Energy Efficient GNSS Signal Acquisition Using Singular Value Decomposition (SVD).

PubMed

Bermúdez Ordoñez, Juan Carlos; Arnaldo Valdés, Rosa María; Gómez Comendador, Fernando

2018-05-16

A significant challenge in global navigation satellite system (GNSS) signal processing is a requirement for a very high sampling rate. The recently-emerging compressed sensing (CS) theory makes processing GNSS signals at a low sampling rate possible if the signal has a sparse representation in a certain space. Based on CS and SVD theories, an algorithm for sampling GNSS signals at a rate much lower than the Nyquist rate and reconstructing the compressed signal is proposed in this research, which is validated after the output from that process still performs signal detection using the standard fast Fourier transform (FFT) parallel frequency space search acquisition. The sparse representation of the GNSS signal is the most important precondition for CS, by constructing a rectangular Toeplitz matrix (TZ) of the transmitted signal, calculating the left singular vectors using SVD from the TZ, to achieve sparse signal representation. Next, obtaining the M-dimensional observation vectors based on the left singular vectors of the SVD, which are equivalent to the sampler operator in standard compressive sensing theory, the signal can be sampled below the Nyquist rate, and can still be reconstructed via ℓ 1 minimization with accuracy using convex optimization. As an added value, there is a GNSS signal acquisition enhancement effect by retaining the useful signal and filtering out noise by projecting the signal into the most significant proper orthogonal modes (PODs) which are the optimal distributions of signal power. The algorithm is validated with real recorded signals, and the results show that the proposed method is effective for sampling, reconstructing intermediate frequency (IF) GNSS signals in the time discrete domain.

Energy Efficient GNSS Signal Acquisition Using Singular Value Decomposition (SVD)

PubMed Central

Arnaldo Valdés, Rosa María; Gómez Comendador, Fernando

2018-01-01

A significant challenge in global navigation satellite system (GNSS) signal processing is a requirement for a very high sampling rate. The recently-emerging compressed sensing (CS) theory makes processing GNSS signals at a low sampling rate possible if the signal has a sparse representation in a certain space. Based on CS and SVD theories, an algorithm for sampling GNSS signals at a rate much lower than the Nyquist rate and reconstructing the compressed signal is proposed in this research, which is validated after the output from that process still performs signal detection using the standard fast Fourier transform (FFT) parallel frequency space search acquisition. The sparse representation of the GNSS signal is the most important precondition for CS, by constructing a rectangular Toeplitz matrix (TZ) of the transmitted signal, calculating the left singular vectors using SVD from the TZ, to achieve sparse signal representation. Next, obtaining the M-dimensional observation vectors based on the left singular vectors of the SVD, which are equivalent to the sampler operator in standard compressive sensing theory, the signal can be sampled below the Nyquist rate, and can still be reconstructed via ℓ1 minimization with accuracy using convex optimization. As an added value, there is a GNSS signal acquisition enhancement effect by retaining the useful signal and filtering out noise by projecting the signal into the most significant proper orthogonal modes (PODs) which are the optimal distributions of signal power. The algorithm is validated with real recorded signals, and the results show that the proposed method is effective for sampling, reconstructing intermediate frequency (IF) GNSS signals in the time discrete domain. PMID:29772731

Poincaré gauge gravity: An emergent scenario

NASA Astrophysics Data System (ADS)

Chkareuli, J. L.

2017-04-01

The Poincaré gauge gravity (PGG) with the underlying vector fields of tetrads and spin-connections is perhaps the best theory candidate for gravitation to be unified with the other three elementary forces of nature. There is a clear analogy between the local frame in PGG and the local internal symmetry space in the Standard Model. As a result, the spin-connection fields, gauging the local frame Lorentz symmetry group S O (1 ,3 )LF , appear in PGG much as photons and gluons appear in SM. We propose that such an analogy may follow from their common emergent nature allowing us to derive PGG in the same way as conventional gauge theories. In essence, we start with an arbitrary theory of some vector and fermion fields which possesses only global spacetime symmetries, such as Lorentz and translational invariance, in flat Minkowski space. The two vector field multiplets involved are proposed to belong, respectively, to the adjoint (Aμi j) and vector (eμi) representations of the starting global Lorentz symmetry. We show that if these prototype vector fields are covariantly constrained, Aμi jAij μ=±MA2 and eμieiμ=±Me2 , thus causing a spontaneous violation of the accompanying global symmetries (MA ,e are their proposed violation scales), then the only possible theory compatible with these length-preserving constraints is turned out to be the gauge invariant PGG, while the corresponding massless (pseudo)Goldstone modes are naturally collected in the emergent gauge fields of tetrads and spin-connections. In a minimal theory case being linear in a curvature we unavoidably come to the Einstein-Cartan theory. The extended theories with propagating spin-connection and tetrad modes are also considered and their possible unification with the Standard Model is briefly discussed.

System and method for extracting dominant orientations from a scene

DOEpatents

Straub, Julian; Rosman, Guy; Freifeld, Oren; Leonard, John J.; Fisher, III; , John W.

2017-05-30

In one embodiment, a method of identifying the dominant orientations of a scene comprises representing a scene as a plurality of directional vectors. The scene may comprise a three-dimensional representation of a scene, and the plurality of directional vectors may comprise a plurality of surface normals. The method further comprises determining, based on the plurality of directional vectors, a plurality of orientations describing the scene. The determined plurality of orientations explains the directionality of the plurality of directional vectors. In certain embodiments, the plurality of orientations may have independent axes of rotation. The plurality of orientations may be determined by representing the plurality of directional vectors as lying on a mathematical representation of a sphere, and inferring the parameters of a statistical model to adapt the plurality of orientations to explain the positioning of the plurality of directional vectors lying on the mathematical representation of the sphere.

A new compact representation of morphological profiles: report on first massive VHR image processing at the JRC

NASA Astrophysics Data System (ADS)

Pesaresi, Martino; Ouzounis, Georgios K.; Gueguen, Lionel

2012-06-01

A new compact representation of dierential morphological prole (DMP) vector elds is presented. It is referred to as the CSL model and is conceived to radically reduce the dimensionality of the DMP descriptors. The model maps three characteristic parameters, namely scale, saliency and level, into the RGB space through a HSV transform. The result is a a medium abstraction semantic layer used for visual exploration, image information mining and pattern classication. Fused with the PANTEX built-up presence index, the CSL model converges to an approximate building footprint representation layer in which color represents building class labels. This process is demonstrated on the rst high resolution (HR) global human settlement layer (GHSL) computed from multi-modal HR and VHR satellite images. Results of the rst massive processing exercise involving several thousands of scenes around the globe are reported along with validation gures.

An Analysis of Different Representations for Vectors and Planes in R[superscript 3]: Learning Challenges

ERIC Educational Resources Information Center

Sandoval, Ivonne; Possani, Edgar

2016-01-01

The purpose of this paper is to present an analysis of the difficulties faced by students when working with different representations of vectors, planes and their intersections in R[superscript 3]. Duval's theoretical framework on semiotic representations is used to design a set of evaluating activities, and later to analyze student work. The…

A Query Expansion Framework in Image Retrieval Domain Based on Local and Global Analysis

PubMed Central

Rahman, M. M.; Antani, S. K.; Thoma, G. R.

2011-01-01

We present an image retrieval framework based on automatic query expansion in a concept feature space by generalizing the vector space model of information retrieval. In this framework, images are represented by vectors of weighted concepts similar to the keyword-based representation used in text retrieval. To generate the concept vocabularies, a statistical model is built by utilizing Support Vector Machine (SVM)-based classification techniques. The images are represented as “bag of concepts” that comprise perceptually and/or semantically distinguishable color and texture patches from local image regions in a multi-dimensional feature space. To explore the correlation between the concepts and overcome the assumption of feature independence in this model, we propose query expansion techniques in the image domain from a new perspective based on both local and global analysis. For the local analysis, the correlations between the concepts based on the co-occurrence pattern, and the metrical constraints based on the neighborhood proximity between the concepts in encoded images, are analyzed by considering local feedback information. We also analyze the concept similarities in the collection as a whole in the form of a similarity thesaurus and propose an efficient query expansion based on the global analysis. The experimental results on a photographic collection of natural scenes and a biomedical database of different imaging modalities demonstrate the effectiveness of the proposed framework in terms of precision and recall. PMID:21822350

Arrows as anchors: An analysis of the material features of electric field vector arrows

NASA Astrophysics Data System (ADS)

Gire, Elizabeth; Price, Edward

2014-12-01

Representations in physics possess both physical and conceptual aspects that are fundamentally intertwined and can interact to support or hinder sense making and computation. We use distributed cognition and the theory of conceptual blending with material anchors to interpret the roles of conceptual and material features of representations in students' use of representations for computation. We focus on the vector-arrows representation of electric fields and describe this representation as a conceptual blend of electric field concepts, physical space, and the material features of the representation (i.e., the physical writing and the surface upon which it is drawn). In this representation, spatial extent (e.g., distance on paper) is used to represent both distances in coordinate space and magnitudes of electric field vectors. In conceptual blending theory, this conflation is described as a clash between the input spaces in the blend. We explore the benefits and drawbacks of this clash, as well as other features of this representation. This analysis is illustrated with examples from clinical problem-solving interviews with upper-division physics majors. We see that while these intermediate physics students make a variety of errors using this representation, they also use the geometric features of the representation to add electric field contributions and to organize the problem situation productively.

Representation and display of vector field topology in fluid flow data sets

NASA Technical Reports Server (NTRS)

Helman, James; Hesselink, Lambertus

1989-01-01

The visualization of physical processes in general and of vector fields in particular is discussed. An approach to visualizing flow topology that is based on the physics and mathematics underlying the physical phenomenon is presented. It involves determining critical points in the flow where the velocity vector vanishes. The critical points, connected by principal lines or planes, determine the topology of the flow. The complexity of the data is reduced without sacrificing the quantitative nature of the data set. By reducing the original vector field to a set of critical points and their connections, a representation of the topology of a two-dimensional vector field that is much smaller than the original data set but retains with full precision the information pertinent to the flow topology is obtained. This representation can be displayed as a set of points and tangent curves or as a graph. Analysis (including algorithms), display, interaction, and implementation aspects are discussed.

Visualization of Morse connection graphs for topologically rich 2D vector fields.

PubMed

Szymczak, Andrzej; Sipeki, Levente

2013-12-01

Recent advances in vector field topologymake it possible to compute its multi-scale graph representations for autonomous 2D vector fields in a robust and efficient manner. One of these representations is a Morse Connection Graph (MCG), a directed graph whose nodes correspond to Morse sets, generalizing stationary points and periodic trajectories, and arcs - to trajectories connecting them. While being useful for simple vector fields, the MCG can be hard to comprehend for topologically rich vector fields, containing a large number of features. This paper describes a visual representation of the MCG, inspired by previous work on graph visualization. Our approach aims to preserve the spatial relationships between the MCG arcs and nodes and highlight the coherent behavior of connecting trajectories. Using simulations of ocean flow, we show that it can provide useful information on the flow structure. This paper focuses specifically on MCGs computed for piecewise constant (PC) vector fields. In particular, we describe extensions of the PC framework that make it more flexible and better suited for analysis of data on complex shaped domains with a boundary. We also describe a topology simplification scheme that makes our MCG visualizations less ambiguous. Despite the focus on the PC framework, our approach could also be applied to graph representations or topological skeletons computed using different methods.

Verifying the equivalence of representations of the knee joint moment vector from a drop vertical jump task.

PubMed

Nichols, Julia K; O'Reilly, Oliver M

2017-03-01

Biomechanics software programs, such as Visual3D, Nexus, Cortex, and OpenSim, have the capability of generating several distinct component representations for joint moments and forces from motion capture data. These representations include those for orthonormal proximal and distal coordinate systems and a non-orthogonal joint coordinate system. In this article, a method is presented to address the challenging problem of evaluating and verifying the equivalence of these representations. The method accommodates the difficulty that there are two possible sets of non-orthogonal basis vectors that can be used to express a vector in the joint coordinate system and is illuminated using motion capture data from a drop vertical jump task. Copyright © 2016 Elsevier B.V. All rights reserved.

Associative memory - An optimum binary neuron representation

NASA Technical Reports Server (NTRS)

Awwal, A. A.; Karim, M. A.; Liu, H. K.

1989-01-01

Convergence mechanism of vectors in the Hopfield's neural network is studied in terms of both weights (i.e., inner products) and Hamming distance. It is shown that Hamming distance should not always be used in determining the convergence of vectors. Instead, weights (which in turn depend on the neuron representation) are found to play a more dominant role in the convergence mechanism. Consequently, a new binary neuron representation for associative memory is proposed. With the new neuron representation, the associative memory responds unambiguously to the partial input in retrieving the stored information.

Vector-based navigation using grid-like representations in artificial agents.

PubMed

Banino, Andrea; Barry, Caswell; Uria, Benigno; Blundell, Charles; Lillicrap, Timothy; Mirowski, Piotr; Pritzel, Alexander; Chadwick, Martin J; Degris, Thomas; Modayil, Joseph; Wayne, Greg; Soyer, Hubert; Viola, Fabio; Zhang, Brian; Goroshin, Ross; Rabinowitz, Neil; Pascanu, Razvan; Beattie, Charlie; Petersen, Stig; Sadik, Amir; Gaffney, Stephen; King, Helen; Kavukcuoglu, Koray; Hassabis, Demis; Hadsell, Raia; Kumaran, Dharshan

2018-05-01

Deep neural networks have achieved impressive successes in fields ranging from object recognition to complex games such as Go 1,2 . Navigation, however, remains a substantial challenge for artificial agents, with deep neural networks trained by reinforcement learning 3-5 failing to rival the proficiency of mammalian spatial behaviour, which is underpinned by grid cells in the entorhinal cortex 6 . Grid cells are thought to provide a multi-scale periodic representation that functions as a metric for coding space 7,8 and is critical for integrating self-motion (path integration) 6,7,9 and planning direct trajectories to goals (vector-based navigation) 7,10,11 . Here we set out to leverage the computational functions of grid cells to develop a deep reinforcement learning agent with mammal-like navigational abilities. We first trained a recurrent network to perform path integration, leading to the emergence of representations resembling grid cells, as well as other entorhinal cell types 12 . We then showed that this representation provided an effective basis for an agent to locate goals in challenging, unfamiliar, and changeable environments-optimizing the primary objective of navigation through deep reinforcement learning. The performance of agents endowed with grid-like representations surpassed that of an expert human and comparison agents, with the metric quantities necessary for vector-based navigation derived from grid-like units within the network. Furthermore, grid-like representations enabled agents to conduct shortcut behaviours reminiscent of those performed by mammals. Our findings show that emergent grid-like representations furnish agents with a Euclidean spatial metric and associated vector operations, providing a foundation for proficient navigation. As such, our results support neuroscientific theories that see grid cells as critical for vector-based navigation 7,10,11 , demonstrating that the latter can be combined with path-based strategies to support navigation in challenging environments.

Representation of magnetic fields in space

NASA Technical Reports Server (NTRS)

Stern, D. P.

1975-01-01

Several methods by which a magnetic field in space can be represented are reviewed with particular attention to problems of the observed geomagnetic field. Time dependence is assumed to be negligible, and five main classes of representation are described by vector potential, scalar potential, orthogonal vectors, Euler potentials, and expanded magnetic field.

Unification with vector-like fermions and signals at LHC

NASA Astrophysics Data System (ADS)

Bhattacherjee, Biplob; Byakti, Pritibhajan; Kushwaha, Ashwani; Vempati, Sudhir K.

2018-05-01

We look for minimal extensions of Standard Model with vector like fermions leading to precision unification of gauge couplings. Constraints from proton decay, Higgs stability and perturbativity are considered. The simplest models contain several copies of vector fermions in two different (incomplete) representations. Some of these models encompass Type III seesaw mechanism for neutrino masses whereas some others have a dark matter candidate. In all the models, at least one of the candidates has non-trivial representation under SU(3)color. In the limit of vanishing Yukawa couplings, new QCD bound states are formed, which can be probed at LHC. The present limits based on results from 13 TeV already probe these particles for masses around a TeV. Similar models can be constructed with three or four vector representations, examples of which are presented.

Amino acid "little Big Bang": representing amino acid substitution matrices as dot products of Euclidian vectors.

PubMed

Zimmermann, Karel; Gibrat, Jean-François

2010-01-04

Sequence comparisons make use of a one-letter representation for amino acids, the necessary quantitative information being supplied by the substitution matrices. This paper deals with the problem of finding a representation that provides a comprehensive description of amino acid intrinsic properties consistent with the substitution matrices. We present a Euclidian vector representation of the amino acids, obtained by the singular value decomposition of the substitution matrices. The substitution matrix entries correspond to the dot product of amino acid vectors. We apply this vector encoding to the study of the relative importance of various amino acid physicochemical properties upon the substitution matrices. We also characterize and compare the PAM and BLOSUM series substitution matrices. This vector encoding introduces a Euclidian metric in the amino acid space, consistent with substitution matrices. Such a numerical description of the amino acid is useful when intrinsic properties of amino acids are necessary, for instance, building sequence profiles or finding consensus sequences, using machine learning algorithms such as Support Vector Machine and Neural Networks algorithms.

Synthesis and Characterization of Thin Films.

DTIC Science & Technology

1987-07-10

impossible in a cubic cell to have a (111) and a (020) plane only about 100 apart as is observed. Similarly, the (220) and (002) reflections cannot both lie...Representations of Polarized Light 3 1.1.1. The ellipse of polarizations 4 1.1.2. The Stokes vector and Poincare sphere 5 1.1.3. The Jones vector 7 1.2...polarized light. Three representations of polarization will be discussed: the ellipse of polarizations, the Stokes vector (and Poincare sphere), and

Communication systems, transceivers, and methods for generating data based on channel characteristics

DOEpatents

Forman, Michael A; Young, Derek

2012-09-18

Examples of methods for generating data based on a communications channel are described. In one such example, a processing unit may generate a first vector representation based in part on at least two characteristics of a communications channel. A constellation having at least two dimensions may be addressed with the first vector representation to identify a first symbol associated with the first vector representation. The constellation represents a plurality of regions, each region associated with a respective symbol. The symbol may be used to generate data, which may stored in an electronic storage medium and used as a cryptographic key or a spreading code or hopping sequence in a modulation technique.

Data Representations for Geographic Information Systems.

ERIC Educational Resources Information Center

Shaffer, Clifford A.

1992-01-01

Surveys the field and literature of geographic information systems (GIS) and spatial data representation as it relates to GIS. Highlights include GIS terms, data types, and operations; vector representations and raster, or grid, representations; spatial indexing; elevation data representations; large spatial databases; and problem areas and future…

Kac determinant and singular vector of the level N representation of Ding-Iohara-Miki algebra

NASA Astrophysics Data System (ADS)

Ohkubo, Yusuke

2018-05-01

In this paper, we obtain the formula for the Kac determinant of the algebra arising from the level N representation of the Ding-Iohara-Miki algebra. It is also discovered that its singular vectors correspond to generalized Macdonald functions (the q-deformed version of the AFLT basis).

Face aging effect simulation model based on multilayer representation and shearlet transform

NASA Astrophysics Data System (ADS)

Li, Yuancheng; Li, Yan

2017-09-01

In order to extract detailed facial features, we build a face aging effect simulation model based on multilayer representation and shearlet transform. The face is divided into three layers: the global layer of the face, the local features layer, and texture layer, which separately establishes the aging model. First, the training samples are classified according to different age groups, and we use active appearance model (AAM) at the global level to obtain facial features. The regression equations of shape and texture with age are obtained by fitting the support vector machine regression, which is based on the radial basis function. We use AAM to simulate the aging of facial organs. Then, for the texture detail layer, we acquire the significant high-frequency characteristic components of the face by using the multiscale shearlet transform. Finally, we get the last simulated aging images of the human face by the fusion algorithm. Experiments are carried out on the FG-NET dataset, and the experimental results show that the simulated face images have less differences from the original image and have a good face aging simulation effect.

Symmetry-preserving contact interaction model for heavy-light mesons

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

Serna, F. E.; Brito, M. A.; Krein, G.

2016-01-22

We use a symmetry-preserving regularization method of ultraviolet divergences in a vector-vector contact interaction model for low-energy QCD. The contact interaction is a representation of nonperturbative kernels used Dyson-Schwinger and Bethe-Salpeter equations. The regularization method is based on a subtraction scheme that avoids standard steps in the evaluation of divergent integrals that invariably lead to symmetry violation. Aiming at the study of heavy-light mesons, we have implemented the method to the pseudoscalar π and K mesons. We have solved the Dyson-Schwinger equation for the u, d and s quark propagators, and obtained the bound-state Bethe-Salpeter amplitudes in a way thatmore » the Ward-Green-Takahashi identities reflecting global symmetries of the model are satisfied for arbitrary routing of the momenta running in loop integrals.« less

Shoelace Formula: Connecting the Area of a Polygon and the Vector Cross Product

ERIC Educational Resources Information Center

Lee, Younhee; Lim, Woong

2017-01-01

Understanding how one representation connects to another and how the essential ideas in that relationship are generalized can result in a mathematical theorem or a formula. In this article, the authors demonstrate this process by connecting a vector cross product in algebraic form to a geometric representation and applying a key mathematical idea…

Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods.

PubMed

Qu, Kaiyang; Han, Ke; Wu, Song; Wang, Guohua; Wei, Leyi

2017-09-22

DNA-binding proteins play vital roles in cellular processes, such as DNA packaging, replication, transcription, regulation, and other DNA-associated activities. The current main prediction method is based on machine learning, and its accuracy mainly depends on the features extraction method. Therefore, using an efficient feature representation method is important to enhance the classification accuracy. However, existing feature representation methods cannot efficiently distinguish DNA-binding proteins from non-DNA-binding proteins. In this paper, a multi-feature representation method, which combines three feature representation methods, namely, K-Skip-N-Grams, Information theory, and Sequential and structural features (SSF), is used to represent the protein sequences and improve feature representation ability. In addition, the classifier is a support vector machine. The mixed-feature representation method is evaluated using 10-fold cross-validation and a test set. Feature vectors, which are obtained from a combination of three feature extractions, show the best performance in 10-fold cross-validation both under non-dimensional reduction and dimensional reduction by max-relevance-max-distance. Moreover, the reduced mixed feature method performs better than the non-reduced mixed feature technique. The feature vectors, which are a combination of SSF and K-Skip-N-Grams, show the best performance in the test set. Among these methods, mixed features exhibit superiority over the single features.

Split Octonion Reformulation for Electromagnetic Chiral Media of Massive Dyons

NASA Astrophysics Data System (ADS)

Chanyal, B. C.

2017-12-01

In an explicit, unified, and covariant formulation of an octonion algebra, we study and generalize the electromagnetic chiral fields equations of massive dyons with the split octonionic representation. Starting with 2×2 Zorn’s vector matrix realization of split-octonion and its dual Euclidean spaces, we represent the unified structure of split octonionic electric and magnetic induction vectors for chiral media. As such, in present paper, we describe the chiral parameter and pairing constants in terms of split octonionic matrix representation of Drude-Born-Fedorov constitutive relations. We have expressed a split octonionic electromagnetic field vector for chiral media, which exhibits the unified field structure of electric and magnetic chiral fields of dyons. The beauty of split octonionic representation of Zorn vector matrix realization is that, the every scalar and vector components have its own meaning in the generalized chiral electromagnetism of dyons. Correspondingly, we obtained the alternative form of generalized Proca-Maxwell’s equations of massive dyons in chiral media. Furthermore, the continuity equations, Poynting theorem and wave propagation for generalized electromagnetic fields of chiral media of massive dyons are established by split octonionic form of Zorn vector matrix algebra.

Instruction-Based Clinical Eye-Tracking Study on the Visual Interpretation of Divergence: How Do Students Look at Vector Field Plots?

ERIC Educational Resources Information Center

Klein, P.; Viiri, J.; Mozaffari, S.; Dengel, A.; Kuhn, J.

2018-01-01

Relating mathematical concepts to graphical representations is a challenging task for students. In this paper, we introduce two visual strategies to qualitatively interpret the divergence of graphical vector field representations. One strategy is based on the graphical interpretation of partial derivatives, while the other is based on the flux…

Qualitative investigation into students' use of divergence and curl in electromagnetism

NASA Astrophysics Data System (ADS)

Bollen, Laurens; van Kampen, Paul; Baily, Charles; De Cock, Mieke

2016-12-01

Many students struggle with the use of mathematics in physics courses. Although typically well trained in rote mathematical calculation, they often lack the ability to apply their acquired skills to physical contexts. Such student difficulties are particularly apparent in undergraduate electrodynamics, which relies heavily on the use of vector calculus. To gain insight into student reasoning when solving problems involving divergence and curl, we conducted eight semistructured individual student interviews. During these interviews, students discussed the divergence and curl of electromagnetic fields using graphical representations, mathematical calculations, and the differential form of Maxwell's equations. We observed that while many students attempt to clarify the problem by making a sketch of the electromagnetic field, they struggle to interpret graphical representations of vector fields in terms of divergence and curl. In addition, some students confuse the characteristics of field line diagrams and field vector plots. By interpreting our results within the conceptual blending framework, we show how a lack of conceptual understanding of the vector operators and difficulties with graphical representations can account for an improper understanding of Maxwell's equations in differential form. Consequently, specific learning materials based on a multiple representation approach are required to clarify Maxwell's equations.

A simple procedure for construction of the orthonormal basis vectors of irreducible representations of O(5) in the OT (3) ⊗ON (2) basis

NASA Astrophysics Data System (ADS)

Pan, Feng; Ding, Xiaoxue; Launey, Kristina D.; Draayer, J. P.

2018-06-01

A simple and effective algebraic isospin projection procedure for constructing orthonormal basis vectors of irreducible representations of O (5) ⊃OT (3) ⊗ON (2) from those in the canonical O (5) ⊃ SUΛ (2) ⊗ SUI (2) basis is outlined. The expansion coefficients are components of null space vectors of the projection matrix with four nonzero elements in each row in general. Explicit formulae for evaluating OT (3)-reduced matrix elements of O (5) generators are derived.

A new image representation for compact and secure communication

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

Prasad, Lakshman; Skourikhine, A. N.

In many areas of nuclear materials management there is a need for communication, archival, and retrieval of annotated image data between heterogeneous platforms and devices to effectively implement safety, security, and safeguards of nuclear materials. Current image formats such as JPEG are not ideally suited in such scenarios as they are not scalable to different viewing formats, and do not provide a high-level representation of images that facilitate automatic object/change detection or annotation. The new Scalable Vector Graphics (SVG) open standard for representing graphical information, recommended by the World Wide Web Consortium (W3C) is designed to address issues of imagemore » scalability, portability, and annotation. However, until now there has been no viable technology to efficiently field images of high visual quality under this standard. Recently, LANL has developed a vectorized image representation that is compatible with the SVG standard and preserves visual quality. This is based on a new geometric framework for characterizing complex features in real-world imagery that incorporates perceptual principles of processing visual information known from cognitive psychology and vision science, to obtain a polygonal image representation of high fidelity. This representation can take advantage of all textual compression and encryption routines unavailable to other image formats. Moreover, this vectorized image representation can be exploited to facilitate automated object recognition that can reduce time required for data review. The objects/features of interest in these vectorized images can be annotated via animated graphics to facilitate quick and easy display and comprehension of processed image content.« less

Imer-product array processor for retrieval of stored images represented by bipolar binary (+1,-1) pixels using partial input trinary pixels represented by (+1,-1)

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang (Inventor); Awwal, Abdul A. S. (Inventor); Karim, Mohammad A. (Inventor)

1993-01-01

An inner-product array processor is provided with thresholding of the inner product during each iteration to make more significant the inner product employed in estimating a vector to be used as the input vector for the next iteration. While stored vectors and estimated vectors are represented in bipolar binary (1,-1), only those elements of an initial partial input vector that are believed to be common with those of a stored vector are represented in bipolar binary; the remaining elements of a partial input vector are set to 0. This mode of representation, in which the known elements of a partial input vector are in bipolar binary form and the remaining elements are set equal to 0, is referred to as trinary representation. The initial inner products corresponding to the partial input vector will then be equal to the number of known elements. Inner-product thresholding is applied to accelerate convergence and to avoid convergence to a negative input product.

On the n-symplectic structure of faithful irreducible representations

NASA Astrophysics Data System (ADS)

Norris, L. K.

2017-04-01

Each faithful irreducible representation of an N-dimensional vector space V1 on an n-dimensional vector space V2 is shown to define a unique irreducible n-symplectic structure on the product manifold V1×V2 . The basic details of the associated Poisson algebra are developed for the special case N = n2, and 2n-dimensional symplectic submanifolds are shown to exist.

The semantic representation of prejudice and stereotypes.

PubMed

Bhatia, Sudeep

2017-07-01

We use a theory of semantic representation to study prejudice and stereotyping. Particularly, we consider large datasets of newspaper articles published in the United States, and apply latent semantic analysis (LSA), a prominent model of human semantic memory, to these datasets to learn representations for common male and female, White, African American, and Latino names. LSA performs a singular value decomposition on word distribution statistics in order to recover word vector representations, and we find that our recovered representations display the types of biases observed in human participants using tasks such as the implicit association test. Importantly, these biases are strongest for vector representations with moderate dimensionality, and weaken or disappear for representations with very high or very low dimensionality. Moderate dimensional LSA models are also the best at learning race, ethnicity, and gender-based categories, suggesting that social category knowledge, acquired through dimensionality reduction on word distribution statistics, can facilitate prejudiced and stereotyped associations. Copyright © 2017 Elsevier B.V. All rights reserved.

Effective data compaction algorithm for vector scan EB writing system

NASA Astrophysics Data System (ADS)

Ueki, Shinichi; Ashida, Isao; Kawahira, Hiroichi

2001-01-01

We have developed a new mask data compaction algorithm dedicated to vector scan electron beam (EB) writing systems for 0.13 μm device generation. Large mask data size has become a significant problem at mask data processing for which data compaction is an important technique. In our new mask data compaction, 'array' representation and 'cell' representation are used. The mask data format for the EB writing system with vector scan supports these representations. The array representation has a pitch and a number of repetitions in both X and Y direction. The cell representation has a definition of figure group and its reference. The new data compaction method has the following three steps. (1) Search arrays of figures by selecting pitches of array so that a number of figures are included. (2) Find out same arrays that have same repetitive pitch and number of figures. (3) Search cells of figures, where the figures in each cell take identical positional relationship. By this new method for the mask data of a 4M-DRAM block gate layer with peripheral circuits, 202 Mbytes without compaction was highly compacted to 6.7 Mbytes in 20 minutes on a 500 MHz PC.

Maplike representation of celestial E-vector orientations in the brain of an insect.

PubMed

Heinze, Stanley; Homberg, Uwe

2007-02-16

For many insects, the polarization pattern of the blue sky serves as a compass cue for spatial navigation. E-vector orientations are detected by photoreceptors in a dorsal rim area of the eye. Polarized-light signals from both eyes are finally integrated in the central complex, a brain area consisting of two subunits, the protocerebral bridge and the central body. Here we show that a topographic representation of zenithal E-vector orientations underlies the columnar organization of the protocerebral bridge in a locust. The maplike arrangement is highly suited to signal head orientation under the open sky.

Virtual world reconstruction using the modeling and simulation extended vector product prototype

DOT National Transportation Integrated Search

1997-05-30

The MS Extended Vector Product (MSEVP) prototype being developed is an extended vector product format-based product containing a continuous surface representation and a consistent view of elevation across the thematic coverages contained within a dat...

Interaction of non-Abelian tensor gauge fields

NASA Astrophysics Data System (ADS)

Savvidy, George

2018-01-01

The non-Abelian tensor gauge fields take value in extended Poincaré algebra. In order to define the invariant Lagrangian we introduce a vector variable in two alternative ways: through the transversal representation of the extended Poincaré algebra and through the path integral over the auxiliary vector field with the U(1) Abelian action. We demonstrate that this allows to fix the unitary gauge and derive scattering amplitudes in spinor representation.

Elementary Treatment of Some Difficulties in the Construction of Irreducible Representations of the Rotation Group in Terms of Products of the Spin-1/2 Representation.

ERIC Educational Resources Information Center

Daniels, J. M.

1979-01-01

Explains why failure to distinguish clearly between three concepts: a vector, its components, and its representatives, renders understanding of how the representations of the rotation group are constructed from products of the spin-half representation, difficult to comprehend. (Author/GA)

A quasi-current representation for information needs inspired by Two-State Vector Formalism

NASA Astrophysics Data System (ADS)

Wang, Panpan; Hou, Yuexian; Li, Jingfei; Zhang, Yazhou; Song, Dawei; Li, Wenjie

2017-09-01

Recently, a number of quantum theory (QT)-based information retrieval (IR) models have been proposed for modeling session search task that users issue queries continuously in order to describe their evolving information needs (IN). However, the standard formalism of QT cannot provide a complete description for users' current IN in a sense that it does not take the 'future' information into consideration. Therefore, to seek a more proper and complete representation for users' IN, we construct a representation of quasi-current IN inspired by an emerging Two-State Vector Formalism (TSVF). With the enlightenment of the completeness of TSVF, a "two-state vector" derived from the 'future' (the current query) and the 'history' (the previous query) is employed to describe users' quasi-current IN in a more complete way. Extensive experiments are conducted on the session tracks of TREC 2013 & 2014, and show that our model outperforms a series of compared IR models.

A novel representation for apoptosis protein subcellular localization prediction using support vector machine.

PubMed

Zhang, Li; Liao, Bo; Li, Dachao; Zhu, Wen

2009-07-21

Apoptosis, or programmed cell death, plays an important role in development of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful to understand the apoptosis mechanism. In this paper, based on the concept that the position distribution information of amino acids is closely related with the structure and function of proteins, we introduce the concept of distance frequency [Matsuda, S., Vert, J.P., Ueda, N., Toh, H., Akutsu, T., 2005. A novel representation of protein sequences for prediction of subcellular location using support vector machines. Protein Sci. 14, 2804-2813] and propose a novel way to calculate distance frequencies. In order to calculate the local features, each protein sequence is separated into p parts with the same length in our paper. Then we use the novel representation of protein sequences and adopt support vector machine to predict subcellular location. The overall prediction accuracy is significantly improved by jackknife test.

Conceptualizing Vectors in College Geometry: A New Framework for Analysis of Student Approaches and Difficulties

ERIC Educational Resources Information Center

Kwon, Oh Hoon

2012-01-01

This dissertation documents a new way of conceptualizing vectors in college mathematics, especially in geometry. First, I will introduce three problems to show the complexity and subtlety of the construct of vectors with the classical vector representations. These highlight the need for a new framework that: (1) differentiates abstraction from a…

Protein sequence comparison based on K-string dictionary.

PubMed

Yu, Chenglong; He, Rong L; Yau, Stephen S-T

2013-10-25

The current K-string-based protein sequence comparisons require large amounts of computer memory because the dimension of the protein vector representation grows exponentially with K. In this paper, we propose a novel concept, the "K-string dictionary", to solve this high-dimensional problem. It allows us to use a much lower dimensional K-string-based frequency or probability vector to represent a protein, and thus significantly reduce the computer memory requirements for their implementation. Furthermore, based on this new concept, we use Singular Value Decomposition to analyze real protein datasets, and the improved protein vector representation allows us to obtain accurate gene trees. © 2013.

Yangians and Yang-Baxter R-operators for ortho-symplectic superalgebras

NASA Astrophysics Data System (ADS)

Fuksa, J.; Isaev, A. P.; Karakhanyan, D.; Kirschner, R.

2017-04-01

Yang-Baxter relations symmetric with respect to the ortho-symplectic superalgebras are studied. We start with the formulation of graded algebras and the linear superspace carrying the vector (fundamental) representation of the ortho-symplectic supergroup. On this basis we study the analogy of the Yang-Baxter operators considered earlier for the cases of orthogonal and symplectic symmetries: the vector (fundamental) R-matrix, the L-operator defining the Yangian algebra and its first and second order evaluations. We investigate the condition for L (u) in the case of the truncated expansion in inverse powers of u and give examples of Lie algebra representations obeying these conditions. We construct the R-operator intertwining two superspinor representations and study the fusion of L-operators involving the tensor product of such representations.

The DTW-based representation space for seismic pattern classification

NASA Astrophysics Data System (ADS)

Orozco-Alzate, Mauricio; Castro-Cabrera, Paola Alexandra; Bicego, Manuele; Londoño-Bonilla, John Makario

2015-12-01

Distinguishing among the different seismic volcanic patterns is still one of the most important and labor-intensive tasks for volcano monitoring. This task could be lightened and made free from subjective bias by using automatic classification techniques. In this context, a core but often overlooked issue is the choice of an appropriate representation of the data to be classified. Recently, it has been suggested that using a relative representation (i.e. proximities, namely dissimilarities on pairs of objects) instead of an absolute one (i.e. features, namely measurements on single objects) is advantageous to exploit the relational information contained in the dissimilarities to derive highly discriminant vector spaces, where any classifier can be used. According to that motivation, this paper investigates the suitability of a dynamic time warping (DTW) dissimilarity-based vector representation for the classification of seismic patterns. Results show the usefulness of such a representation in the seismic pattern classification scenario, including analyses of potential benefits from recent advances in the dissimilarity-based paradigm such as the proper selection of representation sets and the combination of different dissimilarity representations that might be available for the same data.

Electromagnetic multipole moments of elementary spin-1/2, 1, and 3/2 particles

NASA Astrophysics Data System (ADS)

Delgado-Acosta, E. G.; Kirchbach, M.; Napsuciale, M.; Rodríguez, S.

2012-06-01

We study multipole decompositions of the electromagnetic currents of spin-1/2, 1, and 3/2 particles described in terms of representation-specific wave equations which are second order in the momenta and which emerge within the recently elaborated Poincaré covariant-projector method, where the respective Lagrangians explicitly depend on the Lorentz group generators of the representations of interest. The currents are then the ordinary linear Noether currents related to phase invariance, and present themselves always as two-terms motion-plus spin-magnetization currents. The spin-magnetization currents appear weighted by the gyromagnetic ratio g, a free parameter in the method which we fix either by unitarity of forward Compton scattering amplitudes in the ultraviolet for spin-1 and spin-3/2, or in the spin-1/2 case, by their asymptotic vanishing, thus ending up in all three cases with the universal g value of g=2. Within the method under discussion, we calculate the electric multipoles of the above spins for the spinor, the four-vector, and the four-vector-spinor representations, and find it favorable in some aspects, specifically in comparison with the conventional Proca and Rarita-Schwinger frameworks. We furthermore attend to the most general non-Lagrangian spin-3/2 currents, which are allowed by Lorentz invariance to be up to third order in the momenta and construct the linear-current equivalent of identical multipole moments of one of them. We conclude that nonlinear non-Lagrangian spin-3/2 currents are not necessarily more general and more advantageous than the linear spin-3/2 Lagrangian current emerging within the covariant-projector formalism. Finally, we test the representation dependence of the multipoles by placing spin-1 and spin-3/2 in the respective (1,0)⊕(0,1) and (3/2,0)⊕(0,3/2) single-spin representations. We observe representation independence of the charge monopoles and the magnetic dipoles, in contrast to the higher multipoles, which turn out to be representation-dependent. In particular, we find the bi-vector (1,0)⊕(0,1) to be characterized by an electric quadrupole moment of opposite sign to the one found in (1/2,1/2), and consequently to the W boson. This observation allows us to explain the positive electric quadrupole moment of the ρ meson extracted from recent analyses of the ρ meson electric form factor. Our finding points toward the possibility that the ρ-meson could transform as part of an antisymmetric tensor with an a1 mesonlike state as its representation companion, a possibility consistent with the empirically established ρ and a1 vector meson dominance of the hadronic vector and axial-vector currents.

Vector-Based Ground Surface and Object Representation Using Cameras

DTIC Science & Technology

2009-12-01

representations and it is a digital data structure used for the representation of a ground surface in geographical information systems ( GIS ). Figure...Vision API library, and the OpenCV library. Also, the Posix thread library was utilized to quickly capture the source images from cameras. Both

The problems in quantum foundations in the light of gauge theories

NASA Astrophysics Data System (ADS)

Ne'Eman, Yuval

1986-04-01

We review the issues of nonseparability and seemingly acausal propagation of information in EPR, as displayed by experiments and the failure of Bell's inequalities. We show that global effects are in the very nature of the geometric structure of modern physical theories, occurring even at the classical level. The Aharonov-Bohm effect, magnetic monopoles, instantons, etc. result from the topology and homotopy features of the fiber bundle manifolds of gauge theories. The conservation of probabilities, a supposedly highly quantum effect, is also achieved through global geometry equations. The EPR observables all fit in such geometries, and space-time is a truncated representation and is not the correct arena for their understanding. Relativistic quantum field theory represents the global action of the measurement operators as the zero-momentum (and therefore spatially infinitely spread) limit of their wave functions (form factors). We also analyze the collapse of the state vector as a case of spontaneous symmetry breakdown in the apparatus-observed state interaction.

Student Difficulties Regarding Symbolic and Graphical Representations of Vector Fields

ERIC Educational Resources Information Center

Bollen, Laurens; van Kampen, Paul; Baily, Charles; Kelly, Mossy; De Cock, Mieke

2017-01-01

The ability to switch between various representations is an invaluable problem-solving skill in physics. In addition, research has shown that using multiple representations can greatly enhance a person's understanding of mathematical and physical concepts. This paper describes a study of student difficulties regarding interpreting, constructing,…

The application of vector concepts on two skew lines

NASA Astrophysics Data System (ADS)

Alghadari, F.; Turmudi; Herman, T.

2018-01-01

The purpose of this study is knowing how to apply vector concepts on two skew lines in three-dimensional (3D) coordinate and its utilization. Several mathematical concepts have a related function for the other, but the related between the concept of vector and 3D have not applied in learning classroom. In fact, there are studies show that female students have difficulties in learning of 3D than male. It is because of personal spatial intelligence. The relevance of vector concepts creates both learning achievement and mathematical ability of male and female students enables to be balanced. The distance like on a cube, cuboid, or pyramid whose are drawn on the rectangular coordinates of a point in space. Two coordinate points of the lines can be created a vector. The vector of two skew lines has the shortest distance and the angle. Calculating of the shortest distance is started to create two vectors as a representation of line by vector position concept, next to determining a norm-vector of two vector which was obtained by cross-product, and then to create a vector from two combination of pair-points which was passed by two skew line, the shortest distance is scalar orthogonal projection of norm-vector on a vector which is a combination of pair-points. While calculating the angle are used two vectors as a representation of line to dot-product, and the inverse of cosine is yield. The utilization of its application on mathematics learning and orthographic projection method.

The continuous spin representations of the Poincare and super-Poincare groups and their construction by the Inonu-Wigner group contraction

NASA Astrophysics Data System (ADS)

Khan, Abu M. A. S.

We study the continuous spin representation (CSR) of the Poincare group in arbitrary dimensions. In d dimensions, the CSRs are characterized by the length of the light-cone vector and the Dynkin labels of the SO(d-3) short little group which leaves the light-cone vector invariant. In addition to these, a solid angle Od-3 which specifies the direction of the light-cone vector is also required to label the states. We also find supersymmetric generalizations of the CSRs. In four dimensions, the supermultiplet contains one bosonic and one fermionic CSRs which transform into each other under the action of the supercharges. In a five dimensional case, the supermultiplet contains two bosonic and two fermionic CSRs which is like N = 2 supersymmetry in four dimensions. When constructed using Grassmann parameters, the light-cone vector becomes nilpotent. This makes the representation finite dimensional, but at the expense of introducing central charges even though the representation is massless. This leads to zero or negative norm states. The nilpotent constructions are valid only for even dimensions. We also show how the CSRs in four dimensions can be obtained from five dimensions by the combinations of Kaluza-Klein (KK) dimensional reduction and the Inonu-Wigner group contraction. The group contraction is a singular transformation. We show that the group contraction is equivalent to imposing periodic boundary condition along one direction and taking a double singular limit. In this form the contraction parameter is interpreted as the inverse KK radius. We apply this technique to both five dimensional regular massless and massive representations. For the regular massless case, we find that the contraction gives the CSR in four dimensions under a double singular limit and the representation wavefunction is the Bessel function. For the massive case, we use Majorana's infinite component theory as a model for the SO(4) little group. In this case, a triple singular limit is required to yield any CSR in four dimensions. The representation wavefunction is the Bessel function, as expected, but the scale factor is not the length of the light-cone vector. The amplitude and the scale factor are implicit functions of the parameter y which is a ratio of the internal and external coordinates. We also state under what conditions our solutions become identical to Wigner's solution.

Adding localization information in a fingerprint binary feature vector representation

NASA Astrophysics Data System (ADS)

Bringer, Julien; Despiegel, Vincent; Favre, Mélanie

2011-06-01

At BTAS'10, a new framework to transform a fingerprint minutiae template into a binary feature vector of fixed length is described. A fingerprint is characterized by its similarity with a fixed number set of representative local minutiae vicinities. This approach by representative leads to a fixed length binary representation, and, as the approach is local, it enables to deal with local distortions that may occur between two acquisitions. We extend this construction to incorporate additional information in the binary vector, in particular on localization of the vicinities. We explore the use of position and orientation information. The performance improvement is promising for utilization into fast identification algorithms or into privacy protection algorithms.

Compositional and phase relations among rare earth element minerals

NASA Technical Reports Server (NTRS)

Burt, D. M.

1990-01-01

This paper discusses the compositional and phase relationships among minerals in which rare earth elements (REE) occur as essential constituents (e.g., bastnaesite, monazite, xenotime, aeschynite, allanite). Particular consideration is given to the vector representation of complex coupled substitutions in selected REE-bearing minerals and to the REE partitioning between minerals as related to the acid-base tendencies and mineral stabilities. It is shown that the treatment of coupled substitutions as vector quantities facilitates graphical representation of mineral composition spaces.

Human action recognition with group lasso regularized-support vector machine

NASA Astrophysics Data System (ADS)

Luo, Huiwu; Lu, Huanzhang; Wu, Yabei; Zhao, Fei

2016-05-01

The bag-of-visual-words (BOVW) and Fisher kernel are two popular models in human action recognition, and support vector machine (SVM) is the most commonly used classifier for the two models. We show two kinds of group structures in the feature representation constructed by BOVW and Fisher kernel, respectively, since the structural information of feature representation can be seen as a prior for the classifier and can improve the performance of the classifier, which has been verified in several areas. However, the standard SVM employs L2-norm regularization in its learning procedure, which penalizes each variable individually and cannot express the structural information of feature representation. We replace the L2-norm regularization with group lasso regularization in standard SVM, and a group lasso regularized-support vector machine (GLRSVM) is proposed. Then, we embed the group structural information of feature representation into GLRSVM. Finally, we introduce an algorithm to solve the optimization problem of GLRSVM by alternating directions method of multipliers. The experiments evaluated on KTH, YouTube, and Hollywood2 datasets show that our method achieves promising results and improves the state-of-the-art methods on KTH and YouTube datasets.

Joint Smoothed l₀-Norm DOA Estimation Algorithm for Multiple Measurement Vectors in MIMO Radar.

PubMed

Liu, Jing; Zhou, Weidong; Juwono, Filbert H

2017-05-08

Direction-of-arrival (DOA) estimation is usually confronted with a multiple measurement vector (MMV) case. In this paper, a novel fast sparse DOA estimation algorithm, named the joint smoothed l 0 -norm algorithm, is proposed for multiple measurement vectors in multiple-input multiple-output (MIMO) radar. To eliminate the white or colored Gaussian noises, the new method first obtains a low-complexity high-order cumulants based data matrix. Then, the proposed algorithm designs a joint smoothed function tailored for the MMV case, based on which joint smoothed l 0 -norm sparse representation framework is constructed. Finally, for the MMV-based joint smoothed function, the corresponding gradient-based sparse signal reconstruction is designed, thus the DOA estimation can be achieved. The proposed method is a fast sparse representation algorithm, which can solve the MMV problem and perform well for both white and colored Gaussian noises. The proposed joint algorithm is about two orders of magnitude faster than the l 1 -norm minimization based methods, such as l 1 -SVD (singular value decomposition), RV (real-valued) l 1 -SVD and RV l 1 -SRACV (sparse representation array covariance vectors), and achieves better DOA estimation performance.

Efficient Multiple Kernel Learning Algorithms Using Low-Rank Representation.

PubMed

Niu, Wenjia; Xia, Kewen; Zu, Baokai; Bai, Jianchuan

2017-01-01

Unlike Support Vector Machine (SVM), Multiple Kernel Learning (MKL) allows datasets to be free to choose the useful kernels based on their distribution characteristics rather than a precise one. It has been shown in the literature that MKL holds superior recognition accuracy compared with SVM, however, at the expense of time consuming computations. This creates analytical and computational difficulties in solving MKL algorithms. To overcome this issue, we first develop a novel kernel approximation approach for MKL and then propose an efficient Low-Rank MKL (LR-MKL) algorithm by using the Low-Rank Representation (LRR). It is well-acknowledged that LRR can reduce dimension while retaining the data features under a global low-rank constraint. Furthermore, we redesign the binary-class MKL as the multiclass MKL based on pairwise strategy. Finally, the recognition effect and efficiency of LR-MKL are verified on the datasets Yale, ORL, LSVT, and Digit. Experimental results show that the proposed LR-MKL algorithm is an efficient kernel weights allocation method in MKL and boosts the performance of MKL largely.

The anterior hippocampus supports a coarse, global environmental representation and the posterior hippocampus supports fine-grained, local environmental representations.

PubMed

Evensmoen, Hallvard Røe; Lehn, Hanne; Xu, Jian; Witter, Menno P; Nadel, Lynn; Håberg, Asta K

2013-11-01

Representing an environment globally, in a coarse way, and locally, in a fine-grained way, are two fundamental aspects of how our brain interprets the world that surrounds us. The neural correlates of these representations have not been explicated in humans. In this study we used fMRI to investigate these correlates and to explore a possible functional segregation in the hippocampus and parietal cortex. We hypothesized that processing a coarse, global environmental representation engages anterior parts of these regions, whereas processing fine-grained, local environmental information engages posterior parts. Participants learned a virtual environment and then had to find their way during fMRI. After scanning, we assessed strategies used and representations stored. Activation in the hippocampal head (anterior) was related to the multiple distance and global direction judgments and to the use of a coarse, global environmental representation during navigation. Activation in the hippocampal tail (posterior) was related to both local and global direction judgments and to using strategies like number of turns. A structural shape analysis showed that the use of a coarse, global environmental representation was related to larger right hippocampal head volume and smaller right hippocampal tail volume. In the inferior parietal cortex, a similar functional segregation was observed, with global routes represented anteriorly and fine-grained route information such as number of turns represented posteriorly. In conclusion, moving from the anterior to the posterior hippocampus and inferior parietal cortex reflects a shift from processing coarse global environmental representations to processing fine-grained, local environmental representations.

Fast large-scale object retrieval with binary quantization

NASA Astrophysics Data System (ADS)

Zhou, Shifu; Zeng, Dan; Shen, Wei; Zhang, Zhijiang; Tian, Qi

2015-11-01

The objective of large-scale object retrieval systems is to search for images that contain the target object in an image database. Where state-of-the-art approaches rely on global image representations to conduct searches, we consider many boxes per image as candidates to search locally in a picture. In this paper, a feature quantization algorithm called binary quantization is proposed. In binary quantization, a scale-invariant feature transform (SIFT) feature is quantized into a descriptive and discriminative bit-vector, which allows itself to adapt to the classic inverted file structure for box indexing. The inverted file, which stores the bit-vector and box ID where the SIFT feature is located inside, is compact and can be loaded into the main memory for efficient box indexing. We evaluate our approach on available object retrieval datasets. Experimental results demonstrate that the proposed approach is fast and achieves excellent search quality. Therefore, the proposed approach is an improvement over state-of-the-art approaches for object retrieval.

Attention Effects on Neural Population Representations for Shape and Location Are Stronger in the Ventral than Dorsal Stream

PubMed Central

2018-01-01

Abstract We examined how attention causes neural population representations of shape and location to change in ventral stream (AIT) and dorsal stream (LIP). Monkeys performed two identical delayed-match-to-sample (DMTS) tasks, attending either to shape or location. In AIT, shapes were more discriminable when directing attention to shape rather than location, measured by an increase in mean distance between population response vectors. In LIP, attending to location rather than shape did not increase the discriminability of different stimulus locations. Even when factoring out the change in mean vector response distance, multidimensional scaling (MDS) still showed a significant task difference in AIT, but not LIP, indicating that beyond increasing discriminability, attention also causes a nonlinear warping of representation space in AIT. Despite single-cell attentional modulations in both areas, our data show that attentional modulations of population representations are weaker in LIP, likely due to a need to maintain veridical representations for visuomotor control. PMID:29876521

Vectors in Use in a 3D Juggling Game Simulation

ERIC Educational Resources Information Center

Kynigos, Chronis; Latsi, Maria

2006-01-01

The new representations enabled by the educational computer game the "Juggler" can place vectors in a central role both for controlling and measuring the behaviours of objects in a virtual environment simulating motion in three-dimensional spaces. The mathematical meanings constructed by 13 year-old students in relation to vectors as…

Effects of OCR Errors on Ranking and Feedback Using the Vector Space Model.

ERIC Educational Resources Information Center

Taghva, Kazem; And Others

1996-01-01

Reports on the performance of the vector space model in the presence of OCR (optical character recognition) errors in information retrieval. Highlights include precision and recall, a full-text test collection, smart vector representation, impact of weighting parameters, ranking variability, and the effect of relevance feedback. (Author/LRW)

Fusion of fuzzy statistical distributions for classification of thyroid ultrasound patterns.

PubMed

Iakovidis, Dimitris K; Keramidas, Eystratios G; Maroulis, Dimitris

2010-09-01

This paper proposes a novel approach for thyroid ultrasound pattern representation. Considering that texture and echogenicity are correlated with thyroid malignancy, the proposed approach encodes these sonographic features via a noise-resistant representation. This representation is suitable for the discrimination of nodules of high malignancy risk from normal thyroid parenchyma. The material used in this study includes a total of 250 thyroid ultrasound patterns obtained from 75 patients in Greece. The patterns are represented by fused vectors of fuzzy features. Ultrasound texture is represented by fuzzy local binary patterns, whereas echogenicity is represented by fuzzy intensity histograms. The encoded thyroid ultrasound patterns are discriminated by support vector classifiers. The proposed approach was comprehensively evaluated using receiver operating characteristics (ROCs). The results show that the proposed fusion scheme outperforms previous thyroid ultrasound pattern representation methods proposed in the literature. The best classification accuracy was obtained with a polynomial kernel support vector machine, and reached 97.5% as estimated by the area under the ROC curve. The fusion of fuzzy local binary patterns and fuzzy grey-level histogram features is more effective than the state of the art approaches for the representation of thyroid ultrasound patterns and can be effectively utilized for the detection of nodules of high malignancy risk in the context of an intelligent medical system. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Partition function of free conformal fields in 3-plet representation

NASA Astrophysics Data System (ADS)

Beccaria, Matteo; Tseytlin, Arkady A.

2017-05-01

Simplest examples of AdS/CFT duality correspond to free CFTs in d dimensions with fields in vector or adjoint representation of an internal symmetry group dual in the large N limit to a theory of massless or massless plus massive higher spins in AdS d+1. One may also study generalizations when conformal fields belong to higher dimensional representations, i.e. carry more than two internal symmetry indices. Here we consider the case of the 3-fundamental ("3-plet") representation. One motivation is a conjectured connection to multiple M5-brane theory: heuristic arguments suggest that it may be related to an (interacting) CFT of 6d (2,0) tensor multiplets in 3-plet representation of large N symmetry group that has an AdS7 dual. We compute the singlet partition function Z on S 1 × S d-1 for a free field in 3-plet representation of U( N) and analyse its novel large N behaviour. The large N limit of the low temperature expansion of Z which is convergent in the vector and adjoint cases here is only asymptotic, reflecting the much faster growth of the number of singlet operators with dimension, indicating a phase transition at very low temperature. Indeed, while the critical temperatures in the vector ( T c ˜ N γ , γ > 0) and adjoint ( T c ˜ 1) cases are finite, we find that in the 3-plet case T c ˜ (log N)-1, i.e. it approaches zero at large N. We discuss some details of large N solution for the eigenvalue distribution. Similar conclusions apply to higher p-plet representations of U( N) or O( N) and also to the free p-tensor theories invariant under [U( N)] p or [ O( N)] p with p ≥ 3.

Bootstrapping the O(N) archipelago

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

Kos, Filip; Poland, David; Simmons-Duffin, David

2015-11-17

We study 3d CFTs with an O(N) global symmetry using the conformal bootstrap for a system of mixed correlators. Specifically, we consider all nonvanishing scalar four-point functions containing the lowest dimension O(N) vector Φ i and the lowest dimension O(N) singlet s, assumed to be the only relevant operators in their symmetry representations. The constraints of crossing symmetry and unitarity for these four-point functions force the scaling dimensions (Δ Φ , Δ s ) to lie inside small islands. Here, we also make rigorous determinations of current two-point functions in the O(2) and O(3) models, with applications to transport inmore » condensed matter systems.« less

Current Status and Challenges of Atmospheric Data Assimilation

NASA Astrophysics Data System (ADS)

Atlas, R. M.; Gelaro, R.

2016-12-01

The issues of modern atmospheric data assimilation are fairly simple to comprehend but difficult to address, involving the combination of literally billions of model variables and tens of millions of observations daily. In addition to traditional meteorological variables such as wind, temperature pressure and humidity, model state vectors are being expanded to include explicit representation of precipitation, clouds, aerosols and atmospheric trace gases. At the same time, model resolutions are approaching single-kilometer scales globally and new observation types have error characteristics that are increasingly non-Gaussian. This talk describes the current status and challenges of atmospheric data assimilation, including an overview of current methodologies, the difficulty of estimating error statistics, and progress toward coupled earth system analyses.

Global Transport Networks and Infectious Disease Spread

PubMed Central

Tatem, A.J.; Rogers, D.J.; Hay, S.I.

2011-01-01

Air, sea and land transport networks continue to expand in reach, speed of travel and volume of passengers and goods carried. Pathogens and their vectors can now move further, faster and in greater numbers than ever before. Three important consequences of global transport network expansion are infectious disease pandemics, vector invasion events and vector-borne pathogen importation. This review briefly examines some of the important historical examples of these disease and vector movements, such as the global influenza pandemics, the devastating Anopheles gambiae invasion of Brazil and the recent increases in imported Plasmodium falciparum malaria cases. We then outline potential approaches for future studies of disease movement, focussing on vector invasion and vector-borne disease importation. Such approaches allow us to explore the potential implications of international air travel, shipping routes and other methods of transport on global pathogen and vector traffic. PMID:16647974

Boundary Quantum Knizhnik-Zamolodchikov Equations and Bethe Vectors

NASA Astrophysics Data System (ADS)

Reshetikhin, Nicolai; Stokman, Jasper; Vlaar, Bart

2015-06-01

Solutions to boundary quantum Knizhnik-Zamolodchikov equations are constructed as bilateral sums involving "off-shell" Bethe vectors in case the reflection matrix is diagonal and only the 2-dimensional representation of is involved. We also consider their rational and classical degenerations.

The dynamic representation of gravity is suspended when the idiotropic vector is misaligned with gravity.

PubMed

De Sá Teixeira, Nuno Alexandre; Hecht, Heiko

2014-01-01

When people are asked to indicate the vanishing location of a moving target, errors in the direction of motion (representational momentum) and in the direction of gravity (representational gravity) are usually found. These errors possess a temporal course wherein the memory for the location of the target drifts downwards with increasing temporal intervals between target's disappearance and participant's responses (representational trajectory). To assess if representational trajectory is a body-referenced or a world-referenced phenomenon. A behavioral localization method was employed with retention times between 0 and 1400 ms systematically imposed after the target's disappearance. The target could move horizontally (rightwards or leftwards) or vertically (upwards or downwards). Body posture was varied in a counterbalanced order between sitting upright and lying on the side (left lateral decubitus position). In the upright task, the memory for target location drifted downwards with time in the direction of gravity. This time course did not emerge for the decubitus task, where idiotropic dominance was found. The dynamic visual representation of gravity is neither purely body-referenced nor world-referenced. It seems to be modulated instead by the relationship between the idiotropic vector and physical gravity.

Deep Learning Representation from Electroencephalography of Early-Stage Creutzfeldt-Jakob Disease and Features for Differentiation from Rapidly Progressive Dementia.

