traffic Sign board image and the system achieves a recognition rate of 86% using DCT, 90% using DWT and 96% using Hybrid DWT-DCT and SVM.

  18. Pattern-recognition receptors in human eosinophils.

    Science.gov (United States)

    Kvarnhammar, Anne Månsson; Cardell, Lars Olaf

    2012-05-01

    The pattern-recognition receptor (PRR) family includes Toll-like receptors (TLRs), nucleotide-binding oligomerization domain (NOD) -like receptors (NLRs), RIG-I-like receptors (RLRs), C-type lectin receptors (CLRs) and the receptor for advanced glycation end products (RAGE). They recognize various microbial signatures or host-derived danger signals and trigger an immune response. Eosinophils are multifunctional leucocytes involved in the pathogenesis of several inflammatory processes, including parasitic helminth infection, allergic diseases, tissue injury and tumour immunity. Human eosinophils express several PRRs, including TLR1-5, TLR7, TLR9, NOD1, NOD2, Dectin-1 and RAGE. Receptor stimulation induces survival, oxidative burst, activation of the adhesion system and release of cytokines (interleukin-1β, interleukin-6, tumour necrosis factor-α and granulocyte-macrophage colony-stimulating factor), chemokines (interleukin-8 and growth-related oncogene-α) and cytotoxic granule proteins (eosinophil cationic protein, eosinophil-derived neurotoxin, eosinophil peroxidase and major basic protein). It is also evident that eosinophils play an immunomodulatory role by interacting with surrounding cells. The presence of a broad range of PRRs in eosinophils indicates that they are not only involved in defence against parasitic helminths, but also against bacteria, viruses and fungi. From a clinical perspective, eosinophilic PRRs seem to be involved in both allergic and malignant diseases by causing exacerbations and affecting tumour growth, respectively.

  19. Online and Offline Pattern Recognition in PANDA

    Science.gov (United States)

    Boca, Gianluigi

    2016-11-01

    PANDA is one of the four experiments that will run at the new facility FAIR that is being built in Darmstadt, Germany. It is a fixed target experiment: a beam of antiprotons collides on a jet proton target (the maximum center of mass energy is 5.46 GeV). The interaction rate at the startup will be 2MHz with the goal of reaching 20MHz at full luminosity. The beam of antiprotons will be essentially continuous. PANDA will have NO hardware trigger but only a software trigger, to allow for maximum flexibility in the physics program. All those characteristics are severe challenges for the reconstruction code that 1) must be fast, since it has to be validated up to 20MHz interaction rate; 2) must be able to reject fake tracks caused by the remnant hits, belonging to previous or later events in some slow detectors, for example the straw tubes in the central region. The Pattern Recognition (PR) of PANDA will have to run both online to achieve a first fast selection, and offline, at lower rate, for a more refined selection. In PANDA the PR code is continuously evolving; this contribution shows the present status. I will give an overview of three examples of PR following different strategies and/or implemented on different hardware (FPGA, GPUs, CPUs) and, when available, I will report the performances.

  20. Online and Offline Pattern Recognition in PANDA

    Directory of Open Access Journals (Sweden)

    Boca Gianluigi

    2016-01-01

    Full Text Available PANDA is one of the four experiments that will run at the new facility FAIR that is being built in Darmstadt, Germany. It is a fixed target experiment: a beam of antiprotons collides on a jet proton target (the maximum center of mass energy is 5.46 GeV. The interaction rate at the startup will be 2MHz with the goal of reaching 20MHz at full luminosity. The beam of antiprotons will be essentially continuous. PANDA will have NO hardware trigger but only a software trigger, to allow for maximum flexibility in the physics program. All those characteristics are severe challenges for the reconstruction code that 1 must be fast, since it has to be validated up to 20MHz interaction rate; 2 must be able to reject fake tracks caused by the remnant hits, belonging to previous or later events in some slow detectors, for example the straw tubes in the central region. The Pattern Recognition (PR of PANDA will have to run both online to achieve a first fast selection, and offline, at lower rate, for a more refined selection. In PANDA the PR code is continuously evolving; this contribution shows the present status. I will give an overview of three examples of PR following different strategies and/or implemented on different hardware (FPGA, GPUs, CPUs and, when available, I will report the performances.

  1. Analysis of Two-Dimensional Electrophoresis Gel Images

    DEFF Research Database (Denmark)

    Pedersen, Lars

    2002-01-01

    This thesis describes and proposes solutions to some of the currently most important problems in pattern recognition and image analysis of two-dimensional gel electrophoresis (2DGE) images. 2DGE is the leading technique to separate individual proteins in biological samples with many biological...... the methods developed in the literature specifically for matching protein spot patterns, the focus is on a method based on neighbourhood relations. These methods are applied to a range of 2DGE protein spot data in a comparative study. The point pattern matching requires segmentation of the gel images...... and since the correct image segmentation can be difficult, a new alternative approach, exploiting prior knowledge from a reference gel about the protein locations to segment an incoming gel image, is proposed....

  2. Application Of t-Cherry Junction Trees in Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Edith Kovacs

    2010-06-01

    Full Text Available Pattern recognition aims to classify data (patterns based ei-
    ther on a priori knowledge or on statistical information extracted from the data. In this paper we will concentrate on statistical pattern recognition using a new probabilistic approach which makes possible to select the so called 'informative' features. We develop a pattern recognition algorithm which is based on the conditional independence structure underlying the statistical data. Our method was succesfully applied on a real problem of recognizing Parkinson's disease on the basis of voice disorders.

  3. Pattern recognition receptors and gastric cancer

    Directory of Open Access Journals (Sweden)

    Natalia eCastaño-Rodriguez

    2014-07-01

    Full Text Available Chronic inflammation has been associated with an increased risk of several human malignancies, a classic example being gastric cancer (GC. Development of GC is known to result from infection of the gastric mucosa by Helicobacter pylori, which initially induces acute inflammation and, in a subset of patients, progresses over time to chronic inflammation, gastric atrophy, intestinal metaplasia, dysplasia and finally intestinal-type GC.Germ-line encoded receptors known as pattern-recognition receptors (PRRs are critical for generating mature pro-inflammatory cytokines that are crucial for both Th1 and Th2 responses. Given that H. pylori is initially targeted by PRRs, it is conceivable that dysfunction within genes of this arm of the immune system could modulate the host response against H. pylori infection, and subsequently influence the emergence of GC.Current evidence suggests that Toll-like receptors (TLRs (TLR2, TLR3, TLR4, TLR5 and TLR9, nucleotide-binding oligomerization domain (NOD-like receptors (NLRs (NOD1, NOD2 and NLRP3, a C-type lectin receptor (DC-SIGN and retinoic acid-inducible gene (RIG-I-like receptors (RIG-I and MDA5, are involved in both the recognition of H. pylori and gastric carcinogenesis. In addition, polymorphisms in genes involved in the TLR (TLR1, TLR2, TLR4, TLR5, TLR9 and CD14 and NLR (NOD1, NOD2, NLRP3, NLRP12, NLRX1, CASP1, ASC and CARD8 signalling pathways have been shown to modulate the risk of H. pylori infection, gastric precancerous lesions and/or GC. Further, the modulation of PRRs has been suggested to suppress H. pylori-induced inflammation and enhance GC cell apoptosis, highlighting their potential relevance in GC therapeutics. In this review, we present current advances in our understanding of the role of the TLR and NLR signalling pathways in the pathogenesis of GC, address the involvement of other recently identified PRRs in GC, and discuss the potential implications of PRRs in GC immunotherapy.

  4. Searching for Pulsars Using Image Pattern Recognition

    Science.gov (United States)

    Zhu, W. W.; Berndsen, A.; Madsen, E. C.; Tan, M.; Stairs, I. H.; Brazier, A.; Lazarus, P.; Lynch, R.; Scholz, P.; Stovall, K.; Ransom, S. M.; Banaszak, S.; Biwer, C. M.; Cohen, S.; Dartez, L. P.; Flanigan, J.; Lunsford, G.; Martinez, J. G.; Mata, A.; Rohr, M.; Walker, A.; Allen, B.; Bhat, N. D. R.; Bogdanov, S.; Camilo, F.; Chatterjee, S.; Cordes, J. M.; Crawford, F.; Deneva, J. S.; Desvignes, G.; Ferdman, R. D.; Freire, P. C. C.; Hessels, J. W. T.; Jenet, F. A.; Kaplan, D. L.; Kaspi, V. M.; Knispel, B.; Lee, K. J.; van Leeuwen, J.; Lyne, A. G.; McLaughlin, M. A.; Siemens, X.; Spitler, L. G.; Venkataraman, A.

    2014-02-01

    In the modern era of big data, many fields of astronomy are generating huge volumes of data, the analysis of which can sometimes be the limiting factor in research. Fortunately, computer scientists have developed powerful data-mining techniques that can be applied to various fields. In this paper, we present a novel artificial intelligence (AI) program that identifies pulsars from recent surveys by using image pattern recognition with deep neural nets—the PICS (Pulsar Image-based Classification System) AI. The AI mimics human experts and distinguishes pulsars from noise and interference by looking for patterns from candidate plots. Different from other pulsar selection programs that search for expected patterns, the PICS AI is taught the salient features of different pulsars from a set of human-labeled candidates through machine learning. The training candidates are collected from the Pulsar Arecibo L-band Feed Array (PALFA) survey. The information from each pulsar candidate is synthesized in four diagnostic plots, which consist of image data with up to thousands of pixels. The AI takes these data from each candidate as its input and uses thousands of such candidates to train its ~9000 neurons. The deep neural networks in this AI system grant it superior ability to recognize various types of pulsars as well as their harmonic signals. The trained AI's performance has been validated with a large set of candidates from a different pulsar survey, the Green Bank North Celestial Cap survey. In this completely independent test, the PICS ranked 264 out of 277 pulsar-related candidates, including all 56 previously known pulsars and 208 of their harmonics, in the top 961 (1%) of 90,008 test candidates, missing only 13 harmonics. The first non-pulsar candidate appears at rank 187, following 45 pulsars and 141 harmonics. In other words, 100% of the pulsars were ranked in the top 1% of all candidates, while 80% were ranked higher than any noise or interference. The

  5. Searching for pulsars using image pattern recognition

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, W. W.; Berndsen, A.; Madsen, E. C.; Tan, M.; Stairs, I. H. [Department of Physics and Astronomy, 6224 Agricultural Road, University of British Columbia, Vancouver, BC, V6T 1Z1 (Canada); Brazier, A. [Astronomy Department, Cornell University, Ithaca, NY 14853 (United States); Lazarus, P. [Max-Planck-Institut für Radioastronomie, Auf dem Hügel 69, D-53121 Bonn (Germany); Lynch, R.; Scholz, P. [Department of Physics, McGill University, Montreal, QC H3A 2T8 (Canada); Stovall, K.; Cohen, S.; Dartez, L. P.; Lunsford, G.; Martinez, J. G.; Mata, A. [Center for Advanced Radio Astronomy, University of Texas at Brownsville, Brownsville, TX 78520 (United States); Ransom, S. M. [NRAO, Charlottesville, VA 22903 (United States); Banaszak, S.; Biwer, C. M.; Flanigan, J.; Rohr, M., E-mail: zhuww@phas.ubc.ca, E-mail: berndsen@phas.ubc.ca [Center for Gravitation, Cosmology and Astrophysics. University of Wisconsin Milwaukee, Milwaukee, WI 53211 (United States); and others

    2014-02-01

    In the modern era of big data, many fields of astronomy are generating huge volumes of data, the analysis of which can sometimes be the limiting factor in research. Fortunately, computer scientists have developed powerful data-mining techniques that can be applied to various fields. In this paper, we present a novel artificial intelligence (AI) program that identifies pulsars from recent surveys by using image pattern recognition with deep neural nets—the PICS (Pulsar Image-based Classification System) AI. The AI mimics human experts and distinguishes pulsars from noise and interference by looking for patterns from candidate plots. Different from other pulsar selection programs that search for expected patterns, the PICS AI is taught the salient features of different pulsars from a set of human-labeled candidates through machine learning. The training candidates are collected from the Pulsar Arecibo L-band Feed Array (PALFA) survey. The information from each pulsar candidate is synthesized in four diagnostic plots, which consist of image data with up to thousands of pixels. The AI takes these data from each candidate as its input and uses thousands of such candidates to train its ∼9000 neurons. The deep neural networks in this AI system grant it superior ability to recognize various types of pulsars as well as their harmonic signals. The trained AI's performance has been validated with a large set of candidates from a different pulsar survey, the Green Bank North Celestial Cap survey. In this completely independent test, the PICS ranked 264 out of 277 pulsar-related candidates, including all 56 previously known pulsars and 208 of their harmonics, in the top 961 (1%) of 90,008 test candidates, missing only 13 harmonics. The first non-pulsar candidate appears at rank 187, following 45 pulsars and 141 harmonics. In other words, 100% of the pulsars were ranked in the top 1% of all candidates, while 80% were ranked higher than any noise or interference. The

  6. Star pattern recognition method based on neural network

    Institute of Scientific and Technical Information of China (English)

    LI Chunyan; LI Ke; ZHANG Longyun; JIN Shengzhen; ZU Jifeng

    2003-01-01

    Star sensor is an avionics instrument used to provide the absolute 3-axis attitude of a spacecraft by utilizing star observations. The key function is to recognize the observed stars by comparing them with the reference catalogue. Autonomous star pattern recognition requires that similar patterns can be distinguished from each other with a small training set. Therefore, a new method based on neural network technology is proposed and a recognition system containing parallel backpropagation (BP) multi-subnets is designed. The simulation results show that the method performs much better than traditional algorithms and the proposed system can achieve both higher recognition accuracy and faster recognition speed.

  7. Very Large Scale Integration of Nano-Patterned YBa2Cu3O7-delta Josephson Junctions in a Two-Dimensional Array

    Energy Technology Data Exchange (ETDEWEB)

    Cybart, Shane A; Anton, Steven; Wu, Stephen; Clarke, John; Dynes, Robert

    2009-09-01

    Very large scale integration of Josephson junctions in a two-dimensional series-parallel array has been achieved by ion irradiating a YBa{sub 2}Cu{sub 3}O{sub 7-{delta}} film through slits in a nano-fabricated mask created with electron beam lithography and reactive ion etching. The mask consisted of 15,820 high-aspect ratio (20:1), 35-nm wide slits that restricted the irradiation in the film below to form Josephson junctions. Characterizing each parallel segment k, containing 28 junctions, with a single critical current I{sub ck} we found a standard deviation in I{sub ck} of about 16%.

  8. The Pandora Software Development Kit for Pattern Recognition

    CERN Document Server

    Marshall, J S

    2015-01-01

    running pattern recognition algorithms. The Pandora Application Programming Interfaces ensure simple specification of the building-blocks defining a pattern recognition problem. The logic required to solve the problem is implemented in algorithms. The algorithms request operations to create or modify data structures and the operations are performed by the Pandora framework. This design promotes an approach using many decoupled algorithms, each addressing specific topologies. Details of algorithms addressing two pattern recognition problems in High Energy Physics are presented: reconstruction of events at a high-energy e+e- linear collider and reconstruction of cosmic ray or neutrino events in a liquid argon time projection chamber.

  9. Pattern recognition in service of people with disabilities

    CSIR Research Space (South Africa)

    Coetzee, L

    2004-11-01

    Full Text Available This paper analyses a number of disabilities, their assistive devices and the associated technologies in order to highlight the role pattern recognition plays in enabling accessibility and improving human computer interaction for people living...

  10. Applications of evolutionary computation in image processing and pattern recognition

    CERN Document Server

    Cuevas, Erik; Perez-Cisneros, Marco

    2016-01-01

    This book presents the use of efficient Evolutionary Computation (EC) algorithms for solving diverse real-world image processing and pattern recognition problems. It provides an overview of the different aspects of evolutionary methods in order to enable the reader in reaching a global understanding of the field and, in conducting studies on specific evolutionary techniques that are related to applications in image processing and pattern recognition. It explains the basic ideas of the proposed applications in a way that can also be understood by readers outside of the field. Image processing and pattern recognition practitioners who are not evolutionary computation researchers will appreciate the discussed techniques beyond simple theoretical tools since they have been adapted to solve significant problems that commonly arise on such areas. On the other hand, members of the evolutionary computation community can learn the way in which image processing and pattern recognition problems can be translated into an...

  11. The Pandora software development kit for pattern recognition

    Energy Technology Data Exchange (ETDEWEB)

    Marshall, J.S.; Thomson, M.A. [University of Cambridge, Cavendish Laboratory, Cambridge (United Kingdom)

    2015-09-15

    The development of automated solutions to pattern recognition problems is important in many areas of scientific research and human endeavour. This paper describes the implementation of the Pandora software development kit, which aids the process of designing, implementing and running pattern recognition algorithms. The Pandora Application Programming Interfaces ensure simple specification of the building-blocks defining a pattern recognition problem. The logic required to solve the problem is implemented in algorithms. The algorithms request operations to create or modify data structures and the operations are performed by the Pandora framework. This design promotes an approach using many decoupled algorithms, each addressing specific topologies. Details of algorithms addressing two pattern recognition problems in High Energy Physics are presented: reconstruction of events at a high-energy e{sup +}e{sup -} linear collider and reconstruction of cosmic ray or neutrino events in a liquid argon time projection chamber. (orig.)

  12. Scalable pattern recognition algorithms applications in computational biology and bioinformatics

    CERN Document Server

    Maji, Pradipta

    2014-01-01

    Reviews the development of scalable pattern recognition algorithms for computational biology and bioinformatics Includes numerous examples and experimental results to support the theoretical concepts described Concludes each chapter with directions for future research and a comprehensive bibliography

  13. Data analysis and pattern recognition in multiple databases

    CERN Document Server

    Adhikari, Animesh; Pedrycz, Witold

    2014-01-01

    Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types of data analyses are bound to change. Since the number of data collection channels increases in the recent time and becomes more diversified, many real-world data mining tasks can easily acquire multiple databases from various sources. In these cases, data mining becomes more challenging for several essential reasons. We may encounter sensitive data originating from different sources - those cannot be amalgamated. Even if we are allowed to place different data together, we are certainly not able to analyse them when local identities of patterns are required to be retained. Thus, pattern recognition in multiple databases gives rise to a suite of new, challenging problems different from those encountered before. Association rule mining, global pattern discovery, and mining patterns of select items provide different...

  14. Classification of Simultaneous Movements using Surface EMG Pattern Recognition

    OpenAIRE

    Young, Aaron J.; Smith, Lauren H.; Rouse, Elliott J.; Hargrove, Levi J.

    2012-01-01

    Advanced upper-limb prostheses capable of actuating multiple degrees of freedom (DOF) are now commercially available. Pattern recognition algorithms that use surface electromyography (EMG) signals show great promise as multi-DOF controllers. Unfortunately, current pattern recognition systems are limited to activate only one degree of freedom at a time. This study introduces a novel classifier based on Bayesian theory to provide classification of simultaneous movements. This approach and two o...

  15. Data Mining and Pattern Recognition Models for Identifying Inherited Diseases

    DEFF Research Database (Denmark)

    Iddamalgoda, Lahiru; Das, Partha S; Aponso, Achala;

    2016-01-01

    Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately...... prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification- and scoring-based prioritization methods...

  16. MOVING TARGETS PATTERN RECOGNITION BASED ON THE WAVELET NEURAL NETWORK

    Institute of Scientific and Technical Information of China (English)

    Ge Guangying; Chen Lili; Xu Jianjian

    2005-01-01

    Based on pattern recognition theory and neural network technology, moving objects automatic detection and classification method integrating advanced wavelet analysis are discussed in detail. An algorithm of moving targets pattern recognition on the combination of inter-frame difference and wavelet neural network is presented. The experimental results indicate that the designed BP wavelet network using this algorithm can recognize and classify moving targets rapidly and effectively.

  17. Hopfield's Model of Patterns Recognition and Laws of Artistic Perception

    Science.gov (United States)

    Yevin, Igor; Koblyakov, Alexander

    The model of patterns recognition or attractor network model of associative memory, offered by J.Hopfield 1982, is the most known model in theoretical neuroscience. This paper aims to show, that such well-known laws of art perception as the Wundt curve, perception of visual ambiguity in art, and also the model perception of musical tonalities are nothing else than special cases of the Hopfield’s model of patterns recognition.

  18. Face recognition system and method using face pattern words and face pattern bytes

    Energy Technology Data Exchange (ETDEWEB)

    Zheng, Yufeng

    2014-12-23

    The present invention provides a novel system and method for identifying individuals and for face recognition utilizing facial features for face identification. The system and method of the invention comprise creating facial features or face patterns called face pattern words and face pattern bytes for face identification. The invention also provides for pattern recognitions for identification other than face recognition. The invention further provides a means for identifying individuals based on visible and/or thermal images of those individuals by utilizing computer software implemented by instructions on a computer or computer system and a computer readable medium containing instructions on a computer system for face recognition and identification.

  19. Type-2 fuzzy graphical models for pattern recognition

    CERN Document Server

    Zeng, Jia

    2015-01-01

    This book discusses how to combine type-2 fuzzy sets and graphical models to solve a range of real-world pattern recognition problems such as speech recognition, handwritten Chinese character recognition, topic modeling as well as human action recognition. It covers these recent developments while also providing a comprehensive introduction to the fields of type-2 fuzzy sets and graphical models. Though primarily intended for graduate students, researchers and practitioners in fuzzy logic and pattern recognition, the book can also serve as a valuable reference work for researchers without any previous knowledge of these fields. Dr. Jia Zeng is a Professor at the School of Computer Science and Technology, Soochow University, China. Dr. Zhi-Qiang Liu is a Professor at the School of Creative Media, City University of Hong Kong, China.

  20. Emotion recognition a pattern analysis approach

    CERN Document Server

    Konar, Amit

    2014-01-01

    Offers both foundations and advances on emotion recognition in a single volumeProvides a thorough and insightful introduction to the subject by utilizing computational tools of diverse domainsInspires young researchers to prepare themselves for their own researchDemonstrates direction of future research through new technologies, such as Microsoft Kinect, EEG systems etc.

  1. Detection and recognition of angular frequency patterns.

    Science.gov (United States)

    Wilson, Hugh R; Propp, Roni

    2015-05-01

    Previous research has extensively explored visual encoding of smoothly curved, closed contours described by sinusoidal variation of pattern radius as a function of polar angle (RF patterns). Although the contours of many biologically significant objects are curved, we also confront shapes with a more jagged and angular appearance. To study these, we introduce here a novel class of visual stimuli that deform smoothly from a circle to an equilateral polygon with N sides (AF patterns). Threshold measurements reveal that both AF and RF patterns can be discriminated from circles at the same deformation amplitude, approximately 18.0arcsec, which is in the hyperacuity range. Thresholds were slightly higher for patterns with 3.0 cycles than for those with 5.0 cycles. Discrimination between AF and RF patterns was 75% correct at an amplitude that was approximately 3.0 times the threshold amplitude, which implies that AF and RF patterns activate different neural populations. Experiments with jittered patterns in which the contour was broken into several pieces and shifted inward or outward had much less effect on AF patterns than on RF patterns. Similarly, thresholds for single angles of AF patterns showed no significant difference from thresholds for the entire AF pattern. Taken together, these results imply that the visual system incorporates angles explicitly in the representation of closed object contours, but it suggests that angular contours are represented more locally than are curved contours.

  2. Electrocardiogram (ECG) pattern modeling and recognition via deterministic learning

    Institute of Scientific and Technical Information of China (English)

    Xunde DONG; Cong WANG; Junmin HU; Shanxing OU

    2014-01-01

    A method for electrocardiogram (ECG) pattern modeling and recognition via deterministic learning theory is presented in this paper. Instead of recognizing ECG signals beat-to-beat, each ECG signal which contains a number of heartbeats is recognized. The method is based entirely on the temporal features (i.e., the dynamics) of ECG patterns, which contains complete information of ECG patterns. A dynamical model is employed to demonstrate the method, which is capable of generating synthetic ECG signals. Based on the dynamical model, the method is shown in the following two phases:the identification (training) phase and the recognition (test) phase. In the identification phase, the dynamics of ECG patterns is accurately modeled and expressed as constant RBF neural weights through the deterministic learning. In the recognition phase, the modeling results are used for ECG pattern recognition. The main feature of the proposed method is that the dynamics of ECG patterns is accurately modeled and is used for ECG pattern recognition. Experimental studies using the Physikalisch-Technische Bundesanstalt (PTB) database are included to demonstrate the effectiveness of the approach.

  3. Recognition of control chart patterns with incomplete samples

    Science.gov (United States)

    Miftah Abdelrahman Senoussi, Ahmed; Masood, Ibrahim; Nasrull Abdol Rahman, Mohd; Fahrul Hassan, Mohd

    2017-08-01

    In quality control, automated recognition of statistical process control (SPC) chart patterns is an effective technique for monitoring unnatural variation (UV) in manufacturing process. In most studies, focus was given on complete patterns by assuming there is no constrain in the SPC samples. Nevertheless, there is in-practice case whereby the SPC samples cannot be captured properly due to measurement sensor error or human error. Thus, this research aims to design a recognition scheme for incomplete samples pattern that will be useful for an industrial application. The design methodology involves three phases: (i) simulation of UV and SPC chart patterns, (ii) design of pattern recognition scheme, and (iii) evaluation of performance recognition. It involves modelling of the simulated SPC samples in bivariate quality control, raw data input representation, and recognizer training and testing. The proposed technique indicates a high recognition accuracy (normal pattern = 99.5%, shift patterns = 97.5%). This research will provide a new perspective in SPC charting scheme when dealing with constraint in terms of incomplete samples, which is greatly useful for an industrial practitioner in finding the solution for corrective action.

  4. Face Recognition (Patterns Matching & Bio-Metrics

    Directory of Open Access Journals (Sweden)

    Jignesh Dhirubhai Hirapara

    2012-08-01

    Full Text Available Government agencies are investing a considerable amount of resources into improving security systems as result of recent terrorist events that dangerously exposed flaws and weaknesses in today’s safety mechanisms. Badge or password-based authentication procedures are too easy to hack. Biometrics represents a valid alternative but they suffer of drawbacks as well. Iris scanning, for example, is very reliable but too intrusive; fingerprints are socially accepted, but not applicable to non-con sentient people. On the other hand, face recognition represents a good compromise between what’s socially acceptable and what’s reliable, even when operating under controlled conditions. In last decade, many algorithms based on linear/nonlinear methods, neural networks, wavelets, etc. have been proposed. Nevertheless, Face Recognition Vendor Test 2002 shown that most of these approaches encountered problems in outdoor conditions. This lowered their reliability compared to state of the art biometrics.

  5. Evaluation of protein pattern changes in roots and leaves of Zea mays plants in response to nitrate availability by two-dimensional gel electrophoresis analysis

    Directory of Open Access Journals (Sweden)

    Cocucci Maurizio

    2009-08-01

    Full Text Available Abstract Background Nitrogen nutrition is one of the major factors that limit growth and production of crop plants. It affects many processes, such as development, architecture, flowering, senescence and photosynthesis. Although the improvement in technologies for protein study and the widening of gene sequences have made possible the study of the plant proteomes, only limited information on proteome changes occurring in response to nitrogen amount are available up to now. In this work, two-dimensional gel electrophoresis (2-DE has been used to investigate the protein changes induced by NO3- concentration in both roots and leaves of maize (Zea mays L. plants. Moreover, in order to better evaluate the proteomic results, some biochemical and physiological parameters were measured. Results Through 2-DE analysis, 20 and 18 spots that significantly changed their amount at least two folds in response to nitrate addition to the growth medium of starved maize plants were found in roots and leaves, respectively. Most of these spots were identified by Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometry (LC-ESI-MS/MS. In roots, many of these changes were referred to enzymes involved in nitrate assimilation and in metabolic pathways implicated in the balance of the energy and redox status of the cell, among which the pentose phosphate pathway. In leaves, most of the characterized proteins were related to regulation of photosynthesis. Moreover, the up-accumulation of lipoxygenase 10 indicated that the leaf response to a high availability of nitrate may also involve a modification in lipid metabolism. Finally, this proteomic approach suggested that the nutritional status of the plant may affect two different post-translational modifications of phosphoenolpyruvate carboxylase (PEPCase consisting in monoubiquitination and phosphorylation in roots and leaves, respectively. Conclusion This work provides a first characterization of the proteome

  6. Is having similar eye movement patterns during face learning and recognition beneficial for recognition performance? Evidence from hidden Markov modeling.

    Science.gov (United States)

    Chuk, Tim; Chan, Antoni B; Hsiao, Janet H

    2017-05-04

    The hidden Markov model (HMM)-based approach for eye movement analysis is able to reflect individual differences in both spatial and temporal aspects of eye movements. Here we used this approach to understand the relationship between eye movements during face learning and recognition, and its association with recognition performance. We discovered holistic (i.e., mainly looking at the face center) and analytic (i.e., specifically looking at the two eyes in addition to the face center) patterns during both learning and recognition. Although for both learning and recognition, participants who adopted analytic patterns had better recognition performance than those with holistic patterns, a significant positive correlation between the likelihood of participants' patterns being classified as analytic and their recognition performance was only observed during recognition. Significantly more participants adopted holistic patterns during learning than recognition. Interestingly, about 40% of the participants used different patterns between learning and recognition, and among them 90% switched their patterns from holistic at learning to analytic at recognition. In contrast to the scan path theory, which posits that eye movements during learning have to be recapitulated during recognition for the recognition to be successful, participants who used the same or different patterns during learning and recognition did not differ in recognition performance. The similarity between their learning and recognition eye movement patterns also did not correlate with their recognition performance. These findings suggested that perceptuomotor memory elicited by eye movement patterns during learning does not play an important role in recognition. In contrast, the retrieval of diagnostic information for recognition, such as the eyes for face recognition, is a better predictor for recognition performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Postprocessing for character recognition using pattern features and linguistic information

    Science.gov (United States)

    Yoshikawa, Takatoshi; Okamoto, Masayosi; Horii, Hiroshi

    1993-04-01

    We propose a new method of post-processing for character recognition using pattern features and linguistic information. This method corrects errors in the recognition of handwritten Japanese sentences containing Kanji characters. This post-process method is characterized by having two types of character recognition. Improving the accuracy of the character recognition rate of Japanese characters is made difficult by the large number of characters, and the existence of characters with similar patterns. Therefore, it is not practical for a character recognition system to recognize all characters in detail. First, this post-processing method generates a candidate character table by recognizing the simplest features of characters. Then, it selects words corresponding to the character from the candidate character table by referring to a word and grammar dictionary before selecting suitable words. If the correct character is included in the candidate character table, this process can correct an error, however, if the character is not included, it cannot correct an error. Therefore, if this method can presume a character does not exist in a candidate character table by using linguistic information (word and grammar dictionary). It then can verify a presumed character by character recognition using complex features. When this method is applied to an online character recognition system, the accuracy of character recognition improves 93.5% to 94.7%. This proved to be the case when it was used for the editorials of a Japanese newspaper (Asahi Shinbun).

  8. Biometric verification based on grip-pattern recognition

    NARCIS (Netherlands)

    Veldhuis, Raymond; Bazen, Asker; Kauffman, Joost; Hartel, Pieter

    2004-01-01

    This paper describes the design, implementation and evaluation of a user-verification system for a smart gun, which is based on grip-pattern recognition. An existing pressure sensor consisting of an array of 44 £ 44 piezoresistive elements is used to measure the grip pattern. An interface has been d

  9. Biometric verification based on grip-pattern recognition

    NARCIS (Netherlands)

    Veldhuis, Raymond N.J.; Bazen, A.M.; Kauffman, J.A.; Hartel, Pieter H.; Delp, Edward J.; Wong, Ping W.

    This paper describes the design, implementation and evaluation of a user-verification system for a smart gun, which is based on grip-pattern recognition. An existing pressure sensor consisting of an array of 44 x 44 piezoresistive elements is used to measure the grip pattern. An interface has been

  10. Knowledge-based methodology in pattern recognition and understanding

    OpenAIRE

    Haton, Jean-Paul

    1987-01-01

    The interpretation and understanding of complex patterns (e.g. speech, images or other kinds of mono- or multi-dimensional signals) is related both to pattern recognition and artificial intelligence since it necessitates numerical processing as well as symbolic knoledge-based reasoning techniques. This paper presents a state-of-the-art in the field, including basic concepts and practical applications.

  11. Pattern association--a key to recognition of shark attacks.

    Science.gov (United States)

    Cirillo, G; James, H

    2004-12-01

    Investigation of a number of shark attacks in South Australian waters has lead to recognition of pattern similarities on equipment recovered from the scene of such attacks. Six cases are presented in which a common pattern of striations has been noted.

  12. Optimization of fuzzy logic analysis by diagonals for pattern recognition

    Science.gov (United States)

    Habiballa, Hashim; Hires, Matej

    2017-07-01

    The article presents an optimization of the fuzzy logic analysis method for pattern recognition. The enhancements of the original method through the usage of additional two types of pattern components - leftwise diagonal and rightwise diagonal ones. The method is described in theoretical background and further articles show the implementation and experimental verification of the approach.

  13. Pattern Recognition of mtDNA with Associative Models

    Directory of Open Access Journals (Sweden)

    Acevedo María Elena

    2016-01-01

    Full Text Available In this paper we applied an associative memory for the pattern recognition of mtDNA that can be useful to identify bodies and human remains. In particular, we used both morphological hetroassociative memories: max and min. We process the problem of pattern recognition as a classification task. Our proposal showed a correct recall, we obtained the 100% of recalling of all the learned patterns. We simulated a corrupted sample of mtDNA by adding noise of two types: additive and subtractive. The memory showed a correct recall when we applied less or equal than 55% of both types of noise.

  14. Grasping Pattern Recognition and Grasping Force Estimation For Prosthetic Hands

    Directory of Open Access Journals (Sweden)

    Zhang Bing-Ke

    2016-01-01

    Full Text Available Human’s movement can be decoded by surface electromyography (EMG, and the prosthetic hand can be controlled freely through EMG signal. This paper proposes a grasping pattern and force synchronized decoding method for prosthetic hands. Considering pattern recognition and force estimation simultaneously, this paper analyzes whether different muscle contraction levels affect pattern recognition and whether different grasping modes have impact on force estimation, then proposes two schemes to complete EMG simultaneously decoding. Experiments compare the accuracy of the two methods. The results show that there is no much difference between two methods in force estimation, the former’s accuracy of pattern recognition is a little higher than the latter.

  15. Face Recognition Using Local Quantized Patterns and Gabor Filters

    Science.gov (United States)

    Khryashchev, V.; Priorov, A.; Stepanova, O.; Nikitin, A.

    2015-05-01

    The problem of face recognition in a natural or artificial environment has received a great deal of researchers' attention over the last few years. A lot of methods for accurate face recognition have been proposed. Nevertheless, these methods often fail to accurately recognize the person in difficult scenarios, e.g. low resolution, low contrast, pose variations, etc. We therefore propose an approach for accurate and robust face recognition by using local quantized patterns and Gabor filters. The estimation of the eye centers is used as a preprocessing stage. The evaluation of our algorithm on different samples from a standardized FERET database shows that our method is invariant to the general variations of lighting, expression, occlusion and aging. The proposed approach allows about 20% correct recognition accuracy increase compared with the known face recognition algorithms from the OpenCV library. The additional use of Gabor filters can significantly improve the robustness to changes in lighting conditions.

  16. Human cellular protein patterns and their link to genome DNA sequence data: usefulness of two-dimensional gel electrophoresis and microsequencing

    DEFF Research Database (Denmark)

    Celis, J E; Rasmussen, H H; Leffers, H;

    1991-01-01

    Analysis of cellular protein patterns by computer-aided 2-dimensional gel electrophoresis together with recent advances in protein sequence analysis have made possible the establishment of comprehensive 2-dimensional gel protein databases that may link protein and DNA information and that offer a...

  17. Existence problem of optical correlation based pattern recognition

    Institute of Scientific and Technical Information of China (English)

    ZHANG; Yanxin(张延炘); LI; Sumei(李素梅)

    2003-01-01

    The existence problem of optical correlation based pattern recognition, namely its range of validity and its limitation, is discussed in this paper conjointly with the function approximation theory of neural networks. The conclusion is that only if the sets to be recognized are linearly separable (which is rare) or the subsets, in which a segmental sample of the targets is involved,are linearly separable, can the classical 4f optical correlation system carry out the task of recognition inerrably. The recognition principle of a joint transform correlator is the same as that of a 4f system, and so is its range of validities. Based on the demonstration of the existence problem of optical correlation based pattern recognition an evaluation on some important problems that were studied in this field over the past 40 years is presented explicitly.

  18. Subspace methods for pattern recognition in intelligent environment

    CERN Document Server

    Jain, Lakhmi

    2014-01-01

    This research book provides a comprehensive overview of the state-of-the-art subspace learning methods for pattern recognition in intelligent environment. With the fast development of internet and computer technologies, the amount of available data is rapidly increasing in our daily life. How to extract core information or useful features is an important issue. Subspace methods are widely used for dimension reduction and feature extraction in pattern recognition. They transform a high-dimensional data to a lower-dimensional space (subspace), where most information is retained. The book covers a broad spectrum of subspace methods including linear, nonlinear and multilinear subspace learning methods and applications. The applications include face alignment, face recognition, medical image analysis, remote sensing image classification, traffic sign recognition, image clustering, super resolution, edge detection, multi-view facial image synthesis.

