Modeling Interferometric Structures with Birefringent Elements: A Linear Vector-Space Formalism

DTIC Science & Technology

2013-11-12

Annapolis, Maryland ViNceNt J. Urick FraNk BUcholtz Photonics Technology Branch Optical Sciences Division i REPORT DOCUMENTATION PAGE Form...a Linear Vector-Space Formalism Nicholas J. Frigo,1 Vincent J. Urick , and Frank Bucholtz Naval Research Laboratory, Code 5650 4555 Overlook Avenue, SW...Annapolis, MD Unclassified Unlimited Unclassified Unlimited Unclassified Unlimited Unclassified Unlimited 29 Vincent J. Urick (202) 767-9352 Coupled mode

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.

Prediction of hourly PM2.5 using a space-time support vector regression model

NASA Astrophysics Data System (ADS)

Yang, Wentao; Deng, Min; Xu, Feng; Wang, Hang

2018-05-01

Real-time air quality prediction has been an active field of research in atmospheric environmental science. The existing methods of machine learning are widely used to predict pollutant concentrations because of their enhanced ability to handle complex non-linear relationships. However, because pollutant concentration data, as typical geospatial data, also exhibit spatial heterogeneity and spatial dependence, they may violate the assumptions of independent and identically distributed random variables in most of the machine learning methods. As a result, a space-time support vector regression model is proposed to predict hourly PM2.5 concentrations. First, to address spatial heterogeneity, spatial clustering is executed to divide the study area into several homogeneous or quasi-homogeneous subareas. To handle spatial dependence, a Gauss vector weight function is then developed to determine spatial autocorrelation variables as part of the input features. Finally, a local support vector regression model with spatial autocorrelation variables is established for each subarea. Experimental data on PM2.5 concentrations in Beijing are used to verify whether the results of the proposed model are superior to those of other methods.

Unitary Operators on the Document Space.

ERIC Educational Resources Information Center

Hoenkamp, Eduard

2003-01-01

Discusses latent semantic indexing (LSI) that would allow search engines to reduce the dimension of the document space by mapping it into a space spanned by conceptual indices. Topics include vector space models; singular value decomposition (SVD); unitary operators; the Haar transform; and new algorithms. (Author/LRW)

Managing the resilience space of the German energy system - A vector analysis.

PubMed

Schlör, Holger; Venghaus, Sandra; Märker, Carolin; Hake, Jürgen-Friedrich

2018-07-15

The UN Sustainable Development Goals formulated in 2016 confirmed the sustainability concept of the Earth Summit of 1992 and supported UNEP's green economy transition concept. The transformation of the energy system (Energiewende) is the keystone of Germany's sustainability strategy and of the German green economy concept. We use ten updated energy-related indicators of the German sustainability strategy to analyse the German energy system. The development of the sustainable indicators is examined in the monitoring process by a vector analysis performed in two-dimensional Euclidean space (Euclidean plane). The aim of the novel vector analysis is to measure the current status of the Energiewende in Germany and thereby provide decision makers with information about the strains for the specific remaining pathway of the single indicators and of the total system in order to meet the sustainability targets of the Energiewende. Within this vector model, three vectors (the normative sustainable development vector, the real development vector, and the green economy vector) define the resilience space of our analysis. The resilience space encloses a number of vectors representing different pathways with different technological and socio-economic strains to achieve a sustainable development of the green economy. In this space, the decision will be made as to whether the government measures will lead to a resilient energy system or whether a readjustment of indicator targets or political measures is necessary. The vector analysis enables us to analyse both the government's ambitiousness, which is expressed in the sustainability target for the indicators at the start of the sustainability strategy representing the starting preference order of the German government (SPO) and, secondly, the current preference order of German society in order to bridge the remaining distance to reach the specific sustainability goals of the strategy summarized in the current preference order (CPO). Copyright © 2018 Elsevier Ltd. All rights reserved.

Pure state consciousness and its local reduction to neuronal space

NASA Astrophysics Data System (ADS)

Duggins, A. J.

2013-01-01

The single neuronal state can be represented as a vector in a complex space, spanned by an orthonormal basis of integer spike counts. In this model a scalar element of experience is associated with the instantaneous firing rate of a single sensory neuron over repeated stimulus presentations. Here the model is extended to composite neural systems that are tensor products of single neuronal vector spaces. Depiction of the mental state as a vector on this tensor product space is intended to capture the unity of consciousness. The density operator is introduced as its local reduction to the single neuron level, from which the firing rate can again be derived as the objective correlate of a subjective element. However, the relational structure of perceptual experience only emerges when the non-local mental state is considered. A metric of phenomenal proximity between neuronal elements of experience is proposed, based on the cross-correlation function of neurophysiology, but constrained by the association of theoretical extremes of correlation/anticorrelation in inseparable 2-neuron states with identical and opponent elements respectively.

Cosmology and accelerator tests of strongly interacting dark matter

DOE PAGES

Berlin, Asher; Blinov, Nikita; Gori, Stefania; ...

2018-03-23

A natural possibility for dark matter is that it is composed of the stable pions of a QCD-like hidden sector. Existing literature largely assumes that pion self-interactions alone control the early universe cosmology. We point out that processes involving vector mesons typically dominate the physics of dark matter freeze-out and significantly widen the viable mass range for these models. The vector mesons also give rise to striking signals at accelerators. For example, in most of the cosmologically favored parameter space, the vector mesons are naturally long-lived and produce standard model particles in their decays. Electron and proton beam fixed-target experimentsmore » such as HPS, SeaQuest, and LDMX can exploit these signals to explore much of the viable parameter space. As a result, we also comment on dark matter decay inherent in a large class of previously considered models and explain how to ensure dark matter stability.« less

Cosmology and accelerator tests of strongly interacting dark matter

NASA Astrophysics Data System (ADS)

Berlin, Asher; Blinov, Nikita; Gori, Stefania; Schuster, Philip; Toro, Natalia

2018-03-01

A natural possibility for dark matter is that it is composed of the stable pions of a QCD-like hidden sector. Existing literature largely assumes that pion self-interactions alone control the early universe cosmology. We point out that processes involving vector mesons typically dominate the physics of dark matter freeze-out and significantly widen the viable mass range for these models. The vector mesons also give rise to striking signals at accelerators. For example, in most of the cosmologically favored parameter space, the vector mesons are naturally long-lived and produce standard model particles in their decays. Electron and proton beam fixed-target experiments such as HPS, SeaQuest, and LDMX can exploit these signals to explore much of the viable parameter space. We also comment on dark matter decay inherent in a large class of previously considered models and explain how to ensure dark matter stability.

Cosmology and accelerator tests of strongly interacting dark matter

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

Berlin, Asher; Blinov, Nikita; Gori, Stefania

A natural possibility for dark matter is that it is composed of the stable pions of a QCD-like hidden sector. Existing literature largely assumes that pion self-interactions alone control the early universe cosmology. We point out that processes involving vector mesons typically dominate the physics of dark matter freeze-out and significantly widen the viable mass range for these models. The vector mesons also give rise to striking signals at accelerators. For example, in most of the cosmologically favored parameter space, the vector mesons are naturally long-lived and produce standard model particles in their decays. Electron and proton beam fixed-target experimentsmore » such as HPS, SeaQuest, and LDMX can exploit these signals to explore much of the viable parameter space. As a result, we also comment on dark matter decay inherent in a large class of previously considered models and explain how to ensure dark matter stability.« less

Axial vector Z‧ and anomaly cancellation

NASA Astrophysics Data System (ADS)

Ismail, Ahmed; Keung, Wai-Yee; Tsao, Kuo-Hsing; Unwin, James

2017-05-01

Whilst the prospect of new Z‧ gauge bosons with only axial couplings to the Standard Model (SM) fermions is widely discussed, examples of anomaly-free renormalisable models are lacking in the literature. We look to remedy this by constructing several motivated examples. Specifically, we consider axial vectors which couple universally to all SM fermions, as well as those which are generation-specific, leptophilic, and leptophobic. Anomaly cancellation typically requires the presence of new coloured and charged chiral fermions, and we argue that in a large class of models masses of these new states are expected to be comparable to that of the axial vector. Finally, an axial vector mediator could provide a portal between SM and hidden sector states, and we also consider the possibility that the axial vector couples to dark matter. If the dark matter relic density is set due to freeze-out via the axial vector, this strongly constrains the parameter space.

The Creation of Space Vector Models of Buildings From RPAS Photogrammetry Data

NASA Astrophysics Data System (ADS)

Trhan, Ondrej

2017-06-01

The results of Remote Piloted Aircraft System (RPAS) photogrammetry are digital surface models and orthophotos. The main problem of the digital surface models obtained is that buildings are not perpendicular and the shape of roofs is deformed. The task of this paper is to obtain a more accurate digital surface model using building reconstructions. The paper discusses the problem of obtaining and approximating building footprints, reconstructing the final spatial vector digital building model, and modifying the buildings on the digital surface model.

Vector space methods of photometric analysis - Applications to O stars and interstellar reddening

NASA Technical Reports Server (NTRS)

Massa, D.; Lillie, C. F.

1978-01-01

A multivariate vector-space formulation of photometry is developed which accounts for error propagation. An analysis of uvby and H-beta photometry of O stars is presented, with attention given to observational errors, reddening, general uvby photometry, early stars, and models of O stars. The number of observable parameters in O-star continua is investigated, the way these quantities compare with model-atmosphere predictions is considered, and an interstellar reddening law is derived. It is suggested that photospheric expansion affects the formation of the continuum in at least some O stars.

Multiple-output support vector machine regression with feature selection for arousal/valence space emotion assessment.

PubMed

Torres-Valencia, Cristian A; Álvarez, Mauricio A; Orozco-Gutiérrez, Alvaro A

2014-01-01

Human emotion recognition (HER) allows the assessment of an affective state of a subject. Until recently, such emotional states were described in terms of discrete emotions, like happiness or contempt. In order to cover a high range of emotions, researchers in the field have introduced different dimensional spaces for emotion description that allow the characterization of affective states in terms of several variables or dimensions that measure distinct aspects of the emotion. One of the most common of such dimensional spaces is the bidimensional Arousal/Valence space. To the best of our knowledge, all HER systems so far have modelled independently, the dimensions in these dimensional spaces. In this paper, we study the effect of modelling the output dimensions simultaneously and show experimentally the advantages in modeling them in this way. We consider a multimodal approach by including features from the Electroencephalogram and a few physiological signals. For modelling the multiple outputs, we employ a multiple output regressor based on support vector machines. We also include an stage of feature selection that is developed within an embedded approach known as Recursive Feature Elimination (RFE), proposed initially for SVM. The results show that several features can be eliminated using the multiple output support vector regressor with RFE without affecting the performance of the regressor. From the analysis of the features selected in smaller subsets via RFE, it can be observed that the signals that are more informative into the arousal and valence space discrimination are the EEG, Electrooculogram/Electromiogram (EOG/EMG) and the Galvanic Skin Response (GSR).

Exclusive vector meson production with leading neutrons in a saturation model for the dipole amplitude in mixed space

NASA Astrophysics Data System (ADS)

Amaral, J. T.; Becker, V. M.

2018-05-01

We investigate ρ vector meson production in e p collisions at HERA with leading neutrons in the dipole formalism. The interaction of the dipole and the pion is described in a mixed-space approach, in which the dipole-pion scattering amplitude is given by the Marquet-Peschanski-Soyez saturation model, which is based on the traveling wave solutions of the nonlinear Balitsky-Kovchegov equation. We estimate the magnitude of the absorption effects and compare our results with a previous analysis of the same process in full coordinate space. In contrast with this approach, the present study leads to absorption K factors in the range of those predicted by previous theoretical studies on semi-inclusive processes.

Supersymmetric dS/CFT

NASA Astrophysics Data System (ADS)

Hertog, Thomas; Tartaglino-Mazzucchelli, Gabriele; Van Riet, Thomas; Venken, Gerben

2018-02-01

We put forward new explicit realisations of dS/CFT that relate N = 2 supersymmetric Euclidean vector models with reversed spin-statistics in three dimensions to specific supersymmetric Vasiliev theories in four-dimensional de Sitter space. The partition function of the free supersymmetric vector model deformed by a range of low spin deformations that preserve supersymmetry appears to specify a well-defined wave function with asymptotic de Sitter boundary conditions in the bulk. In particular we find the wave function is globally peaked at undeformed de Sitter space, with a low amplitude for strong deformations. This suggests that supersymmetric de Sitter space is stable in higher-spin gravity and in particular free from ghosts. We speculate this is a limiting case of the de Sitter realizations in exotic string theories.

Simulation of an epidemic model with vector transmission

NASA Astrophysics Data System (ADS)

Dickman, Adriana G.; Dickman, Ronald

2015-03-01

We study a lattice model for vector-mediated transmission of a disease in a population consisting of two species, A and B, which contract the disease from one another. Individuals of species A are sedentary, while those of species B (the vector) diffuse in space. Examples of such diseases are malaria, dengue fever, and Pierce's disease in vineyards. The model exhibits a phase transition between an absorbing (infection free) phase and an active one as parameters such as infection rates and vector density are varied. We study the static and dynamic critical behavior of the model using initial spreading, initial decay, and quasistationary simulations. Simulations are checked against mean-field analysis. Although phase transitions to an absorbing state fall generically in the directed percolation universality class, this appears not to be the case for the present model.

Angular motion estimation using dynamic models in a gyro-free inertial measurement unit.

PubMed

Edwan, Ezzaldeen; Knedlik, Stefan; Loffeld, Otmar

2012-01-01

In this paper, we summarize the results of using dynamic models borrowed from tracking theory in describing the time evolution of the state vector to have an estimate of the angular motion in a gyro-free inertial measurement unit (GF-IMU). The GF-IMU is a special type inertial measurement unit (IMU) that uses only a set of accelerometers in inferring the angular motion. Using distributed accelerometers, we get an angular information vector (AIV) composed of angular acceleration and quadratic angular velocity terms. We use a Kalman filter approach to estimate the angular velocity vector since it is not expressed explicitly within the AIV. The bias parameters inherent in the accelerometers measurements' produce a biased AIV and hence the AIV bias parameters are estimated within an augmented state vector. Using dynamic models, the appended bias parameters of the AIV become observable and hence we can have unbiased angular motion estimate. Moreover, a good model is required to extract the maximum amount of information from the observation. Observability analysis is done to determine the conditions for having an observable state space model. For higher grades of accelerometers and under relatively higher sampling frequency, the error of accelerometer measurements is dominated by the noise error. Consequently, simulations are conducted on two models, one has bias parameters appended in the state space model and the other is a reduced model without bias parameters.

Angular Motion Estimation Using Dynamic Models in a Gyro-Free Inertial Measurement Unit

PubMed Central

Edwan, Ezzaldeen; Knedlik, Stefan; Loffeld, Otmar

2012-01-01

In this paper, we summarize the results of using dynamic models borrowed from tracking theory in describing the time evolution of the state vector to have an estimate of the angular motion in a gyro-free inertial measurement unit (GF-IMU). The GF-IMU is a special type inertial measurement unit (IMU) that uses only a set of accelerometers in inferring the angular motion. Using distributed accelerometers, we get an angular information vector (AIV) composed of angular acceleration and quadratic angular velocity terms. We use a Kalman filter approach to estimate the angular velocity vector since it is not expressed explicitly within the AIV. The bias parameters inherent in the accelerometers measurements' produce a biased AIV and hence the AIV bias parameters are estimated within an augmented state vector. Using dynamic models, the appended bias parameters of the AIV become observable and hence we can have unbiased angular motion estimate. Moreover, a good model is required to extract the maximum amount of information from the observation. Observability analysis is done to determine the conditions for having an observable state space model. For higher grades of accelerometers and under relatively higher sampling frequency, the error of accelerometer measurements is dominated by the noise error. Consequently, simulations are conducted on two models, one has bias parameters appended in the state space model and the other is a reduced model without bias parameters. PMID:22778586

An improved approach to infer protein-protein interaction based on a hierarchical vector space model.

PubMed

Zhang, Jiongmin; Jia, Ke; Jia, Jinmeng; Qian, Ying

2018-04-27

Comparing and classifying functions of gene products are important in today's biomedical research. The semantic similarity derived from the Gene Ontology (GO) annotation has been regarded as one of the most widely used indicators for protein interaction. Among the various approaches proposed, those based on the vector space model are relatively simple, but their effectiveness is far from satisfying. We propose a Hierarchical Vector Space Model (HVSM) for computing semantic similarity between different genes or their products, which enhances the basic vector space model by introducing the relation between GO terms. Besides the directly annotated terms, HVSM also takes their ancestors and descendants related by "is_a" and "part_of" relations into account. Moreover, HVSM introduces the concept of a Certainty Factor to calibrate the semantic similarity based on the number of terms annotated to genes. To assess the performance of our method, we applied HVSM to Homo sapiens and Saccharomyces cerevisiae protein-protein interaction datasets. Compared with TCSS, Resnik, and other classic similarity measures, HVSM achieved significant improvement for distinguishing positive from negative protein interactions. We also tested its correlation with sequence, EC, and Pfam similarity using online tool CESSM. HVSM showed an improvement of up to 4% compared to TCSS, 8% compared to IntelliGO, 12% compared to basic VSM, 6% compared to Resnik, 8% compared to Lin, 11% compared to Jiang, 8% compared to Schlicker, and 11% compared to SimGIC using AUC scores. CESSM test showed HVSM was comparable to SimGIC, and superior to all other similarity measures in CESSM as well as TCSS. Supplementary information and the software are available at https://github.com/kejia1215/HVSM .

Spectral flow as a map between N = (2 , 0)-models

NASA Astrophysics Data System (ADS)

Athanasopoulos, P.; Faraggi, A. E.; Gepner, D.

2014-07-01

The space of (2 , 0) models is of particular interest among all heterotic-string models because it includes the models with the minimal SO (10) unification structure, which is well motivated by the Standard Model of particle physics data. The fermionic Z2 ×Z2 heterotic-string models revealed the existence of a new symmetry in the space of string configurations under the exchange of spinors and vectors of the SO (10) GUT group, dubbed spinor-vector duality. In this paper we generalize this idea to arbitrary internal rational conformal field theories (RCFTs). We explain how the spectral flow operator normally acting within a general (2 , 2) theory can be used as a map between (2 , 0) models. We describe the details, give an example and propose more simple currents that can be used in a similar way.

Professor Herman Burger (1893-1965), eminent teacher and scientist, who laid the theoretical foundations of vectorcardiography--and electrocardiography.

PubMed

van Herpen, Gerard

2014-01-01

Einthoven not only designed a high quality instrument, the string galvanometer, for recording the ECG, he also shaped the conceptual framework to understand it. He reduced the body to an equilateral triangle and the cardiac electric activity to a dipole, represented by an arrow (i.e. a vector) in the triangle's center. Up to the present day the interpretation of the ECG is based on the model of a dipole vector being projected on the various leads. The model is practical but intuitive, not physically founded. Burger analysed the relation between heart vector and leads according to the principles of physics. It then follows that an ECG lead must be treated as a vector (lead vector) and that the lead voltage is not simply proportional to the projection of the vector on the lead, but must be multiplied by the value (length) of the lead vector, the lead strength. Anatomical lead axis and electrical lead axis are different entities and the anatomical body space must be distinguished from electrical space. Appreciation of these underlying physical principles should contribute to a better understanding of the ECG. The development of these principles by Burger is described, together with some personal notes and a sketch of the personality of this pioneer of medical physics. Copyright © 2014. Published by Elsevier Inc.

Secure coherent optical multi-carrier system with four-dimensional modulation space and Stokes vector scrambling.

PubMed

Zhang, Lijia; Liu, Bo; Xin, Xiangjun

2015-06-15

A secure enhanced coherent optical multi-carrier system based on Stokes vector scrambling is proposed and experimentally demonstrated. The optical signal with four-dimensional (4D) modulation space has been scrambled intra- and inter-subcarriers, where a multi-layer logistic map is adopted as the chaotic model. An experiment with 61.71-Gb/s encrypted multi-carrier signal is successfully demonstrated with the proposed method. The results indicate a promising solution for the physical secure optical communication.

The effects of vector leptoquark on the ℬb(ℬ = Λ,Σ) →ℬμ+μ- decays

NASA Astrophysics Data System (ADS)

Wang, Shuai-Wei; Huang, Jin-Shu

2016-07-01

In this paper, we have studied the baryonic semileptonic ℬb(ℬ = Λ, Σ) →ℬμ+μ- decays in the vector leptoquark model with U = (3, 3, 2/3) state. Using the parameters’ space constrained through some well-measured decay modes, such as Bs → μ+μ-, Bs -B¯s mixing and B → K∗μ+μ- decays, we show the effects of vector leptoquark state on the double lepton polarization asymmetries of ℬb(ℬ = Λ, Σ) →ℬμ+μ- decays, and find that the double lepton polarization asymmetries, except for PLL, PLN and PNL, are sensitive to the contributions of vector leptoquark model.

Enhanced secure 4-D modulation space optical multi-carrier system based on joint constellation and Stokes vector scrambling.

PubMed

Liu, Bo; Zhang, Lijia; Xin, Xiangjun

2018-03-19

This paper proposes and demonstrates an enhanced secure 4-D modulation optical generalized filter bank multi-carrier (GFBMC) system based on joint constellation and Stokes vector scrambling. The constellation and Stokes vectors are scrambled by using different scrambling parameters. A multi-scroll Chua's circuit map is adopted as the chaotic model. Large secure key space can be obtained due to the multi-scroll attractors and independent operability of subcarriers. A 40.32Gb/s encrypted optical GFBMC signal with 128 parallel subcarriers is successfully demonstrated in the experiment. The results show good resistance against the illegal receiver and indicate a potential way for the future optical multi-carrier system.

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.

Notes from 1999 on computational algorithm of the Local Wave-Vector (LWV) model for the dynamical evolution of the second-rank velocity correlation tensor starting from the mean-flow-coupled Navier-Stokes equations

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

Zemach, Charles; Kurien, Susan

These notes present an account of the Local Wave Vector (LWV) model of a turbulent flow defined throughout physical space. The previously-developed Local Wave Number (LWN) model is taken as a point of departure. Some general properties of turbulent fields and appropriate notation are given first. The LWV model is presently restricted to incompressible flows and the incompressibility assumption is introduced at an early point in the discussion. The assumption that the turbulence is homogeneous is also introduced early on. This assumption can be relaxed by generalizing the space diffusion terms of LWN, but the present discussion is focused onmore » a modeling of homogeneous turbulence.« less

Use of Mapping and Spatial and Space-Time Modeling Approaches in Operational Control of Aedes aegypti and Dengue

PubMed Central

Eisen, Lars; Lozano-Fuentes, Saul

2009-01-01

The aims of this review paper are to 1) provide an overview of how mapping and spatial and space-time modeling approaches have been used to date to visualize and analyze mosquito vector and epidemiologic data for dengue; and 2) discuss the potential for these approaches to be included as routine activities in operational vector and dengue control programs. Geographical information system (GIS) software are becoming more user-friendly and now are complemented by free mapping software that provide access to satellite imagery and basic feature-making tools and have the capacity to generate static maps as well as dynamic time-series maps. Our challenge is now to move beyond the research arena by transferring mapping and GIS technologies and spatial statistical analysis techniques in user-friendly packages to operational vector and dengue control programs. This will enable control programs to, for example, generate risk maps for exposure to dengue virus, develop Priority Area Classifications for vector control, and explore socioeconomic associations with dengue risk. PMID:19399163

A flippon related singlet at the LHC II

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

Li, Tianjun; Maxin, James A.; Mayes, Van E.

2016-06-28

Here, we consider the 750 GeV diphoton resonance at the 13 TeV LHC in the ℱ-SU(5) model with a Standard Model (SM) singlet field which couples to TeV-scale vector-like particles, dubbed flippons. This singlet field assumes the role of the 750 GeV resonance, with production via gluon fusion and subsequent decay to a diphoton via the vector-like particle loops. We present a numerical analysis showing that the observed 8 TeV and 13 TeV diphoton production cross-sections can be generated in the model space with realistic electric charges and Yukawa couplings for light vector-like masses. We further discuss the experimental viabilitymore » of light vector-like masses in a General No-Scale ℱ-SU(5) model, offering a few benchmark scenarios in this consistent GUT that can satisfy all experimental constraints imposed by the LHC and other essential experiments.« less

Approximate Bayesian Computation by Subset Simulation using hierarchical state-space models

NASA Astrophysics Data System (ADS)

Vakilzadeh, Majid K.; Huang, Yong; Beck, James L.; Abrahamsson, Thomas

2017-02-01

A new multi-level Markov Chain Monte Carlo algorithm for Approximate Bayesian Computation, ABC-SubSim, has recently appeared that exploits the Subset Simulation method for efficient rare-event simulation. ABC-SubSim adaptively creates a nested decreasing sequence of data-approximating regions in the output space that correspond to increasingly closer approximations of the observed output vector in this output space. At each level, multiple samples of the model parameter vector are generated by a component-wise Metropolis algorithm so that the predicted output corresponding to each parameter value falls in the current data-approximating region. Theoretically, if continued to the limit, the sequence of data-approximating regions would converge on to the observed output vector and the approximate posterior distributions, which are conditional on the data-approximation region, would become exact, but this is not practically feasible. In this paper we study the performance of the ABC-SubSim algorithm for Bayesian updating of the parameters of dynamical systems using a general hierarchical state-space model. We note that the ABC methodology gives an approximate posterior distribution that actually corresponds to an exact posterior where a uniformly distributed combined measurement and modeling error is added. We also note that ABC algorithms have a problem with learning the uncertain error variances in a stochastic state-space model and so we treat them as nuisance parameters and analytically integrate them out of the posterior distribution. In addition, the statistical efficiency of the original ABC-SubSim algorithm is improved by developing a novel strategy to regulate the proposal variance for the component-wise Metropolis algorithm at each level. We demonstrate that Self-regulated ABC-SubSim is well suited for Bayesian system identification by first applying it successfully to model updating of a two degree-of-freedom linear structure for three cases: globally, locally and un-identifiable model classes, and then to model updating of a two degree-of-freedom nonlinear structure with Duffing nonlinearities in its interstory force-deflection relationship.

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

Khachatryan, Vardan

A search is presented for an excess of events with large missing transverse momentum in association with at least one highly energetic jet, in a data sample of proton-proton collisions at a centre-of-mass energy of 8 TeV. The data correspond to an integrated luminosity of 19.7 inverse femtobarns collected by the CMS experiment at the LHC. The results are interpreted using a set of simplified models for the production of dark matter via a scalar, pseudoscalar, vector, or axial vector mediator. Additional sensitivity is achieved by tagging events consistent with the jets originating from a hadronically decaying vector boson. Thismore » search uses jet substructure techniques to identify hadronically decaying vector bosons in both Lorentz-boosted and resolved scenarios. This analysis yields improvements of 80% in terms of excluded signal cross sections with respect to the previous CMS analysis using the same data set. No significant excess with respect to the standard model expectation is observed and limits are placed on the parameter space of the simplified models. As a result, mediator masses between 80 and 400 GeV in the scalar and pseudoscalar models, and up to 1.5 TeV in the vector and axial vector models, are excluded.« less

Search for dark matter in proton-proton collisions at 8 TeV with missing transverse momentum and vector boson tagged jets

DOE PAGES

Khachatryan, Vardan

2016-12-16

A search is presented for an excess of events with large missing transverse momentum in association with at least one highly energetic jet, in a data sample of proton-proton collisions at a centre-of-mass energy of 8 TeV. The data correspond to an integrated luminosity of 19.7 inverse femtobarns collected by the CMS experiment at the LHC. The results are interpreted using a set of simplified models for the production of dark matter via a scalar, pseudoscalar, vector, or axial vector mediator. Additional sensitivity is achieved by tagging events consistent with the jets originating from a hadronically decaying vector boson. Thismore » search uses jet substructure techniques to identify hadronically decaying vector bosons in both Lorentz-boosted and resolved scenarios. This analysis yields improvements of 80% in terms of excluded signal cross sections with respect to the previous CMS analysis using the same data set. No significant excess with respect to the standard model expectation is observed and limits are placed on the parameter space of the simplified models. As a result, mediator masses between 80 and 400 GeV in the scalar and pseudoscalar models, and up to 1.5 TeV in the vector and axial vector models, are excluded.« less

Search for dark matter in proton-proton collisions at 8 TeV with missing transverse momentum and vector boson tagged jets

NASA Astrophysics Data System (ADS)

CMS Collaboration; Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; König, A.; Krätschmer, I.; Liko, D.; Matsushita, T.; Mikulec, I.; Rabady, D.; Rad, N.; Rahbaran, B.; Rohringer, H.; Schieck, J.; Strauss, J.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; De Wolf, E. A.; Janssen, X.; Lauwers, J.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; Daci, N.; De Bruyn, I.; Deroover, K.; Heracleous, N.; Lowette, S.; Moortgat, S.; Moreels, L.; Olbrechts, A.; Python, Q.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Brun, H.; Caillol, C.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; Léonard, A.; Luetic, J.; Maerschalk, T.; Marinov, A.; Randle-conde, A.; Seva, T.; Vander Velde, C.; Vanlaer, P.; Yonamine, R.; Zenoni, F.; Zhang, F.; Cimmino, A.; Cornelis, T.; Dobur, D.; Fagot, A.; Garcia, G.; Gul, M.; Poyraz, D.; Salva, S.; Schöfbeck, R.; Tytgat, M.; Van Driessche, W.; Yazgan, E.; Zaganidis, N.; Bakhshiansohi, H.; Beluffi, C.; Bondu, O.; Brochet, S.; Bruno, G.; Caudron, A.; De Visscher, S.; Delaere, C.; Delcourt, M.; Forthomme, L.; Francois, B.; Giammanco, A.; Jafari, A.; Jez, P.; Komm, M.; Lemaitre, V.; Magitteri, A.; Mertens, A.; Musich, M.; Nuttens, C.; Piotrzkowski, K.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Wertz, S.; Beliy, N.; Aldá Júnior, W. L.; Alves, F. L.; Alves, G. A.; Brito, L.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Huertas Guativa, L. M.; Malbouisson, H.; Matos Figueiredo, D.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; Dogra, S.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Moon, C. S.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Cheng, T.; Jiang, C. H.; Leggat, D.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Zhang, H.; Zhao, J.; Ban, Y.; Chen, G.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Avila, C.; Cabrera, A.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; González Hernández, C. F.; Ruiz Alvarez, J. D.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Puljak, I.; Ribeiro Cipriano, P. M.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Micanovic, S.; Sudic, L.; Susa, T.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Finger, M.; Finger, M.; Carrera Jarrin, E.; Abdelalim, A. A.; Mohammed, Y.; Salama, E.; Calpas, B.; Kadastik, M.; Murumaa, M.; Perrini, L.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Pekkanen, J.; Voutilainen, M.; Härkönen, J.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Peltola, T.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Ghosh, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Kucher, I.; Locci, E.; Machet, M.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Zghiche, A.; Abdulsalam, A.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Chapon, E.; Charlot, C.; Davignon, O.; Granier de Cassagnac, R.; Jo, M.; Lisniak, S.; Miné, P.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Regnard, S.; Salerno, R.; Sirois, Y.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Agram, J.-L.; Andrea, J.; Aubin, A.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Le Bihan, A.-C.; Merlin, J. A.; Skovpen, K.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Bouvier, E.; Carrillo Montoya, C. A.; Chierici, R.; Contardo, D.; Courbon, B.; Depasse, P.; El Mamouni, H.; Fan, J.; Fay, J.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Popov, A.; Sabes, D.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Toriashvili, T.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Feld, L.; Heister, A.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Ostapchuk, A.; Preuten, M.; Raupach, F.; Schael, S.; Schomakers, C.; Schulte, J. F.; Schulz, J.; Verlage, T.; Weber, H.; Zhukov, V.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hamer, M.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Olschewski, M.; Padeken, K.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Cherepanov, V.; Flügge, G.; Haj Ahmad, W.; Hoehle, F.; Kargoll, B.; Kress, T.; Künsken, A.; Lingemann, J.; Nehrkorn, A.; Nowack, A.; Nugent, I. M.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Asawatangtrakuldee, C.; Beernaert, K.; Behnke, O.; Behrens, U.; Bin Anuar, A. A.; Borras, K.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Diez Pardos, C.; Dolinska, G.; Eckerlin, G.; Eckstein, D.; Eren, E.; Gallo, E.; Garay Garcia, J.; Geiser, A.; Gizhko, A.; Grados Luyando, J. M.; Gunnellini, P.; Harb, A.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; Karacheban, O.; Kasemann, M.; Keaveney, J.; Kieseler, J.; Kleinwort, C.; Korol, I.; Krücker, D.; Lange, W.; Lelek, A.; Leonard, J.; Lipka, K.; Lobanov, A.; Lohmann, W.; Mankel, R.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Ntomari, E.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Roland, B.; Sahin, M. Ö.; Saxena, P.; Schoerner-Sadenius, T.; Seitz, C.; Spannagel, S.; Stefaniuk, N.; Trippkewitz, K. D.; Van Onsem, G. P.; Walsh, R.; Wissing, C.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Dreyer, T.; Garutti, E.; Goebel, K.; Gonzalez, D.; Haller, J.; Hoffmann, M.; Junkes, A.; Klanner, R.; Kogler, R.; Kovalchuk, N.; Lapsien, T.; Lenz, T.; Marchesini, I.; Marconi, D.; Meyer, M.; Niedziela, M.; Nowatschin, D.; Ott, J.; Pantaleo, F.; Peiffer, T.; Perieanu, A.; Poehlsen, J.; Sander, C.; Scharf, C.; Schleper, P.; Schmidt, A.; Schumann, S.; Schwandt, J.; Stadie, H.; Steinbrück, G.; Stober, F. M.; Stöver, M.; Tholen, H.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Vormwald, B.; Barth, C.; Baus, C.; Berger, J.; Butz, E.; Chwalek, T.; Colombo, F.; De Boer, W.; Dierlamm, A.; Fink, S.; Friese, R.; Giffels, M.; Gilbert, A.; Goldenzweig, P.; Haitz, D.; Hartmann, F.; Heindl, S. M.; Husemann, U.; Katkov, I.; Lobelle Pardo, P.; Maier, B.; Mildner, H.; Mozer, M. U.; Müller, T.; Müller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; Röcker, S.; Roscher, F.; Schröder, M.; Shvetsov, I.; Sieber, G.; Simonis, H. J.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weber, M.; Weiler, T.; Williamson, S.; Wöhrmann, C.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Topsis-Giotis, I.; Agapitos, A.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Tziaferi, E.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Loukas, N.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Filipovic, N.; Bencze, G.; Hajdu, C.; Hidas, P.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Makovec, A.; Molnar, J.; Szillasi, Z.; Bartók, M.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Bahinipati, S.; Choudhury, S.; Mal, P.; Mandal, K.; Nayak, A.; Sahoo, D. K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Chawla, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kumar, R.; Mehta, A.; Mittal, M.; Singh, J. B.; Walia, G.; Kumar, Ashok; Bhardwaj, A.; Choudhary, B. C.; Garg, R. B.; Keshri, S.; Malhotra, S.; Naimuddin, M.; Nishu, N.; Ranjan, K.; Sharma, R.; Sharma, V.; Bhattacharya, R.; Bhattacharya, S.; Chatterjee, K.; Dey, S.; Dutt, S.; Dutta, S.; Ghosh, S.; Majumdar, N.; Modak, A.; Mondal, K.; Mukhopadhyay, S.; Nandan, S.; Purohit, A.; Roy, A.; Roy, D.; Roy Chowdhury, S.; Sarkar, S.; Sharan, M.; Thakur, S.; Behera, P. K.; Chudasama, R.; Dutta, D.; Jha, V.; Kumar, V.; Mohanty, A. K.; Netrakanti, P. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Dugad, S.; Kole, G.; Mahakud, B.; Mitra, S.; Mohanty, G. B.; Parida, B.; Sur, N.; Sutar, B.; Banerjee, S.; Bhowmik, S.; Dewanjee, R. K.; Ganguly, S.; Guchait, M.; Jain, Sa.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Sarkar, T.; Wickramage, N.; Chauhan, S.; Dube, S.; Hegde, V.; Kapoor, A.; Kothekar, K.; Rane, A.; Sharma, S.; Behnamian, H.; Chenarani, S.; Eskandari Tadavani, E.; Etesami, S. M.; Fahim, A.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Caputo, C.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Battilana, C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Chhibra, S. S.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Albergo, S.; Chiorboli, M.; Costa, S.; Di Mattia, A.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Gori, V.; Lenzi, P.; Meschini, M.; Paoletti, S.; Sguazzoni, G.; Viliani, L.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Primavera, F.; Calvelli, V.; Ferro, F.; Lo Vetere, M.; Monge, M. R.; Robutti, E.; Tosi, S.; Brianza, L.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Ghezzi, A.; Govoni, P.; Malvezzi, S.; Manzoni, R. A.; Marzocchi, B.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Pigazzini, S.; Ragazzi, S.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; De Nardo, G.; Di Guida, S.; Esposito, M.; Fabozzi, F.; Iorio, A. O. M.; Lanza, G.; Lista, L.; Meola, S.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Benato, L.; Bisello, D.; Boletti, A.; Carlin, R.; Carvalho Antunes De Oliveira, A.; Checchia, P.; Dall'Osso, M.; De Castro Manzano, P.; Dorigo, T.; Dosselli, U.; Gasparini, F.; Gasparini, U.; Gozzelino, A.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Simonetto, F.; Torassa, E.; Zanetti, M.; Zotto, P.; Zucchetta, A.; Zumerle, G.; Braghieri, A.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Leonardi, R.; Mantovani, G.; Menichelli, M.; Saha, A.; Santocchia, A.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Donato, S.; Fedi, G.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Palla, F.; Rizzi, A.; SavoyNavarro, A.; Spagnolo, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Barone, L.; Cavallari, F.; Cipriani, M.; D'imperio, G.; Del Re, D.; Diemoz, M.; Gelli, S.; Jorda, C.; Longo, E.; Margaroli, F.; Meridiani, P.; Organtini, G.; Paramatti, R.; Preiato, F.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bartosik, N.; Bellan, R.; Biino, C.; Cartiglia, N.; Cenna, F.; Costa, M.; Covarelli, R.; Degano, A.; Demaria, N.; Finco, L.; Kiani, B.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Monteil, E.; Obertino, M. M.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Ravera, F.; Romero, A.; Ruspa, M.; Sacchi, R.; Shchelina, K.; Sola, V.; Solano, A.; Staiano, A.; Traczyk, P.; Belforte, S.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; La Licata, C.; Schizzi, A.; Zanetti, A.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Lee, S.; Lee, S. W.; Oh, Y. D.; Sekmen, S.; Son, D. C.; Yang, Y. C.; Lee, A.; Brochero Cifuentes, J. A.; Kim, T. J.; Cho, S.; Choi, S.; Go, Y.; Gyun, D.; Ha, S.; Hong, B.; Jo, Y.; Kim, Y.; Lee, B.; Lee, K.; Lee, K. S.; Lee, S.; Lim, J.; Park, S. K.; Roh, Y.; Almond, J.; Kim, J.; Oh, S. B.; Seo, S. h.; Yang, U. K.; Yoo, H. D.; Yu, G. B.; Choi, M.; Kim, H.; Kim, H.; Kim, J. H.; Lee, J. S. H.; Park, I. C.; Ryu, G.; Ryu, M. S.; Choi, Y.; Goh, J.; Hwang, C.; Lee, J.; Yu, I.; Dudenas, V.; Juodagalvis, A.; Vaitkus, J.; Ahmed, I.; Ibrahim, Z. A.; Komaragiri, J. R.; Md Ali, M. A. B.; Mohamad Idris, F.; Wan Abdullah, W. A. T.; Yusli, M. N.; Zolkapli, Z.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-De La Cruz, I.; Hernandez-Almada, A.; Lopez-Fernandez, R.; Magaña Villalba, R.; Mejia Guisao, J.; Sanchez-Hernandez, A.; Carrillo Moreno, S.; Oropeza Barrera, C.; Vazquez Valencia, F.; Carpinteyro, S.; Pedraza, I.; Salazar Ibarguen, H. A.; Uribe Estrada, C.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Khan, W. A.; Shah, M. A.; Shoaib, M.; Waqas, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Romanowska-Rybinska, K.; Szleper, M.; Zalewski, P.; Bunkowski, K.; Byszuk, A.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Walczak, M.; Bargassa, P.; Beirão Da Cruz E Silva, C.; Di Francesco, A.; Faccioli, P.; Ferreira Parracho, P. G.; Gallinaro, M.; Hollar, J.; Leonardo, N.; Lloret Iglesias, L.; Nemallapudi, M. V.; Rodrigues Antunes, J.; Seixas, J.; Toldaiev, O.; Vadruccio, D.; Varela, J.; Vischia, P.; Afanasiev, S.; Bunin, P.; Gavrilenko, M.; Golutvin, I.; Gorbunov, I.; Kamenev, A.; Karjavin, V.; Lanev, A.; Malakhov, A.; Matveev, V.; Moisenz, P.; Palichik, V.; Perelygin, V.; Shmatov, S.; Shulha, S.; Skatchkov, N.; Smirnov, V.; Voytishin, N.; Zarubin, A.; Chtchipounov, L.; Golovtsov, V.; Ivanov, Y.; Kim, V.; Kuznetsova, E.; Murzin, V.; Oreshkin, V.; Sulimov, V.; Vorobyev, A.; Andreev, Yu.; Dermenev, A.; Gninenko, S.; Golubev, N.; Karneyeu, A.; Kirsanov, M.; Krasnikov, N.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Gavrilov, V.; Lychkovskaya, N.; Popov, V.; Pozdnyakov, I.; Safronov, G.; Spiridonov, A.; Toms, M.; Vlasov, E.; Zhokin, A.; Bylinkin, A.; Chistov, R.; Danilov, M.; Rusinov, V.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Leonidov, A.; Rusakov, S. V.; Terkulov, A.; Baskakov, A.; Belyaev, A.; Boos, E.; Dubinin, M.; Dudko, L.; Ershov, A.; Gribushin, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Miagkov, I.; Obraztsov, S.; Petrushanko, S.; Savrin, V.; Snigirev, A.; Blinov, V.; Skovpen, Y.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Elumakhov, D.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Cirkovic, P.; Devetak, D.; Dordevic, M.; Milosevic, J.; Rekovic, V.; Alcaraz Maestre, J.; Barrio Luna, M.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Escalante Del Valle, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Navarro De Martino, E.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; de Trocóniz, J. F.; Missiroli, M.; Moran, D.; Cuevas, J.; Fernandez Menendez, J.; Gonzalez Caballero, I.; González Fernández, J. R.; Palencia Cortezon, E.; Sanchez Cruz, S.; Suárez Andrés, I.; Vizan Garcia, J. M.; Cabrillo, I. J.; Calderon, A.; Castiñeiras De Saa, J. R.; Curras, E.; Fernandez, M.; Garcia-Ferrero, J.; Gomez, G.; Lopez Virto, A.; Marco, J.; Martinez Rivero, C.; Matorras, F.; Piedra Gomez, J.; Rodrigo, T.; Ruiz-Jimeno, A.; Scodellaro, L.; Trevisani, N.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Auffray, E.; Auzinger, G.; Bachtis, M.; Baillon, P.; Ball, A. H.; Barney, D.; Bloch, P.; Bocci, A.; Bonato, A.; Botta, C.; Camporesi, T.; Castello, R.; Cepeda, M.; Cerminara, G.; D'Alfonso, M.; d'Enterria, D.; Dabrowski, A.; Daponte, V.; David, A.; De Gruttola, M.; De Guio, F.; De Roeck, A.; Di Marco, E.; Dobson, M.; Dorney, B.; du Pree, T.; Duggan, D.; Dünser, M.; Dupont, N.; Elliott-Peisert, A.; Fartoukh, S.; Franzoni, G.; Fulcher, J.; Funk, W.; Gigi, D.; Gill, K.; Girone, M.; Glege, F.; Gulhan, D.; Gundacker, S.; Guthoff, M.; Hammer, J.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Kirschenmann, H.; Knünz, V.; Kornmayer, A.; Kortelainen, M. J.; Kousouris, K.; Krammer, M.; Lecoq, P.; Lourenço, C.; Lucchini, M. T.; Malgeri, L.; Mannelli, M.; Martelli, A.; Meijers, F.; Mersi, S.; Meschi, E.; Moortgat, F.; Morovic, S.; Mulders, M.; Neugebauer, H.; Orfanelli, S.; Orsini, L.; Pape, L.; Perez, E.; Peruzzi, M.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Racz, A.; Reis, T.; Rolandi, G.; Rovere, M.; Ruan, M.; Sakulin, H.; Sauvan, J. B.; Schäfer, C.; Schwick, C.; Seidel, M.; Sharma, A.; Silva, P.; Simon, M.; Sphicas, P.; Steggemann, J.; Stoye, M.; Takahashi, Y.; Tosi, M.; Treille, D.; Triossi, A.; Tsirou, A.; Veckalns, V.; Veres, G. I.; Wardle, N.; Zagozdzinska, A.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Casal, B.; Dissertori, G.; Dittmar, M.; Donegà, M.; Eller, P.; Grab, C.; Heidegger, C.; Hits, D.; Hoss, J.; Kasieczka, G.; Lecomte, P.; Lustermann, W.; Mangano, B.; Marionneau, M.; Martinez Ruiz del Arbol, P.; Masciovecchio, M.; Meinhard, M. T.; Meister, D.; Micheli, F.; Musella, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pata, J.; Pauss, F.; Perrin, G.; Perrozzi, L.; Quittnat, M.; Rossini, M.; Schönenberger, M.; Starodumov, A.; Tavolaro, V. R.; Theofilatos, K.; Wallny, R.; Aarrestad, T. K.; Amsler, C.; Caminada, L.; Canelli, M. F.; De Cosa, A.; Galloni, C.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Lange, C.; Ngadiuba, J.; Pinna, D.; Rauco, G.; Robmann, P.; Salerno, D.; Yang, Y.; Candelise, V.; Doan, T. H.; Jain, Sh.; Khurana, R.; Konyushikhin, M.; Kuo, C. M.; Lin, W.; Lu, Y. J.; Pozdnyakov, A.; Yu, S. S.; Kumar, Arun; Chang, P.; Chang, Y. H.; Chang, Y. W.; Chao, Y.; Chen, K. F.; Chen, P. H.; Dietz, C.; Fiori, F.; Hou, W.-S.; Hsiung, Y.; Liu, Y. F.; Lu, R.-S.; Miñano Moya, M.; Paganis, E.; Psallidas, A.; Tsai, J. f.; Tzeng, Y. M.; Asavapibhop, B.; Singh, G.; Srimanobhas, N.; Suwonjandee, N.; Adiguzel, A.; Cerci, S.; Damarseckin, S.; Demiroglu, Z. S.; Dozen, C.; Dumanoglu, I.; Girgis, S.; Gokbulut, G.; Guler, Y.; Gurpinar, E.; Hos, I.; Kangal, E. E.; Kara, O.; Kiminsu, U.; Oglakci, M.; Onengut, G.; Ozdemir, K.; Sunar Cerci, D.; Tali, B.; Topakli, H.; Turkcapar, S.; Zorbakir, I. S.; Zorbilmez, C.; Bilin, B.; Bilmis, S.; Isildak, B.; Karapinar, G.; Yalvac, M.; Zeyrek, M.; Gülmez, E.; Kaya, M.; Kaya, O.; Yetkin, E. A.; Yetkin, T.; Cakir, A.; Cankocak, K.; Sen, S.; Grynyov, B.; Levchuk, L.; Sorokin, P.; Aggleton, R.; Ball, F.; Beck, L.; Brooke, J. J.; Burns, D.; Clement, E.; Cussans, D.; Flacher, H.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Jacob, J.; Kreczko, L.; Lucas, C.; Newbold, D. M.; Paramesvaran, S.; Poll, A.; Sakuma, T.; Seif El Nasr-storey, S.; Smith, D.; Smith, V. J.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Calligaris, L.; Cieri, D.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Williams, T.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Bundock, A.; Burton, D.; Casasso, S.; Citron, M.; Colling, D.; Corpe, L.; Dauncey, P.; Davies, G.; De Wit, A.; Della Negra, M.; Di Maria, R.; Dunne, P.; Elwood, A.; Futyan, D.; Haddad, Y.; Hall, G.; Iles, G.; James, T.; Lane, R.; Laner, C.; Lucas, R.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mastrolorenzo, L.; Nash, J.; Nikitenko, A.; Pela, J.; Penning, B.; Pesaresi, M.; Raymond, D. M.; Richards, A.; Rose, A.; Seez, C.; Summers, S.; Tapper, A.; Uchida, K.; Vazquez Acosta, M.; Virdee, T.; Wright, J.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Leslie, D.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Borzou, A.; Call, K.; Dittmann, J.; Hatakeyama, K.; Liu, H.; Pastika, N.; Charaf, O.; Cooper, S. I.; Henderson, C.; Rumerio, P.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Berry, E.; Cutts, D.; Garabedian, A.; Hakala, J.; Heintz, U.; Hogan, J. M.; Jesus, O.; Laird, E.; Landsberg, G.; Mao, Z.; Narain, M.; Piperov, S.; Sagir, S.; Spencer, E.; Syarif, R.; Breedon, R.; Breto, G.; Burns, D.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Gardner, M.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Ricci-Tam, F.; Shalhout, S.; Smith, J.; Squires, M.; Stolp, D.; Tripathi, M.; Wilbur, S.; Yohay, R.; Cousins, R.; Everaerts, P.; Florent, A.; Hauser, J.; Ignatenko, M.; Saltzberg, D.; Takasugi, E.; Valuev, V.; Weber, M.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Hanson, G.; Heilman, J.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Malberti, M.; Olmedo Negrete, M.; Paneva, M. I.; Shrinivas, A.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; Derdzinski, M.; Gerosa, R.; Holzner, A.; Klein, D.; Krutelyov, V.; Letts, J.; Macneill, I.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Vartak, A.; Wasserbaech, S.; Welke, C.; Wood, J.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; Bhandari, R.; Bradmiller-Feld, J.; Campagnari, C.; Dishaw, A.; Dutta, V.; Flowers, K.; Franco Sevilla, M.; Geffert, P.; George, C.; Golf, F.; Gouskos, L.; Gran, J.; Heller, R.; Incandela, J.; Mccoll, N.; Mullin, S. D.; Ovcharova, A.; Richman, J.; Stuart, D.; Suarez, I.; West, C.; Yoo, J.; Anderson, D.; Apresyan, A.; Bendavid, J.; Bornheim, A.; Bunn, J.; Chen, Y.; Duarte, J.; Lawhorn, J. M.; Mott, A.; Newman, H. B.; Pena, C.; Spiropulu, M.; Vlimant, J. R.; Xie, S.; Zhu, R. Y.; Andrews, M. B.; Azzolini, V.; Carlson, B.; Ferguson, T.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Ford, W. T.; Jensen, F.; Johnson, A.; Krohn, M.; Mulholland, T.; Stenson, K.; Wagner, S. R.; Alexander, J.; Chaves, J.; Chu, J.; Dittmer, S.; Mcdermott, K.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Tan, S. M.; Tao, Z.; Thom, J.; Tucker, J.; Wittich, P.; Zientek, M.; Winn, D.; Abdullin, S.; Albrow, M.; Apollinari, G.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Cremonesi, M.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hare, D.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; Hu, Z.; Jayatilaka, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kreis, B.; Lammel, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, T.; Lopes De Sá, R.; Lykken, J.; Maeshima, K.; Magini, N.; Marraffino, J. M.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Ristori, L.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; Strobbe, N.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vernieri, C.; Verzocchi, M.; Vidal, R.; Wang, M.; Weber, H. A.; Whitbeck, A.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Brinkerhoff, A.; Carnes, A.; Carver, M.; Curry, D.; Das, S.; Field, R. D.; Furic, I. K.; Konigsberg, J.; Korytov, A.; Ma, P.; Matchev, K.; Mei, H.; Milenovic, P.; Mitselmakher, G.; Rank, D.; Shchutska, L.; Sperka, D.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Ackert, A.; Adams, J. R.; Adams, T.; Askew, A.; Bein, S.; Diamond, B.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Khatiwada, A.; Prosper, H.; Santra, A.; Weinberg, M.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Noonan, D.; Roy, T.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Kurt, P.; O'Brien, C.; Sandoval Gonzalez, I. D.; Turner, P.; Varelas, N.; Wang, H.; Wu, Z.; Zakaria, M.; Zhang, J.; Bilki, B.; Clarida, W.; Dilsiz, K.; Durgut, S.; Gandrajula, R. P.; Haytmyradov, M.; Khristenko, V.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Snyder, C.; Tiras, E.; Wetzel, J.; Yi, K.; Anderson, I.; Blumenfeld, B.; Cocoros, A.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Osherson, M.; Roskes, J.; Sarica, U.; Swartz, M.; Xiao, M.; Xin, Y.; You, C.; Al-bataineh, A.; Baringer, P.; Bean, A.; Bowen, J.; Bruner, C.; Castle, J.; Kenny, R. P.; Kropivnitskaya, A.; Majumder, D.; Mcbrayer, W.; Murray, M.; Sanders, S.; Stringer, R.; Tapia Takaki, J. D.; Wang, Q.; Ivanov, A.; Kaadze, K.; Khalil, S.; Makouski, M.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Toda, S.; Lange, D.; Rebassoo, F.; Wright, D.; Anelli, C.; Baden, A.; Baron, O.; Belloni, A.; Calvert, B.; Eno, S. C.; Ferraioli, C.; Gomez, J. A.; Hadley, N. J.; Jabeen, S.; Kellogg, R. G.; Kolberg, T.; Kunkle, J.; Lu, Y.; Mignerey, A. C.; Shin, Y. H.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Abercrombie, D.; Allen, B.; Apyan, A.; Barbieri, R.; Baty, A.; Bi, R.; Bierwagen, K.; Brandt, S.; Busza, W.; Cali, I. A.; Demiragli, Z.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Hsu, D.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Krajczar, K.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Sumorok, K.; Tatar, K.; Varma, M.; Velicanu, D.; Veverka, J.; Wang, J.; Wang, T. W.; Wyslouch, B.; Yang, M.; Zhukova, V.; Benvenuti, A. C.; Chatterjee, R. M.; Evans, A.; Finkel, A.; Gude, A.; Hansen, P.; Kalafut, S.; Kao, S. C.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bartek, R.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Knowlton, D.; Kravchenko, I.; Malta Rodrigues, A.; Meier, F.; Monroy, J.; Siado, J. E.; Snow, G. R.; Stieger, B.; Alyari, M.; Dolen, J.; George, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Kaisen, J.; Kharchilava, A.; Kumar, A.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Baumgartel, D.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Teixeira De Lima, R.; Trocino, D.; Wang, R.-J.; Wood, D.; Bhattacharya, S.; Hahn, K. A.; Kubik, A.; Kumar, A.; Low, J. F.; Mucia, N.; Odell, N.; Pollack, B.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Dev, N.; Hildreth, M.; Hurtado Anampa, K.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Smith, G.; Taroni, S.; Valls, N.; Wayne, M.; Wolf, M.; Woodard, A.; Alimena, J.; Antonelli, L.; Brinson, J.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Francis, B.; Hart, A.; Hill, C.; Hughes, R.; Ji, W.; Liu, B.; Luo, W.; Puigh, D.; Winer, B. L.; Wulsin, H. W.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Luo, J.; Marlow, D.; Medvedeva, T.; Mei, K.; Mooney, M.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Tully, C.; Zuranski, A.; Malik, S.; Barker, A.; Barnes, V. E.; Folgueras, S.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Jung, K.; Miller, D. H.; Neumeister, N.; Radburn-Smith, B. C.; Shi, X.; Sun, J.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Chen, Z.; Ecklund, K. M.; Geurts, F. J. M.; Guilbaud, M.; Li, W.; Michlin, B.; Northup, M.; Padley, B. P.; Redjimi, R.; Roberts, J.; Rorie, J.; Tu, Z.; Zabel, J.; Betchart, B.; Bodek, A.; de Barbaro, P.; Demina, R.; Duh, Y. t.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Verzetti, M.; Chou, J. P.; Contreras-Campana, E.; Gershtein, Y.; Gómez Espinosa, T. A.; Halkiadakis, E.; Heindl, M.; Hidas, D.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Kyriacou, S.; Lath, A.; Nash, K.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Foerster, M.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Juska, E.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Rose, A.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Cowden, C.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Sun, X.; Wang, Y.; Wolfe, E.; Xia, F.; Clarke, C.; Harr, R.; Karchin, P. E.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ruggles, T.; Savin, A.; Sharma, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.