PubMed

Morabito, Francesco Carlo; Campolo, Maurizio; Mammone, Nadia; Versaci, Mario; Franceschetti, Silvana; Tagliavini, Fabrizio; Sofia, Vito; Fatuzzo, Daniela; Gambardella, Antonio; Labate, Angelo; Mumoli, Laura; Tripodi, Giovanbattista Gaspare; Gasparini, Sara; Cianci, Vittoria; Sueri, Chiara; Ferlazzo, Edoardo; Aguglia, Umberto

2017-03-01

A novel technique of quantitative EEG for differentiating patients with early-stage Creutzfeldt-Jakob disease (CJD) from other forms of rapidly progressive dementia (RPD) is proposed. The discrimination is based on the extraction of suitable features from the time-frequency representation of the EEG signals through continuous wavelet transform (CWT). An average measure of complexity of the EEG signal obtained by permutation entropy (PE) is also included. The dimensionality of the feature space is reduced through a multilayer processing system based on the recently emerged deep learning (DL) concept. The DL processor includes a stacked auto-encoder, trained by unsupervised learning techniques, and a classifier whose parameters are determined in a supervised way by associating the known category labels to the reduced vector of high-level features generated by the previous processing blocks. The supervised learning step is carried out by using either support vector machines (SVM) or multilayer neural networks (MLP-NN). A subset of EEG from patients suffering from Alzheimer's Disease (AD) and healthy controls (HC) is considered for differentiating CJD patients. When fine-tuning the parameters of the global processing system by a supervised learning procedure, the proposed system is able to achieve an average accuracy of 89%, an average sensitivity of 92%, and an average specificity of 89% in differentiating CJD from RPD. Similar results are obtained for CJD versus AD and CJD versus HC.

A de-identifier for medical discharge summaries.

PubMed

Uzuner, Ozlem; Sibanda, Tawanda C; Luo, Yuan; Szolovits, Peter

2008-01-01

Clinical records contain significant medical information that can be useful to researchers in various disciplines. However, these records also contain personal health information (PHI) whose presence limits the use of the records outside of hospitals. The goal of de-identification is to remove all PHI from clinical records. This is a challenging task because many records contain foreign and misspelled PHI; they also contain PHI that are ambiguous with non-PHI. These complications are compounded by the linguistic characteristics of clinical records. For example, medical discharge summaries, which are studied in this paper, are characterized by fragmented, incomplete utterances and domain-specific language; they cannot be fully processed by tools designed for lay language. In this paper, we show that we can de-identify medical discharge summaries using a de-identifier, Stat De-id, based on support vector machines and local context (F-measure=97% on PHI). Our representation of local context aids de-identification even when PHI include out-of-vocabulary words and even when PHI are ambiguous with non-PHI within the same corpus. Comparison of Stat De-id with a rule-based approach shows that local context contributes more to de-identification than dictionaries combined with hand-tailored heuristics (F-measure=85%). Comparison with two well-known named entity recognition (NER) systems, SNoW (F-measure=94%) and IdentiFinder (F-measure=36%), on five representative corpora show that when the language of documents is fragmented, a system with a relatively thorough representation of local context can be a more effective de-identifier than systems that combine (relatively simpler) local context with global context. Comparison with a Conditional Random Field De-identifier (CRFD), which utilizes global context in addition to the local context of Stat De-id, confirms this finding (F-measure=88%) and establishes that strengthening the representation of local context may be more beneficial for de-identification than complementing local with global context.

A De-identifier for Medical Discharge Summaries1

PubMed Central

Uzuner, Özlem; Sibanda, Tawanda C.; Luo, Yuan; Szolovits, Peter

2008-01-01

Objective Clinical records contain significant medical information that can be useful to researchers in various disciplines. However, these records also contain personal health information (PHI) whose presence limits the use of the records outside of hospitals. The goal of de-identification is to remove all PHI from clinical records. This is a challenging task because many records contain foreign and misspelled PHI; they also contain PHI that are ambiguous with non-PHI. These complications are compounded by the linguistic characteristics of clinical records. For example, medical discharge summaries, which are studied in this paper, are characterized by fragmented, incomplete utterances and domain-specific language; they cannot be fully processed by tools designed for lay language. Methods and Results In this paper, we show that we can de-identify medical discharge summaries using a de-identifier, Stat De-id, based on support vector machines and local context (F-measure = 97% on PHI). Our representation of local context aids de-identification even when PHI include out-of-vocabulary words and even when PHI are ambiguous with non-PHI within the same corpus. Comparison of Stat De-id with a rule-based approach shows that local context contributes more to de-identification than dictionaries combined with hand-tailored heuristics (F-measure = 85%). Comparison with two well-known named entity recognition (NER) systems, SNoW (F-measure = 94%) and IdentiFinder (F-measure = 36%), on five representative corpora show that when the language of documents is fragmented, a system with a relatively thorough representation of local context can be a more effective de-identifier than systems that combine (relatively simpler) local context with global context. Comparison with a Conditional Random Field De-identifier (CRFD), which utilizes global context in addition to the local context of Stat De-id, confirms this finding (F-measure = 88%) and establishes that strengthening the representation of local context may be more beneficial for de-identification than complementing local with global context. PMID:18053696

Instruction-based clinical eye-tracking study on the visual interpretation of divergence: How do students look at vector field plots?

NASA Astrophysics Data System (ADS)

Klein, P.; Viiri, J.; Mozaffari, S.; Dengel, A.; Kuhn, J.

2018-06-01

Relating mathematical concepts to graphical representations is a challenging task for students. In this paper, we introduce two visual strategies to qualitatively interpret the divergence of graphical vector field representations. One strategy is based on the graphical interpretation of partial derivatives, while the other is based on the flux concept. We test the effectiveness of both strategies in an instruction-based eye-tracking study with N =41 physics majors. We found that students' performance improved when both strategies were introduced (74% correct) instead of only one strategy (64% correct), and students performed best when they were free to choose between the two strategies (88% correct). This finding supports the idea of introducing multiple representations of a physical concept to foster student understanding. Relevant eye-tracking measures demonstrate that both strategies imply different visual processing of the vector field plots, therefore reflecting conceptual differences between the strategies. Advanced analysis methods further reveal significant differences in eye movements between the best and worst performing students. For instance, the best students performed predominantly horizontal and vertical saccades, indicating correct interpretation of partial derivatives. They also focused on smaller regions when they balanced positive and negative flux. This mixed-method research leads to new insights into student visual processing of vector field representations, highlights the advantages and limitations of eye-tracking methodologies in this context, and discusses implications for teaching and for future research. The introduction of saccadic direction analysis expands traditional methods, and shows the potential to discover new insights into student understanding and learning difficulties.

Support Vector Machine-Based Endmember Extraction

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

Filippi, Anthony M; Archibald, Richard K

Introduced in this paper is the utilization of Support Vector Machines (SVMs) to automatically perform endmember extraction from hyperspectral data. The strengths of SVM are exploited to provide a fast and accurate calculated representation of high-dimensional data sets that may consist of multiple distributions. Once this representation is computed, the number of distributions can be determined without prior knowledge. For each distribution, an optimal transform can be determined that preserves informational content while reducing the data dimensionality, and hence, the computational cost. Finally, endmember extraction for the whole data set is accomplished. Results indicate that this Support Vector Machine-Based Endmembermore » Extraction (SVM-BEE) algorithm has the capability of autonomously determining endmembers from multiple clusters with computational speed and accuracy, while maintaining a robust tolerance to noise.« less

A roadmap for improving the representation of photosynthesis in Earth System Models

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

Rogers, Alistair; Medlyn, Belinda E.; Dukes, Jeffrey S.

Accurate representation of photosynthesis in terrestrial biosphere models (TBMs) is essential for robust projections of global change. However, current representations vary markedly between TBMs, contributing uncertainty projections of global carbon fluxes.

A roadmap for improving the representation of photosynthesis in Earth System Models

DOE PAGES

Rogers, Alistair; Medlyn, Belinda E.; Dukes, Jeffrey S.; ...

2016-11-28

Accurate representation of photosynthesis in terrestrial biosphere models (TBMs) is essential for robust projections of global change. However, current representations vary markedly between TBMs, contributing uncertainty projections of global carbon fluxes.

An application of the Braunbeck method to the Maggi-Rubinowicz field representation

NASA Technical Reports Server (NTRS)

Meneghini, R.

1982-01-01

The Braunbek method is applied to the generalized vector potential associated with the Maggi-rubinowicz representation. Under certain approximations, an asymptotic evaluation of the vector potential is obtained. For observation points away from caustics or shadow boundaries, the field derived from this quantity is the same as that determined from the geometrical theory of diffraction on a singly diffracted edge ray. An evaluation of the field for the simple case of a plane wave normally incident on a circular aperture is presented showing that the field predicted by the Maggi-Rubinowicz theory is continuous across the shadow boundary.

An application of the Braunbeck method to the Maggi-Rubinowicz field representation

NASA Astrophysics Data System (ADS)

Meneghini, R.

1982-06-01

The Braunbek method is applied to the generalized vector potential associated with the Maggi-rubinowicz representation. Under certain approximations, an asymptotic evaluation of the vector potential is obtained. For observation points away from caustics or shadow boundaries, the field derived from this quantity is the same as that determined from the geometrical theory of diffraction on a singly diffracted edge ray. An evaluation of the field for the simple case of a plane wave normally incident on a circular aperture is presented showing that the field predicted by the Maggi-Rubinowicz theory is continuous across the shadow boundary.

Multipole vectors: A new representation of the CMB sky and evidence for statistical anisotropy or non-Gaussianity at 2⩽l⩽8

NASA Astrophysics Data System (ADS)

Copi, Craig J.; Huterer, Dragan; Starkman, Glenn D.

2004-08-01

We propose a novel representation of cosmic microwave anisotropy maps, where each multipole order l is represented by l unit vectors pointing in directions on the sky and an overall magnitude. These “multipole vectors and scalars” transform as vectors under rotations. Like the usual spherical harmonics, multipole vectors form an irreducible representation of the proper rotation group SO(3). However, they are related to the familiar spherical harmonic coefficients alm in a nonlinear way and are therefore sensitive to different aspects of the cosmic microwave background (CMB) anisotropy. Nevertheless, it is straightforward to determine the multipole vectors for a given CMB map and we present an algorithm to compute them. A code implementing this algorithm is available at http://www.phys.cwru.edu/projects/mpvectors/. Using the Wilkinson Microwave Anisotropy Probe (WMAP) full-sky maps, we perform several tests of the hypothesis that the CMB anisotropy is statistically isotropic and Gaussian random. We find that the result from comparing the oriented area of planes defined by these vectors between multipole pairs 2⩽l1≠l2⩽8 is inconsistent with the isotropic Gaussian hypothesis at the 99.4% level for the internal linear combination map and at 98.9% level for the cleaned map of Tegmark et al. A particular correlation is suggested between the l=3 and l=8 multipoles, as well as several other pairs. This effect is entirely different from the now familiar planarity and alignment of the quadrupole and octupole: while the aforementioned is fairly unlikely, the multipole vectors indicate correlations not expected in Gaussian random skies that make them unusually likely. The result persists after accounting for pixel noise and after assuming a residual 10% dust contamination in the cleaned WMAP map. While the definitive analysis of these results will require more work, we hope that multipole vectors will become a valuable tool for various cosmological tests, in particular those of cosmic isotropy.

Global climate change and vector-borne diseases

USGS Publications Warehouse

Ginsberg, H.S.

2002-01-01

Global warming will have different effects on different diseases because of the complex and idiosynchratic interactions between vectors, hosts, and pathogens that influence transmission dynamics of each pathogen. Human activities, including urbanization, rapid global travel, and vector management, have profound effects on disease transmission that can operate on more rapid time scales than does global climate change. The general concern about global warming encouraging the spread of tropical diseases is legitimate, but the effects vary among diseases, and the ecological implications are difficult to predict.

Dynamics of Vortex and Magnetic Lines in Ideal Hydrodynamics and MHD

NASA Astrophysics Data System (ADS)

Kuznetsov, E. A.; Ruban, V. P.

Vortex line and magnetic line representations are introduced for description of flows in ideal hydrodynamics and MHD, respectively. For incompressible fluids it is shown that the equations of motion for vorticity φ and magnetic field with the help of this transformation follow from the variational principle. By means of this representation it is possible to integrate the system of hydrodynamic type with the Hamiltonian H=|φ|dr. It is also demonstrated that these representations allow to remove from the noncanonical Poisson brackets, defined on the space of divergence-free vector fields, degeneracy connected with the vorticity frozenness for the Euler equation and with magnetic field frozenness for ideal MHD. For MHD a new Weber type transformation is found. It is shown how this transformation can be obtained from the two-fluid model when electrons and ions can be considered as two independent fluids. The Weber type transformation for ideal MHD gives the whole Lagrangian vector invariant. When this invariant is absent this transformation coincides with the Clebsch representation analog introduced in [1].

A Data Type for Efficient Representation of Other Data Types

NASA Technical Reports Server (NTRS)

James, Mark

2008-01-01

A self-organizing, monomorphic data type denoted a sequence has been conceived to address certain concerns that arise in programming parallel computers. A sequence in the present sense can be regarded abstractly as a vector, set, bag, queue, or other construct. Heretofore, in programming a parallel computer, it has been necessary for the programmer to state explicitly, at the outset, what parts of the program and the underlying data structures must be represented in parallel form. Not only is this requirement not optimal from the perspective of implementation; it entails an additional requirement that the programmer have intimate understanding of the underlying parallel structure. The present sequence data type overcomes both the implementation and parallel structure obstacles. In so doing, the sequence data type provides unified means by which the programmer can represent a data structure for natural and automatic decomposition to a parallel computing architecture. Sequences exhibit the behavioral and structural characteristics of vectors, but the underlying representations are automatically synthesized from combinations of programmers advice and execution use metrics. Sequences can vary bidirectionally between sparseness and density, making them excellent choices for many kinds of algorithms. The novelty and benefit of this behavior lies in the fact that it can relieve programmers of the details of implementations. The creation of a sequence enables decoupling of a conceptual representation from an implementation. The underlying representation of a sequence is a hybrid of representations composed of vectors, linked lists, connected blocks, and hash tables. The internal structure of a sequence can automatically change from time to time on the basis of how it is being used. Those portions of a sequence where elements have not been added or removed can be as efficient as vectors. As elements are inserted and removed in a given portion, then different methods are utilized to provide both an access and memory strategy that is optimized for that portion and the use to which it is put.

Quantum supergroups and solutions of the Yang-Baxter equation

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

Bracken, A.J.; Gould, M.D.; Zhang, R.B.

1990-05-10

A method is developed for systematically constructing trigonometric and rational solutions of the Yang-Baxter equation using the representation theory of quantum supergroups. New quantum R-matrices are obtained by applying the method to the vector representations of quantum osp(1/2) and gl(m/n).

Learned Vector-Space Models for Document Retrieval.

ERIC Educational Resources Information Center

Caid, William R.; And Others

1995-01-01

The Latent Semantic Indexing and MatchPlus systems examine similar contexts in which words appear and create representational models that capture the similarity of meaning of terms and then use the representation for retrieval. Text Retrieval Conference experiments using these systems demonstrate the computational feasibility of using…

Bayesian Analogy with Relational Transformations

ERIC Educational Resources Information Center

Lu, Hongjing; Chen, Dawn; Holyoak, Keith J.

2012-01-01

How can humans acquire relational representations that enable analogical inference and other forms of high-level reasoning? Using comparative relations as a model domain, we explore the possibility that bottom-up learning mechanisms applied to objects coded as feature vectors can yield representations of relations sufficient to solve analogy…

Electric transition dipole moment in pre-Born-Oppenheimer molecular structure theory.

PubMed

Simmen, Benjamin; Mátyus, Edit; Reiher, Markus

2014-10-21

This paper presents the calculation of the electric transition dipole moment in a pre-Born-Oppenheimer framework. Electrons and nuclei are treated equally in terms of the parametrization of the non-relativistic total wave function, which is written as a linear combination of basis functions constructed from explicitly correlated Gaussian functions and the global vector representation. The integrals of the electric transition dipole moment are derived corresponding to these basis functions in both the length and the velocity representation. The calculations are performed in laboratory-fixed Cartesian coordinates without relying on coordinates which separate the center of mass from the translationally invariant degrees of freedom. The effect of the overall motion is eliminated through translationally invariant integral expressions. The electric transition dipole moment is calculated between two rovibronic levels of the H2 molecule assignable to the lowest rovibrational states of the X (1)Σ(g)(+) and B (1)Σ(u)(+) electronic states in the clamped-nuclei framework. This is the first evaluation of this quantity in a full quantum mechanical treatment without relying on the Born-Oppenheimer approximation.

Spinor Geometry and Signal Transmission in Three-Space

NASA Astrophysics Data System (ADS)

Binz, Ernst; Pods, Sonja; Schempp, Walter

2002-09-01

For a singularity free gradient field in an open set of an oriented Euclidean space of dimension three we define a natural principal bundle out of an immanent complex line bundle. The elements of both bundles are called internal variables. Several other natural bundles are associated with the principal bundle and, in turn, determine the vector field. Two examples are given and it is shown that for a constant vector field circular polarized waves travelling along a field line can be considered as waves of internal variables. Einstein's equation epsilon = m [middle dot] c2 is derived from the geometry of the principal bundle. On SU(2) a relation between spin representations and Schrodinger representations is established. The link between the spin 1/2-model and the Schrodinger representations yields a connection between a microscopic and a macroscopic viewpoint.

Geometric Representations of Condition Queries on Three-Dimensional Vector Fields

NASA Technical Reports Server (NTRS)

Henze, Chris

1999-01-01

Condition queries on distributed data ask where particular conditions are satisfied. It is possible to represent condition queries as geometric objects by plotting field data in various spaces derived from the data, and by selecting loci within these derived spaces which signify the desired conditions. Rather simple geometric partitions of derived spaces can represent complex condition queries because much complexity can be encapsulated in the derived space mapping itself A geometric view of condition queries provides a useful conceptual unification, allowing one to intuitively understand many existing vector field feature detection algorithms -- and to design new ones -- as variations on a common theme. A geometric representation of condition queries also provides a simple and coherent basis for computer implementation, reducing a wide variety of existing and potential vector field feature detection techniques to a few simple geometric operations.

Bayesian analogy with relational transformations.

PubMed

Lu, Hongjing; Chen, Dawn; Holyoak, Keith J

2012-07-01

How can humans acquire relational representations that enable analogical inference and other forms of high-level reasoning? Using comparative relations as a model domain, we explore the possibility that bottom-up learning mechanisms applied to objects coded as feature vectors can yield representations of relations sufficient to solve analogy problems. We introduce Bayesian analogy with relational transformations (BART) and apply the model to the task of learning first-order comparative relations (e.g., larger, smaller, fiercer, meeker) from a set of animal pairs. Inputs are coded by vectors of continuous-valued features, based either on human magnitude ratings, normed feature ratings (De Deyne et al., 2008), or outputs of the topics model (Griffiths, Steyvers, & Tenenbaum, 2007). Bootstrapping from empirical priors, the model is able to induce first-order relations represented as probabilistic weight distributions, even when given positive examples only. These learned representations allow classification of novel instantiations of the relations and yield a symbolic distance effect of the sort obtained with both humans and other primates. BART then transforms its learned weight distributions by importance-guided mapping, thereby placing distinct dimensions into correspondence. These transformed representations allow BART to reliably solve 4-term analogies (e.g., larger:smaller::fiercer:meeker), a type of reasoning that is arguably specific to humans. Our results provide a proof-of-concept that structured analogies can be solved with representations induced from unstructured feature vectors by mechanisms that operate in a largely bottom-up fashion. We discuss potential implications for algorithmic and neural models of relational thinking, as well as for the evolution of abstract thought. Copyright 2012 APA, all rights reserved.

Privacy-Preserving Predictive Modeling: Harmonization of Contextual Embeddings From Different Sources.

PubMed

Huang, Yingxiang; Lee, Junghye; Wang, Shuang; Sun, Jimeng; Liu, Hongfang; Jiang, Xiaoqian

2018-05-16

Data sharing has been a big challenge in biomedical informatics because of privacy concerns. Contextual embedding models have demonstrated a very strong representative capability to describe medical concepts (and their context), and they have shown promise as an alternative way to support deep-learning applications without the need to disclose original data. However, contextual embedding models acquired from individual hospitals cannot be directly combined because their embedding spaces are different, and naive pooling renders combined embeddings useless. The aim of this study was to present a novel approach to address these issues and to promote sharing representation without sharing data. Without sacrificing privacy, we also aimed to build a global model from representations learned from local private data and synchronize information from multiple sources. We propose a methodology that harmonizes different local contextual embeddings into a global model. We used Word2Vec to generate contextual embeddings from each source and Procrustes to fuse different vector models into one common space by using a list of corresponding pairs as anchor points. We performed prediction analysis with harmonized embeddings. We used sequential medical events extracted from the Medical Information Mart for Intensive Care III database to evaluate the proposed methodology in predicting the next likely diagnosis of a new patient using either structured data or unstructured data. Under different experimental scenarios, we confirmed that the global model built from harmonized local models achieves a more accurate prediction than local models and global models built from naive pooling. Such aggregation of local models using our unique harmonization can serve as the proxy for a global model, combining information from a wide range of institutions and information sources. It allows information unique to a certain hospital to become available to other sites, increasing the fluidity of information flow in health care. ©Yingxiang Huang, Junghye Lee, Shuang Wang, Jimeng Sun, Hongfang Liu, Xiaoqian Jiang. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 16.05.2018.

Perturbation theory from automorphic forms

NASA Astrophysics Data System (ADS)

Lambert, Neil; West, Peter

2010-05-01

Using our previous construction of Eisenstein-like automorphic forms we derive formulae for the perturbative and non-perturbative parts for any group and representation. The result is written in terms of the weights of the representation and the derivation is largely group theoretical. Specialising to the E n+1 groups relevant to type II string theory and the representation associated with node n + 1 of the E n+1 Dynkin diagram we explicitly find the perturbative part in terms of String Theory variables, such as the string coupling g d and volume V n . For dimensions seven and higher we find that the perturbation theory involves only two terms. In six dimensions we construct the SO(5, 5) automorphic form using the vector representation. Although these automorphic forms are generally compatible with String Theory, the one relevant to R 4 involves terms with g d -6 and so is problematic. We then study a constrained SO(5, 5) automorphic form, obtained by summing over null vectors, and compute its perturbative part. We find that it is consistent with String Theory and makes precise predictions for the perturbative results. We also study the unconstrained automorphic forms for E 6 in the 27 representation and E 7 in the 133 representation, giving their perturbative part and commenting on their role in String Theory.

Nilpotent representations of classical quantum groups at roots of unity

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

Abe, Yuuki; Nakashima, Toshiki

2005-11-01

Properly specializing the parameters in 'Schnizer modules', for types A,B,C, and D, we get its unique primitive vector. Then we show that the module generated by the primitive vector is an irreducible highest weight module of finite dimensional classical quantum groups at roots of unity.

A Vector Representation for Thermodynamic Relationships

ERIC Educational Resources Information Center

Pogliani, Lionello

2006-01-01

The existing vector formalism method for thermodynamic relationship maintains tractability and uses accessible mathematics, which can be seen as a diverting and entertaining step into the mathematical formalism of thermodynamics and as an elementary application of matrix algebra. The method is based on ideas and operations apt to improve the…

Arrowheaded enhanced multivariance products representation for matrices (AEMPRM): Specifically focusing on infinite matrices and converting arrowheadedness to tridiagonality

NASA Astrophysics Data System (ADS)

Özdemir, Gizem; Demiralp, Metin

2015-12-01

In this work, Enhanced Multivariance Products Representation (EMPR) approach which is a Demiralp-and-his- group extension to the Sobol's High Dimensional Model Representation (HDMR) has been used as the basic tool. Their discrete form have also been developed and used in practice by Demiralp and his group in addition to some other authors for the decomposition of the arrays like vectors, matrices, or multiway arrays. This work specifically focuses on the decomposition of infinite matrices involving denumerable infinitely many rows and columns. To this end the target matrix is first decomposed to the sum of certain outer products and then each outer product is treated by Tridiagonal Matrix Enhanced Multivariance Products Representation (TMEMPR) which has been developed by Demiralp and his group. The result is a three-matrix- factor-product whose kernel (the middle factor) is an arrowheaded matrix while the pre and post factors are invertable matrices decomposed of the support vectors of TMEMPR. This new method is called as Arrowheaded Enhanced Multivariance Products Representation for Matrices. The general purpose is approximation of denumerably infinite matrices with the new method.

Effective Clipart Image Vectorization through Direct Optimization of Bezigons.

PubMed

Yang, Ming; Chao, Hongyang; Zhang, Chi; Guo, Jun; Yuan, Lu; Sun, Jian

2016-02-01

Bezigons, i.e., closed paths composed of Bézier curves, have been widely employed to describe shapes in image vectorization results. However, most existing vectorization techniques infer the bezigons by simply approximating an intermediate vector representation (such as polygons). Consequently, the resultant bezigons are sometimes imperfect due to accumulated errors, fitting ambiguities, and a lack of curve priors, especially for low-resolution images. In this paper, we describe a novel method for vectorizing clipart images. In contrast to previous methods, we directly optimize the bezigons rather than using other intermediate representations; therefore, the resultant bezigons are not only of higher fidelity compared with the original raster image but also more reasonable because they were traced by a proficient expert. To enable such optimization, we have overcome several challenges and have devised a differentiable data energy as well as several curve-based prior terms. To improve the efficiency of the optimization, we also take advantage of the local control property of bezigons and adopt an overlapped piecewise optimization strategy. The experimental results show that our method outperforms both the current state-of-the-art method and commonly used commercial software in terms of bezigon quality.

Machine parts recognition using a trinary associative memory

NASA Technical Reports Server (NTRS)

Awwal, Abdul Ahad S.; Karim, Mohammad A.; Liu, Hua-Kuang

1989-01-01

The convergence mechanism of vectors in Hopfield's neural network in relation to recognition of partially known patterns is studied in terms of both inner products and Hamming distance. It has been shown that Hamming distance should not always be used in determining the convergence of vectors. Instead, inner product weighting coefficients play a more dominant role in certain data representations for determining the convergence mechanism. A trinary neuron representation for associative memory is found to be more effective for associative recall. Applications of the trinary associative memory to reconstruct machine part images that are partially missing are demonstrated by means of computer simulation as examples of the usefulness of this approach.

Machine Parts Recognition Using A Trinary Associative Memory

NASA Astrophysics Data System (ADS)

Awwal, Abdul A. S.; Karim, Mohammad A.; Liu, Hua-Kuang

1989-05-01

The convergence mechanism of vectors in Hopfield's neural network in relation to recognition of partially known patterns is studied in terms of both inner products and Hamming distance. It has been shown that Hamming distance should not always be used in determining the convergence of vectors. Instead, inner product weighting coefficients play a more dominant role in certain data representations for determining the convergence mechanism. A trinary neuron representation for associative memory is found to be more effective for associative recall. Applications of the trinary associative memory to reconstruct machine part images that are partially missing are demonstrated by means of computer simulation as examples of the usefulness of this approach.

Recent Developments In Theory Of Balanced Linear Systems

NASA Technical Reports Server (NTRS)

Gawronski, Wodek

1994-01-01

Report presents theoretical study of some issues of controllability and observability of system represented by linear, time-invariant mathematical model of the form. x = Ax + Bu, y = Cx + Du, x(0) = xo where x is n-dimensional vector representing state of system; u is p-dimensional vector representing control input to system; y is q-dimensional vector representing output of system; n,p, and q are integers; x(0) is intial (zero-time) state vector; and set of matrices (A,B,C,D) said to constitute state-space representation of system.

Attitude Error Representations for Kalman Filtering

NASA Technical Reports Server (NTRS)

Markley, F. Landis; Bauer, Frank H. (Technical Monitor)

2002-01-01

The quaternion has the lowest dimensionality possible for a globally nonsingular attitude representation. The quaternion must obey a unit norm constraint, though, which has led to the development of an extended Kalman filter using a quaternion for the global attitude estimate and a three-component representation for attitude errors. We consider various attitude error representations for this Multiplicative Extended Kalman Filter and its second-order extension.

The Heteronuclear Single-Quantum Correlation (HSQC) Experiment: Vectors versus Product Operators

ERIC Educational Resources Information Center

de la Vega-Herna´ndez, Karen; Antuch, Manuel

2015-01-01

A vectorial representation of the full sequence of events occurring during the 2D-NMR heteronuclear single-quantum correlation (HSQC) experiment is presented. The proposed vectorial representation conveys an understanding of the magnetization evolution during the HSQC pulse sequence for those who have little or no quantum mechanical background.…

Method and apparatus for identification of hazards along an intended travel route

NASA Technical Reports Server (NTRS)

Kronfeld, Kevin M. (Inventor); Lapis, Mary Beth (Inventor); Walling, Karen L. (Inventor); Chackalackal, Mathew S. (Inventor)

2003-01-01

Targets proximate to a travel route plan were evaluated to determine hazardousness. Projected geometric representation of a vehicle determines intrusion of hazardous targets along travel route plan. Geometric representation of hazardous targets projected along motion vector to determine intrusion upon travel route plan. Intrusion assessment presented on user display.

Arrows as Anchors: An Analysis of the Material Features of Electric Field Vector Arrows

ERIC Educational Resources Information Center

Gire, Elizabeth; Price, Edward

2014-01-01

Representations in physics possess both physical and conceptual aspects that are fundamentally intertwined and can interact to support or hinder sense making and computation. We use distributed cognition and the theory of conceptual blending with material anchors to interpret the roles of conceptual and material features of representations in…

Face recognition via sparse representation of SIFT feature on hexagonal-sampling image

NASA Astrophysics Data System (ADS)

Zhang, Daming; Zhang, Xueyong; Li, Lu; Liu, Huayong

2018-04-01

This paper investigates a face recognition approach based on Scale Invariant Feature Transform (SIFT) feature and sparse representation. The approach takes advantage of SIFT which is local feature other than holistic feature in classical Sparse Representation based Classification (SRC) algorithm and possesses strong robustness to expression, pose and illumination variations. Since hexagonal image has more inherit merits than square image to make recognition process more efficient, we extract SIFT keypoint in hexagonal-sampling image. Instead of matching SIFT feature, firstly the sparse representation of each SIFT keypoint is given according the constructed dictionary; secondly these sparse vectors are quantized according dictionary; finally each face image is represented by a histogram and these so-called Bag-of-Words vectors are classified by SVM. Due to use of local feature, the proposed method achieves better result even when the number of training sample is small. In the experiments, the proposed method gave higher face recognition rather than other methods in ORL and Yale B face databases; also, the effectiveness of the hexagonal-sampling in the proposed method is verified.

Using the Logarithm of Odds to Define a Vector Space on Probabilistic Atlases

PubMed Central

Pohl, Kilian M.; Fisher, John; Bouix, Sylvain; Shenton, Martha; McCarley, Robert W.; Grimson, W. Eric L.; Kikinis, Ron; Wells, William M.

2007-01-01

The Logarithm of the Odds ratio (LogOdds) is frequently used in areas such as artificial neural networks, economics, and biology, as an alternative representation of probabilities. Here, we use LogOdds to place probabilistic atlases in a linear vector space. This representation has several useful properties for medical imaging. For example, it not only encodes the shape of multiple anatomical structures but also captures some information concerning uncertainty. We demonstrate that the resulting vector space operations of addition and scalar multiplication have natural probabilistic interpretations. We discuss several examples for placing label maps into the space of LogOdds. First, we relate signed distance maps, a widely used implicit shape representation, to LogOdds and compare it to an alternative that is based on smoothing by spatial Gaussians. We find that the LogOdds approach better preserves shapes in a complex multiple object setting. In the second example, we capture the uncertainty of boundary locations by mapping multiple label maps of the same object into the LogOdds space. Third, we define a framework for non-convex interpolations among atlases that capture different time points in the aging process of a population. We evaluate the accuracy of our representation by generating a deformable shape atlas that captures the variations of anatomical shapes across a population. The deformable atlas is the result of a principal component analysis within the LogOdds space. This atlas is integrated into an existing segmentation approach for MR images. We compare the performance of the resulting implementation in segmenting 20 test cases to a similar approach that uses a more standard shape model that is based on signed distance maps. On this data set, the Bayesian classification model with our new representation outperformed the other approaches in segmenting subcortical structures. PMID:17698403

Chemical reaction vector embeddings: towards predicting drug metabolism in the human gut microbiome.

PubMed

Mallory, Emily K; Acharya, Ambika; Rensi, Stefano E; Turnbaugh, Peter J; Bright, Roselie A; Altman, Russ B

2018-01-01

Bacteria in the human gut have the ability to activate, inactivate, and reactivate drugs with both intended and unintended effects. For example, the drug digoxin is reduced to the inactive metabolite dihydrodigoxin by the gut Actinobacterium E. lenta, and patients colonized with high levels of drug metabolizing strains may have limited response to the drug. Understanding the complete space of drugs that are metabolized by the human gut microbiome is critical for predicting bacteria-drug relationships and their effects on individual patient response. Discovery and validation of drug metabolism via bacterial enzymes has yielded >50 drugs after nearly a century of experimental research. However, there are limited computational tools for screening drugs for potential metabolism by the gut microbiome. We developed a pipeline for comparing and characterizing chemical transformations using continuous vector representations of molecular structure learned using unsupervised representation learning. We applied this pipeline to chemical reaction data from MetaCyc to characterize the utility of vector representations for chemical reaction transformations. After clustering molecular and reaction vectors, we performed enrichment analyses and queries to characterize the space. We detected enriched enzyme names, Gene Ontology terms, and Enzyme Consortium (EC) classes within reaction clusters. In addition, we queried reactions against drug-metabolite transformations known to be metabolized by the human gut microbiome. The top results for these known drug transformations contained similar substructure modifications to the original drug pair. This work enables high throughput screening of drugs and their resulting metabolites against chemical reactions common to gut bacteria.

Spacetime algebra as a powerful tool for electromagnetism

NASA Astrophysics Data System (ADS)

Dressel, Justin; Bliokh, Konstantin Y.; Nori, Franco

2015-08-01

We present a comprehensive introduction to spacetime algebra that emphasizes its practicality and power as a tool for the study of electromagnetism. We carefully develop this natural (Clifford) algebra of the Minkowski spacetime geometry, with a particular focus on its intrinsic (and often overlooked) complex structure. Notably, the scalar imaginary that appears throughout the electromagnetic theory properly corresponds to the unit 4-volume of spacetime itself, and thus has physical meaning. The electric and magnetic fields are combined into a single complex and frame-independent bivector field, which generalizes the Riemann-Silberstein complex vector that has recently resurfaced in studies of the single photon wavefunction. The complex structure of spacetime also underpins the emergence of electromagnetic waves, circular polarizations, the normal variables for canonical quantization, the distinction between electric and magnetic charge, complex spinor representations of Lorentz transformations, and the dual (electric-magnetic field exchange) symmetry that produces helicity conservation in vacuum fields. This latter symmetry manifests as an arbitrary global phase of the complex field, motivating the use of a complex vector potential, along with an associated transverse and gauge-invariant bivector potential, as well as complex (bivector and scalar) Hertz potentials. Our detailed treatment aims to encourage the use of spacetime algebra as a readily available and mature extension to existing vector calculus and tensor methods that can greatly simplify the analysis of fundamentally relativistic objects like the electromagnetic field.

Pulse Vector-Excitation Speech Encoder

NASA Technical Reports Server (NTRS)

Davidson, Grant; Gersho, Allen

1989-01-01

Proposed pulse vector-excitation speech encoder (PVXC) encodes analog speech signals into digital representation for transmission or storage at rates below 5 kilobits per second. Produces high quality of reconstructed speech, but with less computation than required by comparable speech-encoding systems. Has some characteristics of multipulse linear predictive coding (MPLPC) and of code-excited linear prediction (CELP). System uses mathematical model of vocal tract in conjunction with set of excitation vectors and perceptually-based error criterion to synthesize natural-sounding speech.

Multipole Vectors: Decomposing Functions on a Sphere

NASA Astrophysics Data System (ADS)

Copi, C. J.; Huterer, D.; Starkman, G. D.

2011-09-01

We propose a novel representation of cosmic microwave anisotropy maps, where each multipole order l is represented by l unit vectors pointing in directions on the sky and an overall magnitude. These "multipole vectors and scalars" transform as vectors under rotations. Like the usual spherical harmonics, multipole vectors form an irreducible representation of the proper rotation group SO(3). However, they are related to the familiar spherical harmonic coefficients, alm, in a nonlinear way, and are therefore sensitive to different aspects of the CMB anisotropy. Nevertheless, it is straightforward to determine the multipole vectors for a given CMB map and we present an algorithm to compute them. Using the WMAP full-sky maps, we perform several tests of the hypothesis that the CMB anisotropy is statistically isotropic and Gaussian random. We find that the result from comparing the oriented area of planes defined by these vectors between multipole pairs 2<=l1!=l2<=8 is inconsistent with the isotropic Gaussian hypothesis at the 99.4% level for the ILC map and at 98.9% level for the cleaned map of Tegmark et al. A particular correlation is suggested between the l=3 and l=8 multipoles, as well as several other pairs. This effect is entirely different from the now familiar planarity and alignment of the quadrupole and octupole: while the aforementioned is fairly unlikely, the multipole vectors indicate correlations not expected in Gaussian random skies that make them unusually likely. The result persists after accounting for pixel noise and after assuming a residual 10% dust contamination in the cleaned WMAP map. While the definitive analysis of these results will require more work, we hope that multipole vectors will become a valuable tool for various cosmological tests, in particular those of cosmic isotropy.

Global Climate Teleconnections to Forecast Increased Risk of Vector-Borne Animal and Human Disease Transmission

USDA-ARS?s Scientific Manuscript database

We willexamine how climate teleconnect ions and variability impact vector biology and vector borne disease ecology, and demonstrate that global climate monitoring can be used to anticipate and forecast epidemics and epizootics. In this context we willexamine significant worldwide weather anomalies t...

Visualizing global properties of a molecular dynamics trajectory.

PubMed

Zhou, Hao; Li, Shangyang; Makowski, Lee

2016-01-01

Molecular dynamics (MD) trajectories are very large data sets that contain substantial information about the dynamic behavior of a protein. Condensing these data into a form that can provide intuitively useful understanding of the molecular behavior during the trajectory is a substantial challenge that has received relatively little attention. Here, we introduce the sigma-r plot, a plot of the standard deviation of intermolecular distances as a function of that distance. This representation of global dynamics contains within a single, one-dimensional plot, the average range of motion between pairs of atoms within a macromolecule. Comparison of sigma-r plots calculated from 10 ns trajectories of proteins representing the four major SCOP fold classes indicates diversity of dynamic behaviors which are recognizably different among the four classes. Differences in domain structure and molecular weight also produce recognizable features in sigma-r plots, reflective of differences in global dynamics. Plots generated from trajectories with progressively increasing simulation time reflect the increased sampling of the structural ensemble as a function of time. Single amino acid replacements can give rise to changes in global dynamics detectable through comparison of sigma-r plots. Dynamic behavior of substructures can be monitored by careful choice of interatomic vectors included in the calculation. These examples provide demonstrations of the utility of the sigma-r plot to provide a simple measure of the global dynamics of a macromolecule. © 2015 Wiley Periodicals, Inc.

UltraPse: A Universal and Extensible Software Platform for Representing Biological Sequences.

PubMed

Du, Pu-Feng; Zhao, Wei; Miao, Yang-Yang; Wei, Le-Yi; Wang, Likun

2017-11-14

With the avalanche of biological sequences in public databases, one of the most challenging problems in computational biology is to predict their biological functions and cellular attributes. Most of the existing prediction algorithms can only handle fixed-length numerical vectors. Therefore, it is important to be able to represent biological sequences with various lengths using fixed-length numerical vectors. Although several algorithms, as well as software implementations, have been developed to address this problem, these existing programs can only provide a fixed number of representation modes. Every time a new sequence representation mode is developed, a new program will be needed. In this paper, we propose the UltraPse as a universal software platform for this problem. The function of the UltraPse is not only to generate various existing sequence representation modes, but also to simplify all future programming works in developing novel representation modes. The extensibility of UltraPse is particularly enhanced. It allows the users to define their own representation mode, their own physicochemical properties, or even their own types of biological sequences. Moreover, UltraPse is also the fastest software of its kind. The source code package, as well as the executables for both Linux and Windows platforms, can be downloaded from the GitHub repository.

A Parallel Vector Machine for the PM Programming Language

NASA Astrophysics Data System (ADS)

Bellerby, Tim

2016-04-01

PM is a new programming language which aims to make the writing of computational geoscience models on parallel hardware accessible to scientists who are not themselves expert parallel programmers. It is based around the concept of communicating operators: language constructs that enable variables local to a single invocation of a parallelised loop to be viewed as if they were arrays spanning the entire loop domain. This mechanism enables different loop invocations (which may or may not be executing on different processors) to exchange information in a manner that extends the successful Communicating Sequential Processes idiom from single messages to collective communication. Communicating operators avoid the additional synchronisation mechanisms, such as atomic variables, required when programming using the Partitioned Global Address Space (PGAS) paradigm. Using a single loop invocation as the fundamental unit of concurrency enables PM to uniformly represent different levels of parallelism from vector operations through shared memory systems to distributed grids. This paper describes an implementation of PM based on a vectorised virtual machine. On a single processor node, concurrent operations are implemented using masked vector operations. Virtual machine instructions operate on vectors of values and may be unmasked, masked using a Boolean field, or masked using an array of active vector cell locations. Conditional structures (such as if-then-else or while statement implementations) calculate and apply masks to the operations they control. A shift in mask representation from Boolean to location-list occurs when active locations become sufficiently sparse. Parallel loops unfold data structures (or vectors of data structures for nested loops) into vectors of values that may additionally be distributed over multiple computational nodes and then split into micro-threads compatible with the size of the local cache. Inter-node communication is accomplished using standard OpenMP and MPI. Performance analyses of the PM vector machine, demonstrating its scaling properties with respect to domain size and the number of processor nodes will be presented for a range of hardware configurations. The PM software and language definition are being made available under unrestrictive MIT and Creative Commons Attribution licenses respectively: www.pm-lang.org.

Compact Representation of High-Dimensional Feature Vectors for Large-Scale Image Recognition and Retrieval.

PubMed

Zhang, Yu; Wu, Jianxin; Cai, Jianfei

2016-05-01

In large-scale visual recognition and image retrieval tasks, feature vectors, such as Fisher vector (FV) or the vector of locally aggregated descriptors (VLAD), have achieved state-of-the-art results. However, the combination of the large numbers of examples and high-dimensional vectors necessitates dimensionality reduction, in order to reduce its storage and CPU costs to a reasonable range. In spite of the popularity of various feature compression methods, this paper shows that the feature (dimension) selection is a better choice for high-dimensional FV/VLAD than the feature (dimension) compression methods, e.g., product quantization. We show that strong correlation among the feature dimensions in the FV and the VLAD may not exist, which renders feature selection a natural choice. We also show that, many dimensions in FV/VLAD are noise. Throwing them away using feature selection is better than compressing them and useful dimensions altogether using feature compression methods. To choose features, we propose an efficient importance sorting algorithm considering both the supervised and unsupervised cases, for visual recognition and image retrieval, respectively. Combining with the 1-bit quantization, feature selection has achieved both higher accuracy and less computational cost than feature compression methods, such as product quantization, on the FV and the VLAD image representations.

Assessing the Impact of Representational and Contextual Problem Features on Student Use of Right-Hand Rules

ERIC Educational Resources Information Center

Kustusch, Mary Bridget

2016-01-01

Students in introductory physics struggle with vector algebra and these challenges are often associated with contextual and representational features of the problems. Performance on problems about cross product direction is particularly poor and some research suggests that this may be primarily due to misapplied right-hand rules. However, few…

Raster and vector processing for scanned linework

USGS Publications Warehouse

Greenlee, David D.

1987-01-01

An investigation of raster editing techniques, including thinning, filling, and node detecting, was performed by using specialized software. The techniques were based on encoding the state of the 3-by-3 neighborhood surrounding each pixel into a single byte. A prototypical method for converting the edited raster linkwork into vectors was also developed. Once vector representations of the lines were formed, they were formatted as a Digital Line Graph, and further refined by deletion of nonessential vertices and by smoothing with a curve-fitting technique.

Kronecker-Basis-Representation Based Tensor Sparsity and Its Applications to Tensor Recovery.

PubMed

Xie, Qi; Zhao, Qian; Meng, Deyu; Xu, Zongben

2017-08-02

It is well known that the sparsity/low-rank of a vector/matrix can be rationally measured by nonzero-entries-number ($l_0$ norm)/nonzero- singular-values-number (rank), respectively. However, data from real applications are often generated by the interaction of multiple factors, which obviously cannot be sufficiently represented by a vector/matrix, while a high order tensor is expected to provide more faithful representation to deliver the intrinsic structure underlying such data ensembles. Unlike the vector/matrix case, constructing a rational high order sparsity measure for tensor is a relatively harder task. To this aim, in this paper we propose a measure for tensor sparsity, called Kronecker-basis-representation based tensor sparsity measure (KBR briefly), which encodes both sparsity insights delivered by Tucker and CANDECOMP/PARAFAC (CP) low-rank decompositions for a general tensor. Then we study the KBR regularization minimization (KBRM) problem, and design an effective ADMM algorithm for solving it, where each involved parameter can be updated with closed-form equations. Such an efficient solver makes it possible to extend KBR to various tasks like tensor completion and tensor robust principal component analysis. A series of experiments, including multispectral image (MSI) denoising, MSI completion and background subtraction, substantiate the superiority of the proposed methods beyond state-of-the-arts.

Low-rank separated representation surrogates of high-dimensional stochastic functions: Application in Bayesian inference

NASA Astrophysics Data System (ADS)

Validi, AbdoulAhad

2014-03-01

This study introduces a non-intrusive approach in the context of low-rank separated representation to construct a surrogate of high-dimensional stochastic functions, e.g., PDEs/ODEs, in order to decrease the computational cost of Markov Chain Monte Carlo simulations in Bayesian inference. The surrogate model is constructed via a regularized alternative least-square regression with Tikhonov regularization using a roughening matrix computing the gradient of the solution, in conjunction with a perturbation-based error indicator to detect optimal model complexities. The model approximates a vector of a continuous solution at discrete values of a physical variable. The required number of random realizations to achieve a successful approximation linearly depends on the function dimensionality. The computational cost of the model construction is quadratic in the number of random inputs, which potentially tackles the curse of dimensionality in high-dimensional stochastic functions. Furthermore, this vector-valued separated representation-based model, in comparison to the available scalar-valued case, leads to a significant reduction in the cost of approximation by an order of magnitude equal to the vector size. The performance of the method is studied through its application to three numerical examples including a 41-dimensional elliptic PDE and a 21-dimensional cavity flow.

Reflection Positive Stochastic Processes Indexed by Lie Groups

NASA Astrophysics Data System (ADS)

Jorgensen, Palle E. T.; Neeb, Karl-Hermann; Ólafsson, Gestur

2016-06-01

Reflection positivity originates from one of the Osterwalder-Schrader axioms for constructive quantum field theory. It serves as a bridge between euclidean and relativistic quantum field theory. In mathematics, more specifically, in representation theory, it is related to the Cartan duality of symmetric Lie groups (Lie groups with an involution) and results in a transformation of a unitary representation of a symmetric Lie group to a unitary representation of its Cartan dual. In this article we continue our investigation of representation theoretic aspects of reflection positivity by discussing reflection positive Markov processes indexed by Lie groups, measures on path spaces, and invariant gaussian measures in spaces of distribution vectors. This provides new constructions of reflection positive unitary representations.

Students' difficulties with vector calculus in electrodynamics

NASA Astrophysics Data System (ADS)

Bollen, Laurens; van Kampen, Paul; De Cock, Mieke

2015-12-01

Understanding Maxwell's equations in differential form is of great importance when studying the electrodynamic phenomena discussed in advanced electromagnetism courses. It is therefore necessary that students master the use of vector calculus in physical situations. In this light we investigated the difficulties second year students at KU Leuven encounter with the divergence and curl of a vector field in mathematical and physical contexts. We have found that they are quite skilled at doing calculations, but struggle with interpreting graphical representations of vector fields and applying vector calculus to physical situations. We have found strong indications that traditional instruction is not sufficient for our students to fully understand the meaning and power of Maxwell's equations in electrodynamics.

Media coverage of the Zika crisis in Brazil: The construction of a 'war' frame that masked social and gender inequalities.

PubMed

Ribeiro, Barbara; Hartley, Sarah; Nerlich, Brigitte; Jaspal, Rusi

2018-03-01

Between 2015 and 2016, Zika became an epidemic of global concern and the focus of intense media coverage. Using a hybrid model of frame and social representations theory, we examine how the Zika outbreak was reported in two major newspapers in Brazil: O Globo and Folha de São Paulo. The analysis of 186 articles published between December 2015 and May 2016 reveals a dominant 'war' frame supported by two sub-frames: one focused on eradicating the vector (mosquito) and another on controlling microcephaly, placing the burden of prevention on women. Scientific uncertainties about the virus and its relationship to microcephaly coupled with political uncertainties in Brazil increased the power of the war frame. This frame gave prominence and legitimacy to certain representations of disease management during the crisis, masking social and gender inequalities. We show how the cartography of the disease overlaps with that of poverty and regional inequality in Brazil to argue that addressing socio-economic aspects is essential, but normally neglected, in media communications during disease outbreaks like Zika. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Regression-based adaptive sparse polynomial dimensional decomposition for sensitivity analysis

NASA Astrophysics Data System (ADS)

Tang, Kunkun; Congedo, Pietro; Abgrall, Remi

2014-11-01

Polynomial dimensional decomposition (PDD) is employed in this work for global sensitivity analysis and uncertainty quantification of stochastic systems subject to a large number of random input variables. Due to the intimate structure between PDD and Analysis-of-Variance, PDD is able to provide simpler and more direct evaluation of the Sobol' sensitivity indices, when compared to polynomial chaos (PC). Unfortunately, the number of PDD terms grows exponentially with respect to the size of the input random vector, which makes the computational cost of the standard method unaffordable for real engineering applications. In order to address this problem of curse of dimensionality, this work proposes a variance-based adaptive strategy aiming to build a cheap meta-model by sparse-PDD with PDD coefficients computed by regression. During this adaptive procedure, the model representation by PDD only contains few terms, so that the cost to resolve repeatedly the linear system of the least-square regression problem is negligible. The size of the final sparse-PDD representation is much smaller than the full PDD, since only significant terms are eventually retained. Consequently, a much less number of calls to the deterministic model is required to compute the final PDD coefficients.

Vector representation as a tool for detecting characteristic uranium peaks

NASA Astrophysics Data System (ADS)

Forney, Anne Marie

Vector representation is found as a viable tool for identifying the presence of and determining the difference between enriched and naturally occurring uranium. This was accomplished through the isolation of two regions of interest around the uranium-235 (235U) gamma emission at 186 keV and the uranium-238 (238U) gamma emission at 1001 keV. The uranium 186 keV peak is used as a meter for uranium enrichment, and events from this emission occurred more frequently with the increase of the 235U composition. Spectra were taken with the use of a high purity germanium detector in series with a multi-channel analyzer (MCA) and Maestro 32, a MCA emulator and spectral software. The vector representation method was used to compare two spectra by taking their dot product. The output from this method is an angle, which represents the similarity and contrast between the two spectra. When the angle is close to zero the spectra are similar, and as the angle approaches 90 degrees the spectral agreement decreases. The angles were calculated and compared in Microsoft Excel. A 49 % enriched uranyl acetate source containing both gamma emissions from 235U and 238U was used as a reference source to which all spectra were compared. Two other uranium sources were used within this project: a 100.2 nCi highly-enriched uranium source with 97.7 % 235U by weight, and a piece of uranium ore with an approximate exposure rate of 0.2 mR/h (51.5 nC/kg/h) at 1 cm. These two uranium sources provided different ratios of 235U to 238U, leading to different ratios of the 186 keV and 1001 keV peaks. To test the limits of the vector representation method, various source configurations were used. These included placing the source directly on top of the detector, using two distances for the source from the detector, using the source in addition to cobalt-60, and finally two distances for the source from the detector with a one centimeter lead shield. The two distances from the detector without the shielding were 1.3 inches (3.30 cm) and 1 foot (30.48 cm). In the cases using lead shielding, in the first geometry, the source was placed directly on the lead shielding and in the second geometry, the source was placed a foot above the lead shielding and detector. Vector representation output angles higher than a value of 40.3 degrees indicated that uranium was not present in the source. All of the sources tested with an angle below this 40.3 degree cutoff contained some type of uranium. To determine whether the uranium was processed or naturally occurring, 18.0 degrees was chosen as the upper limit for processed uranium sources. Sources that produced an angle above 18.0 degrees and below 40.3 degrees were categorized as naturally occurring uranium. The vector representation technique was able to classify the uranium sources in all of the geometries except for the geometries that included the centimeter of lead.

78 FR 40541 - GDT Tek, Inc., Gemini Explorations, Inc., Genetic Vectors, Inc., and Global Gate Property Corp...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-05

... SECURITIES AND EXCHANGE COMMISSION [File No. 500-1] GDT Tek, Inc., Gemini Explorations, Inc., Genetic Vectors, Inc., and Global Gate Property Corp.; Order of Suspension of Trading July 2, 2013. It... Genetic Vectors, Inc. because it has not filed any periodic reports since the period ended September 30...

Multiscale vector fields for image pattern recognition

NASA Technical Reports Server (NTRS)

Low, Kah-Chan; Coggins, James M.

1990-01-01

A uniform processing framework for low-level vision computing in which a bank of spatial filters maps the image intensity structure at each pixel into an abstract feature space is proposed. Some properties of the filters and the feature space are described. Local orientation is measured by a vector sum in the feature space as follows: each filter's preferred orientation along with the strength of the filter's output determine the orientation and the length of a vector in the feature space; the vectors for all filters are summed to yield a resultant vector for a particular pixel and scale. The orientation of the resultant vector indicates the local orientation, and the magnitude of the vector indicates the strength of the local orientation preference. Limitations of the vector sum method are discussed. Investigations show that the processing framework provides a useful, redundant representation of image structure across orientation and scale.

Incorporating linguistic knowledge for learning distributed word representations.

PubMed

Wang, Yan; Liu, Zhiyuan; Sun, Maosong

2015-01-01

Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining.

Incorporating Linguistic Knowledge for Learning Distributed Word Representations

PubMed Central

Wang, Yan; Liu, Zhiyuan; Sun, Maosong

2015-01-01

Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining. PMID:25874581

Unitary Transformations in 3 D Vector Representation of Qutrit States

DTIC Science & Technology

2018-03-12

Representation of Qutrit States Vinod K Mishra Computational and Information Sciences Directorate, ARL Approved for public... information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and...maintaining the data needed, and completing and reviewing the collection information . Send comments regarding this burden estimate or any other aspect

Good Practices for Learning to Recognize Actions Using FV and VLAD.

PubMed

Wu, Jianxin; Zhang, Yu; Lin, Weiyao

2016-12-01

High dimensional representations such as Fisher vectors (FV) and vectors of locally aggregated descriptors (VLAD) have shown state-of-the-art accuracy for action recognition in videos. The high dimensionality, on the other hand, also causes computational difficulties when scaling up to large-scale video data. This paper makes three lines of contributions to learning to recognize actions using high dimensional representations. First, we reviewed several existing techniques that improve upon FV or VLAD in image classification, and performed extensive empirical evaluations to assess their applicability for action recognition. Our analyses of these empirical results show that normality and bimodality are essential to achieve high accuracy. Second, we proposed a new pooling strategy for VLAD and three simple, efficient, and effective transformations for both FV and VLAD. Both proposed methods have shown higher accuracy than the original FV/VLAD method in extensive evaluations. Third, we proposed and evaluated new feature selection and compression methods for the FV and VLAD representations. This strategy uses only 4% of the storage of the original representation, but achieves comparable or even higher accuracy. Based on these contributions, we recommend a set of good practices for action recognition in videos for practitioners in this field.

Hamiltonian dynamics of vortex and magnetic lines in hydrodynamic type systems

NASA Astrophysics Data System (ADS)

Kuznetsov, E. A.; Ruban, V. P.

2000-01-01

Vortex line and magnetic line representations are introduced for a description of flows in ideal hydrodynamics and magnetohydrodynamics (MHD), respectively. For incompressible fluids, it is shown with the help of this transformation that the equations of motion for vorticity Ω and magnetic field follow from a variational principle. By means of this representation, it is possible to integrate the hydrodynamic type system with the Hamiltonian H=∫\\|Ω\\|dr and some other systems. It is also demonstrated that these representations allow one to remove from the noncanonical Poisson brackets, defined in the space of divergence-free vector fields, the degeneracy connected with the vorticity frozenness for the Euler equation and with magnetic field frozenness for ideal MHD. For MHD, a new Weber-type transformation is found. It is shown how this transformation can be obtained from the two-fluid model when electrons and ions can be considered as two independent fluids. The Weber-type transformation for ideal MHD gives the whole Lagrangian vector invariant. When this invariant is absent, this transformation coincides with the Clebsch representation analog introduced by V.E. Zakharov and E. A. Kuznetsov [Dokl. Ajad. Nauk 194, 1288 (1970) [Sov. Phys. Dokl. 15, 913 (1971)

Converting point-wise nuclear cross sections to pole representation using regularized vector fitting

NASA Astrophysics Data System (ADS)

Peng, Xingjie; Ducru, Pablo; Liu, Shichang; Forget, Benoit; Liang, Jingang; Smith, Kord

2018-03-01

Direct Doppler broadening of nuclear cross sections in Monte Carlo codes has been widely sought for coupled reactor simulations. One recent approach proposed analytical broadening using a pole representation of the commonly used resonance models and the introduction of a local windowing scheme to improve performance (Hwang, 1987; Forget et al., 2014; Josey et al., 2015, 2016). This pole representation has been achieved in the past by converting resonance parameters in the evaluation nuclear data library into poles and residues. However, cross sections of some isotopes are only provided as point-wise data in ENDF/B-VII.1 library. To convert these isotopes to pole representation, a recent approach has been proposed using the relaxed vector fitting (RVF) algorithm (Gustavsen and Semlyen, 1999; Gustavsen, 2006; Liu et al., 2018). This approach however needs to specify ahead of time the number of poles. This article addresses this issue by adding a poles and residues filtering step to the RVF procedure. This regularized VF (ReV-Fit) algorithm is shown to efficiently converge the poles close to the physical ones, eliminating most of the superfluous poles, and thus enabling the conversion of point-wise nuclear cross sections.

Bottom friction optimization for a better barotropic tide modelling

NASA Astrophysics Data System (ADS)

Boutet, Martial; Lathuilière, Cyril; Son Hoang, Hong; Baraille, Rémy

2015-04-01

At a regional scale, barotropic tides are the dominant source of variability of currents and water heights. A precise representation of these processes is essential because of their great impacts on human activities (submersion risks, marine renewable energies, ...). Identified sources of error for tide modelling at a regional scale are the followings: bathymetry, boundary forcing and dissipation due to bottom friction. Nevertheless, bathymetric databases are nowadays known with a good accuracy, especially over shelves, and global tide models performances are better than ever. The most promising improvement is thus the bottom friction representation. The method used to estimate bottom friction is the simultaneous perturbation stochastic approximation (SPSA) which consists in the approximation of the gradient based on a fixed number of cost function measurements, regardless of the dimension of the vector to be estimated. Indeed, each cost function measurement is obtained by randomly perturbing every component of the parameter vector. An important feature of SPSA is its relative ease of implementation. In particular, the method does not require the development of tangent linear and adjoint version of the circulation model. Experiments are carried out to estimate bottom friction with the HYbrid Coordinate Ocean Model (HYCOM) in barotropic mode (one isopycnal layer). The study area is the Northeastern Atlantic margin which is characterized by strong currents and an intense dissipation. Bottom friction is parameterized with a quadratic term and friction coefficient is computed with the water height and the bottom roughness. The latter parameter is the one to be estimated. Assimilated data are the available tide gauge observations. First, the bottom roughness is estimated taking into account bottom sediment natures and bathymetric ranges. Then, it is estimated with geographical degrees of freedom. Finally, the impact of the estimation of a mixed quadratic/linear friction is evaluated.

The Development of the Mental Representations of the Magnitude of Fractions

PubMed Central

Gabriel, Florence C.; Szucs, Denes; Content, Alain

2013-01-01

We investigated the development of the mental representation of the magnitude of fractions during the initial stages of fraction learning in grade 5, 6 and 7 children as well as in adults. We examined the activation of global fraction magnitude in a numerical comparison task and a matching task. There were global distance effects in the comparison task, but not in the matching task. This suggests that the activation of the global magnitude representation of fractions is not automatic in all tasks involving magnitude judgments. The slope of the global distance effect increased during early fraction learning and declined by adulthood, demonstrating that the development of the fraction global distance effect differs from that of the integer distance effect. PMID:24236169

Mapping higher-order relations between brain structure and function with embedded vector representations of connectomes.

PubMed

Rosenthal, Gideon; Váša, František; Griffa, Alessandra; Hagmann, Patric; Amico, Enrico; Goñi, Joaquín; Avidan, Galia; Sporns, Olaf

2018-06-05

Connectomics generates comprehensive maps of brain networks, represented as nodes and their pairwise connections. The functional roles of nodes are defined by their direct and indirect connectivity with the rest of the network. However, the network context is not directly accessible at the level of individual nodes. Similar problems in language processing have been addressed with algorithms such as word2vec that create embeddings of words and their relations in a meaningful low-dimensional vector space. Here we apply this approach to create embedded vector representations of brain networks or connectome embeddings (CE). CE can characterize correspondence relations among brain regions, and can be used to infer links that are lacking from the original structural diffusion imaging, e.g., inter-hemispheric homotopic connections. Moreover, we construct predictive deep models of functional and structural connectivity, and simulate network-wide lesion effects using the face processing system as our application domain. We suggest that CE offers a novel approach to revealing relations between connectome structure and function.