  19. Two-dimensional liquid chromatography

    DEFF Research Database (Denmark)

    Græsbøll, Rune

    of this thesis is on online comprehensive two-dimensional liquid chromatography (online LC×LC) with reverse phase in both dimensions (online RP×RP). Since online RP×RP has not been attempted before within this research group, a significant part of this thesis consists of knowledge and experience gained...

  20. The Relationship between Arithmetic and Reading Achievement and Visual Pattern Recognition in First Grade Children.

    Science.gov (United States)

    Bragman, Ruth; Hardy, Robert C.

    1982-01-01

    Results from testing 20 first graders in a remedial class in Maryland indicated that: same pattern recognition was significantly higher than reverse pattern recognition; identical pattern recognition did not affect performance on reading and arithmetic achievement; reverse pattern recognition significantly affected performance on reading and…

  1. Two-dimensional patterning by a trapping/depletion mechanism: the role of TTG1 and GL3 in Arabidopsis trichome formation.

    Directory of Open Access Journals (Sweden)

    Daniel Bouyer

    2008-06-01

    Full Text Available Trichome patterning in Arabidopsis serves as a model system to study how single cells are selected within a field of initially equivalent cells. Current models explain this pattern by an activator-inhibitor feedback loop. Here, we report that also a newly discovered mechanism is involved by which patterning is governed by the removal of the trichome-promoting factor TRANSPARENT TESTA GLABRA1 (TTG1 from non-trichome cells. We demonstrate by clonal analysis and misexpression studies that Arabidopsis TTG1 can act non-cell-autonomously and by microinjection experiments that TTG1 protein moves between cells. While TTG1 is expressed ubiquitously, TTG1-YFP protein accumulates in trichomes and is depleted in the surrounding cells. TTG1-YFP depletion depends on GLABRA3 (GL3, suggesting that the depletion is governed by a trapping mechanism. To study the potential of the observed trapping/depletion mechanism, we formulated a mathematical model enabling us to evaluate the relevance of each parameter and to identify parameters explaining the paradoxical genetic finding that strong ttg1 alleles are glabrous, while weak alleles exhibit trichome clusters.

  2. Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

    Science.gov (United States)

    Huntsberger, Terry

    2011-01-01

    The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

  3. Maximum and minimum amplitudes of the moiré patterns in one- and two-dimensional binary gratings in relation to the opening ratio.

    Science.gov (United States)

    Saveljev, Vladimir; Kim, Sung-Kyu; Lee, Hyoung; Kim, Hyun-Woo; Lee, Byoungho

    2016-02-08

    The amplitude of the moiré patterns is estimated in relation to the opening ratio in line gratings and square grids. The theory is developed; the experimental measurements are performed. The minimum and the maximum of the amplitude are found. There is a good agreement between the theoretical and experimental data. This is additionally confirmed by the visual observation. The results can be applied to the image quality improvement in autostereoscopic 3D displays, to the measurements, and to the moiré displays.

  4. Relationship between acute strain pattern and recovery in tako-tsubo cardiomyopathy and acute anterior myocardial infarction: a comparative study using two-dimensional longitudinal strain.

    Science.gov (United States)

    Meimoun, Patrick; Abouth, Shirley; Boulanger, Jacques; Luycx-Bore, Anne; Martis, Sonia; Clerc, Jérome

    2014-12-01

    After acute-anterior myocardial infarction (AMI), left ventricular (LV) viable myocardial segments show some degree of active deformation (longitudinal shortening) despite wall motion abnormalities (WMA). Tako-tsubo cardiomyopathy (TTC) is characterized by myocardial stunning; however, it is unclear whether in TTC the strain pattern mimics AMI. To compare the strain-pattern in TTC and AMI using the 2D-longitudinal strain by speckle-tracking in segments with WMA, and its relationship with recovery of function at follow-up. 21 consecutive patients with typical TTC and 21 age-matched AMI patients treated by primary angioplasty had an analysis of LV-longitudinal strain at the acute-phase and at follow-up (1 and 6 months later for TTC and AMI respectively). The recovery of a segment was defined as normal wall motion at follow-up. Among the 706 analyzable LV-segments at the acute-phase, 406 had WMA (TTC 229, AMI 177). At follow-up, total recovery was observed for 45 % segments in AMI and 100 % in TTC, (p strain at follow-up (all, p ≤ 0.01). Furthermore, among the 57 % of segments exhibiting any systolic lengthening duration in AMI, only ¼ recovered, versus 62 % of such segments in TTC with 100 % recovery (p myocardial stunning in TTC and AMI is different according to longitudinal strain.

  5. The role of pattern recognition receptors in the innate recognition of Candida albicans.

    Science.gov (United States)

    Zheng, Nan-Xin; Wang, Yan; Hu, Dan-Dan; Yan, Lan; Jiang, Yuan-Ying

    2015-01-01

    Candida albicans is both a commensal microorganism in healthy individuals and a major fungal pathogen causing high mortality in immunocompromised patients. Yeast-hypha morphological transition is a well known virulence trait of C. albicans. Host innate immunity to C. albicans critically requires pattern recognition receptors (PRRs). In this review, we summarize the PRRs involved in the recognition of C. albicans in epithelial cells, endothelial cells, and phagocytic cells separately. We figure out the differential recognition of yeasts and hyphae, the findings on PRR-deficient mice, and the discoveries on human PRR-related single nucleotide polymorphisms (SNPs).

  6. Diagnosis of Equipment Failures by Pattern Recognition

    DEFF Research Database (Denmark)

    Pau, L. F.

    1974-01-01

    The main problems in relation to automatic fault finding and diagnosis in equipments or production systems are discussed: 1) compression of the syndrome and observation spaces for better discrimination between failure modes; 2) simultaneous display of the failure patterns and the failure instants...

  7. Processing Waveforms as Trees for Pattern Recognition.

    Science.gov (United States)

    1986-05-01

    patterns (after Ganong (15]) 5.7 ECG Classification As in the previous example, waveforms were simulated with additive colored gaussian noise. In order to...Principles and Techniques- (AAPG Course Note Series 13), Amer. Assoc. Pet. Geol., Tulsa, OK,p. 86, (1984). [15] W. F. Ganong , Review of Medical Physiology. Lange, Los Altos, CA. pp. 393-408, (1973). /

  8. COMPARISON ANALYSIS OF WEB USAGE MINING USING PATTERN RECOGNITION TECHNIQUES

    Directory of Open Access Journals (Sweden)

    Nanhay Singh

    2013-07-01

    Full Text Available Web usage mining is the application of data mining techniques to better serve the needs of web-based applications on the web site. In this paper, we analyze the web usage mining by applying the pattern recognition techniques on web log data. Pattern recognition is defined as the act of taking in raw data and making an action based on the ‘category’ of the pattern. Web usage mining is divided into three partsPreprocessing, Pattern discovery and Pattern analysis. Further, this paper intended with experimental work in which web log data is used. We have taken the web log data from the “NASA” web server which is analyzed with “Web Log Explorer”. Web Log Explorer is a web usage mining tool which plays the vital role to carry out this work.

  9. Application of pattern recognition techniques to crime analysis

    Energy Technology Data Exchange (ETDEWEB)

    Bender, C.F.; Cox, L.A. Jr.; Chappell, G.A.

    1976-08-15

    The initial goal was to evaluate the capabilities of current pattern recognition techniques when applied to existing computerized crime data. Performance was to be evaluated both in terms of the system's capability to predict crimes and to optimize police manpower allocation. A relation was sought to predict the crime's susceptibility to solution, based on knowledge of the crime type, location, time, etc. The preliminary results of this work are discussed. They indicate that automatic crime analysis involving pattern recognition techniques is feasible, and that efforts to determine optimum variables and techniques are warranted. 47 figures (RWR)

  10. Detection and recognition of analytes based on their crystallization patterns

    Science.gov (United States)

    Morozov, Victor [Manassas, VA; Bailey, Charles L [Cross Junction, VA; Vsevolodov, Nikolai N [Kensington, MD; Elliott, Adam [Manassas, VA

    2008-05-06

    The invention contemplates a method for recognition of proteins and other biological molecules by imaging morphology, size and distribution of crystalline and amorphous dry residues in droplets (further referred to as "crystallization pattern") containing predetermined amount of certain crystal-forming organic compounds (reporters) to which protein to be analyzed is added. It has been shown that changes in the crystallization patterns of a number of amino-acids can be used as a "signature" of a protein added. It was also found that both the character of changer in the crystallization patter and the fact of such changes can be used as recognition elements in analysis of protein molecules.

  11. Body Fuzzy Pattern Recognition in Woman Basic Block Design

    Institute of Scientific and Technical Information of China (English)

    谢红; 张渭源

    2003-01-01

    Basic block is the foundation of clothing construction design because it is the media between body and clothes and the fitness of clothes should be based on the accuracy of basic block. That needs us to recognize body not to record it. This paper reports the Algorithm of woman body fuzzy pattern recognition. It is organized in three sections:(i) extracting woman body feature; (ii) establishing membership functions of feature indexes;(iii) presenting an Algorithm for woman body fuzzy pattern recognition by example.

  12. Human cellular protein patterns and their link to genome DNA sequence data: usefulness of two-dimensional gel electrophoresis and microsequencing

    DEFF Research Database (Denmark)

    Celis, J E; Rasmussen, H H; Leffers, H

    1991-01-01

    Analysis of cellular protein patterns by computer-aided 2-dimensional gel electrophoresis together with recent advances in protein sequence analysis have made possible the establishment of comprehensive 2-dimensional gel protein databases that may link protein and DNA information and that offer...... a global approach to the study of the cell. Using the integrated approach offered by 2-dimensional gel protein databases it is now possible to reveal phenotype specific protein (or proteins), to microsequence them, to search for homology with previously identified proteins, to clone the cDNAs, to assign...... partial protein sequence to genes for which the full DNA sequence and the chromosome location is known, and to study the regulatory properties and function of groups of proteins that are coordinately expressed in a given biological process. Human 2-dimensional gel protein databases are becoming...

  13. Pattern Recognition of Adsorbing HP Lattice Proteins

    Science.gov (United States)

    Wilson, Matthew S.; Shi, Guangjie; Wüst, Thomas; Landau, David P.; Schmid, Friederike

    2015-03-01

    Protein adsorption is relevant in fields ranging from medicine to industry, and the qualitative behavior exhibited by course-grained models could shed insight for further research in such fields. Our study on the selective adsorption of lattice proteins utilizes the Wang-Landau algorithm to simulate the Hydrophobic-Polar (H-P) model with an efficient set of Monte Carlo moves. Each substrate is modeled as a square pattern of 9 lattice sites which attract either H or P monomers, and are located on an otherwise neutral surface. The fully enumerated set of 102 unique surfaces is simulated with each protein sequence. A collection of 27-monomer sequences is used- each of which is non-degenerate and protein-like. Thermodynamic quantities such as the specific heat and free energy are calculated from the density of states, and are used to investigate the adsorption of lattice proteins on patterned substrates. Research supported by NSF.

  14. Two dimensional unstable scar statistics.

    Energy Technology Data Exchange (ETDEWEB)

    Warne, Larry Kevin; Jorgenson, Roy Eberhardt; Kotulski, Joseph Daniel; Lee, Kelvin S. H. (ITT Industries/AES Los Angeles, CA)

    2006-12-01

    This report examines the localization of time harmonic high frequency modal fields in two dimensional cavities along periodic paths between opposing sides of the cavity. The cases where these orbits lead to unstable localized modes are known as scars. This paper examines the enhancements for these unstable orbits when the opposing mirrors are both convex and concave. In the latter case the construction includes the treatment of interior foci.

  15. Two-Dimensional Vernier Scale

    Science.gov (United States)

    Juday, Richard D.

    1992-01-01

    Modified vernier scale gives accurate two-dimensional coordinates from maps, drawings, or cathode-ray-tube displays. Movable circular overlay rests on fixed rectangular-grid overlay. Pitch of circles nine-tenths that of grid and, for greatest accuracy, radii of circles large compared with pitch of grid. Scale enables user to interpolate between finest divisions of regularly spaced rule simply by observing which mark on auxiliary vernier rule aligns with mark on primary rule.

  16. Three-dimensional mapping of mechanical activation patterns, contractile dyssynchrony and dyscoordination by two-dimensional strain echocardiography: Rationale and design of a novel software toolbox

    Directory of Open Access Journals (Sweden)

    Cramer Maarten J

    2008-05-01

    Full Text Available Abstract Background Dyssynchrony of myocardial deformation is usually described in terms of variability only (e.g. standard deviations SD's. A description in terms of the spatio-temporal distribution pattern (vector-analysis of dyssynchrony or by indices estimating its impact by expressing dyscoordination of shortening in relation to the global ventricular shortening may be preferential. Strain echocardiography by speckle tracking is a new non-invasive, albeit 2-D imaging modality to study myocardial deformation. Methods A post-processing toolbox was designed to incorporate local, speckle tracking-derived deformation data into a 36 segment 3-D model of the left ventricle. Global left ventricular shortening, standard deviations and vectors of timing of shortening were calculated. The impact of dyssynchrony was estimated by comparing the end-systolic values with either early peak values only (early shortening reserve ESR or with all peak values (virtual shortening reserve VSR, and by the internal strain fraction (ISF expressing dyscoordination as the fraction of deformation lost internally due to simultaneous shortening and stretching. These dyssynchrony parameters were compared in 8 volunteers (NL, 8 patients with Wolff-Parkinson-White syndrome (WPW, and 7 patients before (LBBB and after cardiac resynchronization therapy (CRT. Results Dyssynchrony indices merely based on variability failed to detect differences between WPW and NL and failed to demonstrate the effect of CRT. Only the 3-D vector of onset of shortening could distinguish WPW from NL, while at peak shortening and by VSR, ESR and ISF no differences were found. All tested dyssynchrony parameters yielded higher values in LBBB compared to both NL and WPW. CRT reduced the spatial divergence of shortening (both vector magnitude and direction, and improved global ventricular shortening along with reductions in ESR and dyscoordination of shortening expressed by ISF. Conclusion Incorporation

  17. Pattern recognition for electroencephalographic signals based on continuous neural networks.

    Science.gov (United States)

    Alfaro-Ponce, M; Argüelles, A; Chairez, I

    2016-07-01

    This study reports the design and implementation of a pattern recognition algorithm to classify electroencephalographic (EEG) signals based on artificial neural networks (NN) described by ordinary differential equations (ODEs). The training method for this kind of continuous NN (CNN) was developed according to the Lyapunov theory stability analysis. A parallel structure with fixed weights was proposed to perform the classification stage. The pattern recognition efficiency was validated by two methods, a generalization-regularization and a k-fold cross validation (k=5). The classifier was applied on two different databases. The first one was made up by signals collected from patients suffering of epilepsy and it is divided in five different classes. The second database was made up by 90 single EEG trials, divided in three classes. Each class corresponds to a different visual evoked potential. The pattern recognition algorithm achieved a maximum correct classification percentage of 97.2% using the information of the entire database. This value was similar to some results previously reported when this database was used for testing pattern classification. However, these results were obtained when only two classes were considered for the testing. The result reported in this study used the whole set of signals (five different classes). In comparison with similar pattern recognition methods that even considered less number of classes, the proposed CNN proved to achieve the same or even better correct classification results.

  18. Accurate invariant pattern recognition for perspective camera model

    Science.gov (United States)

    Serikova, Mariya G.; Pantyushina, Ekaterina N.; Zyuzin, Vadim V.; Korotaev, Valery V.; Rodrigues, Joel J. P. C.

    2015-05-01

    In this work we present a pattern recognition method based on geometry analysis of a flat pattern. The method provides reliable detection of the pattern in the case when significant perspective deformation is present in the image. The method is based on the fact that collinearity of the lines remains unchanged under perspective transformation. So the recognition feature is the presence of two lines, containing four points each. Eight points form two squares for convenience of applying corner detection algorithms. The method is suitable for automatic pattern detection in a dense environment of false objects. In this work we test the proposed method for statistics of detection and algorithm's performance. For estimation of pattern detection quality we performed image simulation process with random size and spatial frequency of background clutter while both translational (range varied from 200 mm to 1500 mm) and rotational (up to 60°) deformations in given pattern position were added. Simulated measuring system included a camera (4000x4000 sensor with 25 mm lens) and a flat pattern. Tests showed that the proposed method demonstrates no more than 1% recognition error when number of false targets is up to 40.

  19. Photonic implementation of Hopfield neural network for associative pattern recognition

    Science.gov (United States)

    Munshi, Soumika; Bhattacharyya, Siddhartha; Datta, Asit K.

    2001-09-01

    An optical matrix-vector multiplier has ben efficiently used for photonic implementation of Hopfield network model, which is used for binary pattern recognition. Training matrices are recorded on electrically addressed spatial light modulator, where each matrix is composed of the same row of each pattern, that the network is being trained with. After training, if an unknown pattern is presented to the network in the form of a vector, the output vector is obtained by the element that has the highest magnitude through a winner- take-all algorithm. Pattern can be recognized even if the input is noisy and distorted.

  20. Two Challenges of Correct Validation in Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Thomas eNowotny

    2014-09-01

    Full Text Available Supervised pattern recognition is the process of mapping patterns to class labelsthat define their meaning. The core methods for pattern recognitionhave been developed by machine learning experts but due to their broadsuccess an increasing number of non-experts are now employing andrefining them. In this perspective I will discuss the challenge ofcorrect validation of supervised pattern recognition systems, in particular whenemployed by non-experts. To illustrate the problem I will give threeexamples of common errors that I have encountered in the lastyear. Much of this challenge can be addressed by strict procedure invalidation but there are remaining problems of correctlyinterpreting comparative work on exemplary data sets, which I willelucidate on the example of the well-used MNIST data set of handwrittendigits.

  1. Two-Dimensionally-Modulated, Magnetic Structure of Neodymium Metal

    DEFF Research Database (Denmark)

    Lebech, Bente; Bak, P.

    1979-01-01

    The incipient magnetic order of dhcp Nd is described by a two-dimensional, incommensurably modulated structure ("triple-q" structure). The ordering is accompanied by a lattice distortion that forms a similar pattern....

  2. Linear Invariant Multiclass Component Spaces For Optical Pattern Recognition

    Science.gov (United States)

    Hester, Charles F.

    1983-04-01

    Optical processing systems which perform linear transformations on image data at high rates are ideal for image pattern recognition systems. As a result of this processing capability, the linear opera-tion of matched spatial filtering has been explored extensively for pattern recognition. For many practical pattern recognition problems, however, multiclass filtering must be used to overcome the variations of input objects due to image scale changes, image rotations, object aspect differences and sensor differences. Hester and Casasent have shown that a linear mapping can be constructed which images all the class elements of a multiclass set into one out-put element or value. This special multi-class filter concept is extended in this paper to show that a subspace of the multi-class set exists that is invariant with respect to the multiclass mapping under linear operations. The concept of this in-variant space and its generation is detailed and a single example given. A typical optical processing architecture using these invariant elements as filters in an associative pattern recognition system is also presented.

  3. High-density myoelectric pattern recognition toward improved stroke rehabilitation.

    Science.gov (United States)

    Zhang, Xu; Zhou, Ping

    2012-06-01

    Myoelectric pattern-recognition techniques have been developed to infer user's intention of performing different functional movements. Thus electromyogram (EMG) can be used as control signals of assisted devices for people with disabilities. Pattern-recognition-based myoelectric control systems have rarely been designed for stroke survivors. Aiming at developing such a system for improved stroke rehabilitation, this study assessed detection of the affected limb's movement intention using high-density surface EMG recording and pattern-recognition techniques. Surface EMG signals comprised of 89 channels were recorded from 12 hemiparetic stroke subjects while they tried to perform 20 different arm, hand, and finger/thumb movements involving the affected limb. A series of pattern-recognition algorithms were implemented to identify the intended tasks of each stroke subject. High classification accuracies (96.1% ± 4.3%) were achieved, indicating that substantial motor control information can be extracted from paretic muscles of stroke survivors. Such information may potentially facilitate improved stroke rehabilitation.

  4. Statistical pattern recognition for automatic writer identification and verification

    NARCIS (Netherlands)

    Bulacu, Marius Lucian

    2007-01-01

    The thesis addresses the problem of automatic person identification using scanned images of handwriting.Identifying the author of a handwritten sample using automatic image-based methods is an interesting pattern recognition problem with direct applicability in the forensic and historic document

  5. Statistical pattern recognition for automatic writer identification and verification

    NARCIS (Netherlands)

    Bulacu, Marius Lucian

    2007-01-01

    The thesis addresses the problem of automatic person identification using scanned images of handwriting.Identifying the author of a handwritten sample using automatic image-based methods is an interesting pattern recognition problem with direct applicability in the forensic and historic document ana

  6. Information theory in computer vision and pattern recognition

    CERN Document Server

    Escolano, Francisco; Bonev, Boyan

    2009-01-01

    Researchers are bringing information theory elements to the computer vision and pattern recognition (CVPR) arena. Among these elements there are measures (entropy, mutual information), principles (maximum entropy, minimax entropy) and theories (rate distortion theory, method of types). This book explores the latter elements.

  7. Fuzzy Pattern Recognition System for Detection of Alga Distribution

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    To realize the on-line measurement and make analysis on the density of algae and their cluster distribution, the fluorescent detection and fuzzy pattern recognition techniques are used. The principle of fluorescent fiber-optic detection is given as well as the method of fuzzy feature extraction using a class of neural network.

  8. On self-nonself discrimination in pattern recognition

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Wide distribution and broad reactivity are cardinal features of pattern recognition receptors that allow rapid mobiliza-tion of large numbers of effectors to deal with pathogens.However, these features come with significant baggage as the receptors have been shown to interact with many intra-cellular components, collectively called danger-associated

  9. A Fuzzy Neural Network for Fault Pattern Recognition

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    This paper combines fuzzy set theory with AR T neural network, and demonstrates some important properties of the fuzzy ART neural network algorithm. The results from application on a ball bearing diagnosis indicate that a fuzzy ART neural network has an effect of fast stable recognition for fuzzy patterns.

  10. Pattern Recognition Receptors in Innate Immunity, Host Defense, and Immunopathology

    Science.gov (United States)

    Suresh, Rahul; Mosser, David M.

    2013-01-01

    Infection by pathogenic microbes initiates a set of complex interactions between the pathogen and the host mediated by pattern recognition receptors. Innate immune responses play direct roles in host defense during the early stages of infection, and they also exert a profound influence on the generation of the adaptive immune responses that ensue.…

  11. Pattern recognition approach to quantify the atomic structure of graphene

    DEFF Research Database (Denmark)

    Kling, Jens; Vestergaard, Jacob Schack; Dahl, Anders Bjorholm

    2014-01-01

    We report a pattern recognition approach to detect the atomic structure in high-resolution transmission electron microscopy images of graphene. The approach provides quantitative information such as carbon-carbon bond lengths and bond length variations on a global and local scale alike. © 2014...

  12. Pattern recognition algorithm reveals how birds evolve individual egg pattern signatures

    National Research Council Canada - National Science Library

    Stoddard, Mary Caswell; Kilner, Rebecca M; Town, Christopher

    2014-01-01

    .... Here we develop a computer vision tool for analysing visual patterns, NATUREPATTERNMATCH, which breaks new ground by mimicking visual and cognitive processes known to be involved in recognition tasks...

  13. Two-dimensional liquid chromatography

    DEFF Research Database (Denmark)

    Græsbøll, Rune

    Two-dimensional liquid chromatography has received increasing interest due to the rise in demand for analysis of complex chemical mixtures. Separation of complex mixtures is hard to achieve as a simple consequence of the sheer number of analytes, as these samples might contain hundreds or even...... dimensions. As a consequence of the conclusions made within this thesis, the research group has, for the time being, decided against further development of online LC×LC systems, since it was not deemed ideal for the intended application, the analysis of the polar fraction of oil. Trap-and...

  14. 3D face database for human pattern recognition

    Science.gov (United States)

    Song, LiMei; Lu, Lu

    2008-10-01

    Face recognition is an essential work to ensure human safety. It is also an important task in biomedical engineering. 2D image is not enough for precision face recognition. 3D face data includes more exact information, such as the precision size of eyes, mouth, etc. 3D face database is an important part in human pattern recognition. There is a lot of method to get 3D data, such as 3D laser scan system, 3D phase measurement, shape from shading, shape from motion, etc. This paper will introduce a non-orbit, non-contact, non-laser 3D measurement system. The main idea is from shape from stereo technique. Two cameras are used in different angle. A sequence of light will project on the face. Human face, human head, human tooth, human body can all be measured by the system. The visualization data of each person can form to a large 3D face database, which can be used in human recognition. The 3D data can provide a vivid copy of a face, so the recognition exactness can be reached to 100%. Although the 3D data is larger than 2D image, it can be used in the occasion where only few people include, such as the recognition of a family, a small company, etc.

  15. Defect Localization Capabilities of a Global Detection Scheme: Spatial Pattern Recognition Using Full-field Vibration Test Data in Plates

    Science.gov (United States)

    Saleeb, A. F.; Prabhu, M.; Arnold, S. M. (Technical Monitor)

    2002-01-01

    Recently, a conceptually simple approach, based on the notion of defect energy in material space has been developed and extensively studied (from the theoretical and computational standpoints). The present study focuses on its evaluation from the viewpoint of damage localization capabilities in case of two-dimensional plates; i.e., spatial pattern recognition on surfaces. To this end, two different experimental modal test results are utilized; i.e., (1) conventional modal testing using (white noise) excitation and accelerometer-type sensors and (2) pattern recognition using Electronic speckle pattern interferometry (ESPI), a full field method capable of analyzing the mechanical vibration of complex structures. Unlike the conventional modal testing technique (using contacting accelerometers), these emerging ESPI technologies operate in a non-contacting mode, can be used even under hazardous conditions with minimal or no presence of noise and can simultaneously provide measurements for both translations and rotations. Results obtained have clearly demonstrated the robustness and versatility of the global NDE scheme developed. The vectorial character of the indices used, which enabled the extraction of distinct patterns for localizing damages proved very useful. In the context of the targeted pattern recognition paradigm, two algorithms were developed for the interrogation of test measurements; i.e., intensity contour maps for the damaged index, and the associated defect energy vector field plots.

  16. Structural aspects of molecular recognition in the immune system. Part II: Pattern recognition receptors

    OpenAIRE

    2014-01-01

    The vertebrate immune system uses pattern recognition receptors (PRRs) to detect a large variety of molecular signatures (pathogen-associated molecular patterns, PAMPs) from a broad range of different invading pathogens. The PAMPs range in size from relatively small molecules, to others of intermediate size such as bacterial lipopolysaccharide, lipopeptides, and oligosaccharides, to macromolecules such as viral DNA, RNA, and pathogen-derived proteins such as flagellin. Underlying this functio...

  17. A new concept of vertically integrated pattern recognition associative memory

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Ted; Hoff, Jim; Deptuch, Grzegorz; Yarema, Ray; /Fermilab

    2011-11-01

    Hardware-based pattern recognition for fast triggering on particle tracks has been successfully used in high-energy physics experiments for some time. The CDF Silicon Vertex Trigger (SVT) at the Fermilab Tevatron is an excellent example. The method used there, developed in the 1990's, is based on algorithms that use a massively parallel associative memory architecture to identify patterns efficiently at high speed. However, due to much higher occupancy and event rates at the LHC, and the fact that the LHC detectors have a much larger number of channels in their tracking detectors, there is an enormous challenge in implementing fast pattern recognition for a track trigger, requiring about three orders of magnitude more associative memory patterns than what was used in the original CDF SVT. Scaling of current technologies is unlikely to satisfy the scientific needs of the future, and investments in transformational new technologies need to be made. In this paper, we will discuss a new concept of using the emerging 3D vertical integration technology to significantly advance the state-of-the-art for fast pattern recognition within and outside HEP. A generic R and D proposal based on this new concept, with a few institutions involved, has recently been submitted to DOE with the goal to design and perform the ASIC engineering necessary to realize a prototype device. The progress of this R and D project will be reported in the future. Here we will only focus on the concept of this new approach.

  18. Developement of 3D Vertically Integrated Pattern Recognition Associative Memory (VIPRAM)

    Energy Technology Data Exchange (ETDEWEB)

    Deputch, G.; Hoff, J.; Lipton, R.; Liu, T.; Olsen, J.; Ramberg, E.; Wu, Jin-Yuan; Yarema, R.; /Fermilab; Shochet, M.; Tang, F.; /Chicago U.; Demarteau, M.; /Argonne /INFN, Padova

    2011-04-13

    recognition for a track trigger, requiring about three orders of magnitude more associative memory patterns than what was used in the original CDF SVT. Significant improvement in the architecture of associative memory structures is needed to run fast pattern recognition algorithms of this scale. We are proposing the development of 3D integrated circuit technology as a way to implement new associative memory structures for fast pattern recognition applications. Adding a 'third' dimension to the signal processing chain, as compared to the two-dimensional nature of printed circuit boards, Field Programmable Gate Arrays (FPGAs), etc., opens up the possibility for new architectures that could dramatically enhance pattern recognition capability. We are currently performing preliminary design work to demonstrate the feasibility of this approach. In this proposal, we seek to develop the design and perform the ASIC engineering necessary to realize a prototype device. While our focus here is on the Energy Frontier (e.g. the LHC), the approach may have applications in experiments in the Intensity Frontier and the Cosmic Frontier as well as other scientific and medical projects. In fact, the technique that we are proposing is very generic and could have wide applications far beyond track trigger, both within and outside HEP.

  19. Error-Correcting Parsing for Syntactic Pattern Recognition

    Science.gov (United States)

    1977-08-01

    the parser can, at most, generate a partial parse. Therefore, for a given gramar , G, a parser can be used to answer the membership problem, it can...Step 2. ’ ’•’ »- ZZZS^^m^mmimmmimmäk • •- - • •- 124 4.3. An Illustrative Example 4.3.1. Data Preparation A set of English characters Is used to...37. Narasimhan, R. and V. S. N. Reddy, "A Syntax-Aided Recognition Scheme for Handprinted English Letters," Pattern Recognition, Vol. 3, PP. 345

  20. Two-dimensional capillary origami

    Energy Technology Data Exchange (ETDEWEB)

    Brubaker, N.D., E-mail: nbrubaker@math.arizona.edu; Lega, J., E-mail: lega@math.arizona.edu

    2016-01-08

    We describe a global approach to the problem of capillary origami that captures all unfolded equilibrium configurations in the two-dimensional setting where the drop is not required to fully wet the flexible plate. We provide bifurcation diagrams showing the level of encapsulation of each equilibrium configuration as a function of the volume of liquid that it contains, as well as plots representing the energy of each equilibrium branch. These diagrams indicate at what volume level the liquid drop ceases to be attached to the endpoints of the plate, which depends on the value of the contact angle. As in the case of pinned contact points, three different parameter regimes are identified, one of which predicts instantaneous encapsulation for small initial volumes of liquid. - Highlights: • Full solution set of the two-dimensional capillary origami problem. • Fluid does not necessarily wet the entire plate. • Global energy approach provides exact differential equations satisfied by minimizers. • Bifurcation diagrams highlight three different regimes. • Conditions for spontaneous encapsulation are identified.

  1. Natural Cytotoxicity Receptors: Pattern Recognition and Involvement of Carbohydrates

    Directory of Open Access Journals (Sweden)

    Angel Porgador

    2005-01-01

    Full Text Available Natural cytotoxicity receptors (NCRs, expressed by natural killer (NK cells, trigger NK lysis of tumor and virus-infected cells on interaction with cell-surface ligands of these target cells. We have determined that viral hemagglutinins expressed on the surface of virus-infected cells are involved in the recognition by the NCRs, NKp44 and NKp46. Recognition of tumor cells by the NCRs NKp30 and NKp46 involves heparan sulfate epitopes expressed on the tumor cell membrane. Our studies provide new evidence for the identity of the ligands for NCRs and indicate that a broader definition should be applied to pathological patterns recognized by innate immune receptors. Since nonmicrobial endogenous carbohydrate structures contribute significantly to this recognition, there is an imperative need to develop appropriate tools for the facile sequencing of carbohydrate moieties.

  2. [Recognition of corn seeds based on pattern recognition and near infrared spectroscopy technology].

    Science.gov (United States)

    Liu, Tian-Ling; Su, Qi-Ya; Sun, Qun; Yang, Li-Ming

    2012-06-01

    Pattern recognition technology and data mining methods have become a hot topic in chemometrics. Near infrared (NIR) spectroscopic analysis has been widely used in spectrum signal processing and modeling due to its advantages of quickness, simplicity and nondestructiveness. Based on five different methods of pattern recognition, namely the locally linear embedding (LLE), wavelet transform (WT), principal component analysis (PCA), partial least squares (PLS) and support vector machine (SVM), the pattern recognition system for corn seeds is proposed using NIR technology, and applied to classification of 108 hybrid samples and 178 female samples for corn seeds. Firstly, we get rid of noise or reduce the dimension using LLE, WT, PCA and PLS, and then use SVM to identify two-class samples. In the meantime, 1-norm SVM is the method of direct classification and identification. Experimental results for three different spectral regions show that the performances of three methods, i. e. PCA+SVM, LLE+SVM, PLS+SVM, are superior to WT+SVM and 1-norm SVM methods, and obtain a high classification accuracy, which indicates the feasibility and effectiveness of the proposed methods. Moreover, this investigation provides the theoretical support and practical method for recognition of corn seeds utilizing near infrared spectral data.

  3. Structures of pattern recognition receptors reveal molecular mechanisms of autoinhibition, ligand recognition and oligomerization.

    Science.gov (United States)

    Chuenchor, Watchalee; Jin, Tengchuan; Ravilious, Geoffrey; Xiao, T Sam

    2014-02-01

    Pattern recognition receptors (PRRs) are essential sentinels for pathogens or tissue damage and integral components of the innate immune system. Recent structural studies have provided unprecedented insights into the molecular mechanisms of ligand recognition and signal transduction by several PRR families at distinct subcellular compartments. Here we highlight some of the recent discoveries and summarize the common themes that are emerging from these exciting studies. Better mechanistic understanding of the structure and function of the PRRs will improve future prospects of therapeutic targeting of these important innate immune receptors.

  4. Pattern recognition software and techniques for biological image analysis.

    Directory of Open Access Journals (Sweden)

    Lior Shamir

    Full Text Available The increasing prevalence of automated image acquisition systems is enabling new types of microscopy experiments that generate large image datasets. However, there is a perceived lack of robust image analysis systems required to process these diverse datasets. Most automated image analysis systems are tailored for specific types of microscopy, contrast methods, probes, and even cell types. This imposes significant constraints on experimental design, limiting their application to the narrow set of imaging methods for which they were designed. One of the approaches to address these limitations is pattern recognition, which was originally developed for remote sensing, and is increasingly being applied to the biology domain. This approach relies on training a computer to recognize patterns in images rather than developing algorithms or tuning parameters for specific image processing tasks. The generality of this approach promises to enable data mining in extensive image repositories, and provide objective and quantitative imaging assays for routine use. Here, we provide a brief overview of the technologies behind pattern recognition and its use in computer vision for biological and biomedical imaging. We list available software tools that can be used by biologists and suggest practical experimental considerations to make the best use of pattern recognition techniques for imaging assays.

  5. Pattern recognition software and techniques for biological image analysis.

    Science.gov (United States)

    Shamir, Lior; Delaney, John D; Orlov, Nikita; Eckley, D Mark; Goldberg, Ilya G

    2010-11-24

    The increasing prevalence of automated image acquisition systems is enabling new types of microscopy experiments that generate large image datasets. However, there is a perceived lack of robust image analysis systems required to process these diverse datasets. Most automated image analysis systems are tailored for specific types of microscopy, contrast methods, probes, and even cell types. This imposes significant constraints on experimental design, limiting their application to the narrow set of imaging methods for which they were designed. One of the approaches to address these limitations is pattern recognition, which was originally developed for remote sensing, and is increasingly being applied to the biology domain. This approach relies on training a computer to recognize patterns in images rather than developing algorithms or tuning parameters for specific image processing tasks. The generality of this approach promises to enable data mining in extensive image repositories, and provide objective and quantitative imaging assays for routine use. Here, we provide a brief overview of the technologies behind pattern recognition and its use in computer vision for biological and biomedical imaging. We list available software tools that can be used by biologists and suggest practical experimental considerations to make the best use of pattern recognition techniques for imaging assays.

  6. Two-dimensional quantum repeaters

    Science.gov (United States)

    Wallnöfer, J.; Zwerger, M.; Muschik, C.; Sangouard, N.; Dür, W.

    2016-11-01

    The endeavor to develop quantum networks gave rise to a rapidly developing field with far-reaching applications such as secure communication and the realization of distributed computing tasks. This ultimately calls for the creation of flexible multiuser structures that allow for quantum communication between arbitrary pairs of parties in the network and facilitate also multiuser applications. To address this challenge, we propose a two-dimensional quantum repeater architecture to establish long-distance entanglement shared between multiple communication partners in the presence of channel noise and imperfect local control operations. The scheme is based on the creation of self-similar multiqubit entanglement structures at growing scale, where variants of entanglement swapping and multiparty entanglement purification are combined to create high-fidelity entangled states. We show how such networks can be implemented using trapped ions in cavities.