2016-12-01

A search is presented for an excess of events with large missing transverse momentum in association with at least one highly energetic jet, in a data sample of proton-proton collisions at a centre-of-mass energy of 8 TeV. The data correspond to an integrated luminosity of 19.7 fb-1 collected by the CMS experiment at the LHC. The results are interpreted using a set of simplified models for the production of dark matter via a scalar, pseudoscalar, vector, or axial vector mediator. Additional sensitivity is achieved by tagging events consistent with the jets originating from a hadronically decaying vector boson. This search uses jet substructure techniques to identify hadronically decaying vector bosons in both Lorentz-boosted and resolved scenarios. This analysis yields improvements of 80% in terms of excluded signal cross sections with respect to the previous CMS analysis using the same data set. No significant excess with respect to the standard model expectation is observed and limits are placed on the parameter space of the simplified models. Mediator masses between 80 and 400 GeV in the scalar and pseudoscalar models, and up to 1.5 TeV in the vector and axial vector models, are excluded. [Figure not available: see fulltext.

The Absolute Vector Magnetometers on Board Swarm, Lessons Learned From Two Years in Space.

NASA Astrophysics Data System (ADS)

Hulot, G.; Leger, J. M.; Vigneron, P.; Brocco, L.; Olsen, N.; Jager, T.; Bertrand, F.; Fratter, I.; Sirol, O.; Lalanne, X.

2015-12-01

ESA's Swarm satellites carry 4He absolute magnetometers (ASM), designed by CEA-Léti and developed in partnership with CNES. These instruments are the first-ever space-born magnetometers to use a common sensor to simultaneously deliver 1Hz independent absolute scalar and vector readings of the magnetic field. They have provided the very high accuracy scalar field data nominally required by the mission (for both science and calibration purposes, since each satellite also carries a low noise high frequency fluxgate magnetometer designed by DTU), but also very useful experimental absolute vector data. In this presentation, we will report on the status of the instruments, as well as on the various tests and investigations carried out using these experimental data since launch in November 2013. In particular, we will illustrate the advantages of flying ASM instruments on space-born magnetic missions for nominal data quality checks, geomagnetic field modeling and science objectives.

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.

Using the Gravity Model to Estimate the Spatial Spread of Vector-Borne Diseases

PubMed Central

Barrios, José Miguel; Verstraeten, Willem W.; Maes, Piet; Aerts, Jean-Marie; Farifteh, Jamshid; Coppin, Pol

2012-01-01

The gravity models are commonly used spatial interaction models. They have been widely applied in a large set of domains dealing with interactions amongst spatial entities. The spread of vector-borne diseases is also related to the intensity of interaction between spatial entities, namely, the physical habitat of pathogens’ vectors and/or hosts, and urban areas, thus humans. This study implements the concept behind gravity models in the spatial spread of two vector-borne diseases, nephropathia epidemica and Lyme borreliosis, based on current knowledge on the transmission mechanism of these diseases. Two sources of information on vegetated systems were tested: the CORINE land cover map and MODIS NDVI. The size of vegetated areas near urban centers and a local indicator of occupation-related exposure were found significant predictors of disease risk. Both the land cover map and the space-borne dataset were suited yet not equivalent input sources to locate and measure vegetated areas of importance for disease spread. The overall results point at the compatibility of the gravity model concept and the spatial spread of vector-borne diseases. PMID:23202882

Using the gravity model to estimate the spatial spread of vector-borne diseases.

PubMed

Barrios, José Miguel; Verstraeten, Willem W; Maes, Piet; Aerts, Jean-Marie; Farifteh, Jamshid; Coppin, Pol

2012-11-30

The gravity models are commonly used spatial interaction models. They have been widely applied in a large set of domains dealing with interactions amongst spatial entities. The spread of vector-borne diseases is also related to the intensity of interaction between spatial entities, namely, the physical habitat of pathogens’ vectors and/or hosts, and urban areas, thus humans. This study implements the concept behind gravity models in the spatial spread of two vector-borne diseases, nephropathia epidemica and Lyme borreliosis, based on current knowledge on the transmission mechanism of these diseases. Two sources of information on vegetated systems were tested: the CORINE land cover map and MODIS NDVI. The size of vegetated areas near urban centers and a local indicator of occupation-related exposure were found significant predictors of disease risk. Both the land cover map and the space-borne dataset were suited yet not equivalent input sources to locate and measure vegetated areas of importance for disease spread. The overall results point at the compatibility of the gravity model concept and the spatial spread of vector-borne diseases.

Complexity of Kronecker Operations on Sparse Matrices with Applications to the Solution of Markov Models

NASA Technical Reports Server (NTRS)

Buchholz, Peter; Ciardo, Gianfranco; Donatelli, Susanna; Kemper, Peter

1997-01-01

We present a systematic discussion of algorithms to multiply a vector by a matrix expressed as the Kronecker product of sparse matrices, extending previous work in a unified notational framework. Then, we use our results to define new algorithms for the solution of large structured Markov models. In addition to a comprehensive overview of existing approaches, we give new results with respect to: (1) managing certain types of state-dependent behavior without incurring extra cost; (2) supporting both Jacobi-style and Gauss-Seidel-style methods by appropriate multiplication algorithms; (3) speeding up algorithms that consider probability vectors of size equal to the "actual" state space instead of the "potential" state space.

On A Nonlinear Generalization of Sparse Coding and Dictionary Learning.

PubMed

Xie, Yuchen; Ho, Jeffrey; Vemuri, Baba

2013-01-01

Existing dictionary learning algorithms are based on the assumption that the data are vectors in an Euclidean vector space ℝ d , and the dictionary is learned from the training data using the vector space structure of ℝ d and its Euclidean L 2 -metric. However, in many applications, features and data often originated from a Riemannian manifold that does not support a global linear (vector space) structure. Furthermore, the extrinsic viewpoint of existing dictionary learning algorithms becomes inappropriate for modeling and incorporating the intrinsic geometry of the manifold that is potentially important and critical to the application. This paper proposes a novel framework for sparse coding and dictionary learning for data on a Riemannian manifold, and it shows that the existing sparse coding and dictionary learning methods can be considered as special (Euclidean) cases of the more general framework proposed here. We show that both the dictionary and sparse coding can be effectively computed for several important classes of Riemannian manifolds, and we validate the proposed method using two well-known classification problems in computer vision and medical imaging analysis.

On A Nonlinear Generalization of Sparse Coding and Dictionary Learning

PubMed Central

Xie, Yuchen; Ho, Jeffrey; Vemuri, Baba

2013-01-01

Existing dictionary learning algorithms are based on the assumption that the data are vectors in an Euclidean vector space ℝd, and the dictionary is learned from the training data using the vector space structure of ℝd and its Euclidean L2-metric. However, in many applications, features and data often originated from a Riemannian manifold that does not support a global linear (vector space) structure. Furthermore, the extrinsic viewpoint of existing dictionary learning algorithms becomes inappropriate for modeling and incorporating the intrinsic geometry of the manifold that is potentially important and critical to the application. This paper proposes a novel framework for sparse coding and dictionary learning for data on a Riemannian manifold, and it shows that the existing sparse coding and dictionary learning methods can be considered as special (Euclidean) cases of the more general framework proposed here. We show that both the dictionary and sparse coding can be effectively computed for several important classes of Riemannian manifolds, and we validate the proposed method using two well-known classification problems in computer vision and medical imaging analysis. PMID:24129583

Computing the modal mass from the state space model in combined experimental-operational modal analysis

NASA Astrophysics Data System (ADS)

Cara, Javier

2016-05-01

Modal parameters comprise natural frequencies, damping ratios, modal vectors and modal masses. In a theoretic framework, these parameters are the basis for the solution of vibration problems using the theory of modal superposition. In practice, they can be computed from input-output vibration data: the usual procedure is to estimate a mathematical model from the data and then to compute the modal parameters from the estimated model. The most popular models for input-output data are based on the frequency response function, but in recent years the state space model in the time domain has become popular among researchers and practitioners of modal analysis with experimental data. In this work, the equations to compute the modal parameters from the state space model when input and output data are available (like in combined experimental-operational modal analysis) are derived in detail using invariants of the state space model: the equations needed to compute natural frequencies, damping ratios and modal vectors are well known in the operational modal analysis framework, but the equation needed to compute the modal masses has not generated much interest in technical literature. These equations are applied to both a numerical simulation and an experimental study in the last part of the work.

Improved dynamic analysis method using load-dependent Ritz vectors

NASA Technical Reports Server (NTRS)

Escobedo-Torres, J.; Ricles, J. M.

1993-01-01

The dynamic analysis of large space structures is important in order to predict their behavior under operating conditions. Computer models of large space structures are characterized by having a large number of degrees of freedom, and the computational effort required to carry out the analysis is very large. Conventional methods of solution utilize a subset of the eigenvectors of the system, but for systems with many degrees of freedom, the solution of the eigenproblem is in many cases the most costly phase of the analysis. For this reason, alternate solution methods need to be considered. It is important that the method chosen for the analysis be efficient and that accurate results be obtainable. It is important that the method chosen for the analysis be efficient and that accurate results be obtainable. The load dependent Ritz vector method is presented as an alternative to the classical normal mode methods for obtaining dynamic responses of large space structures. A simplified model of a space station is used to compare results. Results show that the load dependent Ritz vector method predicts the dynamic response better than the classical normal mode method. Even though this alternate method is very promising, further studies are necessary to fully understand its attributes and limitations.

Fundamental Principles of Classical Mechanics: a Geometrical Perspectives

NASA Astrophysics Data System (ADS)

Lam, Kai S.

2014-07-01

Classical mechanics is the quantitative study of the laws of motion for oscopic physical systems with mass. The fundamental laws of this subject, known as Newton's Laws of Motion, are expressed in terms of second-order differential equations governing the time evolution of vectors in a so-called configuration space of a system (see Chapter 12). In an elementary setting, these are usually vectors in 3-dimensional Euclidean space, such as position vectors of point particles; but typically they can be vectors in higher dimensional and more abstract spaces. A general knowledge of the mathematical properties of vectors, not only in their most intuitive incarnations as directed arrows in physical space but as elements of abstract linear vector spaces, and those of linear operators (transformations) on vector spaces as well, is then indispensable in laying the groundwork for both the physical and the more advanced mathematical - more precisely topological and geometrical - concepts that will prove to be vital in our subject. In this beginning chapter we will review these properties, and introduce the all-important related notions of dual spaces and tensor products of vector spaces. The notational convention for vectorial and tensorial indices used for the rest of this book (except when otherwise specified) will also be established...

TVC actuator model. [for the space shuttle main engine

NASA Technical Reports Server (NTRS)

Baslock, R. W.

1977-01-01

A prototype Space Shuttle Main Engine (SSME) Thrust Vector Control (TVC) Actuator analog model was successfully completed. The prototype, mounted on five printed circuit (PC) boards, was delivered to NASA, checked out and tested using a modular replacement technique on an analog computer. In all cases, the prototype model performed within the recording techniques of the analog computer which is well within the tolerances of the specifications.

Reasoning with Vectors: A Continuous Model for Fast Robust Inference.

PubMed

Widdows, Dominic; Cohen, Trevor

2015-10-01

This paper describes the use of continuous vector space models for reasoning with a formal knowledge base. The practical significance of these models is that they support fast, approximate but robust inference and hypothesis generation, which is complementary to the slow, exact, but sometimes brittle behavior of more traditional deduction engines such as theorem provers. The paper explains the way logical connectives can be used in semantic vector models, and summarizes the development of Predication-based Semantic Indexing, which involves the use of Vector Symbolic Architectures to represent the concepts and relationships from a knowledge base of subject-predicate-object triples. Experiments show that the use of continuous models for formal reasoning is not only possible, but already demonstrably effective for some recognized informatics tasks, and showing promise in other traditional problem areas. Examples described in this paper include: predicting new uses for existing drugs in biomedical informatics; removing unwanted meanings from search results in information retrieval and concept navigation; type-inference from attributes; comparing words based on their orthography; and representing tabular data, including modelling numerical values. The algorithms and techniques described in this paper are all publicly released and freely available in the Semantic Vectors open-source software package.

Reasoning with Vectors: A Continuous Model for Fast Robust Inference

PubMed Central

Widdows, Dominic; Cohen, Trevor

2015-01-01

This paper describes the use of continuous vector space models for reasoning with a formal knowledge base. The practical significance of these models is that they support fast, approximate but robust inference and hypothesis generation, which is complementary to the slow, exact, but sometimes brittle behavior of more traditional deduction engines such as theorem provers. The paper explains the way logical connectives can be used in semantic vector models, and summarizes the development of Predication-based Semantic Indexing, which involves the use of Vector Symbolic Architectures to represent the concepts and relationships from a knowledge base of subject-predicate-object triples. Experiments show that the use of continuous models for formal reasoning is not only possible, but already demonstrably effective for some recognized informatics tasks, and showing promise in other traditional problem areas. Examples described in this paper include: predicting new uses for existing drugs in biomedical informatics; removing unwanted meanings from search results in information retrieval and concept navigation; type-inference from attributes; comparing words based on their orthography; and representing tabular data, including modelling numerical values. The algorithms and techniques described in this paper are all publicly released and freely available in the Semantic Vectors open-source software package.1 PMID:26582967

Plant Seeds as Model Vectors for the Transfer of Life Through Space

NASA Astrophysics Data System (ADS)

Tepfer, David; Leach, Sydney

2006-12-01

We consider plant seeds as terrestrial models for a vectored life form that could protect biological information in space. Seeds consist of maternal tissue surrounding and protecting an embryo. Some seeds resist deleterious conditions found in space: ultra low vacuum, extreme temperatures and radiation, including intense UV light. In a receptive environment, seeds could liberate a viable embryo, viable higher cells or a viable free-living organism (an endosymbiont or endophyte). Even if viability is lost, seeds still contain functional macro and small molecules (DNA, RNA, proteins, amino acids, lipids, etc.) that could provide the chemical basis for starting or modifying life. The possible release of endophytes or endosymbionts from a seed-like space traveler suggests that multiple domains of life, defined in DNA sequence phylogenies, could be disseminated simultaneously from Earth. We consider the possibility of exospermia, the outward transfer of life, as well as introspermia, the inward transfer of life-both as a contemporary and ancient events.

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 curvaton with varying kinetic function

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

Dimopoulos, Konstantinos; Karciauskas, Mindaugas; Wagstaff, Jacques M.

2010-01-15

A new model realization of the vector curvaton paradigm is presented and analyzed. The model consists of a single massive Abelian vector field, with a Maxwell-type kinetic term. By assuming that the kinetic function and the mass of the vector field are appropriately varying during inflation, it is shown that a scale-invariant spectrum of superhorizon perturbations can be generated. These perturbations can contribute to the curvature perturbation of the Universe. If the vector field remains light at the end of inflation it is found that it can generate substantial statistical anisotropy in the spectrum and bispectrum of the curvature perturbation.more » In this case the non-Gaussianity in the curvature perturbation is predominantly anisotropic, which will be a testable prediction in the near future. If, on the other hand, the vector field is heavy at the end of inflation then it is demonstrated that particle production is approximately isotropic and the vector field alone can give rise to the curvature perturbation, without directly involving any fundamental scalar field. The parameter space for both possibilities is shown to be substantial. Finally, toy models are presented which show that the desired variation of the mass and kinetic function of the vector field can be realistically obtained, without unnatural tunings, in the context of supergravity or superstrings.« less

Intrinsic Bayesian Active Contours for Extraction of Object Boundaries in Images

PubMed Central

Srivastava, Anuj

2010-01-01

We present a framework for incorporating prior information about high-probability shapes in the process of contour extraction and object recognition in images. Here one studies shapes as elements of an infinite-dimensional, non-linear quotient space, and statistics of shapes are defined and computed intrinsically using differential geometry of this shape space. Prior models on shapes are constructed using probability distributions on tangent bundles of shape spaces. Similar to the past work on active contours, where curves are driven by vector fields based on image gradients and roughness penalties, we incorporate the prior shape knowledge in the form of vector fields on curves. Through experimental results, we demonstrate the use of prior shape models in the estimation of object boundaries, and their success in handling partial obscuration and missing data. Furthermore, we describe the use of this framework in shape-based object recognition or classification. PMID:21076692

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.

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

Assessing semantic similarity of texts - Methods and algorithms

NASA Astrophysics Data System (ADS)

Rozeva, Anna; Zerkova, Silvia

2017-12-01

Assessing the semantic similarity of texts is an important part of different text-related applications like educational systems, information retrieval, text summarization, etc. This task is performed by sophisticated analysis, which implements text-mining techniques. Text mining involves several pre-processing steps, which provide for obtaining structured representative model of the documents in a corpus by means of extracting and selecting the features, characterizing their content. Generally the model is vector-based and enables further analysis with knowledge discovery approaches. Algorithms and measures are used for assessing texts at syntactical and semantic level. An important text-mining method and similarity measure is latent semantic analysis (LSA). It provides for reducing the dimensionality of the document vector space and better capturing the text semantics. The mathematical background of LSA for deriving the meaning of the words in a given text by exploring their co-occurrence is examined. The algorithm for obtaining the vector representation of words and their corresponding latent concepts in a reduced multidimensional space as well as similarity calculation are presented.

Topology of Document Retrieval Systems.

ERIC Educational Resources Information Center

Everett, Daniel M.; Cater, Steven C.

1992-01-01

Explains the use of a topological structure to examine the closeness between documents in retrieval systems and analyzes the topological structure of a vector-space model, a fuzzy-set model, an extended Boolean model, a probabilistic model, and a TIRS (Topological Information Retrieval System) model. Proofs for the results are appended. (17…

Elasticity of fractal materials using the continuum model with non-integer dimensional space

NASA Astrophysics Data System (ADS)

Tarasov, Vasily E.

2015-01-01

Using a generalization of vector calculus for space with non-integer dimension, we consider elastic properties of fractal materials. Fractal materials are described by continuum models with non-integer dimensional space. A generalization of elasticity equations for non-integer dimensional space, and its solutions for the equilibrium case of fractal materials are suggested. Elasticity problems for fractal hollow ball and cylindrical fractal elastic pipe with inside and outside pressures, for rotating cylindrical fractal pipe, for gradient elasticity and thermoelasticity of fractal materials are solved.

Do vegetated rooftops attract more mosquitoes? Monitoring disease vector abundance on urban green roofs.

PubMed

Wong, Gwendolyn K L; Jim, C Y

2016-12-15

Green roof, an increasingly common constituent of urban green infrastructure, can provide multiple ecosystem services and mitigate climate-change and urban-heat-island challenges. Its adoption has been beset by a longstanding preconception of attracting urban pests like mosquitoes. As more cities may become vulnerable to emerging and re-emerging mosquito-borne infectious diseases, the knowledge gap needs to be filled. This study gauges the habitat preference of vector mosquitoes for extensive green roofs vis-à-vis positive and negative control sites in an urban setting. Seven sites in a university campus were selected to represent three experimental treatments: green roofs (GR), ground-level blue-green spaces as positive controls (PC), and bare roofs as negative controls (NC). Mosquito-trapping devices were deployed for a year from March 2015 to 2016. Human-biting mosquito species known to transmit infectious diseases in the region were identified and recorded as target species. Generalized linear models evaluated the effects of site type, season, and weather on vector-mosquito abundance. Our model revealed site type as a significant predictor of vector mosquito abundance, with considerably more vector mosquitoes captured in PC than in GR and NC. Vector abundance was higher in NC than in GR, attributed to the occasional presence of water pools in depressions of roofing membrane after rainfall. Our data also demonstrated seasonal differences in abundance. Weather variables were evaluated to assess human-vector contact risks under different weather conditions. Culex quinquefasciatus, a competent vector of diseases including lymphatic filariasis and West Nile fever, could be the most adaptable species. Our analysis demonstrates that green roofs are not particularly preferred by local vector mosquitoes compared to bare roofs and other urban spaces in a humid subtropical setting. The findings call for a better understanding of vector ecology in diverse urban landscapes to improve disease control efficacy amidst surging urbanization and changing climate. Copyright © 2016 Elsevier B.V. All rights reserved.

Integral transformation solution of free-space cylindrical vector beams and prediction of modified Bessel-Gaussian vector beams.

PubMed

Li, Chun-Fang

2007-12-15

A unified description of free-space cylindrical vector beams is presented that is an integral transformation solution to the vector Helmholtz equation and the transversality condition. In the paraxial condition, this solution not only includes the known J(1) Bessel-Gaussian vector beam and the axisymmetric Laguerre-Gaussian vector beam that were obtained by solving the paraxial wave equations but also predicts two kinds of vector beam, called a modified Bessel-Gaussian vector beam.

A Vector Space Model for Automatic Indexing.

ERIC Educational Resources Information Center

Salton, G.; And Others

In a document retrieval, or other pattern matching environment where stored entities (documents) are compared with each other, or with incoming patterns (search requests), it appears that the best indexing (property) space is one where each entity lies as far away from the others as possible; that is, retrieval performance correlates inversely…

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

Climate-based models for West Nile Culex mosquito vectors in the Northeastern US

NASA Astrophysics Data System (ADS)

Gong, Hongfei; Degaetano, Arthur T.; Harrington, Laura C.

2011-05-01

Climate-based models simulating Culex mosquito population abundance in the Northeastern US were developed. Two West Nile vector species, Culex pipiens and Culex restuans, were included in model simulations. The model was optimized by a parameter-space search within biological bounds. Mosquito population dynamics were driven by major environmental factors including temperature, rainfall, evaporation rate and photoperiod. The results show a strong correlation between the timing of early population increases (as early warning of West Nile virus risk) and decreases in late summer. Simulated abundance was highly correlated with actual mosquito capture in New Jersey light traps and validated with field data. This climate-based model simulates the population dynamics of both the adult and immature mosquito life stage of Culex arbovirus vectors in the Northeastern US. It is expected to have direct and practical application for mosquito control and West Nile prevention programs.

Constraints and stability in vector theories with spontaneous Lorentz violation

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

Bluhm, Robert; Gagne, Nolan L.; Potting, Robertus

2008-06-15

Vector theories with spontaneous Lorentz violation, known as bumblebee models, are examined in flat spacetime using a Hamiltonian constraint analysis. In some of these models, Nambu-Goldstone modes appear with properties similar to photons in electromagnetism. However, depending on the form of the theory, additional modes and constraints can appear that have no counterparts in electromagnetism. An examination of these constraints and additional degrees of freedom, including their nonlinear effects, is made for a variety of models with different kinetic and potential terms, and the results are compared with electromagnetism. The Hamiltonian constraint analysis also permits an investigation of the stabilitymore » of these models. For certain bumblebee theories with a timelike vector, suitable restrictions of the initial-value solutions are identified that yield ghost-free models with a positive Hamiltonian. In each case, the restricted phase space is found to match that of electromagnetism in a nonlinear gauge.« less

A Re-Unification of Two Competing Models for Document Retrieval.

ERIC Educational Resources Information Center

Bodoff, David

1999-01-01

Examines query-oriented versus document-oriented information retrieval and feedback learning. Highlights include a reunification of the two approaches for probabilistic document retrieval and for vector space model (VSM) retrieval; learning in VSM and in probabilistic models; multi-dimensional scaling; and ongoing field studies. (LRW)

Equivalent Dynamic Models.

PubMed

Molenaar, Peter C M

2017-01-01

Equivalences of two classes of dynamic models for weakly stationary multivariate time series are discussed: dynamic factor models and autoregressive models. It is shown that exploratory dynamic factor models can be rotated, yielding an infinite set of equivalent solutions for any observed series. It also is shown that dynamic factor models with lagged factor loadings are not equivalent to the currently popular state-space models, and that restriction of attention to the latter type of models may yield invalid results. The known equivalent vector autoregressive model types, standard and structural, are given a new interpretation in which they are conceived of as the extremes of an innovating type of hybrid vector autoregressive models. It is shown that consideration of hybrid models solves many problems, in particular with Granger causality testing.

Observables of QCD diffraction

NASA Astrophysics Data System (ADS)

Mieskolainen, Mikael; Orava, Risto

2017-03-01

A new combinatorial vector space measurement model is introduced for soft QCD diffraction. The model independent mathematical construction resolves experimental complications; the theoretical framework of the approach includes the Good-Walker view of diffraction, Regge phenomenology together with AGK cutting rules and random fluctuations.

The Use of Sparse Direct Solver in Vector Finite Element Modeling for Calculating Two Dimensional (2-D) Magnetotelluric Responses in Transverse Electric (TE) Mode

NASA Astrophysics Data System (ADS)

Yihaa Roodhiyah, Lisa’; Tjong, Tiffany; Nurhasan; Sutarno, D.

2018-04-01

The late research, linear matrices of vector finite element in two dimensional(2-D) magnetotelluric (MT) responses modeling was solved by non-sparse direct solver in TE mode. Nevertheless, there is some weakness which have to be improved especially accuracy in the low frequency (10-3 Hz-10-5 Hz) which is not achieved yet and high cost computation in dense mesh. In this work, the solver which is used is sparse direct solver instead of non-sparse direct solverto overcome the weaknesses of solving linear matrices of vector finite element metod using non-sparse direct solver. Sparse direct solver will be advantageous in solving linear matrices of vector finite element method because of the matrix properties which is symmetrical and sparse. The validation of sparse direct solver in solving linear matrices of vector finite element has been done for a homogen half-space model and vertical contact model by analytical solution. Thevalidation result of sparse direct solver in solving linear matrices of vector finite element shows that sparse direct solver is more stable than non-sparse direct solver in computing linear problem of vector finite element method especially in low frequency. In the end, the accuracy of 2D MT responses modelling in low frequency (10-3 Hz-10-5 Hz) has been reached out under the efficient allocation memory of array and less computational time consuming.

Chiral symmetry and π - π scattering in the Covariant Spectator Theory

DOE PAGES

Biernat, Elmar P.; Peña, M. T.; Ribeiro, J. E.; ...

2014-11-14

The π-π scattering amplitude calculated with a model for the quark-antiquark interaction in the framework of the Covariant Spectator Theory (CST) is shown to satisfy the Adler zero constraint imposed by chiral symmetry. The CST formalism is established in Minkowski space and our calculations are performed in momentum space. We prove that the axial-vector Ward-Takahashi identity is satisfied by our model. Then we show that, similarly to what happens within the Bethe-Salpeter formalism, application of the axial-vector Ward Takahashi identity to the CST π-π scattering amplitude allows us to sum the intermediate quark-quark interactions to all orders. Thus, the Adlermore » self-consistency zero for π-π scattering in the chiral limit emerges as the result for this sum.« less

Data-driven Model of the ICME Propagation through the Solar Corona and Inner Heliosphere

NASA Astrophysics Data System (ADS)

Yalim, M. S.; Pogorelov, N.; Singh, T.; Liu, Y.

2017-12-01

The solar wind (SW) emerging from the Sun is the main driving mechanism of solar events which may lead to geomagnetic storms that are the primary causes of space weather disturbances that affect the magnetic environment of Earth and may have hazardous effects on the space-borne and ground-based technological systems as well as human health. Therefore, accurate modeling of the SW is very important to understand the underlying mechanisms of such storms.Getting ready for the Parker Solar Probe mission, we have developed a data-driven magnetohydrodynamic (MHD) model of the global solar corona which utilizes characteristic boundary conditions implemented within the Multi-Scale Fluid-Kinetic Simulation Suite (MS-FLUKSS) - a collection of problem oriented routines incorporated into the Chombo adaptive mesh refinement framework developed at Lawrence Berkeley National Laboratory. Our global solar corona model can be driven by both synoptic and synchronic vector magnetogram data obtained by the Solar Dynamics Observatory/Helioseismic and Magnetic Imager (SDO/HMI) and the horizontal velocity data on the photosphere obtained by applying the Differential Affine Velocity Estimatorfor Vector Magnetograms (DAVE4VM) method on the HMI-observed vector magnetic fields.Our CME generation model is based on Gibson-Low-type flux ropes the parameters of which are determined from analysis of observational data from STEREO/SECCHI, SDO/AIA and SOHO/LASCO, and by applying the Graduate Cylindrical Shell model for the flux rope reconstruction.In this study, we will present the results of three-dimensional global simulations of ICME propagation through our characteristically-consistent MHD model of the background SW from the Sun to Earth driven by HMI-observed vector magnetic fields and validate our results using multiple spacecraft data at 1 AU.

All (4,0): Sigma models with (4,0) off-shell supersymmetry

NASA Astrophysics Data System (ADS)

Hull, Chris; Lindström, Ulf

2017-08-01

Off-shell (4, 0) supermultiplets in 2-dimensions are formulated. These are used to construct sigma models whose target spaces are vector bundles over manifolds that are hyperkähler with torsion. The off-shell supersymmetry implies that the complex structures are simultaneously integrable and allows us to write actions using extended superspace and projective superspace, giving an explicit construction of the target space geometries.

Orientation Modeling for Amateur Cameras by Matching Image Line Features and Building Vector Data

NASA Astrophysics Data System (ADS)

Hung, C. H.; Chang, W. C.; Chen, L. C.

2016-06-01

With the popularity of geospatial applications, database updating is getting important due to the environmental changes over time. Imagery provides a lower cost and efficient way to update the database. Three dimensional objects can be measured by space intersection using conjugate image points and orientation parameters of cameras. However, precise orientation parameters of light amateur cameras are not always available due to their costliness and heaviness of precision GPS and IMU. To automatize data updating, the correspondence of object vector data and image may be built to improve the accuracy of direct georeferencing. This study contains four major parts, (1) back-projection of object vector data, (2) extraction of image feature lines, (3) object-image feature line matching, and (4) line-based orientation modeling. In order to construct the correspondence of features between an image and a building model, the building vector features were back-projected onto the image using the initial camera orientation from GPS and IMU. Image line features were extracted from the imagery. Afterwards, the matching procedure was done by assessing the similarity between the extracted image features and the back-projected ones. Then, the fourth part utilized line features in orientation modeling. The line-based orientation modeling was performed by the integration of line parametric equations into collinearity condition equations. The experiment data included images with 0.06 m resolution acquired by Canon EOS Mark 5D II camera on a Microdrones MD4-1000 UAV. Experimental results indicate that 2.1 pixel accuracy may be reached, which is equivalent to 0.12 m in the object space.

Feature-space-based FMRI analysis using the optimal linear transformation.

PubMed

Sun, Fengrong; Morris, Drew; Lee, Wayne; Taylor, Margot J; Mills, Travis; Babyn, Paul S

2010-09-01

The optimal linear transformation (OLT), an image analysis technique of feature space, was first presented in the field of MRI. This paper proposes a method of extending OLT from MRI to functional MRI (fMRI) to improve the activation-detection performance over conventional approaches of fMRI analysis. In this method, first, ideal hemodynamic response time series for different stimuli were generated by convolving the theoretical hemodynamic response model with the stimulus timing. Second, constructing hypothetical signature vectors for different activity patterns of interest by virtue of the ideal hemodynamic responses, OLT was used to extract features of fMRI data. The resultant feature space had particular geometric clustering properties. It was then classified into different groups, each pertaining to an activity pattern of interest; the applied signature vector for each group was obtained by averaging. Third, using the applied signature vectors, OLT was applied again to generate fMRI composite images with high SNRs for the desired activity patterns. Simulations and a blocked fMRI experiment were employed for the method to be verified and compared with the general linear model (GLM)-based analysis. The simulation studies and the experimental results indicated the superiority of the proposed method over the GLM-based analysis in detecting brain activities.

Einstein-aether theory: dynamics of relativistic particles with spin or polarization in a Gödel-type universe

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

Balakin, Alexander B.; Popov, Vladimir A., E-mail: alexander.balakin@kpfu.ru, E-mail: vladipopov@mail.ru

In the framework of the Einstein-aether theory we consider a cosmological model, which describes the evolution of the unit dynamic vector field with activated rotational degree of freedom. We discuss exact solutions of the Einstein-aether theory, for which the space-time is of the Gödel-type, the velocity four-vector of the aether motion is characterized by a non-vanishing vorticity, thus the rotational vectorial modes can be associated with the source of the universe rotation. The main goal of our paper is to study the motion of test relativistic particles with a vectorial internal degree of freedom (spin or polarization), which is coupledmore » to the unit dynamic vector field. The particles are considered as the test ones in the given space-time background of the Gödel-type; the spin (polarization) coupling to the unit dynamic vector field is modeled using exact solutions of three types. The first exact solution describes the aether with arbitrary Jacobson's coupling constants; the second one relates to the case, when the Jacobson's constant responsible for the vorticity is vanishing; the third exact solution is obtained using three constraints for the coupling constants. The analysis of the exact expressions, which are obtained for the particle momentum and for the spin (polarization) four-vector components, shows that the interaction of the spin (polarization) with the unit vector field induces a rotation, which is additional to the geodesic precession of the spin (polarization) associated with the universe rotation as a whole.« less

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

Torsion as a dark matter candidate from the Higgs portal

NASA Astrophysics Data System (ADS)

Belyaev, Alexander S.; Thomas, Marc C.; Shapiro, Ilya L.

2017-05-01

Torsion is a metric-independent component of gravitation, which may provide a more general geometry than the one taking place within general relativity. On the other hand, torsion could lead to interesting phenomenology in both particle physics and cosmology. In the present work it is shown that a torsion field interacting with the SM Higgs doublet and having a negligible coupling to standard model (SM) fermions is protected from decaying by a Z2 symmetry, and therefore becomes a promising dark matter (DM) candidate. This model provides a good motivation for Higgs portal vector DM scenario. We evaluate the DM relic density and explore direct DM detection and collider constraints on this model to understand its consistency with experimental data and establish the most up-to-date limits on its parameter space. We have found in the model when the Higgs boson is only partly responsible for the generation of torsion mass, there is a region of parameter space where torsion contributes 100% to the DM budget of the Universe. Furthermore, we present the first results on the potential of the LHC to probe the parameter space of minimal scenario with Higgs portal vector DM using mono-jet searches and have found that LHC at high luminosity will be sensitive to the substantial part of model parameter space which cannot be probed by other experiments.

Single Vector Calibration System for Multi-Axis Load Cells and Method for Calibrating a Multi-Axis Load Cell

NASA Technical Reports Server (NTRS)

Parker, Peter A. (Inventor)

2003-01-01

A single vector calibration system is provided which facilitates the calibration of multi-axis load cells, including wind tunnel force balances. The single vector system provides the capability to calibrate a multi-axis load cell using a single directional load, for example loading solely in the gravitational direction. The system manipulates the load cell in three-dimensional space, while keeping the uni-directional calibration load aligned. The use of a single vector calibration load reduces the set-up time for the multi-axis load combinations needed to generate a complete calibration mathematical model. The system also reduces load application inaccuracies caused by the conventional requirement to generate multiple force vectors. The simplicity of the system reduces calibration time and cost, while simultaneously increasing calibration accuracy.

The Vector Space as a Unifying Concept in School Mathematics.

ERIC Educational Resources Information Center

Riggle, Timothy Andrew

The purpose of this study was to show how the concept of vector space can serve as a unifying thread for mathematics programs--elementary school to pre-calculus college level mathematics. Indicated are a number of opportunities to demonstrate how emphasis upon the vector space structure can enhance the organization of the mathematics curriculum.…

A new Bayesian recursive technique for parameter estimation

NASA Astrophysics Data System (ADS)

Kaheil, Yasir H.; Gill, M. Kashif; McKee, Mac; Bastidas, Luis

2006-08-01

The performance of any model depends on how well its associated parameters are estimated. In the current application, a localized Bayesian recursive estimation (LOBARE) approach is devised for parameter estimation. The LOBARE methodology is an extension of the Bayesian recursive estimation (BARE) method. It is applied in this paper on two different types of models: an artificial intelligence (AI) model in the form of a support vector machine (SVM) application for forecasting soil moisture and a conceptual rainfall-runoff (CRR) model represented by the Sacramento soil moisture accounting (SAC-SMA) model. Support vector machines, based on statistical learning theory (SLT), represent the modeling task as a quadratic optimization problem and have already been used in various applications in hydrology. They require estimation of three parameters. SAC-SMA is a very well known model that estimates runoff. It has a 13-dimensional parameter space. In the LOBARE approach presented here, Bayesian inference is used in an iterative fashion to estimate the parameter space that will most likely enclose a best parameter set. This is done by narrowing the sampling space through updating the "parent" bounds based on their fitness. These bounds are actually the parameter sets that were selected by BARE runs on subspaces of the initial parameter space. The new approach results in faster convergence toward the optimal parameter set using minimum training/calibration data and fewer sets of parameter values. The efficacy of the localized methodology is also compared with the previously used BARE algorithm.

Chiral-symmetry breaking and confinement in Minkowski space

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

Biernat, Elmer P.; Pena, M. T.; Ribiero, J. E.

2016-01-01

We present a model for the quark-antiquark interaction formulated in Minkowski space using the Covariant Spectator Theory. The quark propagators are dressed with the same kernel that describes the interaction between different quarks. By applying the axial-vector Ward-Takahashi identity we show that our model satisfies the Adler-zero constraint imposed by chiral symmetry. For this model, our Minkowski-space results of the dressed quark mass function are compared to lattice QCD data obtained in Euclidean space. The mass function is then used in the calculation of the electromagnetic pion form factor in relativistic impulse approximation, and the results are presented and comparedmore » with the experimental data from JLab.« less

Chiral-symmetry breaking and confinement in Minkowski space

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

Biernat, Elmar P.; Peña, M. T.; Departamento de Física, Instituto Superior Técnico

2016-01-22

We present a model for the quark-antiquark interaction formulated in Minkowski space using the Covariant Spectator Theory. The quark propagators are dressed with the same kernel that describes the interaction between different quarks. By applying the axial-vector Ward-Takahashi identity we show that our model satisfies the Adler-zero constraint imposed by chiral symmetry. For this model, our Minkowski-space results of the dressed quark mass function are compared to lattice QCD data obtained in Euclidean space. The mass function is then used in the calculation of the electromagnetic pion form factor in relativistic impulse approximation, and the results are presented and comparedmore » with the experimental data from JLab.« less

Space-Based Remote Sensing of Atmospheric Aerosols: The Multi-Angle Spectro-Polarimetric Frontier

NASA Technical Reports Server (NTRS)

Kokhanovsky, A. A.; Davis, A. B.; Cairns, B.; Dubovik, O.; Hasekamp, O. P.; Sano, I.; Mukai, S.; Rozanov, V. V.; Litvinov, P.; Lapyonok, T.;

Ontology-based vector space model and fuzzy query expansion to retrieve knowledge on medical computational problem solutions.

PubMed

Bratsas, Charalampos; Koutkias, Vassilis; Kaimakamis, Evangelos; Bamidis, Panagiotis; Maglaveras, Nicos

2007-01-01

Medical Computational Problem (MCP) solving is related to medical problems and their computerized algorithmic solutions. In this paper, an extension of an ontology-based model to fuzzy logic is presented, as a means to enhance the information retrieval (IR) procedure in semantic management of MCPs. We present herein the methodology followed for the fuzzy expansion of the ontology model, the fuzzy query expansion procedure, as well as an appropriate ontology-based Vector Space Model (VSM) that was constructed for efficient mapping of user-defined MCP search criteria and MCP acquired knowledge. The relevant fuzzy thesaurus is constructed by calculating the simultaneous occurrences of terms and the term-to-term similarities derived from the ontology that utilizes UMLS (Unified Medical Language System) concepts by using Concept Unique Identifiers (CUI), synonyms, semantic types, and broader-narrower relationships for fuzzy query expansion. The current approach constitutes a sophisticated advance for effective, semantics-based MCP-related IR.

Vectorized and multitasked solution of the few-group neutron diffusion equations

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

Zee, S.K.; Turinsky, P.J.; Shayer, Z.

1989-03-01

A numerical algorithm with parallelism was used to solve the two-group, multidimensional neutron diffusion equations on computers characterized by shared memory, vector pipeline, and multi-CPU architecture features. Specifically, solutions were obtained on the Cray X/MP-48, the IBM-3090 with vector facilities, and the FPS-164. The material-centered mesh finite difference method approximation and outer-inner iteration method were employed. Parallelism was introduced in the inner iterations using the cyclic line successive overrelaxation iterative method and solving in parallel across lines. The outer iterations were completed using the Chebyshev semi-iterative method that allows parallelism to be introduced in both space and energy groups. Formore » the three-dimensional model, power, soluble boron, and transient fission product feedbacks were included. Concentrating on the pressurized water reactor (PWR), the thermal-hydraulic calculation of moderator density assumed single-phase flow and a closed flow channel, allowing parallelism to be introduced in the solution across the radial plane. Using a pinwise detail, quarter-core model of a typical PWR in cycle 1, for the two-dimensional model without feedback the measured million floating point operations per second (MFLOPS)/vector speedups were 83/11.7. 18/2.2, and 2.4/5.6 on the Cray, IBM, and FPS without multitasking, respectively. Lower performance was observed with a coarser mesh, i.e., shorter vector length, due to vector pipeline start-up. For an 18 x 18 x 30 (x-y-z) three-dimensional model with feedback of the same core, MFLOPS/vector speedups of --61/6.7 and an execution time of 0.8 CPU seconds on the Cray without multitasking were measured. Finally, using two CPUs and the vector pipelines of the Cray, a multitasking efficiency of 81% was noted for the three-dimensional model.« less

Product demand forecasts using wavelet kernel support vector machine and particle swarm optimization in manufacture system

NASA Astrophysics Data System (ADS)

Wu, Qi

2010-03-01

Demand forecasts play a crucial role in supply chain management. The future demand for a certain product is the basis for the respective replenishment systems. Aiming at demand series with small samples, seasonal character, nonlinearity, randomicity and fuzziness, the existing support vector kernel does not approach the random curve of the sales time series in the space (quadratic continuous integral space). In this paper, we present a hybrid intelligent system combining the wavelet kernel support vector machine and particle swarm optimization for demand forecasting. The results of application in car sale series forecasting show that the forecasting approach based on the hybrid PSOWv-SVM model is effective and feasible, the comparison between the method proposed in this paper and other ones is also given, which proves that this method is, for the discussed example, better than hybrid PSOv-SVM and other traditional methods.

The Fifteen-Year Attitude History of the Wide Field Planetary Camera 2 Radiator and Collection Efficiencies for Micrometeoroids and Orbital Debris

NASA Technical Reports Server (NTRS)

Anz-Meador, Phillip D.; Liou, Jer-Chyi; Cooke, William J.; Koehler, H.

2010-01-01

An examination of the Hubble Space Telescope (HST) Wide Field Planetary Camera 2 (WFPC-2) radiator assembly was conducted at NASA Goddard Space Flight Center (GSFC) during the summer of 2009. Immediately apparent was a distinct biasing of the largest 45 impact features towards one side of the radiator, in contrast to an approximately uniform distribution of smaller impacts. Such a distribution may be a consequence of the HST s attitude history and pointing requirements for the cold radiator, or of environmental effects, such as an anisotropic distribution of the responsible population in that size regime. Understanding the size-dependent spatial distribution of impact features is essential to the general analysis of these features. We have obtained from GSFC a 15 minute temporal resolution record of the state vector (Earth Centered Inertial position and velocity) and HST attitude, consisting of the orientation of the velocity and HST-sun vectors in HST body coordinates. This paper reviews the actual state vector and attitude history of the radiator in the context of the randomly tumbling plate assumption and assesses the statistical likelihood (or collection efficiency) of the radiator for the micrometeoroid and orbital debris environments. The NASA Marshall Space Flight Center s Meteoroid Environment Model is used to assess the micrometeoroid component. The NASA Orbital Debris Engineering Model (ORDEM) is used to model the orbital debris component. Modeling results are compared with observations of the impact feature spatial distribution, and the relative contribution of each environmental component are examined in detail.

Rhotrix Vector Spaces

ERIC Educational Resources Information Center

Aminu, Abdulhadi

2010-01-01

By rhotrix we understand an object that lies in some way between (n x n)-dimensional matrices and (2n - 1) x (2n - 1)-dimensional matrices. Representation of vectors in rhotrices is different from the representation of vectors in matrices. A number of vector spaces in matrices and their properties are known. On the other hand, little seems to be…

A Functional Central Limit Theorem for the Becker-Döring Model

NASA Astrophysics Data System (ADS)

Sun, Wen

2018-04-01

We investigate the fluctuations of the stochastic Becker-Döring model of polymerization when the initial size of the system converges to infinity. A functional central limit problem is proved for the vector of the number of polymers of a given size. It is shown that the stochastic process associated to fluctuations is converging to the strong solution of an infinite dimensional stochastic differential equation (SDE) in a Hilbert space. We also prove that, at equilibrium, the solution of this SDE is a Gaussian process. The proofs are based on a specific representation of the evolution equations, the introduction of a convenient Hilbert space and several technical estimates to control the fluctuations, especially of the first coordinate which interacts with all components of the infinite dimensional vector representing the state of the process.

Thyra Abstract Interface Package

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

Bartlett, Roscoe A.

2005-09-01

Thrya primarily defines a set of abstract C++ class interfaces needed for the development of abstract numerical atgorithms (ANAs) such as iterative linear solvers, transient solvers all the way up to optimization. At the foundation of these interfaces are abstract C++ classes for vectors, vector spaces, linear operators and multi-vectors. Also included in the Thyra package is C++ code for creating concrete vector, vector space, linear operator, and multi-vector subclasses as well as other utilities to aid in the development of ANAs. Currently, very general and efficient concrete subclass implementations exist for serial and SPMD in-core vectors and multi-vectors. Codemore » also currently exists for testing objects and providing composite objects such as product vectors.« less

An online spatio-temporal prediction model for dengue fever epidemic in Kaohsiung,Taiwan

NASA Astrophysics Data System (ADS)

Cheng, Ming-Hung; Yu, Hwa-Lung; Angulo, Jose; Christakos, George

2013-04-01

Dengue Fever (DF) is one of the most serious vector-borne infectious diseases in tropical and subtropical areas. DF epidemics occur in Taiwan annually especially during summer and fall seasons. Kaohsiung city has been one of the major DF hotspots in decades. The emergence and re-emergence of the DF epidemic is complex and can be influenced by various factors including space-time dynamics of human and vector populations and virus serotypes as well as the associated uncertainties. This study integrates a stochastic space-time "Susceptible-Infected-Recovered" model under Bayesian maximum entropy framework (BME-SIR) to perform real-time prediction of disease diffusion across space-time. The proposed model is applied for spatiotemporal prediction of the DF epidemic at Kaohsiung city during 2002 when the historical series of high DF cases was recorded. The online prediction by BME-SIR model updates the parameters of SIR model and infected cases across districts over time. Results show that the proposed model is rigorous to initial guess of unknown model parameters, i.e. transmission and recovery rates, which can depend upon the virus serotypes and various human interventions. This study shows that spatial diffusion can be well characterized by BME-SIR model, especially at the district surrounding the disease outbreak locations. The prediction performance at DF hotspots, i.e. Cianjhen and Sanmin, can be degraded due to the implementation of various disease control strategies during the epidemics. The proposed online disease prediction BME-SIR model can provide the governmental agency with a valuable reference to timely identify, control, and efficiently prevent DF spread across space-time.

Querying and Ranking XML Documents.

ERIC Educational Resources Information Center

Schlieder, Torsten; Meuss, Holger

2002-01-01

Discussion of XML, information retrieval, precision, and recall focuses on a retrieval technique that adopts the similarity measure of the vector space model, incorporates the document structure, and supports structured queries. Topics include a query model based on tree matching; structured queries and term-based ranking; and term frequency and…

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…

Fractal electrodynamics via non-integer dimensional space approach

NASA Astrophysics Data System (ADS)

Tarasov, Vasily E.

2015-09-01

Using the recently suggested vector calculus for non-integer dimensional space, we consider electrodynamics problems in isotropic case. This calculus allows us to describe fractal media in the framework of continuum models with non-integer dimensional space. We consider electric and magnetic fields of fractal media with charges and currents in the framework of continuum models with non-integer dimensional spaces. An application of the fractal Gauss's law, the fractal Ampere's circuital law, the fractal Poisson equation for electric potential, and equation for fractal stream of charges are suggested. Lorentz invariance and speed of light in fractal electrodynamics are discussed. An expression for effective refractive index of non-integer dimensional space is suggested.

Pseudoscalar portal dark matter and new signatures of vector-like fermions

DOE PAGES

Fan, JiJi; Koushiappas, Savvas M.; Landsberg, Greg

2016-01-19

Fermionic dark matter interacting with the Standard Model sector through a pseudoscalar portal could evade the direct detection constraints while preserving a WIMP miracle. Here, we study the LHC constraints on the pseudoscalar production in simplified models with the pseudoscalar either dominantly coupled to b quarks ormore » $${{\\tau}}$$ leptons and explore their implications for the GeV excesses in gamma ray observations. We also investigate models with new vector-like fermions that could realize the simplfied models of pseudoscalar portal dark matter. Furthermore, these models yield new decay channels and signatures of vector-like fermions, for instance, bbb; b$${{\\tau}}$$ $${{\\tau}}$$, and $${{\\tau}}$$ $${{\\tau}}$$ $${{\\tau}}$$ resonances. Some of the signatures have already been strongly constrained by the existing LHC searches and the parameter space fitting the gamma ray excess is further restricted. Conversely, the pure $${{\\tau}}$$-rich final state is only weakly constrained so far due to the small electroweak production rate.« less

Searches for vector-like quarks at future colliders and implications for composite Higgs models with dark matter

NASA Astrophysics Data System (ADS)

Chala, Mikael; Gröber, Ramona; Spannowsky, Michael

2018-03-01

Many composite Higgs models predict the existence of vector-like quarks with masses outside the reach of the LHC, e.g. m Q ≳ 2 TeV, in particular if these models contain a dark matter candidate. In such models the mass of the new resonances is bounded from above to satisfy the constraint from the observed relic density. We therefore develop new strategies to search for vector-like quarks at a future 100 TeV collider and evaluate what masses and interactions can be probed. We find that masses as large as ˜ 6.4 (˜9) TeV can be tested if the fermionic resonances decay into Standard Model (dark matter) particles. We also discuss the complementarity of dark matter searches, showing that most of the parameter space can be closed. On balance, this study motivates further the consideration of a higher-energy hadron collider for a next generation of facilities.

Extended vector-tensor theories

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

Kimura, Rampei; Naruko, Atsushi; Yoshida, Daisuke, E-mail: rampei@th.phys.titech.ac.jp, E-mail: naruko@th.phys.titech.ac.jp, E-mail: yoshida@th.phys.titech.ac.jp

Recently, several extensions of massive vector theory in curved space-time have been proposed in many literatures. In this paper, we consider the most general vector-tensor theories that contain up to two derivatives with respect to metric and vector field. By imposing a degeneracy condition of the Lagrangian in the context of ADM decomposition of space-time to eliminate an unwanted mode, we construct a new class of massive vector theories where five degrees of freedom can propagate, corresponding to three for massive vector modes and two for massless tensor modes. We find that the generalized Proca and the beyond generalized Procamore » theories up to the quartic Lagrangian, which should be included in this formulation, are degenerate theories even in curved space-time. Finally, introducing new metric and vector field transformations, we investigate the properties of thus obtained theories under such transformations.« less

L'espace articulaire de la Robotique Industrielle est un espace vectorielIndustrial Robotics joint space is a vector space

NASA Astrophysics Data System (ADS)

Tondu, Bertrand

2003-05-01

The mathematical modelling of industrial robots is based on the vectorial nature of the n-dimensional joint space of the robot, defined as a kinematic chain with n degrees of freedom. However, in our opinion, the vectorial nature of the joint space has been insufficiently discussed in the literature. We establish the vectorial nature of the joint space of an industrial robot from the fundamental studies of B. Roth on screws. To cite this article: B. Tondu, C. R. Mecanique 331 (2003).

Time-specific ecological niche modeling predicts spatial dynamics of vector insects and human dengue cases.

PubMed

Peterson, A Townsend; Martínez-Campos, Carmen; Nakazawa, Yoshinori; Martínez-Meyer, Enrique

2005-09-01

Numerous human diseases-malaria, dengue, yellow fever and leishmaniasis, to name a few-are transmitted by insect vectors with brief life cycles and biting activity that varies in both space and time. Although the general geographic distributions of these epidemiologically important species are known, the spatiotemporal variation in their emergence and activity remains poorly understood. We used ecological niche modeling via a genetic algorithm to produce time-specific predictive models of monthly distributions of Aedes aegypti in Mexico in 1995. Significant predictions of monthly mosquito activity and distributions indicate that predicting spatiotemporal dynamics of disease vector species is feasible; significant coincidence with human cases of dengue indicate that these dynamics probably translate directly into transmission of dengue virus to humans. This approach provides new potential for optimizing use of resources for disease prevention and remediation via automated forecasting of disease transmission risk.

Intelligent classifier for dynamic fault patterns based on hidden Markov model

NASA Astrophysics Data System (ADS)

Xu, Bo; Feng, Yuguang; Yu, Jinsong

2006-11-01

It's difficult to build precise mathematical models for complex engineering systems because of the complexity of the structure and dynamics characteristics. Intelligent fault diagnosis introduces artificial intelligence and works in a different way without building the analytical mathematical model of a diagnostic object, so it's a practical approach to solve diagnostic problems of complex systems. This paper presents an intelligent fault diagnosis method, an integrated fault-pattern classifier based on Hidden Markov Model (HMM). This classifier consists of dynamic time warping (DTW) algorithm, self-organizing feature mapping (SOFM) network and Hidden Markov Model. First, after dynamic observation vector in measuring space is processed by DTW, the error vector including the fault feature of being tested system is obtained. Then a SOFM network is used as a feature extractor and vector quantization processor. Finally, fault diagnosis is realized by fault patterns classifying with the Hidden Markov Model classifier. The importing of dynamic time warping solves the problem of feature extracting from dynamic process vectors of complex system such as aeroengine, and makes it come true to diagnose complex system by utilizing dynamic process information. Simulating experiments show that the diagnosis model is easy to extend, and the fault pattern classifier is efficient and is convenient to the detecting and diagnosing of new faults.

Adaptive h -refinement for reduced-order models: ADAPTIVE h -refinement for reduced-order models

DOE PAGES

Carlberg, Kevin T.