Open Source Software in Teaching Physics: A Case Study on Vector Algebra and Visual Representations

ERIC Educational Resources Information Center

Cataloglu, Erdat

2006-01-01

This study aims to report the effort on teaching vector algebra using free open source software (FOSS). Recent studies showed that students have difficulties in learning basic physics concepts. Constructivist learning theories suggest the use of visual and hands-on activities in learning. We will report on the software used for this purpose. The…

Use of vectors in sequence analysis.

PubMed

Ishikawa, T; Yamamoto, K; Yoshikura, H

1987-10-01

Applications of the vector diagram, a new type of representation of protein structure, in homology search of various proteins including oncogene products are presented. The method takes account of various kinds of information concerning the properties of amino acids, such as Chou and Fasman's probability data. The method can detect conformational similarities of proteins which may not be detected by the conventional programs.

Manga Vectorization and Manipulation with Procedural Simple Screentone.

PubMed

Yao, Chih-Yuan; Hung, Shih-Hsuan; Li, Guo-Wei; Chen, I-Yu; Adhitya, Reza; Lai, Yu-Chi

2017-02-01

Manga are a popular artistic form around the world, and artists use simple line drawing and screentone to create all kinds of interesting productions. Vectorization is helpful to digitally reproduce these elements for proper content and intention delivery on electronic devices. Therefore, this study aims at transforming scanned Manga to a vector representation for interactive manipulation and real-time rendering with arbitrary resolution. Our system first decomposes the patch into rough Manga elements including possible borders and shading regions using adaptive binarization and screentone detector. We classify detected screentone into simple and complex patterns: our system extracts simple screentone properties for refining screentone borders, estimating lighting, compensating missing strokes inside screentone regions, and later resolution independently rendering with our procedural shaders. Our system treats the others as complex screentone areas and vectorizes them with our proposed line tracer which aims at locating boundaries of all shading regions and polishing all shading borders with the curve-based Gaussian refiner. A user can lay down simple scribbles to cluster Manga elements intuitively for the formation of semantic components, and our system vectorizes these components into shading meshes along with embedded Bézier curves as a unified foundation for consistent manipulation including pattern manipulation, deformation, and lighting addition. Our system can real-time and resolution independently render the shading regions with our procedural shaders and drawing borders with the curve-based shader. For Manga manipulation, the proposed vector representation can be not only magnified without artifacts but also deformed easily to generate interesting results.

A combined representation method for use in band structure calculations. 1: Method

NASA Technical Reports Server (NTRS)

Friedli, C.; Ashcroft, N. W.

1975-01-01

A representation was described whose basis levels combine the important physical aspects of a finite set of plane waves with those of a set of Bloch tight-binding levels. The chosen combination has a particularly simple dependence on the wave vector within the Brillouin Zone, and its use in reducing the standard one-electron band structure problem to the usual secular equation has the advantage that the lattice sums involved in the calculation of the matrix elements are actually independent of the wave vector. For systems with complicated crystal structures, for which the Korringa-Kohn-Rostoker (KKR), Augmented-Plane Wave (APW) and Orthogonalized-Plane Wave (OPW) methods are difficult to apply, the present method leads to results with satisfactory accuracy and convergence.

E11, brane dynamics and duality symmetries

NASA Astrophysics Data System (ADS)

West, Peter

2018-05-01

Following arXiv:hep-th/0412336 we use the nonlinear realisation of the semi-direct product of E11 and its vector representation to construct brane dynamics. The brane moves through a space-time which arises in the nonlinear realisation from the vector representation and it contains the usual embedding coordinates as well as the worldvolume fields. The resulting equations of motion are first order in derivatives and can be thought of as duality relations. Each brane carries the full E11 symmetry and so the Cremmer-Julia duality symmetries. We apply this theory to find the dynamics of the IIA and IIB strings, the M2 and M5 branes, the IIB D3 brane as well as the one and two branes in seven dimensions.

Gauging hidden symmetries in two dimensions

NASA Astrophysics Data System (ADS)

Samtleben, Henning; Weidner, Martin

2007-08-01

We initiate the systematic construction of gauged matter-coupled supergravity theories in two dimensions. Subgroups of the affine global symmetry group of toroidally compactified supergravity can be gauged by coupling vector fields with minimal couplings and a particular topological term. The gauge groups typically include hidden symmetries that are not among the target-space isometries of the ungauged theory. The gaugings constructed in this paper are described group-theoretically in terms of a constant embedding tensor subject to a number of constraints which parametrizes the different theories and entirely encodes the gauged Lagrangian. The prime example is the bosonic sector of the maximally supersymmetric theory whose ungauged version admits an affine fraktur e9 global symmetry algebra. The various parameters (related to higher-dimensional p-form fluxes, geometric and non-geometric fluxes, etc.) which characterize the possible gaugings, combine into an embedding tensor transforming in the basic representation of fraktur e9. This yields an infinite-dimensional class of maximally supersymmetric theories in two dimensions. We work out and discuss several examples of higher-dimensional origin which can be systematically analyzed using the different gradings of fraktur e9.

A novel approach to modeling atmospheric convection

NASA Astrophysics Data System (ADS)

Goodman, A.

2016-12-01

The inadequate representation of clouds continues to be a large source of uncertainty in the projections from global climate models (GCMs). With continuous advances in computational power, however, the ability for GCMs to explicitly resolve cumulus convection will soon be realized. For this purpose, Jung and Arakawa (2008) proposed the Vector Vorticity Model (VVM), in which vorticity is the predicted variable instead of momentum. This has the advantage of eliminating the pressure gradient force within the framework of an anelastic system. However, the VVM was designed for use on a planar quadrilateral grid, making it unsuitable for implementation in global models discretized on the sphere. Here we have proposed a modification to the VVM where instead the curl of the horizontal vorticity is the primary predicted variable. This allows us to maintain the benefits of the original VVM while working within the constraints of a non-quadrilateral mesh. We found that our proposed model produced results from a warm bubble simulation that were consistent with the VVM. Further improvements that can be made to the VVM are also discussed.

Remote sensing, global warming, and vector-borne disease

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

Wood, B.; Beck, L.; Dister, S.

1997-12-31

The relationship between climate change and the pattern of vector-borne disease can be viewed at a variety of spatial and temporal scales. At one extreme are changes such as global warming, which are continental in scale and occur over periods of years, decades, or longer. At the opposite extreme are changes associated with severe weather events, which can occur at local and regional scales over periods of days, weeks, or months. Key ecological factors affecting the distribution of vector-borne diseases include temperature, precipitation, and habitat availability, and their impact on vectors, pathogens, reservoirs, and hosts. Global warming can potentially altermore » these factors, thereby affecting the spatial and temporal patterns of disease.« less

Health-related quality of life in patients with hepatocellular carcinoma: the mediation effects of illness perceptions and coping.

PubMed

Fan, Sheng-Yu; Eiser, Christine; Ho, Ming-Chih; Lin, Cheng-Yao

2013-06-01

The aims of this study were to explore health-related quality of life (HRQOL) in patients with hepatocellular carcinoma (HCC). We report the following: (1) differences in HRQOL between patients with HCC and the general population; (2) significant physical and psychological predictors of HRQOL; and (3) mediation effects of illness perceptions and coping on HRQOL. Patients with HCC (n = 286) from Taiwan completed standardized measures of HRQOL, illness perception (cognitive representations, emotional representations and illness comprehensibility) and coping (emotion-oriented and problem-orientation coping). Demographic and physical variables were also collected. Patients with HCC had worse global HRQOL, physical, role, cognitive and social functioning, but better emotional functioning than the general population. Physical variables and cognitive representation were significant predictors of global HRQOL, physical functioning and emotional functioning. Cognitive representation mediated the relationships between physical variables and global HRQOL, physical functioning and emotional functioning, but coping only mediated the relationship between cognitive representation and global HRQOL. The results suggest that physical variables have direct effects on global HRQOL and physical functioning, but there were also partial mediations through cognitive representation. The effect of physical variables on emotional functioning was mediated through cognitive and emotional representations. Patients with better performance status and positive illness perceptions tended to report better HRQOL, but those with negative illness perceptions and who used more emotion-oriented coping had worse HRQOL. Limitations of the work associated with use of theory and measures developed in Europe and the US are discussed, as are the clinical implications for patients with HCC. Copyright © 2012 John Wiley & Sons, Ltd.

A representation of solution of stochastic differential equations

NASA Astrophysics Data System (ADS)

Kim, Yoon Tae; Jeon, Jong Woo

2006-03-01

We prove that the logarithm of the formal power series, obtained from a stochastic differential equation, is an element in the closure of the Lie algebra generated by vector fields being coefficients of equations. By using this result, we obtain a representation of the solution of stochastic differential equations in terms of Lie brackets and iterated Stratonovich integrals in the algebra of formal power series.

From puddles to planet: modeling approaches to vector-borne diseases at varying resolution and scale.

PubMed

Eckhoff, Philip A; Bever, Caitlin A; Gerardin, Jaline; Wenger, Edward A; Smith, David L

2015-08-01

Since the original Ross-Macdonald formulations of vector-borne disease transmission, there has been a broad proliferation of mathematical models of vector-borne disease, but many of these models retain most to all of the simplifying assumptions of the original formulations. Recently, there has been a new expansion of mathematical frameworks that contain explicit representations of the vector life cycle including aquatic stages, multiple vector species, host heterogeneity in biting rate, realistic vector feeding behavior, and spatial heterogeneity. In particular, there are now multiple frameworks for spatially explicit dynamics with movements of vector, host, or both. These frameworks are flexible and powerful, but require additional data to take advantage of these features. For a given question posed, utilizing a range of models with varying complexity and assumptions can provide a deeper understanding of the answers derived from models. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Adeno-associated virus gene therapy vector scAAVIGF-I for transduction of equine articular chondrocytes and RNA-seq analysis.

PubMed

Hemphill, D D; McIlwraith, C W; Slayden, R A; Samulski, R J; Goodrich, L R

2016-05-01

IGF-I is one of several anabolic factors being investigated for the treatment of osteoarthritis (OA). Due to the short biological half-life, extended administration is required for more robust cartilage healing. Here we create a self-complimentary adeno-associated virus (AAV) gene therapy vector utilizing the transgene for IGF-I. Various biochemical assays were performed to investigate the cellular response to scAAVIGF-I treatment vs an scAAVGFP positive transduction control and a negative for transduction control culture. RNA-sequencing analysis was also performed to establish a differential regulation profile of scAAVIGF-I transduced chondrocytes. Biochemical analyses indicated an average media IGF-I concentration of 608 ng/ml in the scAAVIGF-I transduced chondrocytes. This increase in IGF-I led to increased expression of collagen type II and aggrecan and increased protein concentrations of cellular collagen type II and media glycosaminoglycan vs both controls. RNA-seq revealed a global regulatory pattern consisting of 113 differentially regulated GO categories including those for chondrocyte and cartilage development and regulation of apoptosis. This research substantiates that scAAVIGF-I gene therapy vector increased production of IGF-I to clinically relevant levels with a biological response by chondrocytes conducive to increased cartilage healing. The RNA-seq further established a set of differentially expressed genes and gene ontologies induced by the scAAVIGF-I vector while controlling for AAV infection. This dataset provides a static representation of the cellular transcriptome that, while only consisting of one time point, will allow for further gene expression analyses to compare additional cartilage healing therapeutics or a transient cellular response. Copyright © 2015. Published by Elsevier Ltd.

A phenomenological calculus of Wiener description space.

PubMed

Richardson, I W; Louie, A H

2007-10-01

The phenomenological calculus is a categorical example of Robert Rosen's modeling relation. This paper is an alligation of the phenomenological calculus and generalized harmonic analysis, another categorical example. Our epistemological exploration continues into the realm of Wiener description space, in which constitutive parameters are extended from vectors to vector-valued functions of a real variable. Inherent in the phenomenology are fundamental representations of time and nearness to equilibrium.

Context-Aware Local Binary Feature Learning for Face Recognition.

PubMed

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

2018-05-01

In this paper, we propose a context-aware local binary feature learning (CA-LBFL) method for face recognition. Unlike existing learning-based local face descriptors such as discriminant face descriptor (DFD) and compact binary face descriptor (CBFD) which learn each feature code individually, our CA-LBFL exploits the contextual information of adjacent bits by constraining the number of shifts from different binary bits, so that more robust information can be exploited for face representation. Given a face image, we first extract pixel difference vectors (PDV) in local patches, and learn a discriminative mapping in an unsupervised manner to project each pixel difference vector into a context-aware binary vector. Then, we perform clustering on the learned binary codes to construct a codebook, and extract a histogram feature for each face image with the learned codebook as the final representation. In order to exploit local information from different scales, we propose a context-aware local binary multi-scale feature learning (CA-LBMFL) method to jointly learn multiple projection matrices for face representation. To make the proposed methods applicable for heterogeneous face recognition, we present a coupled CA-LBFL (C-CA-LBFL) method and a coupled CA-LBMFL (C-CA-LBMFL) method to reduce the modality gap of corresponding heterogeneous faces in the feature level, respectively. Extensive experimental results on four widely used face datasets clearly show that our methods outperform most state-of-the-art face descriptors.

Heading-vector navigation based on head-direction cells and path integration.

PubMed

Kubie, John L; Fenton, André A

2009-05-01

Insect navigation is guided by heading vectors that are computed by path integration. Mammalian navigation models, on the other hand, are typically based on map-like place representations provided by hippocampal place cells. Such models compute optimal routes as a continuous series of locations that connect the current location to a goal. We propose a "heading-vector" model in which head-direction cells or their derivatives serve both as key elements in constructing the optimal route and as the straight-line guidance during route execution. The model is based on a memory structure termed the "shortcut matrix," which is constructed during the initial exploration of an environment when a set of shortcut vectors between sequential pairs of visited waypoint locations is stored. A mechanism is proposed for calculating and storing these vectors that relies on a hypothesized cell type termed an "accumulating head-direction cell." Following exploration, shortcut vectors connecting all pairs of waypoint locations are computed by vector arithmetic and stored in the shortcut matrix. On re-entry, when local view or place representations query the shortcut matrix with a current waypoint and goal, a shortcut trajectory is retrieved. Since the trajectory direction is in head-direction compass coordinates, navigation is accomplished by tracking the firing of head-direction cells that are tuned to the heading angle. Section 1 of the manuscript describes the properties of accumulating head-direction cells. It then shows how accumulating head-direction cells can store local vectors and perform vector arithmetic to perform path-integration-based homing. Section 2 describes the construction and use of the shortcut matrix for computing direct paths between any pair of locations that have been registered in the shortcut matrix. In the discussion, we analyze the advantages of heading-based navigation over map-based navigation. Finally, we survey behavioral evidence that nonhippocampal, heading-based navigation is used in small mammals and humans. Copyright 2008 Wiley-Liss, Inc.

Chemical ecology of animal and human pathogen vectors in a changing global climate.

PubMed

Pickett, John A; Birkett, Michael A; Dewhirst, Sarah Y; Logan, James G; Omolo, Maurice O; Torto, Baldwyn; Pelletier, Julien; Syed, Zainulabeuddin; Leal, Walter S

2010-01-01

Infectious diseases affecting livestock and human health that involve vector-borne pathogens are a global problem, unrestricted by borders or boundaries, which may be exacerbated by changing global climate. Thus, the availability of effective tools for control of pathogen vectors is of the utmost importance. The aim of this article is to review, selectively, current knowledge of the chemical ecology of pathogen vectors that affect livestock and human health in the developed and developing world, based on key note lectures presented in a symposium on "The Chemical Ecology of Disease Vectors" at the 25th Annual ISCE meeting in Neuchatel, Switzerland. The focus is on the deployment of semiochemicals for monitoring and control strategies, and discusses briefly future directions that such research should proceed along, bearing in mind the environmental challenges associated with climate change that we will face during the 21st century.

Drivers for the emergence and re-emergence of vector-borne protozoal and bacterial diseases.

PubMed

Harrus, S; Baneth, G

2005-10-01

In recent years, vector-borne parasitic and bacterial diseases have emerged or re-emerged in many geographical regions causing global health and economic problems that involve humans, livestock, companion animals and wild life. The ecology and epidemiology of vector-borne diseases are affected by the interrelations between three major factors comprising the pathogen, the host (human, animal or vector) and the environment. Important drivers for the emergence and spread of vector-borne parasites include habitat changes, alterations in water storage and irrigation habits, atmospheric and climate changes, immunosuppression by HIV, pollution, development of insecticide and drug resistance, globalization and the significant increase in international trade, tourism and travel. War and civil unrest, and governmental or global management failure are also major contributors to the spread of infectious diseases. The improvement of epidemic understanding and planning together with the development of new diagnostic molecular techniques in the last few decades have allowed researchers to better diagnose and trace pathogens, their origin and routes of infection, and to develop preventive public health and intervention programs. Health care workers, physicians, veterinarians and biosecurity officers should play a key role in future prevention of vector-borne diseases. A coordinated global approach for the prevention of vector-borne diseases should be implemented by international organizations and governmental agencies in collaboration with research institutions.

Vectorized Monte Carlo methods for reactor lattice analysis

NASA Technical Reports Server (NTRS)

Brown, F. B.

1984-01-01

Some of the new computational methods and equivalent mathematical representations of physics models used in the MCV code, a vectorized continuous-enery Monte Carlo code for use on the CYBER-205 computer are discussed. While the principal application of MCV is the neutronics analysis of repeating reactor lattices, the new methods used in MCV should be generally useful for vectorizing Monte Carlo for other applications. For background, a brief overview of the vector processing features of the CYBER-205 is included, followed by a discussion of the fundamentals of Monte Carlo vectorization. The physics models used in the MCV vectorized Monte Carlo code are then summarized. The new methods used in scattering analysis are presented along with details of several key, highly specialized computational routines. Finally, speedups relative to CDC-7600 scalar Monte Carlo are discussed.

Student Understanding of Cross Product Direction and Use of Right-hand Rules: An Exploration of Representation and Context-dependence

NASA Astrophysics Data System (ADS)

Kustusch, Mary Bridget

2011-12-01

Students in introductory physics struggle with vector algebra and with cross product direction in particular. Some have suggested that this may be due to misapplied right-hand rules, but there are few studies that have had the resolution to explore this. Additionally, previous research on student understanding has noted several kinds of representation-dependence of student performance with vector algebra in both physics and non-physics (or math) contexts (e.g. Hawkins et al., 2009; Van Deventer, 2008). Yet with few exceptions (e.g. Scaife and Heckler, 2010), these findings have not been applied to cross product direction questions or the use of right-hand rules. Also, the extensive work in spatial cognition is particularly applicable to cross product direction due to the spatial and kinesthetic nature of the right-hand rule. A synthesis of the literature from these various fields reveals four categories of problem features likely to impact the understanding of cross product direction: (1) the type of reasoning required, (2) the orientation of the vectors, (3) the need for parallel transport, and (4) the physics context and features (or lack thereof). These features formed the basis of the present effort to systematically explore the context-dependence and representation- dependence of student performance on cross product direction questions. This study used a mix of qualitative and quantitative techniques to analyze twenty-seven individual think-aloud interviews. During these interviews, second semester introductory physics students answered 80-100 cross product direction questions in different contexts and with varying problem features. These features were then used as the predictors in regression analyses for correctness and response time. In addition, each problem was coded for the methods used and the errors made to gain a deeper understanding of student behavior and the impact of these features. The results revealed a wide variety of methods (including six different right-hand rules), many different types of errors, and significant context-dependence and representation-dependence for the features mentioned above. Problems that required reasoning backward to find A⃗ (for C⃗=A⃗ xB⃗ ) presented the biggest challenge for students. Participants who recognized the non-commutativity of the cross product would often reverse the order ( B⃗xA⃗ ) on these problems. Also, this error occurred less frequently when a Guess and Check method was used in addition to the right-hand rule. Three different aspects of orientation had a significant impact on performance: (1) the physical discomfort of using a right-hand rule, (2) the plane of the given vectors, and to a lesser extent, (3) the angle between the vectors. One participant was more likely to switch the order of the vectors for the physically awkward orientations than for the physically easy orientations; and there was evidence that some of the difficulty with vector orientations that were not in the xy-plane was due to misinterpretations of the into and out of the page symbols. The impact of both physical discomfort and the plane of the vectors was reduced when participants rotated the paper. Unlike other problem features, the issue of parallel transport did not appear to be nearly as prevalent for cross product direction as it is for vector addition and subtraction. In addition to these findings, this study confirmed earlier findings regarding physics difficulties with magnetic field and magnetic force, such as differences in performance based on the representation of magnetic field (Scaife and Heckler, 2010) and confusion between electric and magnetic fields (Maloney et al., 2001). It also provided evidence of physics difficulties with magnetic field and magnetic force that have been suspected but never explored, specifically the impact of the sign of the charge and the observation location. This study demonstrated that student difficulty with cross product direction is not as simple as misapplied right-hand rules, although this is an issue. Student behavior on cross product direction questions is significantly dependent on both the context of the question and the representation of various problem features. Although more research is necessary, particularly in regard to individual differences, this study represents a significant step forward in our understanding of student difficulties with cross product direction.

Software tool for data mining and its applications

NASA Astrophysics Data System (ADS)

Yang, Jie; Ye, Chenzhou; Chen, Nianyi

2002-03-01

A software tool for data mining is introduced, which integrates pattern recognition (PCA, Fisher, clustering, hyperenvelop, regression), artificial intelligence (knowledge representation, decision trees), statistical learning (rough set, support vector machine), computational intelligence (neural network, genetic algorithm, fuzzy systems). It consists of nine function models: pattern recognition, decision trees, association rule, fuzzy rule, neural network, genetic algorithm, Hyper Envelop, support vector machine, visualization. The principle and knowledge representation of some function models of data mining are described. The software tool of data mining is realized by Visual C++ under Windows 2000. Nonmonotony in data mining is dealt with by concept hierarchy and layered mining. The software tool of data mining has satisfactorily applied in the prediction of regularities of the formation of ternary intermetallic compounds in alloy systems, and diagnosis of brain glioma.

A path-oriented matrix-based knowledge representation system

NASA Technical Reports Server (NTRS)

Feyock, Stefan; Karamouzis, Stamos T.

1993-01-01

Experience has shown that designing a good representation is often the key to turning hard problems into simple ones. Most AI (Artificial Intelligence) search/representation techniques are oriented toward an infinite domain of objects and arbitrary relations among them. In reality much of what needs to be represented in AI can be expressed using a finite domain and unary or binary predicates. Well-known vector- and matrix-based representations can efficiently represent finite domains and unary/binary predicates, and allow effective extraction of path information by generalized transitive closure/path matrix computations. In order to avoid space limitations a set of abstract sparse matrix data types was developed along with a set of operations on them. This representation forms the basis of an intelligent information system for representing and manipulating relational data.

Global Change and Human Vulnerability to Vector-Borne Diseases

PubMed Central

Sutherst, Robert W.

2004-01-01

Global change includes climate change and climate variability, land use, water storage and irrigation, human population growth and urbanization, trade and travel, and chemical pollution. Impacts on vector-borne diseases, including malaria, dengue fever, infections by other arboviruses, schistosomiasis, trypanosomiasis, onchocerciasis, and leishmaniasis are reviewed. While climate change is global in nature and poses unknown future risks to humans and natural ecosystems, other local changes are occurring more rapidly on a global scale and are having significant effects on vector-borne diseases. History is invaluable as a pointer to future risks, but direct extrapolation is no longer possible because the climate is changing. Researchers are therefore embracing computer simulation models and global change scenarios to explore the risks. Credible ranking of the extent to which different vector-borne diseases will be affected awaits a rigorous analysis. Adaptation to the changes is threatened by the ongoing loss of drugs and pesticides due to the selection of resistant strains of pathogens and vectors. The vulnerability of communities to the changes in impacts depends on their adaptive capacity, which requires both appropriate technology and responsive public health systems. The availability of resources in turn depends on social stability, economic wealth, and priority allocation of resources to public health. PMID:14726459

Reconstructing householder vectors from Tall-Skinny QR

DOE PAGES

Ballard, Grey Malone; Demmel, James; Grigori, Laura; ...

2015-08-05

The Tall-Skinny QR (TSQR) algorithm is more communication efficient than the standard Householder algorithm for QR decomposition of matrices with many more rows than columns. However, TSQR produces a different representation of the orthogonal factor and therefore requires more software development to support the new representation. Further, implicitly applying the orthogonal factor to the trailing matrix in the context of factoring a square matrix is more complicated and costly than with the Householder representation. We show how to perform TSQR and then reconstruct the Householder vector representation with the same asymptotic communication efficiency and little extra computational cost. We demonstratemore » the high performance and numerical stability of this algorithm both theoretically and empirically. The new Householder reconstruction algorithm allows us to design more efficient parallel QR algorithms, with significantly lower latency cost compared to Householder QR and lower bandwidth and latency costs compared with Communication-Avoiding QR (CAQR) algorithm. Experiments on supercomputers demonstrate the benefits of the communication cost improvements: in particular, our experiments show substantial improvements over tuned library implementations for tall-and-skinny matrices. Furthermore, we also provide algorithmic improvements to the Householder QR and CAQR algorithms, and we investigate several alternatives to the Householder reconstruction algorithm that sacrifice guarantees on numerical stability in some cases in order to obtain higher performance.« less

Compressing interpreted satellite imagery for geographic information systems applications over extensive regions

USGS Publications Warehouse

Miller, Stephan W.

1981-01-01

A second set of related problems deals with how this format and other representations of spatial entities, such as vector formats for point and line features, can be interrelated for manipulation, retrieval, and analysis by a spatial database management subsystem. Methods have been developed for interrelating areal data sets in the raster format with point and line data in a vector format and these are described.

Implementation of a fast digital optical matrix-vector multiplier using a holographic look-up table and residue arithmetic

NASA Technical Reports Server (NTRS)

Habiby, Sarry F.; Collins, Stuart A., Jr.

1987-01-01

The design and implementation of a digital (numerical) optical matrix-vector multiplier are presented. A Hughes liquid crystal light valve, the residue arithmetic representation, and a holographic optical memory are used to construct position coded optical look-up tables. All operations are performed in effectively one light valve response time with a potential for a high information density.

Implementation of a fast digital optical matrix-vector multiplier using a holographic look-up table and residue arithmetic.

PubMed

Habiby, S F; Collins, S A

1987-11-01

The design and implementation of a digital (numerical) optical matrix-vector multiplier are presented. A Hughes liquid crystal light valve, the residue arithmetic representation, and a holographic optical memory are used to construct position coded optical look-up tables. All operations are performed in effectively one light valve response time with a potential for a high information density.

DYMAFLEX: DYnamic Manipulation FLight EXperiment

DTIC Science & Technology

2013-09-03

thrust per nozzle and minimize propellant mass and tank mass. This study compared carbon dioxide, nitrous oxide, and R134-A. These results were...equations of mo- tion of a space manipulator, showing their top- level, matrix- vector representation to be of iden- tical form to those of a fixed-base...the system inertia matrix, q is the po- sition state vector (consisting of the manipulator joint angles θ, spacecraft attitude quaternion, and

Hydrological and geomorphological controls of malaria transmission

NASA Astrophysics Data System (ADS)

Smith, M. W.; Macklin, M. G.; Thomas, C. J.

2013-01-01

Malaria risk is linked inextricably to the hydrological and geomorphological processes that form vector breeding sites. Yet environmental controls of malaria transmission are often represented by temperature and rainfall amounts, ignoring hydrological and geomorphological influences altogether. Continental-scale studies incorporate hydrology implicitly through simple minimum rainfall thresholds, while community-scale coupled hydrological and entomological models do not represent the actual diversity of the mosquito vector breeding sites. The greatest range of malaria transmission responses to environmental factors is observed at the catchment scale where seemingly contradictory associations between rainfall and malaria risk can be explained by hydrological and geomorphological processes that govern surface water body formation and persistence. This paper extends recent efforts to incorporate ecological factors into malaria-risk models, proposing that the same detailed representation be afforded to hydrological and, at longer timescales relevant for predictions of climate change impacts, geomorphological processes. We review existing representations of environmental controls of malaria and identify a range of hydrologically distinct vector breeding sites from existing literature. We illustrate the potential complexity of interactions among hydrology, geomorphology and vector breeding sites by classifying a range of water bodies observed in a catchment in East Africa. Crucially, the mechanisms driving surface water body formation and destruction must be considered explicitly if we are to produce dynamic spatial models of malaria risk at catchment scales.

Basic-level and superordinate-like categorical representations in early infancy.

PubMed

Behl-Chadha, G

1996-08-01

A series of experiments using the paired-preference procedure examined 3- to 4-month-old infants' ability to form perceptually based categorical representations in the domains of natural kinds and artifacts and probed the underlying organizational structure of these representations. Experiments 1 and 2 found that infants could form categorical representations for chairs that excluded exemplars of couches, beds, and tables and also for couches that excluded exemplars of chairs, beds, and tables. Thus, the adult-like exclusivity shown by infants in the categorization of various animal pictures at the basic-level extends to the domain of artifacts as well--an ecologically significant ability given the numerous artifacts that populate the human environment. Experiments 3 and 4 examined infants' ability to form superordinate-like or global categorical representations for mammals and furniture. It was found that infants could form a global representation for mammals that included novel mammals and excluded other non-mammalian animals such as birds and fish as well as items from cross-ontological categories such as furniture. In addition, it was found that infants formed a representation for furniture that included novel categories of furniture and excluded exemplars from the cross-ontological category of mammals; however, it was less clear if infants' global representation for furniture also excluded other artifacts such as vehicles and thus the category of furniture may have been less exclusively represented. Overall, the present findings, by showing the availability of perceptually driven basic and superordinate-like representations in early infancy that closely correspond to adult conceptual categories, underscore the importance of these early representations for later conceptual representations.

Attitude Representations for Kalman Filtering

NASA Technical Reports Server (NTRS)

Markley, F. Landis; Bauer, Frank H. (Technical Monitor)

2001-01-01

The four-component quaternion has the lowest dimensionality possible for a globally nonsingular attitude representation, it represents the attitude matrix as a homogeneous quadratic function, and its dynamic propagation equation is bilinear in the quaternion and the angular velocity. The quaternion is required to obey a unit norm constraint, though, so Kalman filters often employ a quaternion for the global attitude estimate and a three-component representation for small errors about the estimate. We consider these mixed attitude representations for both a first-order Extended Kalman filter and a second-order filter, as well for quaternion-norm-preserving attitude propagation.

The Application of Auto-Disturbance Rejection Control Optimized by Least Squares Support Vector Machines Method and Time-Frequency Representation in Voltage Source Converter-High Voltage Direct Current System.

PubMed

Liu, Ying-Pei; Liang, Hai-Ping; Gao, Zhong-Ke

2015-01-01

In order to improve the performance of voltage source converter-high voltage direct current (VSC-HVDC) system, we propose an improved auto-disturbance rejection control (ADRC) method based on least squares support vector machines (LSSVM) in the rectifier side. Firstly, we deduce the high frequency transient mathematical model of VSC-HVDC system. Then we investigate the ADRC and LSSVM principles. We ignore the tracking differentiator in the ADRC controller aiming to improve the system dynamic response speed. On this basis, we derive the mathematical model of ADRC controller optimized by LSSVM for direct current voltage loop. Finally we carry out simulations to verify the feasibility and effectiveness of our proposed control method. In addition, we employ the time-frequency representation methods, i.e., Wigner-Ville distribution (WVD) and adaptive optimal kernel (AOK) time-frequency representation, to demonstrate our proposed method performs better than the traditional method from the perspective of energy distribution in time and frequency plane.

The Application of Auto-Disturbance Rejection Control Optimized by Least Squares Support Vector Machines Method and Time-Frequency Representation in Voltage Source Converter-High Voltage Direct Current System

PubMed Central

Gao, Zhong-Ke

2015-01-01

In order to improve the performance of voltage source converter-high voltage direct current (VSC-HVDC) system, we propose an improved auto-disturbance rejection control (ADRC) method based on least squares support vector machines (LSSVM) in the rectifier side. Firstly, we deduce the high frequency transient mathematical model of VSC-HVDC system. Then we investigate the ADRC and LSSVM principles. We ignore the tracking differentiator in the ADRC controller aiming to improve the system dynamic response speed. On this basis, we derive the mathematical model of ADRC controller optimized by LSSVM for direct current voltage loop. Finally we carry out simulations to verify the feasibility and effectiveness of our proposed control method. In addition, we employ the time-frequency representation methods, i.e., Wigner-Ville distribution (WVD) and adaptive optimal kernel (AOK) time-frequency representation, to demonstrate our proposed method performs better than the traditional method from the perspective of energy distribution in time and frequency plane. PMID:26098556

Agricultural mapping using Support Vector Machine-Based Endmember Extraction (SVM-BEE)

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

Archibald, Richard K; Filippi, Anthony M; Bhaduri, Budhendra L

Extracting endmembers from remotely sensed images of vegetated areas can present difficulties. In this research, we applied a recently developed endmember-extraction algorithm based on Support Vector Machines (SVMs) to the problem of semi-autonomous estimation of vegetation endmembers from a hyperspectral image. This algorithm, referred to as Support Vector Machine-Based Endmember Extraction (SVM-BEE), accurately and rapidly yields a computed representation of hyperspectral data that can accommodate multiple distributions. The number of distributions is identified without prior knowledge, based upon this representation. Prior work established that SVM-BEE is robustly noise-tolerant and can semi-automatically and effectively estimate endmembers; synthetic data and a geologicmore » scene were previously analyzed. Here we compared the efficacies of the SVM-BEE and N-FINDR algorithms in extracting endmembers from a predominantly agricultural scene. SVM-BEE was able to estimate vegetation and other endmembers for all classes in the image, which N-FINDR failed to do. Classifications based on SVM-BEE endmembers were markedly more accurate compared with those based on N-FINDR endmembers.« less

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

Webb-Robertson, Bobbie-Jo M.

Accurate identification of peptides is a current challenge in mass spectrometry (MS) based proteomics. The standard approach uses a search routine to compare tandem mass spectra to a database of peptides associated with the target organism. These database search routines yield multiple metrics associated with the quality of the mapping of the experimental spectrum to the theoretical spectrum of a peptide. The structure of these results make separating correct from false identifications difficult and has created a false identification problem. Statistical confidence scores are an approach to battle this false positive problem that has led to significant improvements in peptidemore » identification. We have shown that machine learning, specifically support vector machine (SVM), is an effective approach to separating true peptide identifications from false ones. The SVM-based peptide statistical scoring method transforms a peptide into a vector representation based on database search metrics to train and validate the SVM. In practice, following the database search routine, a peptides is denoted in its vector representation and the SVM generates a single statistical score that is then used to classify presence or absence in the sample« less

Local structure-based image decomposition for feature extraction with applications to face recognition.

PubMed

Qian, Jianjun; Yang, Jian; Xu, Yong

2013-09-01

This paper presents a robust but simple image feature extraction method, called image decomposition based on local structure (IDLS). It is assumed that in the local window of an image, the macro-pixel (patch) of the central pixel, and those of its neighbors, are locally linear. IDLS captures the local structural information by describing the relationship between the central macro-pixel and its neighbors. This relationship is represented with the linear representation coefficients determined using ridge regression. One image is actually decomposed into a series of sub-images (also called structure images) according to a local structure feature vector. All the structure images, after being down-sampled for dimensionality reduction, are concatenated into one super-vector. Fisher linear discriminant analysis is then used to provide a low-dimensional, compact, and discriminative representation for each super-vector. The proposed method is applied to face recognition and examined using our real-world face image database, NUST-RWFR, and five popular, publicly available, benchmark face image databases (AR, Extended Yale B, PIE, FERET, and LFW). Experimental results show the performance advantages of IDLS over state-of-the-art algorithms.

Detecting objects in radiographs for homeland security

NASA Astrophysics Data System (ADS)

Prasad, Lakshman; Snyder, Hans

2005-05-01

We present a general scheme for segmenting a radiographic image into polygons that correspond to visual features. This decomposition provides a vectorized representation that is a high-level description of the image. The polygons correspond to objects or object parts present in the image. This characterization of radiographs allows the direct application of several shape recognition algorithms to identify objects. In this paper we describe the use of constrained Delaunay triangulations as a uniform foundational tool to achieve multiple visual tasks, namely image segmentation, shape decomposition, and parts-based shape matching. Shape decomposition yields parts that serve as tokens representing local shape characteristics. Parts-based shape matching enables the recognition of objects in the presence of occlusions, which commonly occur in radiographs. The polygonal representation of image features affords the efficient design and application of sophisticated geometric filtering methods to detect large-scale structural properties of objects in images. Finally, the representation of radiographs via polygons results in significant reduction of image file sizes and permits the scalable graphical representation of images, along with annotations of detected objects, in the SVG (scalable vector graphics) format that is proposed by the world wide web consortium (W3C). This is a textual representation that can be compressed and encrypted for efficient and secure transmission of information over wireless channels and on the Internet. In particular, our methods described here provide an algorithmic framework for developing image analysis tools for screening cargo at ports of entry for homeland security.

Deterministic binary vectors for efficient automated indexing of MEDLINE/PubMed abstracts.

PubMed

Wahle, Manuel; Widdows, Dominic; Herskovic, Jorge R; Bernstam, Elmer V; Cohen, Trevor

2012-01-01

The need to maintain accessibility of the biomedical literature has led to development of methods to assist human indexers by recommending index terms for newly encountered articles. Given the rapid expansion of this literature, it is essential that these methods be scalable. Document vector representations are commonly used for automated indexing, and Random Indexing (RI) provides the means to generate them efficiently. However, RI is difficult to implement in real-world indexing systems, as (1) efficient nearest-neighbor search requires retaining all document vectors in RAM, and (2) it is necessary to maintain a store of randomly generated term vectors to index future documents. Motivated by these concerns, this paper documents the development and evaluation of a deterministic binary variant of RI. The increased capacity demonstrated by binary vectors has implications for information retrieval, and the elimination of the need to retain term vectors facilitates distributed implementations, enhancing the scalability of RI.

Deterministic Binary Vectors for Efficient Automated Indexing of MEDLINE/PubMed Abstracts

PubMed Central

Wahle, Manuel; Widdows, Dominic; Herskovic, Jorge R.; Bernstam, Elmer V.; Cohen, Trevor

2012-01-01

The need to maintain accessibility of the biomedical literature has led to development of methods to assist human indexers by recommending index terms for newly encountered articles. Given the rapid expansion of this literature, it is essential that these methods be scalable. Document vector representations are commonly used for automated indexing, and Random Indexing (RI) provides the means to generate them efficiently. However, RI is difficult to implement in real-world indexing systems, as (1) efficient nearest-neighbor search requires retaining all document vectors in RAM, and (2) it is necessary to maintain a store of randomly generated term vectors to index future documents. Motivated by these concerns, this paper documents the development and evaluation of a deterministic binary variant of RI. The increased capacity demonstrated by binary vectors has implications for information retrieval, and the elimination of the need to retain term vectors facilitates distributed implementations, enhancing the scalability of RI. PMID:23304369

Global Positioning Systems (GPS) Technology to Study Vector-Pathogen-Host Interactions

DTIC Science & Technology

2012-10-26

viruses and vectors isolated over different geographic regions promote understanding of virus-vector co-evolution and the impact on dengue virus...AFRIMS Virology field site in KPP to be a participant in a regional phase 3 dengue vaccine efficacy trial. The trial is scheduled to begin in 2Q...important human pathogen producing severe illness known as dengue hemorrhagic fever (DHF). Dengue is considered an emerged global public health

Global Positioning Systems (GPS) Technology to Study Vector-Pathogen-Host Interactions

DTIC Science & Technology

2016-12-01

Award Number: W81XWH-11-2-0175 TITLE: Global Positioning Systems (GPS) Technology to Study Vector-Pathogen-Host Interactions PRINCIPAL...Positioning Systems (GPS) Technology to Study Vector-Pathogen-Host Interactions 5b. GRANT NUMBER W81XWH-11-2-0175 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S...objective of this project is to examine the evolutionary consequences of introducing a tetravalent live- attenuated dengue virus vaccine into children in

An accessible four-dimensional treatment of Maxwell's equations in terms of differential forms

NASA Astrophysics Data System (ADS)

Sá, Lucas

2017-03-01

Maxwell’s equations are derived in terms of differential forms in the four-dimensional Minkowski representation, starting from the three-dimensional vector calculus differential version of these equations. Introducing all the mathematical and physical concepts needed (including the tool of differential forms), using only knowledge of elementary vector calculus and the local vector version of Maxwell’s equations, the equations are reduced to a simple and elegant set of two equations for a unified quantity, the electromagnetic field. The treatment should be accessible for students taking a first course on electromagnetism.

Automatic PSO-Based Deformable Structures Markerless Tracking in Laparoscopic Cholecystectomy

NASA Astrophysics Data System (ADS)

Djaghloul, Haroun; Batouche, Mohammed; Jessel, Jean-Pierre

An automatic and markerless tracking method of deformable structures (digestive organs) during laparoscopic cholecystectomy intervention that uses the (PSO) behavour and the preoperative a priori knowledge is presented. The associated shape to the global best particles of the population determines a coarse representation of the targeted organ (the gallbladder) in monocular laparoscopic colored images. The swarm behavour is directed by a new fitness function to be optimized to improve the detection and tracking performance. The function is defined by a linear combination of two terms, namely, the human a priori knowledge term (H) and the particle's density term (D). Under the limits of standard (PSO) characteristics, experimental results on both synthetic and real data show the effectiveness and robustness of our method. Indeed, it outperforms existing methods without need of explicit initialization (such as active contours, deformable models and Gradient Vector Flow) on accuracy and convergence rate.

Excited states of 4He

NASA Astrophysics Data System (ADS)

Aoyama, Shigeyoshi

2013-04-01

The study of the 4He nucleus is important because it is the most basic sub-unit (cluster) in nuclei. We have investigated the structures and the reaction mechanisms in 4He by using the correlated Gaussian basis function with the global vector representation. In order to treat the boundary condition for the ab-initio calculation of the four nucleons, we employ the Microscopic R-matrix Method (MRM) and the Complex Scaling Method (CSM) . Elastic-scattering phase shifts for four-nucleon systems are studied in an ab-initio type cluster model with MRM in order to clarify the role of the tensor force and to investigate cluster distortions in low energy d+d and t+p scattering. For 1S0, the calculated phase shifts show that the t+p and h+n channels are strongly coupled to the d+d channel for the case of the realistic interaction.

Calculations of rate constants for the three-body recombination of H2 in the presence of H2

NASA Technical Reports Server (NTRS)

Schwenke, David W.

1988-01-01

A new global potential energy hypersurface for H2 + H2 is constructed and quasiclassical trajectory calculations performed using the resonance complex theory and energy transfer mechanism to estimate the rate of three body recombination over the temperature range 100 to 5000 K. The new potential is a faithful representation of ab initio electron structure calculations, is unchanged under the operation of exchanging H atoms, and reproduces the accurate H3 potential as one H atom is pulled away. Included in the fitting procedure are geometries expected to be important when one H2 is near or above the dissociation limit. The dynamics calculations explicitly include the motion of all four atoms and are performed efficiently using a vectorized variable-stepsize integrator. The predicted rate constants are approximately a factor of two smaller than experimental estimates over a broad temperature range.

Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties

NASA Astrophysics Data System (ADS)

Xie, Tian; Grossman, Jeffrey C.

2018-04-01

The use of machine learning methods for accelerating the design of crystalline materials usually requires manually constructed feature vectors or complex transformation of atom coordinates to input the crystal structure, which either constrains the model to certain crystal types or makes it difficult to provide chemical insights. Here, we develop a crystal graph convolutional neural networks framework to directly learn material properties from the connection of atoms in the crystal, providing a universal and interpretable representation of crystalline materials. Our method provides a highly accurate prediction of density functional theory calculated properties for eight different properties of crystals with various structure types and compositions after being trained with 1 04 data points. Further, our framework is interpretable because one can extract the contributions from local chemical environments to global properties. Using an example of perovskites, we show how this information can be utilized to discover empirical rules for materials design.

Finger vein recognition with personalized feature selection.

PubMed

Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Meng, Xianjing

2013-08-22

Finger veins are a promising biometric pattern for personalized identification in terms of their advantages over existing biometrics. Based on the spatial pyramid representation and the combination of more effective information such as gray, texture and shape, this paper proposes a simple but powerful feature, called Pyramid Histograms of Gray, Texture and Orientation Gradients (PHGTOG). For a finger vein image, PHGTOG can reflect the global spatial layout and local details of gray, texture and shape. To further improve the recognition performance and reduce the computational complexity, we select a personalized subset of features from PHGTOG for each subject by using the sparse weight vector, which is trained by using LASSO and called PFS-PHGTOG. We conduct extensive experiments to demonstrate the promise of the PHGTOG and PFS-PHGTOG, experimental results on our databases show that PHGTOG outperforms the other existing features. Moreover, PFS-PHGTOG can further boost the performance in comparison with PHGTOG.

Finger Vein Recognition with Personalized Feature Selection

PubMed Central

Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Meng, Xianjing

2013-01-01

Finger veins are a promising biometric pattern for personalized identification in terms of their advantages over existing biometrics. Based on the spatial pyramid representation and the combination of more effective information such as gray, texture and shape, this paper proposes a simple but powerful feature, called Pyramid Histograms of Gray, Texture and Orientation Gradients (PHGTOG). For a finger vein image, PHGTOG can reflect the global spatial layout and local details of gray, texture and shape. To further improve the recognition performance and reduce the computational complexity, we select a personalized subset of features from PHGTOG for each subject by using the sparse weight vector, which is trained by using LASSO and called PFS-PHGTOG. We conduct extensive experiments to demonstrate the promise of the PHGTOG and PFS-PHGTOG, experimental results on our databases show that PHGTOG outperforms the other existing features. Moreover, PFS-PHGTOG can further boost the performance in comparison with PHGTOG. PMID:23974154

Dissociable cognitive mechanisms underlying human path integration.

PubMed

Wiener, Jan M; Berthoz, Alain; Wolbers, Thomas

2011-01-01

Path integration is a fundamental mechanism of spatial navigation. In non-human species, it is assumed to be an online process in which a homing vector is updated continuously during an outward journey. In contrast, human path integration has been conceptualized as a configural process in which travelers store working memory representations of path segments, with the computation of a homing vector only occurring when required. To resolve this apparent discrepancy, we tested whether humans can employ different path integration strategies in the same task. Using a triangle completion paradigm, participants were instructed either to continuously update the start position during locomotion (continuous strategy) or to remember the shape of the outbound path and to calculate home vectors on basis of this representation (configural strategy). While overall homing accuracy was superior in the configural condition, participants were quicker to respond during continuous updating, strongly suggesting that homing vectors were computed online. Corroborating these findings, we observed reliable differences in head orientation during the outbound path: when participants applied the continuous updating strategy, the head deviated significantly from straight ahead in direction of the start place, which can be interpreted as a continuous motor expression of the homing vector. Head orientation-a novel online measure for path integration-can thus inform about the underlying updating mechanism already during locomotion. In addition to demonstrating that humans can employ different cognitive strategies during path integration, our two-systems view helps to resolve recent controversies regarding the role of the medial temporal lobe in human path integration.

Multiple-stage ambiguity in motion perception reveals global computation of local motion directions.

PubMed

Rider, Andrew T; Nishida, Shin'ya; Johnston, Alan

2016-12-01

The motion of a 1D image feature, such as a line, seen through a small aperture, or the small receptive field of a neural motion sensor, is underconstrained, and it is not possible to derive the true motion direction from a single local measurement. This is referred to as the aperture problem. How the visual system solves the aperture problem is a fundamental question in visual motion research. In the estimation of motion vectors through integration of ambiguous local motion measurements at different positions, conventional theories assume that the object motion is a rigid translation, with motion signals sharing a common motion vector within the spatial region over which the aperture problem is solved. However, this strategy fails for global rotation. Here we show that the human visual system can estimate global rotation directly through spatial pooling of locally ambiguous measurements, without an intervening step that computes local motion vectors. We designed a novel ambiguous global flow stimulus, which is globally as well as locally ambiguous. The global ambiguity implies that the stimulus is simultaneously consistent with both a global rigid translation and an infinite number of global rigid rotations. By the standard view, the motion should always be seen as a global translation, but it appears to shift from translation to rotation as observers shift fixation. This finding indicates that the visual system can estimate local vectors using a global rotation constraint, and suggests that local motion ambiguity may not be resolved until consistencies with multiple global motion patterns are assessed.

Modeling the impact of global warming on vector-borne infections

NASA Astrophysics Data System (ADS)

Massad, Eduardo; Coutinho, Francisco Antonio Bezerra; Lopez, Luis Fernandez; da Silva, Daniel Rodrigues

2011-06-01

Global warming will certainly affect the abundance and distribution of disease vectors. The effect of global warming, however, depends on the complex interaction between the human host population and the causative infectious agent. In this work we review some mathematical models that were proposed to study the impact of the increase in ambient temperature on the spread and gravity of some insect-transmitted diseases.

Visualizing Vector Fields Using Line Integral Convolution and Dye Advection

NASA Technical Reports Server (NTRS)

Shen, Han-Wei; Johnson, Christopher R.; Ma, Kwan-Liu

1996-01-01

We present local and global techniques to visualize three-dimensional vector field data. Using the Line Integral Convolution (LIC) method to image the global vector field, our new algorithm allows the user to introduce colored 'dye' into the vector field to highlight local flow features. A fast algorithm is proposed that quickly recomputes the dyed LIC images. In addition, we introduce volume rendering methods that can map the LIC texture on any contour surface and/or translucent region defined by additional scalar quantities, and can follow the advection of colored dye throughout the volume.

Logarithmic M(2,p) minimal models, their logarithmic couplings, and duality

NASA Astrophysics Data System (ADS)

Mathieu, Pierre; Ridout, David

2008-10-01

A natural construction of the logarithmic extension of the M(2,p) (chiral) minimal models is presented, which generalises our previous model of percolation ( p=3). Its key aspect is the replacement of the minimal model irreducible modules by reducible ones obtained by requiring that only one of the two principal singular vectors of each module vanish. The resulting theory is then constructed systematically by repeatedly fusing these building block representations. This generates indecomposable representations of the type which signify the presence of logarithmic partner fields in the theory. The basic data characterising these indecomposable modules, the logarithmic couplings, are computed for many special cases and given a new structural interpretation. Quite remarkably, a number of them are presented in closed analytic form (for general p). These are the prime examples of "gauge-invariant" data—quantities independent of the ambiguities present in defining the logarithmic partner fields. Finally, mere global conformal invariance is shown to enforce strong constraints on the allowed spectrum: It is not possible to include modules other than those generated by the fusion of the model's building blocks. This generalises the statement that there cannot exist two effective central charges in a c=0 model. It also suggests the existence of a second "dual" logarithmic theory for each p. Such dual models are briefly discussed.

A Distributed-Memory Package for Dense Hierarchically Semi-Separable Matrix Computations Using Randomization

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

Rouet, François-Henry; Li, Xiaoye S.; Ghysels, Pieter

In this paper, we present a distributed-memory library for computations with dense structured matrices. A matrix is considered structured if its off-diagonal blocks can be approximated by a rank-deficient matrix with low numerical rank. Here, we use Hierarchically Semi-Separable (HSS) representations. Such matrices appear in many applications, for example, finite-element methods, boundary element methods, and so on. Exploiting this structure allows for fast solution of linear systems and/or fast computation of matrix-vector products, which are the two main building blocks of matrix computations. The compression algorithm that we use, that computes the HSS form of an input dense matrix, reliesmore » on randomized sampling with a novel adaptive sampling mechanism. We discuss the parallelization of this algorithm and also present the parallelization of structured matrix-vector product, structured factorization, and solution routines. The efficiency of the approach is demonstrated on large problems from different academic and industrial applications, on up to 8,000 cores. Finally, this work is part of a more global effort, the STRUctured Matrices PACKage (STRUMPACK) software package for computations with sparse and dense structured matrices. Hence, although useful on their own right, the routines also represent a step in the direction of a distributed-memory sparse solver.« less

A Distributed-Memory Package for Dense Hierarchically Semi-Separable Matrix Computations Using Randomization

DOE PAGES

Rouet, François-Henry; Li, Xiaoye S.; Ghysels, Pieter; ...

2016-06-30

In this paper, we present a distributed-memory library for computations with dense structured matrices. A matrix is considered structured if its off-diagonal blocks can be approximated by a rank-deficient matrix with low numerical rank. Here, we use Hierarchically Semi-Separable (HSS) representations. Such matrices appear in many applications, for example, finite-element methods, boundary element methods, and so on. Exploiting this structure allows for fast solution of linear systems and/or fast computation of matrix-vector products, which are the two main building blocks of matrix computations. The compression algorithm that we use, that computes the HSS form of an input dense matrix, reliesmore » on randomized sampling with a novel adaptive sampling mechanism. We discuss the parallelization of this algorithm and also present the parallelization of structured matrix-vector product, structured factorization, and solution routines. The efficiency of the approach is demonstrated on large problems from different academic and industrial applications, on up to 8,000 cores. Finally, this work is part of a more global effort, the STRUctured Matrices PACKage (STRUMPACK) software package for computations with sparse and dense structured matrices. Hence, although useful on their own right, the routines also represent a step in the direction of a distributed-memory sparse solver.« less

Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images.

PubMed

Zhang, Lefei; Zhang, Qian; Du, Bo; Huang, Xin; Tang, Yuan Yan; Tao, Dacheng

2018-01-01

In hyperspectral remote sensing data mining, it is important to take into account of both spectral and spatial information, such as the spectral signature, texture feature, and morphological property, to improve the performances, e.g., the image classification accuracy. In a feature representation point of view, a nature approach to handle this situation is to concatenate the spectral and spatial features into a single but high dimensional vector and then apply a certain dimension reduction technique directly on that concatenated vector before feed it into the subsequent classifier. However, multiple features from various domains definitely have different physical meanings and statistical properties, and thus such concatenation has not efficiently explore the complementary properties among different features, which should benefit for boost the feature discriminability. Furthermore, it is also difficult to interpret the transformed results of the concatenated vector. Consequently, finding a physically meaningful consensus low dimensional feature representation of original multiple features is still a challenging task. In order to address these issues, we propose a novel feature learning framework, i.e., the simultaneous spectral-spatial feature selection and extraction algorithm, for hyperspectral images spectral-spatial feature representation and classification. Specifically, the proposed method learns a latent low dimensional subspace by projecting the spectral-spatial feature into a common feature space, where the complementary information has been effectively exploited, and simultaneously, only the most significant original features have been transformed. Encouraging experimental results on three public available hyperspectral remote sensing datasets confirm that our proposed method is effective and efficient.

On vector-valued Poincaré series of weight 2

NASA Astrophysics Data System (ADS)

Meneses, Claudio

2017-10-01

Given a pair (Γ , ρ) of a Fuchsian group of the first kind, and a unitary representation ρ of Γ of arbitrary rank, the problem of construction of vector-valued Poincaré series of weight 2 is considered. Implications in the theory of parabolic bundles are discussed. When the genus of the group is zero, it is shown how an explicit basis for the space of these functions can be constructed.

A Galerkin Approach to Define Measured Terrain Surfaces with Analytic Basis Vectors to Produce a Compact Representation

DTIC Science & Technology

2010-11-01

defined herein as terrain whose surface deformation due to a single vehicle traversing the surface is negligible, such as paved roads (both asphalt ...ground vehicle reliability predictions. Current application of this work is limited to the analysis of U.S. Highways, comprised of both asphalt and...Highways that are consistent between asphalt and concrete roads b. The principle terrain characteristics are defined with analytic basis vectors

Identifying spatially similar gene expression patterns in early stage fruit fly embryo images: binary feature versus invariant moment digital representations

PubMed Central

Gurunathan, Rajalakshmi; Van Emden, Bernard; Panchanathan, Sethuraman; Kumar, Sudhir

2004-01-01

Background Modern developmental biology relies heavily on the analysis of embryonic gene expression patterns. Investigators manually inspect hundreds or thousands of expression patterns to identify those that are spatially similar and to ultimately infer potential gene interactions. However, the rapid accumulation of gene expression pattern data over the last two decades, facilitated by high-throughput techniques, has produced a need for the development of efficient approaches for direct comparison of images, rather than their textual descriptions, to identify spatially similar expression patterns. Results The effectiveness of the Binary Feature Vector (BFV) and Invariant Moment Vector (IMV) based digital representations of the gene expression patterns in finding biologically meaningful patterns was compared for a small (226 images) and a large (1819 images) dataset. For each dataset, an ordered list of images, with respect to a query image, was generated to identify overlapping and similar gene expression patterns, in a manner comparable to what a developmental biologist might do. The results showed that the BFV representation consistently outperforms the IMV representation in finding biologically meaningful matches when spatial overlap of the gene expression pattern and the genes involved are considered. Furthermore, we explored the value of conducting image-content based searches in a dataset where individual expression components (or domains) of multi-domain expression patterns were also included separately. We found that this technique improves performance of both IMV and BFV based searches. Conclusions We conclude that the BFV representation consistently produces a more extensive and better list of biologically useful patterns than the IMV representation. The high quality of results obtained scales well as the search database becomes larger, which encourages efforts to build automated image query and retrieval systems for spatial gene expression patterns. PMID:15603586

Ontology Sparse Vector Learning Algorithm for Ontology Similarity Measuring and Ontology Mapping via ADAL Technology

NASA Astrophysics Data System (ADS)

Gao, Wei; Zhu, Linli; Wang, Kaiyun

2015-12-01

Ontology, a model of knowledge representation and storage, has had extensive applications in pharmaceutics, social science, chemistry and biology. In the age of “big data”, the constructed concepts are often represented as higher-dimensional data by scholars, and thus the sparse learning techniques are introduced into ontology algorithms. In this paper, based on the alternating direction augmented Lagrangian method, we present an ontology optimization algorithm for ontological sparse vector learning, and a fast version of such ontology technologies. The optimal sparse vector is obtained by an iterative procedure, and the ontology function is then obtained from the sparse vector. Four simulation experiments show that our ontological sparse vector learning model has a higher precision ratio on plant ontology, humanoid robotics ontology, biology ontology and physics education ontology data for similarity measuring and ontology mapping applications.

Status of pesticide management in the practice of vector control: a global survey in countries at risk of malaria or other major vector-borne diseases.

PubMed

van den Berg, Henk; Hii, Jeffrey; Soares, Agnes; Mnzava, Abraham; Ameneshewa, Birkinesh; Dash, Aditya P; Ejov, Mikhail; Tan, Soo Hian; Matthews, Graham; Yadav, Rajpal S; Zaim, Morteza

2011-05-14

It is critical that vector control pesticides are used for their acceptable purpose without causing adverse effects on health and the environment. This paper provides a global overview of the current status of pesticides management in the practice of vector control. A questionnaire was distributed to WHO member states and completed either by the director of the vector-borne disease control programme or by the national manager for vector control. In all, 113 countries responded to the questionnaire (80% response rate), representing 94% of the total population of the countries targeted. Major gaps were evident in countries in pesticide procurement practices, training on vector control decision making, certification and quality control of pesticide application, monitoring of worker safety, public awareness programmes, and safe disposal of pesticide-related waste. Nevertheless, basic conditions of policy and coordination have been established in many countries through which the management of vector control pesticides could potentially be improved. Most countries responded that they have adopted relevant recommendations by the WHO. Given the deficiencies identified in this first global survey on public health pesticide management and the recent rise in pesticide use for malaria control, the effectiveness and safety of pesticide use are being compromised. This highlights the urgent need for countries to strengthen their capacity on pesticide management and evidence-based decision making within the context of an integrated vector management approach.

Status of pesticide management in the practice of vector control: a global survey in countries at risk of malaria or other major vector-borne diseases

PubMed Central

2011-01-01

Background It is critical that vector control pesticides are used for their acceptable purpose without causing adverse effects on health and the environment. This paper provides a global overview of the current status of pesticides management in the practice of vector control. Methods A questionnaire was distributed to WHO member states and completed either by the director of the vector-borne disease control programme or by the national manager for vector control. In all, 113 countries responded to the questionnaire (80% response rate), representing 94% of the total population of the countries targeted. Results Major gaps were evident in countries in pesticide procurement practices, training on vector control decision making, certification and quality control of pesticide application, monitoring of worker safety, public awareness programmes, and safe disposal of pesticide-related waste. Nevertheless, basic conditions of policy and coordination have been established in many countries through which the management of vector control pesticides could potentially be improved. Most countries responded that they have adopted relevant recommendations by the WHO. Conclusions Given the deficiencies identified in this first global survey on public health pesticide management and the recent rise in pesticide use for malaria control, the effectiveness and safety of pesticide use are being compromised. This highlights the urgent need for countries to strengthen their capacity on pesticide management and evidence-based decision making within the context of an integrated vector management approach. PMID:21569601

Enhancing vector shoreline data using a data fusion approach

NASA Astrophysics Data System (ADS)

Carlotto, Mark; Nebrich, Mark; DeMichele, David

2017-05-01

Vector shoreline (VSL) data is potentially useful in ATR systems that distinguish between objects on land or water. Unfortunately available data such as the NOAA 1:250,000 World Vector Shoreline and NGA Prototype Global Shoreline data cannot be used by themselves to make a land/water determination because of the manner in which the data are compiled. We describe a data fusion approach for creating labeled VSL data using test points from Global 30 Arc-Second Elevation (GTOPO30) data to determine the direction of vector segments; i.e., whether they are in clockwise or counterclockwise order. We show consistently labeled VSL data be used to easily determine whether a point is on land or water using a vector cross product test.