  7. Two-dimensional capillary origami

    Science.gov (United States)

    Brubaker, N. D.; Lega, J.

    2016-01-01

    We describe a global approach to the problem of capillary origami that captures all unfolded equilibrium configurations in the two-dimensional setting where the drop is not required to fully wet the flexible plate. We provide bifurcation diagrams showing the level of encapsulation of each equilibrium configuration as a function of the volume of liquid that it contains, as well as plots representing the energy of each equilibrium branch. These diagrams indicate at what volume level the liquid drop ceases to be attached to the endpoints of the plate, which depends on the value of the contact angle. As in the case of pinned contact points, three different parameter regimes are identified, one of which predicts instantaneous encapsulation for small initial volumes of liquid.

  8. Two-dimensional cubic convolution.

    Science.gov (United States)

    Reichenbach, Stephen E; Geng, Frank

    2003-01-01

    The paper develops two-dimensional (2D), nonseparable, piecewise cubic convolution (PCC) for image interpolation. Traditionally, PCC has been implemented based on a one-dimensional (1D) derivation with a separable generalization to two dimensions. However, typical scenes and imaging systems are not separable, so the traditional approach is suboptimal. We develop a closed-form derivation for a two-parameter, 2D PCC kernel with support [-2,2] x [-2,2] that is constrained for continuity, smoothness, symmetry, and flat-field response. Our analyses, using several image models, including Markov random fields, demonstrate that the 2D PCC yields small improvements in interpolation fidelity over the traditional, separable approach. The constraints on the derivation can be relaxed to provide greater flexibility and performance.

  9. Pattern Recognition-Based Analysis of COPD in CT

    DEFF Research Database (Denmark)

    Sørensen, Lauge Emil Borch Laurs

    individual lung voxel in the CT image and counts the number of voxels below the threshold relative to the total amount of lung voxels. This thesis presents several methods for texture-based quantification of emphysema and/or COPD in CT images of the lungs. The methods rely on image processing and pattern...... recognition. The image processing part deals with characterizing the lung tissue texture using a suitable texture descriptor. Two types of descriptors are considered, the local binary pattern histogram and histograms of filter responses from a multi-scale Gaussian derivative filter bank. The pattern......Computed tomography (CT), a medical imaging technique, offers a detailed view of the human body that can be used for direct inspection of the lung tissue. This allows for in vivo measurement of subtle disease patterns such as the patterns associated with chronic obstructive pulmonary disease (COPD...

  10. Pattern recognition in field crickets: concepts and neural evidence.

    Science.gov (United States)

    Kostarakos, Konstantinos; Hedwig, Berthold

    2015-01-01

    Since decades the acoustic communication behavior of crickets is in the focus of neurobiology aiming to analyze the neural basis of male singing and female phonotactic behavior. For temporal pattern recognition several different concepts have been proposed to elucidate the possible neural mechanisms underlying the tuning of phonotaxis in females. These concepts encompass either some form of a feature detecting mechanism using cross-correlation processing, temporal filter properties of brain neurons or an autocorrelation processing based on a delay-line and coincidence detection mechanism. Current data based on intracellular recordings of auditory brain neurons indicate a sequential processing by excitation and inhibition in a local auditory network within the protocerebrum. The response properties of the brain neurons point towards the concept of an autocorrelation-like mechanism underlying female pattern recognition in which delay-lines by long lasting inhibition may be involved.

  11. Applications of pattern recognition in aluminum alloy texture characterization

    Science.gov (United States)

    Liu, Guizhong; Rehbein, D. K.; Foley, James C.; Thompson, R. B.

    2000-05-01

    This paper presents a methodology to extract texture information in Aluminum alloys using pattern recognition algorithm. The orientation of the samples can be obtained by the orientation Image Microscope (OIM) technique. The ISO DATA pattern recognition algorithm is implemented to classify the OIM data into different clusters. Based on the classification results, the probability density function (pdf) is estimated. Then, the pdf is expanded as a series of Legendre functions with coefficients, i.e., the orientation distribution coefficients (ODC) as texture parameters. Three of these ODC's are of special interests, namely W400, W420, and W440. This paper includes results from ultrasonic NDE and this novel algorithm.—Ames Laboratory is operated for U.S. Department of Energy by Iowa State University under Contract W-7405-ENG-82. This work was supported by the Office of Basic Energy Sciences as a part of the Center of Excellence of the Synthesis and Processing of Advanced Materials.

  12. Learning pattern recognition and decision making in the insect brain

    Science.gov (United States)

    Huerta, R.

    2013-01-01

    We revise the current model of learning pattern recognition in the Mushroom Bodies of the insects using current experimental knowledge about the location of learning, olfactory coding and connectivity. We show that it is possible to have an efficient pattern recognition device based on the architecture of the Mushroom Bodies, sparse code, mutual inhibition and Hebbian leaning only in the connections from the Kenyon cells to the output neurons. We also show that despite the conventional wisdom that believes that artificial neural networks are the bioinspired model of the brain, the Mushroom Bodies actually resemble very closely Support Vector Machines (SVMs). The derived SVM learning rules are situated in the Mushroom Bodies, are nearly identical to standard Hebbian rules, and require inhibition in the output. A very particular prediction of the model is that random elimination of the Kenyon cells in the Mushroom Bodies do not impair the ability to recognize odorants previously learned.

  13. Nonnegative matrix factorization and its applications in pattern recognition

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Matrix factorization is an effective tool for large-scale data processing and analysis. Nonnegative matrix factorization (NMF) method, which decomposes the nonnegative matrix into two nonnegative factor matrices, provides a new way for matrix factorization. NMF is significant in intelligent information processing and pattern recognition. This paper firstly introduces the basic idea of NMF and some new relevant methods. Then we discuss the loss functions and relevant algorithms of NMF in the framework of probabilistic models based on our researches, and the relationship between NMF and information processing of perceptual process. Finally, we make use of NMF to deal with some practical questions of pattern recognition and point out some open problems for NMF.

  14. Contiguous Uniform Deviation for Multiple Linear Regression in Pattern Recognition

    Science.gov (United States)

    Andriana, A. S.; Prihatmanto, D.; Hidaya, E. M. I.; Supriana, I.; Machbub, C.

    2017-01-01

    Understanding images by recognizing its objects is still a challenging task. Face elements detection has been developed by researchers but not yet shows enough information (low resolution in information) needed for recognizing objects. Available face recognition methods still have error in classification and need a huge amount of examples which may still be incomplete. Another approach which is still rare in understanding images uses pattern structures or syntactic grammars describing shape detail features. Image pixel values are also processed as signal patterns which are approximated by mathematical function curve fitting. This paper attempts to add contiguous uniform deviation method to curve fitting algorithm to increase applicability in image recognition system related to object movement. The combination of multiple linear regression and contiguous uniform deviation method are applied to the function of image pixel values, and show results in higher resolution (more information) of visual object detail description in object movement.

  15. Markov sequential pattern recognition : dependency and the unknown class.

    Energy Technology Data Exchange (ETDEWEB)

    Malone, Kevin Thomas; Haschke, Greg Benjamin; Koch, Mark William

    2004-10-01

    The sequential probability ratio test (SPRT) minimizes the expected number of observations to a decision and can solve problems in sequential pattern recognition. Some problems have dependencies between the observations, and Markov chains can model dependencies where the state occupancy probability is geometric. For a non-geometric process we show how to use the effective amount of independent information to modify the decision process, so that we can account for the remaining dependencies. Along with dependencies between observations, a successful system needs to handle the unknown class in unconstrained environments. For example, in an acoustic pattern recognition problem any sound source not belonging to the target set is in the unknown class. We show how to incorporate goodness of fit (GOF) classifiers into the Markov SPRT, and determine the worse case nontarget model. We also develop a multiclass Markov SPRT using the GOF concept.

  16. Online pattern recognition for the ALICE high level trigger

    CERN Document Server

    Bramm, R; Lien, J A; Lindenstruth, V; Loizides, C; Röhrich, D; Skaali, B; Steinbeck, T M; Stock, Reinhard; Ullaland, K; Vestbø, A S; Wiebalck, A

    2003-01-01

    The ALICE High Level Trigger system needs to reconstruct events online at high data rates. Focusing on the Time Projection Chamber we present two pattern recognition methods under investigation: the sequential approach (cluster finding, track follower) and the iterative approach (Hough Transform, cluster assignment, re-fitting). The implementation of the former in hardware indicates that we can reach the designed inspection rate for p-p collisions of 1 kHz with 98% efficiency.

  17. Online pattern recognition for the ALICE high level trigger

    Energy Technology Data Exchange (ETDEWEB)

    Bramm, R.; Helstrup, H.; Lien, J.; Lindenstruth, V.; Loizides, C. E-mail: loizides@ikf.uni-frankfurt.de; Rohrich, D.; Skaali, B.; Steinbeck, T.; Stock, R.; Ullaland, K.; Vestboe, A.; Wiebalck, A

    2003-04-21

    The ALICE High Level Trigger system needs to reconstruct events online at high data rates. Focusing on the Time Projection Chamber we present two pattern recognition methods under investigation: the sequential approach (cluster finding, track follower) and the iterative approach (Hough Transform, cluster assignment, re-fitting). The implementation of the former in hardware indicates that we can reach the designed inspection rate for p-p collisions of 1 kHz with 98% efficiency.

  18. Neurocomputing methods for pattern recognition in nuclear physics

    Energy Technology Data Exchange (ETDEWEB)

    Gyulassy, M.; Dong, D.; Harlander, M. [Lawrence Berkeley Lab., CA (United States)

    1991-12-31

    We review recent progress on the development and applications of novel neurocomputing techniques for pattern recognition problems of relevance to RHIC experiments. The Elastic Tracking algorithm is shown to achieve sub-pad two track resolution without preprocessing. A high pass neural filter is developed for jet analysis and singular deconvolution methods are shown to recover the primordial jet distribution to a surprising high degree of accuracy.

  19. Neurocomputing methods for pattern recognition in nuclear physics

    Energy Technology Data Exchange (ETDEWEB)

    Gyulassy, M.; Dong, D.; Harlander, M. [Lawrence Berkeley Lab., CA (United States)

    1991-12-31

    We review recent progress on the development and applications of novel neurocomputing techniques for pattern recognition problems of relevance to RHIC experiments. The Elastic Tracking algorithm is shown to achieve sub-pad two track resolution without preprocessing. A high pass neural filter is developed for jet analysis and singular deconvolution methods are shown to recover the primordial jet distribution to a surprising high degree of accuracy.

  20. A new paradigm for pattern recognition of drugs.

    Science.gov (United States)

    Potemkin, Vladimir A; Grishina, Maria A

    2008-01-01

    A new paradigm is suggested for pattern recognition of drugs. The approach is based on the combined application of the 4D/3D quantitative structure-activity relationship (QSAR) algorithms BiS and ConGO. The first algorithm, BiS/MC (multiconformational), is used for the search for the conformers interacting with a receptor. The second algorithm, ConGO, has been suggested for the detailed study of the selected conformers' electron density and for the search for the electron structure fragments that determine the pharmacophore and antipharmacophore parts of the compounds. In this work we suggest using a new AlteQ method for the evaluation of the molecular electron density. AlteQ describes the experimental electron density (determined by low-temperature highly accurate X-ray analysis) much better than a number of quantum approaches. Herein this is shown using a comparison of the computed electron density with the results of highly accurate X-ray analysis. In the present study the desirability function is used for the first time for the analysis of the effects of the electron structure in the process of pattern recognition of active and inactive compounds. The suggested method for pattern recognition has been used for the investigation of various sets of compounds such as DNA-antimetabolites, fXa inhibitors, 5-HT(1A), and alpha(1)-AR receptors inhibitors. The pharmacophore and antipharmacophore fragments have been found in the electron structures of the compounds. It has been shown that the pattern recognition cross-validation quality for the datasets is unity.

  1. Linear Programming and Its Application to Pattern Recognition Problems

    Science.gov (United States)

    Omalley, M. J.

    1973-01-01

    Linear programming and linear programming like techniques as applied to pattern recognition problems are discussed. Three relatively recent research articles on such applications are summarized. The main results of each paper are described, indicating the theoretical tools needed to obtain them. A synopsis of the author's comments is presented with regard to the applicability or non-applicability of his methods to particular problems, including computational results wherever given.

  2. Application of advanced pattern recognition to power plant condition assessment

    Energy Technology Data Exchange (ETDEWEB)

    Caudill, M.B.; Griebenow, R.D.; Hansen, E.J.

    1996-05-01

    As electric utilities strive to become more competitive, efficient operation and maintenance of steam power cycles becomes a greater concern. As part of an aggressive thermal performance monitoring and improvement program, Tri-State Generation and Transmission Association has integrated advanced pattern recognition technology with more conventional heat balance analysis methods to monitor and diagnose plant cycle deficiencies. Advanced pattern recognition (APR) technology is used for continuous monitoring of plant operation. It can quickly diagnose faulty instrumentation and supply accurate replacement values, providing confidence in the data used for daily operating and engineering decisions. Furthermore, it accurately identifies calibration drift, providing Tri-State with the information required to allocate manpower to only those instruments requiring maintenance. APR is also integrated into the data validation and analysis portions of annual thermal performance tests, providing increased confidence in test data and reducing data analysis time. This paper will present the advanced pattern recognition methodology applied at Tri-State and the benefits in optimizing plant operations and assessing power plant performance.

  3. Adaptive myoelectric pattern recognition toward improved multifunctional prosthesis control.

    Science.gov (United States)

    Liu, Jie

    2015-04-01

    The non-stationary property of electromyography (EMG) signals in real life settings usually hinders the clinical application of the myoelectric pattern recognition for prosthesis control. The classical EMG pattern recognition approach consists of two separate steps: training and testing, without considering the changes between training and testing data induced by electrode shift, fatigue, impedance changes and psychological factors, and often results in performance degradation. The aim of this study was to develop an adaptive myoelectric pattern recognition system, aiming to retrain the classifier online with the testing data without supervision, providing a self-correction mechanism for suppressing misclassifications. This paper presents an adaptive unsupervised classifier based on support vector machine (SVM) to improve the classification performance. Experimental data from 15 healthy subjects were used to evaluate performance. Preliminary study on intra-session and inter-session EMG data was conducted to verify the performance of the unsupervised adaptive SVM classifier. The unsupervised adaptive SVM classifier outperformed the conventional SVM by 3.3% and 8.0% for the combination of time-domain and autoregressive features in the intra-session and inter-session tests, respectively. The proposed approach is capable of incorporating the useful information in testing data to the classification model by taking into account the overtime changes in the testing data with respect to the training data to retrain the original classifier, therefore providing a self-correction mechanism for suppressing misclassifications.

  4. Spatial pattern recognition of seismic events in South West Colombia

    Science.gov (United States)

    Benítez, Hernán D.; Flórez, Juan F.; Duque, Diana P.; Benavides, Alberto; Lucía Baquero, Olga; Quintero, Jiber

    2013-09-01

    Recognition of seismogenic zones in geographical regions supports seismic hazard studies. This recognition is usually based on visual, qualitative and subjective analysis of data. Spatial pattern recognition provides a well founded means to obtain relevant information from large amounts of data. The purpose of this work is to identify and classify spatial patterns in instrumental data of the South West Colombian seismic database. In this research, clustering tendency analysis validates whether seismic database possesses a clustering structure. A non-supervised fuzzy clustering algorithm creates groups of seismic events. Given the sensitivity of fuzzy clustering algorithms to centroid initial positions, we proposed a methodology to initialize centroids that generates stable partitions with respect to centroid initialization. As a result of this work, a public software tool provides the user with the routines developed for clustering methodology. The analysis of the seismogenic zones obtained reveals meaningful spatial patterns in South-West Colombia. The clustering analysis provides a quantitative location and dispersion of seismogenic zones that facilitates seismological interpretations of seismic activities in South West Colombia.

  5. Inherited variation in pattern recognition receptors and cancer: dangerous liaisons?

    Directory of Open Access Journals (Sweden)

    Yuzhalin AE

    2012-02-01

    Full Text Available Anton G Kutikhin, Arseniy E YuzhalinDepartment of Epidemiology, Kemerovo State Medical Academy, Kemerovo, Russian FederationAbstract: The group of pattern recognition receptors includes families of Toll-like receptors, NOD-like receptors, C-type lectin receptors, and RIG-I-like receptors. They are key sensors for a number of infectious agents, some of which are carcinogenic, and they launch an immune response against them. Inherited structural variation in genes encoding these receptors and proteins of their signaling pathways may affect their function, modulating cancer risk and features of cancer progression. Relevant malignancies, valuable gene polymorphisms, prime questions about future directions, and answers to these questions are analyzed in this review. It is possible to suggest that polymorphisms of genes encoding pattern recognition receptors and proteins of their signaling pathways may be associated with almost all cancer types, particularly with those in which carcinogenic infectious agents are responsible for the substantial share of cases (namely gastric cancer, colorectal cancer, liver cancer, cervical cancer, and nasopharyngeal carcinoma. The concept of selection of polymorphisms for further oncogenomic investigation, based on a combination of results from basic and epidemiological studies, is proposed.Keywords: pattern recognition receptors, Toll-like receptors, NOD-like receptors, C-type lectin receptors, cancer, gene polymorphisms

  6. Conditional Random Fields for Pattern Recognition Applied to Structured Data

    Directory of Open Access Journals (Sweden)

    Tom Burr

    2015-07-01

    Full Text Available Pattern recognition uses measurements from an input domain, X, to predict their labels from an output domain, Y. Image analysis is one setting where one might want to infer whether a pixel patch contains an object that is “manmade” (such as a building or “natural” (such as a tree. Suppose the label for a pixel patch is “manmade”; if the label for a nearby pixel patch is then more likely to be “manmade” there is structure in the output domain that can be exploited to improve pattern recognition performance. Modeling P(X is difficult because features between parts of the model are often correlated. Therefore, conditional random fields (CRFs model structured data using the conditional distribution P(Y|X = x, without specifying a model for P(X, and are well suited for applications with dependent features. This paper has two parts. First, we overview CRFs and their application to pattern recognition in structured problems. Our primary examples are image analysis applications in which there is dependence among samples (pixel patches in the output domain. Second, we identify research topics and present numerical examples.

  7. Plant systems for recognition of pathogen-associated molecular patterns.

    Science.gov (United States)

    Postel, Sandra; Kemmerling, Birgit

    2009-12-01

    Research of the last decade has revealed that plant immunity consists of different layers of defense that have evolved by the co-evolutional battle of plants with its pathogens. Particular light has been shed on PAMP- (pathogen-associated molecular pattern) triggered immunity (PTI) mediated by pattern recognition receptors. Striking similarities exist between the plant and animal innate immune system that point for a common optimized mechanism that has evolved independently in both kingdoms. Pattern recognition receptors (PRRs) from both kingdoms consist of leucine-rich repeat receptor complexes that allow recognition of invading pathogens at the cell surface. In plants, PRRs like FLS2 and EFR are controlled by a co-receptor SERK3/BAK1, also a leucine-rich repeat receptor that dimerizes with the PRRs to support their function. Pathogens can inject effector proteins into the plant cells to suppress the immune responses initiated after perception of PAMPs by PRRs via inhibition or degradation of the receptors. Plants have acquired the ability to recognize the presence of some of these effector proteins which leads to a quick and hypersensitive response to arrest and terminate pathogen growth.

  8. Iris Recognition System Using Fractal Dimensions of Haar Patterns

    Directory of Open Access Journals (Sweden)

    Patnala S. R. Chandra Murty

    2009-09-01

    Full Text Available Classification of iris templates based on their texture patterns is one of the most effective methods in iris recognition systems. This paper proposes a novel algorithm for automatic iris classification based on fractal dimensions of Haar wavelet transforms is presented. Fractal dimensions obtained from multiple scale features are used to characterize the textures completely. Haar wavelet is applied in order to extract the multiple scale features at different resolutions from the iris image. Fractal dimensions are estimated from these patterns and a classifier is used to recognize the given image from a data base. Performance comparison was made among different classifiers.

  9. Mixed pattern matching-based traffic abnormal behavior recognition.

    Science.gov (United States)

    Wu, Jian; Cui, Zhiming; Sheng, Victor S; Shi, Yujie; Zhao, Pengpeng

    2014-01-01

    A motion trajectory is an intuitive representation form in time-space domain for a micromotion behavior of moving target. Trajectory analysis is an important approach to recognize abnormal behaviors of moving targets. Against the complexity of vehicle trajectories, this paper first proposed a trajectory pattern learning method based on dynamic time warping (DTW) and spectral clustering. It introduced the DTW distance to measure the distances between vehicle trajectories and determined the number of clusters automatically by a spectral clustering algorithm based on the distance matrix. Then, it clusters sample data points into different clusters. After the spatial patterns and direction patterns learned from the clusters, a recognition method for detecting vehicle abnormal behaviors based on mixed pattern matching was proposed. The experimental results show that the proposed technical scheme can recognize main types of traffic abnormal behaviors effectively and has good robustness. The real-world application verified its feasibility and the validity.

  10. [Recognition of commensal microflora by pattern recognition receptors in human physiology and pathology].

    Science.gov (United States)

    Bondarenko, V M; Likhoded, V G

    2012-01-01

    Contemporary data on the interaction of commensal microflora and Toll-like pattern recognition receptors are presented. These receptors recognize normal intestine microflora in physiological conditions, and this interaction is necessary for the maintenance of homeostasis and damage reparation of the intestine, for the induction of heat shock cytoprotective proteins. As a side effect in disruption of immunologic tolerance and misbalance of protective immunological mechanisms, multiorgan pathologic changes of organs and tissues may develop, including chronic inflammation processes of various localization.

  11. Classifying Two-dimensional Hyporeductive Triple Algebras

    CERN Document Server

    Issa, A Nourou

    2010-01-01

    Two-dimensional real hyporeductive triple algebras (h.t.a.) are investigated. A classification of such algebras is presented. As a consequence, a classification of two-dimensional real Lie triple algebras (i.e. generalized Lie triple systems) and two-dimensional real Bol algebras is given.

  12. Do subitizing deficits in developmental dyscalculia involve pattern recognition weakness?

    Science.gov (United States)

    Ashkenazi, Sarit; Mark-Zigdon, Nitza; Henik, Avishai

    2013-01-01

    The abilities of children diagnosed with developmental dyscalculia (DD) were examined in two types of object enumeration: subitizing, and small estimation (5-9 dots). Subitizing is usually defined as a fast and accurate assessment of a number of small dots (range 1 to 4 dots), and estimation is an imprecise process to assess a large number of items (range 5 dots or more). Based on reaction time (RT) and accuracy analysis, our results indicated a deficit in the subitizing and small estimation range among DD participants in relation to controls. There are indications that subitizing is based on pattern recognition, thus presenting dots in a canonical shape in the estimation range should result in a subitizing-like pattern. In line with this theory, our control group presented a subitizing-like pattern in the small estimation range for canonically arranged dots, whereas the DD participants presented a deficit in the estimation of canonically arranged dots. The present finding indicates that pattern recognition difficulties may play a significant role in both subitizing and subitizing deficits among those with DD.

  13. On self-nonself discrimination in pattern recognition

    Institute of Scientific and Technical Information of China (English)

    LIU Yang; CHEN GuoYun; ZHENG Pan; TANG Jie

    2010-01-01

    @@ Wide distribution and broad reactivity are cardinal features of pattern recognition receptors that allow rapid mobilization of large numbers of effectors to deal with pathogens.However, these features come with significant baggage as the receptors have been shown to interact with many intracellular components, collectively called danger-associated molecular pattern (DAMP) because they are released during necrosis.It is puzzling how the host manages to mount sterilizing immunity to most pathogens and avoids doing fatal damage in response to aseptic tissue injuries.This paradox was reconciled when we revealed a novel pathway mediated by CD24 and its receptor, Siglec G in mice or Siglec 10 in humans.This pathway represses host responses to DAMPs but not pathogen-associated molecular patterns (PAMPs),thus allowing hosts to discriminate PAMP from DAMP.Disruption of this pathway leads to a devastating systemic inflammatory response when necrosis occurs in mice.Therefore, the CD24/Siglec 10 pathway enables a crossreactive pattern recognition pathway to initiate immunity against pathogens without significant immune-mediated self-destruction in case of tissue injuries.

  14. Two Levels Fusion Decision for Multispectral Image Pattern Recognition

    Science.gov (United States)

    Elmannai, H.; Loghmari, M. A.; Naceur, M. S.

    2015-10-01

    Major goal of multispectral data analysis is land cover classification and related applications. The dimension drawback leads to a small ratio of the remote sensing training data compared to the number of features. Therefore robust methods should be associated to overcome the dimensionality curse. The presented work proposed a pattern recognition approach. Source separation, feature extraction and decisional fusion are the main stages to establish an automatic pattern recognizer. The first stage is pre-processing and is based on non linear source separation. The mixing process is considered non linear with gaussians distributions. The second stage performs feature extraction for Gabor, Wavelet and Curvelet transform. Feature information presentation provides an efficient information description for machine vision projects. The third stage is a decisional fusion performed in two steps. The first step assign the best feature to each source/pattern using the accuracy matrix obtained from the learning data set. The second step is a source majority vote. Classification is performed by Support Vector Machine. Experimentation results show that the proposed fusion method enhances the classification accuracy and provide powerful tool for pattern recognition.

  15. Pattern recognition with “materials that compute”

    Science.gov (United States)

    Fang, Yan; Yashin, Victor V.; Levitan, Steven P.; Balazs, Anna C.

    2016-01-01

    Driven by advances in materials and computer science, researchers are attempting to design systems where the computer and material are one and the same entity. Using theoretical and computational modeling, we design a hybrid material system that can autonomously transduce chemical, mechanical, and electrical energy to perform a computational task in a self-organized manner, without the need for external electrical power sources. Each unit in this system integrates a self-oscillating gel, which undergoes the Belousov-Zhabotinsky (BZ) reaction, with an overlaying piezoelectric (PZ) cantilever. The chemomechanical oscillations of the BZ gels deflect the PZ layer, which consequently generates a voltage across the material. When these BZ-PZ units are connected in series by electrical wires, the oscillations of these units become synchronized across the network, where the mode of synchronization depends on the polarity of the PZ. We show that the network of coupled, synchronizing BZ-PZ oscillators can perform pattern recognition. The “stored” patterns are set of polarities of the individual BZ-PZ units, and the “input” patterns are coded through the initial phase of the oscillations imposed on these units. The results of the modeling show that the input pattern closest to the stored pattern exhibits the fastest convergence time to stable synchronization behavior. In this way, networks of coupled BZ-PZ oscillators achieve pattern recognition. Further, we show that the convergence time to stable synchronization provides a robust measure of the degree of match between the input and stored patterns. Through these studies, we establish experimentally realizable design rules for creating “materials that compute.” PMID:27617290

  16. Two-dimensional function photonic crystals

    CERN Document Server

    Wu, Xiang-Yao; Liu, Xiao-Jing; Liang, Yu

    2016-01-01

    In this paper, we have firstly proposed two-dimensional function photonic crystals, which the dielectric constants of medium columns are the functions of space coordinates $\\vec{r}$, it is different from the two-dimensional conventional photonic crystals constituting by the medium columns of dielectric constants are constants. We find the band gaps of two-dimensional function photonic crystals are different from the two-dimensional conventional photonic crystals, and when the functions form of dielectric constants are different, the band gaps structure should be changed, which can be designed into the appropriate band gaps structures by the two-dimensional function photonic crystals.

  17. Pattern Recognition of EEG Signals and Applications in Robotics

    Institute of Scientific and Technical Information of China (English)

    ZHANG Xiao-dong; CHENG Zhi-qiang; LI De-jun

    2006-01-01

    With the rapid development of brain computer interface (simply called BCI),electroencephalography (EEG) will be another interesting bio-electrical signal applied in robotics after EMG.In order to realize it finally,the accurate measurement and pattern recognition of EEG signal must be a very important and elementary research objective.Based on our current researches and some reports from the other international colleagues in the field,we deeply discuss the basic characteristics of EEG signal,the development and selection of EEG measurement system,feature extraction and recognition methods of EEG signal,and then review EEG's applications in robotics as well as the future research trends in this paper.

  18. Pattern recognition trigger electronics for an imaging atmospheric Cherenkov telescope

    CERN Document Server

    Bradbury, S M

    2002-01-01

    For imaging atmospheric Cherenkov telescopes, which aim to detect electromagnetic air showers with cameras consisting of several hundred photomultiplier pixels, the single pixel trigger rate is dominated by fluctuations in night sky brightness and by ion feedback in the photomultipliers. Pattern recognition trigger electronics may be used to reject night sky background images, thus reducing the data rate to a manageable level. The trigger system described here detects patterns of 2, 3 or 4 adjacent pixel signals within a 331 pixel camera and gives a positive trigger decision in 65 ns. The candidate pixel pattern is compared with the contents of a pre-programmed memory. With the trigger decision timing controlled by a fixed delay the time-jitter inherent in the use of programmable gate arrays is avoided. This system is now in routine operation at the Whipple 10 m Telescope.

  19. New insights into TRP channels: Interaction with pattern recognition receptors.

    Science.gov (United States)

    Han, Huirong; Yi, Fan

    2014-01-01

    An increasing number of studies have implicated that the activation of innate immune system and inflammatory mechanisms are of importance in the pathogenesis of numerous diseases. The innate immune system is present in almost all multicellular organisms in response to pathogens or tissue injury, which is performed via germ-line encoded pattern-recognition receptors (PRRs) to recognize pathogen-associated molecular patterns (PAMPs) or dangers-associated molecular patterns (DAMPs). Intracellular pathways linking immune and inflammatory response to ion channel expression and function have been recently identified. Among ion channels, transient receptor potential (TRP) channels are a major family of non-selective cation-permeable channels that function as polymodal cellular sensors involved in many physiological and pathological processes. In this review, we summarize current knowledge about classifications, functions, and interactions of TRP channels and PRRs, which may provide new insights into their roles in the pathogenesis of inflammatory diseases.

  20. Electronic system with memristive synapses for pattern recognition

    Science.gov (United States)

    Park, Sangsu; Chu, Myonglae; Kim, Jongin; Noh, Jinwoo; Jeon, Moongu; Hun Lee, Byoung; Hwang, Hyunsang; Lee, Boreom; Lee, Byung-Geun

    2015-05-01

    Memristive synapses, the most promising passive devices for synaptic interconnections in artificial neural networks, are the driving force behind recent research on hardware neural networks. Despite significant efforts to utilize memristive synapses, progress to date has only shown the possibility of building a neural network system that can classify simple image patterns. In this article, we report a high-density cross-point memristive synapse array with improved synaptic characteristics. The proposed PCMO-based memristive synapse exhibits the necessary gradual and symmetrical conductance changes, and has been successfully adapted to a neural network system. The system learns, and later recognizes, the human thought pattern corresponding to three vowels, i.e. /a /, /i /, and /u/, using electroencephalography signals generated while a subject imagines speaking vowels. Our successful demonstration of a neural network system for EEG pattern recognition is likely to intrigue many researchers and stimulate a new research direction.

  1. Multi-texture local ternary pattern for face recognition

    Science.gov (United States)

    Essa, Almabrok; Asari, Vijayan

    2017-05-01

    In imagery and pattern analysis domain a variety of descriptors have been proposed and employed for different computer vision applications like face detection and recognition. Many of them are affected under different conditions during the image acquisition process such as variations in illumination and presence of noise, because they totally rely on the image intensity values to encode the image information. To overcome these problems, a novel technique named Multi-Texture Local Ternary Pattern (MTLTP) is proposed in this paper. MTLTP combines the edges and corners based on the local ternary pattern strategy to extract the local texture features of the input image. Then returns a spatial histogram feature vector which is the descriptor for each image that we use to recognize a human being. Experimental results using a k-nearest neighbors classifier (k-NN) on two publicly available datasets justify our algorithm for efficient face recognition in the presence of extreme variations of illumination/lighting environments and slight variation of pose conditions.

  2. Implementation of pattern recognition algorithm based on RBF neural network

    Science.gov (United States)

    Bouchoux, Sophie; Brost, Vincent; Yang, Fan; Grapin, Jean Claude; Paindavoine, Michel

    2002-12-01

    In this paper, we present implementations of a pattern recognition algorithm which uses a RBF (Radial Basis Function) neural network. Our aim is to elaborate a quite efficient system which realizes real time faces tracking and identity verification in natural video sequences. Hardware implementations have been realized on an embedded system developed by our laboratory. This system is based on a DSP (Digital Signal Processor) TMS320C6x. The optimization of implementations allow us to obtain a processing speed of 4.8 images (240x320 pixels) per second with a correct rate of 95% of faces tracking and identity verification.

  3. 6th International Conference on Pattern Recognition and Machine Intelligence

    CERN Document Server

    Gawrysiak, Piotr; Kryszkiewicz, Marzena; Rybiński, Henryk

    2016-01-01

    This book presents valuable contributions devoted to practical applications of Machine Intelligence and Big Data in various branches of the industry. All the contributions are extended versions of presentations delivered at the Industrial Session the 6th International Conference on Pattern Recognition and Machine Intelligence (PREMI 2015) held in Warsaw, Poland at June 30- July 3, 2015, which passed through a rigorous reviewing process. The contributions address real world problems and show innovative solutions used to solve them. This volume will serve as a bridge between researchers and practitioners, as well as between different industry branches, which can benefit from sharing ideas and results.

  4. An Efficient Vein Pattern-based Recognition System

    CERN Document Server

    Soni, Mohit; Rao, M S; Gupta, Phalguni

    2010-01-01

    This paper presents an efficient human recognition system based on vein pattern from the palma dorsa. A new absorption based technique has been proposed to collect good quality images with the help of a low cost camera and light source. The system automatically detects the region of interest from the image and does the necessary preprocessing to extract features. A Euclidean Distance based matching technique has been used for making the decision. It has been tested on a data set of 1750 image samples collected from 341 individuals. The accuracy of the verification system is found to be 99.26% with false rejection rate (FRR) of 0.03%.

  5. Pattern Recognition and Forecast of Coal and Gas Outburst

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Coal and gas outburst is a complicated dynamic phenomenon in coal mines, Multi-factor Pattern Recognition is based on the relevant data obtained from research achievements of Geo-dynamic Division, With the help of spatial data management, the Neuron Network and Cluster algorithm are applied to predict the danger probability of coal and gas outburst in each cell of coal mining district. So a coal-mining district can be divided into three areas: dangerous area, minatory area, and safe area. This achievement has been successfully applied for regional prediction of coal and gas outburst in Huainan mining area in China.

  6. Infrared target recognition based on improved joint local ternary pattern

    Science.gov (United States)

    Sun, Junding; Wu, Xiaosheng

    2016-05-01

    This paper presents a simple, efficient, yet robust approach, named joint orthogonal combination of local ternary pattern, for automatic forward-looking infrared target recognition. It gives more advantages to describe the macroscopic textures and microscopic textures by fusing variety of scales than the traditional LBP-based methods. In addition, it can effectively reduce the feature dimensionality. Further, the rotation invariant and uniform scheme, the robust LTP, and soft concave-convex partition are introduced to enhance its discriminative power. Experimental results demonstrate that the proposed method can achieve competitive results compared with the state-of-the-art methods.

  7. The DELPHI Silicon Tracker in the global pattern recognition

    CERN Document Server

    Elsing, M

    2000-01-01

    ALEPH and DELPHI were the first experiments operating a silicon vertex detector at LEP. During the past 10 years of data taking the DELPHI Silicon Tracker was upgraded three times to follow the different tracking requirements for LEP 1 and LEP 2 as well as to improve the tracking performance. Several steps in the development of the pattern recognition software were done in order to understand and fully exploit the silicon tracker information. This article gives an overview of the final algorithms and concepts of the track reconstruction using the Silicon Tracker in DELPHI.

  8. Self-assembly of two-dimensional DNA crystals

    Institute of Scientific and Technical Information of China (English)

    SONG Cheng; CHEN Yaqing; WEI Shuai; YOU Xiaozeng; XIAO Shoujun

    2004-01-01

    Self-assembly of synthetic oligonucleotides into two-dimensional lattices presents a 'bottom-up' approach to the fabrication of devices on nanometer scale. We report the design and observation of two-dimensional crystalline forms of DNAs that are composed of twenty-one plane oligonucleotides and one phosphate-modified oligonucleotide. These synthetic sequences are designed to self-assemble into four double-crossover (DX) DNA tiles. The 'sticky ends' of these tiles that associate according to Watson-Crick's base pairing are programmed to build up specific periodic patterns upto tens of microns. The patterned crystals are visualized by the transmission electron microscopy.