2014-11-05

Our work presents a method to adaptively refine reduced-order models a posteriori without requiring additional full-order-model solves. The technique is analogous to mesh-adaptive h-refinement: it enriches the reduced-basis space online by ‘splitting’ a given basis vector into several vectors with disjoint support. The splitting scheme is defined by a tree structure constructed offline via recursive k-means clustering of the state variables using snapshot data. This method identifies the vectors to split online using a dual-weighted-residual approach that aims to reduce error in an output quantity of interest. The resulting method generates a hierarchy of subspaces online without requiring large-scale operationsmore » or full-order-model solves. Furthermore, it enables the reduced-order model to satisfy any prescribed error tolerance regardless of its original fidelity, as a completely refined reduced-order model is mathematically equivalent to the original full-order model. Experiments on a parameterized inviscid Burgers equation highlight the ability of the method to capture phenomena (e.g., moving shocks) not contained in the span of the original reduced basis.« less

Space-Time Point Pattern Analysis of Flavescence Dorée Epidemic in a Grapevine Field: Disease Progression and Recovery

PubMed Central

Maggi, Federico; Bosco, Domenico; Galetto, Luciana; Palmano, Sabrina; Marzachì, Cristina

2017-01-01

Analyses of space-time statistical features of a flavescence dorée (FD) epidemic in Vitis vinifera plants are presented. FD spread was surveyed from 2011 to 2015 in a vineyard of 17,500 m2 surface area in the Piemonte region, Italy; count and position of symptomatic plants were used to test the hypothesis of epidemic Complete Spatial Randomness and isotropicity in the space-time static (year-by-year) point pattern measure. Space-time dynamic (year-to-year) point pattern analyses were applied to newly infected and recovered plants to highlight statistics of FD progression and regression over time. Results highlighted point patterns ranging from disperse (at small scales) to aggregated (at large scales) over the years, suggesting that the FD epidemic is characterized by multiscale properties that may depend on infection incidence, vector population, and flight behavior. Dynamic analyses showed moderate preferential progression and regression along rows. Nearly uniform distributions of direction and negative exponential distributions of distance of newly symptomatic and recovered plants relative to existing symptomatic plants highlighted features of vector mobility similar to Brownian motion. These evidences indicate that space-time epidemics modeling should include environmental setting (e.g., vineyard geometry and topography) to capture anisotropicity as well as statistical features of vector flight behavior, plant recovery and susceptibility, and plant mortality. PMID:28111581

Transient radiative transfer in a scattering slab considering polarization.

PubMed

Yi, Hongliang; Ben, Xun; Tan, Heping

2013-11-04

The characteristics of the transient and polarization must be considered for a complete and correct description of short-pulse laser transfer in a scattering medium. A Monte Carlo (MC) method combined with a time shift and superposition principle is developed to simulate transient vector (polarized) radiative transfer in a scattering medium. The transient vector radiative transfer matrix (TVRTM) is defined to describe the transient polarization behavior of short-pulse laser propagating in the scattering medium. According to the definition of reflectivity, a new criterion of reflection at Fresnel surface is presented. In order to improve the computational efficiency and accuracy, a time shift and superposition principle is applied to the MC model for transient vector radiative transfer. The results for transient scalar radiative transfer and steady-state vector radiative transfer are compared with those in published literatures, respectively, and an excellent agreement between them is observed, which validates the correctness of the present model. Finally, transient radiative transfer is simulated considering the polarization effect of short-pulse laser in a scattering medium, and the distributions of Stokes vector in angular and temporal space are presented.

Crosstalk in solar polarization measurements

NASA Technical Reports Server (NTRS)

West, E. A.; Balasubramaniam, K. S.

1992-01-01

The instrumental crosstalk associated with the Marshall Space Flight Center Vector Magnetograph and the solar crosstalk created by the magnetic field are described and their impact on the reconstruction of the solar vector magnetic field is analyzed. It is pointed out that identifying and correcting the crosstalk is important in the development of realistic models describing the solar atmosphere. Solar crosstalk is spatially dependent on the structure of the magnetic field while instrumental crosstalk is dependent on the position of the analyzer.

Attitude estimation from magnetometer and earth-albedo-corrected coarse sun sensor measurements

NASA Astrophysics Data System (ADS)

Appel, Pontus

2005-01-01

For full 3-axes attitude determination the magnetic field vector and the Sun vector can be used. A Coarse Sun Sensor consisting of six solar cells placed on each of the six outer surfaces of the satellite is used for Sun vector determination. This robust and low cost setup is sensitive to surrounding light sources as it sees the whole sky. To compensate for the largest error source, the Earth, an albedo model is developed. The total albedo light vector has contributions from the Earth surface which is illuminated by the Sun and visible from the satellite. Depending on the reflectivity of the Earth surface, the satellite's position and the Sun's position the albedo light changes. This cannot be calculated analytically and hence a numerical model is developed. For on-board computer use the Earth albedo model consisting of data tables is transferred into polynomial functions in order to save memory space. For an absolute worst case the attitude determination error can be held below 2∘. In a nominal case it is better than 1∘.

Thermal noise model of antiferromagnetic dynamics: A macroscopic approach

NASA Astrophysics Data System (ADS)

Li, Xilai; Semenov, Yuriy; Kim, Ki Wook

In the search for post-silicon technologies, antiferromagnetic (AFM) spintronics is receiving widespread attention. Due to faster dynamics when compared with its ferromagnetic counterpart, AFM enables ultra-fast magnetization switching and THz oscillations. A crucial factor that affects the stability of antiferromagnetic dynamics is the thermal fluctuation, rarely considered in AFM research. Here, we derive from theory both stochastic dynamic equations for the macroscopic AFM Neel vector (L-vector) and the corresponding Fokker-Plank equation for the L-vector distribution function. For the dynamic equation approach, thermal noise is modeled by a stochastic fluctuating magnetic field that affects the AFM dynamics. The field is correlated within the correlation time and the amplitude is derived from the energy dissipation theory. For the distribution function approach, the inertial behavior of AFM dynamics forces consideration of the generalized space, including both coordinates and velocities. Finally, applying the proposed thermal noise model, we analyze a particular case of L-vector reversal of AFM nanoparticles by voltage controlled perpendicular magnetic anisotropy (PMA) with a tailored pulse width. This work was supported, in part, by SRC/NRI SWAN.

Impact of spatio-temporal scale of adjustment on variational assimilation of hydrologic and hydrometeorological data in operational distributed hydrologic models

NASA Astrophysics Data System (ADS)

Lee, H.; Seo, D.; McKee, P.; Corby, R.

2009-12-01

One of the large challenges in data assimilation (DA) into distributed hydrologic models is to reduce the large degrees of freedom involved in the inverse problem to avoid overfitting. To assess the sensitivity of the performance of DA to the dimensionality of the inverse problem, we design and carry out real-world experiments in which the control vector in variational DA (VAR) is solved at different scales in space and time, e.g., lumped, semi-distributed, and fully-distributed in space, and hourly, 6 hourly, etc., in time. The size of the control vector is related to the degrees of freedom in the inverse problem. For the assessment, we use the prototype 4-dimenational variational data assimilator (4DVAR) that assimilates streamflow, precipitation and potential evaporation data into the NWS Hydrology Laboratory’s Research Distributed Hydrologic Model (HL-RDHM). In this talk, we present the initial results for a number of basins in Oklahoma and Texas.

Dissipative N-point-vortex Models in the Plane

NASA Astrophysics Data System (ADS)

Shashikanth, Banavara N.

2010-02-01

A method is presented for constructing point vortex models in the plane that dissipate the Hamiltonian function at any prescribed rate and yet conserve the level sets of the invariants of the Hamiltonian model arising from the SE (2) symmetries. The method is purely geometric in that it uses the level sets of the Hamiltonian and the invariants to construct the dissipative field and is based on elementary classical geometry in ℝ3. Extension to higher-dimensional spaces, such as the point vortex phase space, is done using exterior algebra. The method is in fact general enough to apply to any smooth finite-dimensional system with conserved quantities, and, for certain special cases, the dissipative vector field constructed can be associated with an appropriately defined double Nambu-Poisson bracket. The most interesting feature of this method is that it allows for an infinite sequence of such dissipative vector fields to be constructed by repeated application of a symmetric linear operator (matrix) at each point of the intersection of the level sets.

Reduced basis technique for evaluating the sensitivity coefficients of the nonlinear tire response

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.; Tanner, John A.; Peters, Jeanne M.

1992-01-01

An efficient reduced-basis technique is proposed for calculating the sensitivity of nonlinear tire response to variations in the design variables. The tire is modeled using a 2-D, moderate rotation, laminated anisotropic shell theory, including the effects of variation in material and geometric parameters. The vector of structural response and its first-order and second-order sensitivity coefficients are each expressed as a linear combination of a small number of basis vectors. The effectiveness of the basis vectors used in approximating the sensitivity coefficients is demonstrated by a numerical example involving the Space Shuttle nose-gear tire, which is subjected to uniform inflation pressure.

Manifolds for pose tracking from monocular video

NASA Astrophysics Data System (ADS)

Basu, Saurav; Poulin, Joshua; Acton, Scott T.

2015-03-01

We formulate a simple human-pose tracking theory from monocular video based on the fundamental relationship between changes in pose and image motion vectors. We investigate the natural embedding of the low-dimensional body pose space into a high-dimensional space of body configurations that behaves locally in a linear manner. The embedded manifold facilitates the decomposition of the image motion vectors into basis motion vector fields of the tangent space to the manifold. This approach benefits from the style invariance of image motion flow vectors, and experiments to validate the fundamental theory show reasonable accuracy (within 4.9 deg of the ground truth).

Robust stability of second-order systems

NASA Technical Reports Server (NTRS)

Chuang, C.-H.

1993-01-01

A feedback linearization technique is used in conjunction with passivity concepts to design robust controllers for space robots. It is assumed that bounded modeling uncertainties exist in the inertia matrix and the vector representing the coriolis, centripetal, and friction forces. Under these assumptions, the controller guarantees asymptotic tracking of the joint variables. A Lagrangian approach is used to develop a dynamic model for space robots. Closed-loop simulation results are illustrated for a simple case of a single link planar manipulator with freely floating base.

On orthogonal expansions of the space of vector functions which are square-summable over a given domain and the vector analysis operators

NASA Technical Reports Server (NTRS)

Bykhovskiy, E. B.; Smirnov, N. V.

1983-01-01

The Hilbert space L2(omega) of vector functions is studied. A breakdown of L2(omega) into orthogonal subspaces is discussed and the properties of the operators for projection onto these subspaces are investigated from the standpoint of preserving the differential properties of the vectors being projected. Finally, the properties of the operators are examined.

Bundles over nearly-Kahler homogeneous spaces in heterotic string theory

NASA Astrophysics Data System (ADS)

Klaput, Michael; Lukas, Andre; Matti, Cyril

2011-09-01

We construct heterotic vacua based on six-dimensional nearly-Kahler homogeneous manifolds and non-trivial vector bundles thereon. Our examples are based on three specific group coset spaces. It is shown how to construct line bundles over these spaces, compute their properties and build up vector bundles consistent with supersymmetry and anomaly cancelation. It turns out that the most interesting coset is SU(3)/U(1)2. This space supports a large number of vector bundles which lead to consistent heterotic vacua, some of them with three chiral families.

Sensory interactions between six common aroma vectors explain four main red wine aroma nuances.

PubMed

Ferreira, Vicente; Sáenz-Navajas, María-Pilar; Campo, Eva; Herrero, Paula; de la Fuente, Arancha; Fernández-Zurbano, Purificación

2016-05-15

This work aims at assessing the aromatic sensory dimensions linked to 6 common wine aroma vectors (N, norisoprenoids; A, branched acids; F, enolones; E, branched ethyl esters; L, fusel alcohols, M, wood compounds) varying in their natural range of occurrence. Wine models were built by adding the vectors at two levels (fractional factorial design 2(VI)) to a de-aromatised aged red wine. Twenty other different models were evaluated by descriptive analysis. Red, black and dried fruits and woody notes were satisfactorily reproduced. Individual vectors explained just 15% of the sensory space, mostly dependent on perceptual interactions. N influences dried and black fruits and suppresses red fruits. A suppresses black fruits and enhances red and dried fruits. F exerts a major role on red fruits. E suppresses dried fruits and modulates black fruits. L is revealed as a strong suppressor of red fruits and particularly of woody notes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Dual Vector Spaces and Physical Singularities

NASA Astrophysics Data System (ADS)

Rowlands, Peter

Though we often refer to 3-D vector space as constructed from points, there is no mechanism from within its definition for doing this. In particular, space, on its own, cannot accommodate the singularities that we call fundamental particles. This requires a commutative combination of space as we know it with another 3-D vector space, which is dual to the first (in a physical sense). The combination of the two spaces generates a nilpotent quantum mechanics/quantum field theory, which incorporates exact supersymmetry and ultimately removes the anomalies due to self-interaction. Among the many natural consequences of the dual space formalism are half-integral spin for fermions, zitterbewegung, Berry phase and a zero norm Berwald-Moor metric for fermionic states.

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.

Discontinuous finite element method for vector radiative transfer

NASA Astrophysics Data System (ADS)

Wang, Cun-Hai; Yi, Hong-Liang; Tan, He-Ping

2017-03-01

The discontinuous finite element method (DFEM) is applied to solve the vector radiative transfer in participating media. The derivation in a discrete form of the vector radiation governing equations is presented, in which the angular space is discretized by the discrete-ordinates approach with a local refined modification, and the spatial domain is discretized into finite non-overlapped discontinuous elements. The elements in the whole solution domain are connected by modelling the boundary numerical flux between adjacent elements, which makes the DFEM numerically stable for solving radiative transfer equations. Several various problems of vector radiative transfer are tested to verify the performance of the developed DFEM, including vector radiative transfer in a one-dimensional parallel slab containing a Mie/Rayleigh/strong forward scattering medium and a two-dimensional square medium. The fact that DFEM results agree very well with the benchmark solutions in published references shows that the developed DFEM in this paper is accurate and effective for solving vector radiative transfer problems.

Modeling and control of fuel cell based distributed generation systems

NASA Astrophysics Data System (ADS)

Jung, Jin Woo

This dissertation presents circuit models and control algorithms of fuel cell based distributed generation systems (DGS) for two DGS topologies. In the first topology, each DGS unit utilizes a battery in parallel to the fuel cell in a standalone AC power plant and a grid-interconnection. In the second topology, a Z-source converter, which employs both the L and C passive components and shoot-through zero vectors instead of the conventional DC/DC boost power converter in order to step up the DC-link voltage, is adopted for a standalone AC power supply. In Topology 1, two applications are studied: a standalone power generation (Single DGS Unit and Two DGS Units) and a grid-interconnection. First, dynamic model of the fuel cell is given based on electrochemical process. Second, two full-bridge DC to DC converters are adopted and their controllers are designed: an unidirectional full-bridge DC to DC boost converter for the fuel cell and a bidirectional full-bridge DC to DC buck/boost converter for the battery. Third, for a three-phase DC to AC inverter without or with a Delta/Y transformer, a discrete-time state space circuit model is given and two discrete-time feedback controllers are designed: voltage controller in the outer loop and current controller in the inner loop. And last, for load sharing of two DGS units and power flow control of two DGS units or the DGS connected to the grid, real and reactive power controllers are proposed. Particularly, for the grid-connected DGS application, a synchronization issue between an islanding mode and a paralleling mode to the grid is investigated, and two case studies are performed. To demonstrate the proposed circuit models and control strategies, simulation test-beds using Matlab/Simulink are constructed for each configuration of the fuel cell based DGS with a three-phase AC 120 V (L-N)/60 Hz/50 kVA and various simulation results are presented. In Topology 2, this dissertation presents system modeling, modified space vector PWM implementation (MSVPWM) and design of a closed-loop controller of the Z-source converter which utilizes L and C components and shoot-through zero vectors for the standalone AC power generation. The fuel cell system is modeled by an electrical R-C circuit in order to include slow dynamics of the fuel cells and a voltage-current characteristic of a cell is also considered. A discrete-time state space model is derived to implement digital control and a space vector pulse-width modulation (SVPWM) technique is modified to realize the shoot-through zero vectors that boost the DC-link voltage. Also, three discrete-time feedback controllers are designed: a discrete-time optimal voltage controller, a discrete-time sliding mode current controller, and a discrete-time PI DC-link voltage controller. Furthermore, an asymptotic observer is used to reduce the number of sensors and enhance the reliability of the system. To demonstrate the analyzed circuit model and proposed control strategy, various simulation results using Matlab/Simulink are presented under both light/heavy loads and linear/nonlinear loads for a three-phase AC 208 V (L-L)/60 Hz/10 kVA.

Implementation of a new fuzzy vector control of induction motor.

PubMed

Rafa, Souad; Larabi, Abdelkader; Barazane, Linda; Manceur, Malik; Essounbouli, Najib; Hamzaoui, Abdelaziz

2014-05-01

The aim of this paper is to present a new approach to control an induction motor using type-1 fuzzy logic. The induction motor has a nonlinear model, uncertain and strongly coupled. The vector control technique, which is based on the inverse model of the induction motors, solves the coupling problem. Unfortunately, in practice this is not checked because of model uncertainties. Indeed, the presence of the uncertainties led us to use human expertise such as the fuzzy logic techniques. In order to maintain the decoupling and to overcome the problem of the sensitivity to the parametric variations, the field-oriented control is replaced by a new block control. The simulation results show that the both control schemes provide in their basic configuration, comparable performances regarding the decoupling. However, the fuzzy vector control provides the insensitivity to the parametric variations compared to the classical one. The fuzzy vector control scheme is successfully implemented in real-time using a digital signal processor board dSPACE 1104. The efficiency of this technique is verified as well as experimentally at different dynamic operating conditions such as sudden loads change, parameter variations, speed changes, etc. The fuzzy vector control is found to be a best control for application in an induction motor. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Spatial pattern evolution of Aedes aegypti breeding sites in an Argentinean city without a dengue vector control programme.

PubMed

Espinosa, Manuel O; Polop, Francisco; Rotela, Camilo H; Abril, Marcelo; Scavuzzo, Carlos M

2016-11-21

The main objective of this study was to obtain and analyse the space-time dynamics of Aedes aegypti breeding sites in Clorinda City, Formosa Province, Argentina coupled with landscape analysis using the maximum entropy approach in order to generate a dengue vector niche model. In urban areas, without vector control activities, 12 entomologic (larval) samplings were performed during three years (October 2011 to October 2014). The entomologic surveillance area represented 16,511 houses. Predictive models for Aedes distribution were developed using vector breeding abundance data, density analysis, clustering and geoprocessing techniques coupled with Earth observation satellite data. The spatial analysis showed a vector spatial distribution pattern with clusters of high density in the central region of Clorinda with a well-defined high-risk area in the western part of the city. It also showed a differential temporal behaviour among different areas, which could have implications for risk models and control strategies at the urban scale. The niche model obtained for Ae. aegypti, based on only one year of field data, showed that 85.8% of the distribution of breeding sites is explained by the percentage of water supply (48.2%), urban distribution (33.2%), and the percentage of urban coverage (4.4%). The consequences for the development of control strategies are discussed with reference to the results obtained using distribution maps based on environmental variables.

Cross-entropy embedding of high-dimensional data using the neural gas model.

PubMed

Estévez, Pablo A; Figueroa, Cristián J; Saito, Kazumi

2005-01-01

A cross-entropy approach to mapping high-dimensional data into a low-dimensional space embedding is presented. The method allows to project simultaneously the input data and the codebook vectors, obtained with the Neural Gas (NG) quantizer algorithm, into a low-dimensional output space. The aim of this approach is to preserve the relationship defined by the NG neighborhood function for each pair of input and codebook vectors. A cost function based on the cross-entropy between input and output probabilities is minimized by using a Newton-Raphson method. The new approach is compared with Sammon's non-linear mapping (NLM) and the hierarchical approach of combining a vector quantizer such as the self-organizing feature map (SOM) or NG with the NLM recall algorithm. In comparison with these techniques, our method delivers a clear visualization of both data points and codebooks, and it achieves a better mapping quality in terms of the topology preservation measure q(m).

PSOFuzzySVM-TMH: identification of transmembrane helix segments using ensemble feature space by incorporated fuzzy support vector machine.

PubMed

Hayat, Maqsood; Tahir, Muhammad

2015-08-01

Membrane protein is a central component of the cell that manages intra and extracellular processes. Membrane proteins execute a diversity of functions that are vital for the survival of organisms. The topology of transmembrane proteins describes the number of transmembrane (TM) helix segments and its orientation. However, owing to the lack of its recognized structures, the identification of TM helix and its topology through experimental methods is laborious with low throughput. In order to identify TM helix segments reliably, accurately, and effectively from topogenic sequences, we propose the PSOFuzzySVM-TMH model. In this model, evolutionary based information position specific scoring matrix and discrete based information 6-letter exchange group are used to formulate transmembrane protein sequences. The noisy and extraneous attributes are eradicated using an optimization selection technique, particle swarm optimization, from both feature spaces. Finally, the selected feature spaces are combined in order to form ensemble feature space. Fuzzy-support vector Machine is utilized as a classification algorithm. Two benchmark datasets, including low and high resolution datasets, are used. At various levels, the performance of the PSOFuzzySVM-TMH model is assessed through 10-fold cross validation test. The empirical results reveal that the proposed framework PSOFuzzySVM-TMH outperforms in terms of classification performance in the examined datasets. It is ascertained that the proposed model might be a useful and high throughput tool for academia and research community for further structure and functional studies on transmembrane proteins.

The Local Stellar Velocity Field via Vector Spherical Harmonics

NASA Technical Reports Server (NTRS)

Makarov, V. V.; Murphy, D. W.

2007-01-01

We analyze the local field of stellar tangential velocities for a sample of 42,339 nonbinary Hipparcos stars with accurate parallaxes, using a vector spherical harmonic formalism.We derive simple relations between the parameters of the classical linear model (Ogorodnikov-Milne) of the local systemic field and low-degree terms of the general vector harmonic decomposition. Taking advantage of these relationships, we determine the solar velocity with respect to the local stars of (V(sub X), V(sub Y), V(sub Z)) = (10.5, 18.5, 7.3) +/- 0.1 km s(exp -1) not for the asymmetric drift with respect to the local standard of rest. If only stars more distant than 100 pc are considered, the peculiar solar motion is (V(sub X), V(sub Y), V(sub Z)) = (9.9, 15.6, 6.9) +/- 0.2 km s(exp -1). The adverse effects of harmonic leakage, which occurs between the reflex solar motion represented by the three electric vector harmonics in the velocity space and higher degree harmonics in the proper-motion space, are eliminated in our analysis by direct subtraction of the reflex solar velocity in its tangential components for each star...

Genetic algorithm and graph theory based matrix factorization method for online friend recommendation.

PubMed

Li, Qu; Yao, Min; Yang, Jianhua; Xu, Ning

2014-01-01

Online friend recommendation is a fast developing topic in web mining. In this paper, we used SVD matrix factorization to model user and item feature vector and used stochastic gradient descent to amend parameter and improve accuracy. To tackle cold start problem and data sparsity, we used KNN model to influence user feature vector. At the same time, we used graph theory to partition communities with fairly low time and space complexity. What is more, matrix factorization can combine online and offline recommendation. Experiments showed that the hybrid recommendation algorithm is able to recommend online friends with good accuracy.

Gradient-based controllers for timed continuous Petri nets

NASA Astrophysics Data System (ADS)

Lefebvre, Dimitri; Leclercq, Edouard; Druaux, Fabrice; Thomas, Philippe

2015-07-01

This paper is about control design for timed continuous Petri nets that are described as piecewise affine systems. In this context, the marking vector is considered as the state space vector, weighted marking of place subsets are defined as the model outputs and the model inputs correspond to multiplicative control actions that slow down the firing rate of some controllable transitions. Structural and functional sensitivity of the outputs with respect to the inputs are discussed in terms of Petri nets. Then, gradient-based controllers (GBC) are developed in order to adapt the control actions of the controllable transitions according to desired trajectories of the outputs.

Channel analysis for single photon underwater free space quantum key distribution.

PubMed

Shi, Peng; Zhao, Shi-Cheng; Gu, Yong-Jian; Li, Wen-Dong

2015-03-01

We investigate the optical absorption and scattering properties of underwater media pertinent to our underwater free space quantum key distribution (QKD) channel model. With the vector radiative transfer theory and Monte Carlo method, we obtain the attenuation of photons, the fidelity of the scattered photons, the quantum bit error rate, and the sifted key generation rate of underwater quantum communication. It can be observed from our simulations that the most secure single photon underwater free space QKD is feasible in the clearest ocean water.

All ASD complex and real 4-dimensional Einstein spaces with Λ≠0 admitting a nonnull Killing vector

NASA Astrophysics Data System (ADS)

Chudecki, Adam

2016-12-01

Anti-self-dual (ASD) 4-dimensional complex Einstein spaces with nonzero cosmological constant Λ equipped with a nonnull Killing vector are considered. It is shown that any conformally nonflat metric of such spaces can be always brought to a special form and the Einstein field equations can be reduced to the Boyer-Finley-Plebański equation (Toda field equation). Some alternative forms of the metric are discussed. All possible real slices (neutral, Euclidean and Lorentzian) of ASD complex Einstein spaces with Λ≠0 admitting a nonnull Killing vector are found.

ISBDD Model for Classification of Hyperspectral Remote Sensing Imagery

PubMed Central

Li, Na; Xu, Zhaopeng; Zhao, Huijie; Huang, Xinchen; Drummond, Jane; Wang, Daming

2018-01-01

The diverse density (DD) algorithm was proposed to handle the problem of low classification accuracy when training samples contain interference such as mixed pixels. The DD algorithm can learn a feature vector from training bags, which comprise instances (pixels). However, the feature vector learned by the DD algorithm cannot always effectively represent one type of ground cover. To handle this problem, an instance space-based diverse density (ISBDD) model that employs a novel training strategy is proposed in this paper. In the ISBDD model, DD values of each pixel are computed instead of learning a feature vector, and as a result, the pixel can be classified according to its DD values. Airborne hyperspectral data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor and the Push-broom Hyperspectral Imager (PHI) are applied to evaluate the performance of the proposed model. Results show that the overall classification accuracy of ISBDD model on the AVIRIS and PHI images is up to 97.65% and 89.02%, respectively, while the kappa coefficient is up to 0.97 and 0.88, respectively. PMID:29510547

3D Position and Velocity Vector Computations of Objects Jettisoned from the International Space Station Using Close-Range Photogrammetry Approach

NASA Technical Reports Server (NTRS)

Papanyan, Valeri; Oshle, Edward; Adamo, Daniel

2008-01-01

Measurement of the jettisoned object departure trajectory and velocity vector in the International Space Station (ISS) reference frame is vitally important for prompt evaluation of the object s imminent orbit. We report on the first successful application of photogrammetric analysis of the ISS imagery for the prompt computation of the jettisoned object s position and velocity vectors. As post-EVA analyses examples, we present the Floating Potential Probe (FPP) and the Russian "Orlan" Space Suit jettisons, as well as the near-real-time (provided in several hours after the separation) computations of the Video Stanchion Support Assembly Flight Support Assembly (VSSA-FSA) and Early Ammonia Servicer (EAS) jettisons during the US astronauts space-walk. Standard close-range photogrammetry analysis was used during this EVA to analyze two on-board camera image sequences down-linked from the ISS. In this approach the ISS camera orientations were computed from known coordinates of several reference points on the ISS hardware. Then the position of the jettisoned object for each time-frame was computed from its image in each frame of the video-clips. In another, "quick-look" approach used in near-real time, orientation of the cameras was computed from their position (from the ISS CAD model) and operational data (pan and tilt) then location of the jettisoned object was calculated only for several frames of the two synchronized movies. Keywords: Photogrammetry, International Space Station, jettisons, image analysis.

State space model approach for forecasting the use of electrical energy (a case study on: PT. PLN (Persero) district of Kroya)

NASA Astrophysics Data System (ADS)

Kurniati, Devi; Hoyyi, Abdul; Widiharih, Tatik

2018-05-01

Time series data is a series of data taken or measured based on observations at the same time interval. Time series data analysis is used to perform data analysis considering the effect of time. The purpose of time series analysis is to know the characteristics and patterns of a data and predict a data value in some future period based on data in the past. One of the forecasting methods used for time series data is the state space model. This study discusses the modeling and forecasting of electric energy consumption using the state space model for univariate data. The modeling stage is began with optimal Autoregressive (AR) order selection, determination of state vector through canonical correlation analysis, estimation of parameter, and forecasting. The result of this research shows that modeling of electric energy consumption using state space model of order 4 with Mean Absolute Percentage Error (MAPE) value 3.655%, so the model is very good forecasting category.

Cosmology in beyond-generalized Proca theories

NASA Astrophysics Data System (ADS)

Nakamura, Shintaro; Kase, Ryotaro; Tsujikawa, Shinji

2017-05-01

The beyond-generalized Proca theories are the extension of second-order massive vector-tensor theories (dubbed generalized Proca theories) with two transverse vector modes and one longitudinal scalar besides two tensor polarizations. Even with this extension, the propagating degrees of freedom remain unchanged on the isotropic cosmological background without an Ostrogradski instability. We study the cosmology in beyond-generalized Proca theories by paying particular attention to the dynamics of late-time cosmic acceleration and resulting observational consequences. We derive conditions for avoiding ghosts and instabilities of tensor, vector, and scalar perturbations and discuss viable parameter spaces in concrete models allowing the dark energy equation of state smaller than -1 . The propagation speeds of those perturbations are subject to modifications beyond the domain of generalized Proca theories. There is a mixing between scalar and matter sound speeds, but such a mixing is suppressed during most of the cosmic expansion history without causing a new instability. On the other hand, we find that derivative interactions arising in beyond-generalized Proca theories give rise to important modifications to the cosmic growth history. The growth rate of matter perturbations can be compatible with the redshift-space distortion data due to the realization of gravitational interaction weaker than that in generalized Proca theories. Thus, it is possible to distinguish the dark energy model in beyond-generalized Proca theories from the counterpart in generalized Proca theories as well as from the Λ CDM model.

Spatial extent of a hydrothermal system at Kilauea Volcano, Hawaii, determined from array analyses of shallow long-period seismicity 1. Method

USGS Publications Warehouse

Almendros, J.; Chouet, B.; Dawson, P.

2001-01-01

We present a probabilistic method to locate the source of seismic events using seismic antennas. The method is based on a comparison of the event azimuths and slownesses derived from frequency-slowness analyses of array data, with a slowness vector model. Several slowness vector models are considered including both homogeneous and horizontally layered half-spaces and also a more complex medium representing the actual topography and three-dimensional velocity structure of the region under study. In this latter model the slowness vector is obtained from frequency-slowness analyses of synthetic signals. These signals are generated using the finite difference method and include the effects of topography and velocity structure to reproduce as closely as possible the behavior of the observed wave fields. A comparison of these results with those obtained with a homogeneous half-space demonstrates the importance of structural and topographic effects, which, if ignored, lead to a bias in the source location. We use synthetic seismograms to test the accuracy and stability of the method and to investigate the effect of our choice of probability distributions. We conclude that this location method can provide the source position of shallow events within a complex volcanic structure such as Kilauea Volcano with an error of ??200 m. Copyright 2001 by the American Geophysical Union.

Learning with LOGO: Logo and Vectors.

ERIC Educational Resources Information Center

Lough, Tom; Tipps, Steve

1986-01-01

This is the first of a two-part series on the general concept of vector space. Provides tool procedures to allow investigation of vector properties, vector addition and subtraction, and X and Y components. Lists several sources of additional vector ideas. (JM)

Principal fiber bundle description of number scaling for scalars and vectors: application to gauge theory

NASA Astrophysics Data System (ADS)

Benioff, Paul

2015-05-01

The purpose of this paper is to put the description of number scaling and its effects on physics and geometry on a firmer foundation, and to make it more understandable. A main point is that two different concepts, number and number value are combined in the usual representations of number structures. This is valid as long as just one structure of each number type is being considered. It is not valid when different structures of each number type are being considered. Elements of base sets of number structures, considered by themselves, have no meaning. They acquire meaning or value as elements of a number structure. Fiber bundles over a space or space time manifold, M, are described. The fiber consists of a collection of many real or complex number structures and vector space structures. The structures are parameterized by a real or complex scaling factor, s. A vector space at a fiber level, s, has, as scalars, real or complex number structures at the same level. Connections are described that relate scalar and vector space structures at both neighbor M locations and at neighbor scaling levels. Scalar and vector structure valued fields are described and covariant derivatives of these fields are obtained. Two complex vector fields, each with one real and one imaginary field, appear, with one complex field associated with positions in M and the other with position dependent scaling factors. A derivation of the covariant derivative for scalar and vector valued fields gives the same vector fields. The derivation shows that the complex vector field associated with scaling fiber levels is the gradient of a complex scalar field. Use of these results in gauge theory shows that the imaginary part of the vector field associated with M positions acts like the electromagnetic field. The physical relevance of the other three fields, if any, is not known.

Discrete symmetries in the heterotic-string landscape

NASA Astrophysics Data System (ADS)

Athanasopoulos, P.

2015-07-01

We describe a new type of discrete symmetry that relates heterotic-string models. It is based on the spectral flow operator which normally acts within a general N = (2, 2) model and we use this operator to construct a map between N = (2, 0) models. The landscape of N = (2, 0) models is of particular interest among all heterotic-string models for two important reasons: Firstly, N =1 spacetime SUSY requires (2, 0) superconformal invariance and secondly, models with the well motivated by the Standard Model SO(10) unification structure are of this type. This idea was inspired by a new discrete symmetry in the space of fermionic ℤ2 × ℤ2 heterotic-string models that exchanges the spinors and vectors of the SO(10) GUT group, dubbed spinor-vector duality. We will describe how to generalize this to arbitrary internal rational Conformal Field Theories.

Design of an ion thruster movable grid thrust vectoring system

NASA Astrophysics Data System (ADS)

Kural, Aleksander; Leveque, Nicolas; Welch, Chris; Wolanski, Piotr

2004-08-01

Several reasons justify the development of an ion propulsion system thrust vectoring system. Spacecraft launched to date have used ion thrusters mounted on gimbals to control the thrust vector within a range of about ±5°. Such devices have large mass and dimensions, hence the need exists for a more compact system, preferably mounted within the thruster itself. Since the 1970s several thrust vectoring systems have been developed, with the translatable accelerator grid electrode being considered the most promising. Laboratory models of this system have already been built and successfully tested, but there is still room for improvement in their mechanical design. This work aims to investigate possibilities of refining the design of such movable grid thrust vectoring systems. Two grid suspension designs and three types of actuators were evaluated. The actuators examined were a micro electromechanical system, a NanoMuscle shape memory alloy actuator and a piezoelectric driver. Criteria used for choosing the best system included mechanical simplicity (use of the fewest mechanical parts), accuracy, power consumption and behaviour in space conditions. Designs of systems using these actuators are proposed. In addition, a mission to Mercury using the system with piezoelectric drivers has been modelled and its performance presented.

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.

Reduced Order Podolsky Model

NASA Astrophysics Data System (ADS)

Thibes, Ronaldo

2017-02-01

We perform the canonical and path integral quantizations of a lower-order derivatives model describing Podolsky's generalized electrodynamics. The physical content of the model shows an auxiliary massive vector field coupled to the usual electromagnetic field. The equivalence with Podolsky's original model is studied at classical and quantum levels. Concerning the dynamical time evolution, we obtain a theory with two first-class and two second-class constraints in phase space. We calculate explicitly the corresponding Dirac brackets involving both vector fields. We use the Senjanovic procedure to implement the second-class constraints and the Batalin-Fradkin-Vilkovisky path integral quantization scheme to deal with the symmetries generated by the first-class constraints. The physical interpretation of the results turns out to be simpler due to the reduced derivatives order permeating the equations of motion, Dirac brackets and effective action.

The Shock and Vibration Digest. Volume 18, Number 7

DTIC Science & Technology

1986-07-01

long-term dynamic irregularity of a soluble Los Alamos, NM, July 21-23, 1981 quantum mechanical model known as the Jaynes - Cummings model . The analysis...substructure models are obtained % substructure computation can be performed by approximating each state space vector as a independently of the other...Non- and rotational residual flexibilities at the inter- linear joint behavior is modeled by an equivalent face. Data were taken in the form of

Fault Detection of Bearing Systems through EEMD and Optimization Algorithm

PubMed Central

Lee, Dong-Han; Ahn, Jong-Hyo; Koh, Bong-Hwan

2017-01-01

This study proposes a fault detection and diagnosis method for bearing systems using ensemble empirical mode decomposition (EEMD) based feature extraction, in conjunction with particle swarm optimization (PSO), principal component analysis (PCA), and Isomap. First, a mathematical model is assumed to generate vibration signals from damaged bearing components, such as the inner-race, outer-race, and rolling elements. The process of decomposing vibration signals into intrinsic mode functions (IMFs) and extracting statistical features is introduced to develop a damage-sensitive parameter vector. Finally, PCA and Isomap algorithm are used to classify and visualize this parameter vector, to separate damage characteristics from healthy bearing components. Moreover, the PSO-based optimization algorithm improves the classification performance by selecting proper weightings for the parameter vector, to maximize the visualization effect of separating and grouping of parameter vectors in three-dimensional space. PMID:29143772

Quark model with chiral-symmetry breaking and confinement in the Covariant Spectator Theory

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

Biernat, Elmer P.; Pena, Maria Teresa; Ribiero, Jose' Emilio F.

2016-03-01

We propose a model for the quark-antiquark interaction in Minkowski space using the Covariant Spectator Theory. We show that with an equal-weighted scalar-pseudoscalar structure for the confining part of our interaction kernel the axial-vector Ward-Takahashi identity is preserved and our model complies with the Adler-zero constraint for pi-pi-scattering imposed by chiral symmetry.

Predictive control strategies for wind turbine system based on permanent magnet synchronous generator.

PubMed

Maaoui-Ben Hassine, Ikram; Naouar, Mohamed Wissem; Mrabet-Bellaaj, Najiba

2016-05-01

In this paper, Model Predictive Control and Dead-beat predictive control strategies are proposed for the control of a PMSG based wind energy system. The proposed MPC considers the model of the converter-based system to forecast the possible future behavior of the controlled variables. It allows selecting the voltage vector to be applied that leads to a minimum error by minimizing a predefined cost function. The main features of the MPC are low current THD and robustness against parameters variations. The Dead-beat predictive control is based on the system model to compute the optimum voltage vector that ensures zero-steady state error. The optimum voltage vector is then applied through Space Vector Modulation (SVM) technique. The main advantages of the Dead-beat predictive control are low current THD and constant switching frequency. The proposed control techniques are presented and detailed for the control of back-to-back converter in a wind turbine system based on PMSG. Simulation results (under Matlab-Simulink software environment tool) and experimental results (under developed prototyping platform) are presented in order to show the performances of the considered control strategies. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Attacking the mosquito on multiple fronts: Insights from the Vector Control Optimization Model (VCOM) for malaria elimination.

PubMed

Kiware, Samson S; Chitnis, Nakul; Tatarsky, Allison; Wu, Sean; Castellanos, Héctor Manuel Sánchez; Gosling, Roly; Smith, David; Marshall, John M

2017-01-01

Despite great achievements by insecticide-treated nets (ITNs) and indoor residual spraying (IRS) in reducing malaria transmission, it is unlikely these tools will be sufficient to eliminate malaria transmission on their own in many settings today. Fortunately, field experiments indicate that there are many promising vector control interventions that can be used to complement ITNs and/or IRS by targeting a wide range of biological and environmental mosquito resources. The majority of these experiments were performed to test a single vector control intervention in isolation; however, there is growing evidence and consensus that effective vector control with the goal of malaria elimination will require a combination of interventions. We have developed a model of mosquito population dynamic to describe the mosquito life and feeding cycles and to optimize the impact of vector control intervention combinations at suppressing mosquito populations. The model simulations were performed for the main three malaria vectors in sub-Saharan Africa, Anopheles gambiae s.s, An. arabiensis and An. funestus. We considered areas having low, moderate and high malaria transmission, corresponding to entomological inoculation rates of 10, 50 and 100 infective bites per person per year, respectively. In all settings, we considered baseline ITN coverage of 50% or 80% in addition to a range of other vector control tools to interrupt malaria transmission. The model was used to sweep through parameters space to select the best optimal intervention packages. Sample model simulations indicate that, starting with ITNs at a coverage of 50% (An. gambiae s.s. and An. funestus) or 80% (An. arabiensis) and adding interventions that do not require human participation (e.g. larviciding at 80% coverage, endectocide treated cattle at 50% coverage and attractive toxic sugar baits at 50% coverage) may be sufficient to suppress all the three species to an extent required to achieve local malaria elimination. The Vector Control Optimization Model (VCOM) is a computational tool to predict the impact of combined vector control interventions at the mosquito population level in a range of eco-epidemiological settings. The model predicts specific combinations of vector control tools to achieve local malaria elimination in a range of eco-epidemiological settings and can assist researchers and program decision-makers on the design of experimental or operational research to test vector control interventions. A corresponding graphical user interface is available for national malaria control programs and other end users.

First stage of LISA data processing. II. Alternative filtering dynamic models for LISA

NASA Astrophysics Data System (ADS)

Wang, Yan; Heinzel, Gerhard; Danzmann, Karsten

2015-08-01

Space-borne gravitational wave detectors, such as (e)LISA, are designed to operate in the low-frequency band (mHz to Hz), where there is a variety of gravitational wave sources of great scientific value [arXiv:1305.5720 and S. Babak et al., Classical Quantum Gravity 28, 114001 (2011)]. To achieve the extraordinary sensitivity of these detectors, the precise synchronization of the clocks on the separate spacecraft and the accurate determination of the interspacecraft distances are important ingredients. In our previous paper [Y. Wang et al., Phys. Rev. D 90, 064016 (2014)], we have described a hybrid-extend Kalman filter with a full state vector to do this job. In this paper, we explore several different state vectors and their corresponding (phenomenological) dynamic models to reduce the redundancy in the full state vector, to accelerate the algorithm, and to make the algorithm easily extendable to more complicated scenarios.

Hypermultiplet gaugings and supersymmetric solutions from 11D and massive IIA supergravity on H^{(p,q)} spaces

NASA Astrophysics Data System (ADS)

Guarino, Adolfo

2018-03-01

Supersymmetric {AdS}4, {AdS}2 × Σ 2 and asymptotically AdS4 black hole solutions are studied in the context of non-minimal N=2 supergravity models involving three vector multiplets (STU-model) and Abelian gaugings of the universal hypermultiplet moduli space. Such models correspond to consistent subsectors of the {SO}(p,q) and {ISO}(p,q) gauged maximal supergravities that arise from the reduction of 11D and massive IIA supergravity on {H}^{(p,q)} spaces down to four dimensions. A unified description of all the models is provided in terms of a square-root prepotential and the gauging of a duality-hidden symmetry pair of the universal hypermultiplet. Some aspects of M-theory and massive IIA holography are mentioned in passing.

Families of vector-like deformations of relativistic quantum phase spaces, twists and symmetries

NASA Astrophysics Data System (ADS)

Meljanac, Daniel; Meljanac, Stjepan; Pikutić, Danijel

2017-12-01

Families of vector-like deformed relativistic quantum phase spaces and corresponding realizations are analyzed. A method for a general construction of the star product is presented. The corresponding twist, expressed in terms of phase space coordinates, in the Hopf algebroid sense is presented. General linear realizations are considered and corresponding twists, in terms of momenta and Poincaré-Weyl generators or gl(n) generators are constructed and R-matrix is discussed. A classification of linear realizations leading to vector-like deformed phase spaces is given. There are three types of spaces: (i) commutative spaces, (ii) κ -Minkowski spaces and (iii) κ -Snyder spaces. The corresponding star products are (i) associative and commutative (but non-local), (ii) associative and non-commutative and (iii) non-associative and non-commutative, respectively. Twisted symmetry algebras are considered. Transposed twists and left-right dual algebras are presented. Finally, some physical applications are discussed.

Notes on quantitative structure-properties relationships (QSPR) (1): A discussion on a QSPR dimensionality paradox (QSPR DP) and its quantum resolution.

PubMed

Carbó-Dorca, Ramon; Gallegos, Ana; Sánchez, Angel J

2009-05-01

Classical quantitative structure-properties relationship (QSPR) statistical techniques unavoidably present an inherent paradoxical computational context. They rely on the definition of a Gram matrix in descriptor spaces, which is used afterwards to reduce the original dimension via several possible kinds of algebraic manipulations. From there, effective models for the computation of unknown properties of known molecular structures are obtained. However, the reduced descriptor dimension causes linear dependence within the set of discrete vector molecular representations, leading to positive semi-definite Gram matrices in molecular spaces. To resolve this QSPR dimensionality paradox (QSPR DP) here is proposed to adopt as starting point the quantum QSPR (QQSPR) computational framework perspective, where density functions act as infinite dimensional descriptors. The fundamental QQSPR equation, deduced from employing quantum expectation value numerical evaluation, can be approximately solved in order to obtain models exempt of the QSPR DP. The substitution of the quantum similarity matrix by an empirical Gram matrix in molecular spaces, build up with the original non manipulated discrete molecular descriptor vectors, permits to obtain classical QSPR models with the same characteristics as in QQSPR, that is: possessing a certain degree of causality and explicitly independent of the descriptor dimension. 2008 Wiley Periodicals, Inc.

Using latent semantic analysis and the predication algorithm to improve extraction of meanings from a diagnostic corpus.

PubMed

Jorge-Botana, Guillermo; Olmos, Ricardo; León, José Antonio

2009-11-01

There is currently a widespread interest in indexing and extracting taxonomic information from large text collections. An example is the automatic categorization of informally written medical or psychological diagnoses, followed by the extraction of epidemiological information or even terms and structures needed to formulate guiding questions as an heuristic tool for helping doctors. Vector space models have been successfully used to this end (Lee, Cimino, Zhu, Sable, Shanker, Ely & Yu, 2006; Pakhomov, Buntrock & Chute, 2006). In this study we use a computational model known as Latent Semantic Analysis (LSA) on a diagnostic corpus with the aim of retrieving definitions (in the form of lists of semantic neighbors) of common structures it contains (e.g. "storm phobia", "dog phobia") or less common structures that might be formed by logical combinations of categories and diagnostic symptoms (e.g. "gun personality" or "germ personality"). In the quest to bring definitions into line with the meaning of structures and make them in some way representative, various problems commonly arise while recovering content using vector space models. We propose some approaches which bypass these problems, such as Kintsch's (2001) predication algorithm and some corrections to the way lists of neighbors are obtained, which have already been tested on semantic spaces in a non-specific domain (Jorge-Botana, León, Olmos & Hassan-Montero, under review). The results support the idea that the predication algorithm may also be useful for extracting more precise meanings of certain structures from scientific corpora, and that the introduction of some corrections based on vector length may increases its efficiency on non-representative terms.

Analysis of the sensitivity properties of a model of vector-borne bubonic plague.

PubMed

Buzby, Megan; Neckels, David; Antolin, Michael F; Estep, Donald

2008-09-06

Model sensitivity is a key to evaluation of mathematical models in ecology and evolution, especially in complex models with numerous parameters. In this paper, we use some recently developed methods for sensitivity analysis to study the parameter sensitivity of a model of vector-borne bubonic plague in a rodent population proposed by Keeling & Gilligan. The new sensitivity tools are based on a variational analysis involving the adjoint equation. The new approach provides a relatively inexpensive way to obtain derivative information about model output with respect to parameters. We use this approach to determine the sensitivity of a quantity of interest (the force of infection from rats and their fleas to humans) to various model parameters, determine a region over which linearization at a specific parameter reference point is valid, develop a global picture of the output surface, and search for maxima and minima in a given region in the parameter space.

Investigations on the hierarchy of reference frames in geodesy and geodynamics

NASA Technical Reports Server (NTRS)

Grafarend, E. W.; Mueller, I. I.; Papo, H. B.; Richter, B.

1979-01-01

Problems related to reference directions were investigated. Space and time variant angular parameters are illustrated in hierarchic structures or towers. Using least squares techniques, model towers of triads are presented which allow the formation of linear observation equations. Translational and rotational degrees of freedom (origin and orientation) are discussed along with and the notion of length and scale degrees of freedom. According to the notion of scale parallelism, scale factors with respect to a unit length are given. Three-dimensional geodesy was constructed from the set of three base vectors (gravity, earth-rotation and the ecliptic normal vector). Space and time variations are given with respect to a polar and singular value decomposition or in terms of changes in translation, rotation, deformation (shear, dilatation or angular and scale distortions).

Macroscopic theory of dark sector

NASA Astrophysics Data System (ADS)

Meierovich, Boris

A simple Lagrangian with squared covariant divergence of a vector field as a kinetic term turned out an adequate tool for macroscopic description of the dark sector. The zero-mass field acts as the dark energy. Its energy-momentum tensor is a simple additive to the cosmological constant [1]. Space-like and time-like massive vector fields describe two different forms of dark matter. The space-like massive vector field is attractive. It is responsible for the observed plateau in galaxy rotation curves [2]. The time-like massive field displays repulsive elasticity. In balance with dark energy and ordinary matter it provides a four parametric diversity of regular solutions of the Einstein equations describing different possible cosmological and oscillating non-singular scenarios of evolution of the universe [3]. In particular, the singular big bang turns into a regular inflation-like transition from contraction to expansion with the accelerate expansion at late times. The fine-tuned Friedman-Robertson-Walker singular solution corresponds to the particular limiting case at the boundary of existence of regular oscillating solutions in the absence of vector fields. The simplicity of the general covariant expression for the energy-momentum tensor allows to analyse the main properties of the dark sector analytically and avoid unnecessary model assumptions. It opens a possibility to trace how the additional attraction of the space-like dark matter, dominating in the galaxy scale, transforms into the elastic repulsion of the time-like dark matter, dominating in the scale of the Universe. 1. B. E. Meierovich. "Vector fields in multidimensional cosmology". Phys. Rev. D 84, 064037 (2011). 2. B. E. Meierovich. "Galaxy rotation curves driven by massive vector fields: Key to the theory of the dark sector". Phys. Rev. D 87, 103510, (2013). 3. B. E. Meierovich. "Towards the theory of the evolution of the Universe". Phys. Rev. D 85, 123544 (2012).

Projective mappings and dimensions of vector spaces of three types of Killing-Yano tensors on pseudo Riemannian manifolds of constant curvature

NASA Astrophysics Data System (ADS)

Mikeš, Josef; Stepanov, Sergey; Hinterleitner, Irena

2012-07-01

In our paper we have determined the dimension of the space of conformal Killing-Yano tensors and the dimensions of its two subspaces of closed conformal Killing-Yano and Killing-Yano tensors on pseudo Riemannian manifolds of constant curvature. This result is a generalization of well known results on sharp upper bounds of the dimensions of the vector spaces of conformal Killing-Yano, Killing-Yano and concircular vector fields on pseudo Riemannian manifolds of constant curvature.

Energy Dissipation of Rayleigh Waves due to Absorption Along the Path by the Use of Finite Element Method

DTIC Science & Technology

1979-07-31

3 x 3 t Strain vector a ij,j Space derivative of the stress tensor Fi Force vector per unit volume o Density x CHAPTER III F Total force K Stiffness...matrix 6Vector displacements M Mass matrix B Space operating matrix DO Matrix moduli 2 x 3 DZ Operating matrix in Z direction N Matrix of shape...dissipating medium the deformation of a solid is a function of time, temperature and space . Creep phenomenon is a deformation process in which there is

The Sequential Implementation of Array Processors when there is Directional Uncertainty

DTIC Science & Technology

1975-08-01

University of Washington kindly supplied office space and ccputing facilities. -The author hat, benefited greatly from discussions with several other...if i Q- inverse of Q I L general observation space R general vector of observation _KR general observation vector of dimension K Exiv] "Tf -- ’ -"-T’T...7" i ’i ’:"’ - ’ ; ’ ’ ’ ’ ’ ’" ’"- Glossary of Symbols (continued) R. ith observation 1 Rm real vector space of dimension m R(T) autocorrelation

Models of Disease Vector Control: When Can Aggressive Initial Intervention Lower Long-Term Cost?

PubMed

Oduro, Bismark; Grijalva, Mario J; Just, Winfried

2018-04-01

Insecticide spraying of housing units is an important control measure for vector-borne infections such as Chagas disease. As vectors may invade both from other infested houses and sylvatic areas and as the effectiveness of insecticide wears off over time, the dynamics of (re)infestations can be approximated by [Formula: see text]-type models with a reservoir, where housing units are treated as hosts, and insecticide spraying corresponds to removal of hosts. Here, we investigate three ODE-based models of this type. We describe a dual-rate effect where an initially very high spraying rate can push the system into a region of the state space with low endemic levels of infestation that can be maintained in the long run at relatively moderate cost, while in the absence of an aggressive initial intervention the same average cost would only allow a much less significant reduction in long-term infestation levels. We determine some sufficient and some necessary conditions under which this effect occurs and show that it is robust in models that incorporate some heterogeneity in the relevant properties of housing units.

Relevance of Web Documents:Ghosts Consensus Method.

ERIC Educational Resources Information Center

Gorbunov, Andrey L.

2002-01-01

Discusses how to improve the quality of Internet search systems and introduces the Ghosts Consensus Method which is free from the drawbacks of digital democracy algorithms and is based on linear programming tasks. Highlights include vector space models; determining relevant documents; and enriching query terms. (LRW)

Transformation to equivalent dimensions—a new methodology to study earthquake clustering

NASA Astrophysics Data System (ADS)

Lasocki, Stanislaw

2014-05-01

A seismic event is represented by a point in a parameter space, quantified by the vector of parameter values. Studies of earthquake clustering involve considering distances between such points in multidimensional spaces. However, the metrics of earthquake parameters are different, hence the metric in a multidimensional parameter space cannot be readily defined. The present paper proposes a solution of this metric problem based on a concept of probabilistic equivalence of earthquake parameters. Under this concept the lengths of parameter intervals are equivalent if the probability for earthquakes to take values from either interval is the same. Earthquake clustering is studied in an equivalent rather than the original dimensions space, where the equivalent dimension (ED) of a parameter is its cumulative distribution function. All transformed parameters are of linear scale in [0, 1] interval and the distance between earthquakes represented by vectors in any ED space is Euclidean. The unknown, in general, cumulative distributions of earthquake parameters are estimated from earthquake catalogues by means of the model-free non-parametric kernel estimation method. Potential of the transformation to EDs is illustrated by two examples of use: to find hierarchically closest neighbours in time-space and to assess temporal variations of earthquake clustering in a specific 4-D phase space.

Users’ Manual and Validation of the Automated Grading System (AGS): Improving the Quality of Intelligence Summaries Using Feedback from an Unsupervised Model of Semantics

DTIC Science & Technology

2012-12-01

trajectories in space, and are therefore very highly similar, and a cosine of 0 indicates that the two vectors are unrelated. The vector of a good summary...topic. The effectiveness of the AGS’s ability to automatically grade student assignment is completely dependent on a good match between this corpus...students to summarise “User Documents” that focused on fishing, then a good corpus would contain documents about the various types of fishing

Pattern classification using an olfactory model with PCA feature selection in electronic noses: study and application.

PubMed

Fu, Jun; Huang, Canqin; Xing, Jianguo; Zheng, Junbao

2012-01-01

Biologically-inspired models and algorithms are considered as promising sensor array signal processing methods for electronic noses. Feature selection is one of the most important issues for developing robust pattern recognition models in machine learning. This paper describes an investigation into the classification performance of a bionic olfactory model with the increase of the dimensions of input feature vector (outer factor) as well as its parallel channels (inner factor). The principal component analysis technique was applied for feature selection and dimension reduction. Two data sets of three classes of wine derived from different cultivars and five classes of green tea derived from five different provinces of China were used for experiments. In the former case the results showed that the average correct classification rate increased as more principal components were put in to feature vector. In the latter case the results showed that sufficient parallel channels should be reserved in the model to avoid pattern space crowding. We concluded that 6~8 channels of the model with principal component feature vector values of at least 90% cumulative variance is adequate for a classification task of 3~5 pattern classes considering the trade-off between time consumption and classification rate.