DD-PREF: a language for expressing preferences over sets

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri; desJardins, Marie

2005-01-01

We present a representation language, DD-PREF (for Diversity and Depth PREFrences), for specifying the desired diversity and depth of sets of objects where each object is represented as a vector of feature values.

Adaptive surrogate modeling by ANOVA and sparse polynomial dimensional decomposition for global sensitivity analysis in fluid simulation

NASA Astrophysics Data System (ADS)

Tang, Kunkun; Congedo, Pietro M.; Abgrall, Rémi

2016-06-01

The Polynomial Dimensional Decomposition (PDD) is employed in this work for the global sensitivity analysis and uncertainty quantification (UQ) of stochastic systems subject to a moderate to large number of input random variables. Due to the intimate connection between the PDD and the Analysis of Variance (ANOVA) approaches, PDD is able to provide a simpler and more direct evaluation of the Sobol' sensitivity indices, when compared to the Polynomial Chaos expansion (PC). Unfortunately, the number of PDD terms grows exponentially with respect to the size of the input random vector, which makes the computational cost of standard methods unaffordable for real engineering applications. In order to address the problem of the curse of dimensionality, this work proposes essentially variance-based adaptive strategies aiming to build a cheap meta-model (i.e. surrogate model) by employing the sparse PDD approach with its coefficients computed by regression. Three levels of adaptivity are carried out in this paper: 1) the truncated dimensionality for ANOVA component functions, 2) the active dimension technique especially for second- and higher-order parameter interactions, and 3) the stepwise regression approach designed to retain only the most influential polynomials in the PDD expansion. During this adaptive procedure featuring stepwise regressions, the surrogate model representation keeps containing few terms, so that the cost to resolve repeatedly the linear systems of the least-squares regression problem is negligible. The size of the finally obtained sparse PDD representation is much smaller than the one of the full expansion, since only significant terms are eventually retained. Consequently, a much smaller number of calls to the deterministic model is required to compute the final PDD coefficients.

Malaria and other vector-borne infection surveillance in the U.S. Department of Defense Armed Forces Health Surveillance Center-Global Emerging Infections Surveillance program: review of 2009 accomplishments.

PubMed

Fukuda, Mark M; Klein, Terry A; Kochel, Tadeusz; Quandelacy, Talia M; Smith, Bryan L; Villinski, Jeff; Bethell, Delia; Tyner, Stuart; Se, Youry; Lon, Chanthap; Saunders, David; Johnson, Jacob; Wagar, Eric; Walsh, Douglas; Kasper, Matthew; Sanchez, Jose L; Witt, Clara J; Cheng, Qin; Waters, Norman; Shrestha, Sanjaya K; Pavlin, Julie A; Lescano, Andres G; Graf, Paul C F; Richardson, Jason H; Durand, Salomon; Rogers, William O; Blazes, David L; Russell, Kevin L; Akala, Hoseah; Gaydos, Joel C; DeFraites, Robert F; Gosi, Panita; Timmermans, Ans; Yasuda, Chad; Brice, Gary; Eyase, Fred; Kronmann, Karl; Sebeny, Peter; Gibbons, Robert; Jarman, Richard; Waitumbi, John; Schnabel, David; Richards, Allen; Shanks, Dennis

2011-03-04

Vector-borne infections (VBI) are defined as infectious diseases transmitted by the bite or mechanical transfer of arthropod vectors. They constitute a significant proportion of the global infectious disease burden. United States (U.S.) Department of Defense (DoD) personnel are especially vulnerable to VBIs due to occupational contact with arthropod vectors, immunological naiveté to previously unencountered pathogens, and limited diagnostic and treatment options available in the austere and unstable environments sometimes associated with military operations. In addition to the risk uniquely encountered by military populations, other factors have driven the worldwide emergence of VBIs. Unprecedented levels of global travel, tourism and trade, and blurred lines of demarcation between zoonotic VBI reservoirs and human populations increase vector exposure. Urban growth in previously undeveloped regions and perturbations in global weather patterns also contribute to the rise of VBIs. The Armed Forces Health Surveillance Center-Global Emerging Infections Surveillance and Response System (AFHSC-GEIS) and its partners at DoD overseas laboratories form a network to better characterize the nature, emergence and growth of VBIs globally. In 2009 the network tested 19,730 specimens from 25 sites for Plasmodium species and malaria drug resistance phenotypes and nearly another 10,000 samples to determine the etiologies of non-Plasmodium species VBIs from regions spanning from Oceania to Africa, South America, and northeast, south and Southeast Asia. This review describes recent VBI-related epidemiological studies conducted by AFHSC-GEIS partner laboratories within the OCONUS DoD laboratory network emphasizing their impact on human populations.

Correlated Topic Vector for Scene Classification.

PubMed

Wei, Pengxu; Qin, Fei; Wan, Fang; Zhu, Yi; Jiao, Jianbin; Ye, Qixiang

2017-07-01

Scene images usually involve semantic correlations, particularly when considering large-scale image data sets. This paper proposes a novel generative image representation, correlated topic vector, to model such semantic correlations. Oriented from the correlated topic model, correlated topic vector intends to naturally utilize the correlations among topics, which are seldom considered in the conventional feature encoding, e.g., Fisher vector, but do exist in scene images. It is expected that the involvement of correlations can increase the discriminative capability of the learned generative model and consequently improve the recognition accuracy. Incorporated with the Fisher kernel method, correlated topic vector inherits the advantages of Fisher vector. The contributions to the topics of visual words have been further employed by incorporating the Fisher kernel framework to indicate the differences among scenes. Combined with the deep convolutional neural network (CNN) features and Gibbs sampling solution, correlated topic vector shows great potential when processing large-scale and complex scene image data sets. Experiments on two scene image data sets demonstrate that correlated topic vector improves significantly the deep CNN features, and outperforms existing Fisher kernel-based features.

Wigner functions for nonparaxial, arbitrarily polarized electromagnetic wave fields in free space.

PubMed

Alonso, Miguel A

2004-11-01

New representations are defined for describing electromagnetic wave fields in free space exactly in terms of rays for any wavelength, level of coherence or polarization, and numerical aperture, as long as there are no evanescent components. These representations correspond to tensors assigned to each ray such that the electric and magnetic energy densities, the Poynting vector, and the polarization properties of the field correspond to simple integrals involving these tensors for the rays that go through the specified point. For partially coherent fields, the ray-based approach provided by the new representations can reduce dramatically the computation times for the physical properties mentioned earlier.

Arctic indigenous peoples as representations and representatives of climate change.

PubMed

Martello, Marybeth Long

2008-06-01

Recent scientific findings, as presented in the Arctic Climate Impact Assessment (ACIA), indicate that climate change in the Arctic is happening now, at a faster rate than elsewhere in the world, and with major implications for peoples of the Arctic (especially indigenous peoples) and the rest of the planet. This paper examines scientific and political representations of Arctic indigenous peoples that have been central to the production and articulation of these claims. ACIA employs novel forms and strategies of representation that reflect changing conceptual models and practices of global change science and depict indigenous peoples as expert, exotic, and at-risk. These portrayals emerge alongside the growing political activism of Arctic indigenous peoples who present themselves as representatives or embodiments of climate change itself as they advocate for climate change mitigation policies. These mutually constitutive forms of representation suggest that scientific ways of seeing the global environment shape and are shaped by the public image and voice of global citizens. Likewise, the authority, credibility, and visibility of Arctic indigenous activists derive, in part, from their status as at-risk experts, a status buttressed by new scientific frameworks and methods that recognize and rely on the local experiences and knowledges of indigenous peoples. Analyses of these relationships linking scientific and political representations of Arctic climate change build upon science and technology studies (STS) scholarship on visualization, challenge conventional notions of globalization, and raise questions about power and accountability in global climate change research.

Modeling the impact of global warming on vector-borne infections.

PubMed

Massad, Eduardo; Coutinho, Francisco Antonio Bezerra; Lopez, Luis Fernandez; da Silva, Daniel Rodrigues

2011-06-01

Global warming will certainly affect the abundance and distribution of disease vectors. The effect of global warming, however, depends on the complex interaction between the human host population and the causative infectious agent. In this work we review some mathematical models that were proposed to study the impact of the increase in ambient temperature on the spread and gravity of some insect-transmitted diseases. Copyright © 2011 Elsevier B.V. All rights reserved.

Visualization of the energy flow for guided forward and backward waves in and around a fluid-loaded elastic cylindrical shell via the Poynting vector field

NASA Astrophysics Data System (ADS)

Dean, Cleon E.; Braselton, James P.

2004-05-01

Color-coded and vector-arrow grid representations of the Poynting vector field are used to show the energy flow in and around a fluid-loaded elastic cylindrical shell for both forward- and backward-propagating waves. The present work uses a method adapted from a simpler technique due to Kaduchak and Marston [G. Kaduchak and P. L. Marston, ``Traveling-wave decomposition of surface displacements associated with scattering by a cylindrical shell: Numerical evaluation displaying guided forward and backward wave properties,'' J. Acoust. Soc. Am. 98, 3501-3507 (1995)] to isolate unidirectional energy flows.

The reliability of humerothoracic angles during arm elevation depends on the representation of rotations.

PubMed

López-Pascual, Juan; Cáceres, Magda Liliana; De Rosario, Helios; Page, Álvaro

2016-02-08

The reliability of joint rotation measurements is an issue of major interest, especially in clinical applications. The effect of instrumental errors and soft tissue artifacts on the variability of human motion measures is well known, but the influence of the representation of joint motion has not yet been studied. The aim of the study was to compare the within-subject reliability of three rotation formalisms for the calculation of the shoulder elevation joint angles. Five repetitions of humeral elevation in the scapular plane of 27 healthy subjects were recorded using a stereophotogrammetry system. The humerothoracic joint angles were calculated using the YX'Y" and XZ'Y" Euler angle sequences and the attitude vector. A within-subject repeatability study was performed for the three representations. ICC, SEM and CV were the indices used to estimate the error in the calculation of the angle amplitudes and the angular waveforms with each method. Excellent results were obtained in all representations for the main angle (elevation), but there were remarkable differences for axial rotation and plane of elevation. The YX'Y" sequence generally had the poorest reliability in the secondary angles. The XZ'Y' sequence proved to be the most reliable representation of axial rotation, whereas the attitude vector had the highest reliability in the plane of elevation. These results highlight the importance of selecting the method used to describe the joint motion when within-subjects reliability is an important issue of the experiment. This may be of particular importance when the secondary angles of motions are being studied. Copyright © 2016 Elsevier Ltd. All rights reserved.

Prediction of protein structural classes by Chou's pseudo amino acid composition: approached using continuous wavelet transform and principal component analysis.

PubMed

Li, Zhan-Chao; Zhou, Xi-Bin; Dai, Zong; Zou, Xiao-Yong

2009-07-01

A prior knowledge of protein structural classes can provide useful information about its overall structure, so it is very important for quick and accurate determination of protein structural class with computation method in protein science. One of the key for computation method is accurate protein sample representation. Here, based on the concept of Chou's pseudo-amino acid composition (AAC, Chou, Proteins: structure, function, and genetics, 43:246-255, 2001), a novel method of feature extraction that combined continuous wavelet transform (CWT) with principal component analysis (PCA) was introduced for the prediction of protein structural classes. Firstly, the digital signal was obtained by mapping each amino acid according to various physicochemical properties. Secondly, CWT was utilized to extract new feature vector based on wavelet power spectrum (WPS), which contains more abundant information of sequence order in frequency domain and time domain, and PCA was then used to reorganize the feature vector to decrease information redundancy and computational complexity. Finally, a pseudo-amino acid composition feature vector was further formed to represent primary sequence by coupling AAC vector with a set of new feature vector of WPS in an orthogonal space by PCA. As a showcase, the rigorous jackknife cross-validation test was performed on the working datasets. The results indicated that prediction quality has been improved, and the current approach of protein representation may serve as a useful complementary vehicle in classifying other attributes of proteins, such as enzyme family class, subcellular localization, membrane protein types and protein secondary structure, etc.

Duality-symmetric supersymmetric Yang-Mills theory in three dimensions

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

Nishino, Hitoshi; Rajpoot, Subhash

We formulate a duality-symmetric N=1 supersymmetric Yang-Mills theory in three dimensions. Our field content is (A{sub {mu}}{sup I},{lambda}{sup I},{phi}{sup I}), where the index I is for the adjoint representation of an arbitrary gauge group G. Our Hodge duality symmetry is F{sub {mu}{nu}}{sup I}=+{epsilon}{sub {mu}{nu}}{sup {rho}D}{sub {rho}{phi}}{sup I}. Because of this relationship, the presence of two physical fields A{sub {mu}}{sup I} and {phi}{sup I} within the same N=1 supermultiplet poses no problem. We can couple this multiplet to another vector multiplet (C{sub {mu}}{sup I},{chi}{sup I};B{sub {mu}{nu}}{sup I}) with 1+1 physical degrees of freedom modulo dim G. Thanks to peculiar couplings andmore » supersymmetry, the usual problem with an extra vector field in a nontrivial representation does not arise in our system.« less

Surface representations of two- and three-dimensional fluid flow topology

NASA Technical Reports Server (NTRS)

Helman, James L.; Hesselink, Lambertus

1990-01-01

We discuss our work using critical point analysis to generate representations of the vector field topology of numerical flow data sets. Critical points are located and characterized in a two-dimensional domain, which may be either a two-dimensional flow field or the tangential velocity field near a three-dimensional body. Tangent curves are then integrated out along the principal directions of certain classes of critical points. The points and curves are linked to form a skeleton representing the two-dimensional vector field topology. When generated from the tangential velocity field near a body in a three-dimensional flow, the skeleton includes the critical points and curves which provide a basis for analyzing the three-dimensional structure of the flow separation. The points along the separation curves in the skeleton are used to start tangent curve integrations to generate surfaces representing the topology of the associated flow separations.

The harmonic oscillator and nuclear physics

NASA Technical Reports Server (NTRS)

Rowe, D. J.

1993-01-01

The three-dimensional harmonic oscillator plays a central role in nuclear physics. It provides the underlying structure of the independent-particle shell model and gives rise to the dynamical group structures on which models of nuclear collective motion are based. It is shown that the three-dimensional harmonic oscillator features a rich variety of coherent states, including vibrations of the monopole, dipole, and quadrupole types, and rotations of the rigid flow, vortex flow, and irrotational flow types. Nuclear collective states exhibit all of these flows. It is also shown that the coherent state representations, which have their origins in applications to the dynamical groups of the simple harmonic oscillator, can be extended to vector coherent state representations with a much wider range of applicability. As a result, coherent state theory and vector coherent state theory become powerful tools in the application of algebraic methods in physics.

Cascading effect of economic globalization on human risks of scrub typhus and tick-borne rickettsial diseases.

PubMed

Kuo, Chi-Chien; Huang, Jing-Lun; Shu, Pei-Yun; Lee, Pei-Lung; Kelt, Douglas A; Wang, Hsi-Chieh

2012-09-01

The increase in global travel and trade has facilitated the dissemination of disease vectors. Globalization can also indirectly affect vector-borne diseases through the liberalization of cross-border trade, which has far-reaching, worldwide effects on agricultural practices and may in turn influence vectors through the modification of the ecological landscape. While the cascading effect of economic globalization on vector-borne diseases, sometimes acting synergistically with regional agricultural policy, could be substantial and have significant economic, agricultural, and public health implications, research into this remains very limited. We evaluated how abandonment of rice paddies in Taiwan after joining the World Trade Organization, along with periodic plowing, an agricultural policy to reduce farm pests in abandoned fields can unexpectedly influence risks to diseases transmitted by ticks and chiggers (larval trombiculid mites), which we collected from their small-mammal hosts. Sampling was limited to abandoned (fallow) and plowed fields due to the challenge of trapping small mammals in flooded rice paddies. Striped field mice (Apodemus agrarius) are the main hosts for both vectors. They harbored six times more ticks and three times more chiggers in fallow than in plowed plots. The proportion of ticks infected with Rickettsia spp. (etiologic agent of spotted fever) was three times higher in fallow plots, while that of Orientia tsutsugamushi (scrub typhus) in chiggers was similar in both treatments. Fallow plots had more ground cover and higher vegetation than plowed ones. Moreover, ticks and chiggers in both field types were dominated by species known to infest humans. Because ticks and chiggers should exhibit very low survival in flooded rice paddies, we propose that farm abandonment in Taiwan, driven by globalization, may have inadvertently led to increased risks of spotted fever and scrub typhus. However, periodic plowing can unintentionally mitigate vector burdens. Economic globalization can have unexpected consequences on disease risk through modification of the agricultural landscape, but the outcome may also be influenced by agricultural policies, calling for further research on vector-borne diseases and their control from broader perspectives.

Tensor Sparse Coding for Positive Definite Matrices.

PubMed

Sivalingam, Ravishankar; Boley, Daniel; Morellas, Vassilios; Papanikolopoulos, Nikos

2013-08-02

In recent years, there has been extensive research on sparse representation of vector-valued signals. In the matrix case, the data points are merely vectorized and treated as vectors thereafter (for e.g., image patches). However, this approach cannot be used for all matrices, as it may destroy the inherent structure of the data. Symmetric positive definite (SPD) matrices constitute one such class of signals, where their implicit structure of positive eigenvalues is lost upon vectorization. This paper proposes a novel sparse coding technique for positive definite matrices, which respects the structure of the Riemannian manifold and preserves the positivity of their eigenvalues, without resorting to vectorization. Synthetic and real-world computer vision experiments with region covariance descriptors demonstrate the need for and the applicability of the new sparse coding model. This work serves to bridge the gap between the sparse modeling paradigm and the space of positive definite matrices.

Tensor sparse coding for positive definite matrices.

PubMed

Sivalingam, Ravishankar; Boley, Daniel; Morellas, Vassilios; Papanikolopoulos, Nikolaos

2014-03-01

In recent years, there has been extensive research on sparse representation of vector-valued signals. In the matrix case, the data points are merely vectorized and treated as vectors thereafter (for example, image patches). However, this approach cannot be used for all matrices, as it may destroy the inherent structure of the data. Symmetric positive definite (SPD) matrices constitute one such class of signals, where their implicit structure of positive eigenvalues is lost upon vectorization. This paper proposes a novel sparse coding technique for positive definite matrices, which respects the structure of the Riemannian manifold and preserves the positivity of their eigenvalues, without resorting to vectorization. Synthetic and real-world computer vision experiments with region covariance descriptors demonstrate the need for and the applicability of the new sparse coding model. This work serves to bridge the gap between the sparse modeling paradigm and the space of positive definite matrices.

Vector representation of user's view using self-organizing map

NASA Astrophysics Data System (ADS)

Ae, Tadashi; Yamaguchi, Tomohisa; Monden, Eri; Kawabata, Shunji; Kamitani, Motoki

2004-05-01

There exist various objects, such as pictures, music, texts, etc., around our environment. We have a view for these objects by looking, reading or listening. Our view is concerned with our behaviors deeply, and is very important to understand our behaviors. Therefore, we propose a method which acquires a view as a vector, and apply the vector to sequence generation. We focus on sequences of the data of which a user selects from a multimedia database containing pictures, music, movie, etc.. These data cannot be stereotyped because user's view for them changes by each user. Therefore, we represent the structure of the multimedia database as the vector representing user's view and the stereotyped vector, and acquire sequences containing the structure as elements. We demonstrate a city-sequence generation system which reflects user's intension as an application of sequence generation containing user's view. We apply the self-organizing map to this system to represent user's view.

A method of recovering the initial vectors of globally coupled map lattices based on symbolic dynamics

NASA Astrophysics Data System (ADS)

Sun, Li-Sha; Kang, Xiao-Yun; Zhang, Qiong; Lin, Lan-Xin

2011-12-01

Based on symbolic dynamics, a novel computationally efficient algorithm is proposed to estimate the unknown initial vectors of globally coupled map lattices (CMLs). It is proved that not all inverse chaotic mapping functions are satisfied for contraction mapping. It is found that the values in phase space do not always converge on their initial values with respect to sufficient backward iteration of the symbolic vectors in terms of global convergence or divergence (CD). Both CD property and the coupling strength are directly related to the mapping function of the existing CML. Furthermore, the CD properties of Logistic, Bernoulli, and Tent chaotic mapping functions are investigated and compared. Various simulation results and the performances of the initial vector estimation with different signal-to-noise ratios (SNRs) are also provided to confirm the proposed algorithm. Finally, based on the spatiotemporal chaotic characteristics of the CML, the conditions of estimating the initial vectors using symbolic dynamics are discussed. The presented method provides both theoretical and experimental results for better understanding and characterizing the behaviours of spatiotemporal chaotic systems.

Extracting Information from Electronic Medical Records to Identify the Obesity Status of a Patient Based on Comorbidities and Bodyweight Measures.

PubMed

Figueroa, Rosa L; Flores, Christopher A

2016-08-01

Obesity is a chronic disease with an increasing impact on the world's population. In this work, we present a method of identifying obesity automatically using text mining techniques and information related to body weight measures and obesity comorbidities. We used a dataset of 3015 de-identified medical records that contain labels for two classification problems. The first classification problem distinguishes between obesity, overweight, normal weight, and underweight. The second classification problem differentiates between obesity types: super obesity, morbid obesity, severe obesity and moderate obesity. We used a Bag of Words approach to represent the records together with unigram and bigram representations of the features. We implemented two approaches: a hierarchical method and a nonhierarchical one. We used Support Vector Machine and Naïve Bayes together with ten-fold cross validation to evaluate and compare performances. Our results indicate that the hierarchical approach does not work as well as the nonhierarchical one. In general, our results show that Support Vector Machine obtains better performances than Naïve Bayes for both classification problems. We also observed that bigram representation improves performance compared with unigram representation.

The organization of conspecific face space in nonhuman primates

PubMed Central

Parr, Lisa A.; Taubert, Jessica; Little, Anthony C.; Hancock, Peter J. B.

2013-01-01

Humans and chimpanzees demonstrate numerous cognitive specializations for processing faces, but comparative studies with monkeys suggest that these may be the result of recent evolutionary adaptations. The present study utilized the novel approach of face space, a powerful theoretical framework used to understand the representation of face identity in humans, to further explore species differences in face processing. According to the theory, faces are represented by vectors in a multidimensional space, the centre of which is defined by an average face. Each dimension codes features important for describing a face’s identity, and vector length codes the feature’s distinctiveness. Chimpanzees and rhesus monkeys discriminated male and female conspecifics’ faces, rated by humans for their distinctiveness, using a computerized task. Multidimensional scaling analyses showed that the organization of face space was similar between humans and chimpanzees. Distinctive faces had the longest vectors and were the easiest for chimpanzees to discriminate. In contrast, distinctiveness did not correlate with the performance of rhesus monkeys. The feature dimensions for each species’ face space were visualized and described using morphing techniques. These results confirm species differences in the perceptual representation of conspecific faces, which are discussed within an evolutionary framework. PMID:22670823

Validation of SplitVectors Encoding for Quantitative Visualization of Large-Magnitude-Range Vector Fields

PubMed Central

Zhao, Henan; Bryant, Garnett W.; Griffin, Wesley; Terrill, Judith E.; Chen, Jian

2017-01-01

We designed and evaluated SplitVectors, a new vector field display approach to help scientists perform new discrimination tasks on large-magnitude-range scientific data shown in three-dimensional (3D) visualization environments. SplitVectors uses scientific notation to display vector magnitude, thus improving legibility. We present an empirical study comparing the SplitVectors approach with three other approaches - direct linear representation, logarithmic, and text display commonly used in scientific visualizations. Twenty participants performed three domain analysis tasks: reading numerical values (a discrimination task), finding the ratio between values (a discrimination task), and finding the larger of two vectors (a pattern detection task). Participants used both mono and stereo conditions. Our results suggest the following: (1) SplitVectors improve accuracy by about 10 times compared to linear mapping and by four times to logarithmic in discrimination tasks; (2) SplitVectors have no significant differences from the textual display approach, but reduce cluttering in the scene; (3) SplitVectors and textual display are less sensitive to data scale than linear and logarithmic approaches; (4) using logarithmic can be problematic as participants' confidence was as high as directly reading from the textual display, but their accuracy was poor; and (5) Stereoscopy improved performance, especially in more challenging discrimination tasks. PMID:28113469

Validation of SplitVectors Encoding for Quantitative Visualization of Large-Magnitude-Range Vector Fields.

PubMed

Henan Zhao; Bryant, Garnett W; Griffin, Wesley; Terrill, Judith E; Jian Chen

2017-06-01

We designed and evaluated SplitVectors, a new vector field display approach to help scientists perform new discrimination tasks on large-magnitude-range scientific data shown in three-dimensional (3D) visualization environments. SplitVectors uses scientific notation to display vector magnitude, thus improving legibility. We present an empirical study comparing the SplitVectors approach with three other approaches - direct linear representation, logarithmic, and text display commonly used in scientific visualizations. Twenty participants performed three domain analysis tasks: reading numerical values (a discrimination task), finding the ratio between values (a discrimination task), and finding the larger of two vectors (a pattern detection task). Participants used both mono and stereo conditions. Our results suggest the following: (1) SplitVectors improve accuracy by about 10 times compared to linear mapping and by four times to logarithmic in discrimination tasks; (2) SplitVectors have no significant differences from the textual display approach, but reduce cluttering in the scene; (3) SplitVectors and textual display are less sensitive to data scale than linear and logarithmic approaches; (4) using logarithmic can be problematic as participants' confidence was as high as directly reading from the textual display, but their accuracy was poor; and (5) Stereoscopy improved performance, especially in more challenging discrimination tasks.

Global Seasonal Climatologies of Ocean Chlorophyll: Blending In situ and Satellite Data for the CZCS Era

NASA Technical Reports Server (NTRS)

Gregg, Watson W.; Conkright, Margarita E.

1999-01-01

The historical archives of in situ (National Oceanographic Data Center) and satellite (Coastal Zone Color Scanner) chlorophyll data were combined using the blended analysis method of Reynolds [1988] in an attempt to construct an improved climatological seasonal representation of global chlorophyll distributions. The results of the blended analysis differed dramatically from the CZCS representation: global chlorophyll estimates increased 8-35% in the blended analysis depending upon season. Regional differences were even larger, up to 140% in the equatorial Indian Ocean in summer (during the southwest monsoon). Tropical Pacific chlorophyll values increased 25-41%. The results suggested that the CZCS generally underestimates chlorophyll. Regional and seasonal differences in the blended analysis were sufficiently large as to produce a different representation of global chlorophyll distributions than otherwise inferred from CZCS data alone. Analyses of primary production and biogeochemical cycles may be substantially impacted by these results.

Young Children's Self-Concepts Include Representations of Abstract Traits and the Global Self.

PubMed

Cimpian, Andrei; Hammond, Matthew D; Mazza, Giulia; Corry, Grace

2017-11-01

There is debate about the abstractness of young children's self-concepts-specifically, whether they include representations of (a) general traits and abilities and (b) the global self. Four studies (N = 176 children aged 4-7) suggested these representations are indeed part of early self-concepts. Studies 1 and 2 reexamined prior evidence that young children cannot represent traits and abilities. The results suggested that children's seemingly immature judgments in previous studies were due to peculiarities of the task context not the inadequacy of children's self-concepts. Similarly, Studies 3 and 4 revealed that, contrary to claims of immaturity in reasoning about the global self, young children update their global self-evaluations in flexible, context-sensitive ways. This evidence suggests continuity in the structure of self-concepts across childhood. © 2017 The Authors. Child Development © 2017 Society for Research in Child Development, Inc.

Malaria and Other Vector-Borne Infection Surveillance in the U.S. Department of Defense Armed Forces Health Surveillance Center-Global Program: Review of 2009 Accomplishments

DTIC Science & Technology

2011-03-04

global travel, tourism and trade, and blurred lines of demarcation between zoonotic VBI reservoirs and human populations increase vector exposure. Urban...Unprecedented levels of global travel, tourism and trade, and blurred lines of demarcation between zoonotic VBI reservoirs and human populations...made in 2009 to enhance or establish hospi- tal-based febrile illness surveillance platforms in Azer- baijan, Bolivia, Cambodia, Ecuador , Georgia

Grid-based lattice summation of electrostatic potentials by assembled rank-structured tensor approximation

NASA Astrophysics Data System (ADS)

Khoromskaia, Venera; Khoromskij, Boris N.

2014-12-01

Our recent method for low-rank tensor representation of sums of the arbitrarily positioned electrostatic potentials discretized on a 3D Cartesian grid reduces the 3D tensor summation to operations involving only 1D vectors however retaining the linear complexity scaling in the number of potentials. Here, we introduce and study a novel tensor approach for fast and accurate assembled summation of a large number of lattice-allocated potentials represented on 3D N × N × N grid with the computational requirements only weakly dependent on the number of summed potentials. It is based on the assembled low-rank canonical tensor representations of the collected potentials using pointwise sums of shifted canonical vectors representing the single generating function, say the Newton kernel. For a sum of electrostatic potentials over L × L × L lattice embedded in a box the required storage scales linearly in the 1D grid-size, O(N) , while the numerical cost is estimated by O(NL) . For periodic boundary conditions, the storage demand remains proportional to the 1D grid-size of a unit cell, n = N / L, while the numerical cost reduces to O(N) , that outperforms the FFT-based Ewald-type summation algorithms of complexity O(N3 log N) . The complexity in the grid parameter N can be reduced even to the logarithmic scale O(log N) by using data-sparse representation of canonical N-vectors via the quantics tensor approximation. For justification, we prove an upper bound on the quantics ranks for the canonical vectors in the overall lattice sum. The presented approach is beneficial in applications which require further functional calculus with the lattice potential, say, scalar product with a function, integration or differentiation, which can be performed easily in tensor arithmetics on large 3D grids with 1D cost. Numerical tests illustrate the performance of the tensor summation method and confirm the estimated bounds on the tensor ranks.

A roadmap for improving the representation of photosynthesis in Earth system models.

PubMed

Rogers, Alistair; Medlyn, Belinda E; Dukes, Jeffrey S; Bonan, Gordon; von Caemmerer, Susanne; Dietze, Michael C; Kattge, Jens; Leakey, Andrew D B; Mercado, Lina M; Niinemets, Ülo; Prentice, I Colin; Serbin, Shawn P; Sitch, Stephen; Way, Danielle A; Zaehle, Sönke

2017-01-01

Accurate representation of photosynthesis in terrestrial biosphere models (TBMs) is essential for robust projections of global change. However, current representations vary markedly between TBMs, contributing uncertainty to projections of global carbon fluxes. Here we compared the representation of photosynthesis in seven TBMs by examining leaf and canopy level responses of photosynthetic CO 2 assimilation (A) to key environmental variables: light, temperature, CO 2 concentration, vapor pressure deficit and soil water content. We identified research areas where limited process knowledge prevents inclusion of physiological phenomena in current TBMs and research areas where data are urgently needed for model parameterization or evaluation. We provide a roadmap for new science needed to improve the representation of photosynthesis in the next generation of terrestrial biosphere and Earth system models. No claim to original US Government works New Phytologist © 2016 New Phytologist Trust.

Multi-stage Vector-Borne Zoonoses Models: A Global Analysis.

PubMed

Bichara, Derdei; Iggidr, Abderrahman; Smith, Laura

2018-04-25

A class of models that describes the interactions between multiple host species and an arthropod vector is formulated and its dynamics investigated. A host-vector disease model where the host's infection is structured into n stages is formulated and a complete global dynamics analysis is provided. The basic reproduction number acts as a sharp threshold, that is, the disease-free equilibrium is globally asymptotically stable (GAS) whenever [Formula: see text] and that a unique interior endemic equilibrium exists and is GAS if [Formula: see text]. We proceed to extend this model with m host species, capturing a class of zoonoses where the cross-species bridge is an arthropod vector. The basic reproduction number of the multi-host-vector, [Formula: see text], is derived and shown to be the sum of basic reproduction numbers of the model when each host is isolated with an arthropod vector. It is shown that the disease will persist in all hosts as long as it persists in one host. Moreover, the overall basic reproduction number increases with respect to the host and that bringing the basic reproduction number of each isolated host below unity in each host is not sufficient to eradicate the disease in all hosts. This is a type of "amplification effect," that is, for the considered vector-borne zoonoses, the increase in host diversity increases the basic reproduction number and therefore the disease burden.

Knowledge representation of motor activity of patients with Parkinson's disease.

PubMed

Kostek, Bożena; Kupryjanow, Adam; Czyżewski, Andrzej

An approach to the knowledge representation extraction from biomedical signals analysis concerning motor activity of Parkinson disease patients is proposed in this paper. This is done utilizing accelerometers attached to their body as well as exploiting video image of their hand movements. Experiments are carried out employing artificial neural networks and support vector machine to the recognition of characteristic motor activity disorders in patients. Obtained results indicate that it is possible to interpret some selected patient's body movements with a sufficiently high effectiveness.

Mathematical modeling of Chikungunya fever control

NASA Astrophysics Data System (ADS)

Hincapié-Palacio, Doracelly; Ospina, Juan

2015-05-01

Chikungunya fever is a global concern due to the occurrence of large outbreaks, the presence of persistent arthropathy and its rapid expansion throughout various continents. Globalization and climate change have contributed to the expansion of the geographical areas where mosquitoes Aedes aegypti and Aedes albopictus (Stegomyia) remain. It is necessary to improve the techniques of vector control in the presence of large outbreaks in The American Region. We derive measures of disease control, using a mathematical model of mosquito-human interaction, by means of three scenarios: a) a single vector b) two vectors, c) two vectors and human and non-human reservoirs. The basic reproductive number and critical control measures were deduced by using computer algebra with Maple (Maplesoft Inc, Ontario Canada). Control measures were simulated with parameter values obtained from published data. According to the number of households in high risk areas, the goals of effective vector control to reduce the likelihood of mosquito-human transmission would be established. Besides the two vectors, if presence of other non-human reservoirs were reported, the monthly target of effective elimination of the vector would be approximately double compared to the presence of a single vector. The model shows the need to periodically evaluate the effectiveness of vector control measures.

Malaria and other vector-borne infection surveillance in the U.S. Department of Defense Armed Forces Health Surveillance Center-Global Emerging Infections Surveillance program: review of 2009 accomplishments

PubMed Central

2011-01-01

Vector-borne infections (VBI) are defined as infectious diseases transmitted by the bite or mechanical transfer of arthropod vectors. They constitute a significant proportion of the global infectious disease burden. United States (U.S.) Department of Defense (DoD) personnel are especially vulnerable to VBIs due to occupational contact with arthropod vectors, immunological naiveté to previously unencountered pathogens, and limited diagnostic and treatment options available in the austere and unstable environments sometimes associated with military operations. In addition to the risk uniquely encountered by military populations, other factors have driven the worldwide emergence of VBIs. Unprecedented levels of global travel, tourism and trade, and blurred lines of demarcation between zoonotic VBI reservoirs and human populations increase vector exposure. Urban growth in previously undeveloped regions and perturbations in global weather patterns also contribute to the rise of VBIs. The Armed Forces Health Surveillance Center-Global Emerging Infections Surveillance and Response System (AFHSC-GEIS) and its partners at DoD overseas laboratories form a network to better characterize the nature, emergence and growth of VBIs globally. In 2009 the network tested 19,730 specimens from 25 sites for Plasmodium species and malaria drug resistance phenotypes and nearly another 10,000 samples to determine the etiologies of non-Plasmodium species VBIs from regions spanning from Oceania to Africa, South America, and northeast, south and Southeast Asia. This review describes recent VBI-related epidemiological studies conducted by AFHSC-GEIS partner laboratories within the OCONUS DoD laboratory network emphasizing their impact on human populations. PMID:21388569

Modeling Musical Context With Word2Vec

NASA Astrophysics Data System (ADS)

Herremans, Dorien; Chuan, Ching-Hua

2017-05-01

We present a semantic vector space model for capturing complex polyphonic musical context. A word2vec model based on a skip-gram representation with negative sampling was used to model slices of music from a dataset of Beethoven's piano sonatas. A visualization of the reduced vector space using t-distributed stochastic neighbor embedding shows that the resulting embedded vector space captures tonal relationships, even without any explicit information about the musical contents of the slices. Secondly, an excerpt of the Moonlight Sonata from Beethoven was altered by replacing slices based on context similarity. The resulting music shows that the selected slice based on similar word2vec context also has a relatively short tonal distance from the original slice.

A graphics to scalable vector graphics adaptation framework for progressive remote line rendering on mobile devices

NASA Astrophysics Data System (ADS)

Le, Minh Tuan; Nguyen, Congdu; Yoon, Dae-Il; Jung, Eun Ku; Kim, Hae-Kwang

2007-12-01

In this paper, we introduce a graphics to Scalable Vector Graphics (SVG) adaptation framework with a mechanism of vector graphics transmission to overcome the shortcoming of real-time representation and interaction experiences of 3D graphics application running on mobile devices. We therefore develop an interactive 3D visualization system based on the proposed framework for rapidly representing a 3D scene on mobile devices without having to download it from the server. Our system scenario is composed of a client viewer and a graphic to SVG adaptation server. The client viewer offers the user to access to the same 3D contents with different devices according to consumer interactions.

1-norm support vector novelty detection and its sparseness.

PubMed

Zhang, Li; Zhou, WeiDa

2013-12-01

This paper proposes a 1-norm support vector novelty detection (SVND) method and discusses its sparseness. 1-norm SVND is formulated as a linear programming problem and uses two techniques for inducing sparseness, or the 1-norm regularization and the hinge loss function. We also find two upper bounds on the sparseness of 1-norm SVND, or exact support vector (ESV) and kernel Gram matrix rank bounds. The ESV bound indicates that 1-norm SVND has a sparser representation model than SVND. The kernel Gram matrix rank bound can loosely estimate the sparseness of 1-norm SVND. Experimental results show that 1-norm SVND is feasible and effective. Copyright © 2013 Elsevier Ltd. All rights reserved.

Real-Valued Covariance Vector Sparsity-Inducing DOA Estimation for Monostatic MIMO Radar

PubMed Central

Wang, Xianpeng; Wang, Wei; Li, Xin; Liu, Jing

2015-01-01

In this paper, a real-valued covariance vector sparsity-inducing method for direction of arrival (DOA) estimation is proposed in monostatic multiple-input multiple-output (MIMO) radar. Exploiting the special configuration of monostatic MIMO radar, low-dimensional real-valued received data can be obtained by using the reduced-dimensional transformation and unitary transformation technique. Then, based on the Khatri–Rao product, a real-valued sparse representation framework of the covariance vector is formulated to estimate DOA. Compared to the existing sparsity-inducing DOA estimation methods, the proposed method provides better angle estimation performance and lower computational complexity. Simulation results verify the effectiveness and advantage of the proposed method. PMID:26569241

Real-Valued Covariance Vector Sparsity-Inducing DOA Estimation for Monostatic MIMO Radar.

PubMed

Wang, Xianpeng; Wang, Wei; Li, Xin; Liu, Jing

2015-11-10

In this paper, a real-valued covariance vector sparsity-inducing method for direction of arrival (DOA) estimation is proposed in monostatic multiple-input multiple-output (MIMO) radar. Exploiting the special configuration of monostatic MIMO radar, low-dimensional real-valued received data can be obtained by using the reduced-dimensional transformation and unitary transformation technique. Then, based on the Khatri-Rao product, a real-valued sparse representation framework of the covariance vector is formulated to estimate DOA. Compared to the existing sparsity-inducing DOA estimation methods, the proposed method provides better angle estimation performance and lower computational complexity. Simulation results verify the effectiveness and advantage of the proposed method.

User Modeling for Contextual Suggestion

DTIC Science & Technology

2014-11-01

information retrieval literature ( Salton et al., 1975). To apply this metric, we converted the user interest model into a vector representation with all...Discovering Virtual Interest Groups across Chat Rooms, International Conference on Knowledge Management and Information Sharing (KMIS 2012). [7] Salton , G., A

Correlating lepton flavor universality violation in B decays with μ →e γ using leptoquarks

NASA Astrophysics Data System (ADS)

Crivellin, Andreas; Müller, Dario; Signer, Adrian; Ulrich, Yannick

2018-01-01

Motivated by the measurements of b →s ℓ+ℓ-transitions,includingR (K ) and R (K *), we examine lepton flavor (universality) violation in B decays and its connections to μ →e γ in generic leptoquark models. Considering all 10 representations of scalar and vector leptoquarks under the Standard Model gauge group we compute the tree-level matching for semileptonic b -quark operators as well as their loop effects in ℓ→ℓ'γ. In our phenomenological analysis, we correlate R (K ), R (K*)and the other b →s μ+μ- data to μ →e γ and b →s μ e transitions for the three leptoquark representations that generate left-handed currents in b →s ℓ+ℓ-transitionsand,therefore, provide a good fit to data. We find that while new physics contributions to muons are required by the global fit, couplings to electrons can be sizeable without violating the stringent bounds from μ →e γ . In fact, if the effect in electrons in b →s ℓ+ℓ- has the opposite sign from the effect in muons, the bound from μ →e γ can always be avoided. However, unavoidable effects in b →s μ e transitions (i.e. Bs→μ e , B →K μ e , etc.) appear that are within the reach of LHCb and BELLE II.

A Predictive Model for Medical Events Based on Contextual Embedding of Temporal Sequences

PubMed Central

Wang, Zhimu; Huang, Yingxiang; Wang, Shuang; Wang, Fei; Jiang, Xiaoqian

2016-01-01

Background Medical concepts are inherently ambiguous and error-prone due to human fallibility, which makes it hard for them to be fully used by classical machine learning methods (eg, for tasks like early stage disease prediction). Objective Our work was to create a new machine-friendly representation that resembles the semantics of medical concepts. We then developed a sequential predictive model for medical events based on this new representation. Methods We developed novel contextual embedding techniques to combine different medical events (eg, diagnoses, prescriptions, and labs tests). Each medical event is converted into a numerical vector that resembles its “semantics,” via which the similarity between medical events can be easily measured. We developed simple and effective predictive models based on these vectors to predict novel diagnoses. Results We evaluated our sequential prediction model (and standard learning methods) in estimating the risk of potential diseases based on our contextual embedding representation. Our model achieved an area under the receiver operating characteristic (ROC) curve (AUC) of 0.79 on chronic systolic heart failure and an average AUC of 0.67 (over the 80 most common diagnoses) using the Medical Information Mart for Intensive Care III (MIMIC-III) dataset. Conclusions We propose a general early prognosis predictor for 80 different diagnoses. Our method computes numeric representation for each medical event to uncover the potential meaning of those events. Our results demonstrate the efficiency of the proposed method, which will benefit patients and physicians by offering more accurate diagnosis. PMID:27888170

Featureless classification of light curves

NASA Astrophysics Data System (ADS)

Kügler, S. D.; Gianniotis, N.; Polsterer, K. L.

2015-08-01

In the era of rapidly increasing amounts of time series data, classification of variable objects has become the main objective of time-domain astronomy. Classification of irregularly sampled time series is particularly difficult because the data cannot be represented naturally as a vector which can be directly fed into a classifier. In the literature, various statistical features serve as vector representations. In this work, we represent time series by a density model. The density model captures all the information available, including measurement errors. Hence, we view this model as a generalization to the static features which directly can be derived, e.g. as moments from the density. Similarity between each pair of time series is quantified by the distance between their respective models. Classification is performed on the obtained distance matrix. In the numerical experiments, we use data from the OGLE (Optical Gravitational Lensing Experiment) and ASAS (All Sky Automated Survey) surveys and demonstrate that the proposed representation performs up to par with the best currently used feature-based approaches. The density representation preserves all static information present in the observational data, in contrast to a less-complete description by features. The density representation is an upper boundary in terms of information made available to the classifier. Consequently, the predictive power of the proposed classification depends on the choice of similarity measure and classifier, only. Due to its principled nature, we advocate that this new approach of representing time series has potential in tasks beyond classification, e.g. unsupervised learning.

Numerical flux formulas for the Euler and Navier-Stokes equations. 2: Progress in flux-vector splitting

NASA Technical Reports Server (NTRS)

Coirier, William J.; Vanleer, Bram

1991-01-01

The accuracy of various numerical flux functions for the inviscid fluxes when used for Navier-Stokes computations is studied. The flux functions are benchmarked for solutions of the viscous, hypersonic flow past a 10 degree cone at zero angle of attack using first order, upwind spatial differencing. The Harten-Lax/Roe flux is found to give a good boundary layer representation, although its robustness is an issue. Some hybrid flux formulas, where the concepts of flux-vector and flux-difference splitting are combined, are shown to give unsatisfactory pressure distributions; there is still room for improvement. Investigations of low diffusion, pure flux-vector splittings indicate that a pure flux-vector splitting can be developed that eliminates spurious diffusion across the boundary layer. The resulting first-order scheme is marginally stable and not monotone.

Predicting and understanding law-making with word vectors and an ensemble model.

PubMed

Nay, John J

2017-01-01

Out of nearly 70,000 bills introduced in the U.S. Congress from 2001 to 2015, only 2,513 were enacted. We developed a machine learning approach to forecasting the probability that any bill will become law. Starting in 2001 with the 107th Congress, we trained models on data from previous Congresses, predicted all bills in the current Congress, and repeated until the 113th Congress served as the test. For prediction we scored each sentence of a bill with a language model that embeds legislative vocabulary into a high-dimensional, semantic-laden vector space. This language representation enables our investigation into which words increase the probability of enactment for any topic. To test the relative importance of text and context, we compared the text model to a context-only model that uses variables such as whether the bill's sponsor is in the majority party. To test the effect of changes to bills after their introduction on our ability to predict their final outcome, we compared using the bill text and meta-data available at the time of introduction with using the most recent data. At the time of introduction context-only predictions outperform text-only, and with the newest data text-only outperforms context-only. Combining text and context always performs best. We conducted a global sensitivity analysis on the combined model to determine important variables predicting enactment.

Predicting and understanding law-making with word vectors and an ensemble model

PubMed Central

Nay, John J.

2017-01-01

Out of nearly 70,000 bills introduced in the U.S. Congress from 2001 to 2015, only 2,513 were enacted. We developed a machine learning approach to forecasting the probability that any bill will become law. Starting in 2001 with the 107th Congress, we trained models on data from previous Congresses, predicted all bills in the current Congress, and repeated until the 113th Congress served as the test. For prediction we scored each sentence of a bill with a language model that embeds legislative vocabulary into a high-dimensional, semantic-laden vector space. This language representation enables our investigation into which words increase the probability of enactment for any topic. To test the relative importance of text and context, we compared the text model to a context-only model that uses variables such as whether the bill’s sponsor is in the majority party. To test the effect of changes to bills after their introduction on our ability to predict their final outcome, we compared using the bill text and meta-data available at the time of introduction with using the most recent data. At the time of introduction context-only predictions outperform text-only, and with the newest data text-only outperforms context-only. Combining text and context always performs best. We conducted a global sensitivity analysis on the combined model to determine important variables predicting enactment. PMID:28489868

A Reaction-Diffusion Model of Vector-Borne Disease with Periodic Delays

NASA Astrophysics Data System (ADS)

Wu, Ruiwen; Zhao, Xiao-Qiang

2018-06-01

A vector-borne disease is caused by a range of pathogens and transmitted to hosts through vectors. To investigate the multiple effects of the spatial heterogeneity, the temperature sensitivity of extrinsic incubation period and intrinsic incubation period, and the seasonality on disease transmission, we propose a nonlocal reaction-diffusion model of vector-borne disease with periodic delays. We introduce the basic reproduction number R_0 for this model and then establish a threshold-type result on its global dynamics in terms of R_0 . In the case where all the coefficients are constants, we also prove the global attractivity of the positive constant steady state when R_0>1 . Numerically, we study the malaria transmission in Maputo Province, Mozambique.

Novel Spectral Representations and Sparsity-Driven Algorithms for Shape Modeling and Analysis

NASA Astrophysics Data System (ADS)

Zhong, Ming

In this dissertation, we focus on extending classical spectral shape analysis by incorporating spectral graph wavelets and sparsity-seeking algorithms. Defined with the graph Laplacian eigenbasis, the spectral graph wavelets are localized both in the vertex domain and graph spectral domain, and thus are very effective in describing local geometry. With a rich dictionary of elementary vectors and forcing certain sparsity constraints, a real life signal can often be well approximated by a very sparse coefficient representation. The many successful applications of sparse signal representation in computer vision and image processing inspire us to explore the idea of employing sparse modeling techniques with dictionary of spectral basis to solve various shape modeling problems. Conventional spectral mesh compression uses the eigenfunctions of mesh Laplacian as shape bases, which are highly inefficient in representing local geometry. To ameliorate, we advocate an innovative approach to 3D mesh compression using spectral graph wavelets as dictionary to encode mesh geometry. The spectral graph wavelets are locally defined at individual vertices and can better capture local shape information than Laplacian eigenbasis. The multi-scale SGWs form a redundant dictionary as shape basis, so we formulate the compression of 3D shape as a sparse approximation problem that can be readily handled by greedy pursuit algorithms. Surface inpainting refers to the completion or recovery of missing shape geometry based on the shape information that is currently available. We devise a new surface inpainting algorithm founded upon the theory and techniques of sparse signal recovery. Instead of estimating the missing geometry directly, our novel method is to find this low-dimensional representation which describes the entire original shape. More specifically, we find that, for many shapes, the vertex coordinate function can be well approximated by a very sparse coefficient representation with respect to the dictionary comprising its Laplacian eigenbasis, and it is then possible to recover this sparse representation from partial measurements of the original shape. Taking advantage of the sparsity cue, we advocate a novel variational approach for surface inpainting, integrating data fidelity constraints on the shape domain with coefficient sparsity constraints on the transformed domain. Because of the powerful properties of Laplacian eigenbasis, the inpainting results of our method tend to be globally coherent with the remaining shape. Informative and discriminative feature descriptors are vital in qualitative and quantitative shape analysis for a large variety of graphics applications. We advocate novel strategies to define generalized, user-specified features on shapes. Our new region descriptors are primarily built upon the coefficients of spectral graph wavelets that are both multi-scale and multi-level in nature, consisting of both local and global information. Based on our novel spectral feature descriptor, we developed a user-specified feature detection framework and a tensor-based shape matching algorithm. Through various experiments, we demonstrate the competitive performance of our proposed methods and the great potential of spectral basis and sparsity-driven methods for shape modeling.

On bipartite pure-state entanglement structure in terms of disentanglement

NASA Astrophysics Data System (ADS)

Herbut, Fedor

2006-12-01

Schrödinger's disentanglement [E. Schrödinger, Proc. Cambridge Philos. Soc. 31, 555 (1935)], i.e., remote state decomposition, as a physical way to study entanglement, is carried one step further with respect to previous work in investigating the qualitative side of entanglement in any bipartite state vector. Remote measurement (or, equivalently, remote orthogonal state decomposition) from previous work is generalized to remote linearly independent complete state decomposition both in the nonselective and the selective versions. The results are displayed in terms of commutative square diagrams, which show the power and beauty of the physical meaning of the (antiunitary) correlation operator inherent in the given bipartite state vector. This operator, together with the subsystem states (reduced density operators), constitutes the so-called correlated subsystem picture. It is the central part of the antilinear representation of a bipartite state vector, and it is a kind of core of its entanglement structure. The generalization of previously elaborated disentanglement expounded in this article is a synthesis of the antilinear representation of bipartite state vectors, which is reviewed, and the relevant results of [Cassinelli et al., J. Math. Anal. Appl. 210, 472 (1997)] in mathematical analysis, which are summed up. Linearly independent bases (finite or infinite) are shown to be almost as useful in some quantum mechanical studies as orthonormal ones. Finally, it is shown that linearly independent remote pure-state preparation carries the highest probability of occurrence. This singles out linearly independent remote influence from all possible ones.

Global traffic and disease vector dispersal

PubMed Central

Tatem, Andrew J.; Hay, Simon I.; Rogers, David J.

2006-01-01

The expansion of global air travel and seaborne trade overcomes geographic barriers to insect disease vectors, enabling them to move great distances in short periods of time. Here we apply a coupled human–environment framework to describe the historical spread of Aedes albopictus, a competent mosquito vector of 22 arboviruses in the laboratory. We contrast this dispersal with the relatively unchanged distribution of Anopheles gambiae and examine possible future movements of this malaria vector. We use a comprehensive database of international ship and aircraft traffic movements, combined with climatic information, to remap the global transportation network in terms of disease vector suitability and accessibility. The expansion of the range of Ae. albopictus proved to be surprisingly predictable using this combination of climate and traffic data. Traffic volumes were more than twice as high on shipping routes running from the historical distribution of Ae. albopictus to ports where it has established in comparison with routes to climatically similar ports where it has yet to invade. In contrast, An. gambiae has rarely spread from Africa, which we suggest is partly due to the low volume of sea traffic from the continent and, until very recently, a European destination for most flights. PMID:16606847

Custodial vector model

NASA Astrophysics Data System (ADS)

Becciolini, Diego; Franzosi, Diogo Buarque; Foadi, Roshan; Frandsen, Mads T.; Hapola, Tuomas; Sannino, Francesco

2015-07-01

We analyze the Large Hadron Collider (LHC) phenomenology of heavy vector resonances with a S U (2 )L×S U (2 )R spectral global symmetry. This symmetry partially protects the electroweak S parameter from large contributions of the vector resonances. The resulting custodial vector model spectrum and interactions with the standard model fields lead to distinct signatures at the LHC in the diboson, dilepton, and associated Higgs channels.

Air travel and vector-borne disease movement.

PubMed

Tatem, A J; Huang, Z; Das, A; Qi, Q; Roth, J; Qiu, Y

2012-12-01

Recent decades have seen substantial expansions in the global air travel network and rapid increases in traffic volumes. The effects of this are well studied in terms of the spread of directly transmitted infections, but the role of air travel in the movement of vector-borne diseases is less well understood. Increasingly however, wider reaching surveillance for vector-borne diseases and our improving abilities to map the distributions of vectors and the diseases they carry, are providing opportunities to better our understanding of the impact of increasing air travel. Here we examine global trends in the continued expansion of air transport and its impact upon epidemiology. Novel malaria and chikungunya examples are presented, detailing how geospatial data in combination with information on air traffic can be used to predict the risks of vector-borne disease importation and establishment. Finally, we describe the development of an online tool, the Vector-Borne Disease Airline Importation Risk (VBD-Air) tool, which brings together spatial data on air traffic and vector-borne disease distributions to quantify the seasonally changing risks for importation to non-endemic regions. Such a framework provides the first steps towards an ultimate goal of adaptive management based on near real time flight data and vector-borne disease surveillance.

Vector Doppler: spatial sampling analysis and presentation techniques for real-time systems

NASA Astrophysics Data System (ADS)

Capineri, Lorenzo; Scabia, Marco; Masotti, Leonardo F.

2001-05-01

The aim of the vector Doppler (VD) technique is the quantitative reconstruction of a velocity field independently of the ultrasonic probe axis to flow angle. In particular vector Doppler is interesting for studying vascular pathologies related to complex blood flow conditions. Clinical applications require a real-time operating mode and the capability to perform Doppler measurements over a defined volume. The combination of these two characteristics produces a real-time vector velocity map. In previous works the authors investigated the theory of pulsed wave (PW) vector Doppler and developed an experimental system capable of producing off-line 3D vector velocity maps. Afterwards, for producing dynamic velocity vector maps, we realized a new 2D vector Doppler system based on a modified commercial echograph. The measurement and presentation of a vector velocity field requires a correct spatial sampling that must satisfy the Shannon criterion. In this work we tackled this problem, establishing a relationship between sampling steps and scanning system characteristics. Another problem posed by the vector Doppler technique is the data representation in real-time that should be easy to interpret for the physician. With this in mine we attempted a multimedia solution that uses both interpolated images and sound to represent the information of the measured vector velocity map. These presentation techniques were experimented for real-time scanning on flow phantoms and preliminary measurements in vivo on a human carotid artery.

Magnetic space-based field measurements

NASA Technical Reports Server (NTRS)

Langel, R. A.

1981-01-01

Because the near Earth magnetic field is a complex combination of fields from outside the Earth of fields from its core and of fields from its crust, measurements from space prove to be the only practical way to obtain timely, global surveys. Due to difficulty in making accurate vector measurements, early satellites such as Sputnik and Vanguard measured only the magnitude survey. The attitude accuracy was 20 arc sec. Both the Earth's core fields and the fields arising from its crust were mapped from satellite data. The standard model of the core consists of a scalar potential represented by a spherical harmonics series. Models of the crustal field are relatively new. Mathematical representation is achieved in localized areas by arrays of dipoles appropriately located in the Earth's crust. Measurements of the Earth's field are used in navigation, to map charged particles in the magnetosphere, to study fluid properties in the Earth's core, to infer conductivity of the upper mantels, and to delineate regional scale geological features.

Diffuse Pacific-North American plate boundary: 1000 km of dextral shear inferred from modeling geodetic data

USGS Publications Warehouse

Parsons, T.; Thatcher, W.

2011-01-01

Geodetic measurements tell us that the eastern part of the Basin and Range Province expands in an east-west direction relative to stable North America, whereas the western part of the province moves to the northwest. We develop three-dimensional finite element representations of the western United States lithosphere in an effort to understand the global positioning system (GPS) signal. The models are constrained by known bounding-block velocities and topography, and Basin and Range Province deformation is represented by simple plastic (thermal creep) rheology. We show that active Basin and Range spreading by gravity collapse is expected to have a strong southward component that does not match the GPS signal. We can reconcile the gravitational component of displacement with observed velocity vectors if the Pacific plate applies northwest-directed shear stress to the Basin and Range via the Sierra Nevada block. This effect reaches at least 1000 km east of the San Andreas fault in our models. ?? 2011 Geological Society of America.

Global Representations of Goal-Directed Behavior in Distinct Cell Types of Mouse Neocortex

PubMed Central

Allen, William E.; Kauvar, Isaac V.; Chen, Michael Z.; Richman, Ethan B.; Yang, Samuel J.; Chan, Ken; Gradinaru, Viviana; Deverman, Benjamin E.; Luo, Liqun; Deisseroth, Karl

2017-01-01

SUMMARY The successful planning and execution of adaptive behaviors in mammals may require long-range coordination of neural networks throughout cerebral cortex. The neuronal implementation of signals that could orchestrate cortex-wide activity remains unclear. Here, we develop and apply methods for cortex-wide Ca2+ imaging in mice performing decision-making behavior and identify a global cortical representation of task engagement encoded in the activity dynamics of both single cells and superficial neuropil distributed across the majority of dorsal cortex. The activity of multiple molecularly defined cell types was found to reflect this representation with type-specific dynamics. Focal optogenetic inhibition tiled across cortex revealed a crucial role for frontal cortex in triggering this cortex-wide phenomenon; local inhibition of this region blocked both the cortex-wide response to task-initiating cues and the voluntary behavior. These findings reveal cell-type-specific processes in cortex for globally representing goal-directed behavior and identify a major cortical node that gates the global broadcast of task-related information. PMID:28521139

Prediction of cause of death from forensic autopsy reports using text classification techniques: A comparative study.