  9. An auditory feature detection circuit for sound pattern recognition.

    Science.gov (United States)

    Schöneich, Stefan; Kostarakos, Konstantinos; Hedwig, Berthold

    2015-09-01

    From human language to birdsong and the chirps of insects, acoustic communication is based on amplitude and frequency modulation of sound signals. Whereas frequency processing starts at the level of the hearing organs, temporal features of the sound amplitude such as rhythms or pulse rates require processing by central auditory neurons. Besides several theoretical concepts, brain circuits that detect temporal features of a sound signal are poorly understood. We focused on acoustically communicating field crickets and show how five neurons in the brain of females form an auditory feature detector circuit for the pulse pattern of the male calling song. The processing is based on a coincidence detector mechanism that selectively responds when a direct neural response and an intrinsically delayed response to the sound pulses coincide. This circuit provides the basis for auditory mate recognition in field crickets and reveals a principal mechanism of sensory processing underlying the perception of temporal patterns.

  10. Memristor-MOS analog correlator for pattern recognition system.

    Science.gov (United States)

    Han, Ca-Ram; Lee, Sang-Jin; Oh, Kwang-Seok; Cho, Kyoungrok

    2013-05-01

    Emergence of new materials having significant improved properties continues to influence the formulation of novel architectures and as such new developments pave the way for innovative circuits and systems such as those required in visual imaging and recognition systems. In this paper we introduce a novel approach for the design of an analog comparator suitable for pattern matching using two Memristors as part of both the stored image data as well as that of the input signal. Our proposed comparator based on Memristor-CMOS fabrication process generates a signal indicating similarity/dissimilarity between two pattern data derived from image sensor and the corresponding Memristor-based template memory. For convenience, we also present an overview of a simplified Memristor model and hence provide simulation results for comparison with that of a conventional analog CMOS comparator.

  11. A bacterial tyrosine phosphatase inhibits plant pattern recognition receptor activation.

    Science.gov (United States)

    Macho, Alberto P; Schwessinger, Benjamin; Ntoukakis, Vardis; Brutus, Alexandre; Segonzac, Cécile; Roy, Sonali; Kadota, Yasuhiro; Oh, Man-Ho; Sklenar, Jan; Derbyshire, Paul; Lozano-Durán, Rosa; Malinovsky, Frederikke Gro; Monaghan, Jacqueline; Menke, Frank L; Huber, Steven C; He, Sheng Yang; Zipfel, Cyril

    2014-03-28

    Innate immunity relies on the perception of pathogen-associated molecular patterns (PAMPs) by pattern-recognition receptors (PRRs) located on the host cell's surface. Many plant PRRs are kinases. Here, we report that the Arabidopsis receptor kinase EF-TU RECEPTOR (EFR), which perceives the elf18 peptide derived from bacterial elongation factor Tu, is activated upon ligand binding by phosphorylation on its tyrosine residues. Phosphorylation of a single tyrosine residue, Y836, is required for activation of EFR and downstream immunity to the phytopathogenic bacterium Pseudomonas syringae. A tyrosine phosphatase, HopAO1, secreted by P. syringae, reduces EFR phosphorylation and prevents subsequent immune responses. Thus, host and pathogen compete to take control of PRR tyrosine phosphorylation used to initiate antibacterial immunity.

  12. Inductive class representation and its central role in pattern recognition

    Energy Technology Data Exchange (ETDEWEB)

    Goldfarb, L. [Univ. of New Brunswick, Fredericton, New Brunswick (Canada)

    1996-12-31

    The definition of inductive learning (IL) based on the new concept of inductive class representation (ICR) is given. The ICR, in addition to the ability to recognize a noise-corrupted object from the class, must also provide the means to generate every element in the resulting approximation of the class, i.e., the emphasis is on the generative capability of the ICR. Thus, the IL problem absorbs the main difficulties associated with a satisfactory formulation of the pattern recognition problem. This formulation of the IL problem appeared gradually as a result of the development of a fundamentally new formal model of IL--evolving transformation system (ETS) model. The model with striking clarity suggests that IL is the basic process which produces all the necessary {open_quotes}structures{close_quotes} for the recognition process, which is built directly on top of it. Based on the training set, the IL process, constructs optimal discriminatory (symbolic) weighted {open_quotes}features{close_quotes} which induce the corresponding optimal (symbolic) distance measure. The distance measure is a generalization of the weighted Levenshtein, or edit, distance defined on strings over a finite alphabet. The ETS model has emerged as a result of an attempt to unify two basic, but inadequate, approaches to pattern recognition: the classical vector space based and the syntactic approaches. ETS also elucidates with remarkable clarity the nature of the interrelationships between the corresponding symbolic and numeric mechanisms, in which the symbolic mechanisms play a more fundamental part. The model, in fact, suggests the first formal definition of the symbolic mathematical structure and also suggests a fundamentally different, more satisfactory, way of introducing the concept of fuzziness. The importance of the ICR concept to semiotics and semantics should become apparent as soon as one fully realizes that it represents the class and specifies the semantics of the class.

  13. Pattern recognition with TiOx-based memristive devices

    Directory of Open Access Journals (Sweden)

    Finn Zahari

    2015-07-01

    Full Text Available We report on the development of TiOx-based memristive devices for bio-inspired neuromorphic systems. In particular, capacitor like structures of Al/AlOx/TiOx/Al with, respectively 20 nm and 50 nm thick TiOx-layers were fabricated and analyzed in terms of their use in neural network circuits. Therefore, an equivalent circuit model is presented which mimics the observed device properties on a qualitative level and relies on mobile oxygen ions by taking electronic transport through local conducting filaments and hopping between TiOx defect states into account. The model also comprises back diffusion of oxygen ions and allows for a realistic description of the experimental recorded device characteristics. The in Refs. [1-3] reported computing paradigms for pattern recognition have been used as guidelines for a device performance investigation at the network level. In particular, simulations of a spiking neural network are presented which allows for pattern recognition. As input patterns hand written digits taken from the MNIST Data base have been used. Within the network the memristive devices are arranged in a cross-bar array connected by 196 input neurons and ten output neurons. While, each input neuron corresponds to a specific pixel of the image of the input pattern, the output neurons were implemented as spiking neurons. In addition, the output neurons were inhibitory linked within an winner-take-it-all network and consist of a homeostasis-like behavior for their spiking thresholds. Based on the network simulation essential requirements for the development of optimal memristive device for neuromorphic circuits are discussed.

  14. Playing Tag with ANN: Boosted Top Identification with Pattern Recognition

    CERN Document Server

    Almeida, Leandro G; Cliche, Mathieu; Lee, Seung J; Perelstein, Maxim

    2015-01-01

    Many searches for physics beyond the Standard Model at the Large Hadron Collider (LHC) rely on top tagging algorithms, which discriminate between boosted hadronic top quarks and the much more common jets initiated by light quarks and gluons. We note that the hadronic calorimeter (HCAL) effectively takes a "digital image" of each jet, with pixel intensities given by energy deposits in individual HCAL cells. Viewed in this way, top tagging becomes a canonical pattern recognition problem. With this motivation, we present a novel top tagging algorithm based on an Artificial Neural Network (ANN), one of the most popular approaches to pattern recognition. The ANN is trained on a large sample of boosted tops and light quark/gluon jets, and is then applied to independent test samples. The ANN tagger demonstrated excellent performance in a Monte Carlo study: for example, for jets with p_T in the 1100-1200 GeV range, 60% top-tag efficiency can be achieved with a 4% mis-tag rate. We discuss the physical features of the ...

  15. Assessment of Structural Damage Condition Based on Fuzzy Pattern Recognition

    Institute of Scientific and Technical Information of China (English)

    WU Zi-yan; ZHANG Yu

    2008-01-01

    This paper presents a new method of damage condition assessment that allows accommodating other types of uncertainties due to ambiguity, vagueness, and fuzziness that are statistically non-describable. In this method, healthy observations are used to construct a fuzzy set representing sound performance characteristics. Additionally, the bounds on the similarities among the structural damage states are prescribed by using the state similarity matrix. Thus, an optimal group fuzzy sets representing damage states such as little, moderate, and severe damage can be inferred as an inverse problem from healthy observations only. The optimal group of damage fuzzy sets is used to classify a set of observations at any unknown state of damage using the principles of fuzzy pattern recognition based on an approximate principle. This method can be embedded into the system of Structural Health Monitoring (SHM) to give advice about structural maintenance and life prediction. Finally, a case study, which comes from Reference [9] for damage pattern recognition is presented and discussed. The compared result illustrates our method is more effective and general, so it is very practical in engineering.

  16. Boosting training for myoelectric pattern recognition using Mixed-LDA.

    Science.gov (United States)

    Liu, Jianwei; Sheng, Xinjun; Zhang, Dingguo; Zhu, Xiangyang

    2014-01-01

    Pattern recognition based myoelectric prostheses (MP) need a training procedure for calibrating the classifier. Due to the non-stationarity inhered in surface electromyography (sEMG) signals, the system should be retrained day by day in long-term use of MP. To boost the training procedure in later periods, we propose a method, namely Mixed-LDA, which computes the parameters of LDA through combining the model estimated on the incoming training samples of the current day with the prior models available from earlier days. An experiment ranged for 10 days on 5 subjects was carried out to simulate the long-term use of MP. Results show that the Mixed-LDA is significantly better than the baseline method (LDA) when few samples are used as training set in the new (current) day. For instance, in the task including 13 hand and wrist motions, the average classification rate of the Mixed-LDA is 88.74% when the number of training samples is 104 (LDA: 79.32%). This implies that the approach has the potential to improve the usability of MP based on pattern recognition by reducing the training time.

  17. Hadamard States and Two-dimensional Gravity

    CERN Document Server

    Salehi, H

    2001-01-01

    We have used a two-dimensional analog of the Hadamard state-condition to study the local constraints on the two-point function of a linear quantum field conformally coupled to a two-dimensional gravitational background. We develop a dynamical model in which the determination of the state of the quantum field is essentially related to the determination of a conformal frame. A particular conformal frame is then introduced in which a two-dimensional gravitational equation is established.

  18. Topological defects in two-dimensional crystals

    OpenAIRE

    Chen, Yong; Qi, Wei-Kai

    2008-01-01

    By using topological current theory, we study the inner topological structure of the topological defects in two-dimensional (2D) crystal. We find that there are two elementary point defects topological current in two-dimensional crystal, one for dislocations and the other for disclinations. The topological quantization and evolution of topological defects in two-dimensional crystals are discussed. Finally, We compare our theory with Brownian-dynamics simulations in 2D Yukawa systems.

  19. Computational intelligence in multi-feature visual pattern recognition hand posture and face recognition using biologically inspired approaches

    CERN Document Server

    Pisharady, Pramod Kumar; Poh, Loh Ai

    2014-01-01

    This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds. The book has 3 parts. Part 1 describes various research issues in the field with a survey of the related literature. Part 2 presents computational intelligence based algorithms for feature selection and classification. The algorithms are discriminative and fast. The main application area considered is hand posture recognition. The book also discusses utility of these algorithms in other visual as well as non-visual pattern recognition tasks including face recognition, general object recognition and cancer / tumor classification. Part 3 presents biologically inspired algorithms for feature extraction. The visual cortex model based features discussed have invariance with respect to appearance and size of the hand, and provide good...

  20. Equivalency of two-dimensional algebras

    Energy Technology Data Exchange (ETDEWEB)

    Santos, Gildemar Carneiro dos; Pomponet Filho, Balbino Jose S. [Universidade Federal da Bahia (UFBA), BA (Brazil). Inst. de Fisica

    2011-07-01

    Full text: Let us consider a vector z = xi + yj over the field of real numbers, whose basis (i,j) satisfy a given algebra. Any property of this algebra will be reflected in any function of z, so we can state that the knowledge of the properties of an algebra leads to more general conclusions than the knowledge of the properties of a function. However structural properties of an algebra do not change when this algebra suffers a linear transformation, though the structural constants defining this algebra do change. We say that two algebras are equivalent to each other whenever they are related by a linear transformation. In this case, we have found that some relations between the structural constants are sufficient to recognize whether or not an algebra is equivalent to another. In spite that the basis transform linearly, the structural constants change like a third order tensor, but some combinations of these tensors result in a linear transformation, allowing to write the entries of the transformation matrix as function of the structural constants. Eventually, a systematic way to find the transformation matrix between these equivalent algebras is obtained. In this sense, we have performed the thorough classification of associative commutative two-dimensional algebras, and find that even non-division algebra may be helpful in solving non-linear dynamic systems. The Mandelbrot set was used to have a pictorial view of each algebra, since equivalent algebras result in the same pattern. Presently we have succeeded in classifying some non-associative two-dimensional algebras, a task more difficult than for associative one. (author)

  1. The use of global image characteristics for neural network pattern recognitions

    Science.gov (United States)

    Kulyas, Maksim O.; Kulyas, Oleg L.; Loshkarev, Aleksey S.

    2017-04-01

    The recognition system is observed, where the information is transferred by images of symbols generated by a television camera. For descriptors of objects the coefficients of two-dimensional Fourier transformation generated in a special way. For solution of the task of classification the one-layer neural network trained on reference images is used. Fast learning of a neural network with a single neuron calculation of coefficients is applied.

  2. Principal Component Analysis for pattern recognition in volcano seismic spectra

    Science.gov (United States)

    Unglert, Katharina; Jellinek, A. Mark

    2016-04-01

    Variations in the spectral content of volcano seismicity can relate to changes in volcanic activity. Low-frequency seismic signals often precede or accompany volcanic eruptions. However, they are commonly manually identified in spectra or spectrograms, and their definition in spectral space differs from one volcanic setting to the next. Increasingly long time series of monitoring data at volcano observatories require automated tools to facilitate rapid processing and aid with pattern identification related to impending eruptions. Furthermore, knowledge transfer between volcanic settings is difficult if the methods to identify and analyze the characteristics of seismic signals differ. To address these challenges we have developed a pattern recognition technique based on a combination of Principal Component Analysis and hierarchical clustering applied to volcano seismic spectra. This technique can be used to characterize the dominant spectral components of volcano seismicity without the need for any a priori knowledge of different signal classes. Preliminary results from applying our method to volcanic tremor from a range of volcanoes including K¯ı lauea, Okmok, Pavlof, and Redoubt suggest that spectral patterns from K¯ı lauea and Okmok are similar, whereas at Pavlof and Redoubt spectra have their own, distinct patterns.

  3. Pattern-Recognition System for Approaching a Known Target

    Science.gov (United States)

    Huntsberger, Terrance; Cheng, Yang

    2008-01-01

    A closed-loop pattern-recognition system is designed to provide guidance for maneuvering a small exploratory robotic vehicle (rover) on Mars to return to a landed spacecraft to deliver soil and rock samples that the spacecraft would subsequently bring back to Earth. The system could be adapted to terrestrial use in guiding mobile robots to approach known structures that humans could not approach safely, for such purposes as reconnaissance in military or law-enforcement applications, terrestrial scientific exploration, and removal of explosive or other hazardous items. The system has been demonstrated in experiments in which the Field Integrated Design and Operations (FIDO) rover (a prototype Mars rover equipped with a video camera for guidance) is made to return to a mockup of Mars-lander spacecraft. The FIDO rover camera autonomously acquires an image of the lander from a distance of 125 m in an outdoor environment. Then under guidance by an algorithm that performs fusion of multiple line and texture features in digitized images acquired by the camera, the rover traverses the intervening terrain, using features derived from images of the lander truss structure. Then by use of precise pattern matching for determining the position and orientation of the rover relative to the lander, the rover aligns itself with the bottom of ramps extending from the lander, in preparation for climbing the ramps to deliver samples to the lander. The most innovative aspect of the system is a set of pattern-recognition algorithms that govern a three-phase visual-guidance sequence for approaching the lander. During the first phase, a multifeature fusion algorithm integrates the outputs of a horizontal-line-detection algorithm and a wavelet-transform-based visual-area-of-interest algorithm for detecting the lander from a significant distance. The horizontal-line-detection algorithm is used to determine candidate lander locations based on detection of a horizontal deck that is part of the

  4. Nonlinear dynamics of pattern formation and pattern recognition in the rabbit olfactory bulb

    Science.gov (United States)

    Baird, Bill

    1986-10-01

    A mathematical model of the process of pattern recognition in the first olfactory sensory cortex of the rabbit is presented. It explains the formation and alteration of spatial patterns in neural activity observed experimentally during classical Pavlovian conditioning. On each inspiration of the animal, a surge of receptor input enters the olfactory bulb. EEG activity recorded at the surface of the bulb undergoes a transition from a low amplitude background state of temporal disorder to coherent oscillation. There is a distinctive spatial pattern of rms amplitude in this oscillation which changes reliably to a second pattern during each successful recognition by the animal of a conditioned stimulus odor. When a new odor is paired as conditioned stimulus, these patterns are replaced by new patterns that stabilize as the animal adapts to the new environment. I will argue that a unification of the theories of pattern formation and associative memory is required to account for these observations. This is achieved in a model of the bulb as a discrete excitable medium with spatially inhomogeneous coupling expressed by a connection matrix. The theory of multiple Hopf bifurcations is employed to find coupled equations for the amplitudes of competing unstable oscillatory modes. These may be created in the system by proper coupling and selectively evoked by specific classes of inputs. This allows a view of limit cycle attractors as “stored” fixed points of a gradient vector field and thereby recovers the more familiar dynamical systems picture of associative memory.

  5. Strongly interacting two-dimensional Dirac fermions

    NARCIS (Netherlands)

    Lim, L.K.; Lazarides, A.; Hemmerich, Andreas; de Morais Smith, C.

    2009-01-01

    We show how strongly interacting two-dimensional Dirac fermions can be realized with ultracold atoms in a two-dimensional optical square lattice with an experimentally realistic, inherent gauge field, which breaks time reversal and inversion symmetries. We find remarkable phenomena in a temperature

  6. Topology optimization of two-dimensional waveguides

    DEFF Research Database (Denmark)

    Jensen, Jakob Søndergaard; Sigmund, Ole

    2003-01-01

    In this work we use the method of topology optimization to design two-dimensional waveguides with low transmission loss.......In this work we use the method of topology optimization to design two-dimensional waveguides with low transmission loss....

  7. Improving myoelectric pattern recognition robustness to electrode shift by changing interelectrode distance and electrode configuration.

    Science.gov (United States)

    Young, Aaron J; Hargrove, Levi J; Kuiken, Todd A

    2012-03-01

    Pattern recognition of myoelectric signals for prosthesis control has been extensively studied in research settings and is close to clinical implementation. These systems are capable of intuitively controlling the next generation of dexterous prosthetic hands. However, pattern recognition systems perform poorly in the presence of electrode shift, defined as movement of surface electrodes with respect to the underlying muscles. This paper focused on investigating the optimal interelectrode distance, channel configuration, and electromyography feature sets for myoelectric pattern recognition in the presence of electrode shift. Increasing interelectrode distance from 2 to 4 cm improved pattern recognition system performance in terms of classification error and controllability (p pattern recognition control. Finally, we investigated different feature sets for pattern recognition control using a linear discriminant analysis classifier and found that an autoregressive set significantly (p < 0.01) reduced sensitivity to electrode shift compared to a traditional time-domain feature set.

  8. The Role of Pattern Recognition Receptors in Intestinal Inflammation

    Science.gov (United States)

    Fukata, Masayuki; Arditi, Moshe

    2013-01-01

    Recognition of microorganisms by pattern recognition receptors (PRRs) is the primary component of innate immunity that is responsible for the maintenance of host-microbial interactions in intestinal mucosa. Disregulation in host-commensal interactions has been implicated as the central pathogenesis of inflammatory bowel disease (IBD), which predisposes to developing colorectal cancer. Recent animal studies have begun to outline some unique physiology and pathology involving each PRR signaling in the intestine. The major roles played by PRRs in the gut appear to be regulation of the number and the composition of commensal bacteria, epithelial proliferation and mucosal permiability in response to epithelial injury. In addition, PRR signaling in lamina propria immune cells may be involved in induction of inflammation in response to invasion of pathogens. Because some PRR-deficient mice have shown variable susceptibility to colitis, the outcome of intestinal inflammation may be modified depending on PRR signaling in epithelial cells, immune cells, and the composition of commensal flora. Through recent findings in animal models of IBD, this review will discuss how abnormal PRR signaling may contribute to the pathogenesis of inflammation and inflammation-associated tumorigenesis in the intestine. PMID:23515136

  9. A novel thermal face recognition approach using face pattern words

    Science.gov (United States)

    Zheng, Yufeng

    2010-04-01

    A reliable thermal face recognition system can enhance the national security applications such as prevention against terrorism, surveillance, monitoring and tracking, especially at nighttime. The system can be applied at airports, customs or high-alert facilities (e.g., nuclear power plant) for 24 hours a day. In this paper, we propose a novel face recognition approach utilizing thermal (long wave infrared) face images that can automatically identify a subject at both daytime and nighttime. With a properly acquired thermal image (as a query image) in monitoring zone, the following processes will be employed: normalization and denoising, face detection, face alignment, face masking, Gabor wavelet transform, face pattern words (FPWs) creation, face identification by similarity measure (Hamming distance). If eyeglasses are present on a subject's face, an eyeglasses mask will be automatically extracted from the querying face image, and then masked with all comparing FPWs (no more transforms). A high identification rate (97.44% with Top-1 match) has been achieved upon our preliminary face dataset (of 39 subjects) from the proposed approach regardless operating time and glasses-wearing condition.e

  10. Polygon cluster pattern recognition based on new visual distance

    Science.gov (United States)

    Shuai, Yun; Shuai, Haiyan; Ni, Lin

    2007-06-01

    The pattern recognition of polygon clusters is a most attention-getting problem in spatial data mining. The paper carries through a research on this problem, based on spatial cognition principle and visual recognition Gestalt principle combining with spatial clustering method, and creates two innovations: First, the paper carries through a great improvement to the concept---"visual distance". In the definition of this concept, not only are Euclid's Distance, orientation difference and dimension discrepancy comprehensively thought out, but also is "similarity degree of object shape" crucially considered. In the calculation of "visual distance", the distance calculation model is built using Delaunay Triangulation geometrical structure. Second, the research adopts spatial clustering analysis based on MST Tree. In the design of pruning algorithm, the study initiates data automatism delamination mechanism and introduces Simulated Annealing Optimization Algorithm. This study provides a new research thread for GIS development, namely, GIS is an intersection principle, whose research method should be open and diverse. Any mature technology of other relative principles can be introduced into the study of GIS, but, they need to be improved on technical measures according to the principles of GIS as "spatial cognition science". Only to do this, can GIS develop forward on a higher and stronger plane.

  11. Distorted Pattern Recognition and Analysis with the Help of IEf Graph Representation

    Directory of Open Access Journals (Sweden)

    Adam Sedziwy

    2002-01-01

    Full Text Available An algorithm for distorted pattern recognition is presented. lt's generalization of M Flasinski results (Pattern Recognition, 27, 1-16, 1992. A new formalism allows to make both qualitative and quantitive distortion analysis. It also enlarges parser flexibility by extending the set of patterns which may be recognized.

  12. Auditory Pattern Recognition and Brief Tone Discrimination of Children with Reading Disorders

    Science.gov (United States)

    Walker, Marianna M.; Givens, Gregg D.; Cranford, Jerry L.; Holbert, Don; Walker, Letitia

    2006-01-01

    Auditory pattern recognition skills in children with reading disorders were investigated using perceptual tests involving discrimination of frequency and duration tonal patterns. A behavioral test battery involving recognition of the pattern of presentation of tone triads was used in which individual components differed in either frequency or…

  13. ARM11-based video capture system and two-dimensional code recognition%基于ARM11的视频采集系统及二维码识别

    Institute of Scientific and Technical Information of China (English)

    段东波; 靳天玉

    2013-01-01

    With the development of information technology,more and more application of ARM embedded system as the core. Therefore,further research ARM core and based on the ARM core application will make it better to meet the practical need. This article through to ARM core as well as the embedded Linux research, using QT programming,realized the video acquisition which based on Samsung S3C6410 processor and QR code recognition.The article emphasis on describes the process of Embedded Linux transplantation, Video acquisition and QR code recognition.%随着信息技术的发展,越来越多的领域应用ARM作为嵌入式系统的核心。因此,深入研究ARM核心以及基于ARM核心的应用使其更好的符合实际需要,便显得尤为重要。本文通过对ARM核心以及嵌入式Linux的研究,利用QT编程,实现了基于三星S3C6410处理器的视频采集以及二维码识别。文章重点描述了嵌入式Linux的移植、视频采集以及二维码识别等应用程序的流程。

  14. A Gesture Recognition System for Detecting Behavioral Patterns of ADHD.

    Science.gov (United States)

    Bautista, Miguel Ángel; Hernández-Vela, Antonio; Escalera, Sergio; Igual, Laura; Pujol, Oriol; Moya, Josep; Violant, Verónica; Anguera, María T

    2016-01-01

    We present an application of gesture recognition using an extension of dynamic time warping (DTW) to recognize behavioral patterns of attention deficit hyperactivity disorder (ADHD). We propose an extension of DTW using one-class classifiers in order to be able to encode the variability of a gesture category, and thus, perform an alignment between a gesture sample and a gesture class. We model the set of gesture samples of a certain gesture category using either Gaussian mixture models or an approximation of convex hulls. Thus, we add a theoretical contribution to classical warping path in DTW by including local modeling of intraclass gesture variability. This methodology is applied in a clinical context, detecting a group of ADHD behavioral patterns defined by experts in psychology/psychiatry, to provide support to clinicians in the diagnose procedure. The proposed methodology is tested on a novel multimodal dataset (RGB plus depth) of ADHD children recordings with behavioral patterns. We obtain satisfying results when compared to standard state-of-the-art approaches in the DTW context.

  15. Pattern recognition receptors and central nervous system repair.

    Science.gov (United States)

    Kigerl, Kristina A; de Rivero Vaccari, Juan Pablo; Dietrich, W Dalton; Popovich, Phillip G; Keane, Robert W

    2014-08-01

    Pattern recognition receptors (PRRs) are part of the innate immune response and were originally discovered for their role in recognizing pathogens by ligating specific pathogen associated molecular patterns (PAMPs) expressed by microbes. Now the role of PRRs in sterile inflammation is also appreciated, responding to endogenous stimuli referred to as "damage associated molecular patterns" (DAMPs) instead of PAMPs. The main families of PRRs include Toll-like receptors (TLRs), Nod-like receptors (NLRs), RIG-like receptors (RLRs), AIM2-like receptors (ALRs), and C-type lectin receptors. Broad expression of these PRRs in the CNS and the release of DAMPs in and around sites of injury suggest an important role for these receptor families in mediating post-injury inflammation. Considerable data now show that PRRs are among the first responders to CNS injury and activation of these receptors on microglia, neurons, and astrocytes triggers an innate immune response in the brain and spinal cord. Here we discuss how the various PRR families are activated and can influence injury and repair processes following CNS injury.

  16. Online Pattern Recognition for the ALICE High Level Trigger

    CERN Document Server

    Lindenstruth, V; Röhrich, D; Skaali, B; Steinbeck, T M; Stock, Reinhard; Tilsner, H; Ullaland, K; Vestbø, A S; Vik, T

    2004-01-01

    The ALICE High Level Trigger has to process data online, in order to select interesting (sub)events, or to compress data efficiently by modeling techniques.Focusing on the main data source, the Time Projection Chamber (TPC), we present two pattern recognition methods under investigation: a sequential approach "cluster finder" and "track follower") and an iterative approach ("track candidate finder" and "cluster deconvoluter"). We show, that the former is suited for pp and low multiplicity PbPb collisions, whereas the latter might be applicable for high multiplicity PbPb collisions, if it turns out, that more than 8000 charged particles would have to be reconstructed inside the TPC. Based on the developed tracking schemes we show, that using modeling techniques a compression factor of around 10 might be achievable

  17. Online Pattern Recognition for the ALICE High Level Trigger

    Science.gov (United States)

    Lindenstruth, V.; Loizides, C.; Rohrich, D.; Skaali, B.; Steinbeck, T.; Stock, R.; Tilsner, H.; Ullaland, K.; Vestbo, A.; Vik, T.

    2004-06-01

    The ALICE high level trigger has to process data online, in order to select interesting (sub)events, or to compress data efficiently by modeling techniques. Focusing on the main data source, the time projection chamber (TPC), we present two pattern recognition methods under investigation: a sequential approach (cluster finder and track follower) and an iterative approach (track candidate finder and cluster deconvoluter). We show, that the former is suited for pp and low multiplicity PbPb collisions, whereas the latter might be applicable for high multiplicity PbPb collisions of dN/dy>3000. Based on the developed tracking schemes we show that using modeling techniques, a compression factor of around 10 might be achievable.

  18. Air Target Fuzzy Pattern Recognition Threat-Judgment Model

    Institute of Scientific and Technical Information of China (English)

    童幼堂; 王建明

    2003-01-01

    Threat-judgment is a complicated fuzzy inference problem. Up to now no relevant unified theory and measuring standard have been developed. It is very difficult to establish a threat-judgment model with high reliability in the air defense system for the naval warships. Air target threat level judgment is an important component in naval warship combat command decision-making systems. According to the threat level judgment of air targets during the air defense of single naval warship, a fuzzy pattern recognition model for judging the threat from air targets is established. Then an algorithm for identifying the parameters in the model is presented. The model has an adaptive feature and can dynamically update its parameters according to the state change of the attacking targets and the environment. The method presented here can be used for the air defense system threat judgment in the naval warships.

  19. Terahertz Imaging for Biomedical Applications Pattern Recognition and Tomographic Reconstruction

    CERN Document Server

    Yin, Xiaoxia; Abbott, Derek

    2012-01-01

    Terahertz Imaging for Biomedical Applications: Pattern Recognition and Tomographic Reconstruction presents the necessary algorithms needed to assist screening, diagnosis, and treatment, and these algorithms will play a critical role in the accurate detection of abnormalities present in biomedical imaging. Terahertz biomedical imaging has become an area of interest due to its ability to simultaneously acquire both image and spectral information. Terahertz imaging systems are being commercialized with an increasing number of trials performed in a biomedical setting. Terahertz tomographic imaging and detection technology contributes to the ability to identify opaque objects with clear boundaries,and would be useful to both in vivo and ex vivo environments. This book also: Introduces terahertz radiation techniques and provides a number of topical examples of signal and image processing, as well as machine learning Presents the most recent developments in an emerging field, terahertz radiation Utilizes new methods...

  20. Pattern recognition on brain magnetic resonance imaging in alpha dystroglycanopathies

    Directory of Open Access Journals (Sweden)

    Bindu Parayil

    2010-01-01

    Full Text Available Alpha dystroglycanopathies are heterogeneous group of disorders both phenotypically and genetically. A subgroup of these patients has characteristic brain imaging findings. Four patients with typical imaging findings of alpha dystroglycanopathy are reported. Phenotypic features included: global developmental delay, contractures, hypotonia and oculomotor abnormalities in all. Other manifestations were consanguinity (3, seizures (3, macrocephaly (1, microcephaly (3, retinal changes (2 and hypogenitalism (2. Magnetic resonance imaging (MRI of the brain revealed polymicrogyria, white matter changes, pontine hypoplasia, and subcortical cerebellar cysts in all the patients, ventriculomegaly, callosal abnormalities, and absent septum pellucidum in two and Dandy -Walker variant malformation in three. Magnetic resonace imaging of the first cousin of one the patient had the same characteristic imaging features. Brain imaging findings were almost identical despite heterogeneity in clinical presentation and histopathological features. Pattern recognition of MR imaging features may serve as a clue to the diagnosis of alpha dystroglycanopathy.

  1. Orthogonal combination of local binary patterns for dynamic texture recognition

    Science.gov (United States)

    Chen, Yin; Guo, Xuejun; Klein, Dominik

    2015-12-01

    Dynamic texture (DT) is an extension of texture to the temporal domain. Recognizing DTs has received increasing attention. Volume local binary pattern (VLBP) is the most widely used descriptor for DTs. However, it is time consuming to recognize DTs using VLBP due to the large scale of data and the high dimensionality of the descriptor itself. In this paper, we propose a new operator called orthogonal combination of VLBP (OC-VLBP) for DT recognition. The original VLBP is decomposed both longitudinally and latitudinally, and then combined to constitute the OC-VLBP operator, so that the dimensionality of the original VLBP descriptor is lowered. The experimental results show that the proposed operator significantly reduces the computational costs of recognizing DTs without much loss in recognizing accuracy.

  2. Quantitative EEG Applying the Statistical Recognition Pattern Method

    DEFF Research Database (Denmark)

    Engedal, Knut; Snaedal, Jon; Hoegh, Peter

    2015-01-01

    BACKGROUND/AIM: The aim of this study was to examine the discriminatory power of quantitative EEG (qEEG) applying the statistical pattern recognition (SPR) method to separate Alzheimer's disease (AD) patients from elderly individuals without dementia and from other dementia patients. METHODS...... accepted criteria by at least 2 clinicians. EEGs were recorded in a standardized way and analyzed independently of the clinical diagnoses, using the SPR method. RESULTS: In receiver operating characteristic curve analyses, the qEEGs separated AD patients from healthy elderly individuals with an area under...... the curve (AUC) of 0.90, representing a sensitivity of 84% and a specificity of 81%. The qEEGs further separated patients with Lewy body dementia or Parkinson's disease dementia from AD patients with an AUC of 0.9, a sensitivity of 85% and a specificity of 87%. CONCLUSION: qEEG using the SPR method could...

  3. Pattern recognition computation using action potential timing for stimulus representation

    Science.gov (United States)

    Hopfield, J. J.

    1995-07-01

    A computational model is described in which the sizes of variables are represented by the explicit times at which action potentials occur, rather than by the more usual 'firing rate' of neurons. The comparison of patterns over sets of analogue variables is done by a network using different delays for different information paths. This mode of computation explains how one scheme of neuroarchitecture can be used for very different sensory modalities and seemingly different computations. The oscillations and anatomy of the mammalian olfactory systems have a simple interpretation in terms of this representation, and relate to processing in the auditory system. Single-electrode recording would not detect such neural computing. Recognition 'units' in this style respond more like radial basis function units than elementary sigmoid units.

  4. SVD-EBP Algorithm for Iris Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Mr. Babasaheb G. Patil

    2011-12-01

    Full Text Available This paper proposes a neural network approach based on Error Back Propagation (EBP for classification of different eye images. To reduce the complexity of layered neural network the dimensions of input vectors are optimized using Singular Value Decomposition (SVD. The main objective of this work is to prove usefulness of SVD to form a compact set of features for classification by EBP algorithm. The results of our work indicate that optimum classification values are obtained with SVD dimensions of 20 and maximum number of classes as 9 with the state-of-the art computational resources The details of this combined system named as SVD-EBP system for Iris pattern recognition and the results thereof are presented in this paper

  5. Pattern Recognition and Natural Language Processing: State of the Art

    Directory of Open Access Journals (Sweden)

    Mirjana Kocaleva

    2016-05-01

    Full Text Available Development of information technologies is growing steadily. With the latest software technologies development and application of the methods of artificial intelligence and machine learning intelligence embededs in computers, the expectations are that in near future computers will be able to solve problems themselves like people do. Artificial intelligence emulates human behavior on computers. Rather than executing instructions one by one, as theyare programmed, machine learning employs prior experience/data that is used in the process of system’s training. In this state of the art paper, common methods in AI, such as machine learning, pattern recognition and the natural language processing (NLP are discussed. Also are given standard architecture of NLP processing system and the level thatisneeded for understanding NLP. Lastly the statistical NLP processing and multi-word expressions are described.

  6. Innate immune pattern recognition: a cell biological perspective.

    Science.gov (United States)

    Brubaker, Sky W; Bonham, Kevin S; Zanoni, Ivan; Kagan, Jonathan C

    2015-01-01

    Receptors of the innate immune system detect conserved determinants of microbial and viral origin. Activation of these receptors initiates signaling events that culminate in an effective immune response. Recently, the view that innate immune signaling events rely on and operate within a complex cellular infrastructure has become an important framework for understanding the regulation of innate immunity. Compartmentalization within this infrastructure provides the cell with the ability to assign spatial information to microbial detection and regulate immune responses. Several cell biological processes play a role in the regulation of innate signaling responses; at the same time, innate signaling can engage cellular processes as a form of defense or to promote immunological memory. In this review, we highlight these aspects of cell biology in pattern-recognition receptor signaling by focusing on signals that originate from the cell surface, from endosomal compartments, and from within the cytosol.

  7. Proposal for the development of 3D Vertically Integrated Pattern Recognition Associative Memory (VIPRAM)

    Energy Technology Data Exchange (ETDEWEB)

    Deptuch, Gregory; Hoff, Jim; Kwan, Simon; Lipton, Ron; Liu, Ted; Ramberg, Erik; Todri, Aida; Yarema, Ray; /Fermilab; Demarteua, Marcel,; Drake, Gary; Weerts, Harry; /Argonne /Chicago U. /Padua U. /INFN, Padua

    2010-10-01

    Future particle physics experiments looking for rare processes will have no choice but to address the demanding challenges of fast pattern recognition in triggering as detector hit density becomes significantly higher due to the high luminosity required to produce the rare process. The authors propose to develop a 3D Vertically Integrated Pattern Recognition Associative Memory (VIPRAM) chip for HEP applications, to advance the state-of-the-art for pattern recognition and track reconstruction for fast triggering.