Characterising dark matter searches at colliders and direct detection experiments: Vector mediators

DOE PAGES

Buchmueller, Oliver; Dolan, Matthew J.; Malik, Sarah A.; ...

2015-01-09

We introduce a Minimal Simplified Dark Matter (MSDM) framework to quantitatively characterise dark matter (DM) searches at the LHC. We study two MSDM models where the DM is a Dirac fermion which interacts with a vector and axial-vector mediator. The models are characterised by four parameters: m DM, M med , g DM and g q, the DM and mediator masses, and the mediator couplings to DM and quarks respectively. The MSDM models accurately capture the full event kinematics, and the dependence on all masses and couplings can be systematically studied. The interpretation of mono-jet searches in this framework canmore » be used to establish an equal-footing comparison with direct detection experiments. For theories with a vector mediator, LHC mono-jet searches possess better sensitivity than direct detection searches for light DM masses (≲5 GeV). For axial-vector mediators, LHC and direct detection searches generally probe orthogonal directions in the parameter space. We explore the projected limits of these searches from the ultimate reach of the LHC and multi-ton xenon direct detection experiments, and find that the complementarity of the searches remains. In conclusion, we provide a comparison of limits in the MSDM and effective field theory (EFT) frameworks to highlight the deficiencies of the EFT framework, particularly when exploring the complementarity of mono-jet and direct detection searches.« less

Capabilities of software "Vector-M" for a diagnostics of the ionosphere state from auroral emissions images and plasma characteristics from the different orbits as a part of the system of control of space weather

NASA Astrophysics Data System (ADS)

Avdyushev, V.; Banshchikova, M.; Chuvashov, I.; Kuzmin, A.

2017-09-01

In the paper are presented capabilities of software "Vector-M" for a diagnostics of the ionosphere state from auroral emissions images and plasma characteristics from the different orbits as a part of the system of control of space weather. The software "Vector-M" is developed by the celestial mechanics and astrometry department of Tomsk State University in collaboration with Space Research Institute (Moscow) and Central Aerological Observatory of Russian Federal Service for Hydrometeorology and Environmental Monitoring. The software "Vector-M" is intended for calculation of attendant geophysical and astronomical information for the centre of mass of the spacecraft and the space of observations in the experiment with auroral imager Aurovisor-VIS/MP in the orbit of the perspective Meteor-MP spacecraft.

Displacement field for an edge dislocation in a layered half-space

USGS Publications Warehouse

Savage, J.C.

1998-01-01

The displacement field for an edge dislocation in an Earth model consisting of a layer welded to a half-space of different material is found in the form of a Fourier integral following the method given by Weeks et al. [1968]. There are four elementary solutions to be considered: the dislocation is either in the half-space or the layer and the Burgers vector is either parallel or perpendicular to the layer. A general two-dimensional solution for a dip-slip faulting or dike injection (arbitrary dip) can be constructed from a superposition of these elementary solutions. Surface deformations have been calculated for an edge dislocation located at the interface with Burgers vector inclined 0??, 30??, 60??, and 90?? to the interface for the case where the rigidity of the layer is half of that of the half-space and the Poisson ratios are the same. Those displacement fields have been compared to the displacement fields generated by similarly situated edge dislocations in a uniform half-space. The surface displacement field produced by the edge dislocation in the layered half-space is very similar to that produced by an edge dislocation at a different depth in a uniform half-space. In general, a low-modulus (high-modulus) layer causes the half-space equivalent dislocation to appear shallower (deeper) than the actual dislocation in the layered half-space.

Dynamics of aquatic ecosystems and models under toxicant stress: State space analysis, covariance structure, and ecological risk

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

Johnson, A.R.; Bartell, S.M.

1988-06-01

The state of an ecosystem at any time t may be characterized by a multidimensional state vector x(t). Changes in state are represented by the trajectory traced out by x(t) over time. The effects of toxicant stress are summarized by the displacement of a perturbed state vector, x/sub p/(t), relative to an appropriate control, x/sub c/(t). Within a multivariate statistical framework, the response of an ecosystem to perturbation is conveniently quantified by the distance separating x/sub p/(t) from x/sub c/(t) as measured by a Mahalanobis metric. Use of the Mahalanobis metric requires that the covariance matrix associated with the controlmore » state vector be estimated. State space displacement analysis was applied to data on the response of aquatic microcosms and outdoor ponds to alkylphenols. Dose-response relationships were derived using calculated state space separations as integrated measures of the ecological effects of toxicant exposure. Inspection of the data also revealed that the covariance structure varied both with time and with toxicant exposure, suggesting that analysis of such changes might be a useful tool for probing control mechanisms underlying ecosystem dynamics. 90 refs., 53 figs., 9 tabs.« less

Trends in space activities in 2014: The significance of the space activities of governments

NASA Astrophysics Data System (ADS)

Paikowsky, Deganit; Baram, Gil; Ben-Israel, Isaac

2016-01-01

This article addresses the principal events of 2014 in the field of space activities, and extrapolates from them the primary trends that can be identified in governmental space activities. In 2014, global space activities centered on two vectors. The first was geopolitical, and the second relates to the matrix between increasing commercial space activities and traditional governmental space activities. In light of these two vectors, the article outlines and analyzes trends of space exploration, human spaceflights, industry and technology, cooperation versus self-reliance, and space security and sustainability. It also reviews the space activities of the leading space-faring nations.

Application of Diagnostic Analysis Tools to the Ares I Thrust Vector Control System

NASA Technical Reports Server (NTRS)

Maul, William A.; Melcher, Kevin J.; Chicatelli, Amy K.; Johnson, Stephen B.

2010-01-01

The NASA Ares I Crew Launch Vehicle is being designed to support missions to the International Space Station (ISS), to the Moon, and beyond. The Ares I is undergoing design and development utilizing commercial-off-the-shelf tools and hardware when applicable, along with cutting edge launch technologies and state-of-the-art design and development. In support of the vehicle s design and development, the Ares Functional Fault Analysis group was tasked to develop an Ares Vehicle Diagnostic Model (AVDM) and to demonstrate the capability of that model to support failure-related analyses and design integration. One important component of the AVDM is the Upper Stage (US) Thrust Vector Control (TVC) diagnostic model-a representation of the failure space of the US TVC subsystem. This paper first presents an overview of the AVDM, its development approach, and the software used to implement the model and conduct diagnostic analysis. It then uses the US TVC diagnostic model to illustrate details of the development, implementation, analysis, and verification processes. Finally, the paper describes how the AVDM model can impact both design and ground operations, and how some of these impacts are being realized during discussions of US TVC diagnostic analyses with US TVC designers.

Modeling vector-borne disease risk in migratory animals under climate change.

PubMed

Hall, Richard J; Brown, Leone M; Altizer, Sonia

2016-08-01

Recent theory suggests that animals that migrate to breed at higher latitudes may benefit from reduced pressure from natural enemies, including pathogens ("migratory escape"), and that migration itself weeds out infected individuals and lowers infection prevalence ("migratory culling"). The distribution and activity period of arthropod disease vectors in temperate regions is expected to respond rapidly to climate change, which could reduce the potential for migratory escape. However, climate change could have the opposite effect of reducing transmission if differential responses in the phenology and distribution of migrants and disease vectors reduce their overlap in space and time. Here we outline a simple modeling framework for exploring the influence of climate change on vector-borne disease dynamics in a migratory host. We investigate two scenarios under which pathogen transmission dynamics might be mediated by climate change: (1) vectors respond more rapidly than migrants to advancing phenology at temperate breeding sites, causing peak susceptible host density and vector emergence to diverge ("migratory mismatch") and (2) reduced migratory propensity allows increased nonbreeding survival of infected hosts and larger breeding-site epidemics (loss of migratory culling, here referred to as "sedentary amplification"). Our results highlight the need for continued surveillance of climate-induced changes to migratory behavior and vector activity to predict pathogen prevalence and its impacts on migratory animals. © The Author 2016. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Estimation of relative order tensors, and reconstruction of vectors in space using unassigned RDC data and its application

NASA Astrophysics Data System (ADS)

Miao, Xijiang; Mukhopadhyay, Rishi; Valafar, Homayoun

2008-10-01

Advances in NMR instrumentation and pulse sequence design have resulted in easier acquisition of Residual Dipolar Coupling (RDC) data. However, computational and theoretical analysis of this type of data has continued to challenge the international community of investigators because of their complexity and rich information content. Contemporary use of RDC data has required a-priori assignment, which significantly increases the overall cost of structural analysis. This article introduces a novel algorithm that utilizes unassigned RDC data acquired from multiple alignment media ( nD-RDC, n ⩾ 3) for simultaneous extraction of the relative order tensor matrices and reconstruction of the interacting vectors in space. Estimation of the relative order tensors and reconstruction of the interacting vectors can be invaluable in a number of endeavors. An example application has been presented where the reconstructed vectors have been used to quantify the fitness of a template protein structure to the unknown protein structure. This work has other important direct applications such as verification of the novelty of an unknown protein and validation of the accuracy of an available protein structure model in drug design. More importantly, the presented work has the potential to bridge the gap between experimental and computational methods of structure determination.

Hemispheric Patterns in Electric Current Helicity of Solar Magnetic Fields During Solar Cycle 24: Results from SOLIS, SDO and Hinode

NASA Astrophysics Data System (ADS)

Gusain, S.

2017-12-01

We study the hemispheric patterns in electric current helicity distribution on the Sun. Magnetic field vector in the photosphere is now routinely measured by variety of instruments. SOLIS/VSM of NSO observes full disk Stokes spectra in photospheric lines which are used to derive vector magnetograms. Hinode SP is a space based spectropolarimeter which has the same observable as SOLIS albeit with limited field-of-view (FOV) but high spatial resolution. SDO/HMI derives vector magnetograms from full disk Stokes measurements, with rather limited spectral resolution, from space in a different photospheric line. Further, these datasets now exist for several years. SOLIS/VSM from 2003, Hinode SP from 2006, and SDO HMI since 2010. Using these time series of vector magnetograms we compute the electric current density in active regions during solar cycle 24 and study the hemispheric distributions. Many studies show that the helicity parameters and proxies show a strong hemispheric bias, such that Northern hemisphere has preferentially negative and southern positive helicity, respectively. We will confirm these results for cycle 24 from three different datasets and evaluate the statistical significance of the hemispheric bias. Further, we discuss the solar cycle variation in the hemispheric helicity pattern during cycle 24 and discuss its implications in terms of solar dynamo models.

State-Dependent Pseudo-Linear Filter for Spacecraft Attitude and Rate Estimation

NASA Technical Reports Server (NTRS)

Bar-Itzhack, Itzhack Y.; Harman, Richard R.

2001-01-01

This paper presents the development and performance of a special algorithm for estimating the attitude and angular rate of a spacecraft. The algorithm is a pseudo-linear Kalman filter, which is an ordinary linear Kalman filter that operates on a linear model whose matrices are current state estimate dependent. The nonlinear rotational dynamics equation of the spacecraft is presented in the state space as a state-dependent linear system. Two types of measurements are considered. One type is a measurement of the quaternion of rotation, which is obtained from a newly introduced star tracker based apparatus. The other type of measurement is that of vectors, which permits the use of a variety of vector measuring sensors like sun sensors and magnetometers. While quaternion measurements are related linearly to the state vector, vector measurements constitute a nonlinear function of the state vector. Therefore, in this paper, a state-dependent linear measurement equation is developed for the vector measurement case. The state-dependent pseudo linear filter is applied to simulated spacecraft rotations and adequate estimates of the spacecraft attitude and rate are obtained for the case of quaternion measurements as well as of vector measurements.

Design, Assembly, Integration, and Testing of a Power Processing Unit for a Cylindrical Hall Thruster, the NORSAT-2 Flatsat, and the Vector Gravimeter for Asteroids Instrument Computer

NASA Astrophysics Data System (ADS)

Svatos, Adam Ladislav

This thesis describes the author's contributions to three separate projects. The bus of the NORSAT-2 satellite was developed by the Space Flight Laboratory (SFL) for the Norwegian Space Centre (NSC) and Space Norway. The author's contributions to the mission were performing unit tests for the components of all the spacecraft subsystems as well as designing and assembling the flatsat from flight spares. Gedex's Vector Gravimeter for Asteroids (VEGA) is an accelerometer for spacecraft. The author's contributions to this payload were modifying the instrument computer board schematic, designing the printed circuit board, developing and applying test software, and performing thermal acceptance testing of two instrument computer boards. The SFL's cylindrical Hall effect thruster combines the cylindrical configuration for a Hall thruster and uses permanent magnets to achieve miniaturization and low power consumption, respectively. The author's contributions were to design, build, and test an engineering model power processing unit.

Poynting vector, energy densities, and pressure of collective transverse electromagnetic fluctuations in unmagnetized plasmas

NASA Astrophysics Data System (ADS)

Schlickeiser, R.

2012-01-01

A systematic calculation of the electromagnetic properties (Poynting vector, electromagnetic energy, and pressure) of the collective transverse fluctuations in unmagnetized plasmas with velocity-anisotropic plasma particle distributions functions is presented. Time-averaged electromagnetic properties for monochromatic weakly damped wave-like fluctuations and space-averaged electromagnetic properties for monochromatic weakly propagating and aperiodic fluctuations are calculated. For aperiodic fluctuations, the Poynting vector as well as the sum of the space-averaged electric and magnetic field energy densities vanish. However, aperiodic fluctuations possess a positive pressure given by its magnetic energy density. This finite pressure density pa of aperiodic fluctuations has important consequences for the dynamics of cosmic unmagnetized plasmas such as the intergalactic medium after reionization. Adopting the standard cosmological evolution model, we show that this additional pressure changes the expansion law of the universe leading to further deceleration. Negative vacuum pressure counterbalances this deceleration to an accelerating universe provided that the negative vacuum pressure is greater than 1.5pa, which we estimate to be of the order 2.1 . 10-16 dyn cm-2.

River flow prediction using hybrid models of support vector regression with the wavelet transform, singular spectrum analysis and chaotic approach

NASA Astrophysics Data System (ADS)

Baydaroğlu, Özlem; Koçak, Kasım; Duran, Kemal

2018-06-01

Prediction of water amount that will enter the reservoirs in the following month is of vital importance especially for semi-arid countries like Turkey. Climate projections emphasize that water scarcity will be one of the serious problems in the future. This study presents a methodology for predicting river flow for the subsequent month based on the time series of observed monthly river flow with hybrid models of support vector regression (SVR). Monthly river flow over the period 1940-2012 observed for the Kızılırmak River in Turkey has been used for training the method, which then has been applied for predictions over a period of 3 years. SVR is a specific implementation of support vector machines (SVMs), which transforms the observed input data time series into a high-dimensional feature space (input matrix) by way of a kernel function and performs a linear regression in this space. SVR requires a special input matrix. The input matrix was produced by wavelet transforms (WT), singular spectrum analysis (SSA), and a chaotic approach (CA) applied to the input time series. WT convolutes the original time series into a series of wavelets, and SSA decomposes the time series into a trend, an oscillatory and a noise component by singular value decomposition. CA uses a phase space formed by trajectories, which represent the dynamics producing the time series. These three methods for producing the input matrix for the SVR proved successful, while the SVR-WT combination resulted in the highest coefficient of determination and the lowest mean absolute error.

Method and System for Temporal Filtering in Video Compression Systems

NASA Technical Reports Server (NTRS)

Lu, Ligang; He, Drake; Jagmohan, Ashish; Sheinin, Vadim

2011-01-01

Three related innovations combine improved non-linear motion estimation, video coding, and video compression. The first system comprises a method in which side information is generated using an adaptive, non-linear motion model. This method enables extrapolating and interpolating a visual signal, including determining the first motion vector between the first pixel position in a first image to a second pixel position in a second image; determining a second motion vector between the second pixel position in the second image and a third pixel position in a third image; determining a third motion vector between the first pixel position in the first image and the second pixel position in the second image, the second pixel position in the second image, and the third pixel position in the third image using a non-linear model; and determining a position of the fourth pixel in a fourth image based upon the third motion vector. For the video compression element, the video encoder has low computational complexity and high compression efficiency. The disclosed system comprises a video encoder and a decoder. The encoder converts the source frame into a space-frequency representation, estimates the conditional statistics of at least one vector of space-frequency coefficients with similar frequencies, and is conditioned on previously encoded data. It estimates an encoding rate based on the conditional statistics and applies a Slepian-Wolf code with the computed encoding rate. The method for decoding includes generating a side-information vector of frequency coefficients based on previously decoded source data and encoder statistics and previous reconstructions of the source frequency vector. It also performs Slepian-Wolf decoding of a source frequency vector based on the generated side-information and the Slepian-Wolf code bits. The video coding element includes receiving a first reference frame having a first pixel value at a first pixel position, a second reference frame having a second pixel value at a second pixel position, and a third reference frame having a third pixel value at a third pixel position. It determines a first motion vector between the first pixel position and the second pixel position, a second motion vector between the second pixel position and the third pixel position, and a fourth pixel value for a fourth frame based upon a linear or nonlinear combination of the first pixel value, the second pixel value, and the third pixel value. A stationary filtering process determines the estimated pixel values. The parameters of the filter may be predetermined constants.

The role of remote sensing and GIS for spatial prediction of vector-borne diseases transmission: a systematic review.

PubMed

Palaniyandi, M

2012-12-01

There have been several attempts made to the appreciation of remote sensing and GIS for the study of vectors, biodiversity, vector presence, vector abundance and the vector-borne diseases with respect to space and time. This study was made for reviewing and appraising the potential use of remote sensing and GIS applications for spatial prediction of vector-borne diseases transmission. The nature of the presence and the abundance of vectors and vector-borne diseases, disease infection and the disease transmission are not ubiquitous and are confined with geographical, environmental and climatic factors, and are localized. The presence of vectors and vector-borne diseases is most complex in nature, however, it is confined and fueled by the geographical, climatic and environmental factors including man-made factors. The usefulness of the present day availability of the information derived from the satellite data including vegetation indices of canopy cover and its density, soil types, soil moisture, soil texture, soil depth, etc. is integrating the information in the expert GIS engine for the spatial analysis of other geoclimatic and geoenvironmental variables. The present study gives the detailed information on the classical studies of the past and present, and the future role of remote sensing and GIS for the vector-borne diseases control. The ecological modeling directly gives us the relevant information to understand the spatial variation of the vector biodiversity, vector presence, vector abundance and the vector-borne diseases in association with geoclimatic and the environmental variables. The probability map of the geographical distribution and seasonal variations of horizontal and vertical distribution of vector abundance and its association with vector -borne diseases can be obtained with low cost remote sensing and GIS tool with reliable data and speed.

Electricity Load Forecasting Using Support Vector Regression with Memetic Algorithms

PubMed Central

Hu, Zhongyi; Xiong, Tao

2013-01-01

Electricity load forecasting is an important issue that is widely explored and examined in power systems operation literature and commercial transactions in electricity markets literature as well. Among the existing forecasting models, support vector regression (SVR) has gained much attention. Considering the performance of SVR highly depends on its parameters; this study proposed a firefly algorithm (FA) based memetic algorithm (FA-MA) to appropriately determine the parameters of SVR forecasting model. In the proposed FA-MA algorithm, the FA algorithm is applied to explore the solution space, and the pattern search is used to conduct individual learning and thus enhance the exploitation of FA. Experimental results confirm that the proposed FA-MA based SVR model can not only yield more accurate forecasting results than the other four evolutionary algorithms based SVR models and three well-known forecasting models but also outperform the hybrid algorithms in the related existing literature. PMID:24459425

Electricity load forecasting using support vector regression with memetic algorithms.

PubMed

Hu, Zhongyi; Bao, Yukun; Xiong, Tao

2013-01-01

Electricity load forecasting is an important issue that is widely explored and examined in power systems operation literature and commercial transactions in electricity markets literature as well. Among the existing forecasting models, support vector regression (SVR) has gained much attention. Considering the performance of SVR highly depends on its parameters; this study proposed a firefly algorithm (FA) based memetic algorithm (FA-MA) to appropriately determine the parameters of SVR forecasting model. In the proposed FA-MA algorithm, the FA algorithm is applied to explore the solution space, and the pattern search is used to conduct individual learning and thus enhance the exploitation of FA. Experimental results confirm that the proposed FA-MA based SVR model can not only yield more accurate forecasting results than the other four evolutionary algorithms based SVR models and three well-known forecasting models but also outperform the hybrid algorithms in the related existing literature.

Habitat suitability and ecological niche profile of major malaria vectors in Cameroon

PubMed Central

2009-01-01

Background Suitability of environmental conditions determines a species distribution in space and time. Understanding and modelling the ecological niche of mosquito disease vectors can, therefore, be a powerful predictor of the risk of exposure to the pathogens they transmit. In Africa, five anophelines are responsible for over 95% of total malaria transmission. However, detailed knowledge of the geographic distribution and ecological requirements of these species is to date still inadequate. Methods Indoor-resting mosquitoes were sampled from 386 villages covering the full range of ecological settings available in Cameroon, Central Africa. Using a predictive species distribution modeling approach based only on presence records, habitat suitability maps were constructed for the five major malaria vectors Anopheles gambiae, Anopheles funestus, Anopheles arabiensis, Anopheles nili and Anopheles moucheti. The influence of 17 climatic, topographic, and land use variables on mosquito geographic distribution was assessed by multivariate regression and ordination techniques. Results Twenty-four anopheline species were collected, of which 17 are known to transmit malaria in Africa. Ecological Niche Factor Analysis, Habitat Suitability modeling and Canonical Correspondence Analysis revealed marked differences among the five major malaria vector species, both in terms of ecological requirements and niche breadth. Eco-geographical variables (EGVs) related to human activity had the highest impact on habitat suitability for the five major malaria vectors, with areas of low population density being of marginal or unsuitable habitat quality. Sunlight exposure, rainfall, evapo-transpiration, relative humidity, and wind speed were among the most discriminative EGVs separating "forest" from "savanna" species. Conclusions The distribution of major malaria vectors in Cameroon is strongly affected by the impact of humans on the environment, with variables related to proximity to human settings being among the best predictors of habitat suitability. The ecologically more tolerant species An. gambiae and An. funestus were recorded in a wide range of eco-climatic settings. The other three major vectors, An. arabiensis, An. moucheti, and An. nili, were more specialized. Ecological niche and species distribution modelling should help improve malaria vector control interventions by targeting places and times where the impact on vector populations and disease transmission can be optimized. PMID:20028559

Habitat suitability and ecological niche profile of major malaria vectors in Cameroon.

PubMed

Ayala, Diego; Costantini, Carlo; Ose, Kenji; Kamdem, Guy C; Antonio-Nkondjio, Christophe; Agbor, Jean-Pierre; Awono-Ambene, Parfait; Fontenille, Didier; Simard, Frédéric

2009-12-23

Suitability of environmental conditions determines a species distribution in space and time. Understanding and modelling the ecological niche of mosquito disease vectors can, therefore, be a powerful predictor of the risk of exposure to the pathogens they transmit. In Africa, five anophelines are responsible for over 95% of total malaria transmission. However, detailed knowledge of the geographic distribution and ecological requirements of these species is to date still inadequate. Indoor-resting mosquitoes were sampled from 386 villages covering the full range of ecological settings available in Cameroon, Central Africa. Using a predictive species distribution modeling approach based only on presence records, habitat suitability maps were constructed for the five major malaria vectors Anopheles gambiae, Anopheles funestus, Anopheles arabiensis, Anopheles nili and Anopheles moucheti. The influence of 17 climatic, topographic, and land use variables on mosquito geographic distribution was assessed by multivariate regression and ordination techniques. Twenty-four anopheline species were collected, of which 17 are known to transmit malaria in Africa. Ecological Niche Factor Analysis, Habitat Suitability modeling and Canonical Correspondence Analysis revealed marked differences among the five major malaria vector species, both in terms of ecological requirements and niche breadth. Eco-geographical variables (EGVs) related to human activity had the highest impact on habitat suitability for the five major malaria vectors, with areas of low population density being of marginal or unsuitable habitat quality. Sunlight exposure, rainfall, evapo-transpiration, relative humidity, and wind speed were among the most discriminative EGVs separating "forest" from "savanna" species. The distribution of major malaria vectors in Cameroon is strongly affected by the impact of humans on the environment, with variables related to proximity to human settings being among the best predictors of habitat suitability. The ecologically more tolerant species An. gambiae and An. funestus were recorded in a wide range of eco-climatic settings. The other three major vectors, An. arabiensis, An. moucheti, and An. nili, were more specialized. Ecological niche and species distribution modelling should help improve malaria vector control interventions by targeting places and times where the impact on vector populations and disease transmission can be optimized.

The SAMEX Vector Magnetograph: A Design Study for a Space-Based Solar Vector Magnetograph

NASA Technical Reports Server (NTRS)

Hagyard, M. J.; Gary, G. A.; West, E. A.

1988-01-01

This report presents the results of a pre-phase A study performed by the Marshall Space Flight Center (MSFC) for the Air Force Geophysics Laboratory (AFGL) to develop a design concept for a space-based solar vector magnetograph and hydrogen-alpha telescope. These are two of the core instruments for a proposed Air Force mission, the Solar Activities Measurement Experiments (SAMEX). This mission is designed to study the processes which give rise to activity in the solar atmosphere and to develop techniques for predicting solar activity and its effects on the terrestrial environment.

Vectoring of parallel synthetic jets: A parametric study

NASA Astrophysics Data System (ADS)

Berk, Tim; Gomit, Guillaume; Ganapathisubramani, Bharathram

2016-11-01

The vectoring of a pair of parallel synthetic jets can be described using five dimensionless parameters: the aspect ratio of the slots, the Strouhal number, the Reynolds number, the phase difference between the jets and the spacing between the slots. In the present study, the influence of the latter four on the vectoring behaviour of the jets is examined experimentally using particle image velocimetry. Time-averaged velocity maps are used to study the variations in vectoring behaviour for a parametric sweep of each of the four parameters independently. A topological map is constructed for the full four-dimensional parameter space. The vectoring behaviour is described both qualitatively and quantitatively. A vectoring mechanism is proposed, based on measured vortex positions. We acknowledge the financial support from the European Research Council (ERC Grant Agreement No. 277472).

Resident Space Object Characterization and Behavior Understanding via Machine Learning and Ontology-based Bayesian Networks

NASA Astrophysics Data System (ADS)

Furfaro, R.; Linares, R.; Gaylor, D.; Jah, M.; Walls, R.

2016-09-01

In this paper, we present an end-to-end approach that employs machine learning techniques and Ontology-based Bayesian Networks (BN) to characterize the behavior of resident space objects. State-of-the-Art machine learning architectures (e.g. Extreme Learning Machines, Convolutional Deep Networks) are trained on physical models to learn the Resident Space Object (RSO) features in the vectorized energy and momentum states and parameters. The mapping from measurements to vectorized energy and momentum states and parameters enables behavior characterization via clustering in the features space and subsequent RSO classification. Additionally, Space Object Behavioral Ontologies (SOBO) are employed to define and capture the domain knowledge-base (KB) and BNs are constructed from the SOBO in a semi-automatic fashion to execute probabilistic reasoning over conclusions drawn from trained classifiers and/or directly from processed data. Such an approach enables integrating machine learning classifiers and probabilistic reasoning to support higher-level decision making for space domain awareness applications. The innovation here is to use these methods (which have enjoyed great success in other domains) in synergy so that it enables a "from data to discovery" paradigm by facilitating the linkage and fusion of large and disparate sources of information via a Big Data Science and Analytics framework.

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.

Predictability of a Coupled Model of ENSO Using Singular Vector Analysis: Optimal Growth and Forecast Skill.

NASA Astrophysics Data System (ADS)

Xue, Yan

The optimal growth and its relationship with the forecast skill of the Zebiak and Cane model are studied using a simple statistical model best fit to the original nonlinear model and local linear tangent models about idealized climatic states (the mean background and ENSO cycles in a long model run), and the actual forecast states, including two sets of runs using two different initialization procedures. The seasonally varying Markov model best fit to a suite of 3-year forecasts in a reduced EOF space (18 EOFs) fits the original nonlinear model reasonably well and has comparable or better forecast skill. The initial error growth in a linear evolution operator A is governed by the eigenvalues of A^{T}A, and the square roots of eigenvalues and eigenvectors of A^{T}A are named singular values and singular vectors. One dominant growing singular vector is found, and the optimal 6 month growth rate is largest for a (boreal) spring start and smallest for a fall start. Most of the variation in the optimal growth rate of the two forecasts is seasonal, attributable to the seasonal variations in the mean background, except that in the cold events it is substantially suppressed. It is found that the mean background (zero anomaly) is the most unstable state, and the "forecast IC states" are more unstable than the "coupled model states". One dominant growing singular vector is found, characterized by north-south and east -west dipoles, convergent winds on the equator in the eastern Pacific and a deepened thermocline in the whole equatorial belt. This singular vector is insensitive to initial time and optimization time, but its final pattern is a strong function of initial states. The ENSO system is inherently unpredictable for the dominant singular vector can amplify 5-fold to 24-fold in 6 months and evolve into the large scales characteristic of ENSO. However, the inherent ENSO predictability is only a secondary factor, while the mismatches between the model and data is a primary factor controlling the current forecast skill.

Gravity Research on Plants: Use of Single-Cell Experimental Models

PubMed Central

Chebli, Youssef; Geitmann, Anja

2011-01-01

Future space missions and implementation of permanent bases on Moon and Mars will greatly depend on the availability of ambient air and sustainable food supply. Therefore, understanding the effects of altered gravity conditions on plant metabolism and growth is vital for space missions and extra-terrestrial human existence. In this mini-review we summarize how plant cells are thought to perceive changes in magnitude and orientation of the gravity vector. The particular advantages of several single-celled model systems for gravity research are explored and an overview over recent advancements and potential use of these systems is provided. PMID:22639598

Semantic Search of Web Services

ERIC Educational Resources Information Center

Hao, Ke

2013-01-01

This dissertation addresses semantic search of Web services using natural language processing. We first survey various existing approaches, focusing on the fact that the expensive costs of current semantic annotation frameworks result in limited use of semantic search for large scale applications. We then propose a vector space model based service…

Development of 4D mathematical observer models for the task-based evaluation of gated myocardial perfusion SPECT

NASA Astrophysics Data System (ADS)

Lee, Taek-Soo; Frey, Eric C.; Tsui, Benjamin M. W.

2015-04-01

This paper presents two 4D mathematical observer models for the detection of motion defects in 4D gated medical images. Their performance was compared with results from human observers in detecting a regional motion abnormality in simulated 4D gated myocardial perfusion (MP) SPECT images. The first 4D mathematical observer model extends the conventional channelized Hotelling observer (CHO) based on a set of 2D spatial channels and the second is a proposed model that uses a set of 4D space-time channels. Simulated projection data were generated using the 4D NURBS-based cardiac-torso (NCAT) phantom with 16 gates/cardiac cycle. The activity distribution modelled uptake of 99mTc MIBI with normal perfusion and a regional wall motion defect. An analytical projector was used in the simulation and the filtered backprojection (FBP) algorithm was used in image reconstruction followed by spatial and temporal low-pass filtering with various cut-off frequencies. Then, we extracted 2D image slices from each time frame and reorganized them into a set of cine images. For the first model, we applied 2D spatial channels to the cine images and generated a set of feature vectors that were stacked for the images from different slices of the heart. The process was repeated for each of the 1,024 noise realizations, and CHO and receiver operating characteristics (ROC) analysis methodologies were applied to the ensemble of the feature vectors to compute areas under the ROC curves (AUCs). For the second model, a set of 4D space-time channels was developed and applied to the sets of cine images to produce space-time feature vectors to which the CHO methodology was applied. The AUC values of the second model showed better agreement (Spearman’s rank correlation (SRC) coefficient = 0.8) to human observer results than those from the first model (SRC coefficient = 0.4). The agreement with human observers indicates the proposed 4D mathematical observer model provides a good predictor of the performance of human observers in detecting regional motion defects in 4D gated MP SPECT images. The result supports the use of the observer model in the optimization and evaluation of 4D image reconstruction and compensation methods for improving the detection of motion abnormalities in 4D gated MP SPECT images.

Combined-probability space and certainty or uncertainty relations for a finite-level quantum system

NASA Astrophysics Data System (ADS)

Sehrawat, Arun

2017-08-01

The Born rule provides a probability vector (distribution) with a quantum state for a measurement setting. For two settings, we have a pair of vectors from the same quantum state. Each pair forms a combined-probability vector that obeys certain quantum constraints, which are triangle inequalities in our case. Such a restricted set of combined vectors, called the combined-probability space, is presented here for a d -level quantum system (qudit). The combined space is a compact convex subset of a Euclidean space, and all its extreme points come from a family of parametric curves. Considering a suitable concave function on the combined space to estimate the uncertainty, we deliver an uncertainty relation by finding its global minimum on the curves for a qudit. If one chooses an appropriate concave (or convex) function, then there is no need to search for the absolute minimum (maximum) over the whole space; it will be on the parametric curves. So these curves are quite useful for establishing an uncertainty (or a certainty) relation for a general pair of settings. We also demonstrate that many known tight certainty or uncertainty relations for a qubit can be obtained with the triangle inequalities.

Spectrum-doubled heavy vector bosons at the LHC

DOE PAGES

Appelquist, Thomas; Bai, Yang; Ingoldby, James; ...

2016-01-19

We study a simple effective field theory incorporating six heavy vector bosons together with the standard-model field content. The new particles preserve custodial symmetry as well as an approximate left-right parity symmetry. The enhanced symmetry of the model allows it to satisfy precision electroweak constraints and bounds from Higgs physics in a regime where all the couplings are perturbative and where the amount of fine-tuning is comparable to that in the standard model itself. We find that the model could explain the recently observed excesses in di-boson processes at invariant mass close to 2TeV from LHC Run 1 for amore » range of allowed parameter space. The masses of all the particles differ by no more than roughly 10%. In a portion of the allowed parameter space only one of the new particles has a production cross section large enough to be detectable with the energy and luminosity of Run 1, both via its decay to WZ and to Wh, while the others have suppressed production rates. Furthermore, the model can be tested at the higher-energy and higher-luminosity run of the LHC even for an overall scale of the new particles higher than 3TeV.« less

Informedia at TRECVID2014: MED and MER, Semantic Indexing, Surveillance Event Detection

DTIC Science & Technology

2014-11-10

multiple ranked lists for a given system query. Our system incorporates various retrieval methods such as Vector Space Model, tf-idf, BM25, language...separable space before applying the linear classifier. As the EFM is an approximation, we run the risk of a slight drop in performance. Figure 4 shows...validation set are fused. • CMU_Run3: After removing junk shots (by the junk /black frame detectors), MultiModal Pseudo Relevance Feedback (MMPRF) [12

Methods of Contemporary Gauge Theory

NASA Astrophysics Data System (ADS)

Makeenko, Yuri

2002-08-01

Preface; Part I. Path Integrals: 1. Operator calculus; 2. Second quantization; 3. Quantum anomalies from path integral; 4. Instantons in quantum mechanics; Part II. Lattice Gauge Theories: 5. Observables in gauge theories; 6. Gauge fields on a lattice; 7. Lattice methods; 8. Fermions on a lattice; 9. Finite temperatures; Part III. 1/N Expansion: 10. O(N) vector models; 11. Multicolor QCD; 12. QCD in loop space; 13. Matrix models; Part IV. Reduced Models: 14. Eguchi-Kawai model; 15. Twisted reduced models; 16. Non-commutative gauge theories.

Methods of Contemporary Gauge Theory

NASA Astrophysics Data System (ADS)

Makeenko, Yuri

2005-11-01

Preface; Part I. Path Integrals: 1. Operator calculus; 2. Second quantization; 3. Quantum anomalies from path integral; 4. Instantons in quantum mechanics; Part II. Lattice Gauge Theories: 5. Observables in gauge theories; 6. Gauge fields on a lattice; 7. Lattice methods; 8. Fermions on a lattice; 9. Finite temperatures; Part III. 1/N Expansion: 10. O(N) vector models; 11. Multicolor QCD; 12. QCD in loop space; 13. Matrix models; Part IV. Reduced Models: 14. Eguchi-Kawai model; 15. Twisted reduced models; 16. Non-commutative gauge theories.

Error enhancement in geomagnetic models derived from scalar data

NASA Technical Reports Server (NTRS)

Stern, D. P.; Bredekamp, J. H.

1975-01-01

An investigation conducted by Backus (1970) regarding the possible existence of two harmonic functions of certain characteristics in three-dimensional space is considered. The derivation of a model of the main geomagnetic field from scalar data is discussed along with a numerical simulation study. It is found that experimental discrepancies between vector field observations and the predictions of the model may have a mathematical origin, related to the work of Backus.

O Electromagnetic Power Waves and Power Density Components.

NASA Astrophysics Data System (ADS)

Petzold, Donald Wayne

1980-12-01

On January 10, 1884 Lord Rayleigh presented a paper entitled "On the Transfer of Energy in the Electromagnetic Field" to the Royal Society of London. This paper had been authored by the late Fellow of Trinity College, Cambridge, Professor J. H. Poynting and in it he claimed that there was a general law for the transfer of electromagnetic energy. He argued that associated with each point in space is a quantity, that has since been called the Poynting vector, that is a measure of the rate of energy flow per unit area. His analysis was concerned with the integration of this power density vector at all points over an enclosing surface of a specific volume. The interpretation of this Poynting vector as a true measure of the local power density was viewed with great skepticism unless the vector was integrated over a closed surface, as the development of the concept required. However, within the last decade or so Shadowitz indicates that a number of prominent authors have argued that the criticism of the interpretation of Poynting's vector as a local power density vector is unjustified. The present paper is not concerned with these arguments but instead is concerned with a decomposition of Poynting's power density vector into two and only two components: one vector which has the same direction as Poynting's vector and which is called the forward power density vector, and another vector, directed opposite to the Poynting vector and called the reverse power density vector. These new local forward and reverse power density vectors will be shown to be dependent upon forward and reverse power wave vectors and these vectors in turn will be related to newly defined forward and reverse components of the electric and magnetic fields. The sum of these forward and reverse power density vectors, which is simply the original Poynting vector, is associated with the total electromagnetic energy traveling past the local point. Another vector which is the difference between the forward and reverse power density vectors and which will be shown to be associated with the total electric and magnetic field energy densities existing at a local point will also be introduced. These local forward and reverse power density vectors may be integrated over a surface to determine the forward and reverse powers and from these results problems related to maximum power transfer or efficiency of electromagnetic energy transmission in space may be studied in a manner similar to that presently being done with transmission lines, wave guides, and more recently with two port multiport lumped parameter systems. These new forward and reverse power density vectors at a point in space are analogous to the forward and revoltages or currents and power waves as used with the transmission line, waveguide, or port. These power wave vectors in space are a generalization of the power waves as developed by Penfield, Youla, and Kurokawa and used with the scattering parameters associated with transmission lines, waveguides and ports.

Human action classification using procrustes shape theory

NASA Astrophysics Data System (ADS)

Cho, Wanhyun; Kim, Sangkyoon; Park, Soonyoung; Lee, Myungeun

2015-02-01

In this paper, we propose new method that can classify a human action using Procrustes shape theory. First, we extract a pre-shape configuration vector of landmarks from each frame of an image sequence representing an arbitrary human action, and then we have derived the Procrustes fit vector for pre-shape configuration vector. Second, we extract a set of pre-shape vectors from tanning sample stored at database, and we compute a Procrustes mean shape vector for these preshape vectors. Third, we extract a sequence of the pre-shape vectors from input video, and we project this sequence of pre-shape vectors on the tangent space with respect to the pole taking as a sequence of mean shape vectors corresponding with a target video. And we calculate the Procrustes distance between two sequences of the projection pre-shape vectors on the tangent space and the mean shape vectors. Finally, we classify the input video into the human action class with minimum Procrustes distance. We assess a performance of the proposed method using one public dataset, namely Weizmann human action dataset. Experimental results reveal that the proposed method performs very good on this dataset.

Theory of the lattice Boltzmann Method: Dispersion, Dissipation, Isotropy, Galilean Invariance, and Stability

NASA Technical Reports Server (NTRS)

Lallemand, Pierre; Luo, Li-Shi

2000-01-01

The generalized hydrodynamics (the wave vector dependence of the transport coefficients) of a generalized lattice Boltzmann equation (LBE) is studied in detail. The generalized lattice Boltzmann equation is constructed in moment space rather than in discrete velocity space. The generalized hydrodynamics of the model is obtained by solving the dispersion equation of the linearized LBE either analytically by using perturbation technique or numerically. The proposed LBE model has a maximum number of adjustable parameters for the given set of discrete velocities. Generalized hydrodynamics characterizes dispersion, dissipation (hyper-viscosities), anisotropy, and lack of Galilean invariance of the model, and can be applied to select the values of the adjustable parameters which optimize the properties of the model. The proposed generalized hydrodynamic analysis also provides some insights into stability and proper initial conditions for LBE simulations. The stability properties of some 2D LBE models are analyzed and compared with each other in the parameter space of the mean streaming velocity and the viscous relaxation time. The procedure described in this work can be applied to analyze other LBE models. As examples, LBE models with various interpolation schemes are analyzed. Numerical results on shear flow with an initially discontinuous velocity profile (shock) with or without a constant streaming velocity are shown to demonstrate the dispersion effects in the LBE model; the results compare favorably with our theoretical analysis. We also show that whereas linear analysis of the LBE evolution operator is equivalent to Chapman-Enskog analysis in the long wave-length limit (wave vector k = 0), it can also provide results for large values of k. Such results are important for the stability and other hydrodynamic properties of the LBE method and cannot be obtained through Chapman-Enskog analysis.

Vector wind profile gust model

NASA Technical Reports Server (NTRS)

Adelfang, S. I.

1979-01-01

Work towards establishing a vector wind profile gust model for the Space Transportation System flight operations and trade studies is reported. To date, all the statistical and computational techniques required were established and partially implemented. An analysis of wind profile gust at Cape Kennedy within the theoretical framework is presented. The variability of theoretical and observed gust magnitude with filter type, altitude, and season is described. Various examples are presented which illustrate agreement between theoretical and observed gust percentiles. The preliminary analysis of the gust data indicates a strong variability with altitude, season, and wavelength regime. An extension of the analyses to include conditional distributions of gust magnitude given gust length, distributions of gust modulus, and phase differences between gust components has begun.

Fast proton decay

NASA Astrophysics Data System (ADS)

Li, Tianjun; Nanopoulos, Dimitri V.; Walker, Joel W.

2010-10-01

We consider proton decay in the testable flipped SU(5)×U(1)X models with TeV-scale vector-like particles which can be realized in free fermionic string constructions and F-theory model building. We significantly improve upon the determination of light threshold effects from prior studies, and perform a fresh calculation of the second loop for the process p→eπ from the heavy gauge boson exchange. The cumulative result is comparatively fast proton decay, with a majority of the most plausible parameter space within reach of the future Hyper-Kamiokande and DUSEL experiments. Because the TeV-scale vector-like particles can be produced at the LHC, we predict a strong correlation between the most exciting particle physics experiments of the coming decade.

Bright, dark, and mixed vector soliton solutions of the general coupled nonlinear Schrödinger equations.

PubMed

Agalarov, Agalar; Zhulego, Vladimir; Gadzhimuradov, Telman

2015-04-01

The reduction procedure for the general coupled nonlinear Schrödinger (GCNLS) equations with four-wave mixing terms is proposed. It is shown that the GCNLS system is equivalent to the well known integrable families of the Manakov and Makhankov U(n,m)-vector models. This equivalence allows us to construct bright-bright and dark-dark solitons and a quasibreather-dark solution with unconventional dynamics: the density of the first component oscillates in space and time, whereas the density of the second component does not. The collision properties of solitons are also studied.

Feasibility study for a numerical aerodynamic simulation facility. Volume 3: FMP language specification/user manual

NASA Technical Reports Server (NTRS)

Kenner, B. G.; Lincoln, N. R.

1979-01-01

The manual is intended to show the revisions and additions to the current STAR FORTRAN. The changes are made to incorporate an FMP (Flow Model Processor) for use in the Numerical Aerodynamic Simulation Facility (NASF) for the purpose of simulating fluid flow over three-dimensional bodies in wind tunnel environments and in free space. The FORTRAN programming language for the STAR-100 computer contains both CDC and unique STAR extensions to the standard FORTRAN. Several of the STAR FORTRAN extensions to standard FOR-TRAN allow the FORTRAN user to exploit the vector processing capabilities of the STAR computer. In STAR FORTRAN, vectors can be expressed with an explicit notation, functions are provided that return vector results, and special call statements enable access to any machine instruction.

Optimized decoy state QKD for underwater free space communication

NASA Astrophysics Data System (ADS)

Lopes, Minal; Sarwade, Nisha

Quantum cryptography (QC) is envisioned as a solution for global key distribution through fiber optic, free space and underwater optical communication due to its unconditional security. In view of this, this paper investigates underwater free space quantum key distribution (QKD) model for enhanced transmission distance, secret key rates and security. It is reported that secure underwater free space QKD is feasible in the clearest ocean water with the sifted key rates up to 207kbps. This paper extends this work by testing performance of optimized decoy state QKD protocol with underwater free space communication model. The attenuation of photons, quantum bit error rate and the sifted key generation rate of underwater quantum communication is obtained with vector radiative transfer theory and Monte Carlo method. It is observed from the simulations that optimized decoy state QKD evidently enhances the underwater secret key transmission distance as well as secret key rates.

Topic detection using paragraph vectors to support active learning in systematic reviews.

PubMed

Hashimoto, Kazuma; Kontonatsios, Georgios; Miwa, Makoto; Ananiadou, Sophia

2016-08-01

Systematic reviews require expert reviewers to manually screen thousands of citations in order to identify all relevant articles to the review. Active learning text classification is a supervised machine learning approach that has been shown to significantly reduce the manual annotation workload by semi-automating the citation screening process of systematic reviews. In this paper, we present a new topic detection method that induces an informative representation of studies, to improve the performance of the underlying active learner. Our proposed topic detection method uses a neural network-based vector space model to capture semantic similarities between documents. We firstly represent documents within the vector space, and cluster the documents into a predefined number of clusters. The centroids of the clusters are treated as latent topics. We then represent each document as a mixture of latent topics. For evaluation purposes, we employ the active learning strategy using both our novel topic detection method and a baseline topic model (i.e., Latent Dirichlet Allocation). Results obtained demonstrate that our method is able to achieve a high sensitivity of eligible studies and a significantly reduced manual annotation cost when compared to the baseline method. This observation is consistent across two clinical and three public health reviews. The tool introduced in this work is available from https://nactem.ac.uk/pvtopic/. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Application of Hyperspectal Techniques to Monitoring & Management of Invasive Plant Species Infestation

DTIC Science & Technology

2008-01-09

The image data as acquired from the sensor is a data cloud in multi- dimensional space with each band generating an axis of dimension. When the data... The color of a material is defined by the direction of its unit vector in n- dimensional spectral space . The length of the vector relates only to how...to n- dimensional space . SAM determines the similarity

Development of a NEW Vector Magnetograph at Marshall Space Flight Center

NASA Technical Reports Server (NTRS)

West, Edward; Hagyard, Mona; Gary, Allen; Smith, James; Adams, Mitzi; Rose, M. Franklin (Technical Monitor)

2001-01-01

This paper will describe the Experimental Vector Magnetograph that has been developed at the Marshall Space Flight Center (MSFC). This instrument was designed to improve linear polarization measurements by replacing electro-optic and rotating waveplate modulators with a rotating linear analyzer. Our paper will describe the motivation for developing this magnetograph, compare this instrument with traditional magnetograph designs, and present a comparison of the data acquired by this instrument and original MSFC vector magnetograph.

Evaluation and Validation of Operational RapidScat Ocean Surface Vector Winds

NASA Astrophysics Data System (ADS)

Chang, Paul; Jelenak, Zorana; Soisuvarn, Seubson; Said, Faozi; Sienkiewicz, Joseph; Brennan, Michael

2015-04-01

NASA launched RapidScat to the International Space Station (ISS) on September 21, 2014 on a two-year mission to support global monitoring of ocean winds for improved weather forecasting and climate studies. The JPL-developed space-based scatterometer is conically scanning and operates at ku-band (13.4 GHz) similar to QuikSCAT. The ISS-RapidScat's measurement swath is approximately 900 kilometers and covers the majority of the ocean between 51.6 degrees north and south latitude (approximately from north of Vancouver, Canada, to the southern tip of Patagonia) in 48 hours. RapidScat data are currently being posted at a spacing of 25 kilometers, but a version to be released in the near future will improve the postings to 12.5 kilometers. RapidScat ocean surface wind vector data are being provided in near real-time to NOAA, and other operational users such as the U.S. Navy, the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), the Indian Space Research Organisation (ISRO) and the Royal Netherlands Meteorological Institute (KNMI). The quality of the RapidScat OSVW data are assessed by collocating the data in space and time with "truth" data. Typically "truth" data will include, but are not limited to, the NWS global forecast model analysis (GDAS) fields, buoys, ASCAT, WindSat, AMSR-2, and aircraft measurements during hurricane and winter storm experiment flights. The standard statistical analysis used for satellite microwave wind sensors will be utilized to characterize the RapidScat wind vector retrievals. The global numerical weather prediction (NWP) models are a convenient source of "truth" data because they are available 4 times/day globally which results in the accumulation of a large number of collocations over a relatively short amount of time. The NWP model fields are not "truth" in the same way an actual observation would be, however, as long as there are no systematic errors in the NWP model output the collocations will converge in the mean for winds between approximately 3-20 m/s. The NWP models typically do not properly resolve the very low and high wind speeds in part due to limitations of the spatial scales they can account for. Buoy measurements, aircraft-based measurements and other satellite retrievals can be more directly compared on a point-by-point basis. The RapidScat OSVW validation results will be presented and discussed. Utilization examples of these data in support of NOAA's marine weather forecasting and warning mission will also be presented and discussed.

Tests and analysis of a vented D thrust deflecting nozzle on a turbofan engine. [conducted at the outdoor aerodynamic research facility of the Ames Research Center

NASA Technical Reports Server (NTRS)

Roseberg, E. W.

1982-01-01

The objectives were to: obtain nozzle performance characteristics in and out of ground effects; demonstrate the compatibility of the nozzle with a turbofan engine; obtain pressure and temperature distributions on the surface of the D vented nozzle; and establish a correlation of the nozzle performance between small scale and large scale models. The test nozzle was a boilerplate model of the MCAIR D vented nozzle configured for operation with a General Electric YTF-34-F5 turbofan engine. The nozzle was configured to provide: a thrust vectoring range of 0 to 115 deg; a yaw vectoring range of 0 to 10 deg; variable nozzle area control; and variable spacing between the core exit and nozzle entrance station. Compatibility between the YTF-34-T5 turbofan engine and the D vented nozzle was demonstrated. Velocity coefficients of 0.96 and greater were obtained for 90 deg of thrust vectoring. The nozzle walls remained cool during all test conditions.

Model of Four-Dimensional Sub-Proton Euclidean Space with Real Time for Valence Quarks. Lagrangian Mechanics

NASA Astrophysics Data System (ADS)

Kreymer, E. L.

2018-06-01

The model of Euclidean space with imaginary time used in sub-hadron physics uses only part of it since this part is isomorphic to Minkowski space and has the velocity limit 0 ≤ ||v Ei|| ≤ 1. The model of four-dimensional Euclidean space with real time (E space), in which 0 ≤ ||v E|| ≤ ∞ is investigated. The vectors of this space have E-invariants, equal or analogous to the invariants of Minkowski space. All relations between physical quantities in E-space, after they are mapped into Minkowski space, satisfy the principles of SRT and are Lorentz-invariant, and the velocity of light corresponds to infinite velocity. Results obtained in the model are different from the physical laws in Minkowski space. Thus, from the model of the Lagrangian mechanics of quarks in a centrally symmetric attractive potential it follows that the energy-mass of a quark decreases with increase of the velocity and is equal to zero for v = ∞. This made it possible to establish the conditions of emission and absorption of gluons by quarks. The effect of emission of gluons by high-energy quarks was discovered experimentally significantly earlier. The model describes for the first time the dynamic coupling of the masses of constituent and current quarks and reveals new possibilities in the study of intrahardon space. The classical trajectory of the oscillation of quarks in protons is described.

Fine-scale mapping of vector habitats using very high resolution satellite imagery: a liver fluke case-study.

PubMed

De Roeck, Els; Van Coillie, Frieke; De Wulf, Robert; Soenen, Karen; Charlier, Johannes; Vercruysse, Jozef; Hantson, Wouter; Ducheyne, Els; Hendrickx, Guy

2014-12-01

The visualization of vector occurrence in space and time is an important aspect of studying vector-borne diseases. Detailed maps of possible vector habitats provide valuable information for the prediction of infection risk zones but are currently lacking for most parts of the world. Nonetheless, monitoring vector habitats from the finest scales up to farm level is of key importance to refine currently existing broad-scale infection risk models. Using Fasciola hepatica, a parasite liver fluke, as a case in point, this study illustrates the potential of very high resolution (VHR) optical satellite imagery to efficiently and semi-automatically detect detailed vector habitats. A WorldView2 satellite image capable of <5m resolution was acquired in the spring of 2013 for the area around Bruges, Belgium, a region where dairy farms suffer from liver fluke infections transmitted by freshwater snails. The vector thrives in small water bodies (SWBs), such as ponds, ditches and other humid areas consisting of open water, aquatic vegetation and/or inundated grass. These water bodies can be as small as a few m2 and are most often not present on existing land cover maps because of their small size. We present a classification procedure based on object-based image analysis (OBIA) that proved valuable to detect SWBs at a fine scale in an operational and semi-automated way. The classification results were compared to field and other reference data such as existing broad-scale maps and expert knowledge. Overall, the SWB detection accuracy reached up to 87%. The resulting fine-scale SWB map can be used as input for spatial distribution modelling of the liver fluke snail vector to enable development of improved infection risk mapping and management advice adapted to specific, local farm situations.

Pattern Classification Using an Olfactory Model with PCA Feature Selection in Electronic Noses: Study and Application

PubMed Central

Fu, Jun; Huang, Canqin; Xing, Jianguo; Zheng, Junbao

2012-01-01

Biologically-inspired models and algorithms are considered as promising sensor array signal processing methods for electronic noses. Feature selection is one of the most important issues for developing robust pattern recognition models in machine learning. This paper describes an investigation into the classification performance of a bionic olfactory model with the increase of the dimensions of input feature vector (outer factor) as well as its parallel channels (inner factor). The principal component analysis technique was applied for feature selection and dimension reduction. Two data sets of three classes of wine derived from different cultivars and five classes of green tea derived from five different provinces of China were used for experiments. In the former case the results showed that the average correct classification rate increased as more principal components were put in to feature vector. In the latter case the results showed that sufficient parallel channels should be reserved in the model to avoid pattern space crowding. We concluded that 6∼8 channels of the model with principal component feature vector values of at least 90% cumulative variance is adequate for a classification task of 3∼5 pattern classes considering the trade-off between time consumption and classification rate. PMID:22736979

The BGS magnetic field candidate models for the 12th generation IGRF

NASA Astrophysics Data System (ADS)

Hamilton, Brian; Ridley, Victoria A.; Beggan, Ciarán D.; Macmillan, Susan

2015-05-01

We describe the candidate models submitted by the British Geological Survey for the 12th generation International Geomagnetic Reference Field. These models are extracted from a spherical harmonic `parent model' derived from vector and scalar magnetic field data from satellite and observatory sources. These data cover the period 2009.0 to 2014.7 and include measurements from the recently launched European Space Agency (ESA) Swarm satellite constellation. The parent model's internal field time dependence for degrees 1 to 13 is represented by order 6 B-splines with knots at yearly intervals. The parent model's degree 1 external field time dependence is described by periodic functions for the annual and semi-annual signals and by dependence on the 20-min Vector Magnetic Disturbance index. Signals induced by these external fields are also parameterized. Satellite data are weighted by spatial density and by two different noise estimators: (a) by standard deviation along segments of the satellite track and (b) a larger-scale noise estimator defined in terms of a measure of vector activity at the geographically closest magnetic observatories to the sample point. Forecasting of the magnetic field secular variation beyond the span of data is by advection of the main field using core surface flows.