PubMed

Mujtaba, Ghulam; Shuib, Liyana; Raj, Ram Gopal; Rajandram, Retnagowri; Shaikh, Khairunisa

2018-07-01

Automatic text classification techniques are useful for classifying plaintext medical documents. This study aims to automatically predict the cause of death from free text forensic autopsy reports by comparing various schemes for feature extraction, term weighing or feature value representation, text classification, and feature reduction. For experiments, the autopsy reports belonging to eight different causes of death were collected, preprocessed and converted into 43 master feature vectors using various schemes for feature extraction, representation, and reduction. The six different text classification techniques were applied on these 43 master feature vectors to construct a classification model that can predict the cause of death. Finally, classification model performance was evaluated using four performance measures i.e. overall accuracy, macro precision, macro-F-measure, and macro recall. From experiments, it was found that that unigram features obtained the highest performance compared to bigram, trigram, and hybrid-gram features. Furthermore, in feature representation schemes, term frequency, and term frequency with inverse document frequency obtained similar and better results when compared with binary frequency, and normalized term frequency with inverse document frequency. Furthermore, the chi-square feature reduction approach outperformed Pearson correlation, and information gain approaches. Finally, in text classification algorithms, support vector machine classifier outperforms random forest, Naive Bayes, k-nearest neighbor, decision tree, and ensemble-voted classifier. Our results and comparisons hold practical importance and serve as references for future works. Moreover, the comparison outputs will act as state-of-art techniques to compare future proposals with existing automated text classification techniques. Copyright © 2017 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Ontology patterns for tabular representations of biomedical knowledge on neglected tropical diseases

PubMed Central

Santana, Filipe; Schober, Daniel; Medeiros, Zulma; Freitas, Fred; Schulz, Stefan

2011-01-01

Motivation: Ontology-like domain knowledge is frequently published in a tabular format embedded in scientific publications. We explore the re-use of such tabular content in the process of building NTDO, an ontology of neglected tropical diseases (NTDs), where the representation of the interdependencies between hosts, pathogens and vectors plays a crucial role. Results: As a proof of concept we analyzed a tabular compilation of knowledge about pathogens, vectors and geographic locations involved in the transmission of NTDs. After a thorough ontological analysis of the domain of interest, we formulated a comprehensive design pattern, rooted in the biomedical domain upper level ontology BioTop. This pattern was implemented in a VBA script which takes cell contents of an Excel spreadsheet and transforms them into OWL-DL. After minor manual post-processing, the correctness and completeness of the ontology was tested using pre-formulated competence questions as description logics (DL) queries. The expected results could be reproduced by the ontology. The proposed approach is recommended for optimizing the acquisition of ontological domain knowledge from tabular representations. Availability and implementation: Domain examples, source code and ontology are freely available on the web at http://www.cin.ufpe.br/~ntdo. Contact: fss3@cin.ufpe.br PMID:21685092

Random function representation of stationary stochastic vector processes for probability density evolution analysis of wind-induced structures

NASA Astrophysics Data System (ADS)

Liu, Zhangjun; Liu, Zenghui

2018-06-01

This paper develops a hybrid approach of spectral representation and random function for simulating stationary stochastic vector processes. In the proposed approach, the high-dimensional random variables, included in the original spectral representation (OSR) formula, could be effectively reduced to only two elementary random variables by introducing the random functions that serve as random constraints. Based on this, a satisfactory simulation accuracy can be guaranteed by selecting a small representative point set of the elementary random variables. The probability information of the stochastic excitations can be fully emerged through just several hundred of sample functions generated by the proposed approach. Therefore, combined with the probability density evolution method (PDEM), it could be able to implement dynamic response analysis and reliability assessment of engineering structures. For illustrative purposes, a stochastic turbulence wind velocity field acting on a frame-shear-wall structure is simulated by constructing three types of random functions to demonstrate the accuracy and efficiency of the proposed approach. Careful and in-depth studies concerning the probability density evolution analysis of the wind-induced structure have been conducted so as to better illustrate the application prospects of the proposed approach. Numerical examples also show that the proposed approach possesses a good robustness.

Vestibular stimulation interferes with the dynamics of an internal representation of gravity.

PubMed

De Sá Teixeira, Nuno Alexandre; Hecht, Heiko; Diaz Artiles, Ana; Seyedmadani, Kimia; Sherwood, David P; Young, Laurence R

2017-11-01

The remembered vanishing location of a moving target has been found to be displaced downward in the direction of gravity (representational gravity) and more so with increasing retention intervals, suggesting that the visual spatial updating recruits an internal model of gravity. Despite being consistently linked with gravity, few inquiries have been made about the role of vestibular information in these trends. Previous experiments with static tilting of observers' bodies suggest that under conflicting cues between the idiotropic vector and vestibular signals, the dynamic drift in memory is reduced to a constant displacement along the body's main axis. The present experiment aims to replicate and extend these outcomes while keeping the observers' bodies unchanged in relation to physical gravity by varying the gravito-inertial acceleration using a short-radius centrifuge. Observers were shown, while accelerated to varying degrees, targets moving along several directions and were required to indicate the perceived vanishing location after a variable interval. Increases of the gravito-inertial force (up to 1.4G), orthogonal to the idiotropic vector, did not affect the direction of representational gravity, but significantly disrupted its time course. The role and functioning of an internal model of gravity for spatial perception and orientation are discussed in light of the results.

Phason thermal transport of three-helix state in insulating chiral magnets

NASA Astrophysics Data System (ADS)

Tatara, Gen

2018-06-01

Thermal dynamics of the three-helix state in a chiral magnet is studied based on a phason representation. Although phason representation is convenient for intuitive description, it is not straightforwardly compatible with microscopic linear response calculation of transport phenomena, because it is a (semi)macroscopic picture obtained by a coarse graining. By separating the slow phason mode and fast magnon mode, we show that phason thermal dynamics is driven by thermal magnon flow via the spin-transfer effect. The magnon and phason velocities are calculated by use of thermal vector potential formalism.

New vector-like fermions and flavor physics

DOE PAGES

Ishiwata, Koji; Ligeti, Zoltan; Wise, Mark B.

2015-10-06

We study renormalizable extensions of the standard model that contain vector-like fermions in a (single) complex representation of the standard model gauge group. There are 11 models where the vector-like fermions Yukawa couple to the standard model fermions via the Higgs field. These models do not introduce additional fine-tunings. They can lead to, and are constrained by, a number of different flavor-changing processes involving leptons and quarks, as well as direct searches. An interesting feature of the models with strongly interacting vector-like fermions is that constraints from neutral meson mixings (apart from CP violation inmore » $$ {K}^0-{\\overline{K}}^0 $$ mixing) are not sensitive to higher scales than other flavor-changing neutral-current processes. We identify order 1/(4πM) 2 (where M is the vector-like fermion mass) one-loop contributions to the coefficients of the four-quark operators for meson mixing, that are not suppressed by standard model quark masses and/or mixing angles.« less

Direction-of-arrival estimation for a uniform circular acoustic vector-sensor array mounted around a cylindrical baffle

NASA Astrophysics Data System (ADS)

Yang, DeSen; Zhu, ZhongRui

2012-12-01

This work investigates the direction-of-arrival (DOA) estimation for a uniform circular acoustic Vector-Sensor Array (UCAVSA) mounted around a cylindrical baffle. The total pressure field and the total particle velocity field near the surface of the cylindrical baffle are analyzed theoretically by applying the method of spatial Fourier transform. Then the so-called modal vector-sensor array signal processing algorithm, which is based on the decomposed wavefield representations, for the UCAVSA mounted around the cylindrical baffle is proposed. Simulation and experimental results show that the UCAVSA mounted around the cylindrical baffle has distinct advantages over the same manifold of traditional uniform circular pressure-sensor array (UCPSA). It is pointed out that the acoustic Vector-Sensor (AVS) could be used under the condition of the cylindrical baffle and that the UCAVSA mounted around the cylindrical baffle could also combine the anti-noise performance of the AVS with spatial resolution performance of array system by means of modal vector-sensor array signal processing algorithms.

On the description of conical intersections—A continuous representation of the local topography of seams of conical intersection of three or more electronic states: A generalization of the two state result

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

Zhu, Xiaolei, E-mail: virtualzx@gmail.com; Yarkony, David R., E-mail: yarkony@jhu.edu

2014-11-07

For conical intersections of two states (I,J = I + 1) the vectors defining the branching or g-h plane, the energy difference gradient vector g{sup I,J}, and the interstate coupling vector h{sup I,J}, can be made orthogonal by a one parameter rotation of the degenerate electronic eigenstates. The representation obtained from this rotation is used to construct the parameters that describe the vicinity of the conical intersection seam, the conical parameters, s{sup I,J}{sub x} (R), s{sup I,J}{sub y} (R), g{sup I,J}(R), and h{sup I,J}(R). As a result of the orthogonalization these parameters can be made continuous functions of R, themore » internuclear coordinates. In this work we generalize this notion to construct continuous parametrizations of conical intersection seams of three or more states. The generalization derives from a recently introduced procedure for using non-degenerate electronic states to construct coupled diabatic states that represent adiabatic states coupled by conical intersections. The procedure is illustrated using the seam of conical intersections of three states in parazolyl as an example.« less

The effect of global warming on infectious diseases.

PubMed

Kurane, Ichiro

2010-12-01

Global warming has various effects on human health. The main indirect effects are on infectious diseases. Although the effects on infectious diseases will be detected worldwide, the degree and types of the effect are different, depending on the location of the respective countries and socioeconomical situations. Among infectious diseases, water- and foodborne infectious diseases and vector-borne infectious diseases are two main categories that are forecasted to be most affected. The effect on vector-borne infectious diseases such as malaria and dengue fever is mainly because of the expansion of the infested areas of vector mosquitoes and increase in the number and feeding activity of infected mosquitoes. There will be increase in the number of cases with water- and foodborne diarrhoeal diseases. Even with the strongest mitigation procedures, global warming cannot be avoided for decades. Therefore, implementation of adaptation measures to the effect of global warming is the most practical action we can take. It is generally accepted that the impacts of global warming on infectious diseases have not been apparent at this point yet in East Asia. However, these impacts will appear in one form or another if global warming continues to progress in future. Further research on the impacts of global warming on infectious diseases and on future prospects should be conducted.

A Heisenberg Algebra Bundle of a Vector Field in Three-Space and its Weyl Quantization

NASA Astrophysics Data System (ADS)

Binz, Ernst; Pods, Sonja

2006-01-01

In these notes we associate a natural Heisenberg group bundle Ha with a singularity free smooth vector field X = (id,a) on a submanifold M in a Euclidean three-space. This bundle yields naturally an infinite dimensional Heisenberg group HX∞. A representation of the C*-group algebra of HX∞ is a quantization. It causes a natural Weyl-deformation quantization of X. The influence of the topological structure of M on this quantization is encoded in the Chern class of a canonical complex line bundle inside Ha.

Decision Support Tool for Deep Energy Efficiency Retrofits in DoD Installations

DTIC Science & Technology

2014-01-01

representations (HDMR). Chemical Engineering Science, 57, 4445–4460. 2. Sobol ’, I., 2001. Global sensitivity indices for nonlinear mathematical...models and their Monte Carlo estimates. Mathematics and computers in simulation, 55, 271–280. 3. Sobol , I. and Kucherenko, S., 2009. Derivative based...representations (HDMR). Chemical Engineering Science, 57, 4445–4460. 16. Sobol ’, I., 2001. Global sensitivity indices for nonlinear mathematical models and

Granger Causality Testing with Intensive Longitudinal Data.

PubMed

Molenaar, Peter C M

2018-06-01

The availability of intensive longitudinal data obtained by means of ambulatory assessment opens up new prospects for prevention research in that it allows the derivation of subject-specific dynamic networks of interacting variables by means of vector autoregressive (VAR) modeling. The dynamic networks thus obtained can be subjected to Granger causality testing in order to identify causal relations among the observed time-dependent variables. VARs have two equivalent representations: standard and structural. Results obtained with Granger causality testing depend upon which representation is chosen, yet no criteria exist on which this important choice can be based. A new equivalent representation is introduced called hybrid VARs with which the best representation can be chosen in a data-driven way. Partial directed coherence, a frequency-domain statistic for Granger causality testing, is shown to perform optimally when based on hybrid VARs. An application to real data is provided.

Control of Initialized Fractional-Order Systems. Revised

NASA Technical Reports Server (NTRS)

Hartley, Tom T.; Lorenzo, Carl F.

2002-01-01

Due to the importance of historical effects in fractional-order systems, this paper presents a general fractional-order control theory that includes the time-varying initialization response. Previous studies have not properly accounted for these historical effects. The initialization response, along with the forced response, for fractional-order systems is determined. Stability properties of fractional-order systems are presented in the complex w-plane, which is a transformation of the s-plane. Time responses are discussed with respect to pole positions in the complex w-plane and frequency response behavior is included. A fractional-order vector space representation, which is a generalization of the state space concept, is presented including the initialization response. Control methods for vector representations of initialized fractional-order systems are shown. Nyquist, root-locus, and other input-output control methods are adapted to the control of fractional-order systems. Finally, the fractional-order differintegral is generalized to continuous order-distributions that have the possibility of including a continuum of fractional orders in a system element.

Control of Initialized Fractional-Order Systems

NASA Technical Reports Server (NTRS)

Hartly, Tom T.; Lorenzo, Carl F.

2002-01-01

Due to the importance of historical effects in fractional-order systems, this paper presents a general fractional-order control theory that includes the time-varying initialization response. Previous studies have not properly accounted for these historical effects. The initialization response, along with the forced response, for fractional-order systems is determined. Stability properties of fractional-order systems are presented in the complex Airplane, which is a transformation of the s-plane. Time responses are discussed with respect to pole positions in the complex Airplane and frequency response behavior is included. A fractional-order vector space representation, which is a generalization of the state space concept, is presented including the initialization response. Control methods for vector representations of initialized fractional-order systems are shown. Nyquist, root-locus, and other input-output control methods are adapted to the control of fractional-order systems. Finally, the fractional-order differintegral is generalized to continuous order-distributions that have the possibility of including a continuum of fractional orders in a system element.

Applying knowledge engineering and representation methods to improve support vector machine and multivariate probabilistic neural network CAD performance

NASA Astrophysics Data System (ADS)

Land, Walker H., Jr.; Anderson, Frances; Smith, Tom; Fahlbusch, Stephen; Choma, Robert; Wong, Lut

2005-04-01

Achieving consistent and correct database cases is crucial to the correct evaluation of any computer-assisted diagnostic (CAD) paradigm. This paper describes the application of artificial intelligence (AI), knowledge engineering (KE) and knowledge representation (KR) to a data set of ~2500 cases from six separate hospitals, with the objective of removing/reducing inconsistent outlier data. Several support vector machine (SVM) kernels were used to measure diagnostic performance of the original and a "cleaned" data set. Specifically, KE and ER principles were applied to the two data sets which were re-examined with respect to the environment and agents. One data set was found to contain 25 non-characterizable sets. The other data set contained 180 non-characterizable sets. CAD system performance was measured with both the original and "cleaned" data sets using two SVM kernels as well as a multivariate probabilistic neural network (PNN). Results demonstrated: (i) a 10% average improvement in overall Az and (ii) approximately a 50% average improvement in partial Az.

High-order graph matching based feature selection for Alzheimer's disease identification.

PubMed

Liu, Feng; Suk, Heung-Il; Wee, Chong-Yaw; Chen, Huafu; Shen, Dinggang

2013-01-01

One of the main limitations of l1-norm feature selection is that it focuses on estimating the target vector for each sample individually without considering relations with other samples. However, it's believed that the geometrical relation among target vectors in the training set may provide useful information, and it would be natural to expect that the predicted vectors have similar geometric relations as the target vectors. To overcome these limitations, we formulate this as a graph-matching feature selection problem between a predicted graph and a target graph. In the predicted graph a node is represented by predicted vector that may describe regional gray matter volume or cortical thickness features, and in the target graph a node is represented by target vector that include class label and clinical scores. In particular, we devise new regularization terms in sparse representation to impose high-order graph matching between the target vectors and the predicted ones. Finally, the selected regional gray matter volume and cortical thickness features are fused in kernel space for classification. Using the ADNI dataset, we evaluate the effectiveness of the proposed method and obtain the accuracies of 92.17% and 81.57% in AD and MCI classification, respectively.

Fast protein tertiary structure retrieval based on global surface shape similarity.

PubMed

Sael, Lee; Li, Bin; La, David; Fang, Yi; Ramani, Karthik; Rustamov, Raif; Kihara, Daisuke

2008-09-01

Characterization and identification of similar tertiary structure of proteins provides rich information for investigating function and evolution. The importance of structure similarity searches is increasing as structure databases continue to expand, partly due to the structural genomics projects. A crucial drawback of conventional protein structure comparison methods, which compare structures by their main-chain orientation or the spatial arrangement of secondary structure, is that a database search is too slow to be done in real-time. Here we introduce a global surface shape representation by three-dimensional (3D) Zernike descriptors, which represent a protein structure compactly as a series expansion of 3D functions. With this simplified representation, the search speed against a few thousand structures takes less than a minute. To investigate the agreement between surface representation defined by 3D Zernike descriptor and conventional main-chain based representation, a benchmark was performed against a protein classification generated by the combinatorial extension algorithm. Despite the different representation, 3D Zernike descriptor retrieved proteins of the same conformation defined by combinatorial extension in 89.6% of the cases within the top five closest structures. The real-time protein structure search by 3D Zernike descriptor will open up new possibility of large-scale global and local protein surface shape comparison. 2008 Wiley-Liss, Inc.

Mathematical Methods for Physics and Engineering Third Edition Paperback Set

NASA Astrophysics Data System (ADS)

Riley, Ken F.; Hobson, Mike P.; Bence, Stephen J.

2006-06-01

Prefaces; 1. Preliminary algebra; 2. Preliminary calculus; 3. Complex numbers and hyperbolic functions; 4. Series and limits; 5. Partial differentiation; 6. Multiple integrals; 7. Vector algebra; 8. Matrices and vector spaces; 9. Normal modes; 10. Vector calculus; 11. Line, surface and volume integrals; 12. Fourier series; 13. Integral transforms; 14. First-order ordinary differential equations; 15. Higher-order ordinary differential equations; 16. Series solutions of ordinary differential equations; 17. Eigenfunction methods for differential equations; 18. Special functions; 19. Quantum operators; 20. Partial differential equations: general and particular; 21. Partial differential equations: separation of variables; 22. Calculus of variations; 23. Integral equations; 24. Complex variables; 25. Application of complex variables; 26. Tensors; 27. Numerical methods; 28. Group theory; 29. Representation theory; 30. Probability; 31. Statistics; Index.

Vector representation of lithium and other mica compositions

NASA Technical Reports Server (NTRS)

Burt, Donald M.

1991-01-01

In contrast to mathematics, where a vector of one component defines a line, in chemical petrology a one-component system is a point, and two components are needed to define a line, three for a plane, and four for a space. Here, an attempt is made to show how these differences in the definition of a component can be resolved, with lithium micas used as an example. In particular, the condensed composition space theoretically accessible to Li-Fe-Al micas is shown to be an irregular three-dimensional polyhedron, rather than the triangle Al(3+)-Fe(2+)-Li(+), used by some researchers. This result is demonstrated starting with the annite composition and using exchange operators graphically as vectors that generate all of the other mica compositions.

The boundary vector cell model of place cell firing and spatial memory

PubMed Central

Barry, Caswell; Lever, Colin; Hayman, Robin; Hartley, Tom; Burton, Stephen; O'Keefe, John; Jeffery, Kate; Burgess, Neil

2009-01-01

We review evidence for the boundary vector cell model of the environmental determinants of the firing of hippocampal place cells. Preliminary experimental results are presented concerning the effects of addition or removal of environmental boundaries on place cell firing and evidence that boundary vector cells may exist in the subiculum. We review and update computational simulations predicting the location of human search within a virtual environment of variable geometry, assuming that boundary vector cells provide one of the input representations of location used in mammalian spatial memory. Finally, we extend the model to include experience-dependent modification of connection strengths through a BCM-like learning rule, and compare the effects to experimental data on the firing of place cells under geometrical manipulations to their environment. The relationship between neurophysiological results in rats and spatial behaviour in humans is discussed. PMID:16703944

[Transposition errors during learning to reproduce a sequence by the right- and the left-hand movements: simulation of positional and movement coding].

PubMed

Liakhovetskiĭ, V A; Bobrova, E V; Skopin, G N

2012-01-01

Transposition errors during the reproduction of a hand movement sequence make it possible to receive important information on the internal representation of this sequence in the motor working memory. Analysis of such errors showed that learning to reproduce sequences of the left-hand movements improves the system of positional coding (coding ofpositions), while learning of the right-hand movements improves the system of vector coding (coding of movements). Learning of the right-hand movements after the left-hand performance involved the system of positional coding "imposed" by the left hand. Learning of the left-hand movements after the right-hand performance activated the system of vector coding. Transposition errors during learning to reproduce movement sequences can be explained by neural network using either vector coding or both vector and positional coding.

IIB supergravity and the E 6(6) covariant vector-tensor hierarchy

DOE PAGES

Ciceri, Franz; de Wit, Bernard; Varela, Oscar

2015-04-20

IIB supergravity is reformulated with a manifest local USp(8) invariance that makes the embedding of five-dimensional maximal supergravities transparent. In this formulation the ten-dimensional theory exhibits all the 27 one-form fields and 22 of the 27 two-form fields that are required by the vector-tensor hierarchy of the five-dimensional theory. The missing 5 two-form fields must transform in the same representation as a descendant of the ten-dimensional ‘dual graviton’. The invariant E 6(6) symmetric tensor that appears in the vector-tensor hierarchy is reproduced. Generalized vielbeine are derived from the supersymmetry transformations of the vector fields, as well as consistent expressions formore » the USp(8) covariant fermion fields. Implications are further discussed for the consistency of the truncation of IIB supergravity compactified on the five-sphere to maximal gauged supergravity in five space-time dimensions with an SO(6) gauge group.« less

Method and system for efficient video compression with low-complexity encoder

NASA Technical Reports Server (NTRS)

Chen, Jun (Inventor); He, Dake (Inventor); Sheinin, Vadim (Inventor); Jagmohan, Ashish (Inventor); Lu, Ligang (Inventor)

2012-01-01

Disclosed are a method and system for video compression, wherein the video encoder has low computational complexity and high compression efficiency. The disclosed system comprises a video encoder and a video decoder, wherein the method for encoding includes the steps of converting a source frame into a space-frequency representation; estimating conditional statistics of at least one vector of space-frequency coefficients; estimating encoding rates based on the said conditional statistics; and applying Slepian-Wolf codes with the said computed encoding rates. The preferred method for decoding includes the steps of; generating a side-information vector of frequency coefficients based on previously decoded source data, encoder statistics, and previous reconstructions of the source frequency vector; and performing Slepian-Wolf decoding of at least one source frequency vector based on the generated side-information, the Slepian-Wolf code bits and the encoder statistics.

Global ensemble texture representations are critical to rapid scene perception.

PubMed

Brady, Timothy F; Shafer-Skelton, Anna; Alvarez, George A

2017-06-01

Traditionally, recognizing the objects within a scene has been treated as a prerequisite to recognizing the scene itself. However, research now suggests that the ability to rapidly recognize visual scenes could be supported by global properties of the scene itself rather than the objects within the scene. Here, we argue for a particular instantiation of this view: That scenes are recognized by treating them as a global texture and processing the pattern of orientations and spatial frequencies across different areas of the scene without recognizing any objects. To test this model, we asked whether there is a link between how proficient individuals are at rapid scene perception and how proficiently they represent simple spatial patterns of orientation information (global ensemble texture). We find a significant and selective correlation between these tasks, suggesting a link between scene perception and spatial ensemble tasks but not nonspatial summary statistics In a second and third experiment, we additionally show that global ensemble texture information is not only associated with scene recognition, but that preserving only global ensemble texture information from scenes is sufficient to support rapid scene perception; however, preserving the same information is not sufficient for object recognition. Thus, global ensemble texture alone is sufficient to allow activation of scene representations but not object representations. Together, these results provide evidence for a view of scene recognition based on global ensemble texture rather than a view based purely on objects or on nonspatially localized global properties. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

An improved two-dimensional depth-integrated flow equation for rough-walled fractures

NASA Astrophysics Data System (ADS)

Mallikamas, Wasin; Rajaram, Harihar

2010-08-01

We present the development of an improved 2-D flow equation for rough-walled fractures. Our improved equation accounts for the influence of midsurface tortuosity and the fact that the aperture normal to the midsurface is in general smaller than the vertical aperture. It thus improves upon the well-known Reynolds equation that is widely used for modeling flow in fractures. Unlike the Reynolds equation, our approach begins from the lubrication approximation applied in an inclined local coordinate system tangential to the fracture midsurface. The local flow equation thus obtained is rigorously transformed to an arbitrary global Cartesian coordinate system, invoking the concepts of covariant and contravariant transformations for vectors defined on surfaces. Unlike previously proposed improvements to the Reynolds equation, our improved flow equation accounts for tortuosity both along and perpendicular to a flow path. Our approach also leads to a well-defined anisotropic local transmissivity tensor relating the representations of the flux and head gradient vectors in a global Cartesian coordinate system. We show that the principal components of the transmissivity tensor and the orientation of its principal axes depend on the directional local midsurface slopes. In rough-walled fractures, the orientations of the principal axes of the local transmissivity tensor will vary from point to point. The local transmissivity tensor also incorporates the influence of the local normal aperture, which is uniquely defined at each point in the fracture. Our improved flow equation is a rigorous statement of mass conservation in any global Cartesian coordinate system. We present three examples of simple geometries to compare our flow equation to analytical solutions obtained using the exact Stokes equations: an inclined parallel plate, and circumferential and axial flows in an incomplete annulus. The effective transmissivities predicted by our flow equation agree very well with values obtained using the exact Stokes equations in all these cases. We discuss potential limitations of our depth-integrated equation, which include the neglect of convergence/divergence and the inaccuracies implicit in any depth-averaging process near sharp corners where the wall and midsurface curvatures are large.

Recent Weather Extremes and Impacts on Agricultural Production and Vector-Borne Disease Outbreak Patterns

DTIC Science & Technology

2014-03-21

funding from USDA Foreign Agricultural Service towards the Global Agricultural Monitoring project, DoD Armed Forces Health Surveillance Center’s...Global Emerging Infections Surveillance and Response System (AFHSC/GEIS) under the Human Febrile and Vector -Borne Illnesses (FVBI) Program and USDA ...outbreaks during the 2010?2012 period. We utilized 2000?2012 vegetation index and land surface temperature data from NASA ?s satellitebased Moderate

Insights from agriculture for the management of insecticide resistance in disease vectors.

PubMed

Sternberg, Eleanore D; Thomas, Matthew B

2018-04-01

Key to contemporary management of diseases such as malaria, dengue, and filariasis is control of the insect vectors responsible for transmission. Insecticide-based interventions have contributed to declines in disease burdens in many areas, but this progress could be threatened by the emergence of insecticide resistance in vector populations. Insecticide resistance is likewise a major concern in agriculture, where insect pests can cause substantial yield losses. Here, we explore overlaps between understanding and managing insecticide resistance in agriculture and in public health. We have used the Global Plan for Insecticide Resistance Management in malaria vectors, developed under the auspices of the World Health Organization Global Malaria Program, as a framework for this exploration because it serves as one of the few cohesive documents for managing a global insecticide resistance crisis. Generally, this comparison highlights some fundamental differences between insect control in agriculture and in public health. Moreover, we emphasize that the success of insecticide resistance management strategies is strongly dependent on the biological specifics of each system. We suggest that the biological, operational, and regulatory differences between agriculture and public health limit the wholesale transfer of knowledge and practices from one system to the other. Nonetheless, there are some valuable insights from agriculture that could assist in advancing the existing Global Plan for Insecticide Resistance Management framework.

Epidemic spreading and global stability of an SIS model with an infective vector on complex networks

NASA Astrophysics Data System (ADS)

Kang, Huiyan; Fu, Xinchu

2015-10-01

In this paper, we present a new SIS model with delay on scale-free networks. The model is suitable to describe some epidemics which are not only transmitted by a vector but also spread between individuals by direct contacts. In view of the biological relevance and real spreading process, we introduce a delay to denote average incubation period of disease in a vector. By mathematical analysis, we obtain the epidemic threshold and prove the global stability of equilibria. The simulation shows the delay will effect the epidemic spreading. Finally, we investigate and compare two major immunization strategies, uniform immunization and targeted immunization.

Inflation with a massive vector field nonminimally coupled to gravity

NASA Astrophysics Data System (ADS)

Páramos, J.

2018-01-01

The possibility that inflation is driven by a massive vector field with SO(3) global symmetry nonminimally coupled to gravity is presented. Through an appropriate Ansatz for the vector field, the behaviour of the equations of motion is studied through the ensuing dynamical system, focusing on the characterisation of the ensuing fixed points.

Measurements of wind vectors, eddy momentum transports, and energy conversions in Jupiter's atmosphere from Voyager 1 images

NASA Astrophysics Data System (ADS)

Beebe, R. F.; Ingersoll, A. P.; Hunt, G. E.; Mitchell, J. L.; Muller, J.-P.

1980-01-01

Voyager 1 narrow-angle images were used to obtain displacements of features down to 100 to 200 km in size over intervals of 10 hours. A global map of velocity vectors and longitudinally averaged zonal wind vectors as functions of the latitude, is presented and discussed

PatterNet: a system to learn compact physical design pattern representations for pattern-based analytics

NASA Astrophysics Data System (ADS)

Lutich, Andrey

2017-07-01

This research considers the problem of generating compact vector representations of physical design patterns for analytics purposes in semiconductor patterning domain. PatterNet uses a deep artificial neural network to learn mapping of physical design patterns to a compact Euclidean hyperspace. Distances among mapped patterns in this space correspond to dissimilarities among patterns defined at the time of the network training. Once the mapping network has been trained, PatterNet embeddings can be used as feature vectors with standard machine learning algorithms, and pattern search, comparison, and clustering become trivial problems. PatterNet is inspired by the concepts developed within the framework of generative adversarial networks as well as the FaceNet. Our method facilitates a deep neural network (DNN) to learn directly the compact representation by supplying it with pairs of design patterns and dissimilarity among these patterns defined by a user. In the simplest case, the dissimilarity is represented by an area of the XOR of two patterns. Important to realize that our PatterNet approach is very different to the methods developed for deep learning on image data. In contrast to "conventional" pictures, the patterns in the CAD world are the lists of polygon vertex coordinates. The method solely relies on the promise of deep learning to discover internal structure of the incoming data and learn its hierarchical representations. Artificial intelligence arising from the combination of PatterNet and clustering analysis very precisely follows intuition of patterning/optical proximity correction experts paving the way toward human-like and human-friendly engineering tools.

A Synopsis of Global Mapping of Freshwater Habitats and Biodiversity: Implications for Conservation

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

McManamay, Ryan A.; Griffiths, Natalie A.; DeRolph, Christopher R.

Accurately mapping freshwater habitats and biodiversity at high-resolutions across the globe is essential for assessing the vulnerability and threats to freshwater organisms and prioritizing conservation efforts. Since the 2000s, extensive efforts have been devoted to mapping global freshwater habitats (rivers, lakes, and wetlands), the spatial representation of which has changed dramatically over time with new geospatial data products and improved remote sensing technologies. Some of these mapping efforts, however, are still coarse representations of actual conditions. Likewise, the resolution and scope of global freshwater biodiversity compilation efforts have also increased, but are yet to mirror the spatial resolution and fidelitymore » of mapped freshwater environments. In our synopsis, we find that efforts to map freshwater habitats have been conducted independently of those for freshwater biodiversity; subsequently, there is little congruence in the spatial representation and resolution of the two efforts. We suggest that global species distribution models are needed to fill this information gap; however, limiting data on habitat characteristics at scales that complement freshwater habitats has prohibited global high-resolution biogeography efforts. Emerging research trends, such as mapping habitat alteration in freshwater ecosystems and trait biogeography, show great promise in mechanistically linking global anthropogenic stressors to freshwater biodiversity decline and extinction risk.« less

Inelastic Vector Soliton Collisions: A Lattice-Based Quantum Representation

DTIC Science & Technology

2004-01-01

components in these orthogonal polarizations will travel at slightly different speeds. It can be shown (Lakshmanan & Kanna 2001) that the slowly varying...media. Phys. Rev. E 58, 6752-6758. Kivshar, Y. S. & Agrawal, G. P. 2003 Optical solitons. Academic. Lakshmanan, M. & Kanna , T. 2001 Shape changing

Pneumothorax detection in chest radiographs using local and global texture signatures

NASA Astrophysics Data System (ADS)

Geva, Ofer; Zimmerman-Moreno, Gali; Lieberman, Sivan; Konen, Eli; Greenspan, Hayit

2015-03-01

A novel framework for automatic detection of pneumothorax abnormality in chest radiographs is presented. The suggested method is based on a texture analysis approach combined with supervised learning techniques. The proposed framework consists of two main steps: at first, a texture analysis process is performed for detection of local abnormalities. Labeled image patches are extracted in the texture analysis procedure following which local analysis values are incorporated into a novel global image representation. The global representation is used for training and detection of the abnormality at the image level. The presented global representation is designed based on the distinctive shape of the lung, taking into account the characteristics of typical pneumothorax abnormalities. A supervised learning process was performed on both the local and global data, leading to trained detection system. The system was tested on a dataset of 108 upright chest radiographs. Several state of the art texture feature sets were experimented with (Local Binary Patterns, Maximum Response filters). The optimal configuration yielded sensitivity of 81% with specificity of 87%. The results of the evaluation are promising, establishing the current framework as a basis for additional improvements and extensions.

Geosmithia associated with bark beetles and woodborers in the western USA: taxonomic diversity and vector specificity.

PubMed

Kolařík, Miroslav; Hulcr, Jiri; Tisserat, Ned; De Beer, Wilhelm; Kostovčík, Martin; Kolaříková, Zuzana; Seybold, Steven J; Rizzo, David M

2017-01-01

Fungi in the genus Geosmithia (Ascomycota: Hypocreales) are frequent associates of bark beetles and woodborers that colonize hardwood and coniferous trees. One species, Geosmithia morbida, is an economically damaging invasive species. The authors surveyed the Geosmithia species of California and Colorado, USA, to (i) provide baseline data on taxonomy of Geosmithia and beetle vector specificity across the western USA; (ii) investigate the subcortical beetle fauna for alternative vectors of the invasive G. morbida; and (iii) interpret the community composition of this region within the emerging global biogeography of Geosmithia. Geosmithia was detected in 87% of 126 beetle samples obtained from 39 plant species. Twenty-nine species of Geosmithia were distinguished, of which 13 may be new species. Bark beetles from hardwoods, Cupressus, and Sequoia appear to be regular vectors, with Geosmithia present in all beetle gallery systems examined. Other subcortical insects appear to vector Geosmithia at lower frequencies. Overall, most Geosmithia have a distinct level of vector specificity (mostly high, sometimes low) enabling their separation to generalists and specialists. Plant pathogenic Geosmithia morbida was not found in association with any other beetle besides Pityophthorus juglandis. However, four additional Geosmithia species were found in P. juglandis galleries. When integrated with recent data from other continents, a global pattern of Geosmithia distribution across continents, latitudes, and vectors is emerging: of the 29 Geosmithia species found in the western USA, 12 have not been reported outside of the USA. The most frequently encountered species with the widest global distribution also had the broadest range of beetle vectors. Several Geosmithia spp. with very narrow vector ranges in Europe exhibited the similar degree of specialization in the USA. Such strong canalization in association could reflect an ancient origin of each individual association, or a recent origin and a subsequent diversification in North America.

Mobile Knowledge, Karma Points and Digital Peers: The Tacit Epistemology and Linguistic Representation of MOOCs

ERIC Educational Resources Information Center

Portmess, Lisa

2013-01-01

Media representations of massive open online courses (MOOCs) such as those offered by Coursera, edX and Udacity reflect tension and ambiguity in their bold promise of democratized education and global knowledge sharing. An approach to MOOCs that emphasizes the tacit epistemology of such representations suggests a richer account of the ambiguities…

Global velocity constrained cloud motion prediction for short-term solar forecasting

NASA Astrophysics Data System (ADS)

Chen, Yanjun; Li, Wei; Zhang, Chongyang; Hu, Chuanping

2016-09-01

Cloud motion is the primary reason for short-term solar power output fluctuation. In this work, a new cloud motion estimation algorithm using a global velocity constraint is proposed. Compared to the most used Particle Image Velocity (PIV) algorithm, which assumes the homogeneity of motion vectors, the proposed method can capture the accurate motion vector for each cloud block, including both the motional tendency and morphological changes. Specifically, global velocity derived from PIV is first calculated, and then fine-grained cloud motion estimation can be achieved by global velocity based cloud block researching and multi-scale cloud block matching. Experimental results show that the proposed global velocity constrained cloud motion prediction achieves comparable performance to the existing PIV and filtered PIV algorithms, especially in a short prediction horizon.

Common themes in changing vector-borne disease scenarios.

PubMed

Molyneux, David H

2003-01-01

The impact of climate change on disease patterns is controversial. However, global burden of disease studies suggest that infectious diseases will contribute a proportionately smaller burden of disease over the next 2 decades as non-communicable diseases emerge as public health problems. However, infectious diseases contribute proportionately more in the poorest quintile of the population. Notwithstanding the different views of the impact of global warming on vector-borne infections this paper reviews the conditions which drive the changing epidemiology of these infections and suggests that such change is linked by common themes including interactions of generalist vectors and reservoir hosts at interfaces with humans, reduced biodiversity associated with anthropogenic environmental changes, increases in Plasmodium falciparum: P. vivax ratios and well-described land use changes such as hydrological, urbanization, agricultural, mining and forest-associated impacts (extractive activities, road building, deforestation and migration) which are seen on a global scale.

Developing the Second Generation CMORPH: A Prototype

NASA Astrophysics Data System (ADS)

Xie, Pingping; Joyce, Robert

2014-05-01

A prototype system of the second generation CMORPH is being developed at NOAA Climate Prediction Center (CPC) to produce global analyses of 30-min precipitation on a 0.05deg lat/lon grid over the entire globe from pole to pole through integration of information from satellite observations as well as numerical model simulations. The second generation CMORPH is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). Inputs to the system include rainfall and snowfall rate retrievals from passive microwave (PMW) measurements aboard all available low earth orbit (LEO) satellites, estimates derived from infrared (IR) observations of geostationary (GEO) as well as LEO platforms, and precipitation simulations from numerical global models. First, precipitation estimation / retrievals from various sources are mapped onto a global grid of 0.05deg lat/lon and calibrated against a common reference field to ensure consistency in their precipitation rate PDF structures. The motion vectors for the precipitating cloud systems are then defined using information from both satellite IR observations and precipitation fields generated by the NCEP Climate Forecast System Reanalysis (CFSR). To this end, motion vectors are first computed from CFSR hourly precipitation fields through cross-correlation analysis of consecutive hourly precipitation fields on the global T382 (~35 km) grid. In a similar manner, separate processing is also performed on satellite IR-based precipitation estimates to derive motion vectors from observations. A blended analysis of precipitating cloud motion vectors is then constructed through the combination of CFSR and satellite-derived vectors with an objective analysis technique. Fine resolution mapped PMW precipitation retrievals are then separately propagated along the motion vectors from their respective observation times to the target analysis time from both forward and backward directions. The CMORPH high resolution precipitation analyses are finally constructed through the combination of propagated PMW retrievals with the IR based estimates for the target analysis time. This Kalman Filter based CMORPH processing is performed for rainfall and snowfall fields separately with the same motion vectors. Experiments have been conducted for two periods of two months each, July - August 2009, and January - February 2010, to explore the development of an optimal algorithm that generates global precipitation for summer and winter situations. Preliminary results demonstrated technical feasibility to construct global rainfall and snowfall analyses through the integration of information from multiple sources. More work is underway to refine various technical components of the system for operational applications of the system. Detailed results will be reported at the EGU meeting.

An image understanding system using attributed symbolic representation and inexact graph-matching

NASA Astrophysics Data System (ADS)

Eshera, M. A.; Fu, K.-S.

1986-09-01

A powerful image understanding system using a semantic-syntactic representation scheme consisting of attributed relational graphs (ARGs) is proposed for the analysis of the global information content of images. A multilayer graph transducer scheme performs the extraction of ARG representations from images, with ARG nodes representing the global image features, and the relations between features represented by the attributed branches between corresponding nodes. An efficient dynamic programming technique is employed to derive the distance between two ARGs and the inexact matching of their respective components. Noise, distortion and ambiguity in real-world images are handled through modeling in the transducer mapping rules and through the appropriate cost of error-transformation for the inexact matching of the representation. The system is demonstrated for the case of locating objects in a scene composed of complex overlapped objects, and the case of target detection in noisy and distorted synthetic aperture radar image.

Spectroscopy of SU(4) composite Higgs theory with two distinct fermion representations

NASA Astrophysics Data System (ADS)

Ayyar, Venkitesh; DeGrand, Thomas; Golterman, Maarten; Hackett, Daniel C.; Jay, William I.; Neil, Ethan T.; Shamir, Yigal; Svetitsky, Benjamin

2018-04-01

We have simulated the SU(4) lattice gauge theory coupled to dynamical fermions in the fundamental and two-index antisymmetric (sextet) representations simultaneously. Such theories arise naturally in the context of composite Higgs models that include a partially composite top quark. We describe the low-lying meson spectrum of the theory and fit the pseudoscalar masses and decay constants to chiral perturbation theory. We infer as well the mass and decay constant of the Goldstone boson corresponding to the nonanomalous U(1) symmetry of the model. Our results are broadly consistent with large-Nc scaling and vector-meson dominance.

Dynamic belief state representations.

PubMed

Lee, Daniel D; Ortega, Pedro A; Stocker, Alan A

2014-04-01

Perceptual and control systems are tasked with the challenge of accurately and efficiently estimating the dynamic states of objects in the environment. To properly account for uncertainty, it is necessary to maintain a dynamical belief state representation rather than a single state vector. In this review, canonical algorithms for computing and updating belief states in robotic applications are delineated, and connections to biological systems are highlighted. A navigation example is used to illustrate the importance of properly accounting for correlations between belief state components, and to motivate the need for further investigations in psychophysics and neurobiology. Copyright © 2014 Elsevier Ltd. All rights reserved.

Combining Relevance Vector Machines and exponential regression for bearing residual life estimation

NASA Astrophysics Data System (ADS)

Di Maio, Francesco; Tsui, Kwok Leung; Zio, Enrico

2012-08-01

In this paper we present a new procedure for estimating the bearing Residual Useful Life (RUL) by combining data-driven and model-based techniques. Respectively, we resort to (i) Relevance Vector Machines (RVMs) for selecting a low number of significant basis functions, called Relevant Vectors (RVs), and (ii) exponential regression to compute and continuously update residual life estimations. The combination of these techniques is developed with reference to partially degraded thrust ball bearings and tested on real world vibration-based degradation data. On the case study considered, the proposed procedure outperforms other model-based methods, with the added value of an adequate representation of the uncertainty associated to the estimates of the quantification of the credibility of the results by the Prognostic Horizon (PH) metric.

Student Solution Manual for Mathematical Methods for Physics and Engineering Third Edition

NASA Astrophysics Data System (ADS)

Riley, K. F.; Hobson, M. P.

2006-03-01

Preface; 1. Preliminary algebra; 2. Preliminary calculus; 3. Complex numbers and hyperbolic functions; 4. Series and limits; 5. Partial differentiation; 6. Multiple integrals; 7. Vector algebra; 8. Matrices and vector spaces; 9. Normal modes; 10. Vector calculus; 11. Line, surface and volume integrals; 12. Fourier series; 13. Integral transforms; 14. First-order ordinary differential equations; 15. Higher-order ordinary differential equations; 16. Series solutions of ordinary differential equations; 17. Eigenfunction methods for differential equations; 18. Special functions; 19. Quantum operators; 20. Partial differential equations: general and particular; 21. Partial differential equations: separation of variables; 22. Calculus of variations; 23. Integral equations; 24. Complex variables; 25. Application of complex variables; 26. Tensors; 27. Numerical methods; 28. Group theory; 29. Representation theory; 30. Probability; 31. Statistics.

Social representations of climate change in Swedish lay focus groups: local or distant, gradual or catastrophic?

PubMed

Wibeck, Victoria

2014-02-01

This paper explores social representations of climate change, investigating how climate change is discussed by Swedish laypeople interacting in focus group interviews. The analysis focuses on prototypical examples and metaphors, which were key devices for objectifying climate change representations. The paper analyzes how the interaction of focus group participants with other speakers, ideas, arguments, and broader social representations shaped their representations of climate change. Climate change was understood as a global but distant issue with severe consequences. There was a dynamic tension between representations of climate change as a gradual vs. unpredictable process. Implications for climate change communication are discussed.

Magsat vector magnetometer calibration using Magsat geomagnetic field measurements

NASA Technical Reports Server (NTRS)

Lancaster, E. R.; Jennings, T.; Morrissey, M.; Langel, R. A.

1980-01-01

From the time of its launch on Oct. 30, 1979 into a nearly polar, Sun synchronous orbit, until it reentered the Earth's atmosphere on June 11, 1980, Magsat measured and transmitted more than three complete sets of global magnetic field data. The data obtained from the mission will be used primarily to compute a currently accurate model of the Earth's main magnetic field, to update and refine world and regional magnetic charts, and to develop a global scalar and vector crustal magnetic anomaly map. The in-flight calibration procecure used for 39 vector magnetometer system parameters is described as well as results obtained from some data sets and the numerical studies designed to evaluate the results.

A study of different modeling choices for simulating platelets within the immersed boundary method

PubMed Central

Shankar, Varun; Wright, Grady B.; Fogelson, Aaron L.; Kirby, Robert M.

2012-01-01

The Immersed Boundary (IB) method is a widely-used numerical methodology for the simulation of fluid–structure interaction problems. The IB method utilizes an Eulerian discretization for the fluid equations of motion while maintaining a Lagrangian representation of structural objects. Operators are defined for transmitting information (forces and velocities) between these two representations. Most IB simulations represent their structures with piecewise linear approximations and utilize Hookean spring models to approximate structural forces. Our specific motivation is the modeling of platelets in hemodynamic flows. In this paper, we study two alternative representations – radial basis functions (RBFs) and Fourier-based (trigonometric polynomials and spherical harmonics) representations – for the modeling of platelets in two and three dimensions within the IB framework, and compare our results with the traditional piecewise linear approximation methodology. For different representative shapes, we examine the geometric modeling errors (position and normal vectors), force computation errors, and computational cost and provide an engineering trade-off strategy for when and why one might select to employ these different representations. PMID:23585704

Development of a Multiple Input Integrated Pole-to-Pole Global CMORPH

NASA Astrophysics Data System (ADS)

Joyce, R.; Xie, P.

2013-12-01

A test system is being developed at NOAA Climate Prediction Center (CPC) to produce a passive microwave (PMW), IR-based, and model integrated high-resolution precipitation estimation on a 0.05olat/lon grid covering the entire globe from pole to pole. Experiments have been conducted for a summer Test Bed period using data for July and August of 2009. The pole-to-pole global CMORPH system is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). First, retrievals of instantaneous precipitation rates from PMW observations aboard nine low earth orbit (LEO) satellites are decoded and pole-to-pole mapped onto a 0.05olat/lon grid over the globe. Also precipitation estimates from LEO AVHRR retrievals are derived using a PDF matching of LEO IR with calibrated microwave combined (MWCOMB) precipitation retrievals. The motion vectors for the precipitating cloud systems are defined using information from both satellite IR observations and precipitation fields generated by the NCEP Climate Forecast System Reanalysis (CFSR). To this end, motion vectors are first computed for the CFSR hourly precipitation fields through cross-correlation analysis of consecutive hourly precipitation fields on the global T382 (~35 km) grid. In a similar manner, separate processing is also performed on satellite IR-based precipitation estimates to derive motion vectors from observations. A blended analysis of precipitating cloud motion vectors is then constructed through the combination of CFSR and satellite-derived vectors utilizing a two-dimensional optimal interpolation (2D-OI) method, in which CFSR-derived motion vectors are used as the first guess and subsequently satellite derived vectors modify the first guess. Weights used to generate the combinations are defined under the OI framework as a function of error statistics for the CFSR and satellite IR based motion vectors. The screened and calibrated PMW and AVHRR derived precipitation estimates are then separately spatially propagated forward and backward in time, using precipitating cloud motion vectors, from their observation time to the next PMW observation. The PMW estimates propagated in both the forward and backward directions are then combined with propagated IR-based precipitation estimates under the Kalman Filter framework, with weights defined based on previously determined error statistics dependent on latitude, season, surface type, and temporal distance from observation time. Performance of the pole-to-pole global CMORPH and its key components, including combined PMW (MWCOMB), IR-based, and model precipitation, as well as model-derived, IR-based, and blended precipitation motion vectors, will be examined against NSSL Q2 radar observed precipitation estimates over CONUS, Finland FMI radar precipitation, and a daily gauge-based analysis including daily Canadian surface reports over global land. Also an initial investigation will be performed over a January - February 2010 winter Test Bed period. Detailed results will be reported at the Fall 2013 AGU Meeting.

repRNA: a web server for generating various feature vectors of RNA sequences.

PubMed

Liu, Bin; Liu, Fule; Fang, Longyun; Wang, Xiaolong; Chou, Kuo-Chen

2016-02-01

With the rapid growth of RNA sequences generated in the postgenomic age, it is highly desired to develop a flexible method that can generate various kinds of vectors to represent these sequences by focusing on their different features. This is because nearly all the existing machine-learning methods, such as SVM (support vector machine) and KNN (k-nearest neighbor), can only handle vectors but not sequences. To meet the increasing demands and speed up the genome analyses, we have developed a new web server, called "representations of RNA sequences" (repRNA). Compared with the existing methods, repRNA is much more comprehensive, flexible and powerful, as reflected by the following facts: (1) it can generate 11 different modes of feature vectors for users to choose according to their investigation purposes; (2) it allows users to select the features from 22 built-in physicochemical properties and even those defined by users' own; (3) the resultant feature vectors and the secondary structures of the corresponding RNA sequences can be visualized. The repRNA web server is freely accessible to the public at http://bioinformatics.hitsz.edu.cn/repRNA/ .

Vector fields in a tight laser focus: comparison of models.

PubMed

Peatross, Justin; Berrondo, Manuel; Smith, Dallas; Ware, Michael

2017-06-26

We assess several widely used vector models of a Gaussian laser beam in the context of more accurate vector diffraction integration. For the analysis, we present a streamlined derivation of the vector fields of a uniformly polarized beam reflected from an ideal parabolic mirror, both inside and outside of the resulting focus. This exact solution to Maxwell's equations, first developed in 1920 by V. S. Ignatovsky, is highly relevant to high-intensity laser experiments since the boundary conditions at a focusing optic dictate the form of the focus in a manner analogous to a physical experiment. In contrast, many models simply assume a field profile near the focus and develop the surrounding vector fields consistent with Maxwell's equations. In comparing the Ignatovsky result with popular closed-form analytic vector models of a Gaussian beam, we find that the relatively simple model developed by Erikson and Singh in 1994 provides good agreement in the paraxial limit. Models involving a Lax expansion introduce a divergences outside of the focus while providing little if any improvement in the focal region. Extremely tight focusing produces a somewhat complicated structure in the focus, and requires the Ignatovsky model for accurate representation.

Morphology of the southern African geomagnetic field derived from observatory and repeat station survey observations: 2005-2014

NASA Astrophysics Data System (ADS)

Kotzé, P. B.; Korte, M.

2016-02-01

Geomagnetic field data from four observatories and annual field surveys between 2005 and 2015 provide a detailed description of Earth's magnetic field changes over South Africa, Namibia and Botswana on time scales of less than 1 year. The southern African area is characterized by rapid changes in the secular variation pattern and lies in close proximity to the South Atlantic Anomaly (SAA) where the geomagnetic field intensity is almost 30 % weaker than in other regions at similar latitudes around the globe. Several geomagnetic secular acceleration (SA) pulses (geomagnetic jerks) around 2007, 2010 and 2012 could be identified over the last decade in southern Africa. We present a new regional field model for declination and horizontal and vertical intensity over southern Africa (Southern African REGional (SAREG)) which is based on field survey and observatory data and covering the time interval from 2005 to 2014, i.e. including the period between 2010 and 2013 when no low Earth-orbiting vector field satellite data are available. A comparative evaluation between SAREG and global field models like CHAOS-5, the CHAMP, Orsted and SAC-C model of the Earth's magnetic field and International Geomagnetic Reference Field (IGRF-12) reveals that a simple regional field model based on a relatively dense ground network is able to provide a realistic representation of the geomagnetic field in this area. We particularly note that a global field model like CHAOS-5 does not always indicate similar short-period patterns in the field components as revealed by observatory data, while representing the general secular variation reasonably well during the time interval without near-Earth satellite vector field data. This investigation further shows the inhomogeneous occurrence and distribution of secular variation impulses in the different geomagnetic field components and at different locations in southern African.

Formal Provenance Representation of the Data and Information Supporting the National Climate Assessment

NASA Technical Reports Server (NTRS)

Tilmes, Curt

2014-01-01

The Global Change Information System (GCIS) provides a framework for the formal representation of structured metadata about data and information about global change. The pilot deployment of the system supports the National Climate Assessment (NCA), a major report of the U.S. Global Change Research Program (USGCRP). A consumer of that report can use the system to browse and explore that supporting information. Additionally, capturing that information into a structured data model and presenting it in standard formats through well defined open inter- faces, including query interfaces suitable for data mining and linking with other databases, the information becomes valuable for other analytic uses as well.

Hybrid generative-discriminative approach to age-invariant face recognition

NASA Astrophysics Data System (ADS)

Sajid, Muhammad; Shafique, Tamoor

2018-03-01

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

Assessing the impact of representational and contextual problem features on student use of right-hand rules

NASA Astrophysics Data System (ADS)

Kustusch, Mary Bridget

2016-06-01

Students in introductory physics struggle with vector algebra and these challenges are often associated with contextual and representational features of the problems. Performance on problems about cross product direction is particularly poor and some research suggests that this may be primarily due to misapplied right-hand rules. However, few studies have had the resolution to explore student use of right-hand rules in detail. This study reviews literature in several disciplines, including spatial cognition, to identify ten contextual and representational problem features that are most likely to influence performance on problems requiring a right-hand rule. Two quantitative measures of performance (correctness and response time) and two qualitative measures (methods used and type of errors made) were used to explore the impact of these problem features on student performance. Quantitative results are consistent with expectations from the literature, but reveal that some features (such as the type of reasoning required and the physical awkwardness of using a right-hand rule) have a greater impact than others (such as whether the vectors are placed together or separate). Additional insight is gained by the qualitative analysis, including identifying sources of difficulty not previously discussed in the literature and revealing that the use of supplemental methods, such as physically rotating the paper, can mitigate errors associated with certain features.

Learning Compact Binary Face Descriptor for Face Recognition.

PubMed

Lu, Jiwen; Liong, Venice Erin; Zhou, Xiuzhuang; Zhou, Jie

2015-10-01

Binary feature descriptors such as local binary patterns (LBP) and its variations have been widely used in many face recognition systems due to their excellent robustness and strong discriminative power. However, most existing binary face descriptors are hand-crafted, which require strong prior knowledge to engineer them by hand. In this paper, we propose a compact binary face descriptor (CBFD) feature learning method for face representation and recognition. Given each face image, we first extract pixel difference vectors (PDVs) in local patches by computing the difference between each pixel and its neighboring pixels. Then, we learn a feature mapping to project these pixel difference vectors into low-dimensional binary vectors in an unsupervised manner, where 1) the variance of all binary codes in the training set is maximized, 2) the loss between the original real-valued codes and the learned binary codes is minimized, and 3) binary codes evenly distribute at each learned bin, so that the redundancy information in PDVs is removed and compact binary codes are obtained. Lastly, we cluster and pool these binary codes into a histogram feature as the final representation for each face image. Moreover, we propose a coupled CBFD (C-CBFD) method by reducing the modality gap of heterogeneous faces at the feature level to make our method applicable to heterogeneous face recognition. Extensive experimental results on five widely used face datasets show that our methods outperform state-of-the-art face descriptors.

Exploratory Model Analysis of the Space Based Infrared System (SBIRS) Low Global Scheduler Problem

DTIC Science & Technology

1999-12-01

solution. The non- linear least squares model is defined as Y = f{e,t) where: 0 =M-element parameter vector Y =N-element vector of all data t...NAVAL POSTGRADUATE SCHOOL Monterey, California THESIS EXPLORATORY MODEL ANALYSIS OF THE SPACE BASED INFRARED SYSTEM (SBIRS) LOW GLOBAL SCHEDULER...December 1999 3. REPORT TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE EXPLORATORY MODEL ANALYSIS OF THE SPACE BASED INFRARED SYSTEM

Improving the representation of photosynthesis in Earth system models

NASA Astrophysics Data System (ADS)

Rogers, A.; Medlyn, B. E.; Dukes, J.; Bonan, G. B.; von Caemmerer, S.; Dietze, M.; Kattge, J.; Leakey, A. D.; Mercado, L. M.; Niinemets, U.; Prentice, I. C. C.; Serbin, S.; Sitch, S.; Way, D. A.; Zaehle, S.

2015-12-01

Continued use of fossil fuel drives an accelerating increase in atmospheric CO2 concentration ([CO2]) and is the principal cause of global climate change. Many of the observed and projected impacts of rising [CO2] portend increasing environmental and economic risk, yet the uncertainty surrounding the projection of our future climate by Earth System Models (ESMs) is unacceptably high. Improving confidence in our estimation of future [CO2] is essential if we seek to project global change with greater confidence. There are critical uncertainties over the long term response of terrestrial CO2 uptake to global change, more specifically, over the size of the terrestrial carbon sink and over its sensitivity to rising [CO2] and temperature. Reducing the uncertainty associated with model representation of the largest CO2 flux on the planet is therefore an essential part of improving confidence in projections of global change. Here we have examined model representation of photosynthesis in seven process models including several global models that underlie the representation of photosynthesis in the land surface model component of ESMs that were part of the recent Fifth Assessment Report from the IPCC. Our approach was to focus on how physiological responses are represented by these models, and to better understand how structural and parametric differences drive variation in model responses to light, CO2, nutrients, temperature, vapor pressure deficit and soil moisture. We challenged each model to produce leaf and canopy responses to these factors to help us identify areas in which current process knowledge and emerging data sets could be used to improve model skill, and also identify knowledge gaps in current understanding that directly impact model outputs. We hope this work will provide a roadmap for the scientific activity that is necessary to advance process representation, parameterization and scaling of photosynthesis in the next generation of Earth System Models.

Chromosome preference of disease genes and vectorization for the prediction of non-coding disease genes.

PubMed

Peng, Hui; Lan, Chaowang; Liu, Yuansheng; Liu, Tao; Blumenstein, Michael; Li, Jinyan

2017-10-03

Disease-related protein-coding genes have been widely studied, but disease-related non-coding genes remain largely unknown. This work introduces a new vector to represent diseases, and applies the newly vectorized data for a positive-unlabeled learning algorithm to predict and rank disease-related long non-coding RNA (lncRNA) genes. This novel vector representation for diseases consists of two sub-vectors, one is composed of 45 elements, characterizing the information entropies of the disease genes distribution over 45 chromosome substructures. This idea is supported by our observation that some substructures (e.g., the chromosome 6 p-arm) are highly preferred by disease-related protein coding genes, while some (e.g., the 21 p-arm) are not favored at all. The second sub-vector is 30-dimensional, characterizing the distribution of disease gene enriched KEGG pathways in comparison with our manually created pathway groups. The second sub-vector complements with the first one to differentiate between various diseases. Our prediction method outperforms the state-of-the-art methods on benchmark datasets for prioritizing disease related lncRNA genes. The method also works well when only the sequence information of an lncRNA gene is known, or even when a given disease has no currently recognized long non-coding genes.

Chromosome preference of disease genes and vectorization for the prediction of non-coding disease genes

PubMed Central

Peng, Hui; Lan, Chaowang; Liu, Yuansheng; Liu, Tao; Blumenstein, Michael; Li, Jinyan

2017-01-01

Disease-related protein-coding genes have been widely studied, but disease-related non-coding genes remain largely unknown. This work introduces a new vector to represent diseases, and applies the newly vectorized data for a positive-unlabeled learning algorithm to predict and rank disease-related long non-coding RNA (lncRNA) genes. This novel vector representation for diseases consists of two sub-vectors, one is composed of 45 elements, characterizing the information entropies of the disease genes distribution over 45 chromosome substructures. This idea is supported by our observation that some substructures (e.g., the chromosome 6 p-arm) are highly preferred by disease-related protein coding genes, while some (e.g., the 21 p-arm) are not favored at all. The second sub-vector is 30-dimensional, characterizing the distribution of disease gene enriched KEGG pathways in comparison with our manually created pathway groups. The second sub-vector complements with the first one to differentiate between various diseases. Our prediction method outperforms the state-of-the-art methods on benchmark datasets for prioritizing disease related lncRNA genes. The method also works well when only the sequence information of an lncRNA gene is known, or even when a given disease has no currently recognized long non-coding genes. PMID:29108274

Tensor Fukunaga-Koontz transform for small target detection in infrared images

NASA Astrophysics Data System (ADS)

Liu, Ruiming; Wang, Jingzhuo; Yang, Huizhen; Gong, Chenglong; Zhou, Yuanshen; Liu, Lipeng; Zhang, Zhen; Shen, Shuli

2016-09-01

Infrared small targets detection plays a crucial role in warning and tracking systems. Some novel methods based on pattern recognition technology catch much attention from researchers. However, those classic methods must reshape images into vectors with the high dimensionality. Moreover, vectorizing breaks the natural structure and correlations in the image data. Image representation based on tensor treats images as matrices and can hold the natural structure and correlation information. So tensor algorithms have better classification performance than vector algorithms. Fukunaga-Koontz transform is one of classification algorithms and it is a vector version method with the disadvantage of all vector algorithms. In this paper, we first extended the Fukunaga-Koontz transform into its tensor version, tensor Fukunaga-Koontz transform. Then we designed a method based on tensor Fukunaga-Koontz transform for detecting targets and used it to detect small targets in infrared images. The experimental results, comparison through signal-to-clutter, signal-to-clutter gain and background suppression factor, have validated the advantage of the target detection based on the tensor Fukunaga-Koontz transform over that based on the Fukunaga-Koontz transform.