  8. Rotation-Invariant Neural Pattern Recognition System Using Extracted Descriptive Symmetrical Patterns

    Directory of Open Access Journals (Sweden)

    YRehab F. Abdel-Kader, Rabab M. Ramadan, Fayez W. Zaki , and Emad El-Sayed1

    2012-05-01

    Full Text Available In this paper a novel rotation-invariant neural-based pattern recognition system is proposed. The system incorporates a new image preprocessing technique to extract rotation-invariant descriptive patterns from the shapes. The proposed system applies a three phase algorithm on the shape image to extract the rotation-invariant pattern. First, the orientation angle of the shape is calculated using a newly developed shape orientation technique. The technique is effective, computationally inexpensive and can be applied to shapes with several non-equally separated axes of symmetry. A simple method to calculate the average angle of the shape’s axes of symmetry is defined. In this technique, only the first moment of inertia is considered to reduce the computational cost. In the second phase, the image is rotated using a simple rotation technique to adapt its orientation angle to any specific reference angle. Finally in the third phase, the image preprocessor creates a symmetrical pattern about the axis with the calculated orientation angle and the perpendicular axis on it. Performing this operation in both the neural network training and application phases, ensures that the test rotated patterns will enter the network in the same position as in the training. Three different approaches were used to create the symmetrical patterns from the shapes. Experimental results indicate that the proposed approach is very effective and provide a recognition rate up to 99.5%.

  9. Proceedings of the Second Annual Symposium on Mathematical Pattern Recognition and Image Analysis Program

    Science.gov (United States)

    Guseman, L. F., Jr. (Principal Investigator)

    1984-01-01

    Several papers addressing image analysis and pattern recognition techniques for satellite imagery are presented. Texture classification, image rectification and registration, spatial parameter estimation, and surface fitting are discussed.

  10. Image Reconstruction, Recognition, Using Image Processing, Pattern Recognition and the Hough Transform.

    Science.gov (United States)

    Seshadri, M. D.

    1992-01-01

    In this dissertation research, we have demonstrated the need for integration of various imaging methodologies, such as image reconstruction from projections, image processing, pattern and feature recognition using chain codes and the Hough transform. Further an integration of these image processing techniques have been brought about for medical imaging systems. An example of this is, classification and identification of brain scans, into normal, haemorrhaged, and lacunar infarcted brain scans. Low level processing was performed using LOG and a variation of LOG. Intermediate level processing used contour completion and chain encoding. Hough transform was used to detect any analytic shapes in the edge images. All these information were used by the data abstraction routine which also extracted information from the user, in the form of a general query. These were input into a backpropagation, which is a very popular supervised neural network. During learning process an output vector was supplied by the expert to the neural network. While performing the neural network compared the input and with the help of the weight matrix computed the output. This output was compared with the expert's opinion and a percentage deviation was calculated. In the case of brain scans this value was about 95%, when the test input vector did not vary, by more than two pixels with the training or learning input vector. A good classification of the brain scans were performed using the integrated imaging system. Identification of various organs in the abdominal region was also successful, within 90% recognition rate, depending on the noise in the image.

  11. Feature dimensionality reduction for myoelectric pattern recognition: a comparison study of feature selection and feature projection methods.

    Science.gov (United States)

    Liu, Jie

    2014-12-01

    This study investigates the effect of the feature dimensionality reduction strategies on the classification of surface electromyography (EMG) signals toward developing a practical myoelectric control system. Two dimensionality reduction strategies, feature selection and feature projection, were tested on both EMG feature sets, respectively. A feature selection based myoelectric pattern recognition system was introduced to select the features by eliminating the redundant features of EMG recordings instead of directly choosing a subset of EMG channels. The Markov random field (MRF) method and a forward orthogonal search algorithm were employed to evaluate the contribution of each individual feature to the classification, respectively. Our results from 15 healthy subjects indicate that, with a feature selection analysis, independent of the type of feature set, across all subjects high overall accuracies can be achieved in classification of seven different forearm motions with a small number of top ranked original EMG features obtained from the forearm muscles (average overall classification accuracy >95% with 12 selected EMG features). Compared to various feature dimensionality reduction techniques in myoelectric pattern recognition, the proposed filter-based feature selection approach is independent of the type of classification algorithms and features, which can effectively reduce the redundant information not only across different channels, but also cross different features in the same channel. This may enable robust EMG feature dimensionality reduction without needing to change ongoing, practical use of classification algorithms, an important step toward clinical utility.

  12. Dynamical Pattern Vector in Pattern Recognition with the Use of Thermal Images

    Directory of Open Access Journals (Sweden)

    Kuś Zygmunt

    2016-01-01

    Full Text Available The goal of the following paper was to develop the methodology of object tracking in adverse conditions. Suddenly appearing clouds, fog or smoke could be the examples of atmospheric conditions. We used thermal and visible images in each moment during object tracking. We computed the pattern vectors of the tracked object on the basis of the visual and thermal images separately. The pattern vector and current feature vector for an image of a given type are used to compute the distance between the object pattern vector and feature vector calculated for a given location of the aperture. It is calculated for both: the visual and thermal image. The crux of the proposed method was the algorithm of selection which distance (for visual or thermal image was used for object tracking. It was obtained by multiplying the values of the distances between a pattern vector and current feature vector by some coefficients (different for thermal and visual images. The values of these coefficients depended on the usefulness of a given type of an image for pattern recognition. This usefulness was defined by the variability of the particular pixels in the image which is represented by calculating gradient in the image. On top of that, this study presented the examples of the object recognition by means of the developed method.

  13. Two-dimensional localized structures in harmonically forced oscillatory systems

    Science.gov (United States)

    Ma, Y.-P.; Knobloch, E.

    2016-12-01

    Two-dimensional spatially localized structures in the complex Ginzburg-Landau equation with 1:1 resonance are studied near the simultaneous presence of a steady front between two spatially homogeneous equilibria and a supercritical Turing bifurcation on one of them. The bifurcation structures of steady circular fronts and localized target patterns are computed in the Turing-stable and Turing-unstable regimes. In particular, localized target patterns grow along the solution branch via ring insertion at the core in a process reminiscent of defect-mediated snaking in one spatial dimension. Stability of axisymmetric solutions on these branches with respect to axisymmetric and nonaxisymmetric perturbations is determined, and parameter regimes with stable axisymmetric oscillons are identified. Direct numerical simulations reveal novel depinning dynamics of localized target patterns in the radial direction, and of circular and planar localized hexagonal patterns in the fully two-dimensional system.

  14. Early recognition of apical ballooning syndrome by global longitudinal strain using speckle tracking imaging--the evil eye pattern, a case series.

    Science.gov (United States)

    Sosa, Sualy; Banchs, Jose

    2015-07-01

    We report 4 cases of patients diagnosed with stress-induced cardiomyopathy and the pattern of typical apical ballooning syndrome (ABS), who presented to our institution with chest pain, mildly elevated cardiac enzymes and ischemic electrocardiographic changes, found to have severe hypokinesis or akinesis of the mid to apical segments with dynamic basal segments on two-dimensional (2D) echocardiography along with a global longitudinal strain (GLS) pattern markedly different from the typical left anterior descending artery (LAD) myocardial infarction pattern. All of them had a similar GLS pattern on presentation, which was easy to recognize on the polar map the day of the event. Three of the patients underwent left heart catheterization and found to have nonobstructive coronary artery disease (CAD). We discuss the usefulness of early recognition of ABS using GLS images. © 2015, Wiley Periodicals, Inc.

  15. Pattern recognition algorithm reveals how birds evolve individual egg pattern signatures.

    Science.gov (United States)

    Stoddard, Mary Caswell; Kilner, Rebecca M; Town, Christopher

    2014-06-18

    Pattern-based identity signatures are commonplace in the animal kingdom, but how they are recognized is poorly understood. Here we develop a computer vision tool for analysing visual patterns, NATUREPATTERNMATCH, which breaks new ground by mimicking visual and cognitive processes known to be involved in recognition tasks. We apply this tool to a long-standing question about the evolution of recognizable signatures. The common cuckoo (Cuculus canorus) is a notorious cheat that sneaks its mimetic eggs into nests of other species. Can host birds fight back against cuckoo forgery by evolving highly recognizable signatures? Using NATUREPATTERNMATCH, we show that hosts subjected to the best cuckoo mimicry have evolved the most recognizable egg pattern signatures. Theory predicts that effective pattern signatures should be simultaneously replicable, distinctive and complex. However, our results reveal that recognizable signatures need not incorporate all three of these features. Moreover, different hosts have evolved effective signatures in diverse ways.

  16. Network patterns recognition for automatic dermatologic images classification

    Science.gov (United States)

    Grana, Costantino; Daniele, Vanini; Pellacani, Giovanni; Seidenari, Stefania; Cucchiara, Rita

    2007-03-01

    In this paper we focus on the problem of automatic classification of melanocytic lesions, aiming at identifying the presence of reticular patterns. The recognition of reticular lesions is an important step in the description of the pigmented network, in order to obtain meaningful diagnostic information. Parameters like color, size or symmetry could benefit from the knowledge of having a reticular or non-reticular lesion. The detection of network patterns is performed with a three-steps procedure. The first step is the localization of line points, by means of the line points detection algorithm, firstly described by Steger. The second step is the linking of such points into a line considering the direction of the line at its endpoints and the number of line points connected to these. Finally a third step discards the meshes which couldn't be closed at the end of the linking procedure and the ones characterized by anomalous values of area or circularity. The number of the valid meshes left and their area with respect to the whole area of the lesion are the inputs of a discriminant function which classifies the lesions into reticular and non-reticular. This approach was tested on two balanced (both sets are formed by 50 reticular and 50 non-reticular images) training and testing sets. We obtained above 86% correct classification of the reticular and non-reticular lesions on real skin images, with a specificity value never lower than 92%.

  17. Two Dimensional Plasmonic Cavities on Moire Surfaces

    Science.gov (United States)

    Balci, Sinan; Kocabas, Askin; Karabiyik, Mustafa; Kocabas, Coskun; Aydinli, Atilla

    2010-03-01

    We investigate surface plasmon polariton (SPP) cavitiy modes on two dimensional Moire surfaces in the visible spectrum. Two dimensional hexagonal Moire surface can be recorded on a photoresist layer using Interference lithography (IL). Two sequential exposures at slightly different angles in IL generate one dimensional Moire surfaces. Further sequential exposure for the same sample at slightly different angles after turning the sample 60 degrees around its own axis generates two dimensional hexagonal Moire cavity. Spectroscopic reflection measurements have shown plasmonic band gaps and cavity states at all the azimuthal angles (omnidirectional cavity and band gap formation) investigated. The plasmonic band gap edge and the cavity states energies show six fold symmetry on the two dimensional Moire surface as measured in reflection measurements.

  18. Two-dimensional function photonic crystals

    Science.gov (United States)

    Liu, Xiao-Jing; Liang, Yu; Ma, Ji; Zhang, Si-Qi; Li, Hong; Wu, Xiang-Yao; Wu, Yi-Heng

    2017-01-01

    In this paper, we have studied two-dimensional function photonic crystals, in which the dielectric constants of medium columns are the functions of space coordinates , that can become true easily by electro-optical effect and optical kerr effect. We calculated the band gap structures of TE and TM waves, and found the TE (TM) wave band gaps of function photonic crystals are wider (narrower) than the conventional photonic crystals. For the two-dimensional function photonic crystals, when the dielectric constant functions change, the band gaps numbers, width and position should be changed, and the band gap structures of two-dimensional function photonic crystals can be adjusted flexibly, the needed band gap structures can be designed by the two-dimensional function photonic crystals, and it can be of help to design optical devices.

  19. Two-Dimensional Planetary Surface Lander

    Science.gov (United States)

    Hemmati, H.; Sengupta, A.; Castillo, J.; McElrath, T.; Roberts, T.; Willis, P.

    2014-06-01

    A systems engineering study was conducted to leverage a new two-dimensional (2D) lander concept with a low per unit cost to enable scientific study at multiple locations with a single entry system as the delivery vehicle.

  20. Facial expression recognition based on improved local ternary pattern and stacked auto-encoder

    Science.gov (United States)

    Wu, Yao; Qiu, Weigen

    2017-08-01

    In order to enhance the robustness of facial expression recognition, we propose a method of facial expression recognition based on improved Local Ternary Pattern (LTP) combined with Stacked Auto-Encoder (SAE). This method uses the improved LTP extraction feature, and then uses the improved depth belief network as the detector and classifier to extract the LTP feature. The combination of LTP and improved deep belief network is realized in facial expression recognition. The recognition rate on CK+ databases has improved significantly.

  1. Dioxin screening in fish product by pattern recognition of biomarkers.

    Science.gov (United States)

    Bassompierre, Marc; Tomasi, Giorgio; Munck, Lars; Bro, Rasmus; Engelsen, Søren Balling

    2007-04-01

    Two alternative, cost- and time-effective dioxin screening methods relying on two categories of potential lipid biomarkers were investigated. A dioxin range varying from 1.1 to 47.1 pg PCDD/F TEQ-WHO/g lipid using 64 fish meal samples was used for model calibration. The methods were based on multivariate models using either (1) fatty acid composition monitored by GC-FID or (2) fluorescence landscape signals analysed using the PARAFAC model and in both cases predicting dioxin content as pgPCDD/F TEQ-WHO/g lipid. In both cases, Partial Least Squares (PLS) regression was performed for predicting the dioxin content of a sample. The GC-FID data analyses was based on automatic peak alignment and integration, enabling extraction of the area of 140 peaks from the gas chromatograms, as opposed to the 31 fatty acids usually considered for fish oil characterisation. In addition to classic PLS employing the whole dataset for calibration, a two-step local PLS modeling approach was performed based upon an initial selection of k number of calibration samples providing the best match to the prediction sample using a so-called k Nearest Neighbors (kNN) approach, then followed by PLS calibration on these kNN selected samples for dioxin prediction. Fluorescence spectroscopy offers a promising non-invasive and ultra-rapid technique, with less than two minutes analysis time. However, fluorescence spectroscopy using the pattern recognition "kNN-PLS" yielded a correlation of 0.76 (r2) and a high root mean square error of prediction of 11.4 pg PCDD/F TEQ-WHO/g lipid. The predictions were improved when the PLS calibration was performed on all the sample with a root mean square error of prediction of 7.0 pg PCDD/F TEQ-WHO/g lipid. Unfortunately, these results failed to demonstrate the potential of fluorophore monitoring as a screening method. In contrast, the overall best screening performance was obtained with the fatty acid profile, when the kNN-PLS combination employed for pattern

  2. Parallel optical Walsh expansion in a pattern recognition preprocessor using planar microlens array

    Science.gov (United States)

    Murashige, Kimio; Akiba, Atsushi; Baba, Toshihiko; Iga, Kenichi

    1992-05-01

    A parallel optical processor developed for a pattern recognition system using a planar microlens array and a Walsh orthogonal expansion spatial filter is developed. The parallel optical Walsh expansion of multiple images made by the planar microlens array with good accuracy, which assures 99-percent recognition of simple numeral characters in the system, is demonstrated. A novel selection method of Walsh expansion coefficients is proposed in order to enlarge the tolerance of the recognition rate against the deformation of input patterns.

  3. Digital image pattern recognition system using normalized Fourier transform and normalized analytical Fourier-Mellin transform

    Science.gov (United States)

    Vélez-Rábago, Rodrigo; Solorza-Calderón, Selene; Jordan-Aramburo, Adina

    2016-12-01

    This work presents an image pattern recognition system invariant to translation, scale and rotation. The system uses the Fourier transform to achieve the invariance to translation and the analytical Forier-Mellin transform for the invariance to scale and rotation. According with the statistical theory of box-plots, the pattern recognition system has a confidence level at least of 95.4%.

  4. Study on improved complete two dimensional principal component analysis and its application to gait recognition%改进的完全二维主成分分析及其在步态识别中的应用研究

    Institute of Scientific and Technical Information of China (English)

    贲晛烨; 安实; 王科俊; 王健

    2011-01-01

    This paper improved complete two dimensional principal component analysis, and proposed three different weighted strategies.It analyzed the essence of weighted scheme in detail.To evaluate the validity of the proposed method and apply it to gait recognition, it conducted experiments on CASIA (B) gait database.Experimental results show that the selection of weighted power exponent has great influence on the recognition result, and can improve the recognition performance by picking the best weight value in experiments.In the end, discussed the reason why the recognition rate of gait with a bag was low in the various walking states.%对完全二维主成分分析算法进行改进,提出三种不同的加权策略,详细地分析它们的本质,并将其应用到步态识别中.在中国科学院自动化所提供的CASIA(B)步态数据库下验证加权方案的有效性,实验结果表明加权幂指数的选取对识别结果的影响比较大,通过实验可以选取最佳的权值,能够做到提高识别性能.最后针对各个行走状态下的步态,分析了背包步态识别率低的原因.

  5. FPGA design of correlation-based pattern recognition

    Science.gov (United States)

    Jridi, Maher; Alfalou, Ayman

    2017-05-01

    Optical/Digital pattern recognition and tracking based on optical/digital correlation are a well-known techniques to detect, identify and localize a target object in a scene. Despite the limited number of treatments required by the correlation scheme, computational time and resources are relatively high. The most computational intensive treatment required by the correlation is the transformation from spatial to spectral domain and then from spectral to spatial domain. Furthermore, these transformations are used on optical/digital encryption schemes like the double random phase encryption (DRPE). In this paper, we present a VLSI architecture for the correlation scheme based on the fast Fourier transform (FFT). One interesting feature of the proposed scheme is its ability to stream image processing in order to perform correlation for video sequences. A trade-off between the hardware consumption and the robustness of the correlation can be made in order to understand the limitations of the correlation implementation in reconfigurable and portable platforms. Experimental results obtained from HDL simulations and FPGA prototype have demonstrated the advantages of the proposed scheme.

  6. Pattern recognition for the anti PANDA forward tacking systems

    Energy Technology Data Exchange (ETDEWEB)

    Galuska, Martin J.; Hu, Jifeng; Kuehn, Wolfgang; Lange, J. Soeren; Liang, Yutie; Muenchow, David; Spruck, Bjoern [Giessen Univ. (Germany). 2. Physikalisches Inst.; Collaboration: PANDA-Collaboration

    2013-07-01

    The anti PANDA experiment is planned to start operation in 2017 as part of the future FAIR facility, which will be built at the site of GSI in Darmstadt. It will utilize antiproton beams with beam momentum resolutions of Δ p/p ≤ 2 . 10{sup -5}. anti PANDA is particularly suited to perform resonance scans of exclusively produced charmonium(-like) states, and thus provide absolute measurements of resonance widths. As it is a fixed target experiment a large fraction of final state particles will be boosted toward forward angles in aforementioned reactions facilitating the importance of forward tracking for the success of the experiment. The key challenges for forward tracking arise from the beam momentum dependent magnetic fields: anti PANDA is comprised of a barrel part with a solenoid field of B{sub z} = 2 T and a forward detector with a dipole field of B . L = 2 Tm. The interference of the aforementioned magnetic fields leads to complex particle tracks making accurate matching of hits challenging. A Hough Transform algorithm for pattern recognition in the Forward Tracking System based upon a parabola track model was developed. The performance of a proof-of-concept implementation was studied with detailed PandaRoot simulations. The algorithm is presented in the poster alongside results for momentum resolution, efficiency and ghost rate. Alternative approaches are discussed. Results for momentum resolution, efficiency and ghost rate are discussed.

  7. Pattern Recognition by Dinamic Feature Analysis Based on PCA

    Directory of Open Access Journals (Sweden)

    Juliana Valencia-Aguirre

    2009-06-01

    Full Text Available Usually, in pattern recognition problems we represent the observations by mean of measures on appropriate variables of data set, these measures can be categorized as Static and Dynamic Features. Static features are not always an accurate representation of data. In these sense, many phenomena are better modeled by dynamic changes on their measures. The advantage of using an extended form (dynamic features is the inclusion of new information that allows us to get a better representation of the object. Nevertheless, sometimes it is difficult in a classification stage to deal with dynamic features, because the associated computational cost often can be higher than we deal with static features. For analyzing such representations, we use Principal Component Analysis (PCA, arranging dynamic data in such a way we can consider variations related to the intrinsic dynamic of observations. Therefore, the method made possible to evaluate the dynamic information about of the observations on a lower dimensionality feature space without decreasing the accuracy performance. Algorithms were tested on real data to classify pathological speech from normal voices, and using PCA for dynamic feature selection, as well.

  8. Interpolation by two-dimensional cubic convolution

    Science.gov (United States)

    Shi, Jiazheng; Reichenbach, Stephen E.

    2003-08-01

    This paper presents results of image interpolation with an improved method for two-dimensional cubic convolution. Convolution with a piecewise cubic is one of the most popular methods for image reconstruction, but the traditional approach uses a separable two-dimensional convolution kernel that is based on a one-dimensional derivation. The traditional, separable method is sub-optimal for the usual case of non-separable images. The improved method in this paper implements the most general non-separable, two-dimensional, piecewise-cubic interpolator with constraints for symmetry, continuity, and smoothness. The improved method of two-dimensional cubic convolution has three parameters that can be tuned to yield maximal fidelity for specific scene ensembles characterized by autocorrelation or power-spectrum. This paper illustrates examples for several scene models (a circular disk of parametric size, a square pulse with parametric rotation, and a Markov random field with parametric spatial detail) and actual images -- presenting the optimal parameters and the resulting fidelity for each model. In these examples, improved two-dimensional cubic convolution is superior to several other popular small-kernel interpolation methods.

  9. Weighted Local Active Pixel Pattern (WLAPP for Face Recognition in Parallel Computation Environment

    Directory of Open Access Journals (Sweden)

    Gundavarapu Mallikarjuna Rao

    2013-10-01

    Full Text Available Abstract  - The availability of multi-core technology resulted totally new computational era. Researchers are keen to explore available potential in state of art-machines for breaking the bearer imposed by serial computation. Face Recognition is one of the challenging applications on so ever computational environment. The main difficulty of traditional Face Recognition algorithms is lack of the scalability. In this paper Weighted Local Active Pixel Pattern (WLAPP, a new scalable Face Recognition Algorithm suitable for parallel environment is proposed.  Local Active Pixel Pattern (LAPP is found to be simple and computational inexpensive compare to Local Binary Patterns (LBP. WLAPP is developed based on concept of LAPP. The experimentation is performed on FG-Net Aging Database with deliberately introduced 20% distortion and the results are encouraging. Keywords — Active pixels, Face Recognition, Local Binary Pattern (LBP, Local Active Pixel Pattern (LAPP, Pattern computing, parallel workers, template, weight computation.  

  10. TWO-DIMENSIONAL TOPOLOGY OF COSMOLOGICAL REIONIZATION

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yougang; Xu, Yidong; Chen, Xuelei [Key Laboratory of Computational Astrophysics, National Astronomical Observatories, Chinese Academy of Sciences, Beijing, 100012 China (China); Park, Changbom [School of Physics, Korea Institute for Advanced Study, 85 Hoegiro, Dongdaemun-gu, Seoul 130-722 (Korea, Republic of); Kim, Juhan, E-mail: wangyg@bao.ac.cn, E-mail: cbp@kias.re.kr [Center for Advanced Computation, Korea Institute for Advanced Study, 85 Hoegiro, Dongdaemun-gu, Seoul 130-722 (Korea, Republic of)

    2015-11-20

    We study the two-dimensional topology of the 21-cm differential brightness temperature for two hydrodynamic radiative transfer simulations and two semi-numerical models. In each model, we calculate the two-dimensional genus curve for the early, middle, and late epochs of reionization. It is found that the genus curve depends strongly on the ionized fraction of hydrogen in each model. The genus curves are significantly different for different reionization scenarios even when the ionized faction is the same. We find that the two-dimensional topology analysis method is a useful tool to constrain the reionization models. Our method can be applied to the future observations such as those of the Square Kilometre Array.

  11. Two dimensional topology of cosmological reionization

    CERN Document Server

    Wang, Yougang; Xu, Yidong; Chen, Xuelei; Kim, Juhan

    2015-01-01

    We study the two-dimensional topology of the 21-cm differential brightness temperature for two hydrodynamic radiative transfer simulations and two semi-numerical models. In each model, we calculate the two dimensional genus curve for the early, middle and late epochs of reionization. It is found that the genus curve depends strongly on the ionized fraction of hydrogen in each model. The genus curves are significantly different for different reionization scenarios even when the ionized faction is the same. We find that the two-dimensional topology analysis method is a useful tool to constrain the reionization models. Our method can be applied to the future observations such as those of the Square Kilometer Array.

  12. Explorative data analysis of two-dimensional electrophoresis gels

    DEFF Research Database (Denmark)

    Schultz, J.; Gottlieb, D.M.; Petersen, Marianne Kjerstine

    2004-01-01

    Methods for classification of two-dimensional (2-DE) electrophoresis gels based on multivariate data analysis are demonstrated. Two-dimensional gels of ten wheat varieties are analyzed and it is demonstrated how to classify the wheat varieties in two qualities and a method for initial screening...... of gels is presented. First, an approach is demonstrated in which no prior knowledge of the separated proteins is used. Alignment of the gels followed by a simple transformation of data makes it possible to analyze the gels in an automated explorative manner by principal component analysis, to determine...... if the gels should be further analyzed. A more detailed approach is done by analyzing spot volume lists by principal components analysis and partial least square regression. The use of spot volume data offers a mean to investigate the spot pattern and link the classified protein patterns to distinct spots...

  13. Molecular assembly on two-dimensional materials

    Science.gov (United States)

    Kumar, Avijit; Banerjee, Kaustuv; Liljeroth, Peter

    2017-02-01

    Molecular self-assembly is a well-known technique to create highly functional nanostructures on surfaces. Self-assembly on two-dimensional (2D) materials is a developing field driven by the interest in functionalization of 2D materials in order to tune their electronic properties. This has resulted in the discovery of several rich and interesting phenomena. Here, we review this progress with an emphasis on the electronic properties of the adsorbates and the substrate in well-defined systems, as unveiled by scanning tunneling microscopy. The review covers three aspects of the self-assembly. The first one focuses on non-covalent self-assembly dealing with site-selectivity due to inherent moiré pattern present on 2D materials grown on substrates. We also see that modification of intermolecular interactions and molecule–substrate interactions influences the assembly drastically and that 2D materials can also be used as a platform to carry out covalent and metal-coordinated assembly. The second part deals with the electronic properties of molecules adsorbed on 2D materials. By virtue of being inert and possessing low density of states near the Fermi level, 2D materials decouple molecules electronically from the underlying metal substrate and allow high-resolution spectroscopy and imaging of molecular orbitals. The moiré pattern on the 2D materials causes site-selective gating and charging of molecules in some cases. The last section covers the effects of self-assembled, acceptor and donor type, organic molecules on the electronic properties of graphene as revealed by spectroscopy and electrical transport measurements. Non-covalent functionalization of 2D materials has already been applied for their application as catalysts and sensors. With the current surge of activity on building van der Waals heterostructures from atomically thin crystals, molecular self-assembly has the potential to add an extra level of flexibility and functionality for applications ranging

  14. Two-dimensional x-ray diffraction

    CERN Document Server

    He, Bob B

    2009-01-01

    Written by one of the pioneers of 2D X-Ray Diffraction, this useful guide covers the fundamentals, experimental methods and applications of two-dimensional x-ray diffraction, including geometry convention, x-ray source and optics, two-dimensional detectors, diffraction data interpretation, and configurations for various applications, such as phase identification, texture, stress, microstructure analysis, crystallinity, thin film analysis and combinatorial screening. Experimental examples in materials research, pharmaceuticals, and forensics are also given. This presents a key resource to resea

  15. Matching Two-dimensional Gel Electrophoresis' Spots

    DEFF Research Database (Denmark)

    Dos Anjos, António; AL-Tam, Faroq; Shahbazkia, Hamid Reza

    2012-01-01

    This paper describes an approach for matching Two-Dimensional Electrophoresis (2-DE) gels' spots, involving the use of image registration. The number of false positive matches produced by the proposed approach is small, when compared to academic and commercial state-of-the-art approaches. This ar......This paper describes an approach for matching Two-Dimensional Electrophoresis (2-DE) gels' spots, involving the use of image registration. The number of false positive matches produced by the proposed approach is small, when compared to academic and commercial state-of-the-art approaches...

  16. Mobility anisotropy of two-dimensional semiconductors

    Science.gov (United States)

    Lang, Haifeng; Zhang, Shuqing; Liu, Zhirong

    2016-12-01

    The carrier mobility of anisotropic two-dimensional semiconductors under longitudinal acoustic phonon scattering was theoretically studied using deformation potential theory. Based on the Boltzmann equation with the relaxation time approximation, an analytic formula of intrinsic anisotropic mobility was derived, showing that the influence of effective mass on mobility anisotropy is larger than those of deformation potential constant or elastic modulus. Parameters were collected for various anisotropic two-dimensional materials (black phosphorus, Hittorf's phosphorus, BC2N , MXene, TiS3, and GeCH3) to calculate their mobility anisotropy. It was revealed that the anisotropic ratio is overestimated by the previously described method.

  17. Towards two-dimensional search engines

    OpenAIRE

    Ermann, Leonardo; Chepelianskii, Alexei D.; Shepelyansky, Dima L.

    2011-01-01

    We study the statistical properties of various directed networks using ranking of their nodes based on the dominant vectors of the Google matrix known as PageRank and CheiRank. On average PageRank orders nodes proportionally to a number of ingoing links, while CheiRank orders nodes proportionally to a number of outgoing links. In this way the ranking of nodes becomes two-dimensional that paves the way for development of two-dimensional search engines of new type. Statistical properties of inf...

  18. Large-area settlement pattern recognition from Landsat-8 data

    Science.gov (United States)

    Wieland, Marc; Pittore, Massimiliano

    2016-09-01

    The study presents an image processing and analysis pipeline that combines object-based image analysis with a Support Vector Machine to derive a multi-layered settlement product from Landsat-8 data over large areas. 43 image scenes are processed over large parts of Central Asia (Southern Kazakhstan, Kyrgyzstan, Tajikistan and Eastern Uzbekistan). The main tasks tackled by this work include built-up area identification, settlement type classification and urban structure types pattern recognition. Besides commonly used accuracy assessments of the resulting map products, thorough performance evaluations are carried out under varying conditions to tune algorithm parameters and assess their applicability for the given tasks. As part of this, several research questions are being addressed. In particular the influence of the improved spatial and spectral resolution of Landsat-8 on the SVM performance to identify built-up areas and urban structure types are evaluated. Also the influence of an extended feature space including digital elevation model features is tested for mountainous regions. Moreover, the spatial distribution of classification uncertainties is analyzed and compared to the heterogeneity of the building stock within the computational unit of the segments. The study concludes that the information content of Landsat-8 images is sufficient for the tested classification tasks and even detailed urban structures could be extracted with satisfying accuracy. Freely available ancillary settlement point location data could further improve the built-up area classification. Digital elevation features and pan-sharpening could, however, not significantly improve the classification results. The study highlights the importance of dynamically tuned classifier parameters, and underlines the use of Shannon entropy computed from the soft answers of the SVM as a valid measure of the spatial distribution of classification uncertainties.

  19. Pattern recognition control outperforms conventional myoelectric control in upper limb patients with targeted muscle reinnervation.

    Science.gov (United States)

    Hargrove, Levi J; Lock, Blair A; Simon, Ann M

    2013-01-01

    Pattern recognition myoelectric control shows great promise as an alternative to conventional amplitude based control to control multiple degree of freedom prosthetic limbs. Many studies have reported pattern recognition classification error performances of less than 10% during offline tests; however, it remains unclear how this translates to real-time control performance. In this contribution, we compare the real-time control performances between pattern recognition and direct myoelectric control (a popular form of conventional amplitude control) for participants who had received targeted muscle reinnervation. The real-time performance was evaluated during three tasks; 1) a box and blocks task, 2) a clothespin relocation task, and 3) a block stacking task. Our results found that pattern recognition significantly outperformed direct control for all three performance tasks. Furthermore, it was found that pattern recognition was configured much quicker. The classification error of the pattern recognition systems used by the patients was found to be 16% ±(1.6%) suggesting that systems with this error rate may still provide excellent control. Finally, patients qualitatively preferred using pattern recognition control and reported the resulting control to be smoother and more consistent.

  20. Kernel Learning of Histogram of Local Gabor Phase Patterns for Face Recognition

    Directory of Open Access Journals (Sweden)

    Bineng Zhong

    2008-06-01

    Full Text Available This paper proposes a new face recognition method, named kernel learning of histogram of local Gabor phase pattern (K-HLGPP, which is based on Daugman’s method for iris recognition and the local XOR pattern (LXP operator. Unlike traditional Gabor usage exploiting the magnitude part in face recognition, we encode the Gabor phase information for face classification by the quadrant bit coding (QBC method. Two schemes are proposed for face recognition. One is based on the nearest-neighbor classifier with chi-square as the similarity measurement, and the other makes kernel discriminant analysis for HLGPP (K-HLGPP using histogram intersection and Gaussian-weighted chi-square kernels. The comparative experiments show that K-HLGPP achieves a higher recognition rate than other well-known face recognition systems on the large-scale standard FERET, FERET200, and CAS-PEAL-R1 databases.

  1. On Assisting a Visual-Facial Affect Recognition System with Keyboard-Stroke Pattern Information

    Science.gov (United States)

    Stathopoulou, I.-O.; Alepis, E.; Tsihrintzis, G. A.; Virvou, M.

    Towards realizing a multimodal affect recognition system, we are considering the advantages of assisting a visual-facial expression recognition system with keyboard-stroke pattern information. Our work is based on the assumption that the visual-facial and keyboard modalities are complementary to each other and that their combination can significantly improve the accuracy in affective user models. Specifically, we present and discuss the development and evaluation process of two corresponding affect recognition subsystems, with emphasis on the recognition of 6 basic emotional states, namely happiness, sadness, surprise, anger and disgust as well as the emotion-less state which we refer to as neutral. We find that emotion recognition by the visual-facial modality can be aided greatly by keyboard-stroke pattern information and the combination of the two modalities can lead to better results towards building a multimodal affect recognition system.

  2. Soft computing approach to pattern classification and object recognition a unified concept

    CERN Document Server

    Ray, Kumar S

    2012-01-01

    Soft Computing Approach to Pattern Classification and Object Recognition establishes an innovative, unified approach to supervised pattern classification and model-based occluded object recognition. The book also surveys various soft computing tools, fuzzy relational calculus (FRC), genetic algorithm (GA) and multilayer perceptron (MLP) to provide a strong foundation for the reader. The supervised approach to pattern classification and model-based approach to occluded object recognition are treated in one framework , one based on either a conventional interpretation or a new interpretation of

  3. Piezoelectricity in Two-Dimensional Materials

    KAUST Repository

    Wu, Tao

    2015-02-25

    Powering up 2D materials: Recent experimental studies confirmed the existence of piezoelectricity - the conversion of mechanical stress into electricity - in two-dimensional single-layer MoS2 nanosheets. The results represent a milestone towards embedding low-dimensional materials into future disruptive technologies. © 2015 Wiley-VCH Verlag GmbH & Co. KGaA.

  4. Kronecker Product of Two-dimensional Arrays

    Institute of Scientific and Technical Information of China (English)

    Lei Hu

    2006-01-01

    Kronecker sequences constructed from short sequences are good sequences for spread spectrum communication systems. In this paper we study a similar problem for two-dimensional arrays, and we determine the linear complexity of the Kronecker product of two arrays. Our result shows that similar good property on linear complexity holds for Kronecker product of arrays.

  5. Two-Dimensional Toda-Heisenberg Lattice

    Directory of Open Access Journals (Sweden)

    Vadim E. Vekslerchik

    2013-06-01

    Full Text Available We consider a nonlinear model that is a combination of the anisotropic two-dimensional classical Heisenberg and Toda-like lattices. In the framework of the Hirota direct approach, we present the field equations of this model as a bilinear system, which is closely related to the Ablowitz-Ladik hierarchy, and derive its N-soliton solutions.

  6. A novel two dimensional particle velocity sensor

    NARCIS (Netherlands)

    Pjetri, Olti; Wiegerink, Remco J.; Lammerink, Theo S.; Krijnen, Gijs J.

    2013-01-01

    In this paper we present a two wire, two-dimensional particle velocity sensor. The miniature sensor of size 1.0x2.5x0.525 mm, consisting of only two crossed wires, shows excellent directional sensitivity in both directions, thus requiring no directivity calibration, and is relatively easy to fabrica

  7. Two-dimensional microstrip detector for neutrons

    Energy Technology Data Exchange (ETDEWEB)

    Oed, A. [Institut Max von Laue - Paul Langevin (ILL), 38 - Grenoble (France)

    1997-04-01

    Because of their robust design, gas microstrip detectors, which were developed at ILL, can be assembled relatively quickly, provided the prefabricated components are available. At the beginning of 1996, orders were received for the construction of three two-dimensional neutron detectors. These detectors have been completed. The detectors are outlined below. (author). 2 refs.

  8. Two-dimensional magma-repository interactions

    NARCIS (Netherlands)

    Bokhove, O.