Effective gravitational couplings for cosmological perturbations in generalized Proca theories

NASA Astrophysics Data System (ADS)

De Felice, Antonio; Heisenberg, Lavinia; Kase, Ryotaro; Mukohyama, Shinji; Tsujikawa, Shinji; Zhang, Ying-li

2016-08-01

We consider the finite interactions of the generalized Proca theory including the sixth-order Lagrangian and derive the full linear perturbation equations of motion on the flat Friedmann-Lemaître-Robertson-Walker background in the presence of a matter perfect fluid. By construction, the propagating degrees of freedom (besides the matter perfect fluid) are two transverse vector perturbations, one longitudinal scalar, and two tensor polarizations. The Lagrangians associated with intrinsic vector modes neither affect the background equations of motion nor the second-order action of tensor perturbations, but they do give rise to nontrivial modifications to the no-ghost condition of vector perturbations and to the propagation speeds of vector and scalar perturbations. We derive the effective gravitational coupling Geff with matter density perturbations under a quasistatic approximation on scales deep inside the sound horizon. We find that the existence of intrinsic vector modes allows a possibility for reducing Geff. In fact, within the parameter space, Geff can be even smaller than the Newton gravitational constant G at the late cosmological epoch, with a peculiar phantom dark energy equation of state (without ghosts). The modifications to the slip parameter η and the evolution of the growth rate f σ8 are discussed as well. Thus, dark energy models in the framework of generalized Proca theories can be observationally distinguished from the Λ CDM model according to both cosmic growth and expansion history. Furthermore, we study the evolution of vector perturbations and show that outside the vector sound horizon the perturbations are nearly frozen and start to decay with oscillations after the horizon entry.

Ensemble Data Assimilation Without Ensembles: Methodology and Application to Ocean Data Assimilation

NASA Technical Reports Server (NTRS)

Keppenne, Christian L.; Rienecker, Michele M.; Kovach, Robin M.; Vernieres, Guillaume

2013-01-01

Two methods to estimate background error covariances for data assimilation are introduced. While both share properties with the ensemble Kalman filter (EnKF), they differ from it in that they do not require the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The first method is referred-to as SAFE (Space Adaptive Forecast error Estimation) because it estimates error covariances from the spatial distribution of model variables within a single state vector. It can thus be thought of as sampling an ensemble in space. The second method, named FAST (Flow Adaptive error Statistics from a Time series), constructs an ensemble sampled from a moving window along a model trajectory. The underlying assumption in these methods is that forecast errors in data assimilation are primarily phase errors in space and/or time.

Acoustic 3D modeling by the method of integral equations

NASA Astrophysics Data System (ADS)

Malovichko, M.; Khokhlov, N.; Yavich, N.; Zhdanov, M.

2018-02-01

This paper presents a parallel algorithm for frequency-domain acoustic modeling by the method of integral equations (IE). The algorithm is applied to seismic simulation. The IE method reduces the size of the problem but leads to a dense system matrix. A tolerable memory consumption and numerical complexity were achieved by applying an iterative solver, accompanied by an effective matrix-vector multiplication operation, based on the fast Fourier transform (FFT). We demonstrate that, the IE system matrix is better conditioned than that of the finite-difference (FD) method, and discuss its relation to a specially preconditioned FD matrix. We considered several methods of matrix-vector multiplication for the free-space and layered host models. The developed algorithm and computer code were benchmarked against the FD time-domain solution. It was demonstrated that, the method could accurately calculate the seismic field for the models with sharp material boundaries and a point source and receiver located close to the free surface. We used OpenMP to speed up the matrix-vector multiplication, while MPI was used to speed up the solution of the system equations, and also for parallelizing across multiple sources. The practical examples and efficiency tests are presented as well.

Fixed points, stable manifolds, weather regimes, and their predictability.

PubMed

Deremble, Bruno; D'Andrea, Fabio; Ghil, Michael

2009-12-01

In a simple, one-layer atmospheric model, we study the links between low-frequency variability and the model's fixed points in phase space. The model dynamics is characterized by the coexistence of multiple "weather regimes." To investigate the transitions from one regime to another, we focus on the identification of stable manifolds associated with fixed points. We show that these manifolds act as separatrices between regimes. We track each manifold by making use of two local predictability measures arising from the meteorological applications of nonlinear dynamics, namely, "bred vectors" and singular vectors. These results are then verified in the framework of ensemble forecasts issued from "clouds" (ensembles) of initial states. The divergence of the trajectories allows us to establish the connections between zones of low predictability, the geometry of the stable manifolds, and transitions between regimes.

An Inter-Personal Information Sharing Model Based on Personalized Recommendations

NASA Astrophysics Data System (ADS)

Kamei, Koji; Funakoshi, Kaname; Akahani, Jun-Ichi; Satoh, Tetsuji

In this paper, we propose an inter-personal information sharing model among individuals based on personalized recommendations. In the proposed model, we define an information resource as shared between people when both of them consider it important --- not merely when they both possess it. In other words, the model defines the importance of information resources based on personalized recommendations from identifiable acquaintances. The proposed method is based on a collaborative filtering system that focuses on evaluations from identifiable acquaintances. It utilizes both user evaluations for documents and their contents. In other words, each user profile is represented as a matrix of credibility to the other users' evaluations on each domain of interests. We extended the content-based collaborative filtering method to distinguish other users to whom the documents should be recommended. We also applied a concept-based vector space model to represent the domain of interests instead of the previous method which represented them by a term-based vector space model. We introduce a personalized concept-base compiled from each user's information repository to improve the information retrieval in the user's environment. Furthermore, the concept-spaces change from user to user since they reflect the personalities of the users. Because of different concept-spaces, the similarity between a document and a user's interest varies for each user. As a result, a user receives recommendations from other users who have different view points, achieving inter-personal information sharing based on personalized recommendations. This paper also describes an experimental simulation of our information sharing model. In our laboratory, five participants accumulated a personal repository of e-mails and web pages from which they built their own concept-base. Then we estimated the user profiles according to personalized concept-bases and sets of documents which others evaluated. We simulated inter-personal recommendation based on the user profiles and evaluated the performance of the recommendation method by comparing the recommended documents to the result of the content-based collaborative filtering.

A Neural Network Architecture For Rapid Model Indexing In Computer Vision Systems

NASA Astrophysics Data System (ADS)

Pawlicki, Ted

1988-03-01

Models of objects stored in memory have been shown to be useful for guiding the processing of computer vision systems. A major consideration in such systems, however, is how stored models are initially accessed and indexed by the system. As the number of stored models increases, the time required to search memory for the correct model becomes high. Parallel distributed, connectionist, neural networks' have been shown to have appealing content addressable memory properties. This paper discusses an architecture for efficient storage and reference of model memories stored as stable patterns of activity in a parallel, distributed, connectionist, neural network. The emergent properties of content addressability and resistance to noise are exploited to perform indexing of the appropriate object centered model from image centered primitives. The system consists of three network modules each of which represent information relative to a different frame of reference. The model memory network is a large state space vector where fields in the vector correspond to ordered component objects and relative, object based spatial relationships between the component objects. The component assertion network represents evidence about the existence of object primitives in the input image. It establishes local frames of reference for object primitives relative to the image based frame of reference. The spatial relationship constraint network is an intermediate representation which enables the association between the object based and the image based frames of reference. This intermediate level represents information about possible object orderings and establishes relative spatial relationships from the image based information in the component assertion network below. It is also constrained by the lawful object orderings in the model memory network above. The system design is consistent with current psychological theories of recognition by component. It also seems to support Marr's notions of hierarchical indexing. (i.e. the specificity, adjunct, and parent indices) It supports the notion that multiple canonical views of an object may have to be stored in memory to enable its efficient identification. The use of variable fields in the state space vectors appears to keep the number of required nodes in the network down to a tractable number while imposing a semantic value on different areas of the state space. This semantic imposition supports an interface between the analogical aspects of neural networks and the propositional paradigms of symbolic processing.

Internal and external potential-field estimation from regional vector data at varying satellite altitude

NASA Astrophysics Data System (ADS)

Plattner, Alain; Simons, Frederik J.

2017-10-01

When modelling satellite data to recover a global planetary magnetic or gravitational potential field, the method of choice remains their analysis in terms of spherical harmonics. When only regional data are available, or when data quality varies strongly with geographic location, the inversion problem becomes severely ill-posed. In those cases, adopting explicitly local methods is to be preferred over adapting global ones (e.g. by regularization). Here, we develop the theory behind a procedure to invert for planetary potential fields from vector observations collected within a spatially bounded region at varying satellite altitude. Our method relies on the construction of spatiospectrally localized bases of functions that mitigate the noise amplification caused by downward continuation (from the satellite altitude to the source) while balancing the conflicting demands for spatial concentration and spectral limitation. The `altitude-cognizant' gradient vector Slepian functions (AC-GVSF) enjoy a noise tolerance under downward continuation that is much improved relative to the `classical' gradient vector Slepian functions (CL-GVSF), which do not factor satellite altitude into their construction. Furthermore, venturing beyond the realm of their first application, published in a preceding paper, in the present article we extend the theory to being able to handle both internal and external potential-field estimation. Solving simultaneously for internal and external fields under the limitation of regional data availability reduces internal-field artefacts introduced by downward-continuing unmodelled external fields, as we show with numerical examples. We explain our solution strategies on the basis of analytic expressions for the behaviour of the estimation bias and variance of models for which signal and noise are uncorrelated, (essentially) space- and band-limited, and spectrally (almost) white. The AC-GVSF are optimal linear combinations of vector spherical harmonics. Their construction is not altogether very computationally demanding when the concentration domains (the regions of spatial concentration) have circular symmetry, for example, on spherical caps or rings—even when the spherical-harmonic bandwidth is large. Data inversion proceeds by solving for the expansion coefficients of truncated function sequences, by least-squares analysis in a reduced-dimensional space. Hence, our method brings high-resolution regional potential-field modelling from incomplete and noisy vector-valued satellite data within reach of contemporary desktop machines.

An Application of Interactive Computer Graphics to the Study of Inferential Statistics and the General Linear Model

DTIC Science & Technology

1991-09-01

matrix, the Regression Sum of Squares (SSR) and Error Sum of Squares (SSE) are also displayed as a percentage of the Total Sum of Squares ( SSTO ...vector when the student compares the SSR to the SSE. In addition to the plot, the actual values of SSR, SSE, and SSTO are also provided. Figure 3 gives the...Es ainSpace = E 3 Error- Eor Space =n t! L . Pro~cio q Yonto Pro~rct on of Y onto the simaton, pac ror Space SSR SSEL0.20 IV = 14,1 +IErrorI 2 SSTO

Extended spin symmetry and the standard model

NASA Astrophysics Data System (ADS)

Besprosvany, J.; Romero, R.

2010-12-01

We review unification ideas and explain the spin-extended model in this context. Its consideration is also motivated by the standard-model puzzles. With the aim of constructing a common description of discrete degrees of freedom, as spin and gauge quantum numbers, the model departs from q-bits and generalized Hilbert spaces. Physical requirements reduce the space to one that is represented by matrices. The classification of the representations is performed through Clifford algebras, with its generators associated with Lorentz and scalar symmetries. We study a reduced space with up to two spinor elements within a matrix direct product. At given dimension, the demand that Lorentz symmetry be maintained, determines the scalar symmetries, which connect to vector-and-chiral gauge-interacting fields; we review the standard-model information in each dimension. We obtain fermions and bosons, with matter fields in the fundamental representation, radiation fields in the adjoint, and scalar particles with the Higgs quantum numbers. We relate the fields' representation in such spaces to the quantum-field-theory one, and the Lagrangian. The model provides a coupling-constant definition.

Automatic Cataloguing and Searching for Retrospective Data by Use of OCR Text.

ERIC Educational Resources Information Center

Tseng, Yuen-Hsien

2001-01-01

Describes efforts in supporting information retrieval from OCR (optical character recognition) degraded text. Reports on approaches used in an automatic cataloging and searching contest for books in multiple languages, including a vector space retrieval model, an n-gram indexing method, and a weighting scheme; and discusses problems of Asian…

Program documentation. Program description and user information for the hydraulics/auxiliary power unit (HYDRA) computer program. [for the space shuttle orbiter

NASA Technical Reports Server (NTRS)

Redwine, W. J.

1979-01-01

A timeline containing altitude, control surface deflection rates and angles, hinge moment loads, thrust vector control gimbal rates, and main throttle settings is used to derive the model. The timeline is constructed from the output of one or more trajectory simulation programs.

Recombinant Enaction: Manipulatives Generate New Procedures in the Imagination, by Extending and Recombining Action Spaces

ERIC Educational Resources Information Center

Rahaman, Jeenath; Agrawal, Harshit; Srivastava, Nisheeth; Chandrasekharan, Sanjay

2018-01-01

Manipulation of physical models such as tangrams and tiles is a popular approach to teaching early mathematics concepts. This pedagogical approach is extended by new computational media, where mathematical entities such as equations and vectors can be virtually manipulated. The cognitive and neural mechanisms supporting such manipulation-based…

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.

Knowledge Space: A Conceptual Basis for the Organization of Knowledge

ERIC Educational Resources Information Center

Meincke, Peter P. M.; Atherton, Pauline

1976-01-01

Proposes a new conceptual basis for visualizing the organization of information, or knowledge, which differentiates between the concept "vectors" for a field of knowledge represented in a multidimensional space, and the state "vectors" for a person based on his understanding of these concepts, and the representational…

Gibbsian Stationary Non-equilibrium States

NASA Astrophysics Data System (ADS)

De Carlo, Leonardo; Gabrielli, Davide

2017-09-01

We study the structure of stationary non-equilibrium states for interacting particle systems from a microscopic viewpoint. In particular we discuss two different discrete geometric constructions. We apply both of them to determine non reversible transition rates corresponding to a fixed invariant measure. The first one uses the equivalence of this problem with the construction of divergence free flows on the transition graph. Since divergence free flows are characterized by cyclic decompositions we can generate families of models from elementary cycles on the configuration space. The second construction is a functional discrete Hodge decomposition for translational covariant discrete vector fields. According to this, for example, the instantaneous current of any interacting particle system on a finite torus can be canonically decomposed in a gradient part, a circulation term and an harmonic component. All the three components are associated with functions on the configuration space. This decomposition is unique and constructive. The stationary condition can be interpreted as an orthogonality condition with respect to an harmonic discrete vector field and we use this decomposition to construct models having a fixed invariant measure.

A Short-Term and High-Resolution System Load Forecasting Approach Using Support Vector Regression with Hybrid Parameters Optimization

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

Jiang, Huaiguang

This work proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of themore » hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization (PSO) is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system.« less

Investigating the Performance of Alternate Regression Weights by Studying All Possible Criteria in Regression Models with a Fixed Set of Predictors

ERIC Educational Resources Information Center

Waller, Niels; Jones, Jeff

2011-01-01

We describe methods for assessing all possible criteria (i.e., dependent variables) and subsets of criteria for regression models with a fixed set of predictors, x (where x is an n x 1 vector of independent variables). Our methods build upon the geometry of regression coefficients (hereafter called regression weights) in n-dimensional space. For a…

Teleoperator and robotics system analysis

NASA Technical Reports Server (NTRS)

Teoh, William

1987-01-01

The Orbital Maneuvering Vehicle (OMV) was designed to operate as a remotely controlled space teleoperator. The design and implementation of OMM (a mathematical model of the OMV) are discussed. The State Vector Transformation Module (SVX), an interface between the OMV simulation model and the mobile base (TOM-B) of the flat floor simulation system is described. A summary of testing procedures and conclusions are presented together with the test data obtained.

Color TV: total variation methods for restoration of vector-valued images.

PubMed

Blomgren, P; Chan, T F

1998-01-01

We propose a new definition of the total variation (TV) norm for vector-valued functions that can be applied to restore color and other vector-valued images. The new TV norm has the desirable properties of 1) not penalizing discontinuities (edges) in the image, 2) being rotationally invariant in the image space, and 3) reducing to the usual TV norm in the scalar case. Some numerical experiments on denoising simple color images in red-green-blue (RGB) color space are presented.

Modeling and parameter identification of impulse response matrix of mechanical systems

NASA Astrophysics Data System (ADS)

Bordatchev, Evgueni V.

1998-12-01

A method for studying the problem of modeling, identification and analysis of mechanical system dynamic characteristic in view of the impulse response matrix for the purpose of adaptive control is developed here. Two types of the impulse response matrices are considered: (i) on displacement, which describes the space-coupled relationship between vectors of the force and simulated displacement, which describes the space-coupled relationship between vectors of the force and simulated displacement and (ii) on acceleration, which also describes the space-coupled relationship between the vectors of the force and measured acceleration. The idea of identification consists of: (a) the practical obtaining of the impulse response matrix on acceleration by 'impact-response' technique; (b) the modeling and parameter estimation of the each impulse response function on acceleration through the fundamental representation of the impulse response function on displacement as a sum of the damped sine curves applying linear and non-linear least square methods; (c) simulating the impulse provides the additional possibility to calculate masses, damper and spring constants. The damped natural frequencies are used as a priori information and are found through the standard FFT analysis. The problem of double numerical integration is avoided by taking two derivations of the fundamental dynamic model of a mechanical system as linear combination of the mass-damper-spring subsystems. The identified impulse response matrix on displacement represents the dynamic properties of the mechanical system. From the engineering point of view, this matrix can be also understood as a 'dynamic passport' of the mechanical system and can be used for dynamic certification and analysis of the dynamic quality. In addition, the suggested approach mathematically reproduces amplitude-frequency response matrix in a low-frequency band and on zero frequency. This allows the possibility of determining the matrix of the static stiffness due to dynamic testing over the time of 10- 15 minutes. As a practical example, the dynamic properties in view of the impulse and frequency response matrices of the lathe spindle are obtained, identified and investigated. The developed approach for modeling and parameter identification appears promising for a wide range o industrial applications; for example, rotary systems.

A Vector Approach to Euclidean Geometry: Inner Product Spaces, Euclidean Geometry and Trigonometry, Volume 2. Teacher's Edition.

ERIC Educational Resources Information Center

Vaughan, Herbert E.; Szabo, Steven

This is the teacher's edition of a text for the second year of a two-year high school geometry course. The course bases plane and solid geometry and trigonometry on the fact that the translations of a Euclidean space constitute a vector space which has an inner product. Congruence is a geometric topic reserved for Volume 2. Volume 2 opens with an…

Vector mesons in the Nambu-Jona-Lasinio model

NASA Astrophysics Data System (ADS)

Schüren, C.; Döring, F.; Ruiz Arriola, E.; Goeke, K.

1993-12-01

We investigate solitonic solutions with baryon number equal to one of the semi-bosonized SU(2) Nambu-Jona-Lasinio model including σ -, π -, ρ -, A 1- and ω-mesons both on the chiral circle ( σ2r) + π2( r) = f2π) and beyond it ( σ2( r) + π2( r) ≠ f2π). The action is treated in the mesonic and baryonic sector in the leading order of the large- Nc expansion (one-quark-loop approximation). The UV-divergent real part of the effective action is rendered finite using different gauge-invariant regularization methods (Pauli-Villars and proper time). The parameters of the model are fixed in two different ways: either approximately by a heat kernel expansion of the effective action up to second order or by an exact calculation of the mesonic on-shell masses. This leaves the constituent quark mass as the only free parameter of the model. In the solitonic sector we pay special attention to the way the Wick rotation from euclidean space back to Minkowski space has to be performed. We get solitonic solutions from hedgehoglike field configurations on the chiral circle for a wide range of couplings. We also find that if the chiral-circle constraint is relaxed vector mesons provide stable solitonic solutions. Moreover, whether the baryon number is carried by the valence quarks or by the Dirac sea depends strongly on the particular values of the constituent quark mass. We also study the low-energy limit of the model and its connection to chiral perturbation theory. To this end a covariant-derivative expansion is performed in the presence of external fields. After integrating out the scalar, vector and axial degrees of freedom this leads to the corresponding low-energy parameters as e.g. pion radii and some threshold parameters for pion-pion scattering. Vector mesons provide a natural explanation for an axial coupling constant at the quark level gAQ lower than one. However, we find for the gAN of the nucleon noticeable deviations from the non-relativistic quark model prediction g AN = {5}/{3}g AQ. For the values of the parameters where solitons are found, pionic radii come out to be too small. Finally, the relation of the present model to other chiral soliton models as well as some effective lagrangians is displayed.

Vectors and Rotations in 3-Dimensions: Vector Algebra for the C++ Programmer

DTIC Science & Technology

2016-12-01

Proving Ground, MD 21005-5068 This report describes 2 C++ classes: a Vector class for performing vector algebra in 3-dimensional space ( 3D ) and a Rotation...class for performing rotations of vectors in 3D . Each class is self-contained in a single header file (Vector.h and Rotation.h) so that a C...vector, rotation, 3D , quaternion, C++ tools, rotation sequence, Euler angles, yaw, pitch, roll, orientation 98 Richard Saucier 410-278-6721Unclassified

Space-Time Modelling of Groundwater Level Using Spartan Covariance Function

NASA Astrophysics Data System (ADS)

Varouchakis, Emmanouil; Hristopulos, Dionissios

2014-05-01

Geostatistical models often need to handle variables that change in space and in time, such as the groundwater level of aquifers. A major advantage of space-time observations is that a higher number of data supports parameter estimation and prediction. In a statistical context, space-time data can be considered as realizations of random fields that are spatially extended and evolve in time. The combination of spatial and temporal measurements in sparsely monitored watersheds can provide very useful information by incorporating spatiotemporal correlations. Spatiotemporal interpolation is usually performed by applying the standard Kriging algorithms extended in a space-time framework. Spatiotemoral covariance functions for groundwater level modelling, however, have not been widely developed. We present a new non-separable theoretical spatiotemporal variogram function which is based on the Spartan covariance family and evaluate its performance in spatiotemporal Kriging (STRK) interpolation. The original spatial expression (Hristopulos and Elogne 2007) that has been successfully used for the spatial interpolation of groundwater level (Varouchakis and Hristopulos 2013) is modified by defining the following space-time normalized distance h = °h2r-+-α h2τ, hr=r- ξr, hτ=τ- ξτ; where r is the spatial lag vector, τ the temporal lag vector, ξr is the correlation length in position space (r) and ξτ in time (τ), h the normalized space-time lag vector, h = |h| is its Euclidean norm of the normalized space-time lag and α the coefficient that determines the relative weight of the time lag. The space-time experimental semivariogram is determined from the biannual (wet and dry period) time series of groundwater level residuals (obtained from the original series after trend removal) between the years 1981 and 2003 at ten sampling stations located in the Mires hydrological basin in the island of Crete (Greece). After the hydrological year 2002-2003 there is a significant groundwater level increase during the wet period of 2003-2004 and a considerable drop during the dry period of 2005-2006. Both periods are associated with significant annual changes in the precipitation compared to the basin average, i.e., a 40% increase and 65% decrease, respectively. We use STRK to 'predict' the groundwater level for the two selected hydrological periods (wet period of 2003-2004 and dry period of 2005-2006) at each sampling station. The predictions are validated using the respective measured values. The novel Spartan spatiotemporal covariance function gives a mean absolute relative prediction error of 12%. This is 45% lower than the respective value obtained with the commonly used product-sum covariance function, and 31% lower than the respective value obtained with a non-separable function based on the diffusion equation (Kolovos et al. 2010). The advantage of the Spartan space-time covariance model is confirmed with statistical measures such as the root mean square standardized error (RMSSE), the modified coefficient of model efficiency, E' (Legates and McCabe, 1999) and the modified Index of Agreement, IoA'(Janssen and Heuberger, 1995). Hristopulos, D. T. and Elogne, S. N. 2007. Analytic properties and covariance functions for a new class of generalized Gibbs random fields. IEEE Transactions on Information Theory, 53, 4667-4467. Janssen, P.H.M. and Heuberger P.S.C. 1995. Calibration of process-oriented models. Ecological Modelling, 83, 55-66. Kolovos, A., Christakos, G., Hristopulos, D. T. and Serre, M. L. 2004. Methods for generating non-separable spatiotemporal covariance models with potential environmental applications. Advances in Water Resources, 27 (8), 815-830. Legates, D.R. and McCabe Jr., G.J. 1999. Evaluating the use of 'goodness-of-fit' measures in hydrologic and hydro climatic model validation. Water Resources Research, 35, 233-241. Varouchakis, E. A. and Hristopulos, D. T. 2013. Improvement of groundwater level prediction in sparsely gauged basins using physical laws and local geographic features as auxiliary variables. Advances in Water Resources, 52, 34-49.

Pushing Memory Bandwidth Limitations Through Efficient Implementations of Block-Krylov Space Solvers on GPUs

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

Clark, M. A.; Strelchenko, Alexei; Vaquero, Alejandro

Lattice quantum chromodynamics simulations in nuclear physics have benefited from a tremendous number of algorithmic advances such as multigrid and eigenvector deflation. These improve the time to solution but do not alleviate the intrinsic memory-bandwidth constraints of the matrix-vector operation dominating iterative solvers. Batching this operation for multiple vectors and exploiting cache and register blocking can yield a super-linear speed up. Block-Krylov solvers can naturally take advantage of such batched matrix-vector operations, further reducing the iterations to solution by sharing the Krylov space between solves. However, practical implementations typically suffer from the quadratic scaling in the number of vector-vector operations.more » Using the QUDA library, we present an implementation of a block-CG solver on NVIDIA GPUs which reduces the memory-bandwidth complexity of vector-vector operations from quadratic to linear. We present results for the HISQ discretization, showing a 5x speedup compared to highly-optimized independent Krylov solves on NVIDIA's SaturnV cluster.« less

Detecting Spatial Patterns of Natural Hazards from the Wikipedia Knowledge Base

NASA Astrophysics Data System (ADS)

Fan, J.; Stewart, K.

2015-07-01

The Wikipedia database is a data source of immense richness and variety. Included in this database are thousands of geotagged articles, including, for example, almost real-time updates on current and historic natural hazards. This includes usercontributed information about the location of natural hazards, the extent of the disasters, and many details relating to response, impact, and recovery. In this research, a computational framework is proposed to detect spatial patterns of natural hazards from the Wikipedia database by combining topic modeling methods with spatial analysis techniques. The computation is performed on the Neon Cluster, a high performance-computing cluster at the University of Iowa. This work uses wildfires as the exemplar hazard, but this framework is easily generalizable to other types of hazards, such as hurricanes or flooding. Latent Dirichlet Allocation (LDA) modeling is first employed to train the entire English Wikipedia dump, transforming the database dump into a 500-dimension topic model. Over 230,000 geo-tagged articles are then extracted from the Wikipedia database, spatially covering the contiguous United States. The geo-tagged articles are converted into an LDA topic space based on the topic model, with each article being represented as a weighted multidimension topic vector. By treating each article's topic vector as an observed point in geographic space, a probability surface is calculated for each of the topics. In this work, Wikipedia articles about wildfires are extracted from the Wikipedia database, forming a wildfire corpus and creating a basis for the topic vector analysis. The spatial distribution of wildfire outbreaks in the US is estimated by calculating the weighted sum of the topic probability surfaces using a map algebra approach, and mapped using GIS. To provide an evaluation of the approach, the estimation is compared to wildfire hazard potential maps created by the USDA Forest service.

The Determination of Forces and Moments on a Gimballed SRM Nozzle Using a Cold Flow Model

NASA Technical Reports Server (NTRS)

Whitesides, R. Harold; Bacchus, David L.; Hengel, John E.

1994-01-01

The Solid Rocket Motor Air Flow Facility (SAF) at NASA Marshall Space Flight Center was used to characterize the flow in the critical aft end and nozzle of a solid propellant rocket motor (SRM) as part of the design phase of development. The SAF is a high pressure, blowdown facility which supplies a controlled flow of air to a subscale model of the internal port and nozzle of a SRM to enable measurement and evaluation of the flow field and surface pressure distributions. The ASRM Aft Section/Nozzle Model is an 8 percent scale model of the 19 second burn time aft port geometry and nozzle of the Advanced Solid Rocket Motor, the now canceled new generation space Shuttle Booster. It has the capability to simulate fixed nozzle gimbal angles of 0, 4, and 8 degrees. The model was tested at full scale motor Reynolds Numbers with extensive surface pressure instrumentation to enable detailed mapping of the surface pressure distributions over the nozzle interior surface, the exterior surface of the nozzle nose and the surface of the simulated propellant grain in the aft motor port. A mathematical analysis and associated numerical procedure were developed to integrate the measured surface pressure distributions to determine the lateral and axial forces on the moveable section of the nozzle, the effective model thrust and the effective aerodynamic thrust vector (as opposed to the geometric nozzle gimbal angle). The nozzle lateral and axial aerodynamic loads and moments about the pivot point are required for design purposes and require complex, three dimensional flow analyses. The alignment of the thrust vector with the nozzle geometric centerline is also a design requirement requiring three dimensional analyses which were supported by this experimental program. The model was tested with all three gimbal angles at three pressure levels to determine Reynolds number effects and reproducibility. This program was successful in demonstrating that a measured surface pressure distribution could be integrated to determine the lateral and axial loads, moments and thrust vector alignment for the scaled model of a large space booster nozzle. Numerical results were provided which are scaleable to the full scale rocket motor and can be used as benchmark data for 3-D CFD analyses.

Observation of Polarization Vortices in Momentum Space

NASA Astrophysics Data System (ADS)

Zhang, Yiwen; Chen, Ang; Liu, Wenzhe; Hsu, Chia Wei; Wang, Bo; Guan, Fang; Liu, Xiaohan; Shi, Lei; Lu, Ling; Zi, Jian

2018-05-01

The vortex, a fundamental topological excitation featuring the in-plane winding of a vector field, is important in various areas such as fluid dynamics, liquid crystals, and superconductors. Although commonly existing in nature, vortices were observed exclusively in real space. Here, we experimentally observed momentum-space vortices as the winding of far-field polarization vectors in the first Brillouin zone of periodic plasmonic structures. Using homemade polarization-resolved momentum-space imaging spectroscopy, we mapped out the dispersion, lifetime, and polarization of all radiative states at the visible wavelengths. The momentum-space vortices were experimentally identified by their winding patterns in the polarization-resolved isofrequency contours and their diverging radiative quality factors. Such polarization vortices can exist robustly on any periodic systems of vectorial fields, while they are not captured by the existing topological band theory developed for scalar fields. Our work provides a new way for designing high-Q plasmonic resonances, generating vector beams, and studying topological photonics in the momentum space.

Observation of Polarization Vortices in Momentum Space.

PubMed

Zhang, Yiwen; Chen, Ang; Liu, Wenzhe; Hsu, Chia Wei; Wang, Bo; Guan, Fang; Liu, Xiaohan; Shi, Lei; Lu, Ling; Zi, Jian

2018-05-04

The vortex, a fundamental topological excitation featuring the in-plane winding of a vector field, is important in various areas such as fluid dynamics, liquid crystals, and superconductors. Although commonly existing in nature, vortices were observed exclusively in real space. Here, we experimentally observed momentum-space vortices as the winding of far-field polarization vectors in the first Brillouin zone of periodic plasmonic structures. Using homemade polarization-resolved momentum-space imaging spectroscopy, we mapped out the dispersion, lifetime, and polarization of all radiative states at the visible wavelengths. The momentum-space vortices were experimentally identified by their winding patterns in the polarization-resolved isofrequency contours and their diverging radiative quality factors. Such polarization vortices can exist robustly on any periodic systems of vectorial fields, while they are not captured by the existing topological band theory developed for scalar fields. Our work provides a new way for designing high-Q plasmonic resonances, generating vector beams, and studying topological photonics in the momentum space.

Data-driven probability concentration and sampling on manifold

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

2016-09-15

A new methodology is proposed for generating realizations of a random vector with values in a finite-dimensional Euclidean space that are statistically consistent with a dataset of observations of this vector. The probability distribution of this random vector, while a priori not known, is presumed to be concentrated on an unknown subset of the Euclidean space. A random matrix is introduced whose columns are independent copies of the random vector and for which the number of columns is the number of data points in the dataset. The approach is based on the use of (i) the multidimensional kernel-density estimation methodmore » for estimating the probability distribution of the random matrix, (ii) a MCMC method for generating realizations for the random matrix, (iii) the diffusion-maps approach for discovering and characterizing the geometry and the structure of the dataset, and (iv) a reduced-order representation of the random matrix, which is constructed using the diffusion-maps vectors associated with the first eigenvalues of the transition matrix relative to the given dataset. The convergence aspects of the proposed methodology are analyzed and a numerical validation is explored through three applications of increasing complexity. The proposed method is found to be robust to noise levels and data complexity as well as to the intrinsic dimension of data and the size of experimental datasets. Both the methodology and the underlying mathematical framework presented in this paper contribute new capabilities and perspectives at the interface of uncertainty quantification, statistical data analysis, stochastic modeling and associated statistical inverse problems.« less

Derivative-Free Estimation of the Score Vector and Observed Information Matrix with Application to State-Space Models

DTIC Science & Technology

2015-07-14

2008). Sequential Monte Carlo smoothing with applica- tion to parameter estimation in non-linear state space models. Bernoulli , 14, 155-179. [22] Parikh...1BcΣ(θ?,δ)(Θ) ] = o ( τk ) for all k ∈ N. (45) The other integral is over the ball BΣ(θ?, δ), i.e. close to θ?; hence we perform a Taylor expansion of...1] R3 (θ, θ?) = ∑ |α|=4 ∂αϕ (θ? + cθ (θ − θ?)) (θ − θ?)α α! . 26 We now use the symmetry of the normal distribution N ( θ?, τ2Σ ) on the ball BΣ(θ

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.

The multiscale coarse-graining method. II. Numerical implementation for coarse-grained molecular models

PubMed Central

Noid, W. G.; Liu, Pu; Wang, Yanting; Chu, Jhih-Wei; Ayton, Gary S.; Izvekov, Sergei; Andersen, Hans C.; Voth, Gregory A.

2008-01-01

The multiscale coarse-graining (MS-CG) method [S. Izvekov and G. A. Voth, J. Phys. Chem. B 109, 2469 (2005);J. Chem. Phys. 123, 134105 (2005)] employs a variational principle to determine an interaction potential for a CG model from simulations of an atomically detailed model of the same system. The companion paper proved that, if no restrictions regarding the form of the CG interaction potential are introduced and if the equilibrium distribution of the atomistic model has been adequately sampled, then the MS-CG variational principle determines the exact many-body potential of mean force (PMF) governing the equilibrium distribution of CG sites generated by the atomistic model. In practice, though, CG force fields are not completely flexible, but only include particular types of interactions between CG sites, e.g., nonbonded forces between pairs of sites. If the CG force field depends linearly on the force field parameters, then the vector valued functions that relate the CG forces to these parameters determine a set of basis vectors that span a vector subspace of CG force fields. The companion paper introduced a distance metric for the vector space of CG force fields and proved that the MS-CG variational principle determines the CG force force field that is within that vector subspace and that is closest to the force field determined by the many-body PMF. The present paper applies the MS-CG variational principle for parametrizing molecular CG force fields and derives a linear least squares problem for the parameter set determining the optimal approximation to this many-body PMF. Linear systems of equations for these CG force field parameters are derived and analyzed in terms of equilibrium structural correlation functions. Numerical calculations for a one-site CG model of methanol and a molecular CG model of the EMIM+∕NO3− ionic liquid are provided to illustrate the method. PMID:18601325

LVQ and backpropagation neural networks applied to NASA SSME data

NASA Technical Reports Server (NTRS)

Doniere, Timothy F.; Dhawan, Atam P.

1993-01-01

Feedfoward neural networks with backpropagation learning have been used as function approximators for modeling the space shuttle main engine (SSME) sensor signals. The modeling of these sensor signals is aimed at the development of a sensor fault detection system that can be used during ground test firings. The generalization capability of a neural network based function approximator depends on the training vectors which in this application may be derived from a number of SSME ground test-firings. This yields a large number of training vectors. Large training sets can cause the time required to train the network to be very large. Also, the network may not be able to generalize for large training sets. To reduce the size of the training sets, the SSME test-firing data is reduced using the learning vector quantization (LVQ) based technique. Different compression ratios were used to obtain compressed data in training the neural network model. The performance of the neural model trained using reduced sets of training patterns is presented and compared with the performance of the model trained using complete data. The LVQ can also be used as a function approximator. The performance of the LVQ as a function approximator using reduced training sets is presented and compared with the performance of the backpropagation network.

3-D minimum-structure inversion of magnetotelluric data using the finite-element method and tetrahedral grids

NASA Astrophysics Data System (ADS)

Jahandari, H.; Farquharson, C. G.

2017-11-01

Unstructured grids enable representing arbitrary structures more accurately and with fewer cells compared to regular structured grids. These grids also allow more efficient refinements compared to rectilinear meshes. In this study, tetrahedral grids are used for the inversion of magnetotelluric (MT) data, which allows for the direct inclusion of topography in the model, for constraining an inversion using a wireframe-based geological model and for local refinement at the observation stations. A minimum-structure method with an iterative model-space Gauss-Newton algorithm for optimization is used. An iterative solver is employed for solving the normal system of equations at each Gauss-Newton step and the sensitivity matrix-vector products that are required by this solver are calculated using pseudo-forward problems. This method alleviates the need to explicitly form the Hessian or Jacobian matrices which significantly reduces the required computation memory. Forward problems are formulated using an edge-based finite-element approach and a sparse direct solver is used for the solutions. This solver allows saving and re-using the factorization of matrices for similar pseudo-forward problems within a Gauss-Newton iteration which greatly minimizes the computation time. Two examples are presented to show the capability of the algorithm: the first example uses a benchmark model while the second example represents a realistic geological setting with topography and a sulphide deposit. The data that are inverted are the full-tensor impedance and the magnetic transfer function vector. The inversions sufficiently recovered the models and reproduced the data, which shows the effectiveness of unstructured grids for complex and realistic MT inversion scenarios. The first example is also used to demonstrate the computational efficiency of the presented model-space method by comparison with its data-space counterpart.

Intelligent Fault Diagnosis of HVCB with Feature Space Optimization-Based Random Forest

PubMed Central

Ma, Suliang; Wu, Jianwen; Wang, Yuhao; Jia, Bowen; Jiang, Yuan

2018-01-01

Mechanical faults of high-voltage circuit breakers (HVCBs) always happen over long-term operation, so extracting the fault features and identifying the fault type have become a key issue for ensuring the security and reliability of power supply. Based on wavelet packet decomposition technology and random forest algorithm, an effective identification system was developed in this paper. First, compared with the incomplete description of Shannon entropy, the wavelet packet time-frequency energy rate (WTFER) was adopted as the input vector for the classifier model in the feature selection procedure. Then, a random forest classifier was used to diagnose the HVCB fault, assess the importance of the feature variable and optimize the feature space. Finally, the approach was verified based on actual HVCB vibration signals by considering six typical fault classes. The comparative experiment results show that the classification accuracy of the proposed method with the origin feature space reached 93.33% and reached up to 95.56% with optimized input feature vector of classifier. This indicates that feature optimization procedure is successful, and the proposed diagnosis algorithm has higher efficiency and robustness than traditional methods. PMID:29659548

A vector scanning processing technique for pulsed laser velocimetry

NASA Technical Reports Server (NTRS)

Wernet, Mark P.; Edwards, Robert V.

1989-01-01

Pulsed laser sheet velocimetry yields nonintrusive measurements of two-dimensional velocity vectors across an extended planar region of a flow. Current processing techniques offer high precision (1 pct) velocity estimates, but can require several hours of processing time on specialized array processors. Under some circumstances, a simple, fast, less accurate (approx. 5 pct), data reduction technique which also gives unambiguous velocity vector information is acceptable. A direct space domain processing technique was examined. The direct space domain processing technique was found to be far superior to any other techniques known, in achieving the objectives listed above. It employs a new data coding and reduction technique, where the particle time history information is used directly. Further, it has no 180 deg directional ambiguity. A complex convection vortex flow was recorded and completely processed in under 2 minutes on an 80386 based PC, producing a 2-D velocity vector map of the flow field. Hence, using this new space domain vector scanning (VS) technique, pulsed laser velocimetry data can be reduced quickly and reasonably accurately, without specialized array processing hardware.

On the electromagnetic fields, Poynting vector, and peak power radiated by lightning return strokes

NASA Technical Reports Server (NTRS)

Krider, E. P.

1992-01-01

The initial radiation fields, Poynting vector, and total electromagnetic power that a vertical return stroke radiates into the upper half space have been computed when the speed of the stroke, nu, is a significant fraction of the speed of light, c, assuming that at large distances and early times the source is an infinitesimal dipole. The initial current is also assumed to satisfy the transmission-line model with a constant nu and to be perpendicular to an infinite, perfectly conducting ground. The effect of a large nu is to increase the radiation fields by a factor of (1-beta-sq cos-sq theta) exp -1, where beta = nu/c and theta is measured from the vertical, and the Poynting vector by a factor of (1-beta-sq cos-sq theta) exp -2.

750 GeV diphoton excess at CERN LHC from a dark sector assisted scalar decay

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

Bhattacharya, Subhaditya; Patra, Sudhanwa; Sahoo, Nirakar

2016-06-06

We present a simple extension of the Standard Model (SM) to explain the recent diphoton excess, reported by CMS and ATLAS at CERN LHC. The SM is extended by a dark sector including a vector-like lepton doublet and a singlet of zero electromagnetic charge, which are odd under a Z{sub 2} symmetry. The charged particle of the vector-like lepton doublet assist the additional scalar, different from SM Higgs, to decay to di-photons of invariant mass around 750 GeV and thus explaining the excess observed at LHC. The admixture of neutral component of the vector-like lepton doublet and singlet constitute themore » dark matter of the Universe. We show the relevant parameter space for correct relic density and direct detection of dark matter.« less

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.

Search for pair production of vector-like top quarks in events with one lepton, jets, and missing transverse momentum in √{s}=13 TeV pp collisions with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdinov, O.; Abeloos, B.; Abidi, S. H.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adelman, J.; Adersberger, M.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agheorghiesei, C.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akatsuka, S.; Akerstedt, H.; Åkesson, T. P. A.; Akilli, E.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albicocco, P.; Verzini, M. J. Alconada; Alderweireldt, S. C.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M.; Gonzalez, B. Alvarez; Piqueras, D. Álvarez; Alviggi, M. G.; Amadio, B. T.; Coutinho, Y. Amaral; Amelung, C.; Amidei, D.; Santos, S. P. 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S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bolz, A. E.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Boscherini, D.; Bosman, M.; Sola, J. D. Bossio; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Madden, W. D. Breaden; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Briglin, D. L.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; de Renstrom, P. A. Bruckman; Bruncko, D.; Bruni, A.; Bruni, G.; Bruni, L. S.; Brunt, BH; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burch, T. J.; Burdin, S.; Burgard, C. D.; Burger, A. M.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Urbán, S. Cabrera; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Lopez, S. Calvente; Calvet, D.; Calvet, S.; Calvet, T. P.; Toro, R. Camacho; Camarda, S.; Camarri, P.; Cameron, D.; Armadans, R. Caminal; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Bret, M. Cano; Cantero, J.; Cao, T.; Garrido, M. D. M. Capeans; Caprini, I.; Caprini, M.; Capua, M.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carlson, B. T.; Carminati, L.; Carney, R. M. D.; Caron, S.; Carquin, E.; Carrá, S.; Carrillo-Montoya, G. D.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castelijn, R.; Gimenez, V. Castillo; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Celebi, E.; Ceradini, F.; Alberich, L. Cerda; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, W. S.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chau, C. C.; Barajas, C. A. Chavez; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheplakov, A.; Cheremushkina, E.; El Moursli, R. Cherkaoui; Cheu, E.; Cheung, K.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chiu, Y. H.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Christodoulou, V.; Chromek-Burckhart, D.; Chu, M. C.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocca, C.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Muiño, P. Conde; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper-Sarkar, A. M.; Cormier, F.; Cormier, K. J. R.; Corradi, M.; Corriveau, F.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Creager, R. A.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cueto, A.; Donszelmann, T. Cuhadar; Cukierman, A. R.; Cummings, J.; Curatolo, M.; Cúth, J.; Czodrowski, P.; D'amen, G.; D'Auria, S.; D'eramo, L.; D'Onofrio, M.; Da Cunha Sargedas De Sousa, M. J.; Da Via, C.; Dabrowski, W.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Daneri, M. F.; Dang, N. P.; Daniells, A. C.; Dann, N. S.; Danninger, M.; Hoffmann, M. Dano; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Daubney, T.; Davey, W.; David, C.; Davidek, T.; Davis, D. R.; Davison, P.; Dawe, E.; Dawson, I.; De, K.; de Asmundis, R.; De Benedetti, A.; De Castro, S.; De Cecco, S.; De Groot, N.; de Jong, P.; De la Torre, H.; De Lorenzi, F.; De Maria, A.; De Pedis, D.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Vasconcelos Corga, K.; De Vivie De Regie, J. B.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Pietra, M. Della; della Volpe, D.; Delmastro, M.; Delporte, C.; Delsart, P. A.; DeMarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Devesa, M. R.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; Di Bello, F. A.; Di Ciaccio, A.; Di Ciaccio, L.; Di Clemente, W. K.; Di Donato, C.; Di Girolamo, A.; Di Girolamo, B.; Di Micco, B.; Di Nardo, R.; Di Petrillo, K. F.; Di Simone, A.; Di Sipio, R.; Di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Cornell, S. Díez; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; do Vale, M. A. B.; Dobos, D.; Dobre, M.; Doglioni, C.; Dolejsi, J.; Dolezal, Z.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Dubreuil, A.; Duchovni, E.; Duckeck, G.; Ducourthial, A.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudder, A. Chr.; Duffield, E. M.; Duflot, L.; Dührssen, M.; Dumancic, M.; Dumitriu, A. E.; Duncan, A. K.; Dunford, M.; Yildiz, H. Duran; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Dyndal, M.; Dziedzic, B. S.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; El Kosseifi, R.; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Ennis, J. S.; Erdmann, J.; Ereditato, A.; Ernst, M.; Errede, S.; Escalier, M.; Escobar, C.; Esposito, B.; Pastor, O. Estrada; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Ezzi, M.; Fabbri, F.; Fabbri, L.; Fabiani, V.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Giannelli, M. Faucci; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenton, M. J.; Fenyuk, A. B.; Feremenga, L.; Martinez, P. Fernandez; Perez, S. Fernandez; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; de Lima, D. E. Ferreira; Ferrer, A.; Ferrere, D.; Ferretti, C.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. C.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, R. R. M.; Flick, T.; Flierl, B. M.; Castillo, L. R. Flores; Flowerdew, M. 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Safai; Saha, P.; Sahinsoy, M.; Saimpert, M.; Saito, M.; Saito, T.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Loyola, J. E. Salazar; Salek, D.; De Bruin, P. H. Sales; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sammel, D.; Sampsonidis, D.; Sampsonidou, D.; Sánchez, J.; Martinez, V. Sanchez; Pineda, A. Sanchez; Sandaker, H.; Sandbach, R. L.; Sander, C. O.; Sandhoff, M.; Sandoval, C.; Sankey, D. P. C.; Sannino, M.; Sano, Y.; Sansoni, A.; Santoni, C.; Santos, H.; Castillo, I. Santoyo; Sapronov, A.; Saraiva, J. G.; Sarrazin, B.; Sasaki, O.; Sato, K.; Sauvan, E.; Savage, G.; Savard, P.; Savic, N.; Sawyer, C.; Sawyer, L.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Scarcella, M.; Schaarschmidt, J.; Schacht, P.; Schachtner, B. M.; Schaefer, D.; Schaefer, L.; Schaefer, R.; Schaeffer, J.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Schiavi, C.; Schier, S.; Schildgen, L. K.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt-Sommerfeld, K. R.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schott, M.; Schouwenberg, J. F. P.; Schovancova, J.; Schramm, S.; Schuh, N.; Schulte, A.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwarz, T. A.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Sciandra, A.; Sciolla, G.; Scornajenghi, M.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Semprini-Cesari, N.; Senkin, S.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Shen, Y.; Sherafati, N.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shipsey, I. P. J.; Shirabe, S.; Shiyakova, M.; Shlomi, J.; Shmeleva, A.; Saadi, D. Shoaleh; Shochet, M. J.; Shojaii, S.; Shope, D. R.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Haddad, E. Sideras; Sidiropoulou, O.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Siral, I.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smiesko, J.; Smirnov, N.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, J. W.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, I. M.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Søgaard, A.; Soh, D. A.; Sokhrannyi, G.; Sanchez, C. A. Solans; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Sopczak, A.; Sosa, D.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spieker, T. M.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; Denis, R. D. St.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanitzki, M. M.; Stapf, B. S.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Stark, S. H.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultan, DMS; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Suruliz, K.; Suster, C. J. E.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Swift, S. P.; Sykora, I.; Sykora, T.; Ta, D.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takasugi, E. H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanaka, S.; Tanioka, R.; Tannenwald, B. B.; Araya, S. Tapia; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Delgado, A. Tavares; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teixeira-Dias, P.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thiele, F.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Tibbetts, M. J.; Torres, R. E. Ticse; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorova-Nova, S.; Todt, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Tornambe, P.; Torrence, E.; Torres, H.; Pastor, E. Torró; Toth, J.; Touchard, F.; Tovey, D. R.; Treado, C. J.; Trefzger, T.; Tresoldi, F.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tsang, K. W.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tulbure, T. T.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turgeman, D.; Cakir, I. Turk; Turra, R.; Tuts, P. M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usui, J.; Vacavant, L.; Vacek, V.; Vachon, B.; Vadla, K. O. H.; Vaidya, A.; Valderanis, C.; Santurio, E. Valdes; Valentinetti, S.; Valero, A.; Valéry, L.; Valkar, S.; Vallier, A.; Ferrer, J. A. Valls; Van Den Wollenberg, W.; van der Graaf, H.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varni, C.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Schroeder, T. Vazquez; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, A. T.; Vermeulen, J. C.; Vetterli, M. C.; Maira, N. Viaux; Viazlo, O.; Vichou, I.; Vickey, T.; Boeriu, O. E. Vickey; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Perez, M. Villaplana; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vishwakarma, A.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vogel, M.; Vokac, P.; Volpi, G.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Milosavljevic, M. Vranjes; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Wagner, P.; Wagner, W.; Wagner-Kuhr, J.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, Q.; Wang, R.; Wang, S. M.; Wang, T.; Wang, W.; Wang, W.; Wang, Z.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, A. F.; Webb, S.; Weber, M. S.; Weber, S. W.; Weber, S. A.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weirich, M.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M. D.; Werner, P.; Wessels, M.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A. S.; White, A.; White, M. J.; White, R.; Whiteson, D.; Whitmore, B. W.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winkels, E.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wobisch, M.; Wolf, T. M. H.; Wolff, R.; Wolter, M. W.; Wolters, H.; Wong, V. W. S.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Wozniak, K. W.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xi, Z.; Xia, L.; Xu, D.; Xu, L.; Xu, T.; Yabsley, B.; Yacoob, S.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamatani, M.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Wong, K. H. Yau; Ye, J.; Ye, S.; Yeletskikh, I.; Yigitbasi, E.; Yildirim, E.; Yorita, K.; Yoshihara, K.; Young, C.; Young, C. J. S.; Yu, J.; Yu, J.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zacharis, G.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanzi, D.; Zeitnitz, C.; Zemaityte, G.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, L.; Zhang, M.; Zhang, P.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Y.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, M.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zou, R.; zur Nedden, M.; Zwalinski, L.

2017-08-01

The results of a search for vector-like top quarks using events with exactly one lepton, at least four jets, and large missing transverse momentum are reported. The search is optimised for pair production of vector-like top quarks in the Z(→νν) t + X decay channel. LHC pp collision data at a centre-of-mass energy of √{s}=13 TeV recorded by the ATLAS detector in 2015 and 2016 are used, corresponding to an integrated luminosity of 36.1 fb-1. No significant excess over the Standard Model expectation is seen and upper limits on the production cross-section of a vector-like T quark pair as a function of the T quark mass are derived. The observed (expected) 95% CL lower limits on the T mass are 870 GeV (890 GeV) for the weak-isospin singlet model, 1.05 TeV (1.06 TeV) for the weak-isospin doublet model and 1.16 TeV (1.17 TeV) for the pure Zt decay mode. Limits are also set on the mass as a function of the decay branching ratios, excluding large parts of the parameter space for masses below 1 TeV. [Figure not available: see fulltext.

Search for pair production of vector-like top quarks in events with one lepton, jets, and missing transverse momentum in $$ \\sqrt{s}=13 $$ TeV pp collisions with the ATLAS detector

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

Aaboud, M.; Aad, G.; Abbott, B.

The results of a search for vector-like top quarks using events with exactly one lepton, at least four jets, and large missing transverse momentum are reported. The search is optimised for pair production of vector-like top quarks in the Z(→vv) t + X decay channel. LHC pp collision data at a centre-of-mass energy of √s=13 TeV recorded by the ATLAS detector in 2015 and 2016 are used, corresponding to an integrated luminosity of 36.1 fb -1 . No significant excess over the Standard Model expectation is seen and upper limits on the production cross-section of a vector-like T quark pairmore » as a function of the T quark mass are derived. The observed (expected) 95% CL lower limits on the T mass are 870 GeV (890 GeV) for the weak-isospin singlet model, 1.05 TeV (1.06 TeV) for the weak-isospin doublet model and 1.16 TeV (1.17 TeV) for the pure Zt decay mode. Limits are also set on the mass as a function of the decay branching ratios, excluding large parts of the parameter space for masses below 1 TeV.« less

Search for pair production of vector-like top quarks in events with one lepton, jets, and missing transverse momentum in $$ \\sqrt{s}=13 $$ TeV pp collisions with the ATLAS detector

DOE PAGES

Aaboud, M.; Aad, G.; Abbott, B.; ...