Globalization, land use and the invasion of West Nile virus

PubMed Central

Kilpatrick, A. Marm

2012-01-01

Many invasive species that have been spread through the globalization of trade and travel are infectious pathogens. A paradigmatic case is the introduction of West Nile virus (WNV) into North America in 1999. A decade of research on the ecology and evolution of WNV includes three findings that provide insight into the outcome of future viral introductions. First, WNV transmission in North America is highest in urbanized and agricultural habitats, in part because the hosts and vectors of WNV are abundant in human-modified areas. Second, after its introduction, the virus quickly adapted to infect local mosquito vectors more efficiently than the originally introduced strain. Third, highly focused feeding patterns of the mosquito vectors of WNV result in unexpected host species being important for transmission. These findings provide a framework for predicting and preventing the emergence of foreign vector-borne pathogens. PMID:22021850

Artemisinin-resistant Plasmodium falciparum clinical isolates can infect diverse mosquito vectors of Southeast Asia and Africa

PubMed Central

St. Laurent, Brandyce; Miller, Becky; Burton, Timothy A.; Amaratunga, Chanaki; Men, Sary; Sovannaroth, Siv; Fay, Michael P.; Miotto, Olivo; Gwadz, Robert W.; Anderson, Jennifer M.; Fairhurst, Rick M.

2015-01-01

Artemisinin-resistant Plasmodium falciparum parasites are rapidly spreading in Southeast Asia, yet nothing is known about their transmission. This knowledge gap and the possibility that these parasites will spread to Africa endanger global efforts to eliminate malaria. Here we produce gametocytes from parasite clinical isolates that displayed artemisinin resistance in patients and in vitro, and use them to infect native and non-native mosquito vectors. We show that contemporary artemisinin-resistant isolates from Cambodia develop and produce sporozoites in two Southeast Asian vectors, Anopheles dirus and Anopheles minimus, and the major African vector, Anopheles coluzzii (formerly Anopheles gambiae M). The ability of artemisinin-resistant parasites to infect such highly diverse Anopheles species, combined with their higher gametocyte prevalence in patients, may explain the rapid expansion of these parasites in Cambodia and neighbouring countries, and further compromise efforts to prevent their global spread. PMID:26485448

Artemisinin-resistant Plasmodium falciparum clinical isolates can infect diverse mosquito vectors of Southeast Asia and Africa.

PubMed

St Laurent, Brandyce; Miller, Becky; Burton, Timothy A; Amaratunga, Chanaki; Men, Sary; Sovannaroth, Siv; Fay, Michael P; Miotto, Olivo; Gwadz, Robert W; Anderson, Jennifer M; Fairhurst, Rick M

2015-10-20

Artemisinin-resistant Plasmodium falciparum parasites are rapidly spreading in Southeast Asia, yet nothing is known about their transmission. This knowledge gap and the possibility that these parasites will spread to Africa endanger global efforts to eliminate malaria. Here we produce gametocytes from parasite clinical isolates that displayed artemisinin resistance in patients and in vitro, and use them to infect native and non-native mosquito vectors. We show that contemporary artemisinin-resistant isolates from Cambodia develop and produce sporozoites in two Southeast Asian vectors, Anopheles dirus and Anopheles minimus, and the major African vector, Anopheles coluzzii (formerly Anopheles gambiae M). The ability of artemisinin-resistant parasites to infect such highly diverse Anopheles species, combined with their higher gametocyte prevalence in patients, may explain the rapid expansion of these parasites in Cambodia and neighbouring countries, and further compromise efforts to prevent their global spread.

Global MHD simulation of magnetosphere using HPF

NASA Astrophysics Data System (ADS)

Ogino, T.

We have translated a 3-dimensional magnetohydrodynamic (MHD) simulation code of the Earth's magnetosphere from VPP Fortran to HPF/JA on the Fujitsu VPP5000/56 vector-parallel supercomputer and the MHD code was fully vectorized and fully parallelized in VPP Fortran. The entire performance and capability of the HPF MHD code could be shown to be almost comparable to that of VPP Fortran. A 3-dimensional global MHD simulation of the earth's magnetosphere was performed at a speed of over 400 Gflops with an efficiency of 76.5% using 56 PEs of Fujitsu VPP5000/56 in vector and parallel computation that permitted comparison with catalog values. We have concluded that fluid and MHD codes that are fully vectorized and fully parallelized in VPP Fortran can be translated with relative ease to HPF/JA, and a code in HPF/JA may be expected to perform comparably to the same code written in VPP Fortran.

Finding a Hadamard matrix by simulated annealing of spin vectors

NASA Astrophysics Data System (ADS)

Bayu Suksmono, Andriyan

2017-05-01

Reformulation of a combinatorial problem into optimization of a statistical-mechanics system enables finding a better solution using heuristics derived from a physical process, such as by the simulated annealing (SA). In this paper, we present a Hadamard matrix (H-matrix) searching method based on the SA on an Ising model. By equivalence, an H-matrix can be converted into a seminormalized Hadamard (SH) matrix, whose first column is unit vector and the rest ones are vectors with equal number of -1 and +1 called SH-vectors. We define SH spin vectors as representation of the SH vectors, which play a similar role as the spins on Ising model. The topology of the lattice is generalized into a graph, whose edges represent orthogonality relationship among the SH spin vectors. Starting from a randomly generated quasi H-matrix Q, which is a matrix similar to the SH-matrix without imposing orthogonality, we perform the SA. The transitions of Q are conducted by random exchange of {+, -} spin-pair within the SH-spin vectors that follow the Metropolis update rule. Upon transition toward zeroth energy, the Q-matrix is evolved following a Markov chain toward an orthogonal matrix, at which the H-matrix is said to be found. We demonstrate the capability of the proposed method to find some low-order H-matrices, including the ones that cannot trivially be constructed by the Sylvester method.

Tiled vector data model for the geographical features of symbolized maps.

PubMed

Li, Lin; Hu, Wei; Zhu, Haihong; Li, You; Zhang, Hang

2017-01-01

Electronic maps (E-maps) provide people with convenience in real-world space. Although web map services can display maps on screens, a more important function is their ability to access geographical features. An E-map that is based on raster tiles is inferior to vector tiles in terms of interactive ability because vector maps provide a convenient and effective method to access and manipulate web map features. However, the critical issue regarding rendering tiled vector maps is that geographical features that are rendered in the form of map symbols via vector tiles may cause visual discontinuities, such as graphic conflicts and losses of data around the borders of tiles, which likely represent the main obstacles to exploring vector map tiles on the web. This paper proposes a tiled vector data model for geographical features in symbolized maps that considers the relationships among geographical features, symbol representations and map renderings. This model presents a method to tailor geographical features in terms of map symbols and 'addition' (join) operations on the following two levels: geographical features and map features. Thus, these maps can resolve the visual discontinuity problem based on the proposed model without weakening the interactivity of vector maps. The proposed model is validated by two map data sets, and the results demonstrate that the rendered (symbolized) web maps present smooth visual continuity.

Integrating vector control across diseases.

PubMed

Golding, Nick; Wilson, Anne L; Moyes, Catherine L; Cano, Jorge; Pigott, David M; Velayudhan, Raman; Brooker, Simon J; Smith, David L; Hay, Simon I; Lindsay, Steve W

2015-10-01

Vector-borne diseases cause a significant proportion of the overall burden of disease across the globe, accounting for over 10 % of the burden of infectious diseases. Despite the availability of effective interventions for many of these diseases, a lack of resources prevents their effective control. Many existing vector control interventions are known to be effective against multiple diseases, so combining vector control programmes to simultaneously tackle several diseases could offer more cost-effective and therefore sustainable disease reductions. The highly successful cross-disease integration of vaccine and mass drug administration programmes in low-resource settings acts a precedent for cross-disease vector control. Whilst deliberate implementation of vector control programmes across multiple diseases has yet to be trialled on a large scale, a number of examples of 'accidental' cross-disease vector control suggest the potential of such an approach. Combining contemporary high-resolution global maps of the major vector-borne pathogens enables us to quantify overlap in their distributions and to estimate the populations jointly at risk of multiple diseases. Such an analysis shows that over 80 % of the global population live in regions of the world at risk from one vector-borne disease, and more than half the world's population live in areas where at least two different vector-borne diseases pose a threat to health. Combining information on co-endemicity with an assessment of the overlap of vector control methods effective against these diseases allows us to highlight opportunities for such integration. Malaria, leishmaniasis, lymphatic filariasis, and dengue are prime candidates for combined vector control. All four of these diseases overlap considerably in their distributions and there is a growing body of evidence for the effectiveness of insecticide-treated nets, screens, and curtains for controlling all of their vectors. The real-world effectiveness of cross-disease vector control programmes can only be evaluated by large-scale trials, but there is clear evidence of the potential of such an approach to enable greater overall health benefit using the limited funds available.

Identification of Alzheimer's disease and mild cognitive impairment using multimodal sparse hierarchical extreme learning machine.

PubMed

Kim, Jongin; Lee, Boreom

2018-05-07

Different modalities such as structural MRI, FDG-PET, and CSF have complementary information, which is likely to be very useful for diagnosis of AD and MCI. Therefore, it is possible to develop a more effective and accurate AD/MCI automatic diagnosis method by integrating complementary information of different modalities. In this paper, we propose multi-modal sparse hierarchical extreme leaning machine (MSH-ELM). We used volume and mean intensity extracted from 93 regions of interest (ROIs) as features of MRI and FDG-PET, respectively, and used p-tau, t-tau, and Aβ42 as CSF features. In detail, high-level representation was individually extracted from each of MRI, FDG-PET, and CSF using a stacked sparse extreme learning machine auto-encoder (sELM-AE). Then, another stacked sELM-AE was devised to acquire a joint hierarchical feature representation by fusing the high-level representations obtained from each modality. Finally, we classified joint hierarchical feature representation using a kernel-based extreme learning machine (KELM). The results of MSH-ELM were compared with those of conventional ELM, single kernel support vector machine (SK-SVM), multiple kernel support vector machine (MK-SVM) and stacked auto-encoder (SAE). Performance was evaluated through 10-fold cross-validation. In the classification of AD vs. HC and MCI vs. HC problem, the proposed MSH-ELM method showed mean balanced accuracies of 96.10% and 86.46%, respectively, which is much better than those of competing methods. In summary, the proposed algorithm exhibits consistently better performance than SK-SVM, ELM, MK-SVM and SAE in the two binary classification problems (AD vs. HC and MCI vs. HC). © 2018 Wiley Periodicals, Inc.

Psoriasis image representation using patch-based dictionary learning for erythema severity scoring.

PubMed

George, Yasmeen; Aldeen, Mohammad; Garnavi, Rahil

2018-06-01

Psoriasis is a chronic skin disease which can be life-threatening. Accurate severity scoring helps dermatologists to decide on the treatment. In this paper, we present a semi-supervised computer-aided system for automatic erythema severity scoring in psoriasis images. Firstly, the unsupervised stage includes a novel image representation method. We construct a dictionary, which is then used in the sparse representation for local feature extraction. To acquire the final image representation vector, an aggregation method is exploited over the local features. Secondly, the supervised phase is where various multi-class machine learning (ML) classifiers are trained for erythema severity scoring. Finally, we compare the proposed system with two popular unsupervised feature extractor methods, namely: bag of visual words model (BoVWs) and AlexNet pretrained model. Root mean square error (RMSE) and F1 score are used as performance measures for the learned dictionaries and the trained ML models, respectively. A psoriasis image set consisting of 676 images, is used in this study. Experimental results demonstrate that the use of the proposed procedure can provide a setup where erythema scoring is accurate and consistent. Also, it is revealed that dictionaries with large number of atoms and small patch sizes yield the best representative erythema severity features. Further, random forest (RF) outperforms other classifiers with F1 score 0.71, followed by support vector machine (SVM) and boosting with 0.66 and 0.64 scores, respectively. Furthermore, the conducted comparative studies confirm the effectiveness of the proposed approach with improvement of 9% and 12% over BoVWs and AlexNet based features, respectively. Crown Copyright © 2018. Published by Elsevier Ltd. All rights reserved.

3D surface parameterization using manifold learning for medial shape representation

NASA Astrophysics Data System (ADS)

Ward, Aaron D.; Hamarneh, Ghassan

2007-03-01

The choice of 3D shape representation for anatomical structures determines the effectiveness with which segmentation, visualization, deformation, and shape statistics are performed. Medial axis-based shape representations have attracted considerable attention due to their inherent ability to encode information about the natural geometry of parts of the anatomy. In this paper, we propose a novel approach, based on nonlinear manifold learning, to the parameterization of medial sheets and object surfaces based on the results of skeletonization. For each single-sheet figure in an anatomical structure, we skeletonize the figure, and classify its surface points according to whether they lie on the upper or lower surface, based on their relationship to the skeleton points. We then perform nonlinear dimensionality reduction on the skeleton, upper, and lower surface points, to find the intrinsic 2D coordinate system of each. We then center a planar mesh over each of the low-dimensional representations of the points, and map the meshes back to 3D using the mappings obtained by manifold learning. Correspondence between mesh vertices, established in their intrinsic 2D coordinate spaces, is used in order to compute the thickness vectors emanating from the medial sheet. We show results of our algorithm on real brain and musculoskeletal structures extracted from MRI, as well as an artificial multi-sheet example. The main advantages to this method are its relative simplicity and noniterative nature, and its ability to correctly compute nonintersecting thickness vectors for a medial sheet regardless of both the amount of coincident bending and thickness in the object, and of the incidence of local concavities and convexities in the object's surface.

The Problem of Representation

ERIC Educational Resources Information Center

Tervo, Juuso

2012-01-01

In "Postphysical Vision: Art Education's Challenge in an Age of Globalized Aesthetics (AMondofesto)" (2008) and "Beyond Aesthetics: Returning Force and Truth to Art and Its Education" (2009), jan jagodzinski argued for politics that go "beyond" representation--a project that radically questions visual culture…

Extracting semantic representations from word co-occurrence statistics: stop-lists, stemming, and SVD.

PubMed

Bullinaria, John A; Levy, Joseph P

2012-09-01

In a previous article, we presented a systematic computational study of the extraction of semantic representations from the word-word co-occurrence statistics of large text corpora. The conclusion was that semantic vectors of pointwise mutual information values from very small co-occurrence windows, together with a cosine distance measure, consistently resulted in the best representations across a range of psychologically relevant semantic tasks. This article extends that study by investigating the use of three further factors--namely, the application of stop-lists, word stemming, and dimensionality reduction using singular value decomposition (SVD)--that have been used to provide improved performance elsewhere. It also introduces an additional semantic task and explores the advantages of using a much larger corpus. This leads to the discovery and analysis of improved SVD-based methods for generating semantic representations (that provide new state-of-the-art performance on a standard TOEFL task) and the identification and discussion of problems and misleading results that can arise without a full systematic study.

Project Physics Reader 1, Concepts of Motion.

ERIC Educational Resources Information Center

Harvard Univ., Cambridge, MA. Harvard Project Physics.

As a supplement to Project Physics Unit 1, 21 articles are presented in this reader. Concepts of motion are discussed under headings: motion, motion in words, representation of movement, introducing vectors, Galileo's discussion of projectile motion, Newton's laws of dynamics, the dynamics of a golf club, report on Tait's lecture on force, and bad…

Three Interpretations of the Matrix Equation Ax = b

ERIC Educational Resources Information Center

Larson, Christine; Zandieh, Michelle

2013-01-01

Many of the central ideas in an introductory undergraduate linear algebra course are closely tied to a set of interpretations of the matrix equation Ax = b (A is a matrix, x and b are vectors): linear combination interpretations, systems interpretations, and transformation interpretations. We consider graphic and symbolic representations for each,…

Spectroscopy and Direct Products: Simpler yet Deeper

ERIC Educational Resources Information Center

Kettle, Sidney F. A.

2010-01-01

When irreducible representations are given in diagrammatic form, it is possible to show direct products pictorially. By giving a similar description of the electric vector associated with a light wave, group-theoretical selection rules (the requirement of a totally symmetric direct product) can also be shown in pictorial form. The [upsilon](CO)…

Representation of microstructural features and magnetic anisotropy of electrical steels in an energy-based vector hysteresis model

NASA Astrophysics Data System (ADS)

Jacques, Kevin; Steentjes, Simon; Henrotte, François; Geuzaine, Christophe; Hameyer, Kay

2018-04-01

This paper demonstrates how the statistical distribution of pinning fields in a ferromagnetic material can be identified systematically from standard magnetic measurements, Epstein frame or Single Sheet Tester (SST). The correlation between the pinning field distribution and microstructural parameters of the material is then analyzed.

Introduction to Matrix Algebra, Student's Text, Unit 23.

ERIC Educational Resources Information Center

Allen, Frank B.; And Others

Unit 23 in the SMSG secondary school mathematics series is a student text covering the following topics in matrix algebra: matrix operations, the algebra of 2 X 2 matrices, matrices and linear systems, representation of column matrices as geometric vectors, and transformations of the plane. Listed in the appendix are four research exercises in…

Implementation of a digital optical matrix-vector multiplier using a holographic look-up table and residue arithmetic

NASA Technical Reports Server (NTRS)

Habiby, Sarry F.

1987-01-01

The design and implementation of a digital (numerical) optical matrix-vector multiplier are presented. The objective is to demonstrate the operation of an optical processor designed to minimize computation time in performing a practical computing application. This is done by using the large array of processing elements in a Hughes liquid crystal light valve, and relying on the residue arithmetic representation, a holographic optical memory, and position coded optical look-up tables. In the design, all operations are performed in effectively one light valve response time regardless of matrix size. The features of the design allowing fast computation include the residue arithmetic representation, the mapping approach to computation, and the holographic memory. In addition, other features of the work include a practical light valve configuration for efficient polarization control, a model for recording multiple exposures in silver halides with equal reconstruction efficiency, and using light from an optical fiber for a reference beam source in constructing the hologram. The design can be extended to implement larger matrix arrays without increasing computation time.

Matrix product representation of the stationary state of the open zero range process

NASA Astrophysics Data System (ADS)

Bertin, Eric; Vanicat, Matthieu

2018-06-01

Many one-dimensional lattice particle models with open boundaries, like the paradigmatic asymmetric simple exclusion process (ASEP), have their stationary states represented in the form of a matrix product, with matrices that do not explicitly depend on the lattice site. In contrast, the stationary state of the open 1D zero-range process (ZRP) takes an inhomogeneous factorized form, with site-dependent probability weights. We show that in spite of the absence of correlations, the stationary state of the open ZRP can also be represented in a matrix product form, where the matrices are site-independent, non-commuting and determined from algebraic relations resulting from the master equation. We recover the known distribution of the open ZRP in two different ways: first, using an explicit representation of the matrices and boundary vectors; second, from the sole knowledge of the algebraic relations satisfied by these matrices and vectors. Finally, an interpretation of the relation between the matrix product form and the inhomogeneous factorized form is proposed within the framework of hidden Markov chains.

In silico toxicity prediction by support vector machine and SMILES representation-based string kernel.

PubMed

Cao, D-S; Zhao, J-C; Yang, Y-N; Zhao, C-X; Yan, J; Liu, S; Hu, Q-N; Xu, Q-S; Liang, Y-Z

2012-01-01

There is a great need to assess the harmful effects or toxicities of chemicals to which man is exposed. In the present paper, the simplified molecular input line entry specification (SMILES) representation-based string kernel, together with the state-of-the-art support vector machine (SVM) algorithm, were used to classify the toxicity of chemicals from the US Environmental Protection Agency Distributed Structure-Searchable Toxicity (DSSTox) database network. In this method, the molecular structure can be directly encoded by a series of SMILES substrings that represent the presence of some chemical elements and different kinds of chemical bonds (double, triple and stereochemistry) in the molecules. Thus, SMILES string kernel can accurately and directly measure the similarities of molecules by a series of local information hidden in the molecules. Two model validation approaches, five-fold cross-validation and independent validation set, were used for assessing the predictive capability of our developed models. The results obtained indicate that SVM based on the SMILES string kernel can be regarded as a very promising and alternative modelling approach for potential toxicity prediction of chemicals.

Selection vector filter framework

NASA Astrophysics Data System (ADS)

Lukac, Rastislav; Plataniotis, Konstantinos N.; Smolka, Bogdan; Venetsanopoulos, Anastasios N.

2003-10-01

We provide a unified framework of nonlinear vector techniques outputting the lowest ranked vector. The proposed framework constitutes a generalized filter class for multichannel signal processing. A new class of nonlinear selection filters are based on the robust order-statistic theory and the minimization of the weighted distance function to other input samples. The proposed method can be designed to perform a variety of filtering operations including previously developed filtering techniques such as vector median, basic vector directional filter, directional distance filter, weighted vector median filters and weighted directional filters. A wide range of filtering operations is guaranteed by the filter structure with two independent weight vectors for angular and distance domains of the vector space. In order to adapt the filter parameters to varying signal and noise statistics, we provide also the generalized optimization algorithms taking the advantage of the weighted median filters and the relationship between standard median filter and vector median filter. Thus, we can deal with both statistical and deterministic aspects of the filter design process. It will be shown that the proposed method holds the required properties such as the capability of modelling the underlying system in the application at hand, the robustness with respect to errors in the model of underlying system, the availability of the training procedure and finally, the simplicity of filter representation, analysis, design and implementation. Simulation studies also indicate that the new filters are computationally attractive and have excellent performance in environments corrupted by bit errors and impulsive noise.

How the public engages with global warming: A social representations approach.

PubMed

Smith, Nicholas; Joffe, Helene

2013-01-01

The present study utilises social representations theory to explore common sense conceptualisations of global warming risk using an in-depth, qualitative methodology. Fifty-six members of a British, London-based 2008 public were initially asked to draw or write four spontaneous "first thoughts or feelings" about global warming. These were then explored via an open-ended, exploratory interview. The analysis revealed that first thoughts, either drawn or written, often mirrored the images used by the British press to depict global warming visually. Thus in terms of media framings, it was their visual rather than their textual content that was spontaneously available for their audiences. Furthermore, an in-depth exploration of interview data revealed that global warming was structured around three themata: self/other, natural/unnatural and certainty/uncertainty, reflecting the complex and often contradictory nature of common sense thinking in relation to risk issues.

Viability of strongly coupled scenarios with a light Higgs-like boson.

PubMed

Pich, Antonio; Rosell, Ignasi; Sanz-Cillero, Juan José

2013-05-03

We present a one-loop calculation of the oblique S and T parameters within strongly coupled models of electroweak symmetry breaking with a light Higgs-like boson. We use a general effective Lagrangian, implementing the chiral symmetry breaking SU(2)(L) [Symbol: see text]SU(2)(R) → SU(2)(L+R) with Goldstone bosons, gauge bosons, the Higgs-like scalar, and one multiplet of vector and axial-vector massive resonance states. Using a dispersive representation and imposing a proper ultraviolet behavior, we obtain S and T at the next-to-leading order in terms of a few resonance parameters. The experimentally allowed range forces the vector and axial-vector states to be heavy, with masses above the TeV scale, and suggests that the Higgs-like scalar should have a WW coupling close to the standard model one. Our conclusions are generic and apply to more specific scenarios such as the minimal SO(5)/SO(4) composite Higgs model.

Effects of Climate and Climate Change on Vectors and Vector-Borne Diseases: Ticks Are Different.

PubMed

Ogden, Nick H; Lindsay, L Robbin

2016-08-01

There has been considerable debate as to whether global risk from vector-borne diseases will be impacted by climate change. This has focussed on important mosquito-borne diseases that are transmitted by the vectors from infected to uninfected humans. However, this debate has mostly ignored the biological diversity of vectors and vector-borne diseases. Here, we review how climate and climate change may impact those most divergent of arthropod disease vector groups: multivoltine insects and hard-bodied (ixodid) ticks. We contrast features of the life cycles and behaviour of these arthropods, and how weather, climate, and climate change may have very different impacts on the spatiotemporal occurrence and abundance of vectors, and the pathogens they transmit. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Global positioning system measurements for crustal deformation: Precision and accuracy

USGS Publications Warehouse

Prescott, W.H.; Davis, J.L.; Svarc, J.L.

1989-01-01

Analysis of 27 repeated observations of Global Positioning System (GPS) position-difference vectors, up to 11 kilometers in length, indicates that the standard deviation of the measurements is 4 millimeters for the north component, 6 millimeters for the east component, and 10 to 20 millimeters for the vertical component. The uncertainty grows slowly with increasing vector length. At 225 kilometers, the standard deviation of the measurement is 6, 11, and 40 millimeters for the north, east, and up components, respectively. Measurements with GPS and Geodolite, an electromagnetic distance-measuring system, over distances of 10 to 40 kilometers agree within 0.2 part per million. Measurements with GPS and very long baseline interferometry of the 225-kilometer vector agree within 0.05 part per million.

A combined vector potential-scalar potential method for FE computation of 3D magnetic fields in electrical devices with iron cores

NASA Technical Reports Server (NTRS)

Wang, R.; Demerdash, N. A.

1991-01-01

A method of combined use of magnetic vector potential based finite-element (FE) formulations and magnetic scalar potential (MSP) based formulations for computation of three-dimensional magnetostatic fields is introduced. In this method, the curl-component of the magnetic field intensity is computed by a reduced magnetic vector potential. This field intensity forms the basic of a forcing function for a global magnetic scalar potential solution over the entire volume of the region. This method allows one to include iron portions sandwiched in between conductors within partitioned current-carrying subregions. The method is most suited for large-scale global-type 3-D magnetostatic field computations in electrical devices, and in particular rotating electric machinery.

Medical Image Retrieval Using Multi-Texton Assignment.

PubMed

Tang, Qiling; Yang, Jirong; Xia, Xianfu

2018-02-01

In this paper, we present a multi-texton representation method for medical image retrieval, which utilizes the locality constraint to encode each filter bank response within its local-coordinate system consisting of the k nearest neighbors in texton dictionary and subsequently employs spatial pyramid matching technique to implement feature vector representation. Comparison with the traditional nearest neighbor assignment followed by texton histogram statistics method, our strategies reduce the quantization errors in mapping process and add information about the spatial layout of texton distributions and, thus, increase the descriptive power of the image representation. We investigate the effects of different parameters on system performance in order to choose the appropriate ones for our datasets and carry out experiments on the IRMA-2009 medical collection and the mammographic patch dataset. The extensive experimental results demonstrate that the proposed method has superior performance.

A CPT for Improving Turbulence and Cloud Processes in the NCEP Global Models

NASA Astrophysics Data System (ADS)

Krueger, S. K.; Moorthi, S.; Randall, D. A.; Pincus, R.; Bogenschutz, P.; Belochitski, A.; Chikira, M.; Dazlich, D. A.; Swales, D. J.; Thakur, P. K.; Yang, F.; Cheng, A.

2016-12-01

Our Climate Process Team (CPT) is based on the premise that the NCEP (National Centers for Environmental Prediction) global models can be improved by installing an integrated, self-consistent description of turbulence, clouds, deep convection, and the interactions between clouds and radiative and microphysical processes. The goal of our CPT is to unify the representation of turbulence and subgrid-scale (SGS) cloud processes and to unify the representation of SGS deep convective precipitation and grid-scale precipitation as the horizontal resolution decreases. We aim to improve the representation of small-scale phenomena by implementing a PDF-based SGS turbulence and cloudiness scheme that replaces the boundary layer turbulence scheme, the shallow convection scheme, and the cloud fraction schemes in the GFS (Global Forecast System) and CFS (Climate Forecast System) global models. We intend to improve the treatment of deep convection by introducing a unified parameterization that scales continuously between the simulation of individual clouds when and where the grid spacing is sufficiently fine and the behavior of a conventional parameterization of deep convection when and where the grid spacing is coarse. We will endeavor to improve the representation of the interactions of clouds, radiation, and microphysics in the GFS/CFS by using the additional information provided by the PDF-based SGS cloud scheme. The team is evaluating the impacts of the model upgrades with metrics used by the NCEP short-range and seasonal forecast operations.

Polynomial chaos representation of databases on manifolds

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

Soize, C., E-mail: christian.soize@univ-paris-est.fr; Ghanem, R., E-mail: ghanem@usc.edu

2017-04-15

Characterizing the polynomial chaos expansion (PCE) of a vector-valued random variable with probability distribution concentrated on a manifold is a relevant problem in data-driven settings. The probability distribution of such random vectors is multimodal in general, leading to potentially very slow convergence of the PCE. In this paper, we build on a recent development for estimating and sampling from probabilities concentrated on a diffusion manifold. The proposed methodology constructs a PCE of the random vector together with an associated generator that samples from the target probability distribution which is estimated from data concentrated in the neighborhood of the manifold. Themore » method is robust and remains efficient for high dimension and large datasets. The resulting polynomial chaos construction on manifolds permits the adaptation of many uncertainty quantification and statistical tools to emerging questions motivated by data-driven queries.« less

Terrain representation impact on periurban catchment morphological properties

NASA Astrophysics Data System (ADS)

Rodriguez, F.; Bocher, E.; Chancibault, K.

2013-04-01

SummaryModelling the hydrological behaviour of suburban catchments requires an estimation of environmental features, including land use and hydrographic networks. Suburban areas display a highly heterogeneous composition and encompass many anthropogenic elements that affect water flow paths, such as ditches, sewers, culverts and embankments. The geographical data available, either raster or vector data, may be of various origins and resolutions. Urban databases often offer very detailed data for sewer networks and 3D streets, yet the data covering rural zones may be coarser. This study is intended to highlight the sensitivity of geographical data as well as the data discretisation method used on the essential features of a periurban catchment, i.e. the catchment border and the drainage network. Three methods are implemented for this purpose. The first is the DEM (for digital elevation model) treatment method, which has traditionally been applied in the field of catchment hydrology. The second is based on urban database analysis and focuses on vector data, i.e. polygons and segments. The third method is a TIN (or triangular irregular network), which provides a consistent description of flow directions from an accurate representation of slope. It is assumed herein that the width function is representative of the catchment's hydrological response. The periurban Chézine catchment, located within the Nantes metropolitan area in western France, serves as the case study. The determination of both the main morphological features and the hydrological response of a suburban catchment varies significantly according to the discretization method employed, especially on upstream rural areas. Vector- and TIN-based methods allow representing the higher drainage density of urban areas, and consequently reveal the impact of these areas on the width function, since the DEM method fails. TINs seem to be more appropriate to take streets into account, because it allows a finer representation of topographical discontinuities. These results may help future developments of distributed hydrological models on periurban areas.

Social Representations and Practices Towards Triatomines and Chagas Disease in Calakmul, México.

PubMed

Valdez-Tah, Alba; Huicochea-Gómez, Laura; Ortega-Canto, Judith; Nazar-Beutelspacher, Austreberta; Ramsey, Janine M

2015-01-01

Vector-borne transmission of Trypanosoma cruzi (VBTTc) is dependent on the concomitant interaction between biological and environmental hazard over the entire landscape, and human vulnerability. Representations and practices of health-disease-care-seeking and territorial appropriation and use were analyzed for VBTTc in a qualitative ethnographic study in the Zoh-Laguna landscape, Campeche, Mexico. In-depth interviews and participatory observation explored representations and practices regarding ethno-ecological knowledge related to vector-transmission, health-disease-care-seeking, and land use processes. The population has a broad knowledge of biting insects, which they believe are all most abundant in the rainy season; the community´s proximity to natural areas is perceived as a barrier to control their abundance. Triatomines are mostly recognized by men, who have detailed knowledge regarding their occurrence and association with mammals in non-domestic fragments, where they report being bitten. Women emphasize the dermal consequences of triatomine bites, but have little knowledge about the disease. Triatomine bites and the chinchoma are "normalized" events which are treated using home remedies, if at all. The neglected condition of Chagas disease in Mexican public health policies, livelihoods which are dependent on primary production, and gender-related knowledge (or lack thereof) are structural circumstances which influence the environment and inhabitants´ living conditions; in turn, these trigger triatomine-human contact. The most important landscape practices producing vulnerability are the activities and mobility within and between landscape fragments causing greater exposure of inhabitants primarily in the dry season. A landscape approach to understanding vulnerability components of VBTTc from health-disease-care-seeking perspectives and based on territorial appropriation and use, is essential where there is continuous movement of vectors between and within all habitats. An understanding of the structural factors which motivate the population´s perceptions, beliefs, and practices and which create and maintain vulnerability is essential to develop culturally relevant and sustainable community-based VBTTc prevention and control.

Social Representations and Practices Towards Triatomines and Chagas Disease in Calakmul, México

PubMed Central

Valdez-Tah, Alba; Huicochea-Gómez, Laura; Ortega-Canto, Judith; Nazar-Beutelspacher, Austreberta; Ramsey, Janine M.

2015-01-01

Vector-borne transmission of Trypanosoma cruzi (VBTTc) is dependent on the concomitant interaction between biological and environmental hazard over the entire landscape, and human vulnerability. Representations and practices of health-disease-care-seeking and territorial appropriation and use were analyzed for VBTTc in a qualitative ethnographic study in the Zoh-Laguna landscape, Campeche, Mexico. In-depth interviews and participatory observation explored representations and practices regarding ethno-ecological knowledge related to vector-transmission, health-disease-care-seeking, and land use processes. The population has a broad knowledge of biting insects, which they believe are all most abundant in the rainy season; the community´s proximity to natural areas is perceived as a barrier to control their abundance. Triatomines are mostly recognized by men, who have detailed knowledge regarding their occurrence and association with mammals in non-domestic fragments, where they report being bitten. Women emphasize the dermal consequences of triatomine bites, but have little knowledge about the disease. Triatomine bites and the chinchoma are “normalized” events which are treated using home remedies, if at all. The neglected condition of Chagas disease in Mexican public health policies, livelihoods which are dependent on primary production, and gender-related knowledge (or lack thereof) are structural circumstances which influence the environment and inhabitants´ living conditions; in turn, these trigger triatomine-human contact. The most important landscape practices producing vulnerability are the activities and mobility within and between landscape fragments causing greater exposure of inhabitants primarily in the dry season. A landscape approach to understanding vulnerability components of VBTTc from health-disease-care-seeking perspectives and based on territorial appropriation and use, is essential where there is continuous movement of vectors between and within all habitats. An understanding of the structural factors which motivate the population´s perceptions, beliefs, and practices and which create and maintain vulnerability is essential to develop culturally relevant and sustainable community-based VBTTc prevention and control. PMID:26204555

Advection modes by optimal mass transfer

NASA Astrophysics Data System (ADS)

Iollo, Angelo; Lombardi, Damiano

2014-02-01

Classical model reduction techniques approximate the solution of a physical model by a limited number of global modes. These modes are usually determined by variants of principal component analysis. Global modes can lead to reduced models that perform well in terms of stability and accuracy. However, when the physics of the model is mainly characterized by advection, the nonlocal representation of the solution by global modes essentially reduces to a Fourier expansion. In this paper we describe a method to determine a low-order representation of advection. This method is based on the solution of Monge-Kantorovich mass transfer problems. Examples of application to point vortex scattering, Korteweg-de Vries equation, and hurricane Dean advection are discussed.

The global compendium of Aedes aegypti and Ae. albopictus occurrence

NASA Astrophysics Data System (ADS)

Kraemer, Moritz U. G.; Sinka, Marianne E.; Duda, Kirsten A.; Mylne, Adrian; Shearer, Freya M.; Brady, Oliver J.; Messina, Jane P.; Barker, Christopher M.; Moore, Chester G.; Carvalho, Roberta G.; Coelho, Giovanini E.; van Bortel, Wim; Hendrickx, Guy; Schaffner, Francis; Wint, G. R. William; Elyazar, Iqbal R. F.; Teng, Hwa-Jen; Hay, Simon I.

2015-07-01

Aedes aegypti and Ae. albopictus are the main vectors transmitting dengue and chikungunya viruses. Despite being pathogens of global public health importance, knowledge of their vectors’ global distribution remains patchy and sparse. A global geographic database of known occurrences of Ae. aegypti and Ae. albopictus between 1960 and 2014 was compiled. Herein we present the database, which comprises occurrence data linked to point or polygon locations, derived from peer-reviewed literature and unpublished studies including national entomological surveys and expert networks. We describe all data collection processes, as well as geo-positioning methods, database management and quality-control procedures. This is the first comprehensive global database of Ae. aegypti and Ae. albopictus occurrence, consisting of 19,930 and 22,137 geo-positioned occurrence records respectively. Both datasets can be used for a variety of mapping and spatial analyses of the vectors and, by inference, the diseases they transmit.

The global compendium of Aedes aegypti and Ae. albopictus occurrence

PubMed Central

Kraemer, Moritz U. G.; Sinka, Marianne E.; Duda, Kirsten A.; Mylne, Adrian; Shearer, Freya M.; Brady, Oliver J.; Messina, Jane P.; Barker, Christopher M.; Moore, Chester G.; Carvalho, Roberta G.; Coelho, Giovanini E.; Van Bortel, Wim; Hendrickx, Guy; Schaffner, Francis; Wint, G. R. William; Elyazar, Iqbal R. F.; Teng, Hwa-Jen; Hay, Simon I.

2015-01-01

Aedes aegypti and Ae. albopictus are the main vectors transmitting dengue and chikungunya viruses. Despite being pathogens of global public health importance, knowledge of their vectors’ global distribution remains patchy and sparse. A global geographic database of known occurrences of Ae. aegypti and Ae. albopictus between 1960 and 2014 was compiled. Herein we present the database, which comprises occurrence data linked to point or polygon locations, derived from peer-reviewed literature and unpublished studies including national entomological surveys and expert networks. We describe all data collection processes, as well as geo-positioning methods, database management and quality-control procedures. This is the first comprehensive global database of Ae. aegypti and Ae. albopictus occurrence, consisting of 19,930 and 22,137 geo-positioned occurrence records respectively. Both datasets can be used for a variety of mapping and spatial analyses of the vectors and, by inference, the diseases they transmit. PMID:26175912

The Effects of Climate Change and Globalization on Mosquito Vectors: Evidence from Jeju Island, South Korea on the Potential for Asian Tiger Mosquito (Aedes albopictus) Influxes and Survival from Vietnam Rather Than Japan

PubMed Central

Jeong, Ji Yeon; Yoo, Seung Jin; Koh, Young-Sang; Lee, Seogjae; Heo, Sang Taek; Seong, Seung-Yong; Lee, Keun Hwa

2013-01-01

Background Climate change affects the survival and transmission of arthropod vectors as well as the development rates of vector-borne pathogens. Increased international travel is also an important factor in the spread of vector-borne diseases (VBDs) such as dengue, West Nile, yellow fever, chikungunya, and malaria. Dengue is the most important vector-borne viral disease. An estimated 2.5 billion people are at risk of infection in the world and there are approximately 50 million dengue infections and an estimated 500,000 individuals are hospitalized with dengue haemorrhagic fever annually. The Asian tiger mosquito (Aedes albopictus) is one of the vectors of dengue virus, and populations already exist on Jeju Island, South Korea. Currently, colder winter temperatures kill off Asian tiger mosquito populations and there is no evidence of the mosquitos being vectors for the dengue virus in this location. However, dengue virus-bearing mosquito vectors can inflow to Jeju Island from endemic area such as Vietnam by increased international travel, and this mosquito vector's survival during colder winter months will likely occur due to the effects of climate change. Methods and Results In this section, we show the geographical distribution of medically important mosquito vectors such as Ae. albopictus, a vector of both dengue and chikungunya viruses; Culex pipiens, a vector of West Nile virus; and Anopheles sinensis, a vector of Plasmodium vivax, within Jeju Island, South Korea. We found a significant association between the mean temperature, amount of precipitation, and density of mosquitoes. The phylogenetic analyses show that an Ae. albopictus, collected in southern area of Jeju Island, was identical to specimens found in Ho Chi Minh, Vietnam, and not Nagasaki, Japan. Conclusion Our results suggest that mosquito vectors or virus-bearing vectors can transmit from epidemic regions of Southeast Asia to Jeju Island and can survive during colder winter months. Therefore, Jeju Island is no longer safe from vector borne diseases (VBDs) due to the effects of globalization and climate change, and we should immediately monitor regional climate change to identify newly emerging VBDs. PMID:23894312

The effects of climate change and globalization on mosquito vectors: evidence from Jeju Island, South Korea on the potential for Asian tiger mosquito (Aedes albopictus) influxes and survival from Vietnam rather than Japan.

PubMed

Lee, Su Hyun; Nam, Kwang Woo; Jeong, Ji Yeon; Yoo, Seung Jin; Koh, Young-Sang; Lee, Seogjae; Heo, Sang Taek; Seong, Seung-Yong; Lee, Keun Hwa

2013-01-01

Climate change affects the survival and transmission of arthropod vectors as well as the development rates of vector-borne pathogens. Increased international travel is also an important factor in the spread of vector-borne diseases (VBDs) such as dengue, West Nile, yellow fever, chikungunya, and malaria. Dengue is the most important vector-borne viral disease. An estimated 2.5 billion people are at risk of infection in the world and there are approximately 50 million dengue infections and an estimated 500,000 individuals are hospitalized with dengue haemorrhagic fever annually. The Asian tiger mosquito (Aedes albopictus) is one of the vectors of dengue virus, and populations already exist on Jeju Island, South Korea. Currently, colder winter temperatures kill off Asian tiger mosquito populations and there is no evidence of the mosquitos being vectors for the dengue virus in this location. However, dengue virus-bearing mosquito vectors can inflow to Jeju Island from endemic area such as Vietnam by increased international travel, and this mosquito vector's survival during colder winter months will likely occur due to the effects of climate change. In this section, we show the geographical distribution of medically important mosquito vectors such as Ae. albopictus, a vector of both dengue and chikungunya viruses; Culex pipiens, a vector of West Nile virus; and Anopheles sinensis, a vector of Plasmodium vivax, within Jeju Island, South Korea. We found a significant association between the mean temperature, amount of precipitation, and density of mosquitoes. The phylogenetic analyses show that an Ae. albopictus, collected in southern area of Jeju Island, was identical to specimens found in Ho Chi Minh, Vietnam, and not Nagasaki, Japan. Our results suggest that mosquito vectors or virus-bearing vectors can transmit from epidemic regions of Southeast Asia to Jeju Island and can survive during colder winter months. Therefore, Jeju Island is no longer safe from vector borne diseases (VBDs) due to the effects of globalization and climate change, and we should immediately monitor regional climate change to identify newly emerging VBDs.

Visual information processing II; Proceedings of the Meeting, Orlando, FL, Apr. 14-16, 1993

NASA Technical Reports Server (NTRS)

Huck, Friedrich O. (Editor); Juday, Richard D. (Editor)

1993-01-01

Various papers on visual information processing are presented. Individual topics addressed include: aliasing as noise, satellite image processing using a hammering neural network, edge-detetion method using visual perception, adaptive vector median filters, design of a reading test for low-vision image warping, spatial transformation architectures, automatic image-enhancement method, redundancy reduction in image coding, lossless gray-scale image compression by predictive GDF, information efficiency in visual communication, optimizing JPEG quantization matrices for different applications, use of forward error correction to maintain image fidelity, effect of peanoscanning on image compression. Also discussed are: computer vision for autonomous robotics in space, optical processor for zero-crossing edge detection, fractal-based image edge detection, simulation of the neon spreading effect by bandpass filtering, wavelet transform (WT) on parallel SIMD architectures, nonseparable 2D wavelet image representation, adaptive image halftoning based on WT, wavelet analysis of global warming, use of the WT for signal detection, perfect reconstruction two-channel rational filter banks, N-wavelet coding for pattern classification, simulation of image of natural objects, number-theoretic coding for iconic systems.

The holographic dual of the Penrose transform

NASA Astrophysics Data System (ADS)

Neiman, Yasha

2018-01-01

We consider the holographic duality between type-A higher-spin gravity in AdS4 and the free U( N) vector model. In the bulk, linearized solutions can be translated into twistor functions via the Penrose transform. We propose a holographic dual to this transform, which translates between twistor functions and CFT sources and operators. We present a twistorial expression for the partition function, which makes global higher-spin symmetry manifest, and appears to automatically include all necessary contact terms. In this picture, twistor space provides a fully nonlocal, gauge-invariant description underlying both bulk and boundary spacetime pictures. While the bulk theory is handled at the linear level, our formula for the partition function includes the effects of bulk interactions. Thus, the CFT is used to solve the bulk, with twistors as a language common to both. A key ingredient in our result is the study of ordinary spacetime symmetries within the fundamental representation of higher-spin algebra. The object that makes these "square root" spacetime symmetries manifest becomes the kernel of our boundary/twistor transform, while the original Penrose transform is identified as a "square root" of CPT.

The Duffin-Kemmer-Petiau oscillator

NASA Technical Reports Server (NTRS)

Nedjadi, Youcef; Barrett, Roger

1995-01-01

In view of current interest in relativistic spin-one systems and the recent work on the Dirac Oscillator, we introduce the Duffin-Kemmer-Petiau (DKP) equation obtained by using an external potential linear in r. Since, in the non-relativistic limit, the spin 1 representation leads to a harmonic oscillator with a spin-orbit coupling of the Thomas form, we call the equation the DKP oscillator. This oscillator is a relativistic generalization of the quantum harmonic oscillator for scalar and vector bosons. We show that it conserves total angular momentum and that it is exactly solvable. We calculate and discuss the eigenspectrum of the DKP oscillator in the spin 1 representation.

Plasmodium evasion of mosquito immunity and global malaria transmission: The lock-and-key theory.

PubMed

Molina-Cruz, Alvaro; Canepa, Gaspar E; Kamath, Nitin; Pavlovic, Noelle V; Mu, Jianbing; Ramphul, Urvashi N; Ramirez, Jose Luis; Barillas-Mury, Carolina

2015-12-08

Plasmodium falciparum malaria originated in Africa and became global as humans migrated to other continents. During this journey, parasites encountered new mosquito species, some of them evolutionarily distant from African vectors. We have previously shown that the Pfs47 protein allows the parasite to evade the mosquito immune system of Anopheles gambiae mosquitoes. Here, we investigated the role of Pfs47-mediated immune evasion in the adaptation of P. falciparum to evolutionarily distant mosquito species. We found that P. falciparum isolates from Africa, Asia, or the Americas have low compatibility to malaria vectors from a different continent, an effect that is mediated by the mosquito immune system. We identified 42 different haplotypes of Pfs47 that have a strong geographic population structure and much lower haplotype diversity outside Africa. Replacement of the Pfs47 haplotypes in a P. falciparum isolate is sufficient to make it compatible to a different mosquito species. Those parasites that express a Pfs47 haplotype compatible with a given vector evade antiplasmodial immunity and survive. We propose that Pfs47-mediated immune evasion has been critical for the globalization of P. falciparum malaria as parasites adapted to new vector species. Our findings predict that this ongoing selective force by the mosquito immune system could influence the dispersal of Plasmodium genetic traits and point to Pfs47 as a potential target to block malaria transmission. A new model, the "lock-and-key theory" of P. falciparum globalization, is proposed, and its implications are discussed.

Sensitivity Analysis of the Static Aeroelastic Response of a Wing

NASA Technical Reports Server (NTRS)

Eldred, Lloyd B.

1993-01-01

A technique to obtain the sensitivity of the static aeroelastic response of a three dimensional wing model is designed and implemented. The formulation is quite general and accepts any aerodynamic and structural analysis capability. A program to combine the discipline level, or local, sensitivities into global sensitivity derivatives is developed. A variety of representations of the wing pressure field are developed and tested to determine the most accurate and efficient scheme for representing the field outside of the aerodynamic code. Chebyshev polynomials are used to globally fit the pressure field. This approach had some difficulties in representing local variations in the field, so a variety of local interpolation polynomial pressure representations are also implemented. These panel based representations use a constant pressure value, a bilinearly interpolated value. or a biquadraticallv interpolated value. The interpolation polynomial approaches do an excellent job of reducing the numerical problems of the global approach for comparable computational effort. Regardless of the pressure representation used. sensitivity and response results with excellent accuracy have been produced for large integrated quantities such as wing tip deflection and trim angle of attack. The sensitivities of such things as individual generalized displacements have been found with fair accuracy. In general, accuracy is found to be proportional to the relative size of the derivatives to the quantity itself.

The Total Gaussian Class of Quasiprobabilities and its Relation to Squeezed-State Excitations

NASA Technical Reports Server (NTRS)

Wuensche, Alfred

1996-01-01

The class of quasiprobabilities obtainable from the Wigner quasiprobability by convolutions with the general class of Gaussian functions is investigated. It can be described by a three-dimensional, in general, complex vector parameter with the property of additivity when composing convolutions. The diagonal representation of this class of quasiprobabilities is connected with a generalization of the displaced Fock states in direction of squeezing. The subclass with real vector parameter is considered more in detail. It is related to the most important kinds of boson operator ordering. The properties of a specific set of discrete excitations of squeezed coherent states are given.

Curvilinear component analysis: a self-organizing neural network for nonlinear mapping of data sets.

PubMed

Demartines, P; Herault, J

1997-01-01

We present a new strategy called "curvilinear component analysis" (CCA) for dimensionality reduction and representation of multidimensional data sets. The principle of CCA is a self-organized neural network performing two tasks: vector quantization (VQ) of the submanifold in the data set (input space); and nonlinear projection (P) of these quantizing vectors toward an output space, providing a revealing unfolding of the submanifold. After learning, the network has the ability to continuously map any new point from one space into another: forward mapping of new points in the input space, or backward mapping of an arbitrary position in the output space.

A new local-global approach for classification.

PubMed

Peres, R T; Pedreira, C E

2010-09-01

In this paper, we propose a new local-global pattern classification scheme that combines supervised and unsupervised approaches, taking advantage of both, local and global environments. We understand as global methods the ones concerned with the aim of constructing a model for the whole problem space using the totality of the available observations. Local methods focus into sub regions of the space, possibly using an appropriately selected subset of the sample. In the proposed method, the sample is first divided in local cells by using a Vector Quantization unsupervised algorithm, the LBG (Linde-Buzo-Gray). In a second stage, the generated assemblage of much easier problems is locally solved with a scheme inspired by Bayes' rule. Four classification methods were implemented for comparison purposes with the proposed scheme: Learning Vector Quantization (LVQ); Feedforward Neural Networks; Support Vector Machine (SVM) and k-Nearest Neighbors. These four methods and the proposed scheme were implemented in eleven datasets, two controlled experiments, plus nine public available datasets from the UCI repository. The proposed method has shown a quite competitive performance when compared to these classical and largely used classifiers. Our method is simple concerning understanding and implementation and is based on very intuitive concepts. Copyright 2010 Elsevier Ltd. All rights reserved.

Establishing a group of endpoints to support collective operations without specifying unique identifiers for any endpoints

DOEpatents

Archer, Charles J.; Blocksom, Michael A.; Ratterman, Joseph D.; Smith, Brian E.; Xue, Hanghon

2016-02-02

A parallel computer executes a number of tasks, each task includes a number of endpoints and the endpoints are configured to support collective operations. In such a parallel computer, establishing a group of endpoints receiving a user specification of a set of endpoints included in a global collection of endpoints, where the user specification defines the set in accordance with a predefined virtual representation of the endpoints, the predefined virtual representation is a data structure setting forth an organization of tasks and endpoints included in the global collection of endpoints and the user specification defines the set of endpoints without a user specification of a particular endpoint; and defining a group of endpoints in dependence upon the predefined virtual representation of the endpoints and the user specification.

Establishing a group of endpoints in a parallel computer

DOEpatents

Archer, Charles J.; Blocksome, Michael A.; Ratterman, Joseph D.; Smith, Brian E.; Xue, Hanhong

2016-02-02

A parallel computer executes a number of tasks, each task includes a number of endpoints and the endpoints are configured to support collective operations. In such a parallel computer, establishing a group of endpoints receiving a user specification of a set of endpoints included in a global collection of endpoints, where the user specification defines the set in accordance with a predefined virtual representation of the endpoints, the predefined virtual representation is a data structure setting forth an organization of tasks and endpoints included in the global collection of endpoints and the user specification defines the set of endpoints without a user specification of a particular endpoint; and defining a group of endpoints in dependence upon the predefined virtual representation of the endpoints and the user specification.

Malaria vector control at a crossroads: public health entomology and the drive to elimination.

PubMed

Mnzava, Abraham P; Macdonald, Michael B; Knox, Tessa B; Temu, Emmanuel A; Shiff, Clive J

2014-09-01

Vector control has been at the core of successful malaria control. However, a dearth of field-oriented vector biologists threatens to undermine global reductions in malaria burden. Skilled cadres are needed to manage insecticide resistance, to maintain coverage with current interventions, to develop new paradigms for tackling 'residual' transmission and to target interventions as transmission becomes increasingly heterogeneous. Recognising this human resource crisis, in September 2013, WHO Global Malaria Programme issued guidance for capacity building in entomology and vector control, including recommendations for countries and implementing partners. Ministries were urged to develop long-range strategic plans for building human resources for public health entomology and vector control (including skills in epidemiology, geographic information systems, operational research and programme management) and to set in place the requisite professional posts and career opportunities. Capacity building and national ownership in all partner projects and a clear exit strategy to sustain human and technical resources after project completion were emphasised. Implementing partners were urged to support global and regional efforts to enhance public health entomology capacity. While the challenges inherent in such capacity building are great, so too are the opportunities to establish the next generation of public health entomologists that will enable programmes to continue on the path to malaria elimination. © The Author 2014. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Hyperresolution Global Land Surface Modeling: Meeting a Grand Challenge for Monitoring Earth's Terrestrial Water

NASA Technical Reports Server (NTRS)

Wood, Eric F.; Roundy, Joshua K.; Troy, Tara J.; van Beek, L. P. H.; Bierkens, Marc F. P.; 4 Blyth, Eleanor; de Roo, Ad; Doell. Petra; Ek, Mike; Famiglietti, James;

Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth's terrestrial water

NASA Astrophysics Data System (ADS)

Wood, Eric F.; Roundy, Joshua K.; Troy, Tara J.; van Beek, L. P. H.; Bierkens, Marc F. P.; Blyth, Eleanor; de Roo, Ad; DöLl, Petra; Ek, Mike; Famiglietti, James; Gochis, David; van de Giesen, Nick; Houser, Paul; Jaffé, Peter R.; Kollet, Stefan; Lehner, Bernhard; Lettenmaier, Dennis P.; Peters-Lidard, Christa; Sivapalan, Murugesu; Sheffield, Justin; Wade, Andrew; Whitehead, Paul

2011-05-01

Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (˜10-100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface-subsurface interactions due to fine-scale topography and vegetation; improved representation of land-atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 109 unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a "grand challenge" to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

Predicting the host of influenza viruses based on the word vector.

PubMed

Xu, Beibei; Tan, Zhiying; Li, Kenli; Jiang, Taijiao; Peng, Yousong

2017-01-01

Newly emerging influenza viruses continue to threaten public health. A rapid determination of the host range of newly discovered influenza viruses would assist in early assessment of their risk. Here, we attempted to predict the host of influenza viruses using the Support Vector Machine (SVM) classifier based on the word vector, a new representation and feature extraction method for biological sequences. The results show that the length of the word within the word vector, the sequence type (DNA or protein) and the species from which the sequences were derived for generating the word vector all influence the performance of models in predicting the host of influenza viruses. In nearly all cases, the models built on the surface proteins hemagglutinin (HA) and neuraminidase (NA) (or their genes) produced better results than internal influenza proteins (or their genes). The best performance was achieved when the model was built on the HA gene based on word vectors (words of three-letters long) generated from DNA sequences of the influenza virus. This results in accuracies of 99.7% for avian, 96.9% for human and 90.6% for swine influenza viruses. Compared to the method of sequence homology best-hit searches using the Basic Local Alignment Search Tool (BLAST), the word vector-based models still need further improvements in predicting the host of influenza A viruses.

Resurgent vector-borne diseases as a global health problem.

PubMed Central

Gubler, D. J.

1998-01-01

Vector-borne infectious diseases are emerging or resurging as a result of changes in public health policy, insecticide and drug resistance, shift in emphasis from prevention to emergency response, demographic and societal changes, and genetic changes in pathogens. Effective prevention strategies can reverse this trend. Research on vaccines, environmentally safe insecticides, alternative approaches to vector control, and training programs for health-care workers are needed. PMID:9716967

A malaria transmission-directed model of mosquito life cycle and ecology

PubMed Central

2011-01-01

Background Malaria is a major public health issue in much of the world, and the mosquito vectors which drive transmission are key targets for interventions. Mathematical models for planning malaria eradication benefit from detailed representations of local mosquito populations, their natural dynamics and their response to campaign pressures. Methods A new model is presented for mosquito population dynamics, effects of weather, and impacts of multiple simultaneous interventions. This model is then embedded in a large-scale individual-based simulation and results for local elimination of malaria are discussed. Mosquito population behaviours, such as anthropophily and indoor feeding, are included to study their effect upon the efficacy of vector control-based elimination campaigns. Results Results for vector control tools, such as bed nets, indoor spraying, larval control and space spraying, both alone and in combination, are displayed for a single-location simulation with vector species and seasonality characteristic of central Tanzania, varying baseline transmission intensity and vector bionomics. The sensitivities to habitat type, anthropophily, indoor feeding, and baseline transmission intensity are explored. Conclusions The ability to model a spectrum of local vector species with different ecologies and behaviours allows local customization of packages of interventions and exploration of the effect of proposed new tools. PMID:21999664

Genetic variation in arthropod vectors of disease-causing organisms: obstacles and opportunities.

PubMed Central

Gooding, R H

1996-01-01

An overview of the genetic variation in arthropods that transmit pathogens to vertebrates is presented, emphasizing the genetics of vector-pathogen relationships and the biochemical genetics of vectors. Vector-pathogen interactions are reviewed briefly as a prelude to a discussion of the genetics of susceptibility and refractoriness in vectors. Susceptibility to pathogens is controlled by maternally inherited factors, sex-linked dominant alleles, and dominant and recessive autosomal genes. There is widespread interpopulation (including intercolony) and temporal variation in susceptibility to pathogens. The amount of biochemical genetic variation in vectors is similar to that found in other invertebrates. However, the amount varies widely among species, among populations within species, and temporally within populations. Biochemical genetic studies show that there is considerable genetic structuring of many vectors at the local, regional, and global levels. It is argued that genetic variation in vectors is critical in understanding vector-pathogen interactions and that genetic variation in vectors creates both obstacles to and opportunities for application of genetic techniques to the control of vectors. PMID:8809462

Implementing Cargo Movement into Climate Based Risk Assessment of Vector-Borne Diseases

PubMed Central

Thomas, Stephanie Margarete; Tjaden, Nils Benjamin; van den Bos, Sanne; Beierkuhnlein, Carl

2014-01-01

During the last decades the disease vector Aedes albopictus (Asian tiger mosquito) has rapidly spread around the globe. Global shipment of goods contributes to its permanent introduction. Invaded regions are facing novel and serious public health concerns, especially regarding the transmission of formerly non-endemic arboviruses such as dengue and chikungunya. The further development and potential spread to other regions depends largely on their climatic suitability. Here, we have developed a tool for identifying and prioritizing European areas at risk for the establishment of Aedes albopictus by taking into account, for the first time, the freight imports from this mosquito’s endemic countries and the climate suitability at harbors and their surrounding regions. In a second step we consider the further transport of containers by train and inland waterways because these types of transport can be well controlled. We identify European regions at risk, where a huge amount of transported goods meet climatically suitable conditions for the disease vector. The current and future suitability of the climate for Aedes albopictus was modeled by a correlative niche model approach and the Regional Climate Model COSMO-CLM. This risk assessment combines impacts of globalization and global warming to improve effective and proactive interventions in disease vector surveillance and control actions. PMID:24658412

Globally invasive, withdrawing at home: Aedes albopictus and Aedes japonicus facing the rise of Aedes flavopictus

NASA Astrophysics Data System (ADS)

Chaves, Luis Fernando

2016-11-01

It has been suggested that climate change may have facilitated the global expansion of invasive disease vectors, since several species have expanded their range as temperatures have warmed. Here, we present results from observations on two major global invasive mosquito vectors (Diptera: Culicidae), Aedes albopictus (Skuse) and Aedes japonicus (Theobald), across the altitudinal range of Mt. Konpira, Nagasaki, Japan, a location within their native range, where Aedes flavopictus Yamada, formerly a rare species, has now become dominant. Spatial abundance patterns of the three species suggest that temperature is an important factor influencing their adult distribution across the altitudinal range of Mt. Konpira. Temporal abundance patterns, by contrast, were associated with rainfall and showed signals of density-dependent regulation in the three species. The spatial and temporal analysis of abundance patterns showed that Ae. flavopictus and Ae. albopictus were negatively associated, even when accounting for differential impacts of weather and other environmental factors in their co-occurrence patterns. Our results highlight a contingency in the expansion of invasive vectors, the potential emergence of changes in their interactions with species in their native communities, and raise the question of whether these changes might be useful to predict the emergence of future invasive vectors.

Fuzzy associative memories

NASA Technical Reports Server (NTRS)

Kosko, Bart

1991-01-01

Mappings between fuzzy cubes are discussed. This level of abstraction provides a surprising and fruitful alternative to the propositional and predicate-calculas reasoning techniques used in expert systems. It allows one to reason with sets instead of propositions. Discussed here are fuzzy and neural function estimators, neural vs. fuzzy representation of structured knowledge, fuzzy vector-matrix multiplication, and fuzzy associative memory (FAM) system architecture.