    2001-01-01

    Two-dimensional simulations of magma-repository interactions reveal that the three phases --a shock tube, shock reflection and amplification, and shock attenuation and decay phase-- in a one-dimensional flow tube model have a precursor. This newly identified phase ``zero'' consists of the impact of

  9. Two-dimensional subwavelength plasmonic lattice solitons

    CERN Document Server

    Ye, F; Hu, B; Panoiu, N C

    2010-01-01

    We present a theoretical study of plasmonic lattice solitons (PLSs) formed in two-dimensional (2D) arrays of metallic nanowires embedded into a nonlinear medium with Kerr nonlinearity. We analyze two classes of 2D PLSs families, namely, fundamental and vortical PLSs in both focusing and defocusing media. Their existence, stability, and subwavelength spatial confinement are studied in detai

  10. A two-dimensional Dirac fermion microscope

    DEFF Research Database (Denmark)

    Bøggild, Peter; Caridad, Jose; Stampfer, Christoph

    2017-01-01

    in the solid state. Here we provide a perspective view on how a two-dimensional (2D) Dirac fermion-based microscope can be realistically implemented and operated, using graphene as a vacuum chamber for ballistic electrons. We use semiclassical simulations to propose concrete architectures and design rules of 2...

  11. The software peculiarities of pattern recognition in track detectors

    Energy Technology Data Exchange (ETDEWEB)

    Starkov, N. [P. N. Lebedev Physical Institute of the Russian Academy of Sciences, Leninskii prosp. 53, 119991 Moscow (Russian Federation)

    2015-12-31

    The different kinds of nuclear track recognition algorithms are represented. Several complicated samples of use them in physical experiments are considered. The some processing methods of complicated images are described.

  12. The Role of Binocular Disparity in Rapid Scene and Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Matteo Valsecchi

    2013-04-01

    Full Text Available We investigated the contribution of binocular disparity to the rapid recognition of scenes and simpler spatial patterns using a paradigm combining backward masked stimulus presentation and short-term match-to-sample recognition. First, we showed that binocular disparity did not contribute significantly to the recognition of briefly presented natural and artificial scenes, even when the availability of monocular cues was reduced. Subsequently, using dense random dot stereograms as stimuli, we showed that observers were in principle able to extract spatial patterns defined only by disparity under brief, masked presentations. Comparing our results with the predictions from a cue-summation model, we showed that combining disparity with luminance did not per se disrupt the processing of disparity. Our results suggest that the rapid recognition of scenes is mediated mostly by a monocular comparison of the images, although we can rely on stereo in fast pattern recognition.

  13. Blueprints of signaling interactions between pattern recognition receptors: implications for the design of vaccine adjuvants

    NARCIS (Netherlands)

    Timmermans, K.; Plantinga, T.S.; Kox, M.; Vaneker, M.; Scheffer, G.J.; Adema, G.J.; Joosten, L.A.B.; Netea, M.G.

    2013-01-01

    Innate immunity activation largely depends on recognition of microorganism structures by Pattern Recognition Receptors (PRRs). PRR downstream signaling results in production of pro- and anti-inflammatory cytokines and other mediators. Moreover, PRR engagement in antigen-presenting cells initiates th

  14. Genetic Variation in Pattern Recognition Receptors and Adaptor Proteins Associated With Development of Chronic Q Fever

    NARCIS (Netherlands)

    Schoffelen, T.; Ammerdorffer, A.; Hagenaars, J.C.; Bleeker-Rovers, C.P.; Wegdam-Blans, M.C.; Wever, P.C.; Joosten, L.A.B.; Meer, J.W.M. van der; Sprong, T.; Netea, M.G.; Deuren, M. van; Vosse, E. van de

    2015-01-01

    BACKGROUND: Q fever is an infection caused by Coxiella burnetii. Persistent infection (chronic Q fever) develops in 1%-5% of patients. We hypothesize that inefficient recognition of C. burnetii and/or activation of host-defense in individuals carrying genetic variants in pattern recognition

  15. Exploring how user routine affects the recognition performance of a lock pattern

    NARCIS (Netherlands)

    Wide, de Lisa; Spreeuwers, Luuk; Veldhuis, Raymond

    2015-01-01

    To protect an Android smartphone against attackers, a lock pattern can be used. Nevertheless, shoulder-surfing and smudge attacks can be used to get access despite of this protection. To combat these attacks, biometric recognition can be added to the lock pattern, such that the lock-pattern applicat

  16. Stress Wave Propagation in Two-dimensional Buckyball Lattice

    Science.gov (United States)

    Xu, Jun; Zheng, Bowen

    2016-11-01

    Orderly arrayed granular crystals exhibit extraordinary capability to tune stress wave propagation. Granular system of higher dimension renders many more stress wave patterns, showing its great potential for physical and engineering applications. At nanoscale, one-dimensionally arranged buckyball (C60) system has shown the ability to support solitary wave. In this paper, stress wave behaviors of two-dimensional buckyball (C60) lattice are investigated based on square close packing and hexagonal close packing. We show that the square close packed system supports highly directional Nesterenko solitary waves along initially excited chains and hexagonal close packed system tends to distribute the impulse and dissipates impact exponentially. Results of numerical calculations based on a two-dimensional nonlinear spring model are in a good agreement with the results of molecular dynamics simulations. This work enhances the understanding of wave properties and allows manipulations of nanoscale lattice and novel design of shock mitigation and nanoscale energy harvesting devices.

  17. Transport behavior of water molecules through two-dimensional nanopores

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, Chongqin; Li, Hui; Meng, Sheng, E-mail: smeng@iphy.ac.cn [Beijing National Laboratory for Condensed Matter Physics and Institute of Physics, Chinese Academy of Sciences, Beijing 100190 (China)

    2014-11-14

    Water transport through a two-dimensional nanoporous membrane has attracted increasing attention in recent years thanks to great demands in water purification and desalination applications. However, few studies have been reported on the microscopic mechanisms of water transport through structured nanopores, especially at the atomistic scale. Here we investigate the microstructure of water flow through two-dimensional model graphene membrane containing a variety of nanopores of different size by using molecular dynamics simulations. Our results clearly indicate that the continuum flow transits to discrete molecular flow patterns with decreasing pore sizes. While for pores with a diameter ≥15 Å water flux exhibits a linear dependence on the pore area, a nonlinear relationship between water flux and pore area has been identified for smaller pores. We attribute this deviation from linear behavior to the presence of discrete water flow, which is strongly influenced by the water-membrane interaction and hydrogen bonding between water molecules.

  18. Transport behavior of water molecules through two-dimensional nanopores

    Science.gov (United States)

    Zhu, Chongqin; Li, Hui; Meng, Sheng

    2014-11-01

    Water transport through a two-dimensional nanoporous membrane has attracted increasing attention in recent years thanks to great demands in water purification and desalination applications. However, few studies have been reported on the microscopic mechanisms of water transport through structured nanopores, especially at the atomistic scale. Here we investigate the microstructure of water flow through two-dimensional model graphene membrane containing a variety of nanopores of different size by using molecular dynamics simulations. Our results clearly indicate that the continuum flow transits to discrete molecular flow patterns with decreasing pore sizes. While for pores with a diameter ≥15 Å water flux exhibits a linear dependence on the pore area, a nonlinear relationship between water flux and pore area has been identified for smaller pores. We attribute this deviation from linear behavior to the presence of discrete water flow, which is strongly influenced by the water-membrane interaction and hydrogen bonding between water molecules.

  19. Proceedings of the NASA Symposium on Mathematical Pattern Recognition and Image Analysis

    Science.gov (United States)

    Guseman, L. F., Jr.

    1983-01-01

    The application of mathematical and statistical analyses techniques to imagery obtained by remote sensors is described by Principal Investigators. Scene-to-map registration, geometric rectification, and image matching are among the pattern recognition aspects discussed.

  20. Compressive phase-only filtering - pattern recognition at extreme compression rates

    CERN Document Server

    Pastor-Calle, David; Mikolajczyk, Michal; Kotynski, Rafal

    2016-01-01

    We introduce a compressive pattern recognition method for non-adaptive Walsh-Hadamard or discrete noiselet-based compressive measurements and show that images measured at extremely high compression rates may still contain sufficient information for pattern recognition and target localization. We report on a compressive pattern recognition experiment with a single-pixel detector with which we validate the proposed method. The correlation signals produced with the phase-only matched filter or with the pure-phase correlation are obtained from the compressive measurements through lasso optimization without the need to reconstruct the original image. This is possible owing to the two properties of phase-only filtering: such filtering is a unitary circulant transform, and the correlation plane it produces in pattern recognition applications is usually sparse.

  1. Developing Autonomic Properties for Distributed Pattern-Recognition Systems with ASSL: A Distributed MARF Case Study

    CERN Document Server

    Vassev, Emil

    2011-01-01

    In this paper, we discuss our research towards developing special properties that introduce autonomic behavior in pattern-recognition systems. In our approach we use ASSL (Autonomic System Specification Language) to formally develop such properties for DMARF (Distributed Modular Audio Recognition Framework). These properties enhance DMARF with an autonomic middleware that manages the four stages of the framework's pattern-recognition pipeline. DMARF is a biologically inspired system employing pattern recognition, signal processing, and natural language processing helping us process audio, textual, or imagery data needed by a variety of scientific applications, e.g., biometric applications. In that context, the notion go autonomic DMARF (ADMARF) can be employed by autonomous and robotic systems that theoretically require less-to-none human intervention other than data collection for pattern analysis and observing the results. In this article, we explain the ASSL specification models for the autonomic propertie...

  2. Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition

    CERN Document Server

    Melin, Patricia

    2012-01-01

    This book describes hybrid intelligent systems using type-2 fuzzy logic and modular neural networks for pattern recognition applications. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful pattern recognition systems. Type-2 fuzzy logic is an extension of traditional type-1 fuzzy logic that enables managing higher levels of uncertainty in complex real world problems, which are of particular importance in the area of pattern recognition. The book is organized in three main parts, each containing a group of chapters built around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which are the basis for achieving intelligent pattern recognition. The second part contains chapters with the main theme of using type-2 fuzzy models and modular neural ne...

  3. Analysis of chemical signals in red fire ants by gas chromatography and pattern recognition techniques

    Science.gov (United States)

    The combination of gas chromatography and pattern recognition (GC/PR) analysis is a powerful tool for investigating complicated biological problems. Clustering, mapping, discriminant development, etc. are necessary to analyze realistically large chromatographic data sets and to seek meaningful relat...

  4. Rotation, scale and translation invariant pattern recognition system for color images

    Science.gov (United States)

    Barajas-García, Carolina; Solorza-Calderón, Selene; Álvarez-Borrego, Josué

    2016-12-01

    This work presents a color image pattern recognition system invariant to rotation, scale and translation. The system works with three 1D signatures, one for each RGB color channel. The signatures are constructed based on Fourier transform, analytic Fourier-Mellin transform and Hilbert binary rings mask. According with the statistical theory of box-plots, the pattern recognition system has a confidence level at least of 95.4%.

  5. Proposal of Pattern Recognition as a necessary and sufficient Principle to Cognitive Science

    OpenAIRE

    de Paiva, Gilberto

    2011-01-01

    Despite the prevalence of the Computational Theory of Mind and the Connectionist Model, the establishing of the key principles of the Cognitive Science are still controversy and inconclusive. This paper proposes the concept of Pattern Recognition as Necessary and Sufficient Principle for a general cognitive science modeling, in a very ambitious scientific proposal. A formal physical definition of the pattern recognition concept is also proposed to solve many key conceptual gaps on the field.

  6. Comparison of protein patterns of xrs-5, a radiosensitive Chinese hamster ovary cell line, and CHO-K1, its radioresistant parent, using two-dimensional gel-electrophoresis

    Energy Technology Data Exchange (ETDEWEB)

    Kramer, J.M. (Miami Univ., Oxford, OH (USA). Dept. of Zoology)

    1991-01-01

    X-ray sensitive strains of Chinese hamster ovary cell lines have been used to analyze radiation repair mechanisms. One cell line, xrs-5, has been shown to be very sensitive to ionizing radiation and radical forming chemical mutagens. This sensitivity is thought to be a result a mutation in the DNA double strand break (DSB) repair mechanism, and its characterization has been a goal of several repair mechanism studies. Using two-dimensional gel electrophoresis, we have detected a protein (MW approximately 55KD) in the DNA/Nuclear Matrix (nucleoid) cell fraction of CHO-Kl cells that is absent in the nucleoid fraction of xrs-5. This protein is present, however, in both CHO-Kl and xrs-5 whole cell protein maps. To determine whether the 55KD protein is responsible for the radiosensitive and defective DSB repair phenotype of xrs-5 cells, studies are now underway to analyze revertants of xrs-5 that are proficient in DSB repair. Furthermore, an effort to sequence the protein in question is planned. 23 refs., 2 figs.

  7. Electronics based on two-dimensional materials.

    Science.gov (United States)

    Fiori, Gianluca; Bonaccorso, Francesco; Iannaccone, Giuseppe; Palacios, Tomás; Neumaier, Daniel; Seabaugh, Alan; Banerjee, Sanjay K; Colombo, Luigi

    2014-10-01

    The compelling demand for higher performance and lower power consumption in electronic systems is the main driving force of the electronics industry's quest for devices and/or architectures based on new materials. Here, we provide a review of electronic devices based on two-dimensional materials, outlining their potential as a technological option beyond scaled complementary metal-oxide-semiconductor switches. We focus on the performance limits and advantages of these materials and associated technologies, when exploited for both digital and analog applications, focusing on the main figures of merit needed to meet industry requirements. We also discuss the use of two-dimensional materials as an enabling factor for flexible electronics and provide our perspectives on future developments.

  8. Two-dimensional ranking of Wikipedia articles

    Science.gov (United States)

    Zhirov, A. O.; Zhirov, O. V.; Shepelyansky, D. L.

    2010-10-01

    The Library of Babel, described by Jorge Luis Borges, stores an enormous amount of information. The Library exists ab aeterno. Wikipedia, a free online encyclopaedia, becomes a modern analogue of such a Library. Information retrieval and ranking of Wikipedia articles become the challenge of modern society. While PageRank highlights very well known nodes with many ingoing links, CheiRank highlights very communicative nodes with many outgoing links. In this way the ranking becomes two-dimensional. Using CheiRank and PageRank we analyze the properties of two-dimensional ranking of all Wikipedia English articles and show that it gives their reliable classification with rich and nontrivial features. Detailed studies are done for countries, universities, personalities, physicists, chess players, Dow-Jones companies and other categories.

  9. Two-Dimensional NMR Lineshape Analysis

    Science.gov (United States)

    Waudby, Christopher A.; Ramos, Andres; Cabrita, Lisa D.; Christodoulou, John

    2016-04-01

    NMR titration experiments are a rich source of structural, mechanistic, thermodynamic and kinetic information on biomolecular interactions, which can be extracted through the quantitative analysis of resonance lineshapes. However, applications of such analyses are frequently limited by peak overlap inherent to complex biomolecular systems. Moreover, systematic errors may arise due to the analysis of two-dimensional data using theoretical frameworks developed for one-dimensional experiments. Here we introduce a more accurate and convenient method for the analysis of such data, based on the direct quantum mechanical simulation and fitting of entire two-dimensional experiments, which we implement in a new software tool, TITAN (TITration ANalysis). We expect the approach, which we demonstrate for a variety of protein-protein and protein-ligand interactions, to be particularly useful in providing information on multi-step or multi-component interactions.

  10. Towards two-dimensional search engines

    CERN Document Server

    Ermann, Leonardo; Shepelyansky, Dima L

    2011-01-01

    We study the statistical properties of various directed networks using ranking of their nodes based on the dominant vectors of the Google matrix known as PageRank and CheiRank. On average PageRank orders nodes proportionally to a number of ingoing links, while CheiRank orders nodes proportionally to a number of outgoing links. In this way the ranking of nodes becomes two-dimensional that paves the way for development of two-dimensional search engines of new type. Information flow properties on PageRank-CheiRank plane are analyzed for networks of British, French and Italian Universities, Wikipedia, Linux Kernel, gene regulation and other networks. Methods of spam links control are also analyzed.

  11. Toward two-dimensional search engines

    Science.gov (United States)

    Ermann, L.; Chepelianskii, A. D.; Shepelyansky, D. L.

    2012-07-01

    We study the statistical properties of various directed networks using ranking of their nodes based on the dominant vectors of the Google matrix known as PageRank and CheiRank. On average PageRank orders nodes proportionally to a number of ingoing links, while CheiRank orders nodes proportionally to a number of outgoing links. In this way, the ranking of nodes becomes two dimensional which paves the way for the development of two-dimensional search engines of a new type. Statistical properties of information flow on the PageRank-CheiRank plane are analyzed for networks of British, French and Italian universities, Wikipedia, Linux Kernel, gene regulation and other networks. A special emphasis is done for British universities networks using the large database publicly available in the UK. Methods of spam links control are also analyzed.

  12. A two-dimensional Dirac fermion microscope

    Science.gov (United States)

    Bøggild, Peter; Caridad, José M.; Stampfer, Christoph; Calogero, Gaetano; Papior, Nick Rübner; Brandbyge, Mads

    2017-06-01

    The electron microscope has been a powerful, highly versatile workhorse in the fields of material and surface science, micro and nanotechnology, biology and geology, for nearly 80 years. The advent of two-dimensional materials opens new possibilities for realizing an analogy to electron microscopy in the solid state. Here we provide a perspective view on how a two-dimensional (2D) Dirac fermion-based microscope can be realistically implemented and operated, using graphene as a vacuum chamber for ballistic electrons. We use semiclassical simulations to propose concrete architectures and design rules of 2D electron guns, deflectors, tunable lenses and various detectors. The simulations show how simple objects can be imaged with well-controlled and collimated in-plane beams consisting of relativistic charge carriers. Finally, we discuss the potential of such microscopes for investigating edges, terminations and defects, as well as interfaces, including external nanoscale structures such as adsorbed molecules, nanoparticles or quantum dots.

  13. A two-dimensional Dirac fermion microscope.

    Science.gov (United States)

    Bøggild, Peter; Caridad, José M; Stampfer, Christoph; Calogero, Gaetano; Papior, Nick Rübner; Brandbyge, Mads

    2017-06-09

    The electron microscope has been a powerful, highly versatile workhorse in the fields of material and surface science, micro and nanotechnology, biology and geology, for nearly 80 years. The advent of two-dimensional materials opens new possibilities for realizing an analogy to electron microscopy in the solid state. Here we provide a perspective view on how a two-dimensional (2D) Dirac fermion-based microscope can be realistically implemented and operated, using graphene as a vacuum chamber for ballistic electrons. We use semiclassical simulations to propose concrete architectures and design rules of 2D electron guns, deflectors, tunable lenses and various detectors. The simulations show how simple objects can be imaged with well-controlled and collimated in-plane beams consisting of relativistic charge carriers. Finally, we discuss the potential of such microscopes for investigating edges, terminations and defects, as well as interfaces, including external nanoscale structures such as adsorbed molecules, nanoparticles or quantum dots.

  14. Two-Dimensional Scheduling: A Review

    Directory of Open Access Journals (Sweden)

    Zhuolei Xiao

    2013-07-01

    Full Text Available In this study, we present a literature review, classification schemes and analysis of methodology for scheduling problems on Batch Processing machine (BP with both processing time and job size constraints which is also regarded as Two-Dimensional (TD scheduling. Special attention is given to scheduling problems with non-identical job sizes and processing times, with details of the basic algorithms and other significant results.

  15. Two dimensional fermions in four dimensional YM

    CERN Document Server

    Narayanan, R

    2009-01-01

    Dirac fermions in the fundamental representation of SU(N) live on a two dimensional torus flatly embedded in $R^4$. They interact with a four dimensional SU(N) Yang Mills vector potential preserving a global chiral symmetry at finite $N$. As the size of the torus in units of $\\frac{1}{\\Lambda_{SU(N)}}$ is varied from small to large, the chiral symmetry gets spontaneously broken in the infinite $N$ limit.

  16. Two-dimensional Kagome photonic bandgap waveguide

    DEFF Research Database (Denmark)

    Nielsen, Jens Bo; Søndergaard, Thomas; Libori, Stig E. Barkou;

    2000-01-01

    The transverse-magnetic photonic-bandgap-guidance properties are investigated for a planar two-dimensional (2-D) Kagome waveguide configuration using a full-vectorial plane-wave-expansion method. Single-moded well-localized low-index guided modes are found. The localization of the optical modes...... is investigated with respect to the width of the 2-D Kagome waveguide, and the number of modes existing for specific frequencies and waveguide widths is mapped out....

  17. String breaking in two-dimensional QCD

    CERN Document Server

    Hornbostel, K J

    1999-01-01

    I present results of a numerical calculation of the effects of light quark-antiquark pairs on the linear heavy-quark potential in light-cone quantized two-dimensional QCD. I extract the potential from the Q-Qbar component of the ground-state wavefunction, and observe string breaking at the heavy-light meson pair threshold. I briefly comment on the states responsible for the breaking.

  18. Two-dimensional supramolecular electron spin arrays.

    Science.gov (United States)

    Wäckerlin, Christian; Nowakowski, Jan; Liu, Shi-Xia; Jaggi, Michael; Siewert, Dorota; Girovsky, Jan; Shchyrba, Aneliia; Hählen, Tatjana; Kleibert, Armin; Oppeneer, Peter M; Nolting, Frithjof; Decurtins, Silvio; Jung, Thomas A; Ballav, Nirmalya

    2013-05-07

    A bottom-up approach is introduced to fabricate two-dimensional self-assembled layers of molecular spin-systems containing Mn and Fe ions arranged in a chessboard lattice. We demonstrate that the Mn and Fe spin states can be reversibly operated by their selective response to coordination/decoordination of volatile ligands like ammonia (NH3). Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Two dimensional echocardiographic detection of intraatrial masses.

    Science.gov (United States)

    DePace, N L; Soulen, R L; Kotler, M N; Mintz, G S

    1981-11-01

    With two dimensional echocardiography, a left atrial mass was detected in 19 patients. Of these, 10 patients with rheumatic mitral stenosis had a left atrial thrombus. The distinctive two dimensional echocardiographic features of left atrial thrombus included a mass of irregular nonmobile laminated echos within an enlarged atrial cavity, usually with a broad base of attachment to the posterior left atrial wall. Seven patients had a left atrial myxoma. Usually, the myxoma appeared as a mottled ovoid, sharply demarcated mobile mass attached to the interatrial septum. One patient had a right atrial angiosarcoma that appeared as a nonmobile mass extending from the inferior vena caval-right atrial junction into the right atrial cavity. One patient had a left atrial leiomyosarcoma producing a highly mobile mass attached to the lateral wall of the left atrium. M mode echocardiography detected six of the seven myxomas, one thrombus and neither of the other tumors. Thus, two dimensional echocardiography appears to be the technique of choice in the detection, localization and differentiation of intraatrial masses.

  20. Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature

    Directory of Open Access Journals (Sweden)

    Shouyi Yin

    2015-01-01

    Full Text Available Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed.

  1. Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System

    Science.gov (United States)

    Partila, Pavol; Voznak, Miroslav; Tovarek, Jaromir

    2015-01-01

    The impact of the classification method and features selection for the speech emotion recognition accuracy is discussed in this paper. Selecting the correct parameters in combination with the classifier is an important part of reducing the complexity of system computing. This step is necessary especially for systems that will be deployed in real-time applications. The reason for the development and improvement of speech emotion recognition systems is wide usability in nowadays automatic voice controlled systems. Berlin database of emotional recordings was used in this experiment. Classification accuracy of artificial neural networks, k-nearest neighbours, and Gaussian mixture model is measured considering the selection of prosodic, spectral, and voice quality features. The purpose was to find an optimal combination of methods and group of features for stress detection in human speech. The research contribution lies in the design of the speech emotion recognition system due to its accuracy and efficiency. PMID:26346654

  2. PTX3, a humoral pattern recognition molecule at the interface between microbe and matrix recognition.

    Science.gov (United States)

    Garlanda, Cecilia; Jaillon, Sebastien; Doni, Andrea; Bottazzi, Barbara; Mantovani, Alberto

    2016-02-01

    Innate immunity consists of a cellular and a humoral arm. PTX3 is a fluid patter recognition molecule (PRM) with antibody-like properties. Gene targeted mice and genetic associations in humans suggest that PTX3 plays a non-redundant role in resistance against selected pathogens (e.g. Aspergillus fumigatus, Pseudomonas aeruginosa, uropathogenic Escherichia coli) and in the regulation of inflammation. PTX3 acts as an extrinsic oncosuppressor by taming complement elicited tumor-promoting inflammation. Recent results indicate that, by interacting with provisional matrix components, PTX3 contributes to the orchestration of tissue repair. An acidic pH sets PTX3 in a tissue repair mode, while retaining anti-microbial recognition. Based on these data and scattered information on humoral PRM and matrix components, we surmise that matrix and microbial recognition are related functions in evolution. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System

    Directory of Open Access Journals (Sweden)

    Pavol Partila

    2015-01-01

    Full Text Available The impact of the classification method and features selection for the speech emotion recognition accuracy is discussed in this paper. Selecting the correct parameters in combination with the classifier is an important part of reducing the complexity of system computing. This step is necessary especially for systems that will be deployed in real-time applications. The reason for the development and improvement of speech emotion recognition systems is wide usability in nowadays automatic voice controlled systems. Berlin database of emotional recordings was used in this experiment. Classification accuracy of artificial neural networks, k-nearest neighbours, and Gaussian mixture model is measured considering the selection of prosodic, spectral, and voice quality features. The purpose was to find an optimal combination of methods and group of features for stress detection in human speech. The research contribution lies in the design of the speech emotion recognition system due to its accuracy and efficiency.

  4. Parsing algorithm for line-drawing pattern recognition

    Science.gov (United States)

    Wang, Patrick S. P.; Zhang, Y. Y.

    1991-02-01

    The concept of " universal array grammar" for off-line line drawing patterns is proposed and an algurithm for transforming two-dirrensional line drawing patterns to parsing sequences based on the " universal array grammar" is constructed.

  5. Pattern recognition in paediatric ecgs: the hidden secrets to clinical ...

    African Journals Online (AJOL)

    typical ECG patterns commonly found in routine paediatric cardiac examination, ECG .... an anterolateral myocardial infarct pattern. Deep Q waves .... The light, which can penetrate tissue and bone, stimulates cell mitochondria to kick-start a ...

  6. Numerical Analysis of Three-Dimensional Object Recognition with Digital Holography

    Institute of Scientific and Technical Information of China (English)

    DING De-Hua; HE Qing-Sheng; WANG Jian-Gang; WU Min-Xian; JIN Guo-Fan

    2004-01-01

    @@ We describe an intrinsic correlation peak of three-dimensional (3D) pattern recognition, which is higher than that of the two-dimensional (2D) pattern recognition and whose difference can reach up to five orders of magnitude in our numerical simulation. The relationship between the 3D objects and their recognition result is formalized and the comparison between the 3D and 2D pattern recognitions as well as the former's independency of the reconstruction distance is presented. Finally, the augmentation of the 3D pattern recognition sensitivity with the increasing surface complexity of the 3D object is also demonstrated.

  7. On-Line Recognition Of Cursive Korean Characters By Descriptions Of Basic Character Patterns And Their Connected Patterns

    Science.gov (United States)

    Lee, Heedong; Nakajima, Masayuki; Agui, Takeshi

    1988-10-01

    The present paper reports an on-line recognition method of cursive Korean characters. In the present method, we treat a Korean character pattern as a finite sequence of basic character patterns. After extracting candidate basic character patterns from an input character pattern, we determine basic character patterns making a Korean character from the candidates by connecting processing. We described basic character patterns and their connected patterns used in the present method according to their features. By extracting and connecting basic character patterns based on the descriptions, we improve description ability of patterns and processing speed. Precise description ability of patterns and extracting candidates can remove unstable writing movements and can separate strokes stably.

  8. The Innovation of O2O Marketing Platform Pattern Based on the Two Dimensional Code%基于二维码的 O2O 营销平台模式创新研究

    Institute of Scientific and Technical Information of China (English)

    徐真

    2015-01-01

    随着移动通信和互联网的快速发展,O2O 营销平台模式应运而生。其后,对 O2O 平台商业模式的探索从未停歇。自2012年二维码于各行各业的广泛应用以来,其作为移动互联网的线下入口,将在诸多方面引领O2O 营销平台模式的创新,具体包括引流阶段的创新、转化阶段的创新、消费阶段的创新、反馈阶段的创新和留存阶段的创新等。并对二级码在我国的未来发展进行了展望。%With the rapid development of mobile communications and the Internet,O2O marketing platform has e-merged and the exploration of the O2O platform business model has been ever growing.In 2012,the emergence of a small black and white box opened a new way for the innovation of O2O marketing platform,which included the drainage stage innovation,the transformation stage innovation,the consumption stage innovation,the feedback phase innovation and the innovation of the retention period.This paper will discuss how the small two-dimensional code promoting the innovation of O2O marketing platform model.

  9. A Training Strategy for Learning Pattern Recognition Control for Myoelectric Prostheses.

    Science.gov (United States)

    Powell, Michael A; Thakor, Nitish V

    2013-01-01

    Pattern recognition-based control of myoelectric prostheses offers amputees a natural, intuitive way of controlling the increasing functionality of modern myoelectric prostheses. While this approach to prosthesis control is certainly attractive, it is a significant departure from existing control methods. The transition from the more traditional methods of direct or proportional control to pattern recognition-based control presents a training challenge that will be unique to each amputee. In this paper we describe specific ways that a transradial amputee, prosthetist, and occupational therapist team can overcome these challenges by developing consistent and distinguishable muscle patterns. A central part of this process is the employment of a computer-based pattern recognition training system with which an amputee can learn and improve pattern recognition skills throughout the process of prosthesis fitting and testing. We describe in detail the manner in which four transradial amputees trained to improve their pattern recognition-based control of a virtual prosthesis by focusing on building consistent, distinguishable muscle patterns. We also describe a three-phase framework for instruction and training: 1) initial demonstration and conceptual instruction, 2) in-clinic testing and initial training, and 3) at-home training.

  10. Electromagnetically induced two-dimensional grating assisted by incoherent pump

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Yu-Yuan; Liu, Zhuan-Zhuan; Wan, Ren-Gang, E-mail: wrg@snnu.edu.cn

    2017-04-25

    We propose a scheme for realizing electromagnetically induced two-dimensional grating in a double-Λ system driven simultaneously by a coherent field and an incoherent pump field. In such an atomic configuration, the absorption is suppressed owing to the incoherent pumping process and the probe can be even amplified, while the refractivity is mainly attributed to the dynamically induced coherence. With the help of a standing-wave pattern coherent field, we obtain periodically modulated refractive index without or with gain, and therefore phase grating or gain-phase grating which diffracts a probe light into high-order direction efficiently can be formed in the medium via appropriate manipulation of the system parameters. The diffraction efficiency attainable by the present gratings can be controlled by tuning the coherent field intensity or the interaction length. Hence, the two-dimensional grating can be utilized as all-optical splitter or router in optical networking and communication. - Highlights: • Two-dimensional grating is coherently induced in four-level atoms. • Phase and gain-phase gratings are obtained assisted by incoherent pump. • The diffraction power is improved due to the enhanced refraction modulation. • The gratings can be utilized as multi-channel all-optical splitter and router.

  11. The role of transparency in perceptual grouping and pattern recognition.

    Science.gov (United States)

    Watanabe, T; Cavanagh, P

    1992-01-01

    The shortest stimulus exposure time for which transparency can be seen was examined. In the first experiment, overlapping digits were presented for 120 ms and the luminance in the overlapping regions was varied. Subjects reported, in separate blocks of trials, either the apparent transparency of the digits or the identity of the digits. When the luminance was set so that one set of digits appeared to be seen through the other, recognition of the digits was high. When the luminance in the overlapping regions did not produce impressions of transparency, digit recognition was low. In the second experiment, digit identification at several stimulus durations was compared between stimuli that had luminance that was valid for transparency and stimuli that had invalid luminance. Performance was found to be higher in the valid luminance condition than in the invalid condition after as little as 60 ms exposure duration. This result suggests that the impression of transparency requires only relatively short exposure durations.

  12. Dentate gyrus supports slope recognition memory, shades of grey-context pattern separation and recognition memory, and CA3 supports pattern completion for object memory.

    Science.gov (United States)

    Kesner, Raymond P; Kirk, Ryan A; Yu, Zhenghui; Polansky, Caitlin; Musso, Nick D

    2016-03-01

    In order to examine the role of the dorsal dentate gyrus (dDG) in slope (vertical space) recognition and possible pattern separation, various slope (vertical space) degrees were used in a novel exploratory paradigm to measure novelty detection for changes in slope (vertical space) recognition memory and slope memory pattern separation in Experiment 1. The results of the experiment indicate that control rats displayed a slope recognition memory function with a pattern separation process for slope memory that is dependent upon the magnitude of change in slope between study and test phases. In contrast, the dDG lesioned rats displayed an impairment in slope recognition memory, though because there was no significant interaction between the two groups and slope memory, a reliable pattern separation impairment for slope could not be firmly established in the DG lesioned rats. In Experiment 2, in order to determine whether, the dDG plays a role in shades of grey spatial context recognition and possible pattern separation, shades of grey were used in a novel exploratory paradigm to measure novelty detection for changes in the shades of grey context environment. The results of the experiment indicate that control rats displayed a shades of grey-context pattern separation effect across levels of separation of context (shades of grey). In contrast, the DG lesioned rats displayed a significant interaction between the two groups and levels of shades of grey suggesting impairment in a pattern separation function for levels of shades of grey. In Experiment 3 in order to determine whether the dorsal CA3 (dCA3) plays a role in object pattern completion, a new task requiring less training and using a choice that was based on choosing the correct set of objects on a two-choice discrimination task was used. The results indicated that control rats displayed a pattern completion function based on the availability of one, two, three or four cues. In contrast, the dCA3 lesioned rats

  13. Tissue pattern recognition error rates and tumor heterogeneity in gastric cancer.

    Science.gov (United States)

    Potts, Steven J; Huff, Sarah E; Lange, Holger; Zakharov, Vladislav; Eberhard, David A; Krueger, Joseph S; Hicks, David G; Young, George David; Johnson, Trevor; Whitney-Miller, Christa L

    2013-01-01

    The anatomic pathology discipline is slowly moving toward a digital workflow, where pathologists will evaluate whole-slide images on a computer monitor rather than glass slides through a microscope. One of the driving factors in this workflow is computer-assisted scoring, which depends on appropriate selection of regions of interest. With advances in tissue pattern recognition techniques, a more precise region of the tissue can be evaluated, no longer bound by the pathologist's patience in manually outlining target tissue areas. Pathologists use entire tissues from which to determine a score in a region of interest when making manual immunohistochemistry assessments. Tissue pattern recognition theoretically offers this same advantage; however, error rates exist in any tissue pattern recognition program, and these error rates contribute to errors in the overall score. To provide a real-world example of tissue pattern recognition, 11 HER2-stained upper gastrointestinal malignancies with high heterogeneity were evaluated. HER2 scoring of gastric cancer was chosen due to its increasing importance in gastrointestinal disease. A method is introduced for quantifying the error rates of tissue pattern recognition. The trade-off between fully sampling tumor with a given tissue pattern recognition error rate versus randomly sampling a limited number of fields of view with higher target accuracy was modeled with a Monte-Carlo simulation. Under most scenarios, stereological methods of sampling-limited fields of view outperformed whole-slide tissue pattern recognition approaches for accurate immunohistochemistry analysis. The importance of educating pathologists in the use of statistical sampling is discussed, along with the emerging role of hybrid whole-tissue imaging and stereological approaches.

  14. Investigation of Time Series Representations and Similarity Measures for Structural Damage Pattern Recognition

    Science.gov (United States)

    Swartz, R. Andrew

    2013-01-01

    This paper investigates the time series representation methods and similarity measures for sensor data feature extraction and structural damage pattern recognition. Both model-based time series representation and dimensionality reduction methods are studied to compare the effectiveness of feature extraction for damage pattern recognition. The evaluation of feature extraction methods is performed by examining the separation of feature vectors among different damage patterns and the pattern recognition success rate. In addition, the impact of similarity measures on the pattern recognition success rate and the metrics for damage localization are also investigated. The test data used in this study are from the System Identification to Monitor Civil Engineering Structures (SIMCES) Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios. A number of progressive damage test case datasets and damage test data with different damage modalities are used. The simulation results show that both time series representation methods and similarity measures have significant impact on the pattern recognition success rate. PMID:24191136

  15. Investigation of time series representations and similarity measures for structural damage pattern recognition.

    Science.gov (United States)

    Liu, Wenjia; Chen, Bo; Swartz, R Andrew

    2013-01-01

    This paper investigates the time series representation methods and similarity measures for sensor data feature extraction and structural damage pattern recognition. Both model-based time series representation and dimensionality reduction methods are studied to compare the effectiveness of feature extraction for damage pattern recognition. The evaluation of feature extraction methods is performed by examining the separation of feature vectors among different damage patterns and the pattern recognition success rate. In addition, the impact of similarity measures on the pattern recognition success rate and the metrics for damage localization are also investigated. The test data used in this study are from the System Identification to Monitor Civil Engineering Structures (SIMCES) Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios. A number of progressive damage test case datasets and damage test data with different damage modalities are used. The simulation results show that both time series representation methods and similarity measures have significant impact on the pattern recognition success rate.