2017-08-16

The results of a search for vector-like top quarks using events with exactly one lepton, at least four jets, and large missing transverse momentum are reported. The search is optimised for pair production of vector-like top quarks in the Z(→vv) t + X decay channel. LHC pp collision data at a centre-of-mass energy of √s=13 TeV recorded by the ATLAS detector in 2015 and 2016 are used, corresponding to an integrated luminosity of 36.1 fb -1 . No significant excess over the Standard Model expectation is seen and upper limits on the production cross-section of a vector-like T quark pairmore » as a function of the T quark mass are derived. The observed (expected) 95% CL lower limits on the T mass are 870 GeV (890 GeV) for the weak-isospin singlet model, 1.05 TeV (1.06 TeV) for the weak-isospin doublet model and 1.16 TeV (1.17 TeV) for the pure Zt decay mode. Limits are also set on the mass as a function of the decay branching ratios, excluding large parts of the parameter space for masses below 1 TeV.« less

DNA condensation and size effects of DNA condensation agent

NASA Astrophysics Data System (ADS)

Liu, Yan-Hui; Jiang, Chong-Ming; Guo, Xin-Miao; Tang, Yan-Lin; Hu, Lin

2013-08-01

Based on the model of the strong correlation of counterions condensed on DNA molecule, by tailoring interaction potential, interduplex spacing and correlation spacing between condensed counterions on DNA molecule and interduplex spacing fluctuation strength, toroidal configuration, rod-like configuration and two-hole configurations are possible. The size effects of counterion structure on the toroidal structure can be detected by this model. The autocorrelation function of the tangent vectors is found as an effective way to detect the structure of toroidal conformations and the generic pathway of the process of DNA condensation. The generic pathway of all of the configurations involves an initial nucleation loop, and the next part of the DNA chain is folded on the top of the initial nucleation loop with different manners, in agreement with the recent experimental results.

Performance characteristics of a variable-area vane nozzle for vectoring an ASTOVL exhaust jet up to 45 deg

NASA Technical Reports Server (NTRS)

Mcardle, Jack G.; Esker, Barbara S.

1993-01-01

Many conceptual designs for advanced short-takeoff, vertical landing (ASTOVL) aircraft need exhaust nozzles that can vector the jet to provide forces and moments for controlling the aircraft's movement or attitude in flight near the ground. A type of nozzle that can both vector the jet and vary the jet flow area is called a vane nozzle. Basically, the nozzle consists of parallel, spaced-apart flow passages formed by pairs of vanes (vanesets) that can be rotated on axes perpendicular to the flow. Two important features of this type of nozzle are the abilities to vector the jet rearward up to 45 degrees and to produce less harsh pressure and velocity footprints during vertical landing than does an equivalent single jet. A one-third-scale model of a generic vane nozzle was tested with unheated air at the NASA Lewis Research Center's Powered Lift Facility. The model had three parallel flow passages. Each passage was formed by a vaneset consisting of a long and a short vane. The longer vanes controlled the jet vector angle, and the shorter controlled the flow area. Nozzle performance for three nominal flow areas (basic and plus or minus 21 percent of basic area), each at nominal jet vector angles from -20 deg (forward of vertical) to +45 deg (rearward of vertical) are presented. The tests were made with the nozzle mounted on a model tailpipe with a blind flange on the end to simulate a closed cruise nozzle, at tailpipe-to-ambient pressure ratios from 1.8 to 4.0. Also included are jet wake data, single-vaneset vector performance for long/short and equal-length vane designs, and pumping capability. The pumping capability arises from the subambient pressure developed in the cavities between the vanesets, which could be used to aspirate flow from a source such as the engine compartment. Some of the performance characteristics are compared with characteristics of a single-jet nozzle previously reported.

A general theory of linear cosmological perturbations: stability conditions, the quasistatic limit and dynamics

NASA Astrophysics Data System (ADS)

Lagos, Macarena; Bellini, Emilio; Noller, Johannes; Ferreira, Pedro G.; Baker, Tessa

2018-03-01

We analyse cosmological perturbations around a homogeneous and isotropic background for scalar-tensor, vector-tensor and bimetric theories of gravity. Building on previous results, we propose a unified view of the effective parameters of all these theories. Based on this structure, we explore the viable space of parameters for each family of models by imposing the absence of ghosts and gradient instabilities. We then focus on the quasistatic regime and confirm that all these theories can be approximated by the phenomenological two-parameter model described by an effective Newton's constant and the gravitational slip. Within the quasistatic regime we pinpoint signatures which can distinguish between the broad classes of models (scalar-tensor, vector-tensor or bimetric). Finally, we present the equations of motion for our unified approach in such a way that they can be implemented in Einstein-Boltzmann solvers.

A note on φ-analytic conformal vector fields

NASA Astrophysics Data System (ADS)

Deshmukh, Sharief; Bin Turki, Nasser

2017-09-01

Taking clue from the analytic vector fields on a complex manifold, φ-analytic conformal vector fields are defined on a Riemannian manifold (Deshmukh and Al-Solamy in Colloq. Math. 112(1):157-161, 2008). In this paper, we use φ-analytic conformal vector fields to find new characterizations of the n-sphere Sn(c) and the Euclidean space (Rn,<,> ).

A Feature Mining Based Approach for the Classification of Text Documents into Disjoint Classes.

ERIC Educational Resources Information Center

Nieto Sanchez, Salvador; Triantaphyllou, Evangelos; Kraft, Donald

2002-01-01

Proposes a new approach for classifying text documents into two disjoint classes. Highlights include a brief overview of document clustering; a data mining approach called the One Clause at a Time (OCAT) algorithm which is based on mathematical logic; vector space model (VSM); and comparing the OCAT to the VSM. (Author/LRW)

An Elementary Treatment of General Inner Products

ERIC Educational Resources Information Center

Graver, Jack E.

2011-01-01

A typical first course on linear algebra is usually restricted to vector spaces over the real numbers and the usual positive-definite inner product. Hence, the proof that dim(S)+ dim(S[perpendicular]) = dim("V") is not presented in a way that is generalizable to non-positive?definite inner products or to vector spaces over other fields. In this…

Constraints on muon-specific dark forces

NASA Astrophysics Data System (ADS)

Karshenboim, Savely G.; McKeen, David; Pospelov, Maxim

2014-10-01

The recent measurement of the Lamb shift in muonic hydrogen allows for the most precise extraction of the charge radius of the proton which is currently in conflict with other determinations based on e-p scattering and hydrogen spectroscopy. This discrepancy could be the result of some new muon-specific force with O(1-100) MeV force carrier—in this paper we concentrate on vector mediators. Such an explanation faces challenges from the constraints imposed by the g-2 of the muon and electron as well as precision spectroscopy of muonic atoms. In this work we complement the family of constraints by calculating the contribution of hypothetical forces to the muonium hyperfine structure. We also compute the two-loop contribution to the electron parity-violating amplitude due to a muon loop, which is sensitive to the muon axial-vector coupling. Overall, we find that the combination of low-energy constraints favors the mass of the mediator to be below 10 MeV and that a certain degree of tuning is required between vector and axial-vector couplings of new vector particles to muons in order to satisfy constraints from muon g-2. However, we also observe that in the absence of a consistent standard model embedding high-energy weak-charged processes accompanied by the emission of new vector particles are strongly enhanced by (E/mV)2, with E a characteristic energy scale and mV the mass of the mediator. In particular, leptonic W decays impose the strongest constraints on such models completely disfavoring the remainder of the parameter space.

A weather-driven model of malaria transmission.

PubMed

Hoshen, Moshe B; Morse, Andrew P

2004-09-06

Climate is a major driving force behind malaria transmission and climate data are often used to account for the spatial, seasonal and interannual variation in malaria transmission. This paper describes a mathematical-biological model of the parasite dynamics, comprising both the weather-dependent within-vector stages and the weather-independent within-host stages. Numerical evaluations of the model in both time and space show that it qualitatively reconstructs the prevalence of infection. A process-based modelling structure has been developed that may be suitable for the simulation of malaria forecasts based on seasonal weather forecasts.

Wigner functions on non-standard symplectic vector spaces

NASA Astrophysics Data System (ADS)

Dias, Nuno Costa; Prata, João Nuno

2018-01-01

We consider the Weyl quantization on a flat non-standard symplectic vector space. We focus mainly on the properties of the Wigner functions defined therein. In particular we show that the sets of Wigner functions on distinct symplectic spaces are different but have non-empty intersections. This extends previous results to arbitrary dimension and arbitrary (constant) symplectic structure. As a by-product we introduce and prove several concepts and results on non-standard symplectic spaces which generalize those on the standard symplectic space, namely, the symplectic spectrum, Williamson's theorem, and Narcowich-Wigner spectra. We also show how Wigner functions on non-standard symplectic spaces behave under the action of an arbitrary linear coordinate transformation.

Assessing Space Weather Applications and Understanding: IMF Bz at L1

NASA Astrophysics Data System (ADS)

Riley, P.; Savani, N.; Mays, M. L.; Austin, H. J.

2017-12-01

The CCMC - International (CCMC-I) is designed as a self-organizing informal forum for facilitating novel global initiatives on space weather research, development, forecasting and education. Here we capitalize on CCMC'AGUs experience in providing highly utilized web-based services, leadership and trusted relationships with space weather model developers. One of the CCMC-I initiatives is the International Forum for Space Weather Capabilities Assessment. As part of this initiative, within the solar and heliosphere domain, we focus our community discussion on forecasting the magnetic structure of interplanetary CMEs and the ambient solar wind. During the International CCMC-LWS Working Meeting in April 2017 the group instigated open communication to agree upon a standardized process by which all current and future models can be compared under an unbiased test. In this poster, we present our initial findings how we expect different models will move forward with validating and forecasting the magnetic vectors of the solar wind at L1. We also present a new IMF Bz Score-board which will be used to assist in the transitioning of research models into more operational settings.

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.

Chagas disease vector control and Taylor's law

PubMed Central

Rodríguez-Planes, Lucía I.; Gaspe, María S.; Cecere, María C.; Cardinal, Marta V.

2017-01-01

Background Large spatial and temporal fluctuations in the population density of living organisms have profound consequences for biodiversity conservation, food production, pest control and disease control, especially vector-borne disease control. Chagas disease vector control based on insecticide spraying could benefit from improved concepts and methods to deal with spatial variations in vector population density. Methodology/Principal findings We show that Taylor's law (TL) of fluctuation scaling describes accurately the mean and variance over space of relative abundance, by habitat, of four insect vectors of Chagas disease (Triatoma infestans, Triatoma guasayana, Triatoma garciabesi and Triatoma sordida) in 33,908 searches of people's dwellings and associated habitats in 79 field surveys in four districts in the Argentine Chaco region, before and after insecticide spraying. As TL predicts, the logarithm of the sample variance of bug relative abundance closely approximates a linear function of the logarithm of the sample mean of abundance in different habitats. Slopes of TL indicate spatial aggregation or variation in habitat suitability. Predictions of new mathematical models of the effect of vector control measures on TL agree overall with field data before and after community-wide spraying of insecticide. Conclusions/Significance A spatial Taylor's law identifies key habitats with high average infestation and spatially highly variable infestation, providing a new instrument for the control and elimination of the vectors of a major human disease. PMID:29190728

Effective Numerical Methods for Solving Elliptical Problems in Strengthened Sobolev Spaces

NASA Technical Reports Server (NTRS)

D'yakonov, Eugene G.

1996-01-01

Fourth-order elliptic boundary value problems in the plane can be reduced to operator equations in Hilbert spaces G that are certain subspaces of the Sobolev space W(sub 2)(exp 2)(Omega) is identical with G(sup (2)). Appearance of asymptotically optimal algorithms for Stokes type problems made it natural to focus on an approach that considers rot w is identical with (D(sub 2)w - D(sub 1)w) is identical with vector of u as a new unknown vector-function, which automatically satisfies the condition div vector of u = 0. In this work, we show that this approach can also be developed for an important class of problems from the theory of plates and shells with stiffeners. The main mathematical problem was to show that the well-known inf-sup condition (normal solvability of the divergence operator) holds for special Hilbert spaces. This result is also essential for certain hydrodynamics problems.

Thrust vector control using electric actuation

NASA Astrophysics Data System (ADS)

Bechtel, Robert T.; Hall, David K.

1995-01-01

Presently, gimbaling of launch vehicle engines for thrust vector control is generally accomplished using a hydraulic system. In the case of the space shuttle solid rocket boosters and main engines, these systems are powered by hydrazine auxiliary power units. Use of electromechanical actuators would provide significant advantages in cost and maintenance. However, present energy source technologies such as batteries are heavy to the point of causing significant weight penalties. Utilizing capacitor technology developed by the Auburn University Space Power Institute in collaboration with the Auburn CCDS, Marshall Space Flight Center (MSFC) and Auburn are developing EMA system components with emphasis on high discharge rate energy sources compatible with space shuttle type thrust vector control requirements. Testing has been done at MSFC as part of EMA system tests with loads up to 66000 newtons for pulse times of several seconds. Results show such an approach to be feasible providing a potential for reduced weight and operations costs for new launch vehicles.

Dynamic analysis of suspension cable based on vector form intrinsic finite element method

NASA Astrophysics Data System (ADS)

Qin, Jian; Qiao, Liang; Wan, Jiancheng; Jiang, Ming; Xia, Yongjun

2017-10-01

A vector finite element method is presented for the dynamic analysis of cable structures based on the vector form intrinsic finite element (VFIFE) and mechanical properties of suspension cable. Firstly, the suspension cable is discretized into different elements by space points, the mass and external forces of suspension cable are transformed into space points. The structural form of cable is described by the space points at different time. The equations of motion for the space points are established according to the Newton’s second law. Then, the element internal forces between the space points are derived from the flexible truss structure. Finally, the motion equations of space points are solved by the central difference method with reasonable time integration step. The tangential tension of the bearing rope in a test ropeway with the moving concentrated loads is calculated and compared with the experimental data. The results show that the tangential tension of suspension cable with moving loads is consistent with the experimental data. This method has high calculated precision and meets the requirements of engineering application.

Search for low mass vector resonances decaying into quark-antiquark pairs in proton-proton collisions at $$ \\sqrt{s}=13 $$ TeV

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

Sirunyan, A. M.; Tumasyan, A.; Adam, W.

Here, a search for narrow vector resonances decaying into quark-antiquark pairs is presented. The analysis is based on data collected in proton-proton collisions atmore » $$\\sqrt{s} = $$ 13 TeV with the CMS detector at the LHC, corresponding to an integrated luminosity of 35.9 fb$$^{-1}$$. The hypothetical resonance is produced with sufficiently high transverse momentum that its decay products are merged into a single jet with two-prong substructure. A signal would be identified as a peak over a smoothly falling background in the distribution of the invariant mass of the jet, using novel jet substructure techniques. No evidence for such a resonance is observed within the mass range of 50-300 GeV. Upper limits at 95% confidence level are set on the production cross section, and presented in a mass-coupling parameter space. The limits further constrain simplified models of dark matter production involving a mediator interacting between quarks and dark matter particles through a vector or axial-vector current. In the framework of these models, the results are the most sensitive to date, extending for the first time the search region to masses below 100 GeV.« less

Search for low mass vector resonances decaying into quark-antiquark pairs in proton-proton collisions at √{s}=13 TeV

NASA Astrophysics Data System (ADS)

Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Ambrogi, F.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Grossmann, J.; Hrubec, J.; Jeitler, M.; König, A.; Krammer, N.; Krätschmer, I.; Liko, D.; Madlener, T.; Mikulec, I.; Pree, E.; Rad, N.; Rohringer, H.; Schieck, J.; Schöfbeck, R.; Spanring, M.; Spitzbart, D.; Waltenberger, W.; Wittmann, J.; Wulz, C.-E.; Zarucki, M.; Chekhovsky, V.; Mossolov, V.; Suarez Gonzalez, J.; De Wolf, E. 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H.; Leggat, D.; Liao, H.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Yazgan, E.; Zhang, H.; Zhang, S.; Zhao, J.; Ban, Y.; Chen, G.; Li, J.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Avila, C.; Cabrera, A.; Chaparro Sierra, L. F.; Florez, C.; González Hernández, C. F.; Ruiz Alvarez, J. D.; Segura Delgado, M. A.; Courbon, B.; Godinovic, N.; Lelas, D.; Puljak, I.; Ribeiro Cipriano, P. M.; Sculac, T.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Mesic, B.; Starodumov, A.; Susa, T.; Ather, M. W.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Finger, M.; Finger, M.; Carrera Jarrin, E.; El-khateeb, E.; Elgammal, S.; Ellithi Kamel, A.; Dewanjee, R. K.; Kadastik, M.; Perrini, L.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Kirschenmann, H.; Pekkanen, J.; Voutilainen, M.; Havukainen, J.; Heikkilä, J. K.; Järvinen, T.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Laurila, S.; Lehti, S.; Lindén, T.; Luukka, P.; Siikonen, H.; Tuominen, E.; Tuominiemi, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Faure, J. L.; Ferri, F.; Ganjour, S.; Ghosh, S.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Kucher, I.; Leloup, C.; Locci, E.; Machet, M.; Malcles, J.; Negro, G.; Rander, J.; Rosowsky, A.; Sahin, M. Ö.; Titov, M.; Abdulsalam, A.; Amendola, C.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Charlot, C.; Granier de Cassagnac, R.; Jo, M.; Lisniak, S.; Lobanov, A.; Martin Blanco, J.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Stahl Leiton, A. G.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Zghiche, A.; Agram, J.-L.; Andrea, J.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Jansová, M.; Le Bihan, A.-C.; Tonon, N.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Fay, J.; Finco, L.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Popov, A.; Sordini, V.; Vander Donckt, M.; Viret, S.; Toriashvili, T.; Tsamalaidze, Z.; Autermann, C.; Feld, L.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Preuten, M.; Schomakers, C.; Schulz, J.; Zhukov, V.; Albert, A.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hamer, M.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Teyssier, D.; Thüer, S.; Flügge, G.; Kargoll, B.; Kress, T.; Künsken, A.; Müller, T.; Nehrkorn, A.; Nowack, A.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Arndt, T.; Asawatangtrakuldee, C.; Beernaert, K.; Behnke, O.; Behrens, U.; Bermúdez Martínez, A.; Bin Anuar, A. A.; Borras, K.; Botta, V.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Diez Pardos, C.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Eren, E.; Gallo, E.; Garay Garcia, J.; Geiser, A.; Grados Luyando, J. M.; Grohsjean, A.; Gunnellini, P.; Guthoff, M.; Harb, A.; Hauk, J.; Hempel, M.; Jung, H.; Kasemann, M.; Keaveney, J.; Kleinwort, C.; Korol, I.; Krücker, D.; Lange, W.; Lelek, A.; Lenz, T.; Leonard, J.; Lipka, K.; Lohmann, W.; Mankel, R.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Ntomari, E.; Pitzl, D.; Raspereza, A.; Savitskyi, M.; Saxena, P.; Shevchenko, R.; Spannagel, S.; Stefaniuk, N.; Van Onsem, G. P.; Walsh, R.; Wen, Y.; Wichmann, K.; Wissing, C.; Zenaiev, O.; Aggleton, R.; Bein, S.; Blobel, V.; Centis Vignali, M.; Dreyer, T.; Garutti, E.; Gonzalez, D.; Haller, J.; Hinzmann, A.; Hoffmann, M.; Karavdina, A.; Klanner, R.; Kogler, R.; Kovalchuk, N.; Kurz, S.; Lapsien, T.; Marconi, D.; Meyer, M.; Niedziela, M.; Nowatschin, D.; Pantaleo, F.; Peiffer, T.; Perieanu, A.; Scharf, C.; Schleper, P.; Schmidt, A.; Schumann, S.; Schwandt, J.; Sonneveld, J.; Stadie, H.; Steinbrück, G.; Stober, F. M.; Stöver, M.; Tholen, H.; Troendle, D.; Usai, E.; Vanhoefer, A.; Vormwald, B.; Akbiyik, M.; Barth, C.; Baselga, M.; Baur, S.; Butz, E.; Caspart, R.; Chwalek, T.; Colombo, F.; De Boer, W.; Dierlamm, A.; Faltermann, N.; Freund, B.; Friese, R.; Giffels, M.; Harrendorf, M. A.; Hartmann, F.; Heindl, S. M.; Husemann, U.; Kassel, F.; Kudella, S.; Mildner, H.; Mozer, M. U.; Müller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; Schröder, M.; Shvetsov, I.; Sieber, G.; Simonis, H. J.; Ulrich, R.; Wayand, S.; Weber, M.; Weiler, T.; Williamson, S.; Wöhrmann, C.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Kyriakis, A.; Loukas, D.; Topsis-Giotis, I.; Karathanasis, G.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Kousouris, K.; Evangelou, I.; Foudas, C.; Gianneios, P.; Katsoulis, P.; Kokkas, P.; Mallios, S.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Strologas, J.; Triantis, F. A.; Tsitsonis, D.; Csanad, M.; Filipovic, N.; Pasztor, G.; Surányi, O.; Veres, G. I.; Bencze, G.; Hajdu, C.; Horvath, D.; Hunyadi, Á.; Sikler, F.; Veszpremi, V.; Beni, N.; Czellar, S.; Karancsi, J.; Makovec, A.; Molnar, J.; Szillasi, Z.; Bartók, M.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Choudhury, S.; Komaragiri, J. R.; Bahinipati, S.; Bhowmik, S.; Mal, P.; Mandal, K.; Nayak, A.; Sahoo, D. K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Chawla, R.; Dhingra, N.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kaur, S.; Kumar, R.; Kumari, P.; Mehta, A.; Singh, J. B.; Walia, G.; Kumar, Ashok; Shah, Aashaq; Bhardwaj, A.; Chauhan, S.; Choudhary, B. C.; Garg, R. B.; Keshri, S.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, R.; Bhardwaj, R.; Bhattacharya, R.; Bhattacharya, S.; Bhawandeep, U.; Dey, S.; Dutt, S.; Dutta, S.; Ghosh, S.; Majumdar, N.; Modak, A.; Mondal, K.; Mukhopadhyay, S.; Nandan, S.; Purohit, A.; Roy, A.; Roy Chowdhury, S.; Sarkar, S.; Sharan, M.; Thakur, S.; Behera, P. K.; Chudasama, R.; Dutta, D.; Jha, V.; Kumar, V.; Mohanty, A. K.; Netrakanti, P. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Dugad, S.; Mahakud, B.; Mitra, S.; Mohanty, G. B.; Sur, N.; Sutar, B.; Banerjee, S.; Bhattacharya, S.; Chatterjee, S.; Das, P.; Guchait, M.; Jain, Sa.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Sarkar, T.; Wickramage, N.; Chauhan, S.; Dube, S.; Hegde, V.; Kapoor, A.; Kothekar, K.; Pandey, S.; Rane, A.; Sharma, S.; Chenarani, S.; Eskandari Tadavani, E.; Etesami, S. M.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Errico, F.; Fiore, L.; Iaselli, G.; Lezki, S.; Maggi, G.; Maggi, M.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Sharma, A.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Battilana, C.; Bonacorsi, D.; Borgonovi, L.; Braibant-Giacomelli, S.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Chhibra, S. S.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Albergo, S.; Costa, S.; Di Mattia, A.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Chatterjee, K.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Lenzi, P.; Meschini, M.; Paoletti, S.; Russo, L.; Sguazzoni, G.; Strom, D.; Viliani, L.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Primavera, F.; Calvelli, V.; Ferro, F.; Robutti, E.; Tosi, S.; Benaglia, A.; Beschi, A.; Brianza, L.; Brivio, F.; Ciriolo, V.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Ghezzi, A.; Govoni, P.; Malberti, M.; Malvezzi, S.; Manzoni, R. A.; Menasce, D.; Moroni, L.; Paganoni, M.; Pauwels, K.; Pedrini, D.; Pigazzini, S.; Ragazzi, S.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; Di Guida, S.; Fabozzi, F.; Fienga, F.; Iorio, A. O. M.; Khan, W. A.; Lista, L.; Meola, S.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Benato, L.; Bisello, D.; Boletti, A.; Carvalho Antunes De Oliveira, A.; Checchia, P.; Dall'Osso, M.; De Castro Manzano, P.; Dorigo, T.; Dosselli, U.; Gasparini, F.; Gozzelino, A.; Lacaprara, S.; Lujan, P.; Margoni, M.; Meneguzzo, A. T.; Pantano, D.; Pozzobon, N.; Ronchese, P.; Rossin, R.; Torassa, E.; Ventura, S.; Zanetti, M.; Zotto, P.; Zumerle, G.; Braghieri, A.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Ressegotti, M.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; Biasini, M.; Bilei, G. M.; Cecchi, C.; Ciangottini, D.; Fanò, L.; Leonardi, R.; Manoni, E.; Mantovani, G.; Mariani, V.; Menichelli, M.; Rossi, A.; Santocchia, A.; Spiga, D.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Boccali, T.; Borrello, L.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Fedi, G.; Giannini, L.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Manca, E.; Mandorli, G.; Messineo, A.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Spagnolo, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Barone, L.; Cavallari, F.; Cipriani, M.; Daci, N.; Del Re, D.; Di Marco, E.; Diemoz, M.; Gelli, S.; Longo, E.; Margaroli, F.; Marzocchi, B.; Meridiani, P.; Organtini, G.; Paramatti, R.; Preiato, F.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bartosik, N.; Bellan, R.; Biino, C.; Cartiglia, N.; Cenna, F.; Costa, M.; Covarelli, R.; Degano, A.; Demaria, N.; Kiani, B.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Monteil, E.; Monteno, M.; Obertino, M. M.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Ravera, F.; Romero, A.; Ruspa, M.; Sacchi, R.; Shchelina, K.; Sola, V.; Solano, A.; Staiano, A.; Traczyk, P.; Belforte, S.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; Zanetti, A.; Kim, D. H.; Kim, G. N.; Kim, M. 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2018-01-01

A search for narrow vector resonances decaying into quark-antiquark pairs is presented. The analysis is based on data collected in proton-proton collisions at √{s}=13 TeV with the CMS detector at the LHC, corresponding to an integrated luminosity of 35.9 fb-1. The hypothetical resonance is produced with sufficiently high transverse momentum that its decay products are merged into a single jet with two-prong substructure. A signal would be identified as a peak over a smoothly falling background in the distribution of the invariant mass of the jet, using novel jet substructure techniques. No evidence for such a resonance is observed within the mass range of 50-300 GeV. Upper limits at 95% confidence level are set on the production cross section, and presented in a mass-coupling parameter space. The limits further constrain simplified models of dark matter production involving a mediator interacting between quarks and dark matter particles through a vector or axial-vector current. In the framework of these models, the results are the most sensitive to date, extending for the first time the search region to masses below 100 GeV. [Figure not available: see fulltext.

Search for low mass vector resonances decaying into quark-antiquark pairs in proton-proton collisions at $$ \\sqrt{s}=13 $$ TeV

DOE PAGES

Sirunyan, A. M.; Tumasyan, A.; Adam, W.; ...

2018-01-22

Here, a search for narrow vector resonances decaying into quark-antiquark pairs is presented. The analysis is based on data collected in proton-proton collisions atmore » $$\\sqrt{s} = $$ 13 TeV with the CMS detector at the LHC, corresponding to an integrated luminosity of 35.9 fb$$^{-1}$$. The hypothetical resonance is produced with sufficiently high transverse momentum that its decay products are merged into a single jet with two-prong substructure. A signal would be identified as a peak over a smoothly falling background in the distribution of the invariant mass of the jet, using novel jet substructure techniques. No evidence for such a resonance is observed within the mass range of 50-300 GeV. Upper limits at 95% confidence level are set on the production cross section, and presented in a mass-coupling parameter space. The limits further constrain simplified models of dark matter production involving a mediator interacting between quarks and dark matter particles through a vector or axial-vector current. In the framework of these models, the results are the most sensitive to date, extending for the first time the search region to masses below 100 GeV.« less

Calibration of Predictor Models Using Multiple Validation Experiments

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2015-01-01

This paper presents a framework for calibrating computational models using data from several and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncertainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models' ability to reproduce the distribution of observations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it casts the model's ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain.

Vector magnetic fields in sunspots. I - Stokes profile analysis using the Marshall Space Flight Center magnetograph

NASA Technical Reports Server (NTRS)

Balasubramaniam, K. S.; West, E. A.

1991-01-01

The Marshall Space Flight Center (MSFC) vector magnetograph is a tunable filter magnetograph with a bandpass of 125 mA. Results are presented of the inversion of Stokes polarization profiles observed with the MSFC vector magnetograph centered on a sunspot to recover the vector magnetic field parameters and thermodynamic parameters of the spectral line forming region using the Fe I 5250.2 A spectral line using a nonlinear least-squares fitting technique. As a preliminary investigation, it is also shown that the recovered thermodynamic parameters could be better understood if the fitted parameters like Doppler width, opacity ratio, and damping constant were broken down into more basic quantities like temperature, microturbulent velocity, or density parameter.

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

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

Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moietymore » with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. Finally, we also give examples of new applications made possible by elucidating the atomic structure of conserved moieties.« less

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

PubMed Central

Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.

2016-01-01

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moiety with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. We also give examples of new applications made possible by elucidating the atomic structure of conserved moieties. PMID:27870845

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

DOE PAGES

Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.

2016-11-21

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moietymore » with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. Finally, we also give examples of new applications made possible by elucidating the atomic structure of conserved moieties.« less

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks.

PubMed

Haraldsdóttir, Hulda S; Fleming, Ronan M T

2016-11-01

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moiety with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. We also give examples of new applications made possible by elucidating the atomic structure of conserved moieties.

Adjudicating between face-coding models with individual-face fMRI responses

PubMed Central

Kriegeskorte, Nikolaus

2017-01-01

The perceptual representation of individual faces is often explained with reference to a norm-based face space. In such spaces, individuals are encoded as vectors where identity is primarily conveyed by direction and distinctiveness by eccentricity. Here we measured human fMRI responses and psychophysical similarity judgments of individual face exemplars, which were generated as realistic 3D animations using a computer-graphics model. We developed and evaluated multiple neurobiologically plausible computational models, each of which predicts a representational distance matrix and a regional-mean activation profile for 24 face stimuli. In the fusiform face area, a face-space coding model with sigmoidal ramp tuning provided a better account of the data than one based on exemplar tuning. However, an image-processing model with weighted banks of Gabor filters performed similarly. Accounting for the data required the inclusion of a measurement-level population averaging mechanism that approximates how fMRI voxels locally average distinct neuronal tunings. Our study demonstrates the importance of comparing multiple models and of modeling the measurement process in computational neuroimaging. PMID:28746335

Characteristic classes of gauge systems

NASA Astrophysics Data System (ADS)

Lyakhovich, S. L.; Sharapov, A. A.

2004-12-01

We define and study invariants which can be uniformly constructed for any gauge system. By a gauge system we understand an (anti-)Poisson supermanifold provided with an odd Hamiltonian self-commuting vector field called a homological vector field. This definition encompasses all the cases usually included into the notion of a gauge theory in physics as well as some other similar (but different) structures like Lie or Courant algebroids. For Lagrangian gauge theories or Hamiltonian first class constrained systems, the homological vector field is identified with the classical BRST transformation operator. We define characteristic classes of a gauge system as universal cohomology classes of the homological vector field, which are uniformly constructed in terms of this vector field itself. Not striving to exhaustively classify all the characteristic classes in this work, we compute those invariants which are built up in terms of the first derivatives of the homological vector field. We also consider the cohomological operations in the space of all the characteristic classes. In particular, we show that the (anti-)Poisson bracket becomes trivial when applied to the space of all the characteristic classes, instead the latter space can be endowed with another Lie bracket operation. Making use of this Lie bracket one can generate new characteristic classes involving higher derivatives of the homological vector field. The simplest characteristic classes are illustrated by the examples relating them to anomalies in the traditional BV or BFV-BRST theory and to characteristic classes of (singular) foliations.

LDA boost classification: boosting by topics

NASA Astrophysics Data System (ADS)

Lei, La; Qiao, Guo; Qimin, Cao; Qitao, Li

2012-12-01

AdaBoost is an efficacious classification algorithm especially in text categorization (TC) tasks. The methodology of setting up a classifier committee and voting on the documents for classification can achieve high categorization precision. However, traditional Vector Space Model can easily lead to the curse of dimensionality and feature sparsity problems; so it affects classification performance seriously. This article proposed a novel classification algorithm called LDABoost based on boosting ideology which uses Latent Dirichlet Allocation (LDA) to modeling the feature space. Instead of using words or phrase, LDABoost use latent topics as the features. In this way, the feature dimension is significantly reduced. Improved Naïve Bayes (NB) is designed as the weaker classifier which keeps the efficiency advantage of classic NB algorithm and has higher precision. Moreover, a two-stage iterative weighted method called Cute Integration in this article is proposed for improving the accuracy by integrating weak classifiers into strong classifier in a more rational way. Mutual Information is used as metrics of weights allocation. The voting information and the categorization decision made by basis classifiers are fully utilized for generating the strong classifier. Experimental results reveals LDABoost making categorization in a low-dimensional space, it has higher accuracy than traditional AdaBoost algorithms and many other classic classification algorithms. Moreover, its runtime consumption is lower than different versions of AdaBoost, TC algorithms based on support vector machine and Neural Networks.

Unidirectional Wave Vector Manipulation in Two-Dimensional Space with an All Passive Acoustic Parity-Time-Symmetric Metamaterials Crystal

NASA Astrophysics Data System (ADS)

Liu, Tuo; Zhu, Xuefeng; Chen, Fei; Liang, Shanjun; Zhu, Jie

2018-03-01

Exploring the concept of non-Hermitian Hamiltonians respecting parity-time symmetry with classical wave systems is of great interest as it enables the experimental investigation of parity-time-symmetric systems through the quantum-classical analogue. Here, we demonstrate unidirectional wave vector manipulation in two-dimensional space, with an all passive acoustic parity-time-symmetric metamaterials crystal. The metamaterials crystal is constructed through interleaving groove- and holey-structured acoustic metamaterials to provide an intrinsic parity-time-symmetric potential that is two-dimensionally extended and curved, which allows the flexible manipulation of unpaired wave vectors. At the transition point from the unbroken to broken parity-time symmetry phase, the unidirectional sound focusing effect (along with reflectionless acoustic transparency in the opposite direction) is experimentally realized over the spectrum. This demonstration confirms the capability of passive acoustic systems to carry the experimental studies on general parity-time symmetry physics and further reveals the unique functionalities enabled by the judiciously tailored unidirectional wave vectors in space.

Application of wavelet-based multi-model Kalman filters to real-time flood forecasting

NASA Astrophysics Data System (ADS)

Chou, Chien-Ming; Wang, Ru-Yih

2004-04-01

This paper presents the application of a multimodel method using a wavelet-based Kalman filter (WKF) bank to simultaneously estimate decomposed state variables and unknown parameters for real-time flood forecasting. Applying the Haar wavelet transform alters the state vector and input vector of the state space. In this way, an overall detail plus approximation describes each new state vector and input vector, which allows the WKF to simultaneously estimate and decompose state variables. The wavelet-based multimodel Kalman filter (WMKF) is a multimodel Kalman filter (MKF), in which the Kalman filter has been substituted for a WKF. The WMKF then obtains M estimated state vectors. Next, the M state-estimates, each of which is weighted by its possibility that is also determined on-line, are combined to form an optimal estimate. Validations conducted for the Wu-Tu watershed, a small watershed in Taiwan, have demonstrated that the method is effective because of the decomposition of wavelet transform, the adaptation of the time-varying Kalman filter and the characteristics of the multimodel method. Validation results also reveal that the resulting method enhances the accuracy of the runoff prediction of the rainfall-runoff process in the Wu-Tu watershed.

On Anholonomic Deformation, Geometry, and Differentiation

DTIC Science & Technology

2013-02-01

αβχ are not necessarily Levi - Civita connection coefficients). The vector cross product × obeys, for two vectors V and W and two covectors α and β , V...three-dimensional space. 2.2.5. Euclidean space. Let GAB(X ) = GA · GB be the metric tensor of the space. The Levi - Civita connection coefficients of GAB...curvature tensor of the Levi - Civita connection vanishes identically: G R A BCD = 2 ( ∂[B G A C]D + G A[B|E|G EC]D ) = 0. (43) In n

Differential Calculus on h-Deformed Spaces

NASA Astrophysics Data System (ADS)

Herlemont, Basile; Ogievetsky, Oleg

2017-10-01

We construct the rings of generalized differential operators on the h-deformed vector space of gl-type. In contrast to the q-deformed vector space, where the ring of differential operators is unique up to an isomorphism, the general ring of h-deformed differential operators {Diff}_{h},σ(n) is labeled by a rational function σ in n variables, satisfying an over-determined system of finite-difference equations. We obtain the general solution of the system and describe some properties of the rings {Diff}_{h},σ(n).

Support vector machine based decision for mechanical fault condition monitoring in induction motor using an advanced Hilbert-Park transform.

PubMed

Ben Salem, Samira; Bacha, Khmais; Chaari, Abdelkader

2012-09-01

In this work we suggest an original fault signature based on an improved combination of Hilbert and Park transforms. Starting from this combination we can create two fault signatures: Hilbert modulus current space vector (HMCSV) and Hilbert phase current space vector (HPCSV). These two fault signatures are subsequently analysed using the classical fast Fourier transform (FFT). The effects of mechanical faults on the HMCSV and HPCSV spectrums are described, and the related frequencies are determined. The magnitudes of spectral components, relative to the studied faults (air-gap eccentricity and outer raceway ball bearing defect), are extracted in order to develop the input vector necessary for learning and testing the support vector machine with an aim of classifying automatically the various states of the induction motor. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Evolution of Lamb Vector as a Vortex Breaking into Turbulence.

NASA Astrophysics Data System (ADS)

Wu, J. Z.; Lu, X. Y.

1996-11-01

In an incompressible flow, either laminar or turbulent, the Lamb vector is solely responsible to nonlinear interactions. While its longitudinal part is balanced by stagnation enthalpy, its transverse part is the unique source (as an external forcing in spectral space) that causes the flow to evolve. Moreover, in Reynolds-averaged flows the turbulent force can be derived exclusively from the Lamb vector instead of the full Reynolds stress tensor. Therefore, studying the evolution of the Lamb vector itself (both longitudinal and transverse parts) is of great interest. We have numerically examined this problem, taking the nonlinear distabilization of a viscous vortex as an example. In the later stage of this evolution we introduced a forcing to keep a statistically steady state, and observed the Lamb vector behavior in the resulting fine turbulence. The result is presented in both physical and spectral spaces.

Hamiltonian and Thermodynamic Modeling of Quantum Turbulence

NASA Astrophysics Data System (ADS)

Grmela, Miroslav

2010-10-01

The state variables in the novel model introduced in this paper are the fields playing this role in the classical Landau-Tisza model and additional fields of mass, entropy (or temperature), superfluid velocity, and gradient of the superfluid velocity, all depending on the position vector and another tree dimensional vector labeling the scale, describing the small-scale structure developed in 4He superfluid experiencing turbulent motion. The fluxes of mass, momentum, energy, and entropy in the position space as well as the fluxes of energy and entropy in scales, appear in the time evolution equations as explicit functions of the state variables and of their conjugates. The fundamental thermodynamic relation relating the fields to their conjugates is left in this paper undetermined. The GENERIC structure of the equations serves two purposes: (i) it guarantees that solutions to the governing equations, independently of the choice of the fundamental thermodynamic relation, agree with the observed compatibility with thermodynamics, and (ii) it is used as a guide in the construction of the novel model.

Optoelectronic Inner-Product Neural Associative Memory

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang

1993-01-01

Optoelectronic apparatus acts as artificial neural network performing associative recall of binary images. Recall process is iterative one involving optical computation of inner products between binary input vector and one or more reference binary vectors in memory. Inner-product method requires far less memory space than matrix-vector method.

Parametric State Space Structuring

NASA Technical Reports Server (NTRS)

Ciardo, Gianfranco; Tilgner, Marco

1997-01-01

Structured approaches based on Kronecker operators for the description and solution of the infinitesimal generator of a continuous-time Markov chains are receiving increasing interest. However, their main advantage, a substantial reduction in the memory requirements during the numerical solution, comes at a price. Methods based on the "potential state space" allocate a probability vector that might be much larger than actually needed. Methods based on the "actual state space", instead, have an additional logarithmic overhead. We present an approach that realizes the advantages of both methods with none of their disadvantages, by partitioning the local state spaces of each submodel. We apply our results to a model of software rendezvous, and show how they reduce memory requirements while, at the same time, improving the efficiency of the computation.

Learning atoms for materials discovery.

PubMed

Zhou, Quan; Tang, Peizhe; Liu, Shenxiu; Pan, Jinbo; Yan, Qimin; Zhang, Shou-Cheng

2018-06-26

Exciting advances have been made in artificial intelligence (AI) during recent decades. Among them, applications of machine learning (ML) and deep learning techniques brought human-competitive performances in various tasks of fields, including image recognition, speech recognition, and natural language understanding. Even in Go, the ancient game of profound complexity, the AI player has already beat human world champions convincingly with and without learning from the human. In this work, we show that our unsupervised machines (Atom2Vec) can learn the basic properties of atoms by themselves from the extensive database of known compounds and materials. These learned properties are represented in terms of high-dimensional vectors, and clustering of atoms in vector space classifies them into meaningful groups consistent with human knowledge. We use the atom vectors as basic input units for neural networks and other ML models designed and trained to predict materials properties, which demonstrate significant accuracy. Copyright © 2018 the Author(s). Published by PNAS.

Search for single production of vector-like top partner decaying to Wb at eγ collision

NASA Astrophysics Data System (ADS)

Yang, Bingfang; Shao, Hongbo; Han, Jinzhong

2018-03-01

In a simplified model including an SU(2) singlet T quark with charge 2/3, we investigate the single vector-like T production at the high energy eγ collision. We study the observability of the vector-like T focusing on the T→ Wb decay channel with W→ l\\bar{ν } at √{s}=2.0 TeV. In this analysis, only two free parameters are involved, namely the T quark coupling strength for single production g^{*} and the mass mT. We scan the parameter space and find that the correlation region of g^{*}\\in [0.24, 0.5] and mT\\in [800, 1360] GeV can be excluded with integrated luminosity L=100 fb^{-1} and the correlation region of g^{*}\\in [0.13, 0.5] and mT\\in [800, 1620] GeV can be excluded with integrated luminosity L=1000 fb^{-1} at 2σ level.

Digital TV processing system

NASA Technical Reports Server (NTRS)

1975-01-01

Two digital video data compression systems directly applicable to the Space Shuttle TV Communication System were described: (1) For the uplink, a low rate monochrome data compressor is used. The compression is achieved by using a motion detection technique in the Hadamard domain. To transform the variable source rate into a fixed rate, an adaptive rate buffer is provided. (2) For the downlink, a color data compressor is considered. The compression is achieved first by intra-color transformation of the original signal vector, into a vector which has lower information entropy. Then two-dimensional data compression techniques are applied to the Hadamard transformed components of this last vector. Mathematical models and data reliability analyses were also provided for the above video data compression techniques transmitted over a channel encoded Gaussian channel. It was shown that substantial gains can be achieved by the combination of video source and channel coding.

Vector and Tensor Analyzing Powers in Deuteron-Proton Breakup

NASA Astrophysics Data System (ADS)

Stephan, E.; Kistryn, St.; Kalantar-Nayestanaki, N.; Biegun, A.; Bodek, K.; Ciepał, I.; Deltuva, A.; Eslami-Kalantari, M.; Fonseca, A. C.; Gasparić, I.; Golak, J.; Jamróz, B.; Joulaeizadeh, L.; Kamada, H.; Kiš, M.; Kłos, B.; Kozela, A.; Mahjour-Shafiei, M.; Mardanpour, H.; Messchendorp, J.; Micherdzińska, A.; Moeini, H.; Nogga, A.; Ramazani-Moghaddam-Arani, A.; Skibiński, R.; Sworst, R.; Witała, H.; Zejma, J.

2011-05-01

High precision data for vector and tensor analyzing powers of the {^1{H}({d},{{pp}}){n}} breakup reaction at 130 and 100 MeV deuteron beam energies have been measured in a large fraction of the phase space. They are compared to the theoretical predictions based on various approaches to describe the three nucleon (3N) system dynamics. Theoretical predictions describe very well the vector analyzing power data, with no need to include any three-nucleon force effects for these observables. Tensor analyzing powers can be also very well reproduced by calculations in most of the studied region, but locally certain discrepancies are observed. At 130 MeV for A xy such discrepancies usually appear, or are enhanced, when model 3N forces are included. Predicted effects of 3NFs are much lower at 100 MeV and at this energy equally good consistency between the data and the calculations is obtained with or without 3NFs.

Human pose tracking from monocular video by traversing an image motion mapped body pose manifold

NASA Astrophysics Data System (ADS)

Basu, Saurav; Poulin, Joshua; Acton, Scott T.

2010-01-01

Tracking human pose from monocular video sequences is a challenging problem due to the large number of independent parameters affecting image appearance and nonlinear relationships between generating parameters and the resultant images. Unlike the current practice of fitting interpolation functions to point correspondences between underlying pose parameters and image appearance, we exploit the relationship between pose parameters and image motion flow vectors in a physically meaningful way. Change in image appearance due to pose change is realized as navigating a low dimensional submanifold of the infinite dimensional Lie group of diffeomorphisms of the two dimensional sphere S2. For small changes in pose, image motion flow vectors lie on the tangent space of the submanifold. Any observed image motion flow vector field is decomposed into the basis motion vector flow fields on the tangent space and combination weights are used to update corresponding pose changes in the different dimensions of the pose parameter space. Image motion flow vectors are largely invariant to style changes in experiments with synthetic and real data where the subjects exhibit variation in appearance and clothing. The experiments demonstrate the robustness of our method (within +/-4° of ground truth) to style variance.

Development and Application of Modern Optimal Controllers for a Membrane Structure Using Vector Second Order Form

NASA Astrophysics Data System (ADS)

Ferhat, Ipar

With increasing advancement in material science and computational power of current computers that allows us to analyze high dimensional systems, very light and large structures are being designed and built for aerospace applications. One example is a reflector of a space telescope that is made of membrane structures. These reflectors are light and foldable which makes the shipment easy and cheaper unlike traditional reflectors made of glass or other heavy materials. However, one of the disadvantages of membranes is that they are very sensitive to external changes, such as thermal load or maneuvering of the space telescope. These effects create vibrations that dramatically affect the performance of the reflector. To overcome vibrations in membranes, in this work, piezoelectric actuators are used to develop distributed controllers for membranes. These actuators generate bending effects to suppress the vibration. The actuators attached to a membrane are relatively thick which makes the system heterogeneous; thus, an analytical solution cannot be obtained to solve the partial differential equation of the system. Therefore, the Finite Element Model is applied to obtain an approximate solution for the membrane actuator system. Another difficulty that arises with very flexible large structures is the dimension of the discretized system. To obtain an accurate result, the system needs to be discretized using smaller segments which makes the dimension of the system very high. This issue will persist as long as the improving technology will allow increasingly complex and large systems to be designed and built. To deal with this difficulty, the analysis of the system and controller development to suppress the vibration are carried out using vector second order form as an alternative to vector first order form. In vector second order form, the number of equations that need to be solved are half of the number equations in vector first order form. Analyzing the system for control characteristics such as stability, controllability and observability is a key step that needs to be carried out before developing a controller. This analysis determines what kind of system is being modeled and the appropriate approach for controller development. Therefore, accuracy of the system analysis is very crucial. The results of the system analysis using vector second order form and vector first order form show the computational advantages of using vector second order form. Using similar concepts, LQR and LQG controllers, that are developed to suppress the vibration, are derived using vector second order form. To develop a controller using vector second order form, two different approaches are used. One is reducing the size of the Algebraic Riccati Equation to half by partitioning the solution matrix. The other approach is using the Hamiltonian method directly in vector second order form. Controllers are developed using both approaches and compared to each other. Some simple solutions for special cases are derived for vector second order form using the reduced Algebraic Riccati Equation. The advantages and drawbacks of both approaches are explained through examples. System analysis and controller applications are carried out for a square membrane system with four actuators. Two different systems with different actuator locations are analyzed. One system has the actuators at the corners of the membrane, the other has the actuators away from the corners. The structural and control effect of actuator locations are demonstrated with mode shapes and simulations. The results of the controller applications and the comparison of the vector first order form with the vector second order form demonstrate the efficacy of the controllers.

Difference-based ridge-type estimator of parameters in restricted partial linear model with correlated errors.

PubMed

Wu, Jibo

2016-01-01

In this article, a generalized difference-based ridge estimator is proposed for the vector parameter in a partial linear model when the errors are dependent. It is supposed that some additional linear constraints may hold to the whole parameter space. Its mean-squared error matrix is compared with the generalized restricted difference-based estimator. Finally, the performance of the new estimator is explained by a simulation study and a numerical example.

Unified control/structure design and modeling research

NASA Technical Reports Server (NTRS)

Mingori, D. L.; Gibson, J. S.; Blelloch, P. A.; Adamian, A.

1986-01-01

To demonstrate the applicability of the control theory for distributed systems to large flexible space structures, research was focused on a model of a space antenna which consists of a rigid hub, flexible ribs, and a mesh reflecting surface. The space antenna model used is discussed along with the finite element approximation of the distributed model. The basic control problem is to design an optimal or near-optimal compensator to suppress the linear vibrations and rigid-body displacements of the structure. The application of an infinite dimensional Linear Quadratic Gaussian (LQG) control theory to flexible structure is discussed. Two basic approaches for robustness enhancement were investigated: loop transfer recovery and sensitivity optimization. A third approach synthesized from elements of these two basic approaches is currently under development. The control driven finite element approximation of flexible structures is discussed. Three sets of finite element basic vectors for computing functional control gains are compared. The possibility of constructing a finite element scheme to approximate the infinite dimensional Hamiltonian system directly, instead of indirectly is discussed.

Soft and hard classification by reproducing kernel Hilbert space methods.

PubMed

Wahba, Grace

2002-12-24

Reproducing kernel Hilbert space (RKHS) methods provide a unified context for solving a wide variety of statistical modelling and function estimation problems. We consider two such problems: We are given a training set [yi, ti, i = 1, em leader, n], where yi is the response for the ith subject, and ti is a vector of attributes for this subject. The value of y(i) is a label that indicates which category it came from. For the first problem, we wish to build a model from the training set that assigns to each t in an attribute domain of interest an estimate of the probability pj(t) that a (future) subject with attribute vector t is in category j. The second problem is in some sense less ambitious; it is to build a model that assigns to each t a label, which classifies a future subject with that t into one of the categories or possibly "none of the above." The approach to the first of these two problems discussed here is a special case of what is known as penalized likelihood estimation. The approach to the second problem is known as the support vector machine. We also note some alternate but closely related approaches to the second problem. These approaches are all obtained as solutions to optimization problems in RKHS. Many other problems, in particular the solution of ill-posed inverse problems, can be obtained as solutions to optimization problems in RKHS and are mentioned in passing. We caution the reader that although a large literature exists in all of these topics, in this inaugural article we are selectively highlighting work of the author, former students, and other collaborators.

Constraining biosphere CO2 flux at regional scale with WRF-CO2 4DVar assimilation system

NASA Astrophysics Data System (ADS)

Zheng, T.

2017-12-01

The WRF-CO2 4DVar assimilation system is updated to include (1) operators for tower based observations (2) chemistry initial and boundary condition in the state vector (3) mechanism for aggregation from simulation model grid to state vector space. The update system is first tested with synthetic data to ensure its accuracy. The system is then used to test regional scale CO2 inversion at MCI (Midcontinental intensive) sites where CO2 mole fraction data were collected at multiple high towers during 2007-2008. The model domain is set to center on Iowa and include 8 towers within its boundary, and it is of 12x12km horizontal grid spacing. First, the relative impacts of the initial and boundary condition are assessed by the system's adjoint model. This is done with 24, 48, 72 hour time span. Second, we assessed the impacts of the transport error, including the misrepresentation of the boundary layer and cumulus activities. Third, we evaluated the different aggregation approach from the native model grid to the control variables (including scaling factors for flux, initial and boundary conditions). Four, we assessed the inversion performance using CO2 observation with different time-interval, and from different tower levels. We also examined the appropriate treatment of the background and observation error covariance in relation with these varying observation data sets.

Fixed points, stable manifolds, weather regimes, and their predictability

DOE PAGES

Deremble, Bruno; D'Andrea, Fabio; Ghil, Michael

2009-10-27

In a simple, one-layer atmospheric model, we study the links between low-frequency variability and the model’s fixed points in phase space. The model dynamics is characterized by the coexistence of multiple ''weather regimes.'' To investigate the transitions from one regime to another, we focus on the identification of stable manifolds associated with fixed points. We show that these manifolds act as separatrices between regimes. We track each manifold by making use of two local predictability measures arising from the meteorological applications of nonlinear dynamics, namely, ''bred vectors'' and singular vectors. These results are then verified in the framework of ensemblemore » forecasts issued from clouds (ensembles) of initial states. The divergence of the trajectories allows us to establish the connections between zones of low predictability, the geometry of the stable manifolds, and transitions between regimes.« less

A unified development of several techniques for the representation of random vectors and data sets

NASA Technical Reports Server (NTRS)

Bundick, W. T.

1973-01-01

Linear vector space theory is used to develop a general representation of a set of data vectors or random vectors by linear combinations of orthonormal vectors such that the mean squared error of the representation is minimized. The orthonormal vectors are shown to be the eigenvectors of an operator. The general representation is applied to several specific problems involving the use of the Karhunen-Loeve expansion, principal component analysis, and empirical orthogonal functions; and the common properties of these representations are developed.

Cyber threat impact assessment and analysis for space vehicle architectures

NASA Astrophysics Data System (ADS)

McGraw, Robert M.; Fowler, Mark J.; Umphress, David; MacDonald, Richard A.

2014-06-01

This paper covers research into an assessment of potential impacts and techniques to detect and mitigate cyber attacks that affect the networks and control systems of space vehicles. Such systems, if subverted by malicious insiders, external hackers and/or supply chain threats, can be controlled in a manner to cause physical damage to the space platforms. Similar attacks on Earth-borne cyber physical systems include the Shamoon, Duqu, Flame and Stuxnet exploits. These have been used to bring down foreign power generation and refining systems. This paper discusses the potential impacts of similar cyber attacks on space-based platforms through the use of simulation models, including custom models developed in Python using SimPy and commercial SATCOM analysis tools, as an example STK/SOLIS. The paper discusses the architecture and fidelity of the simulation model that has been developed for performing the impact assessment. The paper walks through the application of an attack vector at the subsystem level and how it affects the control and orientation of the space vehicle. SimPy is used to model and extract raw impact data at the bus level, while STK/SOLIS is used to extract raw impact data at the subsystem level and to visually display the effect on the physical plant of the space vehicle.

Geosynchronous Orbit Determination Using Space Surveillance Network Observations and Improved Radiative Force Modeling

DTIC Science & Technology

2004-06-01

equinoctial elements , because both sets of orbital elements reference the equinoctial coordinate system. In fact, to...spacecraft position and velocity vectors, or an element set , which represents the orbit using scalar quantities and angle measurements called orbital ...common element sets used to describe elliptical orbits (including circular orbits ) are Keplerian elements , also called classical orbital

Fractal planetary rings: Energy inequalities and random field model

NASA Astrophysics Data System (ADS)

Malyarenko, Anatoliy; Ostoja-Starzewski, Martin

2017-12-01

This study is motivated by a recent observation, based on photographs from the Cassini mission, that Saturn’s rings have a fractal structure in radial direction. Accordingly, two questions are considered: (1) What Newtonian mechanics argument in support of such a fractal structure of planetary rings is possible? (2) What kinematics model of such fractal rings can be formulated? Both challenges are based on taking planetary rings’ spatial structure as being statistically stationary in time and statistically isotropic in space, but statistically nonstationary in space. An answer to the first challenge is given through an energy analysis of circular rings having a self-generated, noninteger-dimensional mass distribution [V. E. Tarasov, Int. J. Mod Phys. B 19, 4103 (2005)]. The second issue is approached by taking the random field of angular velocity vector of a rotating particle of the ring as a random section of a special vector bundle. Using the theory of group representations, we prove that such a field is completely determined by a sequence of continuous positive-definite matrix-valued functions defined on the Cartesian square F2 of the radial cross-section F of the rings, where F is a fat fractal.