Research in computer science

NASA Technical Reports Server (NTRS)

Ortega, J. M.

1984-01-01

The research efforts of University of Virginia students under a NASA sponsored program are summarized and the status of the program is reported. The research includes: testing method evaluations for N version programming; a representation scheme for modeling three dimensional objects; fault tolerant protocols for real time local area networks; performance investigation of Cyber network; XFEM implementation; and vectorizing incomplete Cholesky conjugate gradients.

Vectors, Change of Basis and Matrix Representation: Onto-Semiotic Approach in the Analysis of Creating Meaning

ERIC Educational Resources Information Center

Montiel, Mariana; Wilhelmi, Miguel R.; Vidakovic, Draga; Elstak, Iwan

2012-01-01

In a previous study, the onto-semiotic approach was employed to analyse the mathematical notion of different coordinate systems, as well as some situations and university students' actions related to these coordinate systems in the context of multivariate calculus. This study approaches different coordinate systems through the process of change of…

Skeletal Muscle Fascicle Arrangements Can Be Reconstructed Using a Laplacian Vector Field Simulation

PubMed Central

Choi, Hon Fai; Blemker, Silvia S.

2013-01-01

Skeletal muscles are characterized by a large diversity in anatomical architecture and function. Muscle force and contraction are generated by contractile fiber cells grouped in fascicle bundles, which transmit the mechanical action between origin and insertion attachments of the muscle. Therefore, an adequate representation of fascicle arrangements in computational models of skeletal muscles is important, especially when investigating three-dimensional muscle deformations in finite element models. However, obtaining high resolution in vivo measurements of fascicle arrangements in skeletal muscles is currently still challenging. This motivated the development of methods in previous studies to generate numerical representations of fascicle trajectories using interpolation templates. Here, we present an alternative approach based on the hypothesis of a rotation and divergence free (Laplacian) vector field behavior which reflects observed physical characteristics of fascicle trajectories. To obtain this representation, the Laplace equation was solved in anatomical reconstructions of skeletal muscle shapes based on medical images using a uniform flux boundary condition on the attachment areas. Fascicle tracts were generated through a robust flux based tracing algorithm. The concept of this approach was demonstrated in two-dimensional synthetic examples of typical skeletal muscle architectures. A detailed evaluation was performed in an example of the anatomical human tibialis anterior muscle which showed an overall agreement with measurements from the literature. The utility and capability of the proposed method was further demonstrated in other anatomical examples of human skeletal muscles with a wide range of muscle shapes and attachment morphologies. PMID:24204878

Assessment of Ice Shape Roughness Using a Self-Orgainizing Map Approach

NASA Technical Reports Server (NTRS)

Mcclain, Stephen T.; Kreeger, Richard E.

2013-01-01

Self-organizing maps are neural-network techniques for representing noisy, multidimensional data aligned along a lower-dimensional and nonlinear manifold. For a large set of noisy data, each element of a finite set of codebook vectors is iteratively moved in the direction of the data closest to the winner codebook vector. Through successive iterations, the codebook vectors begin to align with the trends of the higher-dimensional data. Prior investigations of ice shapes have focused on using self-organizing maps to characterize mean ice forms. The Icing Research Branch has recently acquired a high resolution three dimensional scanner system capable of resolving ice shape surface roughness. A method is presented for the evaluation of surface roughness variations using high-resolution surface scans based on a self-organizing map representation of the mean ice shape. The new method is demonstrated for 1) an 18-in. NACA 23012 airfoil 2 AOA just after the initial ice coverage of the leading 5 of the suction surface of the airfoil, 2) a 21-in. NACA 0012 at 0AOA following coverage of the leading 10 of the airfoil surface, and 3) a cold-soaked 21-in.NACA 0012 airfoil without ice. The SOM method resulted in descriptions of the statistical coverage limits and a quantitative representation of early stages of ice roughness formation on the airfoils. Limitations of the SOM method are explored, and the uncertainty limits of the method are investigated using the non-iced NACA 0012 airfoil measurements.

Transnational Feminist Rhetorics in a Digital World

ERIC Educational Resources Information Center

Queen, Mary

2008-01-01

In this essay, the author examines the digital circulations of representations of one Afghan women's rights organization--the Revolutionary Association of Women of Afghanistan (RAWA)--to demonstrate the importance of a global and digital field for feminist rhetorical analysis. Specifically, this analysis traces how women's self-representations are…

Predictiveness of Disease Risk in a Global Outreach Tourist Setting in Thailand Using Meteorological Data and Vector-Borne Disease Incidences

PubMed Central

Ninphanomchai, Suwannapa; Chansang, Chitti; Hii, Yien Ling; Rocklöv, Joacim; Kittayapong, Pattamaporn

2014-01-01

Dengue and malaria are vector-borne diseases and major public health problems worldwide. Changes in climatic factors influence incidences of these diseases. The objective of this study was to investigate the relationship between vector-borne disease incidences and meteorological data, and hence to predict disease risk in a global outreach tourist setting. The retrospective data of dengue and malaria incidences together with local meteorological factors (temperature, rainfall, humidity) registered from 2001 to 2011 on Koh Chang, Thailand were used in this study. Seasonal distribution of disease incidences and its correlation with local climatic factors were analyzed. Seasonal patterns in disease transmission differed between dengue and malaria. Monthly meteorological data and reported disease incidences showed good predictive ability of disease transmission patterns. These findings provide a rational basis for identifying the predictive ability of local meteorological factors on disease incidence that may be useful for the implementation of disease prevention and vector control programs on the tourism island, where climatic factors fluctuate. PMID:25325356

Predictiveness of disease risk in a global outreach tourist setting in Thailand using meteorological data and vector-borne disease incidences.

PubMed

Ninphanomchai, Suwannapa; Chansang, Chitti; Hii, Yien Ling; Rocklöv, Joacim; Kittayapong, Pattamaporn

2014-10-16

Dengue and malaria are vector-borne diseases and major public health problems worldwide. Changes in climatic factors influence incidences of these diseases. The objective of this study was to investigate the relationship between vector-borne disease incidences and meteorological data, and hence to predict disease risk in a global outreach tourist setting. The retrospective data of dengue and malaria incidences together with local meteorological factors (temperature, rainfall, humidity) registered from 2001 to 2011 on Koh Chang, Thailand were used in this study. Seasonal distribution of disease incidences and its correlation with local climatic factors were analyzed. Seasonal patterns in disease transmission differed between dengue and malaria. Monthly meteorological data and reported disease incidences showed good predictive ability of disease transmission patterns. These findings provide a rational basis for identifying the predictive ability of local meteorological factors on disease incidence that may be useful for the implementation of disease prevention and vector control programs on the tourism island, where climatic factors fluctuate.

Global Magnetohydrodynamic Simulation Using High Performance FORTRAN on Parallel Computers

NASA Astrophysics Data System (ADS)

Ogino, T.

High Performance Fortran (HPF) is one of modern and common techniques to achieve high performance parallel computation. We have translated a 3-dimensional magnetohydrodynamic (MHD) simulation code of the Earth's magnetosphere from VPP Fortran to HPF/JA on the Fujitsu VPP5000/56 vector-parallel supercomputer and the MHD code was fully vectorized and fully parallelized in VPP Fortran. The entire performance and capability of the HPF MHD code could be shown to be almost comparable to that of VPP Fortran. A 3-dimensional global MHD simulation of the earth's magnetosphere was performed at a speed of over 400 Gflops with an efficiency of 76.5 VPP5000/56 in vector and parallel computation that permitted comparison with catalog values. We have concluded that fluid and MHD codes that are fully vectorized and fully parallelized in VPP Fortran can be translated with relative ease to HPF/JA, and a code in HPF/JA may be expected to perform comparably to the same code written in VPP Fortran.

The synoptic maps of Br from HMI observations

NASA Astrophysics Data System (ADS)

Hayashi, Keiji; Hoeksema, J. Todd; Liu, Sun; Yang, Xudong; Centeno, Rebecca; Leka, K. D.; Barnes, Graham

2012-03-01

The vector magnetic field measurement can, in principal, give the "true" radial component of the magnetic field. We prepare 4 types of synoptic maps of the radial photospheric magnetic field, from the vector magnetic field data disambiguated by means of the minimum energy method developed at NWRA/CoRA, the vector data determined under the potential-field acute assumption, and the vector data determined under the radial-acute assumption, and the standard line-of-sight magnetogram. The models of the global corona, the MHD and the PFSS, are applied to different types of maps. Although the three-dimensional structures of the global coronal magnetic field with different maps are similar and overall agreeing well the AIA full-disk images, noticeable differences among the model outputs are found especially in the high latitude regions. We will show details of these test maps and discuss the issues in determining the radial component of the photospheric magnetic field near the poles and limb.

Monthly Representations of Mid-Tropospheric Carbon Dioxide from the Atmospheric Infrared Sounder

NASA Technical Reports Server (NTRS)

Pagano, Thomas S.; Olsen, Edward T.; Chahine, Moustafa T.; Ruzmaikin, Alexander; Nguyen, Hai; Jiang, Xun

2011-01-01

The Atmospheric Infrared Sounder (AIRS) on NASA's Earth Observing System Aqua spacecraft was launched in May of 2002 and acquires hyperspectral infrared spectra used to generate a wide range of atmospheric products including temperature, water vapor, and trace gas species including carbon dioxide. Here we present monthly representations of global concentrations of mid-tropospheric carbon dioxide produced from 8 years of data obtained by AIRS between the years of 2003 and 2010. We define them as "representations" rather than "climatologies" to reflect that the files are produced over a relatively short time period and represent summaries of the Level 3 data. Finally, they have not yet been independently validated. The representations have a horizontal resolution of 2.0 deg x 2.5 deg (Latitude x Longitude) and faithfully reproduce the original 8 years of monthly L3 CO2 concentrations with a standard deviation of 1.48 ppm and less than 2% outliers. The representations are intended for use in studies of the global general circulation of CO2 and identification of anomalies in CO2 typically associated with atmospheric transport. The seasonal variability and trend found in the AIRS CO2 data are discussed.

Global differential geometry: An introduction for control engineers

NASA Technical Reports Server (NTRS)

Doolin, B. F.; Martin, C. F.

1982-01-01

The basic concepts and terminology of modern global differential geometry are discussed as an introduction to the Lie theory of differential equations and to the role of Grassmannians in control systems analysis. To reach these topics, the fundamental notions of manifolds, tangent spaces, vector fields, and Lie algebras are discussed and exemplified. An appendix reviews such concepts needed for vector calculus as open and closed sets, compactness, continuity, and derivative. Although the content is mathematical, this is not a mathematical treatise but rather a text for engineers to understand geometric and nonlinear control.

Diverse Region-Based CNN for Hyperspectral Image Classification.

PubMed

Zhang, Mengmeng; Li, Wei; Du, Qian

2018-06-01

Convolutional neural network (CNN) is of great interest in machine learning and has demonstrated excellent performance in hyperspectral image classification. In this paper, we propose a classification framework, called diverse region-based CNN, which can encode semantic context-aware representation to obtain promising features. With merging a diverse set of discriminative appearance factors, the resulting CNN-based representation exhibits spatial-spectral context sensitivity that is essential for accurate pixel classification. The proposed method exploiting diverse region-based inputs to learn contextual interactional features is expected to have more discriminative power. The joint representation containing rich spectral and spatial information is then fed to a fully connected network and the label of each pixel vector is predicted by a softmax layer. Experimental results with widely used hyperspectral image data sets demonstrate that the proposed method can surpass any other conventional deep learning-based classifiers and other state-of-the-art classifiers.

Artificial intelligence systems based on texture descriptors for vaccine development.

PubMed

Nanni, Loris; Brahnam, Sheryl; Lumini, Alessandra

2011-02-01

The aim of this work is to analyze and compare several feature extraction methods for peptide classification that are based on the calculation of texture descriptors starting from a matrix representation of the peptide. This texture-based representation of the peptide is then used to train a support vector machine classifier. In our experiments, the best results are obtained using local binary patterns variants and the discrete cosine transform with selected coefficients. These results are better than those previously reported that employed texture descriptors for peptide representation. In addition, we perform experiments that combine standard approaches based on amino acid sequence. The experimental section reports several tests performed on a vaccine dataset for the prediction of peptides that bind human leukocyte antigens and on a human immunodeficiency virus (HIV-1). Experimental results confirm the usefulness of our novel descriptors. The matlab implementation of our approaches is available at http://bias.csr.unibo.it/nanni/TexturePeptide.zip.

A unified account of gloss and lightness perception in terms of gamut relativity.

PubMed

Vladusich, Tony

2013-08-01

A recently introduced computational theory of visual surface representation, termed gamut relativity, overturns the classical assumption that brightness, lightness, and transparency constitute perceptual dimensions corresponding to the physical dimensions of luminance, diffuse reflectance, and transmittance, respectively. Here I extend the theory to show how surface gloss and lightness can be understood in a unified manner in terms of the vector computation of "layered representations" of surface and illumination properties, rather than as perceptual dimensions corresponding to diffuse and specular reflectance, respectively. The theory simulates the effects of image histogram skewness on surface gloss/lightness and lightness constancy as a function of specular highlight intensity. More generally, gamut relativity clarifies, unifies, and generalizes a wide body of previous theoretical and experimental work aimed at understanding how the visual system parses the retinal image into layered representations of surface and illumination properties.

Predicting perceptual quality of images in realistic scenario using deep filter banks

NASA Astrophysics Data System (ADS)

Zhang, Weixia; Yan, Jia; Hu, Shiyong; Ma, Yang; Deng, Dexiang

2018-03-01

Classical image perceptual quality assessment models usually resort to natural scene statistic methods, which are based on an assumption that certain reliable statistical regularities hold on undistorted images and will be corrupted by introduced distortions. However, these models usually fail to accurately predict degradation severity of images in realistic scenarios since complex, multiple, and interactive authentic distortions usually appear on them. We propose a quality prediction model based on convolutional neural network. Quality-aware features extracted from filter banks of multiple convolutional layers are aggregated into the image representation. Furthermore, an easy-to-implement and effective feature selection strategy is used to further refine the image representation and finally a linear support vector regression model is trained to map image representation into images' subjective perceptual quality scores. The experimental results on benchmark databases present the effectiveness and generalizability of the proposed model.

Global Water Cycle Agreement in the Climate Models Assessed in the IPCC AR4

NASA Technical Reports Server (NTRS)

Waliser, D.; Seo, K. -W.; Schubert, S.; Njoku, E.

2007-01-01

This study examines the fidelity of the global water cycle in the climate model simulations assessed in the IPCC Fourth Assessment Report. The results demonstrate good model agreement in quantities that have had a robust global observational basis and that are physically unambiguous. The worst agreement occurs for quantities that have both poor observational constraints and whose model representations can be physically ambiguous. In addition, components involving water vapor (frozen water) typically exhibit the best (worst) agreement, and fluxes typically exhibit better agreement than reservoirs. These results are discussed in relation to the importance of obtaining accurate model representation of the water cycle and its role in climate change. Recommendations are also given for facilitating the needed model improvements.

Prototype Vector Machine for Large Scale Semi-Supervised Learning

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

Zhang, Kai; Kwok, James T.; Parvin, Bahram

2009-04-29

Practicaldataminingrarelyfalls exactlyinto the supervisedlearning scenario. Rather, the growing amount of unlabeled data poses a big challenge to large-scale semi-supervised learning (SSL). We note that the computationalintensivenessofgraph-based SSLarises largely from the manifold or graph regularization, which in turn lead to large models that are dificult to handle. To alleviate this, we proposed the prototype vector machine (PVM), a highlyscalable,graph-based algorithm for large-scale SSL. Our key innovation is the use of"prototypes vectors" for effcient approximation on both the graph-based regularizer and model representation. The choice of prototypes are grounded upon two important criteria: they not only perform effective low-rank approximation of themore » kernel matrix, but also span a model suffering the minimum information loss compared with the complete model. We demonstrate encouraging performance and appealing scaling properties of the PVM on a number of machine learning benchmark data sets.« less

Using Grid Cells for Navigation

PubMed Central

Bush, Daniel; Barry, Caswell; Manson, Daniel; Burgess, Neil

2015-01-01

Summary Mammals are able to navigate to hidden goal locations by direct routes that may traverse previously unvisited terrain. Empirical evidence suggests that this “vector navigation” relies on an internal representation of space provided by the hippocampal formation. The periodic spatial firing patterns of grid cells in the hippocampal formation offer a compact combinatorial code for location within large-scale space. Here, we consider the computational problem of how to determine the vector between start and goal locations encoded by the firing of grid cells when this vector may be much longer than the largest grid scale. First, we present an algorithmic solution to the problem, inspired by the Fourier shift theorem. Second, we describe several potential neural network implementations of this solution that combine efficiency of search and biological plausibility. Finally, we discuss the empirical predictions of these implementations and their relationship to the anatomy and electrophysiology of the hippocampal formation. PMID:26247860

Upgrades to the NOAA/NESDIS automated Cloud-Motion Vector system

NASA Technical Reports Server (NTRS)

Nieman, Steve; Menzel, W. Paul; Hayden, Christopher M.; Wanzong, Steve; Velden, Christopher S.

1993-01-01

The latest version of the automated cloud motion vector software has yielded significant improvements in the quality of the GOES cloud-drift winds produced operationally by NESDIS. Cloud motion vectors resulting from the automated system are now equal or superior in quality to those which had the benefit of manual quality control a few years ago. The single most important factor in this improvement has been the upgraded auto-editor. Improved tracer selection procedures eliminate targets in difficult regions and allow a higher target density and therefore enhanced coverage in areas of interest. The incorporation of the H2O-intercept height assignment method allows an adequate representation of the heights of semi-transparent clouds in the absence of a CO2-absorption channel. Finally, GOES-8 water-vapor motion winds resulting from the automated system are superior to any done previously by NESDIS and should now be considered as an operational product.

Matrix-vector multiplication using digital partitioning for more accurate optical computing

NASA Technical Reports Server (NTRS)

Gary, C. K.

1992-01-01

Digital partitioning offers a flexible means of increasing the accuracy of an optical matrix-vector processor. This algorithm can be implemented with the same architecture required for a purely analog processor, which gives optical matrix-vector processors the ability to perform high-accuracy calculations at speeds comparable with or greater than electronic computers as well as the ability to perform analog operations at a much greater speed. Digital partitioning is compared with digital multiplication by analog convolution, residue number systems, and redundant number representation in terms of the size and the speed required for an equivalent throughput as well as in terms of the hardware requirements. Digital partitioning and digital multiplication by analog convolution are found to be the most efficient alogrithms if coding time and hardware are considered, and the architecture for digital partitioning permits the use of analog computations to provide the greatest throughput for a single processor.

Vectorized Rebinning Algorithm for Fast Data Down-Sampling

NASA Technical Reports Server (NTRS)

Dean, Bruce; Aronstein, David; Smith, Jeffrey

2013-01-01

A vectorized rebinning (down-sampling) algorithm, applicable to N-dimensional data sets, has been developed that offers a significant reduction in computer run time when compared to conventional rebinning algorithms. For clarity, a two-dimensional version of the algorithm is discussed to illustrate some specific details of the algorithm content, and using the language of image processing, 2D data will be referred to as "images," and each value in an image as a "pixel." The new approach is fully vectorized, i.e., the down-sampling procedure is done as a single step over all image rows, and then as a single step over all image columns. Data rebinning (or down-sampling) is a procedure that uses a discretely sampled N-dimensional data set to create a representation of the same data, but with fewer discrete samples. Such data down-sampling is fundamental to digital signal processing, e.g., for data compression applications.

Impact of climate variability on vector-borne disease transmission

USDA-ARS?s Scientific Manuscript database

We will discuss the impact of climate variability on vector borne diseases and demonstrate that global climate teleconnections can be used to anticipate and forecast, in the case of Rift Valley fever, epidemics and epizootics. In this context we will examine significant worldwide weather anomalies t...

Laboratory Evaluation of a Novel Lethal Ovitrap for Control of Aedes aegypti

USDA-ARS?s Scientific Manuscript database

Aedes aegypti and Aedes albopictus are known to flourish in a variety of natural and residential habitats and are competent vectors of at least 22 different arboviruses including dengue, chikungunya, and zika. Their global distribution, anthropophilic nature, and vector competency make them species ...

Response to Blood Meal in the Fat Body of Anopheles stephensi Using Quantitative Proteomics: Toward New Vector Control Strategies Against Malaria.

PubMed

Kumar, Manish; Mohanty, Ajeet Kumar; Sreenivasamurthy, Sreelakshmi K; Dey, Gourav; Advani, Jayshree; Pinto, Sneha M; Kumar, Ashwani; Prasad, Thottethodi Subrahmanya Keshava

2017-09-01

Malaria remains a grand challenge for disruptive innovation in global health therapeutics and diagnostics. Anopheles stephensi is one of the major vectors of malaria in Asia. Vector and transmission control are key focus areas in the fight against malaria, a field of postgenomics research where proteomics can play a substantive role. Moreover, to identify novel strategies to control the vector population, it is necessary to understand the vector life processes at a global and molecular scale. In this context, fat body is a vital organ required for vitellogenesis, vector immunity, vector physiology, and vector-parasite interaction. Given its central role in energy metabolism, vitellogenesis, and immune function, the proteome profile of the fat body and the impact of blood meal (BM) ingestion on the protein abundances of this vital organ have not been investigated so far. Therefore, using a proteomics approach, we identified the proteins expressed in the fat body of An. stephensi and their differential expression in response to BM ingestion. In all, we identified 3,218 proteins in the fat body using high-resolution mass spectrometry, of which 483 were found to be differentially expressed in response to the BM ingestion. Bioinformatics analysis of these proteins underscored their role in amino acid metabolism, vitellogenesis, lipid transport, signal peptide processing, mosquito immunity, and oxidation-reduction processes. Interestingly, we identified five novel genes, which were found to be differentially expressed upon BM ingestion. Proteins that exhibited altered expression in the present study are potential targets for vector control strategies and development of transmission blocking vaccines in the fight against malaria.

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

Tang, Kunkun, E-mail: ktg@illinois.edu; Inria Bordeaux – Sud-Ouest, Team Cardamom, 200 avenue de la Vieille Tour, 33405 Talence; Congedo, Pietro M.

The Polynomial Dimensional Decomposition (PDD) is employed in this work for the global sensitivity analysis and uncertainty quantification (UQ) of stochastic systems subject to a moderate to large number of input random variables. Due to the intimate connection between the PDD and the Analysis of Variance (ANOVA) approaches, PDD is able to provide a simpler and more direct evaluation of the Sobol' sensitivity indices, when compared to the Polynomial Chaos expansion (PC). Unfortunately, the number of PDD terms grows exponentially with respect to the size of the input random vector, which makes the computational cost of standard methods unaffordable formore » real engineering applications. In order to address the problem of the curse of dimensionality, this work proposes essentially variance-based adaptive strategies aiming to build a cheap meta-model (i.e. surrogate model) by employing the sparse PDD approach with its coefficients computed by regression. Three levels of adaptivity are carried out in this paper: 1) the truncated dimensionality for ANOVA component functions, 2) the active dimension technique especially for second- and higher-order parameter interactions, and 3) the stepwise regression approach designed to retain only the most influential polynomials in the PDD expansion. During this adaptive procedure featuring stepwise regressions, the surrogate model representation keeps containing few terms, so that the cost to resolve repeatedly the linear systems of the least-squares regression problem is negligible. The size of the finally obtained sparse PDD representation is much smaller than the one of the full expansion, since only significant terms are eventually retained. Consequently, a much smaller number of calls to the deterministic model is required to compute the final PDD coefficients.« less

Climate Change and Vector Borne Diseases on NASA Langley Research Center

NASA Technical Reports Server (NTRS)

Cole, Stuart K.; DeYoung, Russell J.; Shepanek, Marc A.; Kamel, Ahmed

2014-01-01

Increasing global temperature, weather patterns with above average storm intensities, and higher sea levels have been identified as phenomena associated with global climate change. As a causal system, climate change could contribute to vector borne diseases in humans. Vectors of concern originate from the vicinity of Langley Research Center include mosquitos and ticks that transmit disease that originate regionally, nationwide, or from outside the US. Recognizing changing conditions, vector borne diseases propagate under climate change conditions, and understanding the conditions in which they may exist or propagate, presents opportunities for monitoring their progress and mitigating their potential impacts through communication, continued monitoring, and adaptation. Personnel comprise a direct and fundamental support to NASA mission success, continuous and improved understanding of climatic conditions, and the resulting consequence of disease from these conditions, helps to reduce risk in terrestrial space technologies, ground operations, and space research. This research addresses conditions which are attributed to climatic conditions which promote environmental conditions conducive to the increase of disease vectors. This investigation includes evaluation of local mosquito population count and rainfall data for statistical correlation and identification of planning recommendations unique to LaRC, other NASA Centers to assess adaptation approaches, Center-level planning strategies.

Characterization and Detection of Vector-borne Diseases in Endemic Transmission Areas

DTIC Science & Technology

2016-01-18

research in her laboratory and for introducing me to her many collaborators and friends all over the world. Thanks to all present and former members of...Luckhart at the University of California Davis for feedback on my dissertation research and manuscripts. Second, I would like to thank Dr. Jon...and mortality due to vector-borne diseases globally. The research described in this dissertation aims to improve detection methods for both the vector

Vector control for malaria and other mosquito-borne diseases. Report of a WHO study group.

PubMed

1995-01-01

Since the Ministerial Conference on Malaria in 1992, which acknowledged the urgent need for worldwide commitment to malaria control, efforts have been directed to implementation of a Global Malaria Control Strategy. Vector control, an essential component of malaria control, has become less effective in recent years, partly as a result of poor use of alternative control tools, inappropriate use of insecticides, lack of an epidemiological basis for interventions, inadequate resources and infrastructure, and weak management. Changing environmental conditions, the behavioural characteristics of certain vectors, and resistance to insecticides have added to the difficulties. This report of a WHO Study Group provides guidelines for the planning, implementation and evaluation of cost-effective and sustainable vector control in the context of the Global Malaria Control Strategy. It reviews the available methods - indoor residual spraying, personal protection, larval control and environmental management - stressing the need for selective and flexible use of interventions according to local conditions. Requirements for data collection and the appropriate use of entomological parameters and techniques are discussed and priorities identified for the development of local capacity for vector control and for operational research. Emphasis is placed both on the monitoring and evaluation of vector control to ensure cost-effectiveness and on the development of strong managerial structures, which can support community participation and intersectoral collaboration and accommodate the control of other vector-borne diseases. The report concludes with recommendations aimed at promoting the targeted and efficient use of vector control in preventing and controlling malaria, thereby reducing the threat to health and socioeconomic development in many tropical countries.

Global Transcriptome Analysis of Aedes aegypti Mosquitoes in Response to Zika Virus Infection.

PubMed

Etebari, Kayvan; Hegde, Shivanand; Saldaña, Miguel A; Widen, Steven G; Wood, Thomas G; Asgari, Sassan; Hughes, Grant L

2017-01-01

Zika virus (ZIKV) of the Flaviviridae family is a recently emerged mosquito-borne virus that has been implicated in the surge of the number of microcephaly instances in South America. The recent rapid spread of the virus led to its declaration as a global health emergency by the World Health Organization. The virus is transmitted mainly by the mosquito Aedes aegypti , which is also the vector of dengue virus; however, little is known about the interactions of the virus with the mosquito vector. In this study, we investigated the transcriptome profiles of whole A. aegypti mosquitoes in response to ZIKV infection at 2, 7, and 14 days postinfection using transcriptome sequencing. Results showed changes in the abundance of a large number of transcripts at each time point following infection, with 18 transcripts commonly changed among the three time points. Gene ontology analysis revealed that most of the altered genes are involved in metabolic processes, cellular processes, and proteolysis. In addition, 486 long intergenic noncoding RNAs that were altered upon ZIKV infection were identified. Further, we found changes of a number of potential mRNA target genes correlating with those of altered host microRNAs. The outcomes provide a basic understanding of A. aegypti responses to ZIKV and help to determine host factors involved in replication or mosquito host antiviral response against the virus. IMPORTANCE Vector-borne viruses pose great risks to human health. Zika virus has recently emerged as a global threat, rapidly expanding its distribution. Understanding the interactions of the virus with mosquito vectors at the molecular level is vital for devising new approaches in inhibiting virus transmission. In this study, we embarked on analyzing the transcriptional response of Aedes aegypti mosquitoes to Zika virus infection. Results showed large changes in both coding and long noncoding RNAs. Analysis of these genes showed similarities with other flaviviruses, including dengue virus, which is transmitted by the same mosquito vector. The outcomes provide a global picture of changes in the mosquito vector in response to Zika virus infection.

Global Transcriptome Analysis of Aedes aegypti Mosquitoes in Response to Zika Virus Infection

PubMed Central

Etebari, Kayvan; Hegde, Shivanand; Saldaña, Miguel A.; Widen, Steven G.; Wood, Thomas G.

2017-01-01

ABSTRACT Zika virus (ZIKV) of the Flaviviridae family is a recently emerged mosquito-borne virus that has been implicated in the surge of the number of microcephaly instances in South America. The recent rapid spread of the virus led to its declaration as a global health emergency by the World Health Organization. The virus is transmitted mainly by the mosquito Aedes aegypti, which is also the vector of dengue virus; however, little is known about the interactions of the virus with the mosquito vector. In this study, we investigated the transcriptome profiles of whole A. aegypti mosquitoes in response to ZIKV infection at 2, 7, and 14 days postinfection using transcriptome sequencing. Results showed changes in the abundance of a large number of transcripts at each time point following infection, with 18 transcripts commonly changed among the three time points. Gene ontology analysis revealed that most of the altered genes are involved in metabolic processes, cellular processes, and proteolysis. In addition, 486 long intergenic noncoding RNAs that were altered upon ZIKV infection were identified. Further, we found changes of a number of potential mRNA target genes correlating with those of altered host microRNAs. The outcomes provide a basic understanding of A. aegypti responses to ZIKV and help to determine host factors involved in replication or mosquito host antiviral response against the virus. IMPORTANCE Vector-borne viruses pose great risks to human health. Zika virus has recently emerged as a global threat, rapidly expanding its distribution. Understanding the interactions of the virus with mosquito vectors at the molecular level is vital for devising new approaches in inhibiting virus transmission. In this study, we embarked on analyzing the transcriptional response of Aedes aegypti mosquitoes to Zika virus infection. Results showed large changes in both coding and long noncoding RNAs. Analysis of these genes showed similarities with other flaviviruses, including dengue virus, which is transmitted by the same mosquito vector. The outcomes provide a global picture of changes in the mosquito vector in response to Zika virus infection. PMID:29202041

Fixed weight Hopfield Neural Network based on optical implementation of all-optical MZI-XNOR logic gate

NASA Astrophysics Data System (ADS)

Nugamesh Mutter, Kussay; Mat Jafri, Mohd Zubir; Abdul Aziz, Azlan

2010-05-01

Many researches are conducted to improve Hopfield Neural Network (HNN) performance especially for speed and memory capacity in different approaches. However, there is still a significant scope of developing HNN using Optical Logic Gates. We propose here a new model of HNN based on all-optical XNOR logic gates for real time color image recognition. Firstly, we improved HNN toward optimum learning and converging operations. We considered each unipolar image as a set of small blocks of 3-pixels as vectors for HNN. This enables to save large number of images in the net with best reaching into global minima, and because there are only eight fixed states of weights so that only single iteration performed to construct a vector with stable state at minimum energy. HNN is useless in dealing with data not in bipolar representation. Therefore, HNN failed to work with color images. In RGB bands each represents different values of brightness, for d-bit RGB image it is simply consists of d-layers of unipolar. Each layer is as a single unipolar image for HNN. In addition, the weight matrices with stability of unity at the diagonal perform clear converging in comparison with no self-connecting architecture. Synchronously, each matrix-matrix multiplication operation would run optically in the second part, since we propose an array of all-optical XOR gates, which uses Mach-Zehnder Interferometer (MZI) for neurons setup and a controlling system to distribute timely signals with inverting to achieve XNOR function. The primary operation and simulation of the proposal HNN is demonstrated.

Multiplicative Versus Additive Filtering for Spacecraft Attitude Determination

NASA Technical Reports Server (NTRS)

Markley, F. Landis

2003-01-01

The absence of a globally nonsingular three-parameter representation of rotations forces attitude Kalman filters to estimate either a singular or a redundant attitude representation. We compare two filtering strategies using simplified kinematics and measurement models. Our favored strategy estimates a three-parameter representation of attitude deviations from a reference attitude specified by a higher- dimensional nonsingular parameterization. The deviations from the reference are assumed to be small enough to avoid any singularity or discontinuity of the three-dimensional parameterization. We point out some disadvantages of the other strategy, which directly estimates the four-parameter quaternion representation.

Global climate change and its potential impact on disease transmission by salinity-tolerant mosquito vectors in coastal zones.

PubMed

Ramasamy, Ranjan; Surendran, Sinnathamby Noble

2012-01-01

Global climate change can potentially increase the transmission of mosquito vector-borne diseases such as malaria, lymphatic filariasis, and dengue in many parts of the world. These predictions are based on the effects of changing temperature, rainfall, and humidity on mosquito breeding and survival, the more rapid development of ingested pathogens in mosquitoes and the more frequent blood feeds at moderately higher ambient temperatures. An expansion of saline and brackish water bodies (water with <0.5 ppt or parts per thousand, 0.5-30 ppt and >30 ppt salt are termed fresh, brackish, and saline respectively) will also take place as a result of global warming causing a rise in sea levels in coastal zones. Its possible impact on the transmission of mosquito-borne diseases has, however, not been adequately appreciated. The relevant impacts of global climate change on the transmission of mosquito-borne diseases in coastal zones are discussed with reference to the Ross-McDonald equation and modeling studies. Evidence is presented to show that an expansion of brackish water bodies in coastal zones can increase the densities of salinity-tolerant mosquitoes like Anopheles sundaicus and Culex sitiens, and lead to the adaptation of fresh water mosquito vectors like Anopheles culicifacies, Anopheles stephensi, Aedes aegypti, and Aedes albopictus to salinity. Rising sea levels may therefore act synergistically with global climate change to increase the transmission of mosquito-borne diseases in coastal zones. Greater attention therefore needs to be devoted to monitoring disease incidence and preimaginal development of vector mosquitoes in artificial and natural coastal brackish/saline habitats. It is important that national and international health agencies are aware of the increased risk of mosquito-borne diseases in coastal zones and develop preventive and mitigating strategies. Application of appropriate counter measures can greatly reduce the potential for increased coastal transmission of mosquito-borne diseases consequent to climate change and a rise in sea levels. It is proposed that the Jaffna peninsula in Sri Lanka may be a useful case study for the impact of rising sea levels on mosquito vectors in tropical coasts.

Global Climate Change and Its Potential Impact on Disease Transmission by Salinity-Tolerant Mosquito Vectors in Coastal Zones

PubMed Central

Ramasamy, Ranjan; Surendran, Sinnathamby Noble

2012-01-01

Global climate change can potentially increase the transmission of mosquito vector-borne diseases such as malaria, lymphatic filariasis, and dengue in many parts of the world. These predictions are based on the effects of changing temperature, rainfall, and humidity on mosquito breeding and survival, the more rapid development of ingested pathogens in mosquitoes and the more frequent blood feeds at moderately higher ambient temperatures. An expansion of saline and brackish water bodies (water with <0.5 ppt or parts per thousand, 0.5–30 ppt and >30 ppt salt are termed fresh, brackish, and saline respectively) will also take place as a result of global warming causing a rise in sea levels in coastal zones. Its possible impact on the transmission of mosquito-borne diseases has, however, not been adequately appreciated. The relevant impacts of global climate change on the transmission of mosquito-borne diseases in coastal zones are discussed with reference to the Ross–McDonald equation and modeling studies. Evidence is presented to show that an expansion of brackish water bodies in coastal zones can increase the densities of salinity-tolerant mosquitoes like Anopheles sundaicus and Culex sitiens, and lead to the adaptation of fresh water mosquito vectors like Anopheles culicifacies, Anopheles stephensi, Aedes aegypti, and Aedes albopictus to salinity. Rising sea levels may therefore act synergistically with global climate change to increase the transmission of mosquito-borne diseases in coastal zones. Greater attention therefore needs to be devoted to monitoring disease incidence and preimaginal development of vector mosquitoes in artificial and natural coastal brackish/saline habitats. It is important that national and international health agencies are aware of the increased risk of mosquito-borne diseases in coastal zones and develop preventive and mitigating strategies. Application of appropriate counter measures can greatly reduce the potential for increased coastal transmission of mosquito-borne diseases consequent to climate change and a rise in sea levels. It is proposed that the Jaffna peninsula in Sri Lanka may be a useful case study for the impact of rising sea levels on mosquito vectors in tropical coasts. PMID:22723781

A stochastic global identification framework for aerospace structures operating under varying flight states

NASA Astrophysics Data System (ADS)

Kopsaftopoulos, Fotis; Nardari, Raphael; Li, Yu-Hung; Chang, Fu-Kuo

2018-01-01

In this work, a novel data-based stochastic "global" identification framework is introduced for aerospace structures operating under varying flight states and uncertainty. In this context, the term "global" refers to the identification of a model that is capable of representing the structure under any admissible flight state based on data recorded from a sample of these states. The proposed framework is based on stochastic time-series models for representing the structural dynamics and aeroelastic response under multiple flight states, with each state characterized by several variables, such as the airspeed, angle of attack, altitude and temperature, forming a flight state vector. The method's cornerstone lies in the new class of Vector-dependent Functionally Pooled (VFP) models which allow the explicit analytical inclusion of the flight state vector into the model parameters and, hence, system dynamics. This is achieved via the use of functional data pooling techniques for optimally treating - as a single entity - the data records corresponding to the various flight states. In this proof-of-concept study the flight state vector is defined by two variables, namely the airspeed and angle of attack of the vehicle. The experimental evaluation and assessment is based on a prototype bio-inspired self-sensing composite wing that is subjected to a series of wind tunnel experiments under multiple flight states. Distributed micro-sensors in the form of stretchable sensor networks are embedded in the composite layup of the wing in order to provide the sensing capabilities. Experimental data collected from piezoelectric sensors are employed for the identification of a stochastic global VFP model via appropriate parameter estimation and model structure selection methods. The estimated VFP model parameters constitute two-dimensional functions of the flight state vector defined by the airspeed and angle of attack. The identified model is able to successfully represent the wing's aeroelastic response under the admissible flight states via a minimum number of estimated parameters compared to standard identification approaches. The obtained results demonstrate the high accuracy and effectiveness of the proposed global identification framework, thus constituting a first step towards the next generation of "fly-by-feel" aerospace vehicles with state awareness capabilities.

Aerosol effects on cloud water amounts were successfully simulated by a global cloud-system resolving model.

PubMed

Sato, Yousuke; Goto, Daisuke; Michibata, Takuro; Suzuki, Kentaroh; Takemura, Toshihiko; Tomita, Hirofumi; Nakajima, Teruyuki

2018-03-07

Aerosols affect climate by modifying cloud properties through their role as cloud condensation nuclei or ice nuclei, called aerosol-cloud interactions. In most global climate models (GCMs), the aerosol-cloud interactions are represented by empirical parameterisations, in which the mass of cloud liquid water (LWP) is assumed to increase monotonically with increasing aerosol loading. Recent satellite observations, however, have yielded contradictory results: LWP can decrease with increasing aerosol loading. This difference implies that GCMs overestimate the aerosol effect, but the reasons for the difference are not obvious. Here, we reproduce satellite-observed LWP responses using a global simulation with explicit representations of cloud microphysics, instead of the parameterisations. Our analyses reveal that the decrease in LWP originates from the response of evaporation and condensation processes to aerosol perturbations, which are not represented in GCMs. The explicit representation of cloud microphysics in global scale modelling reduces the uncertainty of climate prediction.

Collaborative Project: Improving the Representation of Coastal and Estuarine Processes in Earth System Models

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

Bryan, Frank; Dennis, John; MacCready, Parker

This project aimed to improve long term global climate simulations by resolving and enhancing the representation of the processes involved in the cycling of freshwater through estuaries and coastal regions. This was a collaborative multi-institution project consisting of physical oceanographers, climate model developers, and computational scientists. It specifically targeted the DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation.

Final Report Collaborative Project: Improving the Representation of Coastal and Estuarine Processes in Earth System Models

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

Bryan, Frank; Dennis, John; MacCready, Parker

This project aimed to improve long term global climate simulations by resolving and enhancing the representation of the processes involved in the cycling of freshwater through estuaries and coastal regions. This was a collaborative multi-institution project consisting of physical oceanographers, climate model developers, and computational scientists. It specifically targeted the DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation.

Object representations in visual memory: evidence from visual illusions.

PubMed

Ben-Shalom, Asaf; Ganel, Tzvi

2012-07-26

Human visual memory is considered to contain different levels of object representations. Representations in visual working memory (VWM) are thought to contain relatively elaborated information about object structure. Conversely, representations in iconic memory are thought to be more perceptual in nature. In four experiments, we tested the effects of two different categories of visual illusions on representations in VWM and in iconic memory. Unlike VWM that was affected by both types of illusions, iconic memory was immune to the effects of within-object contextual illusions and was affected only by illusions driven by between-objects contextual properties. These results show that iconic and visual working memory contain dissociable representations of object shape. These findings suggest that the global properties of the visual scene are processed prior to the processing of specific elements.

Fusion of Positive Energy Representations of LSpin(2n)

NASA Astrophysics Data System (ADS)

Toledano-Laredo, V.

2004-09-01

Building upon the Jones-Wassermann program of studying Conformal Field Theory using operator algebraic tools, and the work of A. Wassermann on the loop group of LSU(n) (Invent. Math. 133 (1998), 467-538), we give a solution to the problem of fusion for the loop group of Spin(2n). Our approach relies on the use of A. Connes' tensor product of bimodules over a von Neumann algebra to define a multiplicative operation (Connes fusion) on the (integrable) positive energy representations of a given level. The notion of bimodules arises by restricting these representations to loops with support contained in an interval I of the circle or its complement. We study the corresponding Grothendieck ring and show that fusion with the vector representation is given by the Verlinde rules. The computation rests on 1) the solution of a 6-parameter family of Knizhnik-Zamolodchikhov equations and the determination of its monodromy, 2) the explicit construction of the primary fields of the theory, which allows to prove that they define operator-valued distributions and 3) the algebraic theory of superselection sectors developed by Doplicher-Haag-Roberts.

Investigation of Time Series Representations and Similarity Measures for Structural Damage Pattern Recognition

PubMed Central

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

Using graph approach for managing connectivity in integrative landscape modelling

NASA Astrophysics Data System (ADS)

Rabotin, Michael; Fabre, Jean-Christophe; Libres, Aline; Lagacherie, Philippe; Crevoisier, David; Moussa, Roger

2013-04-01

In cultivated landscapes, a lot of landscape elements such as field boundaries, ditches or banks strongly impact water flows, mass and energy fluxes. At the watershed scale, these impacts are strongly conditionned by the connectivity of these landscape elements. An accurate representation of these elements and of their complex spatial arrangements is therefore of great importance for modelling and predicting these impacts.We developped in the framework of the OpenFLUID platform (Software Environment for Modelling Fluxes in Landscapes) a digital landscape representation that takes into account the spatial variabilities and connectivities of diverse landscape elements through the application of the graph theory concepts. The proposed landscape representation consider spatial units connected together to represent the flux exchanges or any other information exchanges. Each spatial unit of the landscape is represented as a node of a graph and relations between units as graph connections. The connections are of two types - parent-child connection and up/downstream connection - which allows OpenFLUID to handle hierarchical graphs. Connections can also carry informations and graph evolution during simulation is possible (connections or elements modifications). This graph approach allows a better genericity on landscape representation, a management of complex connections and facilitate development of new landscape representation algorithms. Graph management is fully operational in OpenFLUID for developers or modelers ; and several graph tools are available such as graph traversal algorithms or graph displays. Graph representation can be managed i) manually by the user (for example in simple catchments) through XML-based files in easily editable and readable format or ii) by using methods of the OpenFLUID-landr library which is an OpenFLUID library relying on common open-source spatial libraries (ogr vector, geos topologic vector and gdal raster libraries). OpenFLUID-landr library has been developed in order i) to be used with no GIS expert skills needed (common gis formats can be read and simplified spatial management is provided), ii) to easily develop adapted rules of landscape discretization and graph creation to follow spatialized model requirements and iii) to allow model developers to manage dynamic and complex spatial topology. Graph management in OpenFLUID are shown with i) examples of hydrological modelizations on complex farmed landscapes and ii) the new implementation of Geo-MHYDAS tool based on the OpenFLUID-landr library, which allows to discretize a landscape and create graph structure for the MHYDAS model requirements.

Imagining Cosmopolitan Space: Spectacle, Rice and Global Citizenship

ERIC Educational Resources Information Center

Parry, Simon

2010-01-01

How do you stage the world? This article reviews how a series of performance installations by the theatre company Stan's Cafe have approached global space. It examines the way "Plague Nation" and "Of All the People in All the World" tackle national and global scale through the representation of populations. Drawing on a…

What Global Perspective Does Our University Foster in Our Students?

ERIC Educational Resources Information Center

Shephard, Kerry; Bourk, Michael; Mirosa, Miranda; Dulgar, Pete

2017-01-01

We used a modified circuit of culture enquiry to explore processes of production, representation and consumption of global perspective at our university, in the context of fostering this perspective as a graduate attribute. We identified four frame packages by which this perspective is understood and communicated. Global perspective is framed…

Central Nervous System Delivery of Helper-Dependent Canine Adenovirus Corrects Neuropathology and Behavior in Mucopolysaccharidosis Type VII Mice

PubMed Central

Ariza, Lorena; Giménez-Llort, Lydia; Cubizolle, Aurélie; Pagès, Gemma; García-Lareu, Belén; Serratrice, Nicolas; Cots, Dan; Thwaite, Rosemary; Chillón, Miguel; Kremer, Eric J.

2014-01-01

Abstract Canine adenovirus type 2 vectors (CAV-2) are promising tools to treat global central nervous system (CNS) disorders because of their preferential transduction of neurons and efficient retrograde axonal transport. Here we tested the potential of a helper-dependent CAV-2 vector expressing β-glucuronidase (HD-RIGIE) in a mouse model of mucopolysaccharidosis type VII (MPS VII), a lysosomal storage disease caused by deficiency in β-glucuronidase activity. MPS VII leads to glycosaminoglycan accumulation into enlarged vesicles in peripheral tissues and the CNS, resulting in peripheral and neuronal dysfunction. After intracranial administration of HD-RIGIE, we show long-term expression of β-glucuronidase that led to correction of neuropathology around the injection site and in distal areas. This phenotypic correction correlated with a decrease in secondary-elevated lysosomal enzyme activity and glycosaminoglycan levels, consistent with global biochemical correction. Moreover, HD-RIGIE-treated mice show significant cognitive improvement. Thus, injections of HD-CAV-2 vectors in the brain allow a global and sustained expression and may have implications for brain therapy in patients with lysosomal storage disease. PMID:24299455

Singularity-free extraction of a quaternion from a direction-cosine matrix. [for spacecraft control and guidance

NASA Technical Reports Server (NTRS)

Klumpp, A. R.

1976-01-01

A computer algorithm for extracting a quaternion from a direction-cosine matrix (DCM) is described. The quaternion provides a four-parameter representation of rotation, as against the nine-parameter representation afforded by a DCM. Commanded attitude in space shuttle steering is conveniently computed by DCM, while actual attitude is computed most compactly as a quaternion, as is attitude error. The unit length of the rotation quaternion, and interchangeable of a quaternion and its negative, are used to advantage in the extraction algorithm. Protection of the algorithm against square root failure and division overflow are considered. Necessary and sufficient conditions for handling the rotation vector element of largest magnitude are discussed

ROPE: Recoverable Order-Preserving Embedding of Natural Language

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

Widemann, David P.; Wang, Eric X.; Thiagarajan, Jayaraman J.

We present a novel Recoverable Order-Preserving Embedding (ROPE) of natural language. ROPE maps natural language passages from sparse concatenated one-hot representations to distributed vector representations of predetermined fixed length. We use Euclidean distance to return search results that are both grammatically and semantically similar. ROPE is based on a series of random projections of distributed word embeddings. We show that our technique typically forms a dictionary with sufficient incoherence such that sparse recovery of the original text is possible. We then show how our embedding allows for efficient and meaningful natural search and retrieval on Microsoft’s COCO dataset and themore » IMDB Movie Review dataset.« less

On Fock-space representations of quantized enveloping algebras related to noncommutative differential geometry

NASA Astrophysics Data System (ADS)

Jurčo, B.; Schlieker, M.

1995-07-01

In this paper explicitly natural (from the geometrical point of view) Fock-space representations (contragradient Verma modules) of the quantized enveloping algebras are constructed. In order to do so, one starts from the Gauss decomposition of the quantum group and introduces the differential operators on the corresponding q-deformed flag manifold (assumed as a left comodule for the quantum group) by a projection to it of the right action of the quantized enveloping algebra on the quantum group. Finally, the representatives of the elements of the quantized enveloping algebra corresponding to the left-invariant vector fields on the quantum group are expressed as first-order differential operators on the q-deformed flag manifold.

Using the Relevance Vector Machine Model Combined with Local Phase Quantization to Predict Protein-Protein Interactions from Protein Sequences.

PubMed

An, Ji-Yong; Meng, Fan-Rong; You, Zhu-Hong; Fang, Yu-Hong; Zhao, Yu-Jun; Zhang, Ming

2016-01-01

We propose a novel computational method known as RVM-LPQ that combines the Relevance Vector Machine (RVM) model and Local Phase Quantization (LPQ) to predict PPIs from protein sequences. The main improvements are the results of representing protein sequences using the LPQ feature representation on a Position Specific Scoring Matrix (PSSM), reducing the influence of noise using a Principal Component Analysis (PCA), and using a Relevance Vector Machine (RVM) based classifier. We perform 5-fold cross-validation experiments on Yeast and Human datasets, and we achieve very high accuracies of 92.65% and 97.62%, respectively, which is significantly better than previous works. To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM) classifier on the Yeast dataset. The experimental results demonstrate that our RVM-LPQ method is obviously better than the SVM-based method. The promising experimental results show the efficiency and simplicity of the proposed method, which can be an automatic decision support tool for future proteomics research.

Analyzing neural responses with vector fields.

PubMed

Buneo, Christopher A

2011-04-15

Analyzing changes in the shape and scale of single cell response fields is a key component of many neurophysiological studies. Typical analyses of shape change involve correlating firing rates between experimental conditions or "cross-correlating" single cell tuning curves by shifting them with respect to one another and correlating the overlapping data. Such shifting results in a loss of data, making interpretation of the resulting correlation coefficients problematic. The problem is particularly acute for two dimensional response fields, which require shifting along two axes. Here, an alternative method for quantifying response field shape and scale based on correlation of vector field representations is introduced. The merits and limitations of the methods are illustrated using both simulated and experimental data. It is shown that vector correlation provides more information on response field changes than scalar correlation without requiring field shifting and concomitant data loss. An extension of this vector field approach is also demonstrated which can be used to identify the manner in which experimental variables are encoded in studies of neural reference frames. Copyright © 2011 Elsevier B.V. All rights reserved.

Geostrophic balance with a full Coriolis Force: implications for low latitutde studies

NASA Technical Reports Server (NTRS)

Juarez, M. de la Torre

2002-01-01

In its standard form, geostrophic balance uses a partial representation of the Coriolis force. The resulting formation has a singularity at the equator, and violates mass and momentum conservation. When the horizontal projection of the planetary rotation vector is considered, the singularity at the equator disappears, continuity can be preserved, and quasigeostrophy can be formulated at planetary scale.

Uncertainty Representation and Interpretation in Model-based Prognostics Algorithms based on Kalman Filter Estimation

DTIC Science & Technology

2012-09-01

interpreting the state vector as the health indicator and a threshold is used on this variable in order to compute EOL (end-of-life) and RUL. Here, we...End-of-life ( EOL ) would match the true spread and would not change from one experiment to another. This is, however, in practice impossible to achieve

Real weights, bound states and duality orbits

NASA Astrophysics Data System (ADS)

Marrani, Alessio; Riccioni, Fabio; Romano, Luca

2016-01-01

We show that the duality orbits of extremal black holes in supergravity theories with symmetric scalar manifolds can be derived by studying the stabilizing subalgebras of suitable representatives, realized as bound states of specific weight vectors of the corresponding representation of the duality symmetry group. The weight vectors always correspond to weights that are real, where the reality properties are derived from the Tits-Satake diagram that identifies the real form of the Lie algebra of the duality symmetry group. Both 𝒩 = 2 magic Maxwell-Einstein supergravities and the semisimple infinite sequences of 𝒩 = 2 and 𝒩 = 4 theories in D = 4 and 5 are considered, and various results, obtained over the years in the literature using different methods, are retrieved. In particular, we show that the stratification of the orbits of these theories occurs because of very specific properties of the representations: in the case of the theory based on the real numbers, whose symmetry group is maximally noncompact and therefore all the weights are real, the stratification is due to the presence of weights of different lengths, while in the other cases it is due to the presence of complex weights.

Secure access control and large scale robust representation for online multimedia event detection.

PubMed

Liu, Changyu; Lu, Bin; Li, Huiling

2014-01-01

We developed an online multimedia event detection (MED) system. However, there are a secure access control issue and a large scale robust representation issue when we want to integrate traditional event detection algorithms into the online environment. For the first issue, we proposed a tree proxy-based and service-oriented access control (TPSAC) model based on the traditional role based access control model. Verification experiments were conducted on the CloudSim simulation platform, and the results showed that the TPSAC model is suitable for the access control of dynamic online environments. For the second issue, inspired by the object-bank scene descriptor, we proposed a 1000-object-bank (1000OBK) event descriptor. Feature vectors of the 1000OBK were extracted from response pyramids of 1000 generic object detectors which were trained on standard annotated image datasets, such as the ImageNet dataset. A spatial bag of words tiling approach was then adopted to encode these feature vectors for bridging the gap between the objects and events. Furthermore, we performed experiments in the context of event classification on the challenging TRECVID MED 2012 dataset, and the results showed that the robust 1000OBK event descriptor outperforms the state-of-the-art approaches.

Computer-Based Method for On-Line Service and Compact Storage of Data

NASA Astrophysics Data System (ADS)

Vasilyev, S. V.

New method for compressing some types of astronomical data is proposed and discussed. The method is intended to provide astronomers more convenient technique for data retrieval from observational databases. The technique is based on the principal component method (PCM) of data analysis and their representation by characteristic vectors and eigenvalues. It allows to change the variety of data records by relatively small number of parameters. The initial data can be restored simply by linear combinations of obtained characteristic vectors. This approach can essentially reduce the dimensions of data being stored in databases and transferred through a netware. Our study shows that resulting volumes of data depend on the required accuracy of the representation and can be several times less than the initial ones. We note that using this method does not prevent applying the widely-used software for further data compressing. As the PCM is able to represent data analytically it can be used for proper adaptation of the requested information to the researcher's aims. Finally, taking into account that the method itself is a powerful tool for data smoothing, modelling and comparison we find it having good prospects for use in computer databases. Some examples of the PCM applications are described.

A general representation scheme for crystalline solids based on Voronoi-tessellation real feature values and atomic property data

PubMed Central

Jalem, Randy; Nakayama, Masanobu; Noda, Yusuke; Le, Tam; Takeuchi, Ichiro; Tateyama, Yoshitaka; Yamazaki, Hisatsugu

2018-01-01

Abstract Increasing attention has been paid to materials informatics approaches that promise efficient and fast discovery and optimization of functional inorganic materials. Technical breakthrough is urgently requested to advance this field and efforts have been made in the development of materials descriptors to encode or represent characteristics of crystalline solids, such as chemical composition, crystal structure, electronic structure, etc. We propose a general representation scheme for crystalline solids that lifts restrictions on atom ordering, cell periodicity, and system cell size based on structural descriptors of directly binned Voronoi-tessellation real feature values and atomic/chemical descriptors based on the electronegativity of elements in the crystal. Comparison was made vs. radial distribution function (RDF) feature vector, in terms of predictive accuracy on density functional theory (DFT) material properties: cohesive energy (CE), density (d), electronic band gap (BG), and decomposition energy (Ed). It was confirmed that the proposed feature vector from Voronoi real value binning generally outperforms the RDF-based one for the prediction of aforementioned properties. Together with electronegativity-based features, Voronoi-tessellation features from a given crystal structure that are derived from second-nearest neighbor information contribute significantly towards prediction. PMID:29707064

A general representation scheme for crystalline solids based on Voronoi-tessellation real feature values and atomic property data.

PubMed

Jalem, Randy; Nakayama, Masanobu; Noda, Yusuke; Le, Tam; Takeuchi, Ichiro; Tateyama, Yoshitaka; Yamazaki, Hisatsugu

2018-01-01

Increasing attention has been paid to materials informatics approaches that promise efficient and fast discovery and optimization of functional inorganic materials. Technical breakthrough is urgently requested to advance this field and efforts have been made in the development of materials descriptors to encode or represent characteristics of crystalline solids, such as chemical composition, crystal structure, electronic structure, etc. We propose a general representation scheme for crystalline solids that lifts restrictions on atom ordering, cell periodicity, and system cell size based on structural descriptors of directly binned Voronoi-tessellation real feature values and atomic/chemical descriptors based on the electronegativity of elements in the crystal. Comparison was made vs. radial distribution function (RDF) feature vector, in terms of predictive accuracy on density functional theory (DFT) material properties: cohesive energy (CE), density ( d ), electronic band gap (BG), and decomposition energy (Ed). It was confirmed that the proposed feature vector from Voronoi real value binning generally outperforms the RDF-based one for the prediction of aforementioned properties. Together with electronegativity-based features, Voronoi-tessellation features from a given crystal structure that are derived from second-nearest neighbor information contribute significantly towards prediction.

A New Technique for System-to-system Transfer of Surface Data

NASA Technical Reports Server (NTRS)

Sterling, M. W.; Lucius, M. E.; Gordon, W. J.

1985-01-01

The purpose is to describe a recently developed technique aimed at providing a universal interface between surface types. In brief, a software package was developed which functions a common denominator of CAD/CAM surface types. This software enable one to convert from any given surface representation to any other target representation. The tiles maintain the same slope continuity as the target surface gram, bicubic patches are used since they allow one to match point, slope, and twist vectors to the target surface. Thus, slopes can be continuous or discontinuous as they are on the target surface. The patches can be of lower order if desired. For example, if only point information is available, the patches produced will be bilinear; however, the number of patches required is likely to increase correspondingly. The patches can be of higher order although many systems will not accept patches of more than order four. The final result of the program is a rectangular grid of bicubic patches. The patches fit the target surface exactly at their corners. Also, the patch corners have the same tangent and twist vectors. Adjacent patches will have slope continuity, unless a discontinuity was indicated by the target surface.

RNA-TVcurve: a Web server for RNA secondary structure comparison based on a multi-scale similarity of its triple vector curve representation.

PubMed

Li, Ying; Shi, Xiaohu; Liang, Yanchun; Xie, Juan; Zhang, Yu; Ma, Qin

2017-01-21

RNAs have been found to carry diverse functionalities in nature. Inferring the similarity between two given RNAs is a fundamental step to understand and interpret their functional relationship. The majority of functional RNAs show conserved secondary structures, rather than sequence conservation. Those algorithms relying on sequence-based features usually have limitations in their prediction performance. Hence, integrating RNA structure features is very critical for RNA analysis. Existing algorithms mainly fall into two categories: alignment-based and alignment-free. The alignment-free algorithms of RNA comparison usually have lower time complexity than alignment-based algorithms. An alignment-free RNA comparison algorithm was proposed, in which novel numerical representations RNA-TVcurve (triple vector curve representation) of RNA sequence and corresponding secondary structure features are provided. Then a multi-scale similarity score of two given RNAs was designed based on wavelet decomposition of their numerical representation. In support of RNA mutation and phylogenetic analysis, a web server (RNA-TVcurve) was designed based on this alignment-free RNA comparison algorithm. It provides three functional modules: 1) visualization of numerical representation of RNA secondary structure; 2) detection of single-point mutation based on secondary structure; and 3) comparison of pairwise and multiple RNA secondary structures. The inputs of the web server require RNA primary sequences, while corresponding secondary structures are optional. For the primary sequences alone, the web server can compute the secondary structures using free energy minimization algorithm in terms of RNAfold tool from Vienna RNA package. RNA-TVcurve is the first integrated web server, based on an alignment-free method, to deliver a suite of RNA analysis functions, including visualization, mutation analysis and multiple RNAs structure comparison. The comparison results with two popular RNA comparison tools, RNApdist and RNAdistance, showcased that RNA-TVcurve can efficiently capture subtle relationships among RNAs for mutation detection and non-coding RNA classification. All the relevant results were shown in an intuitive graphical manner, and can be freely downloaded from this server. RNA-TVcurve, along with test examples and detailed documents, are available at: http://ml.jlu.edu.cn/tvcurve/ .

Predication-based semantic indexing: permutations as a means to encode predications in semantic space.