  16. Weakly disordered two-dimensional Frenkel excitons

    Science.gov (United States)

    Boukahil, A.; Zettili, Nouredine

    2004-03-01

    We report the results of studies of the optical properties of weakly disordered two- dimensional Frenkel excitons in the Coherent Potential Approximation (CPA). An approximate complex Green's function for a square lattice with nearest neighbor interactions is used in the self-consistent equation to determine the coherent potential. It is shown that the Density of States is very much affected by the logarithmic singularities in the Green's function. Our CPA results are in excellent agreement with previous investigations by Schreiber and Toyozawa using the Monte Carlo simulation.

  17. Two-dimensional photonic crystal surfactant detection.

    Science.gov (United States)

    Zhang, Jian-Tao; Smith, Natasha; Asher, Sanford A

    2012-08-07

    We developed a novel two-dimensional (2-D) crystalline colloidal array photonic crystal sensing material for the visual detection of amphiphilic molecules in water. A close-packed polystyrene 2-D array monolayer was embedded in a poly(N-isopropylacrylamide) (PNIPAAm)-based hydrogel film. These 2-D photonic crystals placed on a mirror show intense diffraction that enables them to be used for visual determination of analytes. Binding of surfactant molecules attaches ions to the sensor that swells the PNIPAAm-based hydrogel. The resulting increase in particle spacing red shifts the 2-D diffracted light. Incorporation of more hydrophobic monomers increases the sensitivity to surfactants.

  18. Theory of two-dimensional transformations

    OpenAIRE

    Kanayama, Yutaka J.; Krahn, Gary W.

    1998-01-01

    The article of record may be found at http://dx.doi.org/10.1109/70.720359 Robotics and Automation, IEEE Transactions on This paper proposes a new "heterogeneous" two-dimensional (2D) transformation group ___ to solve motion analysis/planning problems in robotics. In this theory, we use a 3×1 matrix to represent a transformation as opposed to a 3×3 matrix in the homogeneous formulation. First, this theory is as capable as the homogeneous theory, Because of the minimal size, its implement...

  19. Two-dimensional ranking of Wikipedia articles

    CERN Document Server

    Zhirov, A O; Shepelyansky, D L

    2010-01-01

    The Library of Babel, described by Jorge Luis Borges, stores an enormous amount of information. The Library exists {\\it ab aeterno}. Wikipedia, a free online encyclopaedia, becomes a modern analogue of such a Library. Information retrieval and ranking of Wikipedia articles become the challenge of modern society. We analyze the properties of two-dimensional ranking of all Wikipedia English articles and show that it gives their reliable classification with rich and nontrivial features. Detailed studies are done for countries, universities, personalities, physicists, chess players, Dow-Jones companies and other categories.

  20. Mobility anisotropy of two-dimensional semiconductors

    CERN Document Server

    Lang, Haifeng; Liu, Zhirong

    2016-01-01

    The carrier mobility of anisotropic two-dimensional (2D) semiconductors under longitudinal acoustic (LA) phonon scattering was theoretically studied with the deformation potential theory. Based on Boltzmann equation with relaxation time approximation, an analytic formula of intrinsic anisotropic mobility was deduced, which shows that the influence of effective mass to the mobility anisotropy is larger than that of deformation potential constant and elastic modulus. Parameters were collected for various anisotropic 2D materials (black phosphorus, Hittorf's phosphorus, BC$_2$N, MXene, TiS$_3$, GeCH$_3$) to calculate their mobility anisotropy. It was revealed that the anisotropic ratio was overestimated in the past.

  1. Sums of two-dimensional spectral triples

    DEFF Research Database (Denmark)

    Christensen, Erik; Ivan, Cristina

    2007-01-01

    construct a sum of two dimensional modules which reflects some aspects of the topological dimensions of the compact metric space, but this will only give the metric back approximately. At the end we make an explicit computation of the last module for the unit interval in. The metric is recovered exactly......, the Dixmier trace induces a multiple of the Lebesgue integral but the growth of the number of eigenvalues is different from the one found for the standard differential operator on the unit interval....

  2. Binding energy of two-dimensional biexcitons

    DEFF Research Database (Denmark)

    Singh, Jai; Birkedal, Dan; Vadim, Lyssenko;

    1996-01-01

    Using a model structure for a two-dimensional (2D) biexciton confined in a quantum well, it is shown that the form of the Hamiltonian of the 2D biexciton reduces into that of an exciton. The binding energies and Bohr radii of a 2D biexciton in its various internal energy states are derived...... analytically using the fractional dimension approach. The ratio of the binding energy of a 2D biexciton to that of a 2D exciton is found to be 0.228, which agrees very well with the recent experimental value. The results of our approach are compared with those of earlier theories....

  3. Dynamics of film. [two dimensional continua theory

    Science.gov (United States)

    Zak, M.

    1979-01-01

    The general theory of films as two-dimensional continua are elaborated upon. As physical realizations of such a model this paper examines: inextensible films, elastic films, and nets. The suggested dynamic equations have enabled us to find out the characteristic speeds of wave propagation of the invariants of external and internal geometry and formulate the criteria of instability of their shape. Also included herein is a detailed account of the equation describing the film motions beyond the limits of the shape stability accompanied by the formation of wrinkles. The theory is illustrated by examples.

  4. Genetic variation in pattern recognition receptors: functional consequences and susceptibility to infectious disease

    NARCIS (Netherlands)

    Jaeger, M.; Stappers, M.H.; Joosten, L.A.B.; Gyssens, I.C.J.; Netea, M.G.

    2015-01-01

    ABSTRACT Cells of the innate immune system are equipped with surface and cytoplasmic receptors for microorganisms called pattern recognition receptors (PRRs). PRRs recognize specific pathogen-associated molecular patterns and as such are crucial for the activation of the immune system. Currently, fi

  5. Pattern recognition in neural networks with competing dynamics: coexistence of fixed-point and cyclic attractors.

    Science.gov (United States)

    Herrera-Aguilar, José L; Larralde, Hernán; Aldana, Maximino

    2012-01-01

    We study the properties of the dynamical phase transition occurring in neural network models in which a competition between associative memory and sequential pattern recognition exists. This competition occurs through a weighted mixture of the symmetric and asymmetric parts of the synaptic matrix. Through a generating functional formalism, we determine the structure of the parameter space at non-zero temperature and near saturation (i.e., when the number of stored patterns scales with the size of the network), identifying the regions of high and weak pattern correlations, the spin-glass solutions, and the order-disorder transition between these regions. This analysis reveals that, when associative memory is dominant, smooth transitions appear between high correlated regions and spurious states. In contrast when sequential pattern recognition is stronger than associative memory, the transitions are always discontinuous. Additionally, when the symmetric and asymmetric parts of the synaptic matrix are defined in terms of the same set of patterns, there is a discontinuous transition between associative memory and sequential pattern recognition. In contrast, when the symmetric and asymmetric parts of the synaptic matrix are defined in terms of independent sets of patterns, the network is able to perform both associative memory and sequential pattern recognition for a wide range of parameter values.

  6. Pattern recognition in neural networks with competing dynamics: coexistence of fixed-point and cyclic attractors.

    Directory of Open Access Journals (Sweden)

    José L Herrera-Aguilar

    Full Text Available We study the properties of the dynamical phase transition occurring in neural network models in which a competition between associative memory and sequential pattern recognition exists. This competition occurs through a weighted mixture of the symmetric and asymmetric parts of the synaptic matrix. Through a generating functional formalism, we determine the structure of the parameter space at non-zero temperature and near saturation (i.e., when the number of stored patterns scales with the size of the network, identifying the regions of high and weak pattern correlations, the spin-glass solutions, and the order-disorder transition between these regions. This analysis reveals that, when associative memory is dominant, smooth transitions appear between high correlated regions and spurious states. In contrast when sequential pattern recognition is stronger than associative memory, the transitions are always discontinuous. Additionally, when the symmetric and asymmetric parts of the synaptic matrix are defined in terms of the same set of patterns, there is a discontinuous transition between associative memory and sequential pattern recognition. In contrast, when the symmetric and asymmetric parts of the synaptic matrix are defined in terms of independent sets of patterns, the network is able to perform both associative memory and sequential pattern recognition for a wide range of parameter values.

  7. Interfamily transfer of a plant pattern-recognition receptor confers broad-spectrum bacterial resistance

    NARCIS (Netherlands)

    Lacombe, S.; Rougon-Cardoso, A.; Sherwood, E.; Peeters, N.; Dahlbeck, D.; Esse, van H.P.; Smoker, M.; Rallapalli, G.; Thomma, B.P.H.J.; Staskawicz, B.; Jones, J.D.G.; Zipfel, C.

    2010-01-01

    Plant diseases cause massive losses in agriculture. Increasing the natural defenses of plants may reduce the impact of phytopathogens on agricultural productivity. Pattern-recognition receptors (PRRs) detect microbes by recognizing conserved pathogen-associated molecular patterns (PAMPs)1, 2, 3. Alt

  8. Role of Delay of Feedback on Subsequent Pattern Recognition Transfer Tasks.

    Science.gov (United States)

    Schroth, Marvin L.; Lund, Elissa

    1993-01-01

    Two experiments with 100 undergraduates investigated effects of delay of feedback on immediate and delayed transfer tasks involving different pattern recognition strategies. Delay of feedback resulted in greater retention of the concepts underlying construction of the different patterns in all transfer tasks. Results support the Kulhavy-Anderson…

  9. Inhibition of pattern recognition receptor-mediated inflammation by bioactive phytochemicals

    Science.gov (United States)

    Emerging evidence reveals that pattern-recognition receptors (PRRs), Toll-like receptors (TLRs) and Nucleotide-binding oligomerization domain proteins (NODs) mediate both infection-induced and sterile inflammation by recognizing pathogen-associated molecular patterns (PAMPs) and endogenous molecules...

  10. Local kinetic effects in two-dimensional plasma turbulence.

    Science.gov (United States)

    Servidio, S; Valentini, F; Califano, F; Veltri, P

    2012-01-27

    Using direct numerical simulations of a hybrid Vlasov-Maxwell model, kinetic processes are investigated in a two-dimensional turbulent plasma. In the turbulent regime, kinetic effects manifest through a deformation of the ion distribution function. These patterns of non-Maxwellian features are concentrated in space nearby regions of strong magnetic activity: the distribution function is modulated by the magnetic topology, and can elongate along or across the local magnetic field. These results open a new path on the study of kinetic processes such as heating, particle acceleration, and temperature anisotropy, commonly observed in astrophysical and laboratory plasmas.

  11. A robust HOG-based descriptor for pattern recognition

    Science.gov (United States)

    Diaz-Escobar, Julia; Kober, Vitaly

    2016-09-01

    The Histogram of Oriented Gradients (HOG) is a popular feature descriptor used in computer vision and image processing. The technique counts occurrences of gradient orientation in localized portions of an image. The descriptor is sensible to the presence in images of noise, nonuniform illumination, and low contrast. In this work, we propose a robust HOG-based descriptor using the local energy model and phase congruency approach. Computer simulation results are presented for recognition of objects in images affected by additive noise, nonuniform illumination, and geometric distortions using the proposed and conventional HOG descriptors.

  12. Two-dimensional gauge theoretic supergravities

    Science.gov (United States)

    Cangemi, D.; Leblanc, M.

    1994-05-01

    We investigate two-dimensional supergravity theories, which can be built from a topological and gauge invariant action defined on an ordinary surface. One is the N = 1 supersymmetric extension of the Jackiw-Teitelboim model presented by Chamseddine in a superspace formalism. We complement the proof of Montano, Aoaki and Sonnenschein that this extension is topological and gauge invariant, based on the graded de Sitter algebra. Not only do the equations of motion correspond to the supergravity ones and do gauge transformations encompass local supersymmetries, but we also identify the ∫-theory with the superfield formalism action written by Chamseddine. Next, we show that the N = 1 supersymmetric extension of string-inspired two-dimensional dilaton gravity put forward by Park and Strominger cannot be written as a ∫-theory. As an alternative, we propose two topological and gauge theories that are based on a graded extension of the extended Poincaré algebra and satisfy a vanishing-curvature condition. Both models are supersymmetric extensions of the string-inspired dilaton gravity.

  13. Two-Dimensional Theory of Scientific Representation

    Directory of Open Access Journals (Sweden)

    A Yaghmaie

    2013-03-01

    Full Text Available Scientific representation is an interesting topic for philosophers of science, many of whom have recently explored it from different points of view. There are currently two competing approaches to the issue: cognitive and non-cognitive, and each of them claims its own merits over the other. This article tries to provide a hybrid theory of scientific representation, called Two-Dimensional Theory of Scientific Representation, which has the merits of the two accounts and is free of their shortcomings. To do this, we will argue that although scientific representation needs to use the notion of intentionality, such a notion is defined and realized in a simply structural form contrary to what cognitive approach says about intentionality. After a short introduction, the second part of the paper is devoted to introducing theories of scientific representation briefly. In the third part, the structural accounts of representation will be criticized. The next step is to introduce the two-dimensional theory which involves two key components: fixing and structural fitness. It will be argued that fitness is an objective and non-intentional relation, while fixing is intentional.

  14. Two-dimensional shape memory graphene oxide

    Science.gov (United States)

    Chang, Zhenyue; Deng, Junkai; Chandrakumara, Ganaka G.; Yan, Wenyi; Liu, Jefferson Zhe

    2016-06-01

    Driven by the increasing demand for micro-/nano-technologies, stimuli-responsive shape memory materials at nanoscale have recently attracted great research interests. However, by reducing the size of conventional shape memory materials down to approximately nanometre range, the shape memory effect diminishes. Here, using density functional theory calculations, we report the discovery of a shape memory effect in a two-dimensional atomically thin graphene oxide crystal with ordered epoxy groups, namely C8O. A maximum recoverable strain of 14.5% is achieved as a result of reversible phase transition between two intrinsically stable phases. Our calculations conclude co-existence of the two stable phases in a coherent crystal lattice, giving rise to the possibility of constructing multiple temporary shapes in a single material, thus, enabling highly desirable programmability. With an atomic thickness, excellent shape memory mechanical properties and electric field stimulus, the discovery of a two-dimensional shape memory graphene oxide opens a path for the development of exceptional micro-/nano-electromechanical devices.

  15. A Novel Feature Extraction for Robust EMG Pattern Recognition

    CERN Document Server

    Phinyomark, Angkoon; Phukpattaranont, Pornchai

    2009-01-01

    Varieties of noises are major problem in recognition of Electromyography (EMG) signal. Hence, methods to remove noise become most significant in EMG signal analysis. White Gaussian noise (WGN) is used to represent interference in this paper. Generally, WGN is difficult to be removed using typical filtering and solutions to remove WGN are limited. In addition, noise removal is an important step before performing feature extraction, which is used in EMG-based recognition. This research is aimed to present a novel feature that tolerate with WGN. As a result, noise removal algorithm is not needed. Two novel mean and median frequencies (MMNF and MMDF) are presented for robust feature extraction. Sixteen existing features and two novelties are evaluated in a noisy environment. WGN with various signal-to-noise ratios (SNRs), i.e. 20-0 dB, was added to the original EMG signal. The results showed that MMNF performed very well especially in weak EMG signal compared with others. The error of MMNF in weak EMG signal with...

  16. Artificial neural network for bubbles pattern recognition on the images

    Science.gov (United States)

    Poletaev, I. E.; Pervunin, K. S.; Tokarev, M. P.

    2016-10-01

    Two-phase bubble flows have been used in many technological and energy processes as processing oil, chemical and nuclear reactors. This explains large interest to experimental and numerical studies of such flows last several decades. Exploiting of optical diagnostics for analysis of the bubble flows allows researchers obtaining of instantaneous velocity fields and gaseous phase distribution with the high spatial resolution non-intrusively. Behavior of light rays exhibits an intricate manner when they cross interphase boundaries of gaseous bubbles hence the identification of the bubbles images is a complicated problem. This work presents a method of bubbles images identification based on a modern technology of deep learning called convolutional neural networks (CNN). Neural networks are able to determine overlapping, blurred, and non-spherical bubble images. They can increase accuracy of the bubble image recognition, reduce the number of outliers, lower data processing time, and significantly decrease the number of settings for the identification in comparison with standard recognition methods developed before. In addition, usage of GPUs speeds up the learning process of CNN owning to the modern adaptive subgradient optimization techniques.

  17. Pattern recognition of abnormal left ventricle wall motion in cardiac MR.

    Science.gov (United States)

    Lu, Yingli; Radau, Perry; Connelly, Kim; Dick, Alexander; Wright, Graham

    2009-01-01

    There are four main problems that limit application of pattern recognition techniques for recognition of abnormal cardiac left ventricle (LV) wall motion: (1) Normalization of the LV's size, shape, intensity level and position; (2) defining a spatial correspondence between phases and subjects; (3) extracting features; (4) and discriminating abnormal from normal wall motion. Solving these four problems is required for application of pattern recognition techniques to classify the normal and abnormal LV wall motion. In this work, we introduce a normalization scheme to solve the first and second problems. With this scheme, LVs are normalized to the same position, size, and intensity level. Using the normalized images, we proposed an intra-segment classification criterion based on a correlation measure to solve the third and fourth problems. Application of the method to recognition of abnormal cardiac MR LV wall motion showed promising results.

  18. Finger Vein Recognition Using Local Line Binary Pattern

    Directory of Open Access Journals (Sweden)

    Bakhtiar Affendi Rosdi

    2011-11-01

    Full Text Available In this paper, a personal verification method using finger vein is presented. Finger vein can be considered more secured compared to other hands based biometric traits such as fingerprint and palm print because the features are inside the human body. In the proposed method, a new texture descriptor called local line binary pattern (LLBP is utilized as feature extraction technique. The neighbourhood shape in LLBP is a straight line, unlike in local binary pattern (LBP which is a square shape. Experimental results show that the proposed method using LLBP has better performance than the previous methods using LBP and local derivative pattern (LDP.

  19. Existence and Stability of Two-Dimensional Compact-Like Discrete Breathers in Discrete Two-Dimensional Monatomic Square Lattices

    Institute of Scientific and Technical Information of China (English)

    XU Quan; TIAN Qiang

    2007-01-01

    Two-dimensional compact-like discrete breathers in discrete two-dimensional monatomic square lattices are investigated by discussing a generafized discrete two-dimensional monatomic model.It is proven that the twodimensional compact-like discrete breathers exist not only in two-dimensional soft Ф4 potentials but also in hard two-dimensional Ф4 potentials and pure two-dimensional K4 lattices.The measurements of the two-dimensional compact-like discrete breather cores in soft and hard two-dimensional Ф4 potential are determined by coupling parameter K4,while those in pure two-dimensional K4 lattices have no coupling with parameter K4.The stabilities of the two-dimensional compact-like discrete breathers correlate closely to the coupling parameter K4 and the boundary condition of lattices.

  20. Clarifying the role of pattern separation in schizophrenia: the role of recognition and visual discrimination deficits.

    Science.gov (United States)

    Martinelli, Cristina; Shergill, Sukhwinder S

    2015-08-01

    Patients with schizophrenia show marked memory deficits which have a negative impact on their functioning and life quality. Recent models suggest that such deficits might be attributable to defective pattern separation (PS), a hippocampal-based computation involved in the differentiation of overlapping stimuli and their mnemonic representations. One previous study on the topic concluded in favour of pattern separation impairments in the illness. However, this study did not clarify whether more elementary recognition and/or visual discrimination deficits could explain observed group differences. To address this limitation we investigated pattern separation in 22 schizophrenic patients and 24 healthy controls with the use of a task requiring individuals to classify stimuli as repetitions, novel or similar compared to a previous familiarisation phase. In addition, we employed a visual discrimination task involving perceptual similarity judgments on the same images. Results revealed impaired performance in the patient group; both on baseline measure of pattern separation as well as an index of pattern separation rigidity. However, further analyses demonstrated that such differences could be fully explained by recognition and visual discrimination deficits. Our findings suggest that pattern separation in schizophrenia is predicated on earlier recognition and visual discrimination problems. Furthermore, we demonstrate that future studies on pattern separation should include appropriate measures of recognition and visual discrimination performance for the correct interpretation of their findings.

  1. Supervised and Unsupervised Classification for Pattern Recognition Purposes

    Directory of Open Access Journals (Sweden)

    Catalina COCIANU

    2006-01-01

    Full Text Available A cluster analysis task has to identify the grouping trends of data, to decide on the sound clusters as well as to validate somehow the resulted structure. The identification of the grouping tendency existing in a data collection assumes the selection of a framework stated in terms of a mathematical model allowing to express the similarity degree between couples of particular objects, quasi-metrics expressing the similarity between an object an a cluster and between clusters, respectively. In supervised classification, we are provided with a collection of preclassified patterns, and the problem is to label a newly encountered pattern. Typically, the given training patterns are used to learn the descriptions of classes which in turn are used to label a new pattern. The final section of the paper presents a new methodology for supervised learning based on PCA. The classes are represented in the measurement/feature space by a continuous repartitions

  2. Automatic micropropagation of plants--the vision-system: graph rewriting as pattern recognition

    Science.gov (United States)

    Schwanke, Joerg; Megnet, Roland; Jensch, Peter F.

    1993-03-01

    The automation of plant-micropropagation is necessary to produce high amounts of biomass. Plants have to be dissected on particular cutting-points. A vision-system is needed for the recognition of the cutting-points on the plants. With this background, this contribution is directed to the underlying formalism to determine cutting-points on abstract-plant models. We show the usefulness of pattern recognition by graph-rewriting along with some examples in this context.

  3. Two-dimensional optical thermal ratchets based on Fibonacci spirals.

    Science.gov (United States)

    Xiao, Ke; Roichman, Yael; Grier, David G

    2011-07-01

    An ensemble of symmetric potential energy wells arranged at the vertices of a Fibonacci spiral can serve as the basis for an irreducibly two-dimensional thermal ratchet. Periodic rotation of the potential energy landscape through a three-step cycle drives trapped Brownian particles along spiral trajectories through the pattern. Which spiral is selected depends on the angular displacement at each step, with transitions between selected spirals arising at rational proportions of the golden angle. Fibonacci spiral ratchets therefore display an exceptionally rich range of transport properties, including inhomogeneous states in which different parts of the pattern induce motion in different directions. Both the radial and angular components of these trajectories can undergo flux reversal as a function of the scale of the pattern or the rate of rotation.

  4. Color Makes a Difference: Two-Dimensional Object Naming in Literate and Illiterate Subjects

    Science.gov (United States)

    Reis, Alexandra; Faisca, Luis; Ingvar, Martin; Petersson, Karl Magnus

    2006-01-01

    Previous work has shown that illiterate subjects are better at naming two-dimensional representations of real objects when presented as colored photos as compared to black and white drawings. This raises the question if color or textural details selectively improve object recognition and naming in illiterate compared to literate subjects. In this…

  5. Machine Learning Method for Pattern Recognition in Volcano Seismic Spectra

    Science.gov (United States)

    Radic, V.; Unglert, K.; Jellinek, M.

    2016-12-01

    Variations in the spectral content of volcano seismicity related to changes in volcanic activity are commonly identified manually in spectrograms. However, long time series of monitoring data at volcano observatories require tools to facilitate automated and rapid processing. Techniques such as Self-Organizing Maps (SOM), Principal Component Analysis (PCA) and clustering methods can help to quickly and automatically identify important patterns related to impending eruptions. In this study we develop and evaluate an algorithm applied on a set of synthetic volcano seismic spectra as well as observed spectra from Kılauea Volcano, Hawai`i. Our goal is to retrieve a set of known spectral patterns that are associated with dominant phases of volcanic tremor before, during, and after periods of volcanic unrest. The algorithm is based on training a SOM on the spectra and then identifying local maxima and minima on the SOM 'topography'. The topography is derived from the first two PCA modes so that the maxima represent the SOM patterns that carry most of the variance in the spectra. Patterns identified in this way reproduce the known set of spectra. Our results show that, regardless of the level of white noise in the spectra, the algorithm can accurately reproduce the characteristic spectral patterns and their occurrence in time. The ability to rapidly classify spectra of volcano seismic data without prior knowledge of the character of the seismicity at a given volcanic system holds great potential for real time or near-real time applications, and thus ultimately for eruption forecasting.

  6. The pattern-recognition molecule mannan-binding lectin (MBL) in the pathophysiology of diabetic nephropathy

    DEFF Research Database (Denmark)

    Axelgaard, Esben; Thiel, Steffen; Hansen, Troels Krarup

    The pattern-recognition molecule mannan-binding lectin (MBL) in the pathophysiology of diabetic nephropathy Esben Axelgaard*; Steffen Thiel*; Jakob Appel Østergaard† and Troels Krarup Hansen† *Department of Biomedicine, Aarhus University, Wilhelm Meyer´s Allé 4, 8000 Aarhus C, Denmark. †Department...... of Clinical Medicine, Aarhus University and The Danish Diabetes Academy, Nørrebrogade 44, build. 3, 8000 Aarhus C, Denmark The complement system is part of the innate immune system and is an important part of the first line of defence against pathogens. Mannan-binding lectin (MBL) is one of the pattern-recognition...... mechanisms are proposed, 1) the formation of neoepitopes for MBL pattern recognition on host cells would enable lectin pathway activation and 2) inactivation of complement regulatory proteins by glycation that may exaggerate complement attack on host cells. MBL initiates the lectin pathway through binding...

  7. High-voltage cable insulation online monitoring in coal mine based on pattern recognition

    Science.gov (United States)

    Zhao, Yongmei; Li, Junfeng; Wu, Lingjie; Wang, Yanwen

    2017-03-01

    The single-phase grounding fault is the main electrical fault types of the mine power grid. A new cable insulation online monitoring based on pattern recognition is proposed, in case single-phase grounding fault in coal mine. Firstly, using the pattern recognition method, the insulation state of the cable is divided into three types: "good insulation" and "insulation decline symmetrically" and "insulation decline asymmetrically". Then the cables with "insulation decline asymmetrically" can be further analysed and calculated and its insulation parameter value can be determined. The algorithm is simulated and verified. Simulation result shows that: The zero-sequence voltage and each phase voltage and the zero-sequence current of each cable are taken in the coal mine high-voltage system, and the insulation parameter value of each cable can be calculated accurately by using the pattern recognition method.

  8. Bacterial and Fungal Pattern Recognition Receptors in Homologous Innate Signaling Pathways of Insects and Mammals

    Directory of Open Access Journals (Sweden)

    Bethany A Stokes

    2015-01-01

    Full Text Available In response to bacterial and fungal infections in insects and mammals, distinct families of innate immune pattern recognition receptors initiate highly complex intracellular signaling cascades. Those cascades induce a variety of immune functions that restrain the spread of microbes in the host. Insect and mammalian innate immune receptors include molecules that recognize conserved microbial molecular patterns. Innate immune recognition leads to the recruitment of adaptor molecules forming multi-protein complexes that include kinases, transcription factors and other regulatory molecules. Innate immune signaling cascades induce the expression of genes encoding antimicrobial peptides and other key factors that mount and regulate the immune response against microbial challenge. In this review, we summarize our current understanding of the bacterial and fungal pattern recognition receptors for homologous innate signaling pathways of insects and mammals in an effort to provide a framework for future studies.

  9. Human Walking Pattern Recognition Based on KPCA and SVM with Ground Reflex Pressure Signal

    Directory of Open Access Journals (Sweden)

    Zhaoqin Peng

    2013-01-01

    Full Text Available Algorithms based on the ground reflex pressure (GRF signal obtained from a pair of sensing shoes for human walking pattern recognition were investigated. The dimensionality reduction algorithms based on principal component analysis (PCA and kernel principal component analysis (KPCA for walking pattern data compression were studied in order to obtain higher recognition speed. Classifiers based on support vector machine (SVM, SVM-PCA, and SVM-KPCA were designed, and the classification performances of these three kinds of algorithms were compared using data collected from a person who was wearing the sensing shoes. Experimental results showed that the algorithm fusing SVM and KPCA had better recognition performance than the other two methods. Experimental outcomes also confirmed that the sensing shoes developed in this paper can be employed for automatically recognizing human walking pattern in unlimited environments which demonstrated the potential application in the control of exoskeleton robots.

  10. Pattern recognition receptors as potential therapeutic targets in inflammatory rheumatic disease.

    Science.gov (United States)

    Mullen, Lisa M; Chamberlain, Giselle; Sacre, Sandra

    2015-05-15

    The pattern recognition receptors of the innate immune system are part of the first line of defence against pathogens. However, they also have the ability to respond to danger signals that are frequently elevated during tissue damage and at sites of inflammation. Inadvertent activation of pattern recognition receptors has been proposed to contribute to the pathogenesis of many conditions including inflammatory rheumatic diseases. Prolonged inflammation most often results in pain and damage to tissues. In particular, the Toll-like receptors and nucleotide-binding oligomerisation domain-like receptors that form inflammasomes have been postulated as key contributors to the inflammation observed in rheumatoid arthritis, osteoarthritis, gout and systemic lupus erythematosus. As such, there is increasing interest in targeting these receptors for therapeutic treatment in the clinic. Here the role of pattern recognition receptors in the pathogenesis of these diseases is discussed, with an update on the development of interventions to modulate the activity of these potential therapeutic targets.

  11. Optimal excitation of two dimensional Holmboe instabilities

    CERN Document Server

    Constantinou, Navid C

    2010-01-01

    Highly stratified shear layers are rendered unstable even at high stratifications by Holmboe instabilities when the density stratification is concentrated in a small region of the shear layer. These instabilities may cause mixing in highly stratified environments. However these instabilities occur in tongues for a limited range of parameters. We perform Generalized Stability analysis of the two dimensional perturbation dynamics of an inviscid Boussinesq stratified shear layer and show that Holmboe instabilities at high Richardson numbers can be excited by their adjoints at amplitudes that are orders of magnitude larger than by introducing initially the unstable mode itself. We also determine the optimal growth that obtains for parameters for which there is no instability. We find that there is potential for large transient growth regardless of whether the background flow is exponentially stable or not and that the characteristic structure of the Holmboe instability asymptotically emerges for parameter values ...

  12. Phonon hydrodynamics in two-dimensional materials.

    Science.gov (United States)

    Cepellotti, Andrea; Fugallo, Giorgia; Paulatto, Lorenzo; Lazzeri, Michele; Mauri, Francesco; Marzari, Nicola

    2015-03-06

    The conduction of heat in two dimensions displays a wealth of fascinating phenomena of key relevance to the scientific understanding and technological applications of graphene and related materials. Here, we use density-functional perturbation theory and an exact, variational solution of the Boltzmann transport equation to study fully from first-principles phonon transport and heat conductivity in graphene, boron nitride, molybdenum disulphide and the functionalized derivatives graphane and fluorographene. In all these materials, and at variance with typical three-dimensional solids, normal processes keep dominating over Umklapp scattering well-above cryogenic conditions, extending to room temperature and more. As a result, novel regimes emerge, with Poiseuille and Ziman hydrodynamics, hitherto typically confined to ultra-low temperatures, characterizing transport at ordinary conditions. Most remarkably, several of these two-dimensional materials admit wave-like heat diffusion, with second sound present at room temperature and above in graphene, boron nitride and graphane.

  13. Probabilistic Universality in two-dimensional Dynamics

    CERN Document Server

    Lyubich, Mikhail

    2011-01-01

    In this paper we continue to explore infinitely renormalizable H\\'enon maps with small Jacobian. It was shown in [CLM] that contrary to the one-dimensional intuition, the Cantor attractor of such a map is non-rigid and the conjugacy with the one-dimensional Cantor attractor is at most 1/2-H\\"older. Another formulation of this phenomenon is that the scaling structure of the H\\'enon Cantor attractor differs from its one-dimensional counterpart. However, in this paper we prove that the weight assigned by the canonical invariant measure to these bad spots tends to zero on microscopic scales. This phenomenon is called {\\it Probabilistic Universality}. It implies, in particular, that the Hausdorff dimension of the canonical measure is universal. In this way, universality and rigidity phenomena of one-dimensional dynamics assume a probabilistic nature in the two-dimensional world.

  14. Two-dimensional position sensitive neutron detector

    Indian Academy of Sciences (India)

    A M Shaikh; S S Desai; A K Patra

    2004-08-01

    A two-dimensional position sensitive neutron detector has been developed. The detector is a 3He + Kr filled multiwire proportional counter with charge division position readout and has a sensitive area of 345 mm × 345 mm, pixel size 5 mm × 5 mm, active depth 25 mm and is designed for efficiency of 70% for 4 Å neutrons. The detector is tested with 0.5 bar 3He + 1.5 bar krypton gas mixture in active chamber and 2 bar 4He in compensating chamber. The pulse height spectrum recorded at an anode potential of 2000 V shows energy resolution of ∼ 25% for the 764 keV peak. A spatial resolution of 8 mm × 6 mm is achieved. The detector is suitable for SANS studies in the range of 0.02–0.25 Å-1.

  15. Two-dimensional heterostructures for energy storage

    Science.gov (United States)

    Pomerantseva, Ekaterina; Gogotsi, Yury

    2017-07-01

    Two-dimensional (2D) materials provide slit-shaped ion diffusion channels that enable fast movement of lithium and other ions. However, electronic conductivity, the number of intercalation sites, and stability during extended cycling are also crucial for building high-performance energy storage devices. While individual 2D materials, such as graphene, show some of the required properties, none of them can offer all properties needed to maximize energy density, power density, and cycle life. Here we argue that stacking different 2D materials into heterostructured architectures opens an opportunity to construct electrodes that would combine the advantages of the individual building blocks while eliminating the associated shortcomings. We discuss characteristics of common 2D materials and provide examples of 2D heterostructured electrodes that showed new phenomena leading to superior electrochemical performance. We also consider electrode fabrication approaches and finally outline future steps to create 2D heterostructured electrodes that could greatly expand current energy storage technologies.

  16. Rationally synthesized two-dimensional polymers.

    Science.gov (United States)

    Colson, John W; Dichtel, William R

    2013-06-01

    Synthetic polymers exhibit diverse and useful properties and influence most aspects of modern life. Many polymerization methods provide linear or branched macromolecules, frequently with outstanding functional-group tolerance and molecular weight control. In contrast, extending polymerization strategies to two-dimensional periodic structures is in its infancy, and successful examples have emerged only recently through molecular framework, surface science and crystal engineering approaches. In this Review, we describe successful 2D polymerization strategies, as well as seminal research that inspired their development. These methods include the synthesis of 2D covalent organic frameworks as layered crystals and thin films, surface-mediated polymerization of polyfunctional monomers, and solid-state topochemical polymerizations. Early application targets of 2D polymers include gas separation and storage, optoelectronic devices and membranes, each of which might benefit from predictable long-range molecular organization inherent to this macromolecular architecture.

  17. Janus Spectra in Two-Dimensional Flows

    Science.gov (United States)

    Liu, Chien-Chia; Cerbus, Rory T.; Chakraborty, Pinaki

    2016-09-01

    In large-scale atmospheric flows, soap-film flows, and other two-dimensional flows, the exponent of the turbulent energy spectra, α , may theoretically take either of two distinct values, 3 or 5 /3 , but measurements downstream of obstacles have invariably revealed α =3 . Here we report experiments on soap-film flows where downstream of obstacles there exists a sizable interval in which α transitions from 3 to 5 /3 for the streamwise fluctuations but remains equal to 3 for the transverse fluctuations, as if two mutually independent turbulent fields of disparate dynamics were concurrently active within the flow. This species of turbulent energy spectra, which we term the Janus spectra, has never been observed or predicted theoretically. Our results may open up new vistas in the study of turbulence and geophysical flows.

  18. Local doping of two-dimensional materials

    Science.gov (United States)

    Wong, Dillon; Velasco, Jr, Jairo; Ju, Long; Kahn, Salman; Lee, Juwon; Germany, Chad E.; Zettl, Alexander K.; Wang, Feng; Crommie, Michael F.

    2016-09-20

    This disclosure provides systems, methods, and apparatus related to locally doping two-dimensional (2D) materials. In one aspect, an assembly including a substrate, a first insulator disposed on the substrate, a second insulator disposed on the first insulator, and a 2D material disposed on the second insulator is formed. A first voltage is applied between the 2D material and the substrate. With the first voltage applied between the 2D material and the substrate, a second voltage is applied between the 2D material and a probe positioned proximate the 2D material. The second voltage between the 2D material and the probe is removed. The first voltage between the 2D material and the substrate is removed. A portion of the 2D material proximate the probe when the second voltage was applied has a different electron density compared to a remainder of the 2D material.

  19. Two-dimensional fourier transform spectrometer

    Energy Technology Data Exchange (ETDEWEB)

    DeFlores, Lauren; Tokmakoff, Andrei

    2016-10-25

    The present invention relates to a system and methods for acquiring two-dimensional Fourier transform (2D FT) spectra. Overlap of a collinear pulse pair and probe induce a molecular response which is collected by spectral dispersion of the signal modulated probe beam. Simultaneous collection of the molecular response, pulse timing and characteristics permit real time phasing and rapid acquisition of spectra. Full spectra are acquired as a function of pulse pair timings and numerically transformed to achieve the full frequency-frequency spectrum. This method demonstrates the ability to acquire information on molecular dynamics, couplings and structure in a simple apparatus. Multi-dimensional methods can be used for diagnostic and analytical measurements in the biological, biomedical, and chemical fields.