Encoding Dissimilarity Data for Statistical Model Building.

PubMed

Wahba, Grace

2010-12-01

We summarize, review and comment upon three papers which discuss the use of discrete, noisy, incomplete, scattered pairwise dissimilarity data in statistical model building. Convex cone optimization codes are used to embed the objects into a Euclidean space which respects the dissimilarity information while controlling the dimension of the space. A "newbie" algorithm is provided for embedding new objects into this space. This allows the dissimilarity information to be incorporated into a Smoothing Spline ANOVA penalized likelihood model, a Support Vector Machine, or any model that will admit Reproducing Kernel Hilbert Space components, for nonparametric regression, supervised learning, or semi-supervised learning. Future work and open questions are discussed. The papers are: F. Lu, S. Keles, S. Wright and G. Wahba 2005. A framework for kernel regularization with application to protein clustering. Proceedings of the National Academy of Sciences 102, 12332-1233.G. Corrada Bravo, G. Wahba, K. Lee, B. Klein, R. Klein and S. Iyengar 2009. Examining the relative influence of familial, genetic and environmental covariate information in flexible risk models. Proceedings of the National Academy of Sciences 106, 8128-8133F. Lu, Y. Lin and G. Wahba. Robust manifold unfolding with kernel regularization. TR 1008, Department of Statistics, University of Wisconsin-Madison.

Affixation in semantic space: Modeling morpheme meanings with compositional distributional semantics.

PubMed

Marelli, Marco; Baroni, Marco

2015-07-01

The present work proposes a computational model of morpheme combination at the meaning level. The model moves from the tenets of distributional semantics, and assumes that word meanings can be effectively represented by vectors recording their co-occurrence with other words in a large text corpus. Given this assumption, affixes are modeled as functions (matrices) mapping stems onto derived forms. Derived-form meanings can be thought of as the result of a combinatorial procedure that transforms the stem vector on the basis of the affix matrix (e.g., the meaning of nameless is obtained by multiplying the vector of name with the matrix of -less). We show that this architecture accounts for the remarkable human capacity of generating new words that denote novel meanings, correctly predicting semantic intuitions about novel derived forms. Moreover, the proposed compositional approach, once paired with a whole-word route, provides a new interpretative framework for semantic transparency, which is here partially explained in terms of ease of the combinatorial procedure and strength of the transformation brought about by the affix. Model-based predictions are in line with the modulation of semantic transparency on explicit intuitions about existing words, response times in lexical decision, and morphological priming. In conclusion, we introduce a computational model to account for morpheme combination at the meaning level. The model is data-driven, theoretically sound, and empirically supported, and it makes predictions that open new research avenues in the domain of semantic processing. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Solid-state lighting life prediction using extended Kalman filter

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

Lall, Pradeep; Wei, Junchao; Davis, Lynn

2013-07-16

Solid-state lighting (SSL) luminaires containing light emitting diodes (LEDs) have the potential of seeing excessive temperatures when being transported across country or being stored in non-climate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects high temperature exposure for a prolonged period of time will have on the usability and survivability of these devices. The U.S. Department of Energy has made a long term commitment to advance the efficiency, understandingmore » and development of solid-state lighting (SSL) and is making a strong push for the acceptance and use of SSL products to reduce overall energy consumption attributable to lighting. Traditional light sources “burn out” at end-of-life. For an incandescent bulb, the lamp life is defined by B50 life. However, the LEDs have no filament to “burn”. The LEDs continually degrade and the light output decreases eventually below useful levels causing failure. Presently, the TM-21 test standard is used to predict the L70 life of SSL Luminaires from LM-80 test data. The TM-21 model uses an Arrhenius Equation with an Activation Energy, Pre-decay factor and Decay Rates. Several failure mechanisms may be active in a luminaire at a single time causing lumen depreciation. The underlying TM-21 Arrhenius Model may not capture the failure physics in presence of multiple failure mechanisms. Correlation of lumen maintenance with underlying physics of degradation at system-level is needed. In this paper, a Kalman Filter and Extended Kalman Filters have been used to develop a 70% Lumen Maintenance Life Prediction Model for a LEDs used in SSL luminaires. This model can be used to calculate acceleration factors, evaluate failure-probability and identify ALT methodologies for reducing test time. Ten-thousand hour LM-80 test data for various LEDs have been used for model development. System state has been described in state space form using the measurement of the feature vector, velocity of feature vector change and the acceleration of the feature vector change. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. The measured state variable has been related to the underlying damage using physics-based models. Life prediction of L70 life for the LEDs used in SSL luminaires from KF and EKF based models have been compared with the TM-21 model predictions and experimental data.« less

Potential distribution of mosquito vector species in a primary malaria endemic region of Colombia

PubMed Central

Altamiranda-Saavedra, Mariano; Arboleda, Sair; Parra, Juan L.; Peterson, A. Townsend

2017-01-01

Rapid transformation of natural ecosystems changes ecological conditions for important human disease vector species; therefore, an essential task is to identify and understand the variables that shape distributions of these species to optimize efforts toward control and mitigation. Ecological niche modeling was used to estimate the potential distribution and to assess hypotheses of niche similarity among the three main malaria vector species in northern Colombia: Anopheles nuneztovari, An. albimanus, and An. darlingi. Georeferenced point collection data and remotely sensed, fine-resolution satellite imagery were integrated across the Urabá –Bajo Cauca–Alto Sinú malaria endemic area using a maximum entropy algorithm. Results showed that An. nuneztovari has the widest geographic distribution, occupying almost the entire study region; this niche breadth is probably related to the ability of this species to colonize both, natural and disturbed environments. The model for An. darlingi showed that most suitable localities for this species in Bajo Cauca were along the Cauca and Nechí river. The riparian ecosystems in this region and the potential for rapid adaptation by this species to novel environments, may favor the establishment of populations of this species. Apparently, the three main Colombian Anopheles vector species in this endemic area do not occupy environments either with high seasonality, or with low seasonality and high NDVI values. Estimated overlap in geographic space between An. nuneztovari and An. albimanus indicated broad spatial and environmental similarity between these species. An. nuneztovari has a broader niche and potential distribution. Dispersal ability of these species and their ability to occupy diverse environmental situations may facilitate sympatry across many environmental and geographic contexts. These model results may be useful for the design and implementation of malaria species-specific vector control interventions optimized for this important malaria region. PMID:28594942

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.

A proposed physical analog for a quantum probability amplitude

NASA Astrophysics Data System (ADS)

Boyd, Jeffrey

What is the physical analog of a probability amplitude? All quantum mathematics, including quantum information, is built on amplitudes. Every other science uses probabilities; QM alone uses their square root. Why? This question has been asked for a century, but no one previously has proposed an answer. We will present cylindrical helices moving toward a particle source, which particles follow backwards. Consider Feynman's book QED. He speaks of amplitudes moving through space like the hand of a spinning clock. His hand is a complex vector. It traces a cylindrical helix in Cartesian space. The Theory of Elementary Waves changes direction so Feynman's clock faces move toward the particle source. Particles follow amplitudes (quantum waves) backwards. This contradicts wave particle duality. We will present empirical evidence that wave particle duality is wrong about the direction of particles versus waves. This involves a paradigm shift; which are always controversial. We believe that our model is the ONLY proposal ever made for the physical foundations of probability amplitudes. We will show that our ``probability amplitudes'' in physical nature form a Hilbert vector space with adjoints, an inner product and support both linear algebra and Dirac notation.

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

Berres, Anne Sabine

This slide presentation describes basic topological concepts, including topological spaces, homeomorphisms, homotopy, betti numbers. Scalar field topology explores finding topological features and scalar field visualization, and vector field topology explores finding topological features and vector field visualization.

The Local Stellar Velocity Field via Vector Spherical Harmonics

NASA Technical Reports Server (NTRS)

Markarov, V. V.; Murphy, D. W.

2007-01-01

We analyze the local field of stellar tangential velocities for a sample of 42,339 nonbinary Hipparcos stars with accurate parallaxes, using a vector spherical harmonic formalism. We derive simple relations between the parameters of the classical linear model (Ogorodnikov-Milne) of the local systemic field and low-degree terms of the general vector harmonic decomposition. Taking advantage of these relationships, we determine the solar velocity with respect to the local stars of (V(sub X), V(sub Y), V(sub Z)) (10.5, 18.5, 7.3) +/- 0.1 km s(exp -1) not corrected for the asymmetric drift with respect to the local standard of rest. If only stars more distant than 100 pc are considered, the peculiar solar motion is (V(sub X), V(sub Y), V(sub Z)) (9.9, 15.6, 6.9) +/- 0.2 km s(exp -1). The adverse effects of harmonic leakage, which occurs between the reflex solar motion represented by the three electric vector harmonics in the velocity space and higher degree harmonics in the proper-motion space, are eliminated in our analysis by direct subtraction of the reflex solar velocity in its tangential components for each star. The Oort parameters determined by a straightforward least-squares adjustment in vector spherical harmonics are A=14.0 +/- 1.4, B=13.1 +/- 1.2, K=1.1 +/- 1.8, and C=2.9 +/- 1.4 km s(exp -1) kpc(exp -1). The physical meaning and the implications of these parameters are discussed in the framework of a general linear model of the velocity field. We find a few statistically significant higher degree harmonic terms that do not correspond to any parameters in the classical linear model. One of them, a third-degree electric harmonic, is tentatively explained as the response to a negative linear gradient of rotation velocity with distance from the Galactic plane, which we estimate at approximately -20 km s(exp -1) kpc(exp -1). A similar vertical gradient of rotation velocity has been detected for more distant stars representing the thick disk (z greater than 1 kpc), but here we surmise its existence in the thin disk at z less than 200 pc. The most unexpected and unexplained term within the Ogorodnikov-Milne model is the first-degree magnetic harmonic, representing a rigid rotation of the stellar field about the axis -Y pointing opposite to the direction of rotation. This harmonic comes out with a statistically robust coefficient of 6.2 +/- 0.9 km s(exp -1) kpc(exp -1) and is also present in the velocity field of more distant stars. The ensuing upward vertical motion of stars in the general direction of the Galactic center and the downward motion in the anticenter direction are opposite to the vector field expected from the stationary Galactic warp model.

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…

4 × 20 Gbit/s mode division multiplexing over free space using vector modes and a q-plate mode (de)multiplexer

NASA Astrophysics Data System (ADS)

Milione, Giovanni; Lavery, Martin P. J.; Huang, Hao; Ren, Yongxiong; Xie, Guodong; Nguyen, Thien An; Karimi, Ebrahim; Marrucci, Lorenzo; Nolan, Daniel A.; Alfano, Robert R.; Willner, Alan E.

2015-05-01

Vector modes are spatial modes that have spatially inhomogeneous states of polarization, such as, radial and azimuthal polarization. They can produce smaller spot sizes and stronger longitudinal polarization components upon focusing. As a result, they are used for many applications, including optical trapping and nanoscale imaging. In this work, vector modes are used to increase the information capacity of free space optical communication via the method of optical communication referred to as mode division multiplexing. A mode (de)multiplexer for vector modes based on a liquid crystal technology referred to as a q-plate is introduced. As a proof of principle, using the mode (de)multiplexer four vector modes each carrying a 20 Gbit/s quadrature phase shift keying signal on a single wavelength channel (~1550nm), comprising an aggregate 80 Gbit/s, were transmitted ~1m over the lab table with <-16.4 dB (<2%) mode crosstalk. Bit error rates for all vector modes were measured at the forward error correction threshold with power penalties < 3.41dB.

Predicting the magnetic vectors within coronal mass ejections arriving at Earth: 2. Geomagnetic response

NASA Astrophysics Data System (ADS)

Savani, N. P.; Vourlidas, A.; Richardson, I. G.; Szabo, A.; Thompson, B. J.; Pulkkinen, A.; Mays, M. L.; Nieves-Chinchilla, T.; Bothmer, V.

2017-02-01

This is a companion to Savani et al. (2015) that discussed how a first-order prediction of the internal magnetic field of a coronal mass ejection (CME) may be made from observations of its initial state at the Sun for space weather forecasting purposes (Bothmer-Schwenn scheme (BSS) model). For eight CME events, we investigate how uncertainties in their predicted magnetic structure influence predictions of the geomagnetic activity. We use an empirical relationship between the solar wind plasma drivers and Kp index together with the inferred magnetic vectors, to make a prediction of the time variation of Kp (Kp(BSS)). We find a 2σ uncertainty range on the magnetic field magnitude (|B|) provides a practical and convenient solution for predicting the uncertainty in geomagnetic storm strength. We also find the estimated CME velocity is a major source of error in the predicted maximum Kp. The time variation of Kp(BSS) is important for predicting periods of enhanced and maximum geomagnetic activity, driven by southerly directed magnetic fields, and periods of lower activity driven by northerly directed magnetic field. We compare the skill score of our model to a number of other forecasting models, including the NOAA/Space Weather Prediction Center (SWPC) and Community Coordinated Modeling Center (CCMC)/SWRC estimates. The BSS model was the most unbiased prediction model, while the other models predominately tended to significantly overforecast. The True skill score of the BSS prediction model (TSS = 0.43 ± 0.06) exceeds the results of two baseline models and the NOAA/SWPC forecast. The BSS model prediction performed equally with CCMC/SWRC predictions while demonstrating a lower uncertainty.

A weather-driven model of malaria transmission

PubMed Central

Hoshen, Moshe B; Morse, Andrew P

2004-01-01

Background Climate is a major driving force behind malaria transmission and climate data are often used to account for the spatial, seasonal and interannual variation in malaria transmission. Methods This paper describes a mathematical-biological model of the parasite dynamics, comprising both the weather-dependent within-vector stages and the weather-independent within-host stages. Results Numerical evaluations of the model in both time and space show that it qualitatively reconstructs the prevalence of infection. Conclusion A process-based modelling structure has been developed that may be suitable for the simulation of malaria forecasts based on seasonal weather forecasts. PMID:15350206

Selection of optimal complexity for ENSO-EMR model by minimum description length principle

NASA Astrophysics Data System (ADS)

Loskutov, E. M.; Mukhin, D.; Mukhina, A.; Gavrilov, A.; Kondrashov, D. A.; Feigin, A. M.

2012-12-01

One of the main problems arising in modeling of data taken from natural system is finding a phase space suitable for construction of the evolution operator model. Since we usually deal with strongly high-dimensional behavior, we are forced to construct a model working in some projection of system phase space corresponding to time scales of interest. Selection of optimal projection is non-trivial problem since there are many ways to reconstruct phase variables from given time series, especially in the case of a spatio-temporal data field. Actually, finding optimal projection is significant part of model selection, because, on the one hand, the transformation of data to some phase variables vector can be considered as a required component of the model. On the other hand, such an optimization of a phase space makes sense only in relation to the parametrization of the model we use, i.e. representation of evolution operator, so we should find an optimal structure of the model together with phase variables vector. In this paper we propose to use principle of minimal description length (Molkov et al., 2009) for selection models of optimal complexity. The proposed method is applied to optimization of Empirical Model Reduction (EMR) of ENSO phenomenon (Kravtsov et al. 2005, Kondrashov et. al., 2005). This model operates within a subset of leading EOFs constructed from spatio-temporal field of SST in Equatorial Pacific, and has a form of multi-level stochastic differential equations (SDE) with polynomial parameterization of the right-hand side. Optimal values for both the number of EOF, the order of polynomial and number of levels are estimated from the Equatorial Pacific SST dataset. References: Ya. Molkov, D. Mukhin, E. Loskutov, G. Fidelin and A. Feigin, Using the minimum description length principle for global reconstruction of dynamic systems from noisy time series, Phys. Rev. E, Vol. 80, P 046207, 2009 Kravtsov S, Kondrashov D, Ghil M, 2005: Multilevel regression modeling of nonlinear processes: Derivation and applications to climatic variability. J. Climate, 18 (21): 4404-4424. D. Kondrashov, S. Kravtsov, A. W. Robertson and M. Ghil, 2005. A hierarchy of data-based ENSO models. J. Climate, 18, 4425-4444.

Dengue Fever Occurrence and Vector Detection by Larval Survey, Ovitrap and MosquiTRAP: A Space-Time Clusters Analysis

PubMed Central

de Melo, Diogo Portella Ornelas; Scherrer, Luciano Rios; Eiras, Álvaro Eduardo

2012-01-01

The use of vector surveillance tools for preventing dengue disease requires fine assessment of risk, in order to improve vector control activities. Nevertheless, the thresholds between vector detection and dengue fever occurrence are currently not well established. In Belo Horizonte (Minas Gerais, Brazil), dengue has been endemic for several years. From January 2007 to June 2008, the dengue vector Aedes (Stegomyia) aegypti was monitored by ovitrap, the sticky-trap MosquiTRAP™ and larval surveys in an study area in Belo Horizonte. Using a space-time scan for clusters detection implemented in SaTScan software, the vector presence recorded by the different monitoring methods was evaluated. Clusters of vectors and dengue fever were detected. It was verified that ovitrap and MosquiTRAP vector detection methods predicted dengue occurrence better than larval survey, both spatially and temporally. MosquiTRAP and ovitrap presented similar results of space-time intersections to dengue fever clusters. Nevertheless ovitrap clusters presented longer duration periods than MosquiTRAP ones, less acuratelly signalizing the dengue risk areas, since the detection of vector clusters during most of the study period was not necessarily correlated to dengue fever occurrence. It was verified that ovitrap clusters occurred more than 200 days (values ranged from 97.0±35.35 to 283.0±168.4 days) before dengue fever clusters, whereas MosquiTRAP clusters preceded dengue fever clusters by approximately 80 days (values ranged from 65.5±58.7 to 94.0±14. 3 days), the former showing to be more temporally precise. Thus, in the present cluster analysis study MosquiTRAP presented superior results for signaling dengue transmission risks both geographically and temporally. Since early detection is crucial for planning and deploying effective preventions, MosquiTRAP showed to be a reliable tool and this method provides groundwork for the development of even more precise tools. PMID:22848729

Gamow-Teller response in the configuration space of a density-functional-theory-rooted no-core configuration-interaction model

NASA Astrophysics Data System (ADS)

Konieczka, M.; Kortelainen, M.; Satuła, W.

2018-03-01

Background: The atomic nucleus is a unique laboratory in which to study fundamental aspects of the electroweak interaction. This includes a question concerning in medium renormalization of the axial-vector current, which still lacks satisfactory explanation. Study of spin-isospin or Gamow-Teller (GT) response may provide valuable information on both the quenching of the axial-vector coupling constant as well as on nuclear structure and nuclear astrophysics. Purpose: We have performed a seminal calculation of the GT response by using the no-core configuration-interaction approach rooted in multireference density functional theory (DFT-NCCI). The model treats properly isospin and rotational symmetries and can be applied to calculate both the nuclear spectra and transition rates in atomic nuclei, irrespectively of their mass and particle-number parity. Methods: The DFT-NCCI calculation proceeds as follows: First, one builds a configuration space by computing relevant, for a given physical problem, (multi)particle-(multi)hole Slater determinants. Next, one applies the isospin and angular-momentum projections and performs the isospin and K mixing in order to construct a model space composed of linearly dependent states of good angular momentum. Eventually, one mixes the projected states by solving the Hill-Wheeler-Griffin equation. Results: The method is applied to compute the GT strength distribution in selected N ≈Z nuclei including the p -shell 8Li and 8Be nuclei and the s d -shell well-deformed nucleus 24Mg. In order to demonstrate a flexibility of the approach we present also a calculation of the superallowed GT β decay in doubly-magic spherical 100Sn and the low-spin spectrum in 100In. Conclusions: It is demonstrated that the DFT-NCCI model is capable of capturing the GT response satisfactorily well by using a relatively small configuration space, exhausting simultaneously the GT sum rule. The model, due to its flexibility and broad range of applicability, may either serve as a complement or even as an alternative to other theoretical approaches, including the conventional nuclear shell model.

Model Predictive Control of A Matrix-Converter Based Solid State Transformer for Utility Grid Interaction

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

Xue, Yaosuo

The matrix converter solid state transformer (MC-SST), formed from the back-to-back connection of two three-to-single-phase matrix converters, is studied for use in the interconnection of two ac grids. The matrix converter topology provides a light weight and low volume single-stage bidirectional ac-ac power conversion without the need for a dc link. Thus, the lifetime limitations of dc-bus storage capacitors are avoided. However, space vector modulation of this type of MC-SST requires to compute vectors for each of the two MCs, which must be carefully coordinated to avoid commutation failure. An additional controller is also required to control power exchange betweenmore » the two ac grids. In this paper, model predictive control (MPC) is proposed for an MC-SST connecting two different ac power grids. The proposed MPC predicts the circuit variables based on the discrete model of MC-SST system and the cost function is formulated so that the optimal switch vector for the next sample period is selected, thereby generating the required grid currents for the SST. Simulation and experimental studies are carried out to demonstrate the effectiveness and simplicity of the proposed MPC for such MC-SST-based grid interfacing systems.« less

Investigation into Text Classification With Kernel Based Schemes

DTIC Science & Technology

2010-03-01

Document Matrix TDMs Term-Document Matrices TMG Text to Matrix Generator TN True Negative TP True Positive VSM Vector Space Model xxii THIS PAGE...are represented as a term-document matrix, common evaluation metrics, and the software package Text to Matrix Generator ( TMG ). The classifier...AND METRICS This chapter introduces the indexing capabilities of the Text to Matrix Generator ( TMG ) Toolbox. Specific attention is placed on the

Deorbit targeting

NASA Technical Reports Server (NTRS)

Tempelman, W. H.

1973-01-01

The navigation and control of the space shuttle during atmospheric entry are discussed. A functional flow diagram presenting the basic approach to the deorbit targeting problem is presented. The major inputs to be considered are: (1) vehicle state vector, (2) landing site location, (3) entry interface parameters, (4) earliest desired time of landing, and (5) maximum cross range. Mathematical models of the navigational procedures based on controlled thrust times are developed.

Poiseuille equation for steady flow of fractal fluid

NASA Astrophysics Data System (ADS)

Tarasov, Vasily E.

2016-07-01

Fractal fluid is considered in the framework of continuous models with noninteger dimensional spaces (NIDS). A recently proposed vector calculus in NIDS is used to get a description of fractal fluid flow in pipes with circular cross-sections. The Navier-Stokes equations of fractal incompressible viscous fluids are used to derive a generalization of the Poiseuille equation of steady flow of fractal media in pipe.

Error assessment of local tie vectors in space geodesy

NASA Astrophysics Data System (ADS)

Falkenberg, Jana; Heinkelmann, Robert; Schuh, Harald

2014-05-01

For the computation of the ITRF, the data of the geometric space-geodetic techniques on co-location sites are combined. The combination increases the redundancy and offers the possibility to utilize the strengths of each technique while mitigating their weaknesses. To enable the combination of co-located techniques each technique needs to have a well-defined geometric reference point. The linking of the geometric reference points enables the combination of the technique-specific coordinate to a multi-technique site coordinate. The vectors between these reference points are called "local ties". The realization of local ties is usually reached by local surveys of the distances and or angles between the reference points. Identified temporal variations of the reference points are considered in the local tie determination only indirectly by assuming a mean position. Finally, the local ties measured in the local surveying network are to be transformed into the ITRF, the global geocentric equatorial coordinate system of the space-geodetic techniques. The current IERS procedure for the combination of the space-geodetic techniques includes the local tie vectors with an error floor of three millimeters plus a distance dependent component. This error floor, however, significantly underestimates the real accuracy of local tie determination. To fullfill the GGOS goals of 1 mm position and 0.1 mm/yr velocity accuracy, an accuracy of the local tie will be mandatory at the sub-mm level, which is currently not achievable. To assess the local tie effects on ITRF computations, investigations of the error sources will be done to realistically assess and consider them. Hence, a reasonable estimate of all the included errors of the various local ties is needed. An appropriate estimate could also improve the separation of local tie error and technique-specific error contributions to uncertainties and thus access the accuracy of space-geodetic techniques. Our investigations concern the simulation of the error contribution of each component of the local tie definition and determination. A closer look into the models of reference point definition, of accessibility, of measurement, and of transformation is necessary to properly model the error of the local tie. The effect of temporal variations on the local ties will be studied as well. The transformation of the local survey into the ITRF can be assumed to be the largest error contributor, in particular the orientation of the local surveying network to the ITRF.

An algebraic hypothesis about the primeval genetic code architecture.

PubMed

Sánchez, Robersy; Grau, Ricardo

2009-09-01

A plausible architecture of an ancient genetic code is derived from an extended base triplet vector space over the Galois field of the extended base alphabet {D,A,C,G,U}, where symbol D represents one or more hypothetical bases with unspecific pairings. We hypothesized that the high degeneration of a primeval genetic code with five bases and the gradual origin and improvement of a primeval DNA repair system could make possible the transition from ancient to modern genetic codes. Our results suggest that the Watson-Crick base pairing G identical with C and A=U and the non-specific base pairing of the hypothetical ancestral base D used to define the sum and product operations are enough features to determine the coding constraints of the primeval and the modern genetic code, as well as, the transition from the former to the latter. Geometrical and algebraic properties of this vector space reveal that the present codon assignment of the standard genetic code could be induced from a primeval codon assignment. Besides, the Fourier spectrum of the extended DNA genome sequences derived from the multiple sequence alignment suggests that the called period-3 property of the present coding DNA sequences could also exist in the ancient coding DNA sequences. The phylogenetic analyses achieved with metrics defined in the N-dimensional vector space (B(3))(N) of DNA sequences and with the new evolutionary model presented here also suggest that an ancient DNA coding sequence with five or more bases does not contradict the expected evolutionary history.

ViSBARD: Visual System for Browsing, Analysis and Retrieval of Data

NASA Astrophysics Data System (ADS)

Roberts, D. Aaron; Boller, Ryan; Rezapkin, V.; Coleman, J.; McGuire, R.; Goldstein, M.; Kalb, V.; Kulkarni, R.; Luckyanova, M.; Byrnes, J.; Kerbel, U.; Candey, R.; Holmes, C.; Chimiak, R.; Harris, B.

2018-04-01

ViSBARD interactively visualizes and analyzes space physics data. It provides an interactive integrated 3-D and 2-D environment to determine correlations between measurements across many spacecraft. It supports a variety of spacecraft data products and MHD models and is easily extensible to others. ViSBARD provides a way of visualizing multiple vector and scalar quantities as measured by many spacecraft at once. The data are displayed three-dimesionally along the orbits which may be displayed either as connected lines or as points. The data display allows the rapid determination of vector configurations, correlations between many measurements at multiple points, and global relationships. With the addition of magnetohydrodynamic (MHD) model data, this environment can also be used to validate simulation results with observed data, use simulated data to provide a global context for sparse observed data, and apply feature detection techniques to the simulated data.

Top partner-resonance interplay in a composite Higgs framework

NASA Astrophysics Data System (ADS)

Yepes, Juan; Zerwekh, Alfonso

2018-04-01

Guided us by the scenario of weak scale naturalness and the possible existence of exotic resonances, we have explored in a SO(5) Composite Higgs setup the interplay among three matter sectors: elementary, top partners and vector resonances. We parametrize it through explicit interactions of spin-1 SO(4)-resonances, coupled to the SO(5)-invariant fermionic currents and tensors presented in this work. Such invariants are built upon the Standard Model fermion sector as well as top partners sourced by the unbroken SO(4). The mass scales entailed by the top partner and vector resonance sectors will control the low energy effects emerging from our interplaying model. Its phenomenological impact and parameter spaces have been considered via flavor-dijet processes and electric dipole moments bounds. Finally, the strength of the Nambu-Goldstone symmetry breaking and the extra couplings implied by the top partner mass scales are measured in accordance with expected estimations.

Adaptive Hybrid Picture Coding. Volume 2.

DTIC Science & Technology

1985-02-01

ooo5 V.a Measurement Vector ..eho..............57 V.b Size Variable o .entroi* Vector .......... .- 59 V * c Shape Vector .Ř 0-60o oe 6 I V~d...the Program for the Adaptive Line of Sight Method .i.. 18.. o ... .... .... 1 B Details of the Feature Vector FormationProgram .. o ...oo..-....- .122 C ...shape recognition is analogous to recognition of curves in space. Therefore, well known concepts and theorems from differential geometry can be 34 . o

Vehicle Based Vector Sensor

DTIC Science & Technology

2015-09-28

buoyant underwater vehicle with an interior space in which a length of said underwater vehicle is equal to one tenth of the acoustic wavelength...underwater vehicle with an interior space in which a length of said underwater vehicle is equal to one tenth of the acoustic wavelength; an...unmanned underwater vehicle that can function as an acoustic vector sensor. (2) Description of the Prior Art [0004] It is known that a propagating

Representation of magnetic fields in space. [special attention to Geomagnetic fields and Magnetospheric models

NASA Technical Reports Server (NTRS)

Stern, D. P.

1976-01-01

Several mathematical methods which are available for the description of magnetic fields in space are reviewed. Examples of the application of such methods are given, with particular emphasis on work related to the geomagnetic field, and their individual properties and associated problems are described. The methods are grouped in five main classes: (1) methods based on the current density, (2) methods using the scalar magnetic potential, (3) toroidal and poloidal components of the field and spherical vector harmonics, (4) Euler potentials, and (5) local expansions of the field near a given reference point. Special attention is devoted to models of the magnetosphere, to the uniqueness of the scalar potential as derived from observed data, and to the L parameter.

Current algebra, statistical mechanics and quantum models

NASA Astrophysics Data System (ADS)

Vilela Mendes, R.

2017-11-01

Results obtained in the past for free boson systems at zero and nonzero temperatures are revisited to clarify the physical meaning of current algebra reducible functionals which are associated to systems with density fluctuations, leading to observable effects on phase transitions. To use current algebra as a tool for the formulation of quantum statistical mechanics amounts to the construction of unitary representations of diffeomorphism groups. Two mathematical equivalent procedures exist for this purpose. One searches for quasi-invariant measures on configuration spaces, the other for a cyclic vector in Hilbert space. Here, one argues that the second approach is closer to the physical intuition when modelling complex systems. An example of application of the current algebra methodology to the pairing phenomenon in two-dimensional fermion systems is discussed.

Bluetongue virus spread in Europe is a consequence of climatic, landscape and vertebrate host factors as revealed by phylogeographic inference

PubMed Central

Palmarini, Massimo; Mertens, Peter

2017-01-01

Spatio-temporal patterns of the spread of infectious diseases are commonly driven by environmental and ecological factors. This is particularly true for vector-borne diseases because vector populations can be strongly affected by host distribution as well as by climatic and landscape variables. Here, we aim to identify environmental drivers for bluetongue virus (BTV), the causative agent of a major vector-borne disease of ruminants that has emerged multiple times in Europe in recent decades. In order to determine the importance of climatic, landscape and host-related factors affecting BTV diffusion across Europe, we fitted different phylogeographic models to a dataset of 113 time-stamped and geo-referenced BTV genomes, representing multiple strains and serotypes. Diffusion models using continuous space revealed that terrestrial habitat below 300 m altitude, wind direction and higher livestock densities were associated with faster BTV movement. Results of discrete phylogeographic analysis involving generalized linear models broadly supported these findings, but varied considerably with the level of spatial partitioning. Contrary to common perception, we found no evidence for average temperature having a positive effect on BTV diffusion, though both methodological and biological reasons could be responsible for this result. Our study provides important insights into the drivers of BTV transmission at the landscape scale that could inform predictive models of viral spread and have implications for designing control strategies. PMID:29021180

A geometric approach to problems in birational geometry.

PubMed

Chi, Chen-Yu; Yau, Shing-Tung

2008-12-02

A classical set of birational invariants of a variety are its spaces of pluricanonical forms and some of their canonically defined subspaces. Each of these vector spaces admits a typical metric structure which is also birationally invariant. These vector spaces so metrized will be referred to as the pseudonormed spaces of the original varieties. A fundamental question is the following: Given two mildly singular projective varieties with some of the first variety's pseudonormed spaces being isometric to the corresponding ones of the second variety's, can one construct a birational map between them that induces these isometries? In this work, a positive answer to this question is given for varieties of general type. This can be thought of as a theorem of Torelli type for birational equivalence.

The next 25 years: Industrialization of space - Rationale for planning

NASA Technical Reports Server (NTRS)

Von Puttkamer, J.

1977-01-01

A methodology for planning the industralization of space is discussed. The suggested approach combines the extrapolative ('push') approach, in which alternative futures are projected on the basis of past and current trends and tendencies, with the normative ('pull') view, in which an ideal state in the far future is postulated and policies and decisions are directed toward its attainment. Time-reversed vectors of the future are tied to extrapolated, trend-oriented vectors of the quasi-present to identify common plateaus or stepping stones in technological development. Important steps in the industrialization of space to attain the short-range goals of production of space-derived energy, goods and services and the long-range goal of space colonization are discussed.

Support Vector Data Description Model to Map Specific Land Cover with Optimal Parameters Determined from a Window-Based Validation Set.

PubMed

Zhang, Jinshui; Yuan, Zhoumiqi; Shuai, Guanyuan; Pan, Yaozhong; Zhu, Xiufang

2017-04-26

This paper developed an approach, the window-based validation set for support vector data description (WVS-SVDD), to determine optimal parameters for support vector data description (SVDD) model to map specific land cover by integrating training and window-based validation sets. Compared to the conventional approach where the validation set included target and outlier pixels selected visually and randomly, the validation set derived from WVS-SVDD constructed a tightened hypersphere because of the compact constraint by the outlier pixels which were located neighboring to the target class in the spectral feature space. The overall accuracies for wheat and bare land achieved were as high as 89.25% and 83.65%, respectively. However, target class was underestimated because the validation set covers only a small fraction of the heterogeneous spectra of the target class. The different window sizes were then tested to acquire more wheat pixels for validation set. The results showed that classification accuracy increased with the increasing window size and the overall accuracies were higher than 88% at all window size scales. Moreover, WVS-SVDD showed much less sensitivity to the untrained classes than the multi-class support vector machine (SVM) method. Therefore, the developed method showed its merits using the optimal parameters, tradeoff coefficient ( C ) and kernel width ( s ), in mapping homogeneous specific land cover.

Spatio-temporal patterns of distribution of West Nile virus vectors in eastern Piedmont Region, Italy

PubMed Central

2011-01-01

Background West Nile Virus (WNV) transmission in Italy was first reported in 1998 as an equine outbreak near the swamps of Padule di Fucecchio, Tuscany. No other cases were identified during the following decade until 2008, when horse and human outbreaks were reported in Emilia Romagna, North Italy. Since then, WNV outbreaks have occurred annually, spreading from their initial northern foci throughout the country. Following the outbreak in 1998 the Italian public health authority defined a surveillance plan to detect WNV circulation in birds, horses and mosquitoes. By applying spatial statistical analysis (spatial point pattern analysis) and models (Bayesian GLMM models) to a longitudinal dataset on the abundance of the three putative WNV vectors [Ochlerotatus caspius (Pallas 1771), Culex pipiens (Linnaeus 1758) and Culex modestus (Ficalbi 1890)] in eastern Piedmont, we quantified their abundance and distribution in space and time and generated prediction maps outlining the areas with the highest vector productivity and potential for WNV introduction and amplification. Results The highest abundance and significant spatial clusters of Oc. caspius and Cx. modestus were in proximity to rice fields, and for Cx. pipiens, in proximity to highly populated urban areas. The GLMM model showed the importance of weather conditions and environmental factors in predicting mosquito abundance. Distance from the preferential breeding sites and elevation were negatively associated with the number of collected mosquitoes. The Normalized Difference Vegetation Index (NDVI) was positively correlated with mosquito abundance in rice fields (Oc. caspius and Cx. modestus). Based on the best models, we developed prediction maps for the year 2010 outlining the areas where high abundance of vectors could favour the introduction and amplification of WNV. Conclusions Our findings provide useful information for surveillance activities aiming to identify locations where the potential for WNV introduction and local transmission are highest. Such information can be used by vector control offices to stratify control interventions in areas prone to the invasion of WNV and other mosquito-transmitted pathogens. PMID:22152822

Spatio-temporal patterns of distribution of West Nile virus vectors in eastern Piedmont Region, Italy.

PubMed

Bisanzio, Donal; Giacobini, Mario; Bertolotti, Luigi; Mosca, Andrea; Balbo, Luca; Kitron, Uriel; Vazquez-Prokopec, Gonzalo M

2011-12-09

West Nile Virus (WNV) transmission in Italy was first reported in 1998 as an equine outbreak near the swamps of Padule di Fucecchio, Tuscany. No other cases were identified during the following decade until 2008, when horse and human outbreaks were reported in Emilia Romagna, North Italy. Since then, WNV outbreaks have occurred annually, spreading from their initial northern foci throughout the country. Following the outbreak in 1998 the Italian public health authority defined a surveillance plan to detect WNV circulation in birds, horses and mosquitoes. By applying spatial statistical analysis (spatial point pattern analysis) and models (Bayesian GLMM models) to a longitudinal dataset on the abundance of the three putative WNV vectors [Ochlerotatus caspius (Pallas 1771), Culex pipiens (Linnaeus 1758) and Culex modestus (Ficalbi 1890)] in eastern Piedmont, we quantified their abundance and distribution in space and time and generated prediction maps outlining the areas with the highest vector productivity and potential for WNV introduction and amplification. The highest abundance and significant spatial clusters of Oc. caspius and Cx. modestus were in proximity to rice fields, and for Cx. pipiens, in proximity to highly populated urban areas. The GLMM model showed the importance of weather conditions and environmental factors in predicting mosquito abundance. Distance from the preferential breeding sites and elevation were negatively associated with the number of collected mosquitoes. The Normalized Difference Vegetation Index (NDVI) was positively correlated with mosquito abundance in rice fields (Oc. caspius and Cx. modestus). Based on the best models, we developed prediction maps for the year 2010 outlining the areas where high abundance of vectors could favour the introduction and amplification of WNV. Our findings provide useful information for surveillance activities aiming to identify locations where the potential for WNV introduction and local transmission are highest. Such information can be used by vector control offices to stratify control interventions in areas prone to the invasion of WNV and other mosquito-transmitted pathogens.

Comparison Analysis of Recognition Algorithms of Forest-Cover Objects on Hyperspectral Air-Borne and Space-Borne Images

NASA Astrophysics Data System (ADS)

Kozoderov, V. V.; Kondranin, T. V.; Dmitriev, E. V.

2017-12-01

The basic model for the recognition of natural and anthropogenic objects using their spectral and textural features is described in the problem of hyperspectral air-borne and space-borne imagery processing. The model is based on improvements of the Bayesian classifier that is a computational procedure of statistical decision making in machine-learning methods of pattern recognition. The principal component method is implemented to decompose the hyperspectral measurements on the basis of empirical orthogonal functions. Application examples are shown of various modifications of the Bayesian classifier and Support Vector Machine method. Examples are provided of comparing these classifiers and a metrical classifier that operates on finding the minimal Euclidean distance between different points and sets in the multidimensional feature space. A comparison is also carried out with the " K-weighted neighbors" method that is close to the nonparametric Bayesian classifier.

Killing-Yano tensors in spaces admitting a hypersurface orthogonal Killing vector

NASA Astrophysics Data System (ADS)

Garfinkle, David; Glass, E. N.

2013-03-01

Methods are presented for finding Killing-Yano tensors, conformal Killing-Yano tensors, and conformal Killing vectors in spacetimes with a hypersurface orthogonal Killing vector. These methods are similar to a method developed by the authors for finding Killing tensors. In all cases one decomposes both the tensor and the equation it satisfies into pieces along the Killing vector and pieces orthogonal to the Killing vector. Solving the separate equations that result from this decomposition requires less computing than integrating the original equation. In each case, examples are given to illustrate the method.

Embedding of multidimensional time-dependent observations.

PubMed

Barnard, J P; Aldrich, C; Gerber, M

2001-10-01

A method is proposed to reconstruct dynamic attractors by embedding of multivariate observations of dynamic nonlinear processes. The Takens embedding theory is combined with independent component analysis to transform the embedding into a vector space of linearly independent vectors (phase variables). The method is successfully tested against prediction of the unembedded state vector in two case studies of simulated chaotic processes.

Embedding of multidimensional time-dependent observations

NASA Astrophysics Data System (ADS)

Barnard, Jakobus P.; Aldrich, Chris; Gerber, Marius

2001-10-01

A method is proposed to reconstruct dynamic attractors by embedding of multivariate observations of dynamic nonlinear processes. The Takens embedding theory is combined with independent component analysis to transform the embedding into a vector space of linearly independent vectors (phase variables). The method is successfully tested against prediction of the unembedded state vector in two case studies of simulated chaotic processes.

Foundation Mathematics for the Physical Sciences

NASA Astrophysics Data System (ADS)

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

2011-03-01

1. Arithmetic and geometry; 2. Preliminary algebra; 3. Differential calculus; 4. Integral calculus; 5. Complex numbers and hyperbolic functions; 6. Series and limits; 7. Partial differentiation; 8. Multiple integrals; 9. Vector algebra; 10. Matrices and vector spaces; 11. Vector calculus; 12. Line, surface and volume integrals; 13. Laplace transforms; 14. Ordinary differential equations; 15. Elementary probability; Appendices; Index.

Student Solution Manual for Foundation Mathematics for the Physical Sciences

NASA Astrophysics Data System (ADS)

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

2011-03-01

1. Arithmetic and geometry; 2. Preliminary algebra; 3. Differential calculus; 4. Integral calculus; 5. Complex numbers and hyperbolic functions; 6. Series and limits; 7. Partial differentiation; 8. Multiple integrals; 9. Vector algebra; 10. Matrices and vector spaces; 11. Vector calculus; 12. Line, surface and volume integrals; 13. Laplace transforms; 14. Ordinary differential equations; 15. Elementary probability; Appendix.

The assisted prediction modelling frame with hybridisation and ensemble for business risk forecasting and an implementation

NASA Astrophysics Data System (ADS)

Li, Hui; Hong, Lu-Yao; Zhou, Qing; Yu, Hai-Jie

2015-08-01

The business failure of numerous companies results in financial crises. The high social costs associated with such crises have made people to search for effective tools for business risk prediction, among which, support vector machine is very effective. Several modelling means, including single-technique modelling, hybrid modelling, and ensemble modelling, have been suggested in forecasting business risk with support vector machine. However, existing literature seldom focuses on the general modelling frame for business risk prediction, and seldom investigates performance differences among different modelling means. We reviewed researches on forecasting business risk with support vector machine, proposed the general assisted prediction modelling frame with hybridisation and ensemble (APMF-WHAE), and finally, investigated the use of principal components analysis, support vector machine, random sampling, and group decision, under the general frame in forecasting business risk. Under the APMF-WHAE frame with support vector machine as the base predictive model, four specific predictive models were produced, namely, pure support vector machine, a hybrid support vector machine involved with principal components analysis, a support vector machine ensemble involved with random sampling and group decision, and an ensemble of hybrid support vector machine using group decision to integrate various hybrid support vector machines on variables produced from principle components analysis and samples from random sampling. The experimental results indicate that hybrid support vector machine and ensemble of hybrid support vector machines were able to produce dominating performance than pure support vector machine and support vector machine ensemble.

On the origin of Poincaré gauge gravity

NASA Astrophysics Data System (ADS)

Chkareuli, J. L.

2017-06-01

We argue that the origin of Poincaré gauge gravity (PGG) may be related to spontaneous violation of underlying spacetime symmetries involved and appearance of gauge fields as vector Goldstone bosons. 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 assumed to belong, respectively, to the adjoint (Aμij) and vector (eμi) representations of the starting global Lorentz symmetry. We propose that these prototype vector fields are covariantly constrained, Aμij Aijμ = ±MA2 and eμi eiμ = ±Me2 , that causes a spontaneous violation of the accompanying global symmetries (MA,e are their presumed violation scales). It then follows that 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.

[HSV-1 based vector mediated IL-1Rα gene for knee osteoarthritis in rabbits].

PubMed

Wu, Yi; Li, Jianming; Kong, Ying; Chen, Ding; Liu, Bo; Wang, Wanchun

2013-06-01

To investigate the effect and mechanism of herpes simplex virus type 1 (HSV-1) based vector mediated interlukin-1 receptor antagonist (IL-1Rα) gene for knee osteoarthritis in rabbits. HSV-1 vectors containing IL-1Rα genes were constructed and injected into the joint space of the osteoarthritis knee in rabbits for 4 weeks. The rabbits were sacrificed, and the knees were lavaged, dissected and the effect of transgene expression was analyzed. Levels of IL-1Rα and IL-1 expression in the recovered lavage fluids were measured with a cytokine ELISA kit. Cartilage from the lesion areas of medial femoral condyle and synovium were observed with hematoxylin and eosin (cartilage and synovium) and toluidine blue (cartilage). The blank control group was injected pHSV-LacZ vector into rabbit knees. Intra-articular delivery of pHSV-IL-1Rα-LacZ resulted in a significant inhibition of IL-1 level and cartilage degradation compared with those in the blank control group (P<0.05). pHSV-LacZ is an ideal vector to mediate intra-articular gene delivery in the rabbit model of osteoarthritis. Continuous intra-articular expression of IL-1Rα can treat knee osteoarthritis by inhibiting IL-1.

Lorentz symmetric n-particle systems without ``multiple times''

NASA Astrophysics Data System (ADS)

Smith, Felix

2013-05-01

The need for multiple times in relativistic n-particle dynamics is a consequence of Minkowski's postulated symmetry between space and time coordinates in a space-time s = [x1 , . . ,x4 ] = [ x , y , z , ict ] , Eq. (1). Poincaré doubted the need for this space-time symmetry, believing Lorentz covariance could also prevail in some geometries with a three-dimensional position space and a quite different time coordinate. The Hubble expansion observed later justifies a specific geometry of this kind, a negatively curved position 3-space expanding with time at the Hubble rate lH (t) =lH , 0 + cΔt (F. T. Smith, Ann. Fond. L. de Broglie, 30, 179 (2005) and 35, 395 (2010)). Its position 4-vector is not s but q = [x1 , . . ,x4 ] = [ x , y , z , ilH (t) ] , and shows no 4-space symmetry. What is observed is always a difference 4-vector Δq = [ Δx , Δy , Δz , icΔt ] , and this displays the structure of Eq. (1) perfectly. Thus we find the standard 4-vector of special relativity in a geometry that does not require a Minkowski space-time at all, but a quite different geometry with a expanding 3-space symmetry and an independent time. The same Lorentz symmetry with but a single time extends to 2 and n-body systems.

Fast metabolite identification with Input Output Kernel Regression.

PubMed

Brouard, Céline; Shen, Huibin; Dührkop, Kai; d'Alché-Buc, Florence; Böcker, Sebastian; Rousu, Juho

2016-06-15

An important problematic of metabolomics is to identify metabolites using tandem mass spectrometry data. Machine learning methods have been proposed recently to solve this problem by predicting molecular fingerprint vectors and matching these fingerprints against existing molecular structure databases. In this work we propose to address the metabolite identification problem using a structured output prediction approach. This type of approach is not limited to vector output space and can handle structured output space such as the molecule space. We use the Input Output Kernel Regression method to learn the mapping between tandem mass spectra and molecular structures. The principle of this method is to encode the similarities in the input (spectra) space and the similarities in the output (molecule) space using two kernel functions. This method approximates the spectra-molecule mapping in two phases. The first phase corresponds to a regression problem from the input space to the feature space associated to the output kernel. The second phase is a preimage problem, consisting in mapping back the predicted output feature vectors to the molecule space. We show that our approach achieves state-of-the-art accuracy in metabolite identification. Moreover, our method has the advantage of decreasing the running times for the training step and the test step by several orders of magnitude over the preceding methods. celine.brouard@aalto.fi Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Fast metabolite identification with Input Output Kernel Regression

PubMed Central

Brouard, Céline; Shen, Huibin; Dührkop, Kai; d'Alché-Buc, Florence; Böcker, Sebastian; Rousu, Juho

2016-01-01

Motivation: An important problematic of metabolomics is to identify metabolites using tandem mass spectrometry data. Machine learning methods have been proposed recently to solve this problem by predicting molecular fingerprint vectors and matching these fingerprints against existing molecular structure databases. In this work we propose to address the metabolite identification problem using a structured output prediction approach. This type of approach is not limited to vector output space and can handle structured output space such as the molecule space. Results: We use the Input Output Kernel Regression method to learn the mapping between tandem mass spectra and molecular structures. The principle of this method is to encode the similarities in the input (spectra) space and the similarities in the output (molecule) space using two kernel functions. This method approximates the spectra-molecule mapping in two phases. The first phase corresponds to a regression problem from the input space to the feature space associated to the output kernel. The second phase is a preimage problem, consisting in mapping back the predicted output feature vectors to the molecule space. We show that our approach achieves state-of-the-art accuracy in metabolite identification. Moreover, our method has the advantage of decreasing the running times for the training step and the test step by several orders of magnitude over the preceding methods. Availability and implementation: Contact: celine.brouard@aalto.fi Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307628

Definition of Linear Color Models in the RGB Vector Color Space to Detect Red Peaches in Orchard Images Taken under Natural Illumination

PubMed Central

Teixidó, Mercè; Font, Davinia; Pallejà, Tomàs; Tresanchez, Marcel; Nogués, Miquel; Palacín, Jordi

2012-01-01

This work proposes the detection of red peaches in orchard images based on the definition of different linear color models in the RGB vector color space. The classification and segmentation of the pixels of the image is then performed by comparing the color distance from each pixel to the different previously defined linear color models. The methodology proposed has been tested with images obtained in a real orchard under natural light. The peach variety in the orchard was the paraguayo (Prunus persica var. platycarpa) peach with red skin. The segmentation results showed that the area of the red peaches in the images was detected with an average error of 11.6%; 19.7% in the case of bright illumination; 8.2% in the case of low illumination; 8.6% for occlusion up to 33%; 12.2% in the case of occlusion between 34 and 66%; and 23% for occlusion above 66%. Finally, a methodology was proposed to estimate the diameter of the fruits based on an ellipsoidal fitting. A first diameter was obtained by using all the contour pixels and a second diameter was obtained by rejecting some pixels of the contour. This approach enables a rough estimate of the fruit occlusion percentage range by comparing the two diameter estimates. PMID:22969369

Convective Heat Transfer in the Reusable Solid Rocket Motor of the Space Transportation System

NASA Technical Reports Server (NTRS)

Ahmad, Rashid A.; Cash, Stephen F. (Technical Monitor)

2002-01-01

This simulation involved a two-dimensional axisymmetric model of a full motor initial grain of the Reusable Solid Rocket Motor (RSRM) of the Space Transportation System (STS). It was conducted with CFD (computational fluid dynamics) commercial code FLUENT. This analysis was performed to: a) maintain continuity with most related previous analyses, b) serve as a non-vectored baseline for any three-dimensional vectored nozzles, c) provide a relatively simple application and checkout for various CFD solution schemes, grid sensitivity studies, turbulence modeling and heat transfer, and d) calculate nozzle convective heat transfer coefficients. The accuracy of the present results and the selection of the numerical schemes and turbulence models were based on matching the rocket ballistic predictions of mass flow rate, head end pressure, vacuum thrust and specific impulse, and measured chamber pressure drop. Matching these ballistic predictions was found to be good. This study was limited to convective heat transfer and the results compared favorably with existing theory. On the other hand, qualitative comparison with backed-out data of the ratio of the convective heat transfer coefficient to the specific heat at constant pressure was made in a relative manner. This backed-out data was devised to match nozzle erosion that was a result of heat transfer (convective, radiative and conductive), chemical (transpirating), and mechanical (shear and particle impingement forces) effects combined.

Definition of linear color models in the RGB vector color space to detect red peaches in orchard images taken under natural illumination.

PubMed

Teixidó, Mercè; Font, Davinia; Pallejà, Tomàs; Tresanchez, Marcel; Nogués, Miquel; Palacín, Jordi

2012-01-01

This work proposes the detection of red peaches in orchard images based on the definition of different linear color models in the RGB vector color space. The classification and segmentation of the pixels of the image is then performed by comparing the color distance from each pixel to the different previously defined linear color models. The methodology proposed has been tested with images obtained in a real orchard under natural light. The peach variety in the orchard was the paraguayo (Prunus persica var. platycarpa) peach with red skin. The segmentation results showed that the area of the red peaches in the images was detected with an average error of 11.6%; 19.7% in the case of bright illumination; 8.2% in the case of low illumination; 8.6% for occlusion up to 33%; 12.2% in the case of occlusion between 34 and 66%; and 23% for occlusion above 66%. Finally, a methodology was proposed to estimate the diameter of the fruits based on an ellipsoidal fitting. A first diameter was obtained by using all the contour pixels and a second diameter was obtained by rejecting some pixels of the contour. This approach enables a rough estimate of the fruit occlusion percentage range by comparing the two diameter estimates.

Section sigma models coupled to symplectic duality bundles on Lorentzian four-manifolds

NASA Astrophysics Data System (ADS)

Lazaroiu, C. I.; Shahbazi, C. S.

2018-06-01

We give the global mathematical formulation of a class of generalized four-dimensional theories of gravity coupled to scalar matter and to Abelian gauge fields. In such theories, the scalar fields are described by a section of a surjective pseudo-Riemannian submersion π over space-time, whose total space carries a Lorentzian metric making the fibers into totally-geodesic connected Riemannian submanifolds. In particular, π is a fiber bundle endowed with a complete Ehresmann connection whose transport acts through isometries between the fibers. In turn, the Abelian gauge fields are "twisted" by a flat symplectic vector bundle defined over the total space of π. This vector bundle is endowed with a vertical taming which locally encodes the gauge couplings and theta angles of the theory and gives rise to the notion of twisted self-duality, of crucial importance to construct the theory. When the Ehresmann connection of π is integrable, we show that our theories are locally equivalent to ordinary Einstein-Scalar-Maxwell theories and hence provide a global non-trivial extension of the universal bosonic sector of four-dimensional supergravity. In this case, we show using a special trivializing atlas of π that global solutions of such models can be interpreted as classical "locally-geometric" U-folds. In the non-integrable case, our theories differ locally from ordinary Einstein-Scalar-Maxwell theories and may provide a geometric description of classical U-folds which are "locally non-geometric".

A link between torse-forming vector fields and rotational hypersurfaces

NASA Astrophysics Data System (ADS)

Chen, Bang-Yen; Verstraelen, Leopold

Torse-forming vector fields introduced by Yano [On torse forming direction in a Riemannian space, Proc. Imp. Acad. Tokyo 20 (1944) 340-346] are natural extension of concurrent and concircular vector fields. Such vector fields have many nice applications to geometry and mathematical physics. In this paper, we establish a link between rotational hypersurfaces and torse-forming vector fields. More precisely, our main result states that, for a hypersurface M of 𝔼n+1 with n ≥ 3, the tangential component xT of the position vector field of M is a proper torse-forming vector field on M if and only if M is contained in a rotational hypersurface whose axis of rotation contains the origin.