PubMed

Cohen, Trevor; Schvaneveldt, Roger W; Rindflesch, Thomas C

2009-11-14

Corpus-derived distributional models of semantic distance between terms have proved useful in a number of applications. For both theoretical and practical reasons, it is desirable to extend these models to encode discrete concepts and the ways in which they are related to one another. In this paper, we present a novel vector space model that encodes semantic predications derived from MEDLINE by the SemRep system into a compact spatial representation. The associations captured by this method are of a different and complementary nature to those derived by traditional vector space models, and the encoding of predication types presents new possibilities for knowledge discovery and information retrieval.

Dissimilarity representations in lung parenchyma classification

NASA Astrophysics Data System (ADS)

Sørensen, Lauge; de Bruijne, Marleen

2009-02-01

A good problem representation is important for a pattern recognition system to be successful. The traditional approach to statistical pattern recognition is feature representation. More specifically, objects are represented by a number of features in a feature vector space, and classifiers are built in this representation. This is also the general trend in lung parenchyma classification in computed tomography (CT) images, where the features often are measures on feature histograms. Instead, we propose to build normal density based classifiers in dissimilarity representations for lung parenchyma classification. This allows for the classifiers to work on dissimilarities between objects, which might be a more natural way of representing lung parenchyma. In this context, dissimilarity is defined between CT regions of interest (ROI)s. ROIs are represented by their CT attenuation histogram and ROI dissimilarity is defined as a histogram dissimilarity measure between the attenuation histograms. In this setting, the full histograms are utilized according to the chosen histogram dissimilarity measure. We apply this idea to classification of different emphysema patterns as well as normal, healthy tissue. Two dissimilarity representation approaches as well as different histogram dissimilarity measures are considered. The approaches are evaluated on a set of 168 CT ROIs using normal density based classifiers all showing good performance. Compared to using histogram dissimilarity directly as distance in a emph{k} nearest neighbor classifier, which achieves a classification accuracy of 92.9%, the best dissimilarity representation based classifier is significantly better with a classification accuracy of 97.0% (text{emph{p" border="0" class="imgtopleft"> = 0.046).

Gravity Field Changes due to Long-Term Sea Level Changes

NASA Astrophysics Data System (ADS)

Makarynskyy, O.; Kuhn, M.; Featherstone, W. E.

2004-12-01

Long-term sea level changes caused by climatic changes (e.g. global warming) will alter the system Earth. This includes the redistribution of ocean water masses due to the migration of cold fresh water from formerly ice-covered regions to the open oceans mainly caused by the deglaciation of polar ice caps. Consequently also a change in global ocean circulation patterns will occur. Over a longer timescale, such mass redistributions will be followed by isostatic rebound/depression due to the changed surface un/loading, resulting in variable sea level change around the world. These, in turn, will affect the gravity field, location of the geocentre, and the Earth's rotation vector. This presentation focuses mainly on gravity field changes induced by long-term (hundredths to many thousand years) sea level changes using an Earth System Climate Model (ESCM) of intermediate complexity. In this study, the coupled University of Victoria (Victoria, Canada) Earth System Climate Model (Uvic ESCM) was used, which embraces the primary thermodynamic and hydrological components of the climate system including sea and land-ice information. The model was implemented to estimate changes in global precipitation, ocean mass redistribution, seawater temperature and salinity on timescales from hundreds to thousands years under different greenhouse warming scenarios. The sea level change output of the model has been converted into real mass changes by removing the steric effect, computed from seawater temperature and salinity information at different layers also provided by Uvic ESCM. Finally the obtained mass changes have been converted into changes of the gravitational potential and subsequently of the geoid height using a spherical harmonic representation of the different data. Preliminary numerical results are provided for sea level change as well as change in geoid height.

Can Chimpanzee Infants ("Pan Troglodytes") Form Categorical Representations in the Same Manner as Human Infants ("Homo Sapiens")?

ERIC Educational Resources Information Center

Murai, Chizuko; Kosugi, Daisuke; Tomonaga, Masaki; Tanaka, Masayuki; Matsuzawa, Tetsuro; Itakura, Shoji

2005-01-01

We directly compared chimpanzee infants and human infants for categorical representations of three global-like categories (mammals, furniture and vehicles), using the familiarization-novelty preference technique. Neither species received any training during the experiments. We used the time that participants spent looking at the stimulus object…

Gender Divergence in Academics' Representation and Research Productivity: A Nigerian Case Study

ERIC Educational Resources Information Center

Opesade, Adeola Omobola; Famurewa, Kofoworola Folakemi; Igwe, Ebelechukwu Gloria

2017-01-01

Gender equity is increasingly seen as an indicator of development and global acceptance in networks of higher education. Despite this, gender divergence in research productivity of academics coupled with under-representation of women in science has been reported to beset female's scholarly activities. Previous studies provide differing results,…

Cultural Representations in/as the Global Studies Curriculum: Seeing and Knowing China in the United States

ERIC Educational Resources Information Center

Mungur, Amy

2014-01-01

This study is an examination of how two popular magazines, "National Geographic" and "Life" magazine, and one educational journal, "Social Education," perform the work of representation in general, and representing China more specifically. Drawing on postcolonial theorists (Blaut, 1993; Said, 1978; Tchen, 1999; wa…

Participatory Risk Mapping of Malaria Vector Exposure in Northern South America using Environmental and Population Data

PubMed Central

Fuller, D.O.; Troyo, A.; Alimi, T.O.; Beier, J.C.

2014-01-01

Malaria elimination remains a major public health challenge in many tropical regions, including large areas of northern South America. In this study, we present a new high spatial resolution (90 × 90 m) risk map for Colombia and surrounding areas based on environmental and human population data. The map was created through a participatory multi-criteria decision analysis in which expert opinion was solicited to determine key environmental and population risk factors, different fuzzy functions to standardize risk factor inputs, and variable factor weights to combine risk factors in a geographic information system. The new risk map was compared to a map of malaria cases in which cases were aggregated to the municipio (municipality) level. The relationship between mean municipio risk scores and total cases by muncípio showed a weak correlation. However, the relationship between pixel-level risk scores and vector occurrence points for two dominant vector species, Anopheles albimanus and An. darlingi, was significantly different (p < 0.05) from a random point distribution, as was a pooled point distribution for these two vector species and An. nuneztovari. Thus, we conclude that the new risk map derived based on expert opinion provides an accurate spatial representation of risk of potential vector exposure rather than malaria transmission as shown by the pattern of malaria cases, and therefore it may be used to inform public health authorities as to where vector control measures should be prioritized to limit human-vector contact in future malaria outbreaks. PMID:24976656

Global cosmological dynamics for the scalar field representation of the modified Chaplygin gas

NASA Astrophysics Data System (ADS)

Uggla, Claes

2013-09-01

In this paper we investigate the global dynamics for the minimally coupled scalar field representation of the modified Chaplygin gas in the context of flat Friedmann-Lemaître-Robertson Walker cosmology. The tool for doing this is a new set of bounded variables that lead to a regular dynamical system. It is shown that the exact modified Chaplygin gas perfect fluid solution appears as a straight line in the associated phase plane. It is also shown that no other solutions stay close to this solution during their entire temporal evolution, but that there exists an open subset of solutions that stay arbitrarily close during an intermediate time interval, and into the future in the case when the scalar field potential exhibits a global minimum.

Tribal and Locality Dynamics in Afghanistan: A View from the National Military Academy of Afghanistan

DTIC Science & Technology

2009-01-01

CD VVV ∪= with DV countable and nCV ℜ∈ ; XInit ⊆ is a set of initial states; CXVXf →×: is a vector field, assumed to be 4 globally...DV countable and nCV ℜ∈ ; XInit ⊆ is a set of initial states; CXVXf →×: is a vector field, assumed to be globally Lipschitz in CX and...8217 ; V is a finite collection of input variables. We assume ( )CD VVV ∪= with DV countable and nCV ℜ∈ ; XInit ⊆ is a set of initial states

Predictive study on the risk of malaria spreading due to global warming

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

Ono, Masaji

Global warming will bring about a temperature elevation, and the habitat of vectors of infectious diseases, such as malaria and dengue fever, will spread into subtropical or temperate zone. The purpose of this study is to simulate the spreading of these diseases through reexamination of existing data and collection of some additional information by field survey. From these data, the author will establish the relationship between meteorological conditions, vector density and malaria occurrence. And then he will simulate and predict the malaria epidemics in case of temperature elevation in southeast Asia and Japan.

Consolidating strategic planning and operational frameworks for integrated vector management in Eritrea.

PubMed

Chanda, Emmanuel; Ameneshewa, Birkinesh; Mihreteab, Selam; Berhane, Araia; Zehaie, Assefash; Ghebrat, Yohannes; Usman, Abdulmumini

2015-12-02

Contemporary malaria vector control relies on the use of insecticide-based, indoor residual spraying (IRS) and long-lasting insecticidal nets (LLINs). However, malaria-endemic countries, including Eritrea, have struggled to effectively deploy these tools due technical and operational challenges, including the selection of insecticide resistance in malaria vectors. This manuscript outlines the processes undertaken in consolidating strategic planning and operational frameworks for vector control to expedite malaria elimination in Eritrea. The effort to strengthen strategic frameworks for vector control in Eritrea was the 'case' for this study. The integrated vector management (IVM) strategy was developed in 2010 but was not well executed, resulting in a rise in malaria transmission, prompting a process to redefine and relaunch the IVM strategy with integration of other vector borne diseases (VBDs) as the focus. The information sources for this study included all available data and accessible archived documentary records on malaria vector control in Eritrea. Structured literature searches of published, peer-reviewed sources using online, scientific, bibliographic databases, Google Scholar, PubMed and WHO, and a combination of search terms were utilized to gather data. The literature was reviewed and adapted to the local context and translated into the consolidated strategic framework. In Eritrea, communities are grappling with the challenge of VBDs posing public health concerns, including malaria. The global fund financed the scale-up of IRS and LLIN programmes in 2014. Eritrea is transitioning towards malaria elimination and strategic frameworks for vector control have been consolidated by: developing an integrated vector management (IVM) strategy (2015-2019); updating IRS and larval source management (LSM) guidelines; developing training manuals for IRS and LSM; training of national staff in malaria entomology and vector control, including insecticide resistance monitoring techniques; initiating the global plan for insecticide resistance management; conducting needs' assessments and developing standard operating procedure for insectaries; developing a guidance document on malaria vector control based on eco-epidemiological strata, a vector surveillance plan and harmonized mapping, data collection and reporting tools. Eritrea has successfully consolidated strategic frameworks for vector control. Rational decision-making remains critical to ensure that the interventions are effective and their choice is evidence-based, and to optimize the use of resources for vector control. Implementation of effective IVM requires proper collaboration and coordination, consistent technical and financial capacity and support to offer greater benefits.

HMM for hyperspectral spectrum representation and classification with endmember entropy vectors

NASA Astrophysics Data System (ADS)

Arabi, Samir Y. W.; Fernandes, David; Pizarro, Marco A.

2015-10-01

The Hyperspectral images due to its good spectral resolution are extensively used for classification, but its high number of bands requires a higher bandwidth in the transmission data, a higher data storage capability and a higher computational capability in processing systems. This work presents a new methodology for hyperspectral data classification that can work with a reduced number of spectral bands and achieve good results, comparable with processing methods that require all hyperspectral bands. The proposed method for hyperspectral spectra classification is based on the Hidden Markov Model (HMM) associated to each Endmember (EM) of a scene and the conditional probabilities of each EM belongs to each other EM. The EM conditional probability is transformed in EM vector entropy and those vectors are used as reference vectors for the classes in the scene. The conditional probability of a spectrum that will be classified is also transformed in a spectrum entropy vector, which is classified in a given class by the minimum ED (Euclidian Distance) among it and the EM entropy vectors. The methodology was tested with good results using AVIRIS spectra of a scene with 13 EM considering the full 209 bands and the reduced spectral bands of 128, 64 and 32. For the test area its show that can be used only 32 spectral bands instead of the original 209 bands, without significant loss in the classification process.

Global, long-term surface reflectance records from Landsat

USDA-ARS?s Scientific Manuscript database

Global, long-term monitoring of changes in Earth’s land surface requires quantitative comparisons of satellite images acquired under widely varying atmospheric conditions. Although physically based estimates of surface reflectance (SR) ultimately provide the most accurate representation of Earth’s s...

A Nearest Neighbor Classifier Employing Critical Boundary Vectors for Efficient On-Chip Template Reduction.

PubMed

Xia, Wenjun; Mita, Yoshio; Shibata, Tadashi

2016-05-01

Aiming at efficient data condensation and improving accuracy, this paper presents a hardware-friendly template reduction (TR) method for the nearest neighbor (NN) classifiers by introducing the concept of critical boundary vectors. A hardware system is also implemented to demonstrate the feasibility of using an field-programmable gate array (FPGA) to accelerate the proposed method. Initially, k -means centers are used as substitutes for the entire template set. Then, to enhance the classification performance, critical boundary vectors are selected by a novel learning algorithm, which is completed within a single iteration. Moreover, to remove noisy boundary vectors that can mislead the classification in a generalized manner, a global categorization scheme has been explored and applied to the algorithm. The global characterization automatically categorizes each classification problem and rapidly selects the boundary vectors according to the nature of the problem. Finally, only critical boundary vectors and k -means centers are used as the new template set for classification. Experimental results for 24 data sets show that the proposed algorithm can effectively reduce the number of template vectors for classification with a high learning speed. At the same time, it improves the accuracy by an average of 2.17% compared with the traditional NN classifiers and also shows greater accuracy than seven other TR methods. We have shown the feasibility of using a proof-of-concept FPGA system of 256 64-D vectors to accelerate the proposed method on hardware. At a 50-MHz clock frequency, the proposed system achieves a 3.86 times higher learning speed than on a 3.4-GHz PC, while consuming only 1% of the power of that used by the PC.

A nine-dimensional ab initio global potential energy surface for the H2O+ + H2 → H3O+ + H reaction

NASA Astrophysics Data System (ADS)

Li, Anyang; Guo, Hua

2014-06-01

An accurate full-dimensional global potential energy surface (PES) is developed for the title reaction. While the long-range interactions in the reactant asymptote are represented by an analytical expression, the interaction region of the PES is fit to more than 81 000 of ab initio points at the UCCSD(T)-F12b/AVTZ level using the permutation invariant polynomial neural network approach. Fully symmetric with respect to permutation of all four hydrogen atoms, the PES provides a faithful representation of the ab initio points, with a root mean square error of 1.8 meV or 15 cm-1. The reaction path for this exoergic reaction features an attractive and barrierless entrance channel, a submerged saddle point, a shallow H4O+ well, and a barrierless exit channel. The rate coefficients for the title reaction and kinetic isotope effect have been determined on this PES using quasi-classical trajectories, and they are in good agreement with available experimental data. It is further shown that the H2O+ rotational enhancement of reactivity observed experimentally can be traced to the submerged saddle point. Using our recently proposed Sudden Vector Projection model, we demonstrate that a rotational degree of freedom of the H2O+ reactant is strongly coupled with the reaction coordinate at this saddle point, thus unraveling the origin of the pronounced mode specificity in this reaction.

Detection of distorted frames in retinal video-sequences via machine learning

NASA Astrophysics Data System (ADS)

Kolar, Radim; Liberdova, Ivana; Odstrcilik, Jan; Hracho, Michal; Tornow, Ralf P.

2017-07-01

This paper describes detection of distorted frames in retinal sequences based on set of global features extracted from each frame. The feature vector is consequently used in classification step, in which three types of classifiers are tested. The best classification accuracy 96% has been achieved with support vector machine approach.

Overview of current situation of dengue and dengue vector control

USDA-ARS?s Scientific Manuscript database

Dengue is the most important arbovirus of humans in the world. It is caused by one of four closely related virus serotypes whose primary vector is Aedes aegypti and secondarily by Ae. albopictus. A global dengue pandemic began in Southeast Asia after World War II and has intensified during the las...

Subject-based discriminative sparse representation model for detection of concealed information.

PubMed

Akhavan, Amir; Moradi, Mohammad Hassan; Vand, Safa Rafiei

2017-05-01

The use of machine learning approaches in concealed information test (CIT) plays a key role in the progress of this neurophysiological field. In this paper, we presented a new machine learning method for CIT in which each subject is considered independent of the others. The main goal of this study is to adapt the discriminative sparse models to be applicable for subject-based concealed information test. In order to provide sufficient discriminability between guilty and innocent subjects, we introduced a novel discriminative sparse representation model and its appropriate learning methods. For evaluation of the method forty-four subjects participated in a mock crime scenario and their EEG data were recorded. As the model input, in this study the recurrence plot features were extracted from single trial data of different stimuli. Then the extracted feature vectors were reduced using statistical dependency method. The reduced feature vector went through the proposed subject-based sparse model in which the discrimination power of sparse code and reconstruction error were applied simultaneously. Experimental results showed that the proposed approach achieved better performance than other competing discriminative sparse models. The classification accuracy, sensitivity and specificity of the presented sparsity-based method were about 93%, 91% and 95% respectively. Using the EEG data of a single subject in response to different stimuli types and with the aid of the proposed discriminative sparse representation model, one can distinguish guilty subjects from innocent ones. Indeed, this property eliminates the necessity of several subject EEG data in model learning and decision making for a specific subject. Copyright © 2017 Elsevier B.V. All rights reserved.

A Memetic Algorithm for Global Optimization of Multimodal Nonseparable Problems.

PubMed

Zhang, Geng; Li, Yangmin

2016-06-01

It is a big challenging issue of avoiding falling into local optimum especially when facing high-dimensional nonseparable problems where the interdependencies among vector elements are unknown. In order to improve the performance of optimization algorithm, a novel memetic algorithm (MA) called cooperative particle swarm optimizer-modified harmony search (CPSO-MHS) is proposed in this paper, where the CPSO is used for local search and the MHS for global search. The CPSO, as a local search method, uses 1-D swarm to search each dimension separately and thus converges fast. Besides, it can obtain global optimum elements according to our experimental results and analyses. MHS implements the global search by recombining different vector elements and extracting global optimum elements. The interaction between local search and global search creates a set of local search zones, where global optimum elements reside within the search space. The CPSO-MHS algorithm is tested and compared with seven other optimization algorithms on a set of 28 standard benchmarks. Meanwhile, some MAs are also compared according to the results derived directly from their corresponding references. The experimental results demonstrate a good performance of the proposed CPSO-MHS algorithm in solving multimodal nonseparable problems.

Global warming and the potential spread of vector-borne diseases

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

Patz, J.

1996-12-31

Climatic factors influence many vector-borne infectious diseases, in addition to demographic, biological, and ecological determinants. The United Nation`s Intergovernmental Panel on Climate Change (IPCC) estimates an unprecedented global rise of 2.0 C by the year 2100. Of major concern is that these changes can affect the spread of many serious infectious diseases, including malaria and dengue fever. Global warming would directly affect disease transmission by shifting the mosquito`s geographic range, increasing reproductive and biting rates, and shortening pathogen incubation period. Human migration and damage to health infrastructures from the projected increase in climate variability and sea level rise could indirectlymore » contribute to disease transmission. A review of this literature, as well as preliminary data from ongoing studies will be presented.« less

Spatial Pyramid Covariance based Compact Video Code for Robust Face Retrieval in TV-series.

PubMed

Li, Yan; Wang, Ruiping; Cui, Zhen; Shan, Shiguang; Chen, Xilin

2016-10-10

We address the problem of face video retrieval in TV-series which searches video clips based on the presence of specific character, given one face track of his/her. This is tremendously challenging because on one hand, faces in TV-series are captured in largely uncontrolled conditions with complex appearance variations, and on the other hand retrieval task typically needs efficient representation with low time and space complexity. To handle this problem, we propose a compact and discriminative representation for the huge body of video data, named Compact Video Code (CVC). Our method first models the face track by its sample (i.e., frame) covariance matrix to capture the video data variations in a statistical manner. To incorporate discriminative information and obtain more compact video signature suitable for retrieval, the high-dimensional covariance representation is further encoded as a much lower-dimensional binary vector, which finally yields the proposed CVC. Specifically, each bit of the code, i.e., each dimension of the binary vector, is produced via supervised learning in a max margin framework, which aims to make a balance between the discriminability and stability of the code. Besides, we further extend the descriptive granularity of covariance matrix from traditional pixel-level to more general patchlevel, and proceed to propose a novel hierarchical video representation named Spatial Pyramid Covariance (SPC) along with a fast calculation method. Face retrieval experiments on two challenging TV-series video databases, i.e., the Big Bang Theory and Prison Break, demonstrate the competitiveness of the proposed CVC over state-of-the-art retrieval methods. In addition, as a general video matching algorithm, CVC is also evaluated in traditional video face recognition task on a standard Internet database, i.e., YouTube Celebrities, showing its quite promising performance by using an extremely compact code with only 128 bits.

Automatic change detection: does the auditory system use representations of individual stimulus features or gestalts?

PubMed

Deacon, D; Nousak, J M; Pilotti, M; Ritter, W; Yang, C M

1998-07-01

The effects of global and feature-specific probabilities of auditory stimuli were manipulated to determine their effects on the mismatch negativity (MMN) of the human event-related potential. The question of interest was whether the automatic comparison of stimuli indexed by the MMN was performed on representations of individual stimulus features or on gestalt representations of their combined attributes. The design of the study was such that both feature and gestalt representations could have been available to the comparator mechanism generating the MMN. The data were consistent with the interpretation that the MMN was generated following an analysis of stimulus features.

Toward semantic-based retrieval of visual information: a model-based approach

NASA Astrophysics Data System (ADS)

Park, Youngchoon; Golshani, Forouzan; Panchanathan, Sethuraman

2002-07-01

This paper center around the problem of automated visual content classification. To enable classification based image or visual object retrieval, we propose a new image representation scheme called visual context descriptor (VCD) that is a multidimensional vector in which each element represents the frequency of a unique visual property of an image or a region. VCD utilizes the predetermined quality dimensions (i.e., types of features and quantization level) and semantic model templates mined in priori. Not only observed visual cues, but also contextually relevant visual features are proportionally incorporated in VCD. Contextual relevance of a visual cue to a semantic class is determined by using correlation analysis of ground truth samples. Such co-occurrence analysis of visual cues requires transformation of a real-valued visual feature vector (e.g., color histogram, Gabor texture, etc.,) into a discrete event (e.g., terms in text). Good-feature to track, rule of thirds, iterative k-means clustering and TSVQ are involved in transformation of feature vectors into unified symbolic representations called visual terms. Similarity-based visual cue frequency estimation is also proposed and used for ensuring the correctness of model learning and matching since sparseness of sample data causes the unstable results of frequency estimation of visual cues. The proposed method naturally allows integration of heterogeneous visual or temporal or spatial cues in a single classification or matching framework, and can be easily integrated into a semantic knowledge base such as thesaurus, and ontology. Robust semantic visual model template creation and object based image retrieval are demonstrated based on the proposed content description scheme.

Use of exocentric and egocentric representations in the concurrent planning of sequential saccades.

PubMed

Sharika, K M; Ramakrishnan, Arjun; Murthy, Aditya

2014-11-26

The concurrent planning of sequential saccades offers a simple model to study the nature of visuomotor transformations since the second saccade vector needs to be remapped to foveate the second target following the first saccade. Remapping is thought to occur through egocentric mechanisms involving an efference copy of the first saccade that is available around the time of its onset. In contrast, an exocentric representation of the second target relative to the first target, if available, can be used to directly code the second saccade vector. While human volunteers performed a modified double-step task, we examined the role of exocentric encoding in concurrent saccade planning by shifting the first target location well before the efference copy could be used by the oculomotor system. The impact of the first target shift on concurrent processing was tested by examining the end-points of second saccades following a shift of the second target during the first saccade. The frequency of second saccades to the old versus new location of the second target, as well as the propagation of first saccade localization errors, both indices of concurrent processing, were found to be significantly reduced in trials with the first target shift compared to those without it. A similar decrease in concurrent processing was obtained when we shifted the first target but kept constant the second saccade vector. Overall, these results suggest that the brain can use relatively stable visual landmarks, independent of efference copy-based egocentric mechanisms, for concurrent planning of sequential saccades. Copyright © 2014 the authors 0270-6474/14/3416009-13$15.00/0.

Minimal unitary representation of SO∗(8)=SO(6,2) and its SU(2) deformations as massless 6D conformal fields and their supersymmetric extensions

NASA Astrophysics Data System (ADS)

Fernando, Sudarshan; Günaydin, Murat

2010-12-01

We study the minimal unitary representation (minrep) of SO(6,2) over an Hilbert space of functions of five variables, obtained by quantizing its quasiconformal realization. The minrep of SO(6,2), which coincides with the minrep of SO(8) similarly constructed, corresponds to a massless conformal scalar field in six spacetime dimensions. There exists a family of "deformations" of the minrep of SO(8) labeled by the spin t of an SU(2 subgroup of the little group SO(4) of lightlike vectors. These deformations labeled by t are positive energy unitary irreducible representations of SO(8) that describe massless conformal fields in six dimensions. The SU(2 spin t is the six-dimensional counterpart of U(1) deformations of the minrep of 4D conformal group SU(2,2) labeled by helicity. We also construct the supersymmetric extensions of the minimal unitary representation of SO(8) to minimal unitary representations of OSp(8|2N) that describe massless six-dimensional conformal supermultiplets. The minimal unitary supermultiplet of OSp(8|4) is the massless supermultiplet of (2,0) conformal field theory that is believed to be dual to M-theory on AdS×S.

GLOBE Observer Mosquito Habitat Mapper: Geoscience and Public Health Connections

NASA Astrophysics Data System (ADS)

Low, R.; Boger, R. A.

2017-12-01

The global health crisis posed by vector-borne diseases is so great in scope that it is clearly insurmountable without the active help of tens-or hundreds- of thousands of individuals, working to identify and eradicate risk in communities around the world. Mobile devices equipped with data collection capabilities and visualization opportunities are lowering the barrier for participation in data collection efforts. The GLOBE Observer Mosquito Habitat Mapper (MHM) provides citizen scientists with an easy to use mobile platform to identify and locate mosquito breeding sites in their community. The app also supports the identification of vector taxa in the larvae development phase via a built-in key, which provides important information for scientists and public health officials tracking the rate of range expansion of invasive vector species and associated health threats. GO Mosquito is actively working with other citizen scientist programs across the world to ensure interoperability of data through standardization of metadata fields specific to vector monitoring, and through the development of APIs that allow for data exchange and shared data display through a UN-sponsored proof of concept project, Global Mosquito Alert. Avenues of application for mosquito vector data-both directly, by public health entities, and by modelers who employ remotely sensed environmental data to project mosquito population dynamics and epidemic disease will be featured.

How does the dengue vector mosquito Aedes albopictus respond to global warming?

PubMed

Jia, Pengfei; Chen, Xiang; Chen, Jin; Lu, Liang; Liu, Qiyong; Tan, Xiaoyue

2017-03-11

Global warming has a marked influence on the life cycle of epidemic vectors as well as their interactions with human beings. The Aedes albopictus mosquito as the vector of dengue fever surged exponentially in the last decade, raising ecological and epistemological concerns of how climate change altered its growth rate and population dynamics. As the global warming pattern is considerably uneven across four seasons, with a confirmed stronger effect in winter, an emerging need arises as to exploring how the seasonal warming effects influence the annual development of Ae. albopictus. The model consolidates a 35-year climate dataset and designs fifteen warming patterns that increase the temperature of selected seasons. Based on a recently developed mechanistic population model of Ae. albopictus, the model simulates the thermal reaction of blood-fed adults by systematically increasing the temperature from 0.5 to 5 °C at an interval of 0.5 °C in each warming pattern. The results show the warming effects are different across seasons. The warming effects in spring and winter facilitate the development of the species by shortening the diapause period. The warming effect in summer is primarily negative by inhibiting mosquito development. The warming effect in autumn is considerably mixed. However, these warming effects cannot carry over to the following year, possibly due to the fact that under the extreme weather in winter the mosquito fully ceases from development and survives in terms of diapause eggs. As the historical pattern of global warming manifests seasonal fluctuations, this study provides corroborating and previously ignored evidence of how such seasonality affects the mosquito development. Understanding this short-term temperature-driven mechanism as one chain of the transmission events is critical to refining the thermal reaction norms of the epidemic vector under global warming as well as developing effective mosquito prevention and control strategies.

First Use of Synoptic Vector Magnetograms for Global Nonlinear, Force-Free Coronal Magnetic Field Models

NASA Technical Reports Server (NTRS)

Tadesse, T.; Wiegelmann, T.; Gosain, S.; MacNeice, P.; Pevtsov, A. A.

2014-01-01

Context. The magnetic field permeating the solar atmosphere is generally thought to provide the energy for much of the activity seen in the solar corona, such as flares, coronal mass ejections (CMEs), etc. To overcome the unavailability of coronal magnetic field measurements, photospheric magnetic field vector data can be used to reconstruct the coronal field. Currently, there are several modelling techniques being used to calculate three-dimensional field lines into the solar atmosphere. Aims. For the first time, synoptic maps of a photospheric-vector magnetic field synthesized from the vector spectromagnetograph (VSM) on Synoptic Optical Long-term Investigations of the Sun (SOLIS) are used to model the coronal magnetic field and estimate free magnetic energy in the global scale. The free energy (i.e., the energy in excess of the potential field energy) is one of the main indicators used in space weather forecasts to predict the eruptivity of active regions. Methods. We solve the nonlinear force-free field equations using an optimization principle in spherical geometry. The resulting threedimensional magnetic fields are used to estimate the magnetic free energy content E(sub free) = E(sub nlfff) - E(sub pot), which is the difference of the magnetic energies between the nonpotential field and the potential field in the global solar corona. For comparison, we overlay the extrapolated magnetic field lines with the extreme ultraviolet (EUV) observations by the atmospheric imaging assembly (AIA) on board the Solar Dynamics Observatory (SDO). Results. For a single Carrington rotation 2121, we find that the global nonlinear force-free field (NLFFF) magnetic energy density is 10.3% higher than the potential one. Most of this free energy is located in active regions.

Web-based GIS: the vector-borne disease airline importation risk (VBD-AIR) tool

PubMed Central

2012-01-01

Background Over the past century, the size and complexity of the air travel network has increased dramatically. Nowadays, there are 29.6 million scheduled flights per year and around 2.7 billion passengers are transported annually. The rapid expansion of the network increasingly connects regions of endemic vector-borne disease with the rest of the world, resulting in challenges to health systems worldwide in terms of vector-borne pathogen importation and disease vector invasion events. Here we describe the development of a user-friendly Web-based GIS tool: the Vector-Borne Disease Airline Importation Risk Tool (VBD-AIR), to help better define the roles of airports and airlines in the transmission and spread of vector-borne diseases. Methods Spatial datasets on modeled global disease and vector distributions, as well as climatic and air network traffic data were assembled. These were combined to derive relative risk metrics via air travel for imported infections, imported vectors and onward transmission, and incorporated into a three-tier server architecture in a Model-View-Controller framework with distributed GIS components. A user-friendly web-portal was built that enables dynamic querying of the spatial databases to provide relevant information. Results The VBD-AIR tool constructed enables the user to explore the interrelationships among modeled global distributions of vector-borne infectious diseases (malaria. dengue, yellow fever and chikungunya) and international air service routes to quantify seasonally changing risks of vector and vector-borne disease importation and spread by air travel, forming an evidence base to help plan mitigation strategies. The VBD-AIR tool is available at http://www.vbd-air.com. Conclusions VBD-AIR supports a data flow that generates analytical results from disparate but complementary datasets into an organized cartographical presentation on a web map for the assessment of vector-borne disease movements on the air travel network. The framework built provides a flexible and robust informatics infrastructure by separating the modules of functionality through an ontological model for vector-borne disease. The VBD‒AIR tool is designed as an evidence base for visualizing the risks of vector-borne disease by air travel for a wide range of users, including planners and decisions makers based in state and local government, and in particular, those at international and domestic airports tasked with planning for health risks and allocating limited resources. PMID:22892045

Web-based GIS: the vector-borne disease airline importation risk (VBD-AIR) tool.

PubMed

Huang, Zhuojie; Das, Anirrudha; Qiu, Youliang; Tatem, Andrew J

2012-08-14

Over the past century, the size and complexity of the air travel network has increased dramatically. Nowadays, there are 29.6 million scheduled flights per year and around 2.7 billion passengers are transported annually. The rapid expansion of the network increasingly connects regions of endemic vector-borne disease with the rest of the world, resulting in challenges to health systems worldwide in terms of vector-borne pathogen importation and disease vector invasion events. Here we describe the development of a user-friendly Web-based GIS tool: the Vector-Borne Disease Airline Importation Risk Tool (VBD-AIR), to help better define the roles of airports and airlines in the transmission and spread of vector-borne diseases. Spatial datasets on modeled global disease and vector distributions, as well as climatic and air network traffic data were assembled. These were combined to derive relative risk metrics via air travel for imported infections, imported vectors and onward transmission, and incorporated into a three-tier server architecture in a Model-View-Controller framework with distributed GIS components. A user-friendly web-portal was built that enables dynamic querying of the spatial databases to provide relevant information. The VBD-AIR tool constructed enables the user to explore the interrelationships among modeled global distributions of vector-borne infectious diseases (malaria. dengue, yellow fever and chikungunya) and international air service routes to quantify seasonally changing risks of vector and vector-borne disease importation and spread by air travel, forming an evidence base to help plan mitigation strategies. The VBD-AIR tool is available at http://www.vbd-air.com. VBD-AIR supports a data flow that generates analytical results from disparate but complementary datasets into an organized cartographical presentation on a web map for the assessment of vector-borne disease movements on the air travel network. The framework built provides a flexible and robust informatics infrastructure by separating the modules of functionality through an ontological model for vector-borne disease. The VBD‒AIR tool is designed as an evidence base for visualizing the risks of vector-borne disease by air travel for a wide range of users, including planners and decisions makers based in state and local government, and in particular, those at international and domestic airports tasked with planning for health risks and allocating limited resources.

Malaria rapid diagnostic tests.

PubMed

Wilson, Michael L

2012-06-01

Global efforts to control malaria are more complex than those for other infectious diseases, in part because of vector transmission, the complex clinical presentation of Plasmodium infections, >1 Plasmodium species causing infection, geographic distribution of vectors and infection, and drug resistance. The World Health Organization approach to global malaria control focuses on 2 components: vector control and diagnosis and treatment of clinical malaria. Although microscopy performed on peripheral blood smears remains the most widely used diagnostic test and the standard against which other tests are measured, rapid expansion of diagnostic testing worldwide will require use of other diagnostic approaches. This review will focus on the malaria rapid diagnostic test (MRDT) for detecting malaria parasitemia, both in terms of performance characteristics of MRDTs and how they are used under field conditions. The emphasis will be on the performance and use of MRDTs in regions of endemicity, particularly sub-Saharan Africa, where most malaria-related deaths occur.

Re-visiting RHIC snakes: OPERA fields, n 0 dance

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

Meot, F.; Gupta, R.; Huang, H.

In this Tech. Note RHIC snakes and stable spin directionmore » $$\\vector{n}$$ 0(s) are re-visited, based on OPERA-computed field maps of the former. The numerical simulations so undertaken provide various outcomes regarding RHIC optics and spin dynamics, in relation with orbital and focusing effects resulting from the use of this realistic 3-D representation of the snakes.« less

Another elementary proof of the Jordan form of a matrix

NASA Astrophysics Data System (ADS)

Budhi, Wono Setya

2012-05-01

In this paper we establish the Jordan Form for a matrix using the elementary concepts of vector differentiation and partial fractions. The idea comes from the resolvent of the operator. For the matrix, the Laurent series is finite and easy to compute through rational representation. We also give a proof of some famous theorems in matrix analysis as consequences from the result.

Wavelets and the Poincaré half-plane

NASA Astrophysics Data System (ADS)

Klauder, J. R.; Streater, R. F.

1994-01-01

A square-integrable signal of positive energy is transformed into an analytic function in the upper half-plane, on which SL(2,R) acts. It is shown that this analytic function is determined by its scalar products with the discrete family of functions obtained by acting with SL(2,Z) on a cyclic vector, provided that the spin of the representation is less than 3.

Bidirectional reflectance distribution function measurements and analysis of retroreflective materials.

PubMed

Belcour, Laurent; Pacanowski, Romain; Delahaie, Marion; Laville-Geay, Aude; Eupherte, Laure

2014-12-01

We compare the performance of various analytical retroreflecting bidirectional reflectance distribution function (BRDF) models to assess how they reproduce accurately measured data of retroreflecting materials. We introduce a new parametrization, the back vector parametrization, to analyze retroreflecting data, and we show that this parametrization better preserves the isotropy of data. Furthermore, we update existing BRDF models to improve the representation of retroreflective data.

Global rotational motion and displacement estimation of digital image stabilization based on the oblique vectors matching algorithm

NASA Astrophysics Data System (ADS)

Yu, Fei; Hui, Mei; Zhao, Yue-jin

2009-08-01

The image block matching algorithm based on motion vectors of correlative pixels in oblique direction is presented for digital image stabilization. The digital image stabilization is a new generation of image stabilization technique which can obtains the information of relative motion among frames of dynamic image sequences by the method of digital image processing. In this method the matching parameters are calculated from the vectors projected in the oblique direction. The matching parameters based on the vectors contain the information of vectors in transverse and vertical direction in the image blocks at the same time. So the better matching information can be obtained after making correlative operation in the oblique direction. And an iterative weighted least square method is used to eliminate the error of block matching. The weights are related with the pixels' rotational angle. The center of rotation and the global emotion estimation of the shaking image can be obtained by the weighted least square from the estimation of each block chosen evenly from the image. Then, the shaking image can be stabilized with the center of rotation and the global emotion estimation. Also, the algorithm can run at real time by the method of simulated annealing in searching method of block matching. An image processing system based on DSP was used to exam this algorithm. The core processor in the DSP system is TMS320C6416 of TI, and the CCD camera with definition of 720×576 pixels was chosen as the input video signal. Experimental results show that the algorithm can be performed at the real time processing system and have an accurate matching precision.

The Role of Innate Immunity in Conditioning Mosquito Susceptibility to West Nile Virus

PubMed Central

Prasad, Abhishek N.; Brackney, Doug. E.; Ebel, Gregory D.

2013-01-01

Arthropod-borne viruses (arboviruses) represent an emerging threat to human and livestock health globally. In particular, those transmitted by mosquitoes present the greatest challenges to disease control efforts. An understanding of the molecular basis for mosquito innate immunity to arbovirus infection is therefore critical to investigations regarding arbovirus evolution, virus-vector ecology, and mosquito vector competence. In this review, we discuss the current state of understanding regarding mosquito innate immunity to West Nile virus. We draw from the literature with respect to other virus-vector pairings to attempt to draw inferences to gaps in our knowledge about West Nile virus and relevant vectors. PMID:24351797

The dominant Anopheles vectors of human malaria in the Asia-Pacific region: occurrence data, distribution maps and bionomic précis

PubMed Central

2011-01-01

Background The final article in a series of three publications examining the global distribution of 41 dominant vector species (DVS) of malaria is presented here. The first publication examined the DVS from the Americas, with the second covering those species present in Africa, Europe and the Middle East. Here we discuss the 19 DVS of the Asian-Pacific region. This region experiences a high diversity of vector species, many occurring sympatrically, which, combined with the occurrence of a high number of species complexes and suspected species complexes, and behavioural plasticity of many of these major vectors, adds a level of entomological complexity not comparable elsewhere globally. To try and untangle the intricacy of the vectors of this region and to increase the effectiveness of vector control interventions, an understanding of the contemporary distribution of each species, combined with a synthesis of the current knowledge of their behaviour and ecology is needed. Results Expert opinion (EO) range maps, created with the most up-to-date expert knowledge of each DVS distribution, were combined with a contemporary database of occurrence data and a suite of open access, environmental and climatic variables. Using the Boosted Regression Tree (BRT) modelling method, distribution maps of each DVS were produced. The occurrence data were abstracted from the formal, published literature, plus other relevant sources, resulting in the collation of DVS occurrence at 10116 locations across 31 countries, of which 8853 were successfully geo-referenced and 7430 were resolved to spatial areas that could be included in the BRT model. A detailed summary of the information on the bionomics of each species and species complex is also presented. Conclusions This article concludes a project aimed to establish the contemporary global distribution of the DVS of malaria. The three articles produced are intended as a detailed reference for scientists continuing research into the aspects of taxonomy, biology and ecology relevant to species-specific vector control. This research is particularly relevant to help unravel the complicated taxonomic status, ecology and epidemiology of the vectors of the Asia-Pacific region. All the occurrence data, predictive maps and EO-shape files generated during the production of these publications will be made available in the public domain. We hope that this will encourage data sharing to improve future iterations of the distribution maps. PMID:21612587

The dominant Anopheles vectors of human malaria in the Asia-Pacific region: occurrence data, distribution maps and bionomic précis.

PubMed

Sinka, Marianne E; Bangs, Michael J; Manguin, Sylvie; Chareonviriyaphap, Theeraphap; Patil, Anand P; Temperley, William H; Gething, Peter W; Elyazar, Iqbal R F; Kabaria, Caroline W; Harbach, Ralph E; Hay, Simon I

2011-05-25

The final article in a series of three publications examining the global distribution of 41 dominant vector species (DVS) of malaria is presented here. The first publication examined the DVS from the Americas, with the second covering those species present in Africa, Europe and the Middle East. Here we discuss the 19 DVS of the Asian-Pacific region. This region experiences a high diversity of vector species, many occurring sympatrically, which, combined with the occurrence of a high number of species complexes and suspected species complexes, and behavioural plasticity of many of these major vectors, adds a level of entomological complexity not comparable elsewhere globally. To try and untangle the intricacy of the vectors of this region and to increase the effectiveness of vector control interventions, an understanding of the contemporary distribution of each species, combined with a synthesis of the current knowledge of their behaviour and ecology is needed. Expert opinion (EO) range maps, created with the most up-to-date expert knowledge of each DVS distribution, were combined with a contemporary database of occurrence data and a suite of open access, environmental and climatic variables. Using the Boosted Regression Tree (BRT) modelling method, distribution maps of each DVS were produced. The occurrence data were abstracted from the formal, published literature, plus other relevant sources, resulting in the collation of DVS occurrence at 10116 locations across 31 countries, of which 8853 were successfully geo-referenced and 7430 were resolved to spatial areas that could be included in the BRT model. A detailed summary of the information on the bionomics of each species and species complex is also presented. This article concludes a project aimed to establish the contemporary global distribution of the DVS of malaria. The three articles produced are intended as a detailed reference for scientists continuing research into the aspects of taxonomy, biology and ecology relevant to species-specific vector control. This research is particularly relevant to help unravel the complicated taxonomic status, ecology and epidemiology of the vectors of the Asia-Pacific region. All the occurrence data, predictive maps and EO-shape files generated during the production of these publications will be made available in the public domain. We hope that this will encourage data sharing to improve future iterations of the distribution maps.

The mental representations of fractions: adults' same–different judgments

PubMed Central

Gabriel, Florence; Szucs, Denes; Content, Alain

2013-01-01

Two experiments examined whether the processing of the magnitude of fractions is global or componential. Previously, some authors concluded that adults process the numerators and denominators of fractions separately and do not access the global magnitude of fractions. Conversely, others reported evidence suggesting that the global magnitude of fractions is accessed. We hypothesized that in a fraction matching task, participants automatically extract the magnitude of the components but that the activation of the global magnitude of the whole fraction is only optional or strategic. Participants carried out same/different judgment tasks. Two different tasks were used: a physical matching task and a numerical matching task. Pairs of fractions were presented either simultaneously or sequentially. Results showed that participants only accessed the representation of the global magnitude of fractions in the numerical matching task. The mode of stimulus presentation did not affect the processing of fractions. The present study allows a deeper understanding of the conditions in which the magnitude of fractions is mentally represented by using matching tasks and two different modes of presentation. PMID:23847562

Climate teleconnections, weather extremes, and vector-borne disease outbreaks

USDA-ARS?s Scientific Manuscript database

Fluctuations in climate lead to extremes in temperature, rainfall, flooding, and droughts. These climate extremes create ideal ecological conditions that promote mosquito-borne disease transmission that impact global human and animal health. One well known driver of such global scale climate fluctua...

2D and 3D graphical representation of the propagation of electromagnetic waves at the interface with a material with general effective complex permittivity and permeability

NASA Astrophysics Data System (ADS)

Diaz, A.; Ramos, J. G.; Friedman, J. S.

2017-09-01

We developed a web-based instructional and research tool that demonstrates the behavior of electromagnetic waves as they propagate through a homogenous medium and through an interface where the second medium can be characterized by an effective complex permittivity and permeability. Either p- or s-polarization wave components can be chosen and the graphical interface includes 2D wave and 3D component representations. The program enables the study of continuity of electromagnetic components, critical angle, Brewster angle, absorption and amplification, behavior of light in sub-unity and negative-index materials, Poynting vector and phase velocity behavior, and positive and negative Goos- Hänchen shifts.

On the dual equivalence of the self-dual and topologically massive /B∧F models coupled to dynamical fermionic matter

NASA Astrophysics Data System (ADS)

Menezes, R.; Nascimento, J. R. S.; Ribeiro, R. F.; Wotzasek, C.

2002-06-01

We study the equivalence between the /B∧F self-dual (SDB∧F) and the /B∧F topologically massive (TMB∧F) models including the coupling to dynamical, U(1) charged fermionic matter. This is done through an iterative procedure of gauge embedding that produces the dual mapping. In the interactive cases, the minimal coupling adopted for both vector and tensor fields in the self-dual representation is transformed into a non-minimal magnetic like coupling in the topologically massive representation but with the currents swapped. It is known that to establish this equivalence a current-current interaction term is needed to render the matter sector unchanged. We show that both terms arise naturally from the embedding procedure.

Representing motion in a static image: constraints and parallels in art, science, and popular culture.

PubMed

Cutting, James E

2002-01-01

Representing motion in a picture is a challenge to artists, scientists, and all other imagemakers. Moreover, it presents a problem that will not go away with electronic and digital media, because often the pedagogical purpose of the representation of motion is more important than the motion itself. All satisfactory solutions evoke motion-for example, dynamic balance (or broken symmetry), stroboscopic sequences, affine shear (or forward lean), and photographic blur-but they also typically sacrifice the accuracy of the motion represented, a solution often unsuitable for science. Vector representations superimposed on static images allow for accuracy, but are not applicable to all situations. Workable solutions are almost certainly case specific and subject to continual evolution through exploration by imagemakers.

Deep visual-semantic for crowded video understanding

NASA Astrophysics Data System (ADS)

Deng, Chunhua; Zhang, Junwen

2018-03-01

Visual-semantic features play a vital role for crowded video understanding. Convolutional Neural Networks (CNNs) have experienced a significant breakthrough in learning representations from images. However, the learning of visualsemantic features, and how it can be effectively extracted for video analysis, still remains a challenging task. In this study, we propose a novel visual-semantic method to capture both appearance and dynamic representations. In particular, we propose a spatial context method, based on the fractional Fisher vector (FV) encoding on CNN features, which can be regarded as our main contribution. In addition, to capture temporal context information, we also applied fractional encoding method on dynamic images. Experimental results on the WWW crowed video dataset demonstrate that the proposed method outperform the state of the art.

A Reversible Logical Circuit Synthesis Algorithm Based on Decomposition of Cycle Representations of Permutations

NASA Astrophysics Data System (ADS)

Zhu, Wei; Li, Zhiqiang; Zhang, Gaoman; Pan, Suhan; Zhang, Wei

2018-05-01

A reversible function is isomorphic to a permutation and an arbitrary permutation can be represented by a series of cycles. A new synthesis algorithm for 3-qubit reversible circuits was presented. It consists of two parts, the first part used the Number of reversible function's Different Bits (NDBs) to decide whether the NOT gate should be added to decrease the Hamming distance of the input and output vectors; the second part was based on the idea of exploring properties of the cycle representation of permutations, decomposed the cycles to make the permutation closer to the identity permutation and finally turn into the identity permutation, it was realized by using totally controlled Toffoli gates with positive and negative controls.

MISR 17.6 KM Gridded Cloud Motion Vectors: Overview and Assessment

NASA Technical Reports Server (NTRS)

Mueller, Kevin; Garay, Michael; Moroney, Catherine; Jovanovic, Veljko

2012-01-01

The MISR (Multi-angle Imaging SpectroRadiometer) instrument on the Terra satellite has been retrieving cloud motion vectors (CMVs) globally and almost continuously since early in 2000. In February 2012 the new MISR Level 2 Cloud product was publicly released, providing cloud motion vectors at 17.6 km resolution with improved accuracy and roughly threefold increased coverage relative to the 70.4 km resolution vectors of the current MISR Level 2 Stereo product (which remains available). MISR retrieves both horizontal cloud motion and height from the apparent displacement due to parallax and movement of cloud features across three visible channel (670nm) camera views over a span of 200 seconds. The retrieval has comparable accuracy to operational atmospheric motion vectors from other current sensors, but holds the additional advantage of global coverage and finer precision height retrieval that is insensitive to radiometric calibration. The MISR mission is expected to continue operation for many more years, possibly until 2019, and Level 2 Cloud has the possibility of being produced with a sensing-to-availability lag of 5 hours. This report compares MISR CMV with collocated motion vectors from arctic rawinsonde sites, and from the GOES and MODISTerra instruments. CMV at heights below 3 km exhibit the smallest differences, as small as 3.3 m/s for MISR and GOES. Clouds above 3 km exhibit larger differences, as large as 8.9 m/s for MISR and MODIS. Typical differences are on the order of 6 m/s.

Dengue: recent past and future threats

PubMed Central

Rogers, David J.

2015-01-01

This article explores four key questions about statistical models developed to describe the recent past and future of vector-borne diseases, with special emphasis on dengue: (1) How many variables should be used to make predictions about the future of vector-borne diseases?(2) Is the spatial resolution of a climate dataset an important determinant of model accuracy?(3) Does inclusion of the future distributions of vectors affect predictions of the futures of the diseases they transmit?(4) Which are the key predictor variables involved in determining the distributions of vector-borne diseases in the present and future?Examples are given of dengue models using one, five or 10 meteorological variables and at spatial resolutions of from one-sixth to two degrees. Model accuracy is improved with a greater number of descriptor variables, but is surprisingly unaffected by the spatial resolution of the data. Dengue models with a reduced set of climate variables derived from the HadCM3 global circulation model predictions for the 1980s are improved when risk maps for dengue's two main vectors (Aedes aegypti and Aedes albopictus) are also included as predictor variables; disease and vector models are projected into the future using the global circulation model predictions for the 2020s, 2040s and 2080s. The Garthwaite–Koch corr-max transformation is presented as a novel way of showing the relative contribution of each of the input predictor variables to the map predictions. PMID:25688021

International News Flows in the Post-Cold War World: Mapping the News and the News Producers.

ERIC Educational Resources Information Center

Sreberny-Mohammadi, Annabelle

1995-01-01

Reviews the global political environment, major global news providers, and technologies of global news production. Argues for a multinational comparative mapping of international news representation in the 1990s. Outlines a major international venture to update and elaborate the 1979 UNESCO/IAMCR study of foreign news in the media of 29 countries,…

Global, Local, and Graphical Person-Fit Analysis Using Person-Response Functions

ERIC Educational Resources Information Center

Emons, Wilco H. M.; Sijtsma, Klaas; Meijer, Rob R.

2005-01-01

Person-fit statistics test whether the likelihood of a respondent's complete vector of item scores on a test is low given the hypothesized item response theory model. This binary information may be insufficient for diagnosing the cause of a misfitting item-score vector. The authors propose a comprehensive methodology for person-fit analysis in the…

Unsupervised Discovery of Nonlinear Structure Using Contrastive Backpropagation

ERIC Educational Resources Information Center

Hinton, Geoffrey; Osindero, Simon; Welling, Max; Teh, Yee-Whye

2006-01-01

We describe a way of modeling high-dimensional data vectors by using an unsupervised, nonlinear, multilayer neural network in which the activity of each neuron-like unit makes an additive contribution to a global energy score that indicates how surprised the network is by the data vector. The connection weights that determine how the activity of…

Vibration mode shape recognition using image processing

NASA Astrophysics Data System (ADS)

Wang, Weizhuo; Mottershead, John E.; Mares, Cristinel

2009-10-01

Currently the most widely used method for comparing mode shapes from finite elements and experimental measurements is the modal assurance criterion (MAC), which can be interpreted as the cosine of the angle between the numerical and measured eigenvectors. However, the eigenvectors only contain the displacement of discrete coordinates, so that the MAC index carries no explicit information on shape features. New techniques, based upon the well-developed philosophies of image processing (IP) and pattern recognition (PR) are considered in this paper. The Zernike moment descriptor (ZMD), Fourier descriptor (FD), and wavelet descriptor (WD) are the most popular shape descriptors due to their outstanding properties in IP and PR. These include (1) for the ZMD-rotational invariance, expression and computing efficiency, ease of reconstruction and robustness to noise; (2) for the FD—separation of the global shape and shape-details by low and high frequency components, respectively, invariance under geometric transformation; (3) for the WD—multi-scale representation and local feature detection. Once a shape descriptor has been adopted, the comparison of mode shapes is transformed to a comparison of multidimensional shape feature vectors. Deterministic and statistical methods are presented. The deterministic problem of measuring the degree of similarity between two mode shapes (possibly one from a vibration test and the other from a finite element model) may be carried out using Pearson's correlation. Similar shape feature vectors may be arranged in clusters separated by Euclidian distances in the feature space. In the statistical analysis we are typically concerned with the classification of a test mode shape according to clusters of shape feature vectors obtained from a randomised finite element model. The dimension of the statistical problem may often be reduced by principal component analysis. Then, in addition to the Euclidian distance, the Mahalanobis distance, defining the separation of the test point from the cluster in terms of its standard deviation, becomes an important measure. Bayesian decision theory may be applied to formally minimise the risk of misclassification of the test shape feature vector. In this paper the ZMD is applied to the problem of mode shape recognition for a circular plate. Results show that the ZMD has considerable advantages over the traditional MAC index when identifying the cyclically symmetric mode shapes that occur in axisymmetric structures at identical frequencies. Mode shape recognition of rectangular plates is carried out by the FD. Also, the WD is applied to the problem of recognising the mode shapes in the thin and thick regions of a plate with different thicknesses. It shows the benefit of using the WD to identify mode-shapes having both local and global components. The comparison and classification of mode shapes using IP and PR provides a 'toolkit' to complement the conventional MAC approach. The selection of a particular shape descriptor and classification method will depend upon the problem in hand and the experience of the analyst.

Air-climate-energy investigations with a state-level Integrated Assessment Model: GCAM-USA

EPA Science Inventory

The Global Change Assessment Model (GCAM) is a global integrated assessment model used for exploring future scenarios and examining strategies that address air pollution, climate change, and energy goals.  GCAM includes technology-rich representations of the energy, transportatio...

The changing global carbon cycle: Linking plant-soil carbon dynamics to global consequences

USGS Publications Warehouse

Chapin, F. S.; McFarland, J.; McGuire, David A.; Euskirchen, E.S.; Ruess, Roger W.; Kielland, K.

2009-01-01

Synthesis. Current climate systems models that include only NPP and HR are inadequate under conditions of rapid change. Many of the recent advances in biogeochemical understanding are sufficiently mature to substantially improve representation of ecosystem C dynamics in these models.

Video2vec Embeddings Recognize Events When Examples Are Scarce.

PubMed

Habibian, Amirhossein; Mensink, Thomas; Snoek, Cees G M

2017-10-01

This paper aims for event recognition when video examples are scarce or even completely absent. The key in such a challenging setting is a semantic video representation. Rather than building the representation from individual attribute detectors and their annotations, we propose to learn the entire representation from freely available web videos and their descriptions using an embedding between video features and term vectors. In our proposed embedding, which we call Video2vec, the correlations between the words are utilized to learn a more effective representation by optimizing a joint objective balancing descriptiveness and predictability. We show how learning the Video2vec embedding using a multimodal predictability loss, including appearance, motion and audio features, results in a better predictable representation. We also propose an event specific variant of Video2vec to learn a more accurate representation for the words, which are indicative of the event, by introducing a term sensitive descriptiveness loss. Our experiments on three challenging collections of web videos from the NIST TRECVID Multimedia Event Detection and Columbia Consumer Videos datasets demonstrate: i) the advantages of Video2vec over representations using attributes or alternative embeddings, ii) the benefit of fusing video modalities by an embedding over common strategies, iii) the complementarity of term sensitive descriptiveness and multimodal predictability for event recognition. By its ability to improve predictability of present day audio-visual video features, while at the same time maximizing their semantic descriptiveness, Video2vec leads to state-of-the-art accuracy for both few- and zero-example recognition of events in video.

A combined model of sensory and cognitive representations underlying tonal expectations in music: from audio signals to behavior.

PubMed

Collins, Tom; Tillmann, Barbara; Barrett, Frederick S; Delbé, Charles; Janata, Petr

2014-01-01

Listeners' expectations for melodies and harmonies in tonal music are perhaps the most studied aspect of music cognition. Long debated has been whether faster response times (RTs) to more strongly primed events (in a music theoretic sense) are driven by sensory or cognitive mechanisms, such as repetition of sensory information or activation of cognitive schemata that reflect learned tonal knowledge, respectively. We analyzed over 300 stimuli from 7 priming experiments comprising a broad range of musical material, using a model that transforms raw audio signals through a series of plausible physiological and psychological representations spanning a sensory-cognitive continuum. We show that RTs are modeled, in part, by information in periodicity pitch distributions, chroma vectors, and activations of tonal space--a representation on a toroidal surface of the major/minor key relationships in Western tonal music. We show that in tonal space, melodies are grouped by their tonal rather than timbral properties, whereas the reverse is true for the periodicity pitch representation. While tonal space variables explained more of the variation in RTs than did periodicity pitch variables, suggesting a greater contribution of cognitive influences to tonal expectation, a stepwise selection model contained variables from both representations and successfully explained the pattern of RTs across stimulus categories in 4 of the 7 experiments. The addition of closure--a cognitive representation of a specific syntactic relationship--succeeded in explaining results from all 7 experiments. We conclude that multiple representational stages along a sensory-cognitive continuum combine to shape tonal expectations in music. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Gravity Influences the Visual Representation of Object Tilt in Parietal Cortex

PubMed Central

Angelaki, Dora E.

2014-01-01

Sensory systems encode the environment in egocentric (e.g., eye, head, or body) reference frames, creating inherently unstable representations that shift and rotate as we move. However, it is widely speculated that the brain transforms these signals into an allocentric, gravity-centered representation of the world that is stable and independent of the observer's spatial pose. Where and how this representation may be achieved is currently unknown. Here we demonstrate that a subpopulation of neurons in the macaque caudal intraparietal area (CIP) visually encodes object tilt in nonegocentric coordinates defined relative to the gravitational vector. Neuronal responses to the tilt of a visually presented planar surface were measured with the monkey in different spatial orientations (upright and rolled left/right ear down) and then compared. This revealed a continuum of representations in which planar tilt was encoded in a gravity-centered reference frame in approximately one-tenth of the comparisons, intermediate reference frames ranging between gravity-centered and egocentric in approximately two-tenths of the comparisons, and in an egocentric reference frame in less than half of the comparisons. Altogether, almost half of the comparisons revealed a shift in the preferred tilt and/or a gain change consistent with encoding object orientation in nonegocentric coordinates. Through neural network modeling, we further show that a purely gravity-centered representation of object tilt can be achieved directly from the population activity of CIP-like units. These results suggest that area CIP may play a key role in creating a stable, allocentric representation of the environment defined relative to an “earth-vertical” direction. PMID:25339732

Knowledge represented using RDF semantic network in the concept of semantic web

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

Lukasova, A., E-mail: alena.lukasova@osu.cz; Vajgl, M., E-mail: marek.vajgl@osu.cz; Zacek, M., E-mail: martin.zacek@osu.cz

The RDF(S) model has been declared as the basic model to capture knowledge of the semantic web. It provides a common and flexible way to decompose composed knowledge to elementary statements, which can be represented by RDF triples or by RDF graph vectors. From the logical point of view, elements of knowledge can be expressed using at most binary predicates, which can be converted to RDF-triples or graph vectors. However, it is not able to capture implicit knowledge representable by logical formulas. This contribution shows how existing approaches (semantic networks and clausal form logic) can be combined together with RDFmore » to obtain RDF-compatible system with ability to represent implicit knowledge and inference over knowledge base.« less

Face recognition algorithm using extended vector quantization histogram features.

PubMed

Yan, Yan; Lee, Feifei; Wu, Xueqian; Chen, Qiu

2018-01-01

In this paper, we propose a face recognition algorithm based on a combination of vector quantization (VQ) and Markov stationary features (MSF). The VQ algorithm has been shown to be an effective method for generating features; it extracts a codevector histogram as a facial feature representation for face recognition. Still, the VQ histogram features are unable to convey spatial structural information, which to some extent limits their usefulness in discrimination. To alleviate this limitation of VQ histograms, we utilize Markov stationary features (MSF) to extend the VQ histogram-based features so as to add spatial structural information. We demonstrate the effectiveness of our proposed algorithm by achieving recognition results superior to those of several state-of-the-art methods on publicly available face databases.