  20. Two-dimensional fourier transform spectrometer

    Science.gov (United States)

    DeFlores, Lauren; Tokmakoff, Andrei

    2013-09-03

    The present invention relates to a system and methods for acquiring two-dimensional Fourier transform (2D FT) spectra. Overlap of a collinear pulse pair and probe induce a molecular response which is collected by spectral dispersion of the signal modulated probe beam. Simultaneous collection of the molecular response, pulse timing and characteristics permit real time phasing and rapid acquisition of spectra. Full spectra are acquired as a function of pulse pair timings and numerically transformed to achieve the full frequency-frequency spectrum. This method demonstrates the ability to acquire information on molecular dynamics, couplings and structure in a simple apparatus. Multi-dimensional methods can be used for diagnostic and analytical measurements in the biological, biomedical, and chemical fields.

  1. The Role of Verbal Instruction and Visual Guidance in Training Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Jamie S. North

    2017-09-01

    Full Text Available We used a novel approach to examine whether it is possible to improve the perceptual–cognitive skill of pattern recognition using a video-based training intervention. Moreover, we investigated whether any improvements in pattern recognition transfer to an improved ability to make anticipation judgments. Finally, we compared the relative effectiveness of verbal and visual guidance interventions compared to a group that merely viewed the same sequences without any intervention and a control group that only completed pre- and post-tests. We found a significant effect for time of testing. Participants were more sensitive in their ability to perceive patterns and distinguish between novel and familiar sequences at post- compared to pre-test. However, this improvement was not influenced by the nature of the intervention, despite some trends in the data. An analysis of anticipation accuracy showed no change from pre- to post-test following the pattern recognition training intervention, suggesting that the link between pattern perception and anticipation may not be strong. We present a series of recommendations for scientists and practitioners when employing training methods to improve pattern recognition and anticipation.

  2. Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

    Science.gov (United States)

    Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

    2016-11-01

    Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

  3. Hypothetical Pattern Recognition Design Using Multi-Layer Perceptorn Neural Network For Supervised Learning

    Directory of Open Access Journals (Sweden)

    Md. Abdullah-al-mamun

    2015-08-01

    Full Text Available Abstract Humans are capable to identifying diverse shape in the different pattern in the real world as effortless fashion due to their intelligence is grow since born with facing several learning process. Same way we can prepared an machine using human like brain called Artificial Neural Network that can be recognize different pattern from the real world object. Although the various techniques is exists to implementation the pattern recognition but recently the artificial neural network approaches have been giving the significant attention. Because the approached of artificial neural network is like a human brain that is learn from different observation and give a decision the previously learning rule. Over the 50 years research now a days pattern recognition for machine learning using artificial neural network got a significant achievement. For this reason many real world problem can be solve by modeling the pattern recognition process. The objective of this paper is to present the theoretical concept for pattern recognition design using Multi-Layer Perceptorn neural networkin the algorithm of artificial Intelligence as the best possible way of utilizing available resources to make a decision that can be a human like performance.

  4. Automatic SIMD parallelization of embedded applications based on pattern recognition

    NARCIS (Netherlands)

    Manniesing, R.; Karkowski, I.P.; Corporaal, H.

    2000-01-01

    This paper investigates the potential for automatic mapping of typical embedded applications to architectures with multimedia instruction set extensions. For this purpose a (pattern matching based) code transformation engine is used, which involves a three-step process of matching, condition checkin

  5. Postural pattern recognition in children with unilateral cerebral palsy

    Directory of Open Access Journals (Sweden)

    Domagalska-Szopa M

    2014-02-01

    Full Text Available Małgorzata Domagalska-Szopa, Andrzej Szopa School of Health Sciences, Medical University of Silesia, Katowice, Poland Background: Several different strategies for maintaining upright standing posture in children with cerebral palsy (CP were observed. Purpose: The purpose of the present study was to define two different postural patterns in children with unilateral CP, using moiré topography (MT parameters. Additionally, another focus of this article was to outline some implications for managing physiotherapy in children with hemiplegia. Patients and methods: The study included 45 outpatients with unilateral CP. MT examinations were performed using a CQ Elektronik System device. In addition, a weight distribution analysis on the base of support between unaffected and affected body sides was performed simultaneously. A force plate pressure distribution measurement system (PDM-S with Foot Print software was used for these measurements. Results: The cluster analysis revealed four groups: cluster 1 (n=19; 42.22%; cluster 2 (n=7; 15.56%; cluster 3 (n=9; 20.00%; and cluster 4 (n=10; 22.22%. Conclusion: Based on the MT parameters (extracted using a data reduction technique, two postural patterns were described: 1 the pro-gravitational postural pattern; and 2 the anti-gravitational pattern. Keywords: deviation of body posture, strategy of compensation, moiré topography examinations, cluster analysis

  6. Pattern Recognition for Reliability Assessment of Water Distribution Networks

    NARCIS (Netherlands)

    Trifunović, N.

    2012-01-01

    The study presented in this manuscript investigates the patterns that describe reliability of water distribution networks focusing to the node connectivity, energy balance, and economics of construction, operation and maintenance. A number of measures to evaluate the network resilience has been deve

  7. Automatic SIMD parallelization of embedded applications based on pattern recognition

    NARCIS (Netherlands)

    Manniesing, R.; Karkowski, I.P.; Corporaal, H.

    2000-01-01

    This paper investigates the potential for automatic mapping of typical embedded applications to architectures with multimedia instruction set extensions. For this purpose a (pattern matching based) code transformation engine is used, which involves a three-step process of matching, condition

  8. Analysis of the hand vein pattern for people recognition

    Science.gov (United States)

    Castro-Ortega, R.; Toxqui-Quitl, C.; Cristóbal, G.; Marcos, J. Victor; Padilla-Vivanco, A.; Hurtado Pérez, R.

    2015-09-01

    The shape of the hand vascular pattern contains useful and unique features that can be used for identifying and authenticating people, with applications in access control, medicine and financial services. In this work, an optical system for the image acquisition of the hand vascular pattern is implemented. It consists of a CCD camera with sensitivity in the IR and a light source with emission in the 880 nm. The IR radiation interacts with the desoxyhemoglobin, hemoglobin and water present in the blood of the veins, making possible to see the vein pattern underneath skin. The segmentation of the Region Of Interest (ROI) is achieved using geometrical moments locating the centroid of an image. For enhancement of the vein pattern we use the technique of Histogram Equalization and Contrast Limited Adaptive Histogram Equalization (CLAHE). In order to remove unnecessary information such as body hair and skinfolds, a low pass filter is implemented. A method based on geometric moments is used to obtain the invariant descriptors of the input images. The classification task is achieved using Artificial Neural Networks (ANN) and K-Nearest Neighbors (K-nn) algorithms. Experimental results using our database show a percentage of correct classification, higher of 86.36% with ANN for 912 images of 38 people with 12 versions each one.

  9. Determination of ocular torsion by means of automatic pattern recognition

    NARCIS (Netherlands)

    Groen, E.L.; Bos, J.E.; Nacken, P.F.M.; Graaf, B. de

    1996-01-01

    A new, automatic method for determination of human ocular torsion (OT) was devel-oped based on the tracking of iris patterns in digitized video images. Instead of quanti-fying OT by means of cross-correlation of circular iris samples, a procedure commonly applied, this new method automatically selec

  10. Method and system for determining a volume of an object from two-dimensional images

    Science.gov (United States)

    Abercrombie, Robert K [Knoxville, TN; Schlicher, Bob G [Portsmouth, NH

    2010-08-10

    The invention provides a method and a computer program stored in a tangible medium for automatically determining a volume of three-dimensional objects represented in two-dimensional images, by acquiring at two least two-dimensional digitized images, by analyzing the two-dimensional images to identify reference points and geometric patterns, by determining distances between the reference points and the component objects utilizing reference data provided for the three-dimensional object, and by calculating a volume for the three-dimensional object.

  11. Improved Algorithm of Pattern Classification and Recognition Applied in a Coal Dust Sensor

    Institute of Scientific and Technical Information of China (English)

    MA Feng-ying; SONG Shu

    2007-01-01

    To resolve the conflicting requirements of measurement precision and real-time performance speed, an improved algorithm for pattern classification and recognition was developed. The angular distribution of diffracted light varies with particle size. These patterns could be classified into groups with an innovative classification based upon reference dust samples. After such classification patterns could be recognized easily and rapidly by minimizing the variance between the reference pattern and dust sample eigenvectors. Simulation showed that the maximum recognition speed improves 20 fold. This enables the use of a single-chip, real-time inversion algorithm. An increased number of reference patterns reduced the errors in total and respiring coal dust measurements. Experiments in coal mine testify that the accuracy of sensor achieves 95%. Results indicate the improved algorithm enhances the precision and real-time capability of the coal dust sensor effectively.

  12. Water quality assessment for Ulansuhai Lake using fuzzy clustering and pattern recognition

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Water quality assessment of lakes is important to determine functional zones of water use. Considering the fuzziness during the partitioning process for lake water quality in an arid area, a multiplex model of fuzzy clustering with pattern recognition was developed by integrating transitive closure method, ISODATA algorithm in fuzzy clustering and fuzzy pattern recognition. The model was applied to partition the Ulansuhai Lake, a typical shallow lake in arid climate zone in the west part of Inner Mongolia, China and grade the condition of water quality divisions. The results showed that the partition well matched the real conditions of the lake, and the method has been proved accurate in the application.

  13. An Efficient and Robust Singular Value Method for Star Pattern Recognition and Attitude Determination

    Science.gov (United States)

    Juang, Jer-Nan; Kim, Hye-Young; Junkins, John L.

    2003-01-01

    A new star pattern recognition method is developed using singular value decomposition of a measured unit column vector matrix in a measurement frame and the corresponding cataloged vector matrix in a reference frame. It is shown that singular values and right singular vectors are invariant with respect to coordinate transformation and robust under uncertainty. One advantage of singular value comparison is that a pairing process for individual measured and cataloged stars is not necessary, and the attitude estimation and pattern recognition process are not separated. An associated method for mission catalog design is introduced and simulation results are presented.

  14. Color pattern recognition based on the joint fractional Fourier transform correlator

    Institute of Scientific and Technical Information of China (English)

    Weimin Jin; Yupei Zhang

    2007-01-01

    A new system of multi-channel single-output joint fractional Fourier transform correlator (JFRTC) for color pattern recognition is proposed based on the conventional system of multi-channel single-output joint transform correlator (JTC). The theoretical analysis and optical experiments are performed. With this method, one can obtain three correlation peaks at the output plane which show a pair of desired cross-correlation peaks and one auto-correlation peak. In comparison, the conventional system leads to more correlation peaks playing a noise role in color pattern recognition.

  15. Rough-fuzzy pattern recognition applications in bioinformatics and medical imaging

    CERN Document Server

    Maji, Pradipta

    2012-01-01

    Learn how to apply rough-fuzzy computing techniques to solve problems in bioinformatics and medical image processing Emphasizing applications in bioinformatics and medical image processing, this text offers a clear framework that enables readers to take advantage of the latest rough-fuzzy computing techniques to build working pattern recognition models. The authors explain step by step how to integrate rough sets with fuzzy sets in order to best manage the uncertainties in mining large data sets. Chapters are logically organized according to the major phases of pattern recognition systems dev

  16. Temporal pattern recognition based on instantaneous spike rate coding in a simple auditory system.

    Science.gov (United States)

    Nabatiyan, A; Poulet, J F A; de Polavieja, G G; Hedwig, B

    2003-10-01

    Auditory pattern recognition by the CNS is a fundamental process in acoustic communication. Because crickets communicate with stereotyped patterns of constant frequency syllables, they are established models to investigate the neuronal mechanisms of auditory pattern recognition. Here we provide evidence that for the neural processing of amplitude-modulated sounds, the instantaneous spike rate rather than the time-averaged neural activity is the appropriate coding principle by comparing both coding parameters in a thoracic interneuron (Omega neuron ON1) of the cricket (Gryllus bimaculatus) auditory system. When stimulated with different temporal sound patterns, the analysis of the instantaneous spike rate demonstrates that the neuron acts as a low-pass filter for syllable patterns. The instantaneous spike rate is low at high syllable rates, but prominent peaks in the instantaneous spike rate are generated as the syllable rate resembles that of the species-specific pattern. The occurrence and repetition rate of these peaks in the neuronal discharge are sufficient to explain temporal filtering in the cricket auditory pathway as they closely match the tuning of phonotactic behavior to different sound patterns. Thus temporal filtering or "pattern recognition" occurs at an early stage in the auditory pathway.

  17. Recognition of higher order patterns in proteins: immunologic kernels.

    Directory of Open Access Journals (Sweden)

    Robert D Bremel

    Full Text Available By applying analysis of the principal components of amino acid physical properties we predicted cathepsin cleavage sites, MHC binding affinity, and probability of B-cell epitope binding of peptides in tetanus toxin and in ten diverse additional proteins. Cross-correlation of these metrics, for peptides of all possible amino acid index positions, each evaluated in the context of a ±25 amino acid flanking region, indicated that there is a strongly repetitive pattern of short peptides of approximately thirty amino acids each bounded by cathepsin cleavage sites and each comprising B-cell linear epitopes, MHC-I and MHC-II binding peptides. Such "immunologic kernel" peptides comprise all signals necessary for adaptive immunologic cognition, response and recall. The patterns described indicate a higher order spatial integration that forms a symbolic logic coordinating the adaptive immune system.

  18. Pattern Recognition-Based Analysis of COPD in CT

    DEFF Research Database (Denmark)

    Sørensen, Lauge Emil Borch Laurs

    Computed tomography (CT), a medical imaging technique, offers a detailed view of the human body that can be used for direct inspection of the lung tissue. This allows for in vivo measurement of subtle disease patterns such as the patterns associated with chronic obstructive pulmonary disease (COPD......). COPD, also commonly referred to as “smokers’ lungs”, is a lung disease characterized by limitation of the airflow to and from the lungs causing shortness of breath. The disease is expected to rank as the fifth most burdening disease worldwide by 2020 according the the World Health Organization. COPD...... comprises two main components, chronic bronchitis, characterized by inflammation in the airways, and emphysema, characterized by loss of lung tissue. Emphysema basically looks like black blobs of varying sizes within the normal, gray lung tissue in CT, and can therefore be seen as a family of texture...

  19. Fingerprint Recognition using Fuzzy Logic with Triangular Pattern Template

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar

    2006-01-01

    A fingerprint is a pattern of ridges and valleys that exist on the surface of the finger. The uniqueness of a fingerprint is typically determined by the overall pattern of ridges and valleys as well as the local ridge structures e.g., a ridge bifurcation or a ridge ending, which are called minutiae...... points. Designing a reliable automatic fingerprint matching algorithm is quite challenging. However, the popularity of fingerprint sensors as they are becoming smaller and cheaper, automatic identification based on fingerprints is becoming not only attractive but an alternative complement...... to the traditional methods of identification. The critical factor in the widespread use of fingerprints identification is, satisfying the performance e.g., speed of matching and accuracy requirements of the application.  The widely used minutiae-based representation utilizes this discriminatory information available...

  20. Manifold Matching for High-Dimensional Pattern Recognition

    OpenAIRE

    HOTTA, Seiji

    2008-01-01

    In this chapter manifold matching for high-dimensional pattern classification was described. The topics described in this chapter were summarized as follows: The meaning and effectiveness of manifold matching The similarity between various classifiers from the point of view of manifold matching Accuracy improvement for manifold matching Learning rules for manifold matching Experimental results on handwritten digit datasets showed that manifold matching achieved lower error rates than other cl...

  1. Oxidation-specific epitopes are danger-associated molecular patterns recognized by pattern recognition receptors of innate immunity

    DEFF Research Database (Denmark)

    Miller, Yury I; Choi, Soo-Ho; Wiesner, Philipp

    2011-01-01

    are a major target of innate immunity, recognized by a variety of "pattern recognition receptors" (PRRs). By analogy with microbial "pathogen-associated molecular patterns" (PAMPs), we postulate that host-derived, oxidation-specific epitopes can be considered to represent "danger (or damage......)-associated molecular patterns" (DAMPs). We also argue that oxidation-specific epitopes present on apoptotic cells and their cellular debris provided the primary evolutionary pressure for the selection of such PRRs. Furthermore, because many PAMPs on microbes share molecular identity and/or mimicry with oxidation...

  2. Dielectric-barrier discharges in two-dimensional lattice potentials

    CERN Document Server

    Sinclair, Josiah

    2011-01-01

    We use a pin-grid electrode to introduce a corrugated electrical potential into a planar dielectric-barrier discharge (DBD) system, so that the amplitude of the applied electric field has the profile of a two-dimensional square lattice. The lattice potential provides a template for the spatial distribution of plasma filaments in the system and has pronounced effects on the patterns that can form. The positions at which filaments become localized within the lattice unit cell vary with the width of the discharge gap. The patterns that appear when filaments either overfill or under-fill the lattice are reminiscent of those observed in other physical systems involving 2d lattices. We suggest that the connection between lattice-driven DBDs and other areas of physics may benefit from the further development of models that treat plasma filaments as interacting particles.

  3. Isolated structures in two-dimensional optical superlattice

    Science.gov (United States)

    Zou, Xin-Hao; Yang, Bao-Guo; Xu, Xia; Tang, Peng-Ju; Zhou, Xiao-Ji

    2017-10-01

    Overlaying commensurate optical lattices with various configurations called superlattices can lead to exotic lattice topologies and, in turn, a discovery of novel physics. In this study, by overlapping the maxima of lattices, a new isolated structure is created, while the interference of minima can generate various "sublattice" patterns. Three different kinds of primitive lattices are used to demonstrate isolated square, triangular, and hexagonal "sublattice" structures in a two-dimensional optical superlattice, the patterns of which can be manipulated dynamically by tuning the polarization, frequency, and intensity of laser beams. In addition, we propose the method of altering the relative phase to adjust the tunneling amplitudes in "sublattices". Our configurations provide unique opportunities to study particle entanglement in "lattices" formed by intersecting wells and to implement special quantum logic gates in exotic lattice geometries.

  4. Isolated Structures in Two-Dimensional Optical Superlattice

    CERN Document Server

    Zou, Xinhao; Xu, Xia; Tang, Pengju; Zhou, Xiaoji

    2016-01-01

    Overlaying commensurate optical lattices with various configurations called superlattices can lead to exotic lattice topologies and, in turn, a discovery of novel physics. In this study, by overlapping the maxima of lattices, a new isolated structure is created, while the interference of minima can generate various "sublattice" patterns. Three different kinds of primitive lattices are used to demonstrate isolated square, triangular, and hexagonal "sublattice" structures in a two-dimensional optical superlattice, the patterns of which can be manipulated dynamically by tuning the polarization, frequency, and intensity of laser beams. In addition, we propose the method of altering the relative phase to adjust the tunneling amplitudes in "sublattices." Our configurations provide unique opportunities to study particle entanglement in "lattices" formed by intersecting wells and to implement special quantum logic gates in exotic lattice geometries.

  5. On numerical evaluation of two-dimensional phase integrals

    DEFF Research Database (Denmark)

    Lessow, H.; Rusch, W.; Schjær-Jacobsen, Hans

    1975-01-01

    The relative advantages of several common numerical integration algorithms used in computing two-dimensional phase integrals are evaluated.......The relative advantages of several common numerical integration algorithms used in computing two-dimensional phase integrals are evaluated....

  6. Pattern Recognition Using Carbon Nanotube Synaptic Transistors with an Adjustable Weight Update Protocol.

    Science.gov (United States)

    Kim, Sungho; Choi, Bongsik; Lim, Meehyun; Yoon, Jinsu; Lee, Juhee; Kim, Hee-Dong; Choi, Sung-Jin

    2017-03-28

    Recent electronic applications require an efficient computing system that can perform data processing with limited energy consumption. Inspired by the massive parallelism of the human brain, a neuromorphic system (hardware neural network) may provide an efficient computing unit to perform such tasks as classification and recognition. However, the implementation of synaptic devices (i.e., the essential building blocks for emulating the functions of biological synapses) remains challenging due to their uncontrollable weight update protocol and corresponding uncertain effects on the operation of the system, which can lead to a bottleneck in the continuous design and optimization. Here, we demonstrate a synaptic transistor based on highly purified, preseparated 99% semiconducting carbon nanotubes, which can provide adjustable weight update linearity and variation margin. The pattern recognition efficacy is validated using a device-to-system level simulation framework. The enlarged margin rather than the linear weight update can enhance the fault tolerance of the recognition system, which improves the recognition accuracy.

  7. Pattern recognition in the automatic inspection of aluminium castings

    Energy Technology Data Exchange (ETDEWEB)

    Mery, D. [Univ. de Santiago de Chile, Santiego (Chile); Silva, R.R. da; Rebello, J.M.A. [Univ. Federal do Rio de Janeiro (Brazil). Eng. Metalurgical/Materiais; Caloba, L.P. [Univ. Federal do Rio de Janeiro (Brazil). Eng. Electronica

    2003-07-01

    In this paper, we report the results obtained recently by analysing around 400 features measured from 23.000 regions segmented in 50 radioscopic images of cast aluminium wheels with defects. The extracted features are divided into two groups: geometric features (area, perimeter, height, width, roundness, Fourier descriptors, invariant moments, and other shape factors) and grey value features (mean grey value, mean gradient in the boundary, mean second derivate in the region, radiographic contrasts, invariant moments with grey value information, local variance, textural features based on the co-occurrence matrix, coefficients of the discrete Fourier transform, the Karhunen Loeve transform and the discrete cosine transform). We propose a new contrast feature obtained from grey level profiles along straight lines crossing the segmented potential defects. Analysing the area Az under the receiver operation characteristic (ROC) curve, this feature presents the best individual detection performance yielding an area Az=0.9944. In order to make a compact pattern representation and a simple decision strategy, the number of features are reduced using feature selection approaches. The relevance of the selected features is evaluated by calculation of linear correlation coefficient. The results are shown in tables of the linear correlation coefficients between features, and among features and class of defect. In addition, statistical classifiers and classifiers based on neural networks are implemented in order to establish decision boundaries in the space of the selected features which separate patterns (our segmented regions) belonging to two different classes (regular structure or defects).

  8. Volumetric display containing multiple two-dimensional color motion pictures

    Science.gov (United States)

    Hirayama, R.; Shiraki, A.; Nakayama, H.; Kakue, T.; Shimobaba, T.; Ito, T.

    2014-06-01

    We have developed an algorithm which can record multiple two-dimensional (2-D) gradated projection patterns in a single three-dimensional (3-D) object. Each recorded pattern has the individual projected direction and can only be seen from the direction. The proposed algorithm has two important features: the number of recorded patterns is theoretically infinite and no meaningful pattern can be seen outside of the projected directions. In this paper, we expanded the algorithm to record multiple 2-D projection patterns in color. There are two popular ways of color mixing: additive one and subtractive one. Additive color mixing used to mix light is based on RGB colors and subtractive color mixing used to mix inks is based on CMY colors. We made two coloring methods based on the additive mixing and subtractive mixing. We performed numerical simulations of the coloring methods, and confirmed their effectiveness. We also fabricated two types of volumetric display and applied the proposed algorithm to them. One is a cubic displays constructed by light-emitting diodes (LEDs) in 8×8×8 array. Lighting patterns of LEDs are controlled by a microcomputer board. The other one is made of 7×7 array of threads. Each thread is illuminated by a projector connected with PC. As a result of the implementation, we succeeded in recording multiple 2-D color motion pictures in the volumetric displays. Our algorithm can be applied to digital signage, media art and so forth.

  9. Crowding by a single bar: probing pattern recognition mechanisms in the visual periphery.

    Science.gov (United States)

    Põder, Endel

    2014-11-06

    Whereas visual crowding does not greatly affect the detection of the presence of simple visual features, it heavily inhibits combining them into recognizable objects. Still, crowding effects have rarely been directly related to general pattern recognition mechanisms. In this study, pattern recognition mechanisms in visual periphery were probed using a single crowding feature. Observers had to identify the orientation of a rotated T presented briefly in a peripheral location. Adjacent to the target, a single bar was presented. The bar was either horizontal or vertical and located in a random direction from the target. It appears that such a crowding bar has very strong and regular effects on the identification of the target orientation. The observer's responses are determined by approximate relative positions of basic visual features; exact image-based similarity to the target is not important. A version of the "standard model" of object recognition with second-order features explains the main regularities of the data.

  10. Study on local Gabor binary patterns for face representation and recognition

    Science.gov (United States)

    Ge, Wei; Han, Chunling; Quan, Wei

    2015-12-01

    More recently, Local Binary Patterns(LBP) has received much attention in face representation and recognition. The original LBP operator could describe the spatial structure information, which are the variety edge or variety angle features of local facial images essentially, they are important factors of classify different faces. But the scale and orientation of the edge features include more detail information which could be used to classify different persons efficiently, while original LBP operator could not to extract the information. In this paper, based on the introduction of original LBP-based facial representation and recognition, the histogram sequences of local Gabor binary patterns are used to representation facial image. Principal Component Analysis (PCA) method is used to classification the histogram sequences, which have been converted to vectors. Recognition experimental results show that the method we used in this paper increases nearly 6% than the classification performance of original LBP operator.

  11. Summary of the transfer of optical processing to systems: optical pattern recognition program

    Science.gov (United States)

    Lindell, Scott D.

    1995-06-01

    Martin Marietta has successfully completed a TOPS optical pattern recognition program. The program culminated in August 1994 with an automatic target recognition flight demonstration inwhich an M60A2 tank was acquired, identified, and tracked with a visible seeker from a UH-1 helicopter flying a fiber optic guided missile (FOG-M) mission profile. The flight demonstration was conducted by the US Army Missile Command (MICOM) and supported by Martin Marietta. The pattern recognition system performance for acquiring and identifying the M60A2 tank, which was positioned among an array with five other vehicle types, was 90% probability of correct identification and a 4% false identification for over 40,000 frames of imagery processed. Imagery was processed at a 15 Hz input rate with a 1 ft3, 76 W, 4 GFLOP processor performing up to 800 correlations per second.

  12. Study on the classification algorithm of degree of arteriosclerosis based on fuzzy pattern recognition

    Science.gov (United States)

    Ding, Li; Zhou, Runjing; Liu, Guiying

    2010-08-01

    Pulse wave of human body contains large amount of physiological and pathological information, so the degree of arteriosclerosis classification algorithm is study based on fuzzy pattern recognition in this paper. Taking the human's pulse wave as the research object, we can extract the characteristic of time and frequency domain of pulse signal, and select the parameters with a better clustering effect for arteriosclerosis identification. Moreover, the validity of characteristic parameters is verified by fuzzy ISODATA clustering method (FISOCM). Finally, fuzzy pattern recognition system can quantitatively distinguish the degree of arteriosclerosis with patients. By testing the 50 samples in the built pulse database, the experimental result shows that the algorithm is practical and achieves a good classification recognition result.

  13. Multi-radius centralized binary pattern histogram projection for face recognition

    Institute of Scientific and Technical Information of China (English)

    Xiaofeng Fu; Wei Wei

    2009-01-01

    The existing local binary pattern (LBP) operators have several disadvantages such as rather long histograms,lower discrimination,and sensitivity to noise.Aiming at these problems,we propose the centralized binary pattern (CBP) operator.CBP operator can significantly rcduce the histograms' dimensionality,offer stronger discrimination,and decrease the white noise's influence on face images.Moreover,for increasing the recognition accuracy and speed,we use multi-radius CBP histogram as face representation and project it onto locality preserving projection (LPP) space to obtain lower dimensional features.Experiments on FERET and CAS-PEAL databases demonstrate that the proposed method is superior to other modern approaches not only in recognition accuracy but also in recognition speed.

  14. A Dynamic Interval-Valued Intuitionistic Fuzzy Sets Applied to Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Zhenhua Zhang

    2013-01-01

    Full Text Available We present dynamic interval-valued intuitionistic fuzzy sets (DIVIFS, which can improve the recognition accuracy when they are applied to pattern recognition. By analyzing the degree of hesitancy, we propose some DIVIFS models from intuitionistic fuzzy sets (IFS and interval-valued IFS (IVIFS. And then we present a novel ranking condition on the distance of IFS and IVIFS and introduce some distance measures of DIVIFS satisfying the ranking condition. Finally, a pattern recognition example applied to medical diagnosis decision making is given to demonstrate the application of DIVIFS and its distances. The simulation results show that the DIVIFS method is more comprehensive and flexible than the IFS method and the IVIFS method.

  15. Structural basis of recognition of pathogen-associated molecular patterns and inhibition of proinflammatory cytokines by camel peptidoglycan recognition protein.

    Science.gov (United States)

    Sharma, Pradeep; Dube, Divya; Singh, Amar; Mishra, Biswajit; Singh, Nagendra; Sinha, Mau; Dey, Sharmistha; Kaur, Punit; Mitra, Dipendra K; Sharma, Sujata; Singh, Tej P

    2011-05-06

    Peptidoglycan recognition proteins (PGRPs) are involved in the recognition of pathogen-associated molecular patterns. The well known pathogen-associated molecular patterns include LPS from Gram-negative bacteria and lipoteichoic acid (LTA) from Gram-positive bacteria. In this work, the crystal structures of two complexes of the short form of camel PGRP (CPGRP-S) with LPS and LTA determined at 1.7- and 2.1-Å resolutions, respectively, are reported. Both compounds were held firmly inside the complex formed with four CPGRP-S molecules designated A, B, C, and D. The binding cleft is located at the interface of molecules C and D, which is extendable to the interface of molecules A and C. The interface of molecules A and B is tightly packed, whereas that of molecules B and D forms a wide channel. The hydrophilic moieties of these compounds occupy a common region, whereas hydrophobic chains interact with distinct regions in the binding site. The binding studies showed that CPGRP-S binds to LPS and LTA with affinities of 1.6 × 10(-9) and 2.4 × 10(-8) M, respectively. The flow cytometric studies showed that both LPS- and LTA-induced expression of the proinflammatory cytokines TNF-α and IL-6 was inhibited by CPGRP-S. The results of animal studies using mouse models indicated that both LPS- and LTA-induced mortality rates decreased drastically when CPGRP-S was administered. The recognition of both LPS and LTA, their high binding affinities for CPGRP-S, the significant decrease in the production of LPS- and LTA-induced TNF-α and IL-6, and the drastic reduction in the mortality rates in mice by CPGRP-S indicate its useful properties as an antibiotic agent.

  16. Structural Basis of Recognition of Pathogen-associated Molecular Patterns and Inhibition of Proinflammatory Cytokines by Camel Peptidoglycan Recognition Protein*

    Science.gov (United States)

    Sharma, Pradeep; Dube, Divya; Singh, Amar; Mishra, Biswajit; Singh, Nagendra; Sinha, Mau; Dey, Sharmistha; Kaur, Punit; Mitra, Dipendra K.; Sharma, Sujata; Singh, Tej P.

    2011-01-01

    Peptidoglycan recognition proteins (PGRPs) are involved in the recognition of pathogen-associated molecular patterns. The well known pathogen-associated molecular patterns include LPS from Gram-negative bacteria and lipoteichoic acid (LTA) from Gram-positive bacteria. In this work, the crystal structures of two complexes of the short form of camel PGRP (CPGRP-S) with LPS and LTA determined at 1.7- and 2.1-Å resolutions, respectively, are reported. Both compounds were held firmly inside the complex formed with four CPGRP-S molecules designated A, B, C, and D. The binding cleft is located at the interface of molecules C and D, which is extendable to the interface of molecules A and C. The interface of molecules A and B is tightly packed, whereas that of molecules B and D forms a wide channel. The hydrophilic moieties of these compounds occupy a common region, whereas hydrophobic chains interact with distinct regions in the binding site. The binding studies showed that CPGRP-S binds to LPS and LTA with affinities of 1.6 × 10−9 and 2.4 × 10−8 m, respectively. The flow cytometric studies showed that both LPS- and LTA-induced expression of the proinflammatory cytokines TNF-α and IL-6 was inhibited by CPGRP-S. The results of animal studies using mouse models indicated that both LPS- and LTA-induced mortality rates decreased drastically when CPGRP-S was administered. The recognition of both LPS and LTA, their high binding affinities for CPGRP-S, the significant decrease in the production of LPS- and LTA-induced TNF-α and IL-6, and the drastic reduction in the mortality rates in mice by CPGRP-S indicate its useful properties as an antibiotic agent. PMID:21454594

  17. Perspective: Two-dimensional resonance Raman spectroscopy

    Science.gov (United States)

    Molesky, Brian P.; Guo, Zhenkun; Cheshire, Thomas P.; Moran, Andrew M.

    2016-11-01

    Two-dimensional resonance Raman (2DRR) spectroscopy has been developed for studies of photochemical reaction mechanisms and structural heterogeneity in complex systems. The 2DRR method can leverage electronic resonance enhancement to selectively probe chromophores embedded in complex environments (e.g., a cofactor in a protein). In addition, correlations between the two dimensions of the 2DRR spectrum reveal information that is not available in traditional Raman techniques. For example, distributions of reactant and product geometries can be correlated in systems that undergo chemical reactions on the femtosecond time scale. Structural heterogeneity in an ensemble may also be reflected in the 2D spectroscopic line shapes of both reactive and non-reactive systems. In this perspective article, these capabilities of 2DRR spectroscopy are discussed in the context of recent applications to the photodissociation reactions of triiodide and myoglobin. We also address key differences between the signal generation mechanisms for 2DRR and off-resonant 2D Raman spectroscopies. Most notably, it has been shown that these two techniques are subject to a tradeoff between sensitivity to anharmonicity and susceptibility to artifacts. Overall, recent experimental developments and applications of the 2DRR method suggest great potential for the future of the technique.

  18. Janus spectra in two-dimensional flows

    CERN Document Server

    Liu, Chien-Chia; Chakraborty, Pinaki

    2016-01-01

    In theory, large-scale atmospheric flows, soap-film flows and other two-dimensional flows may host two distinct types of turbulent energy spectra---in one, $\\alpha$, the spectral exponent of velocity fluctuations, equals $3$ and the fluctuations are dissipated at the small scales, and in the other, $\\alpha=5/3$ and the fluctuations are dissipated at the large scales---but measurements downstream of obstacles have invariably revealed $\\alpha = 3$. Here we report experiments on soap-film flows where downstream of obstacles there exists a sizable interval in which $\\alpha$ has transitioned from $3$ to $5/3$ for the streamwise fluctuations but remains equal to $3$ for the transverse fluctuations, as if two mutually independent turbulent fields of disparate dynamics were concurrently active within the flow. This species of turbulent energy spectra, which we term the Janus spectra, has never been observed or predicted theoretically. Our results may open up new vistas in the study of turbulence and geophysical flows...

  19. Comparative Two-Dimensional Fluorescence Gel Electrophoresis.

    Science.gov (United States)

    Ackermann, Doreen; König, Simone

    2018-01-01

    Two-dimensional comparative fluorescence gel electrophoresis (CoFGE) uses an internal standard to increase the reproducibility of coordinate assignment for protein spots visualized on 2D polyacrylamide gels. This is particularly important for samples, which need to be compared without the availability of replicates and thus cannot be studied using differential gel electrophoresis (DIGE). CoFGE corrects for gel-to-gel variability by co-running with the sample proteome a standardized marker grid of 80-100 nodes, which is formed by a set of purified proteins. Differentiation of reference and analyte is possible by the use of two fluorescent dyes. Variations in the y-dimension (molecular weight) are corrected by the marker grid. For the optional control of the x-dimension (pI), azo dyes can be used. Experiments are possible in both vertical and horizontal (h) electrophoresis devices, but hCoFGE is much easier to perform. For data analysis, commercial software capable of warping can be adapted.

  20. Two-dimensional hexagonal semiconductors beyond graphene

    Science.gov (United States)

    Nguyen, Bich Ha; Hieu Nguyen, Van

    2016-12-01

    The rapid and successful development of the research on graphene and graphene-based nanostructures has been substantially enlarged to include many other two-dimensional hexagonal semiconductors (THS): phosphorene, silicene, germanene, hexagonal boron nitride (h-BN) and transition metal dichalcogenides (TMDCs) such as MoS2, MoSe2, WS2, WSe2 as well as the van der Waals heterostructures of various THSs (including graphene). The present article is a review of recent works on THSs beyond graphene and van der Waals heterostructures composed of different pairs of all THSs. One among the priorities of new THSs compared to graphene is the presence of a non-vanishing energy bandgap which opened up the ability to fabricate a large number of electronic, optoelectronic and photonic devices on the basis of these new materials and their van der Waals heterostructures. Moreover, a significant progress in the research on TMDCs was the discovery of valley degree of freedom. The results of research on valley degree of freedom and the development of a new technology based on valley degree of freedom-valleytronics are also presented. Thus the scientific contents of the basic research and practical applications os THSs are very rich and extremely promising.