The combined geodetic network adjusted on the reference ellipsoid - a comparison of three functional models for GNSS observations

NASA Astrophysics Data System (ADS)

Kadaj, Roman

2016-12-01

The adjustment problem of the so-called combined (hybrid, integrated) network created with GNSS vectors and terrestrial observations has been the subject of many theoretical and applied works. The network adjustment in various mathematical spaces was considered: in the Cartesian geocentric system on a reference ellipsoid and on a mapping plane. For practical reasons, it often takes a geodetic coordinate system associated with the reference ellipsoid. In this case, the Cartesian GNSS vectors are converted, for example, into geodesic parameters (azimuth and length) on the ellipsoid, but the simple form of converted pseudo-observations are the direct differences of the geodetic coordinates. Unfortunately, such an approach may be essentially distorted by a systematic error resulting from the position error of the GNSS vector, before its projection on the ellipsoid surface. In this paper, an analysis of the impact of this error on the determined measures of geometric ellipsoid elements, including the differences of geodetic coordinates or geodesic parameters is presented. Assuming that the adjustment of a combined network on the ellipsoid shows that the optimal functional approach in relation to the satellite observation, is to create the observational equations directly for the original GNSS Cartesian vector components, writing them directly as a function of the geodetic coordinates (in numerical applications, we use the linearized forms of observational equations with explicitly specified coefficients). While retaining the original character of the Cartesian vector, one avoids any systematic errors that may occur in the conversion of the original GNSS vectors to ellipsoid elements, for example the vector of the geodesic parameters. The problem is theoretically developed and numerically tested. An example of the adjustment of a subnet loaded from the database of reference stations of the ASG-EUPOS system was considered for the preferred functional model of the GNSS observations.

Mining patterns in persistent surveillance systems with smart query and visual analytics

NASA Astrophysics Data System (ADS)

Habibi, Mohammad S.; Shirkhodaie, Amir

2013-05-01

In Persistent Surveillance Systems (PSS) the ability to detect and characterize events geospatially help take pre-emptive steps to counter adversary's actions. Interactive Visual Analytic (VA) model offers this platform for pattern investigation and reasoning to comprehend and/or predict such occurrences. The need for identifying and offsetting these threats requires collecting information from diverse sources, which brings with it increasingly abstract data. These abstract semantic data have a degree of inherent uncertainty and imprecision, and require a method for their filtration before being processed further. In this paper, we have introduced an approach based on Vector Space Modeling (VSM) technique for classification of spatiotemporal sequential patterns of group activities. The feature vectors consist of an array of attributes extracted from generated sensors semantic annotated messages. To facilitate proper similarity matching and detection of time-varying spatiotemporal patterns, a Temporal-Dynamic Time Warping (DTW) method with Gaussian Mixture Model (GMM) for Expectation Maximization (EM) is introduced. DTW is intended for detection of event patterns from neighborhood-proximity semantic frames derived from established ontology. GMM with EM, on the other hand, is employed as a Bayesian probabilistic model to estimated probability of events associated with a detected spatiotemporal pattern. In this paper, we present a new visual analytic tool for testing and evaluation group activities detected under this control scheme. Experimental results demonstrate the effectiveness of proposed approach for discovery and matching of subsequences within sequentially generated patterns space of our experiments.

Comparing success levels of different neural network structures in extracting discriminative information from the response patterns of a temperature-modulated resistive gas sensor

NASA Astrophysics Data System (ADS)

Hosseini-Golgoo, S. M.; Bozorgi, H.; Saberkari, A.

2015-06-01

Performances of three neural networks, consisting of a multi-layer perceptron, a radial basis function, and a neuro-fuzzy network with local linear model tree training algorithm, in modeling and extracting discriminative features from the response patterns of a temperature-modulated resistive gas sensor are quantitatively compared. For response pattern recording, a voltage staircase containing five steps each with a 20 s plateau is applied to the micro-heater of the sensor, when 12 different target gases, each at 11 concentration levels, are present. In each test, the hidden layer neuron weights are taken as the discriminatory feature vector of the target gas. These vectors are then mapped to a 3D feature space using linear discriminant analysis. The discriminative information content of the feature vectors are determined by the calculation of the Fisher’s discriminant ratio, affording quantitative comparison among the success rates achieved by the different neural network structures. The results demonstrate a superior discrimination ratio for features extracted from local linear neuro-fuzzy and radial-basis-function networks with recognition rates of 96.27% and 90.74%, respectively.

Characterizing dark matter interacting with extra charged leptons

NASA Astrophysics Data System (ADS)

Barducci, D.; Deandrea, A.; Moretti, S.; Panizzi, L.; Prager, H.

2018-04-01

In the context of a simplified leptophilic dark matter (DM) scenario where the mediator is a new charged fermion carrying leptonic quantum number and the DM candidate is either scalar or vector, the complementarity of different bounds is analyzed. In this framework, the extra lepton and DM are odd under a Z2 symmetry, and hence the leptonic mediator can only interact with the DM state and Standard Model leptons of various flavors. We show that there is the possibility to characterize the DM spin (scalar or vector), as well as the nature of the mediator, through a combined analysis of cosmological, flavor and collider data. We present an explicit numerical analysis for a set of benchmarks points of the viable parameter space of our scenario.

Flow of Combustion Products Containing Condensed-Phase Particles over a Recessed Vectorable Jet Nozzle

NASA Astrophysics Data System (ADS)

Volkov, K. N.; Denisikhin, S. V.; Emel'yanov, V. N.; Teterina, I. V.

2017-09-01

The flow of combustion products containing condensed-phase particles over the recessed vectorable nozzle of a solid-propellant rocket motor was investigated with the use of the Reynolds-averaged Navier-Stokes equations, equations of the k-ɛ model of turbulence, and the Lagrange approach. The fields of flows of combustion products and the mechanical trajectories of condensed-phase particles in the charge channel, the prenozzle space, and the nozzle unit of this motor were calculated for different angles of swing of the nozzle. The formation of vortices in the gas flow in the neighborhood of the downstream cover of the nozzle and their influence on the movement of particles different in size were considered.

The canonical Lagrangian approach to three-space general relativity

NASA Astrophysics Data System (ADS)

Shyam, Vasudev; Venkatesh, Madhavan

2013-07-01

We study the action for the three-space formalism of general relativity, better known as the Barbour-Foster-Ó Murchadha action, which is a square-root Baierlein-Sharp-Wheeler action. In particular, we explore the (pre)symplectic structure by pulling it back via a Legendre map to the tangent bundle of the configuration space of this action. With it we attain the canonical Lagrangian vector field which generates the gauge transformations (3-diffeomorphisms) and the true physical evolution of the system. This vector field encapsulates all the dynamics of the system. We also discuss briefly the observables and perennials for this theory. We then present a symplectic reduction of the constrained phase space.

Vector Magnetograph Design

NASA Technical Reports Server (NTRS)

Chipman, Russell A.

1996-01-01

This report covers work performed during the period of November 1994 through March 1996 on the design of a Space-borne Solar Vector Magnetograph. This work has been performed as part of a design team under the supervision of Dr. Mona Hagyard and Dr. Alan Gary of the Space Science Laboratory. Many tasks were performed and this report documents the results from some of those tasks, each contained in the corresponding appendix. Appendices are organized in chronological order.

Realistic Covariance Prediction for the Earth Science Constellation

NASA Technical Reports Server (NTRS)

Duncan, Matthew; Long, Anne

2006-01-01

Routine satellite operations for the Earth Science Constellation (ESC) include collision risk assessment between members of the constellation and other orbiting space objects. One component of the risk assessment process is computing the collision probability between two space objects. The collision probability is computed using Monte Carlo techniques as well as by numerically integrating relative state probability density functions. Each algorithm takes as inputs state vector and state vector uncertainty information for both objects. The state vector uncertainty information is expressed in terms of a covariance matrix. The collision probability computation is only as good as the inputs. Therefore, to obtain a collision calculation that is a useful decision-making metric, realistic covariance matrices must be used as inputs to the calculation. This paper describes the process used by the NASA/Goddard Space Flight Center's Earth Science Mission Operations Project to generate realistic covariance predictions for three of the Earth Science Constellation satellites: Aqua, Aura and Terra.

Laplace-Runge-Lenz vector in quantum mechanics in noncommutative space

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

Gáliková, Veronika; Kováčik, Samuel; Prešnajder, Peter

2013-12-15

The main point of this paper is to examine a “hidden” dynamical symmetry connected with the conservation of Laplace-Runge-Lenz vector (LRL) in the hydrogen atom problem solved by means of non-commutative quantum mechanics (NCQM). The basic features of NCQM will be introduced to the reader, the key one being the fact that the notion of a point, or a zero distance in the considered configuration space, is abandoned and replaced with a “fuzzy” structure in such a way that the rotational invariance is preserved. The main facts about the conservation of LRL vector in both classical and quantum theory willmore » be reviewed. Finally, we will search for an analogy in the NCQM, provide our results and their comparison with the QM predictions. The key notions we are going to deal with are non-commutative space, Coulomb-Kepler problem, and symmetry.« less

Adjustable vector Airy light-sheet single optical tweezers: negative radiation forces on a subwavelength spheroid and spin torque reversal

NASA Astrophysics Data System (ADS)

Mitri, Farid G.

2018-01-01

Generalized solutions of vector Airy light-sheets, adjustable per their derivative order m, are introduced stemming from the Lorenz gauge condition and Maxwell's equations using the angular spectrum decomposition method. The Cartesian components of the incident radiated electric, magnetic and time-averaged Poynting vector fields in free space (excluding evanescent waves) are determined and computed with particular emphasis on the derivative order of the Airy light-sheet and the polarization on the magnetic vector potential forming the beam. Negative transverse time-averaged Poynting vector components can arise, while the longitudinal counterparts are always positive. Moreover, the analysis is extended to compute the optical radiation force and spin torque vector components on a lossless dielectric prolate subwavelength spheroid in the framework of the electric dipole approximation. The results show that negative forces and spin torques sign reversal arise depending on the derivative order of the beam, the polarization of the magnetic vector potential, and the orientation of the subwavelength prolate spheroid in space. The spin torque sign reversal suggests that counter-clockwise or clockwise rotations around the center of mass of the subwavelength spheroid can occur. The results find useful applications in single Airy light-sheet tweezers, particle manipulation, handling, and rotation applications to name a few examples.

Distance between RBS and AUG plays an important role in overexpression of recombinant proteins.

PubMed

Berwal, Sunil K; Sreejith, R K; Pal, Jayanta K

2010-10-15

The spacing between ribosome binding site (RBS) and AUG is crucial for efficient overexpression of genes when cloned in prokaryotic expression vectors. We undertook a brief study on the overexpression of genes cloned in Escherichia coli expression vectors, wherein the spacing between the RBS and the start codon was varied. SDS-PAGE and Western blot analysis indicated a high level of protein expression only in constructs where the spacing between RBS and AUG was approximately 40 nucleotides or more, despite the synthesis of the transcripts in the representative cases investigated. Copyright 2010 Elsevier Inc. All rights reserved.

Fractional Snow Cover Mapping by Artificial Neural Networks and Support Vector Machines

NASA Astrophysics Data System (ADS)

Çiftçi, B. B.; Kuter, S.; Akyürek, Z.; Weber, G.-W.

2017-11-01

Snow is an important land cover whose distribution over space and time plays a significant role in various environmental processes. Hence, snow cover mapping with high accuracy is necessary to have a real understanding for present and future climate, water cycle, and ecological changes. This study aims to investigate and compare the design and use of artificial neural networks (ANNs) and support vector machines (SVMs) algorithms for fractional snow cover (FSC) mapping from satellite data. ANN and SVM models with different model building settings are trained by using Moderate Resolution Imaging Spectroradiometer surface reflectance values of bands 1-7, normalized difference snow index and normalized difference vegetation index as predictor variables. Reference FSC maps are generated from higher spatial resolution Landsat ETM+ binary snow cover maps. Results on the independent test data set indicate that the developed ANN model with hyperbolic tangent transfer function in the output layer and the SVM model with radial basis function kernel produce high FSC mapping accuracies with the corresponding values of R = 0.93 and R = 0.92, respectively.

Ring polymer dynamics in curved spaces

NASA Astrophysics Data System (ADS)

Wolf, S.; Curotto, E.

2012-07-01

We formulate an extension of the ring polymer dynamics approach to curved spaces using stereographic projection coordinates. We test the theory by simulating the particle in a ring, {T}^1, mapped by a stereographic projection using three potentials. Two of these are quadratic, and one is a nonconfining sinusoidal model. We propose a new class of algorithms for the integration of the ring polymer Hamilton equations in curved spaces. These are designed to improve the energy conservation of symplectic integrators based on the split operator approach. For manifolds, the position-position autocorrelation function can be formulated in numerous ways. We find that the position-position autocorrelation function computed from configurations in the Euclidean space {R}^2 that contains {T}^1 as a submanifold has the best statistical properties. The agreement with exact results obtained with vector space methods is excellent for all three potentials, for all values of time in the interval simulated, and for a relatively broad range of temperatures.

Mayer control problem with probabilistic uncertainty on initial positions

NASA Astrophysics Data System (ADS)

Marigonda, Antonio; Quincampoix, Marc

2018-03-01

In this paper we introduce and study an optimal control problem in the Mayer's form in the space of probability measures on Rn endowed with the Wasserstein distance. Our aim is to study optimality conditions when the knowledge of the initial state and velocity is subject to some uncertainty, which are modeled by a probability measure on Rd and by a vector-valued measure on Rd, respectively. We provide a characterization of the value function of such a problem as unique solution of an Hamilton-Jacobi-Bellman equation in the space of measures in a suitable viscosity sense. Some applications to a pursuit-evasion game with uncertainty in the state space is also discussed, proving the existence of a value for the game.

Algebraic and radical potential fields. Stability domains in coordinate and parametric space

NASA Astrophysics Data System (ADS)

Uteshev, Alexei Yu.

2018-05-01

A dynamical system d X/d t = F(X; A) is treated where F(X; A) is a polynomial (or some general type of radical contained) function in the vectors of state variables X ∈ ℝn and parameters A ∈ ℝm. We are looking for stability domains in both spaces, i.e. (a) domain ℙ ⊂ ℝm such that for any parameter vector specialization A ∈ ℙ, there exists a stable equilibrium for the dynamical system, and (b) domain 𝕊 ⊂ ℝn such that any point X* ∈ 𝕊 could be made a stable equilibrium by a suitable specialization of the parameter vector A.

Vectorized Jiles-Atherton hysteresis model

NASA Astrophysics Data System (ADS)

Szymański, Grzegorz; Waszak, Michał

2004-01-01

This paper deals with vector hysteresis modeling. A vector model consisting of individual Jiles-Atherton components placed along principal axes is proposed. The cross-axis coupling ensures general vector model properties. Minor loops are obtained using scaling method. The model is intended for efficient finite element method computations defined in terms of magnetic vector potential. Numerical efficiency is ensured by differential susceptibility approach.

LAMDA at TREC CDS track 2015: Clinical Decision Support Track

DTIC Science & Technology

2015-11-20

outperforms all the other vector space models supported by Elasticsearch. MetaMap is the online tool that maps biomedical text to the Metathesaurus, and...cases. The medical knowledge consists of 700,000 biomedical documents supported by the PubMed Central [3] which is online digital database freely...Science Research Program through the National Research Foundation (NRF) of Korea funded by the Ministry of Science, ICT , and Future Planning (MSIP

Flight Dynamics Simulation Modeling and Control of a Large Flexible Tiltrotor Aircraft

DTIC Science & Technology

2014-09-01

matrix from fixed to rotating coordinate systems u longitudinal aircraft velocity, state-space control vector v elastic beam chordwise displacement /lateral...spectrum active control , including flight control systems, rotor load limiting, and vibration and noisetiltion [1]. The development of a high-order...the flutter response of fixed- wing aircraft. The B-52 CCV ( Controls Configured Vehicle) was one of the first aircraft to demonstrate benefits of active

Regularized estimation of Euler pole parameters

NASA Astrophysics Data System (ADS)

Aktuğ, Bahadir; Yildirim, Ömer

2013-07-01

Euler vectors provide a unified framework to quantify the relative or absolute motions of tectonic plates through various geodetic and geophysical observations. With the advent of space geodesy, Euler parameters of several relatively small plates have been determined through the velocities derived from the space geodesy observations. However, the available data are usually insufficient in number and quality to estimate both the Euler vector components and the Euler pole parameters reliably. Since Euler vectors are defined globally in an Earth-centered Cartesian frame, estimation with the limited geographic coverage of the local/regional geodetic networks usually results in highly correlated vector components. In the case of estimating the Euler pole parameters directly, the situation is even worse, and the position of the Euler pole is nearly collinear with the magnitude of the rotation rate. In this study, a new method, which consists of an analytical derivation of the covariance matrix of the Euler vector in an ideal network configuration, is introduced and a regularized estimation method specifically tailored for estimating the Euler vector is presented. The results show that the proposed method outperforms the least squares estimation in terms of the mean squared error.

Space Science

NASA Image and Video Library

1990-10-01

Using the Solar Vector Magnetograph, a solar observation facility at NASA's Marshall Space Flight Center (MSFC), scientists from the National Space Science and Technology Center (NSSTC) in Huntsville, Alabama, are monitoring the explosive potential of magnetic areas of the Sun. This effort could someday lead to better prediction of severe space weather, a phenomenon that occurs when blasts of particles and magnetic fields from the Sun impact the magnetosphere, the magnetic bubble around the Earth. When massive solar explosions, known as coronal mass ejections, blast through the Sun's outer atmosphere and plow toward Earth at speeds of thousands of miles per second, the resulting effects can be harmful to communication satellites and astronauts outside the Earth's magnetosphere. Like severe weather on Earth, severe space weather can be costly. On the ground, the magnetic storm wrought by these solar particles can knock out electric power. The researchers from MSFC and NSSTC's solar physics group develop instruments for measuring magnetic fields on the Sun. With these instruments, the group studies the origin, structure, and evolution of the solar magnetic field and the impact it has on Earth's space environment. This photograph shows the Solar Vector Magnetograph and Dr. Mona Hagyard of MSFC, the director of the observatory who leads the development, operation and research program of the Solar Vector Magnetograph.

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

SAMPEX science pointing with velocity avoidance. [solar anomalous and magnetospheric particle explorer

NASA Technical Reports Server (NTRS)

Frakes, Joseph P.; Henretty, Debra A.; Flatley, Thomas W.; Markley, F. L.; San, Josephine K.; Lightsey, E. G.

1992-01-01

The Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) science pointing mode is presented with the additional constraint of velocity avoidance. This constraint has been added in light of the orbital debris and micrometeoroid fluxes that have been revealed by the Long Duration Exposure Facility (LDEF) recovered in January 1990. These fluxes are 50-100 times higher than the flux tables that were used in the September 1988 proposal to NASA for the SAMPEX mission. The SAMPEX Heavey Ion Large Telescope (HILT) sensor includes a flow-through isobutane proportional counter that is susceptible to penetration by orbital debris and micrometeoroids. Thus, keeping the HILT sensor pointed away from the velocity vector, the direction of maximum flux, will compensate for the higher than expected fluxes. Using an orbital debris model and a micrometeoroid model developed at the Johnson Space Center (JSC), and a SAMPEX dynamic simulator developed by the Guidance and Control Branch at the Goddard Space Flight Center (GSFC), an 'optimal' minimum ram angle (the angle between the HILT boresight and the velocity vector) of 90 degrees has been determined. It is optimal in the sense of minimizing the science pointing performance degradation while providing approximately an 89 percent chance of survival for the HILT sensor over a three year period.

A short-term and high-resolution distribution system load forecasting approach using support vector regression with hybrid parameters optimization

DOE PAGES

Jiang, Huaiguang; Zhang, Yingchen; Muljadi, Eduard; ...

2016-01-01

This paper proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of themore » hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization (PSO) is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system. The performance of the proposed approach is compared to some classic methods in later sections of the paper.« less

Developing a local least-squares support vector machines-based neuro-fuzzy model for nonlinear and chaotic time series prediction.

PubMed

Miranian, A; Abdollahzade, M

2013-02-01

Local modeling approaches, owing to their ability to model different operating regimes of nonlinear systems and processes by independent local models, seem appealing for modeling, identification, and prediction applications. In this paper, we propose a local neuro-fuzzy (LNF) approach based on the least-squares support vector machines (LSSVMs). The proposed LNF approach employs LSSVMs, which are powerful in modeling and predicting time series, as local models and uses hierarchical binary tree (HBT) learning algorithm for fast and efficient estimation of its parameters. The HBT algorithm heuristically partitions the input space into smaller subdomains by axis-orthogonal splits. In each partitioning, the validity functions automatically form a unity partition and therefore normalization side effects, e.g., reactivation, are prevented. Integration of LSSVMs into the LNF network as local models, along with the HBT learning algorithm, yield a high-performance approach for modeling and prediction of complex nonlinear time series. The proposed approach is applied to modeling and predictions of different nonlinear and chaotic real-world and hand-designed systems and time series. Analysis of the prediction results and comparisons with recent and old studies demonstrate the promising performance of the proposed LNF approach with the HBT learning algorithm for modeling and prediction of nonlinear and chaotic systems and time series.

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.

Computing approximate random Delta v magnitude probability densities. [for spacecraft trajectory correction

NASA Technical Reports Server (NTRS)

Chadwick, C.

1984-01-01

This paper describes the development and use of an algorithm to compute approximate statistics of the magnitude of a single random trajectory correction maneuver (TCM) Delta v vector. The TCM Delta v vector is modeled as a three component Cartesian vector each of whose components is a random variable having a normal (Gaussian) distribution with zero mean and possibly unequal standard deviations. The algorithm uses these standard deviations as input to produce approximations to (1) the mean and standard deviation of the magnitude of Delta v, (2) points of the probability density function of the magnitude of Delta v, and (3) points of the cumulative and inverse cumulative distribution functions of Delta v. The approximates are based on Monte Carlo techniques developed in a previous paper by the author and extended here. The algorithm described is expected to be useful in both pre-flight planning and in-flight analysis of maneuver propellant requirements for space missions.

Current harmonics elimination control method for six-phase PM synchronous motor drives.

PubMed

Yuan, Lei; Chen, Ming-liang; Shen, Jian-qing; Xiao, Fei

2015-11-01

To reduce the undesired 5th and 7th stator harmonic current in the six-phase permanent magnet synchronous motor (PMSM), an improved vector control algorithm was proposed based on vector space decomposition (VSD) transformation method, which can control the fundamental and harmonic subspace separately. To improve the traditional VSD technology, a novel synchronous rotating coordinate transformation matrix was presented in this paper, and only using the traditional PI controller in d-q subspace can meet the non-static difference adjustment, the controller parameter design method is given by employing internal model principle. Moreover, the current PI controller parallel with resonant controller is employed in x-y subspace to realize the specific 5th and 7th harmonic component compensation. In addition, a new six-phase SVPWM algorithm based on VSD transformation theory is also proposed. Simulation and experimental results verify the effectiveness of current decoupling vector controller. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Some Applications Of Semigroups And Computer Algebra In Discrete Structures

NASA Astrophysics Data System (ADS)

Bijev, G.

2009-11-01

An algebraic approach to the pseudoinverse generalization problem in Boolean vector spaces is used. A map (p) is defined, which is similar to an orthogonal projection in linear vector spaces. Some other important maps with properties similar to those of the generalized inverses (pseudoinverses) of linear transformations and matrices corresponding to them are also defined and investigated. Let Ax = b be an equation with matrix A and vectors x and b Boolean. Stochastic experiments for solving the equation, which involves the maps defined and use computer algebra methods, have been made. As a result, the Hamming distance between vectors Ax = p(b) and b is equal or close to the least possible. We also share our experience in using computer algebra systems for teaching discrete mathematics and linear algebra and research. Some examples for computations with binary relations using Maple are given.

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.

A variational reconstruction method for undersampled dynamic x-ray tomography based on physical motion models

NASA Astrophysics Data System (ADS)

Burger, Martin; Dirks, Hendrik; Frerking, Lena; Hauptmann, Andreas; Helin, Tapio; Siltanen, Samuli

2017-12-01

In this paper we study the reconstruction of moving object densities from undersampled dynamic x-ray tomography in two dimensions. A particular motivation of this study is to use realistic measurement protocols for practical applications, i.e. we do not assume to have a full Radon transform in each time step, but only projections in few angular directions. This restriction enforces a space-time reconstruction, which we perform by incorporating physical motion models and regularization of motion vectors in a variational framework. The methodology of optical flow, which is one of the most common methods to estimate motion between two images, is utilized to formulate a joint variational model for reconstruction and motion estimation. We provide a basic mathematical analysis of the forward model and the variational model for the image reconstruction. Moreover, we discuss the efficient numerical minimization based on alternating minimizations between images and motion vectors. A variety of results are presented for simulated and real measurement data with different sampling strategy. A key observation is that random sampling combined with our model allows reconstructions of similar amount of measurements and quality as a single static reconstruction.

Applications of Aerodynamic Forces for Spacecraft Orbit Maneuverability in Operationally Responsive Space and Space Reconstitution Needs

DTIC Science & Technology

2012-03-01

observation re = the radius of the Earth at the equator Pn = the Legendre polynomial 26 L = the geocentric latitude, sin The acceleration can then...atmospheric density at an altitude above an %% oblate earth given the position vector in the Geocentric Equatorial %% frame. The position vector is in...Diff between Delta and Geocentric lat rad %% GeoDtLat - Geodetic Latitude -Pi/2 to Pi/2 rad %% GeoCnLat

Multidirectional Scanning Model, MUSCLE, to Vectorize Raster Images with Straight Lines

PubMed Central

Karas, Ismail Rakip; Bayram, Bulent; Batuk, Fatmagul; Akay, Abdullah Emin; Baz, Ibrahim

2008-01-01

This paper presents a new model, MUSCLE (Multidirectional Scanning for Line Extraction), for automatic vectorization of raster images with straight lines. The algorithm of the model implements the line thinning and the simple neighborhood methods to perform vectorization. The model allows users to define specified criteria which are crucial for acquiring the vectorization process. In this model, various raster images can be vectorized such as township plans, maps, architectural drawings, and machine plans. The algorithm of the model was developed by implementing an appropriate computer programming and tested on a basic application. Results, verified by using two well known vectorization programs (WinTopo and Scan2CAD), indicated that the model can successfully vectorize the specified raster data quickly and accurately. PMID:27879843

Multidirectional Scanning Model, MUSCLE, to Vectorize Raster Images with Straight Lines.

PubMed

Karas, Ismail Rakip; Bayram, Bulent; Batuk, Fatmagul; Akay, Abdullah Emin; Baz, Ibrahim

2008-04-15

This paper presents a new model, MUSCLE (Multidirectional Scanning for Line Extraction), for automatic vectorization of raster images with straight lines. The algorithm of the model implements the line thinning and the simple neighborhood methods to perform vectorization. The model allows users to define specified criteria which are crucial for acquiring the vectorization process. In this model, various raster images can be vectorized such as township plans, maps, architectural drawings, and machine plans. The algorithm of the model was developed by implementing an appropriate computer programming and tested on a basic application. Results, verified by using two well known vectorization programs (WinTopo and Scan2CAD), indicated that the model can successfully vectorize the specified raster data quickly and accurately.

Electroweak phase transition in the {mu}{nu}SSM

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

Chung, Daniel J. H.; School of Physics, Korea Institute for Advanced Study, 207-43, Cheongnyangni2-dong, Dongdaemun-gu, Seoul 130-722; Long, Andrew J.

2010-06-15

An extension of the minimal supersymmetric standard model called the {mu}{nu}SSM does not allow a conventional thermal leptogenesis scenario because of the low scale seesaw that it utilizes. Hence, we investigate the possibility of electroweak baryogenesis. Specifically, we identify a parameter region for which the electroweak phase transition is sufficiently strongly first order to realize electroweak baryogenesis. In addition to transitions that are similar to those in the next-to-minimal supersymmetric standard model, we find a novel class of phase transitions in which there is a rotation in the singlet vector space.

Vector autoregressive models: A Gini approach

NASA Astrophysics Data System (ADS)

Mussard, Stéphane; Ndiaye, Oumar Hamady

2018-02-01

In this paper, it is proven that the usual VAR models may be performed in the Gini sense, that is, on a ℓ1 metric space. The Gini regression is robust to outliers. As a consequence, when data are contaminated by extreme values, we show that semi-parametric VAR-Gini regressions may be used to obtain robust estimators. The inference about the estimators is made with the ℓ1 norm. Also, impulse response functions and Gini decompositions for prevision errors are introduced. Finally, Granger's causality tests are properly derived based on U-statistics.

Analysis models for the estimation of oceanic fields

NASA Technical Reports Server (NTRS)

Carter, E. F.; Robinson, A. R.

1987-01-01

A general model for statistically optimal estimates is presented for dealing with scalar, vector and multivariate datasets. The method deals with anisotropic fields and treats space and time dependence equivalently. Problems addressed include the analysis, or the production of synoptic time series of regularly gridded fields from irregular and gappy datasets, and the estimate of fields by compositing observations from several different instruments and sampling schemes. Technical issues are discussed, including the convergence of statistical estimates, the choice of representation of the correlations, the influential domain of an observation, and the efficiency of numerical computations.

Segmented strings coupled to a B-field

NASA Astrophysics Data System (ADS)

Vegh, David

2018-04-01

In this paper we study segmented strings in AdS3 coupled to a background two-form whose field strength is proportional to the volume form. By changing the coupling, the theory interpolates between the Nambu-Goto string and the SL(2, ℝ) Wess-Zumino-Witten model. In terms of the kink momentum vectors, the action is independent of the coupling and the classical theory reduces to a single discrete-time Toda-type theory. The WZW model is a singular point in coupling space where the map into Toda variables degenerates.

Illustrating dynamical symmetries in classical mechanics: The Laplace-Runge-Lenz vector revisited

NASA Astrophysics Data System (ADS)

O'Connell, Ross C.; Jagannathan, Kannan

2003-03-01

The inverse square force law admits a conserved vector that lies in the plane of motion. This vector has been associated with the names of Laplace, Runge, and Lenz, among others. Many workers have explored aspects of the symmetry and degeneracy associated with this vector and with analogous dynamical symmetries. We define a conserved dynamical variable α that characterizes the orientation of the orbit in two-dimensional configuration space for the Kepler problem and an analogous variable β for the isotropic harmonic oscillator. This orbit orientation variable is canonically conjugate to the angular momentum component normal to the plane of motion. We explore the canonical one-parameter group of transformations generated by α(β). Because we have an obvious pair of conserved canonically conjugate variables, it is desirable to use them as a coordinate-momentum pair. In terms of these phase space coordinates, the form of the Hamiltonian is nearly trivial because neither member of the pair can occur explicitly in the Hamiltonian. From these considerations we gain a simple picture of dynamics in phase space. The procedure we use is in the spirit of the Hamilton-Jacobi method.

Identification and Severity Determination of Wheat Stripe Rust and Wheat Leaf Rust Based on Hyperspectral Data Acquired Using a Black-Paper-Based Measuring Method.

PubMed

Wang, Hui; Qin, Feng; Ruan, Liu; Wang, Rui; Liu, Qi; Ma, Zhanhong; Li, Xiaolong; Cheng, Pei; Wang, Haiguang

2016-01-01

It is important to implement detection and assessment of plant diseases based on remotely sensed data for disease monitoring and control. Hyperspectral data of healthy leaves, leaves in incubation period and leaves in diseased period of wheat stripe rust and wheat leaf rust were collected under in-field conditions using a black-paper-based measuring method developed in this study. After data preprocessing, the models to identify the diseases were built using distinguished partial least squares (DPLS) and support vector machine (SVM), and the disease severity inversion models of stripe rust and the disease severity inversion models of leaf rust were built using quantitative partial least squares (QPLS) and support vector regression (SVR). All the models were validated by using leave-one-out cross validation and external validation. The diseases could be discriminated using both distinguished partial least squares and support vector machine with the accuracies of more than 99%. For each wheat rust, disease severity levels were accurately retrieved using both the optimal QPLS models and the optimal SVR models with the coefficients of determination (R2) of more than 0.90 and the root mean square errors (RMSE) of less than 0.15. The results demonstrated that identification and severity evaluation of stripe rust and leaf rust at the leaf level could be implemented based on the hyperspectral data acquired using the developed method. A scientific basis was provided for implementing disease monitoring by using aerial and space remote sensing technologies.

Identification and Severity Determination of Wheat Stripe Rust and Wheat Leaf Rust Based on Hyperspectral Data Acquired Using a Black-Paper-Based Measuring Method

PubMed Central

Ruan, Liu; Wang, Rui; Liu, Qi; Ma, Zhanhong; Li, Xiaolong; Cheng, Pei; Wang, Haiguang

2016-01-01

It is important to implement detection and assessment of plant diseases based on remotely sensed data for disease monitoring and control. Hyperspectral data of healthy leaves, leaves in incubation period and leaves in diseased period of wheat stripe rust and wheat leaf rust were collected under in-field conditions using a black-paper-based measuring method developed in this study. After data preprocessing, the models to identify the diseases were built using distinguished partial least squares (DPLS) and support vector machine (SVM), and the disease severity inversion models of stripe rust and the disease severity inversion models of leaf rust were built using quantitative partial least squares (QPLS) and support vector regression (SVR). All the models were validated by using leave-one-out cross validation and external validation. The diseases could be discriminated using both distinguished partial least squares and support vector machine with the accuracies of more than 99%. For each wheat rust, disease severity levels were accurately retrieved using both the optimal QPLS models and the optimal SVR models with the coefficients of determination (R2) of more than 0.90 and the root mean square errors (RMSE) of less than 0.15. The results demonstrated that identification and severity evaluation of stripe rust and leaf rust at the leaf level could be implemented based on the hyperspectral data acquired using the developed method. A scientific basis was provided for implementing disease monitoring by using aerial and space remote sensing technologies. PMID:27128464

Compound Structure-Independent Activity Prediction in High-Dimensional Target Space.

PubMed

Balfer, Jenny; Hu, Ye; Bajorath, Jürgen

2014-08-01

Profiling of compound libraries against arrays of targets has become an important approach in pharmaceutical research. The prediction of multi-target compound activities also represents an attractive task for machine learning with potential for drug discovery applications. Herein, we have explored activity prediction in high-dimensional target space. Different types of models were derived to predict multi-target activities. The models included naïve Bayesian (NB) and support vector machine (SVM) classifiers based upon compound structure information and NB models derived on the basis of activity profiles, without considering compound structure. Because the latter approach can be applied to incomplete training data and principally depends on the feature independence assumption, SVM modeling was not applicable in this case. Furthermore, iterative hybrid NB models making use of both activity profiles and compound structure information were built. In high-dimensional target space, NB models utilizing activity profile data were found to yield more accurate activity predictions than structure-based NB and SVM models or hybrid models. An in-depth analysis of activity profile-based models revealed the presence of correlation effects across different targets and rationalized prediction accuracy. Taken together, the results indicate that activity profile information can be effectively used to predict the activity of test compounds against novel targets. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Black hole perturbations in vector-tensor theories: the odd-mode analysis

NASA Astrophysics Data System (ADS)

Kase, Ryotaro; Minamitsuji, Masato; Tsujikawa, Shinji; Zhang, Ying-li

2018-02-01

In generalized Proca theories with vector-field derivative couplings, a bunch of hairy black hole solutions have been derived on a static and spherically symmetric background. In this paper, we formulate the odd-parity black hole perturbations in generalized Proca theories by expanding the corresponding action up to second order and investigate whether or not black holes with vector hair suffer ghost or Laplacian instabilities. We show that the models with cubic couplings G3(X), where X=‑AμAμ/2 with a vector field Aμ, do not provide any additional stability condition as in General Relativity. On the other hand, the exact charged stealth Schwarzschild solution with a nonvanishing longitudinal vector component A1, which originates from the coupling to the Einstein tensor GμνAμ Aν equivalent to the quartic coupling G4(X) containing a linear function of X, is unstable in the vicinity of the event horizon. The same instability problem also persists for hairy black holes arising from general quartic power-law couplings G4(X) ⊃ β4 Xn with the nonvanishing A1, while the other branch with A1=0 can be consistent with conditions for the absence of ghost and Laplacian instabilities. We also discuss the case of other exact and numerical black hole solutions associated with intrinsic vector-field derivative couplings and show that there exists a wide range of parameter spaces in which the solutions suffer neither ghost nor Laplacian instabilities against odd-parity perturbations.

Reduced multiple empirical kernel learning machine.

PubMed

Wang, Zhe; Lu, MingZhe; Gao, Daqi

2015-02-01

Multiple kernel learning (MKL) is demonstrated to be flexible and effective in depicting heterogeneous data sources since MKL can introduce multiple kernels rather than a single fixed kernel into applications. However, MKL would get a high time and space complexity in contrast to single kernel learning, which is not expected in real-world applications. Meanwhile, it is known that the kernel mapping ways of MKL generally have two forms including implicit kernel mapping and empirical kernel mapping (EKM), where the latter is less attracted. In this paper, we focus on the MKL with the EKM, and propose a reduced multiple empirical kernel learning machine named RMEKLM for short. To the best of our knowledge, it is the first to reduce both time and space complexity of the MKL with EKM. Different from the existing MKL, the proposed RMEKLM adopts the Gauss Elimination technique to extract a set of feature vectors, which is validated that doing so does not lose much information of the original feature space. Then RMEKLM adopts the extracted feature vectors to span a reduced orthonormal subspace of the feature space, which is visualized in terms of the geometry structure. It can be demonstrated that the spanned subspace is isomorphic to the original feature space, which means that the dot product of two vectors in the original feature space is equal to that of the two corresponding vectors in the generated orthonormal subspace. More importantly, the proposed RMEKLM brings a simpler computation and meanwhile needs a less storage space, especially in the processing of testing. Finally, the experimental results show that RMEKLM owns a much efficient and effective performance in terms of both complexity and classification. The contributions of this paper can be given as follows: (1) by mapping the input space into an orthonormal subspace, the geometry of the generated subspace is visualized; (2) this paper first reduces both the time and space complexity of the EKM-based MKL; (3) this paper adopts the Gauss Elimination, one of the on-the-shelf techniques, to generate a basis of the original feature space, which is stable and efficient.

Modal Test/Analysis Correlation of Space Station Structures Using Nonlinear Sensitivity

NASA Technical Reports Server (NTRS)

Gupta, Viney K.; Newell, James F.; Berke, Laszlo; Armand, Sasan

1992-01-01

The modal correlation problem is formulated as a constrained optimization problem for validation of finite element models (FEM's). For large-scale structural applications, a pragmatic procedure for substructuring, model verification, and system integration is described to achieve effective modal correlation. The space station substructure FEM's are reduced using Lanczos vectors and integrated into a system FEM using Craig-Bampton component modal synthesis. The optimization code is interfaced with MSC/NASTRAN to solve the problem of modal test/analysis correlation; that is, the problem of validating FEM's for launch and on-orbit coupled loads analysis against experimentally observed frequencies and mode shapes. An iterative perturbation algorithm is derived and implemented to update nonlinear sensitivity (derivatives of eigenvalues and eigenvectors) during optimizer iterations, which reduced the number of finite element analyses.

Modal test/analysis correlation of Space Station structures using nonlinear sensitivity

NASA Technical Reports Server (NTRS)

Gupta, Viney K.; Newell, James F.; Berke, Laszlo; Armand, Sasan

1992-01-01

The modal correlation problem is formulated as a constrained optimization problem for validation of finite element models (FEM's). For large-scale structural applications, a pragmatic procedure for substructuring, model verification, and system integration is described to achieve effective modal correlations. The space station substructure FEM's are reduced using Lanczos vectors and integrated into a system FEM using Craig-Bampton component modal synthesis. The optimization code is interfaced with MSC/NASTRAN to solve the problem of modal test/analysis correlation; that is, the problem of validating FEM's for launch and on-orbit coupled loads analysis against experimentally observed frequencies and mode shapes. An iterative perturbation algorithm is derived and implemented to update nonlinear sensitivity (derivatives of eigenvalues and eigenvectors) during optimizer iterations, which reduced the number of finite element analyses.

Are Bred Vectors The Same As Lyapunov Vectors?

NASA Astrophysics Data System (ADS)

Kalnay, E.; Corazza, M.; Cai, M.

Regional loss of predictability is an indication of the instability of the underlying flow, where small errors in the initial conditions (or imperfections in the model) grow to large amplitudes in finite times. The stability properties of evolving flows have been studied using Lyapunov vectors (e.g., Alligood et al, 1996, Ott, 1993, Kalnay, 2002), singular vectors (e.g., Lorenz, 1965, Farrell, 1988, Molteni and Palmer, 1993), and, more recently, with bred vectors (e.g., Szunyogh et al, 1997, Cai et al, 2001). Bred vectors (BVs) are, by construction, closely related to Lyapunov vectors (LVs). In fact, after an infinitely long breeding time, and with the use of infinitesimal ampli- tudes, bred vectors are identical to leading Lyapunov vectors. In practical applications, however, bred vectors are different from Lyapunov vectors in two important ways: a) bred vectors are never globally orthogonalized and are intrinsically local in space and time, and b) they are finite-amplitude, finite-time vectors. These two differences are very significant in a dynamical system whose size is very large. For example, the at- mosphere is large enough to have "room" for several synoptic scale instabilities (e.g., storms) to develop independently in different regions (say, North America and Aus- tralia), and it is complex enough to have several different possible types of instabilities (such as barotropic, baroclinic, convective, and even Brownian motion). Bred vectors share some of their properties with leading LVs (Corazza et al, 2001a, 2001b, Toth and Kalnay, 1993, 1997, Cai et al, 2001). For example, 1) Bred vectors are independent of the norm used to define the size of the perturba- tion. Corazza et al. (2001) showed that bred vectors obtained using a potential enstro- phy norm were indistinguishable from bred vectors obtained using a streamfunction squared norm, in contrast with singular vectors. 2) Bred vectors are independent of the length of the rescaling period as long as the perturbations remain approximately linear (for example, for atmospheric models the interval for rescaling could be varied between a single time step and 1 day without affecting qualitatively the characteristics of the bred vectors. However, the finite-amplitude, finite-time, and lack of orthogonalization of the BVs introduces important differences with LVs: 1) In regions that undergo strong instabilities, the bred vectors tend to be locally domi- 1 nated by simple, low-dimensional structures. Patil et al (2001) showed that the BV-dim (appendix) gives a good estimate of the number of dominant directions (shapes) of the local k bred vectors. For example, if half of them are aligned in one direction, and half in a different direction, the BV-dim is about two. If the majority of the bred vectors are aligned predominantly in one direction and only a few are aligned in a second direction, then the BV-dim is between 1 and 2. Patil et al., (2001) showed that the regions with low dimensionality cover about 20% of the atmosphere. They also found that these low-dimensionality regions have a very well defined vertical structure, and a typical lifetime of 3-7 days. The low dimensionality identifies regions where the in- stability of the basic flow has manifested itself in a low number of preferred directions of perturbation growth. 2) Using a Quasi-Geostrophic simulation system of data assimilation developed by Morss (1999), Corazza et al (2001a, b) found that bred vectors have structures that closely resemble the background (short forecasts used as first guess) errors, which in turn dominate the local analysis errors. This is especially true in regions of low dimensionality, which is not surprising if these are unstable regions where errors grow in preferred shapes. 3) The number of bred vectors needed to represent the unstable subspace in the QG system is small (about 6-10). This was shown by computing the local BV-dim as a function of the number of independent bred vectors. Convergence in the local dimen- sion starts to occur at about 6 BVs, and is essentially complete when the number of vectors is about 10-15 (Corazza et al, 2001a). This should be contrasted with the re- sults of Snyder and Joly (1998) and Palmer et al (1998) who showed that hundreds of Lyapunov vectors with positive Lyapunov exponents are needed to represent the attractor of the system in quasi-geostrophic models. 4) Since only a few bred vectors are needed, and background errors project strongly in the subspace of bred vectors, Corazza et al (2001b) were able to develop cost-efficient methods to improve the 3D-Var data assimilation by adding to the background error covariance terms proportional to the outer product of the bred vectors, thus represent- ing the "errors of the day". This approach led to a reduction of analysis error variance of about 40% at very low cost. 5) The fact that BVs have finite amplitude provides a natural way to filter out instabil- ities present in the system that have fast growth, but saturate nonlinearly at such small amplitudes that they are irrelevant for ensemble perturbations. As shown by Lorenz (1996) Lyapunov vectors (and singular vectors) of models including these physical phenomena would be dominated by the fast but small amplitude instabilities, unless they are explicitly excluded from the linearized models. Bred vectors, on the other 2 hand, through the choice of an appropriate size for the perturbation, provide a natural filter based on nonlinear saturation of fast but irrelevant instabilities. 6) Every bred vector is qualitatively similar to the *leading* LV. LVs beyond the leading LV are obtained by orthogonalization after each time step with respect to the previous LVs subspace. The orthogonalization requires the introduction of a norm. With an enstrophy norm, the successive LVs have larger and larger horizontal scales, and a choice of a stream function norm would lead to successively smaller scales in the LVs. Beyond the first few LVs, there is little qualitative similarity between the background errors and the LVs. In summary, in a system like the atmosphere with enough physical space for several independent local instabilities, BVs and LVs share some properties but they also have significant differences. BV are finite-amplitude, finite-time, and because they are not globally orthogonalized, they have local properties in space. Bred vectors are akin to the leading LV, but bred vectors derived from different arbitrary initial perturba- tions remain distinct from each other, instead of collapsing into a single leading vec- tor, presumably because the nonlinear terms and physical parameterizations introduce sufficient stochastic forcing to avoid such convergence. As a result, there is no need for global orthogonalization, and the number of bred vectors required to describe the natural instabilities in an atmospheric system (from a local point of view) is much smaller than the number of Lyapunov vectors with positive Lyapunov exponents. The BVs are independent of the norm, whereas the LVs beyond the first one do depend on the choice of norm: for example, they become larger in scale with a vorticity norm, and smaller with a stream function norm. These properties of BVs result in significant advantages for data assimilation and en- semble forecasting for the atmosphere. Errors in the analysis have structures very similar to bred vectors, and it is found that they project very strongly on the subspace of a few bred vectors. This is not true for either Lyapunov vectors beyond the lead- ing LVs, or for singular vectors unless they are constructed with a norm based on the analysis error covariance matrix (or a bred vector covariance). The similarity between bred vectors and analysis errors leads to the ability to include "errors of the day" in the background error covariance and a significant improvement of the analysis beyond 3D-Var at a very low cost (Corazza, 2001b). References Alligood K. T., T. D. Sauer and J. A. Yorke, 1996: Chaos: an introduction to dynamical systems. Springer-Verlag, New York. Buizza R., J. Tribbia, F. Molteni and T. Palmer, 1993: Computation of optimal unstable 3 structures for numerical weather prediction models. Tellus, 45A, 388-407. Cai, M., E. Kalnay and Z. Toth, 2001: Potential impact of bred vectors on ensemble forecasting and data assimilation in the Zebiak-Cane model. Submitted to J of Climate. Corazza, M., E. Kalnay, D. J. Patil, R. Morss, M. Cai, I. Szunyogh, B. R. Hunt, E. Ott and J. Yorke, 2001: Use of the breeding technique to determine the structure of the "errors of the day". Submitted to Nonlinear Processes in Geophysics. Corazza, M., E. Kalnay, DJ Patil, E. Ott, J. Yorke, I Szunyogh and M. Cai, 2001: Use of the breeding technique in the estimation of the background error covariance matrix for a quasigeostrophic model. AMS Symposium on Observations, Data Assimilation and Predictability, Preprints volume, Orlando, FA, 14-17 January 2002. Farrell, B., 1988: Small error dynamics and the predictability of atmospheric flow, J. Atmos. Sciences, 45, 163-172. Kalnay, E 2002: Atmospheric modeling, data assimilation and predictability. Chapter 6. Cambridge University Press, UK. In press. Kalnay E and Z Toth 1994: Removing growing errors in the analysis. Preprints, Tenth Conference on Numerical Weather Prediction, pp 212-215. Amer. Meteor. Soc., July 18-22, 1994. Lorenz, E.N., 1965: A study of the predictability of a 28-variable atmospheric model. Tellus, 21, 289-307. Lorenz, E.N., 1996: Predictability- A problem partly solved. Proceedings of the ECMWF Seminar on Predictability, Reading, England, Vol. 1 1-18. Molteni F. and TN Palmer, 1993: Predictability and finite-time instability of the north- ern winter circulation. Q. J. Roy. Meteorol. Soc. 119, 269-298. Morss, R.E.: 1999: Adaptive observations: Idealized sampling strategies for improving numerical weather prediction. Ph.D. Thesis, Massachussetts Institute of Technology, 225pp. Ott, E., 1993: Chaos in Dynamical Systems. Cambridge University Press. New York. Palmer, TN, R. Gelaro, J. Barkmeijer and R. Buizza, 1998: Singular vectors, metrics and adaptive observations. J. Atmos Sciences, 55, 633-653. Patil, DJ, BR Hunt, E Kalnay, J. Yorke, and E. Ott, 2001: Local low dimensionality of atmospheric dynamics. Phys. Rev. Lett., 86, 5878. Patil, DJ, I. Szunyogh, BR Hunt, E Kalnay, E Ott, and J. Yorke, 2001: Using large 4 member ensembles to isolate local low dimensionality of atmospheric dynamics. AMS Symposium on Observations, Data Assimilation and Predictability, Preprints volume, Orlando, FA, 14-17 January 2002. Snyder, C. and A. Joly, 1998: Development of perturbations within growing baroclinic waves. Q. J. Roy. Meteor. Soc., 124, pp 1961. Szunyogh, I, E. Kalnay and Z. Toth, 1997: A comparison of Lyapunov and Singular vectors in a low resolution GCM. Tellus, 49A, 200-227. Toth, Z and E Kalnay 1993: Ensemble forecasting at NMC - the generation of pertur- bations. Bull. Amer. Meteorol. Soc., 74, 2317-2330. Toth, Z and E Kalnay 1997: Ensemble forecasting at NCEP and the breeding method. Mon Wea Rev, 125, 3297-3319. * Corresponding author address: Eugenia Kalnay, Meteorology Depart- ment, University of Maryland, College Park, MD 20742-2425, USA; email: ekalnay@atmos.umd.edu Appendix: BV-dimension Patil et al., (2001) defined local bred vectors around a point in the 3-dimensional grid of the model by taking the 24 closest horizontal neighbors. If there are k bred vectors available, and N model variables for each grid point, the k local bred vectors form the columns of a 25Nxk matrix B. The kxk covariance matrix is C=B^T B. Its eigen- values are positive, and its eigenvectors v(i) are the singular vectors of the local bred vector subspace. The Bred Vector dimension (BV-dim) measures the local effective dimension: BV-dim[s,s,...,s(k)]={SUM[s(i)]}^2/SUM[s(i)]^2 where s(i) are the square roots of the eigenvalues of the covariance matrix. 5

Generalized sidelobe canceller beamforming method for ultrasound imaging.

PubMed

Wang, Ping; Li, Na; Luo, Han-Wu; Zhu, Yong-Kun; Cui, Shi-Gang

2017-03-01

A modified generalized sidelobe canceller (IGSC) algorithm is proposed to enhance the resolution and robustness against the noise of the traditional generalized sidelobe canceller (GSC) and coherence factor combined method (GSC-CF). In the GSC algorithm, weighting vector is divided into adaptive and non-adaptive parts, while the non-adaptive part does not block all the desired signal. A modified steer vector of the IGSC algorithm is generated by the projection of the non-adaptive vector on the signal space constructed by the covariance matrix of received data. The blocking matrix is generated based on the orthogonal complementary space of the modified steer vector and the weighting vector is updated subsequently. The performance of IGSC was investigated by simulations and experiments. Through simulations, IGSC outperformed GSC-CF in terms of spatial resolution by 0.1 mm regardless there is noise or not, as well as the contrast ratio respect. The proposed IGSC can be further improved by combining with CF. The experimental results also validated the effectiveness of the proposed algorithm with dataset provided by the University of Michigan.

Time-based self-spacing techniques using cockpit display of traffic information during approach to landing in a terminal area vectoring environment

NASA Technical Reports Server (NTRS)

Williams, D. H.

1983-01-01

A simulation study was undertaken to evaluate two time-based self-spacing techniques for in-trail following during terminal area approach. An electronic traffic display was provided in the weather radarscope location. The displayed self-spacing cues allowed the simulated aircraft to follow and to maintain spacing on another aircraft which was being vectored by air traffic control (ATC) for landing in a high-density terminal area. Separation performance data indicate the information provided on the traffic display was adequate for the test subjects to accurately follow the approach path of another aircraft without the assistance of ATC. The time-based technique with a constant-delay spacing criterion produced the most satisfactory spacing performance. Pilot comments indicate the workload associated with the self-separation task was very high and that additional spacing command information and/or aircraft autopilot functions would be desirable for operational implementational of the self-spacing task.

Hypercyclic subspaces for Frechet space operators

NASA Astrophysics Data System (ADS)

Petersson, Henrik

2006-07-01

A continuous linear operator is hypercyclic if there is an such that the orbit {Tnx} is dense, and such a vector x is said to be hypercyclic for T. Recent progress show that it is possible to characterize Banach space operators that have a hypercyclic subspace, i.e., an infinite dimensional closed subspace of, except for zero, hypercyclic vectors. The following is known to hold: A Banach space operator T has a hypercyclic subspace if there is a sequence (ni) and an infinite dimensional closed subspace such that T is hereditarily hypercyclic for (ni) and Tni->0 pointwise on E. In this note we extend this result to the setting of Frechet spaces that admit a continuous norm, and study some applications for important function spaces. As an application we also prove that any infinite dimensional separable Frechet space with a continuous norm admits an operator with a hypercyclic subspace.

A space-efficient quantum computer simulator suitable for high-speed FPGA implementation

NASA Astrophysics Data System (ADS)

Frank, Michael P.; Oniciuc, Liviu; Meyer-Baese, Uwe H.; Chiorescu, Irinel

2009-05-01

Conventional vector-based simulators for quantum computers are quite limited in the size of the quantum circuits they can handle, due to the worst-case exponential growth of even sparse representations of the full quantum state vector as a function of the number of quantum operations applied. However, this exponential-space requirement can be avoided by using general space-time tradeoffs long known to complexity theorists, which can be appropriately optimized for this particular problem in a way that also illustrates some interesting reformulations of quantum mechanics. In this paper, we describe the design and empirical space/time complexity measurements of a working software prototype of a quantum computer simulator that avoids excessive space requirements. Due to its space-efficiency, this design is well-suited to embedding in single-chip environments, permitting especially fast execution that avoids access latencies to main memory. We plan to prototype our design on a standard FPGA development board.

Helicons in uniform fields. I. Wave diagnostics with hodograms

NASA Astrophysics Data System (ADS)

Urrutia, J. M.; Stenzel, R. L.

2018-03-01

The wave equation for whistler waves is well known and has been solved in Cartesian and cylindrical coordinates, yielding plane waves and cylindrical waves. In space plasmas, waves are usually assumed to be plane waves; in small laboratory plasmas, they are often assumed to be cylindrical "helicon" eigenmodes. Experimental observations fall in between both models. Real waves are usually bounded and may rotate like helicons. Such helicons are studied experimentally in a large laboratory plasma which is essentially a uniform, unbounded plasma. The waves are excited by loop antennas whose properties determine the field rotation and transverse dimensions. Both m = 0 and m = 1 helicon modes are produced and analyzed by measuring the wave magnetic field in three dimensional space and time. From Ampère's law and Ohm's law, the current density and electric field vectors are obtained. Hodograms for these vectors are produced. The sign ambiguity of the hodogram normal with respect to the direction of wave propagation is demonstrated. In general, electric and magnetic hodograms differ but both together yield the wave vector direction unambiguously. Vector fields of the hodogram normal yield the phase flow including phase rotation for helicons. Some helicons can have locally a linear polarization which is identified by the hodogram ellipticity. Alternatively the amplitude oscillation in time yields a measure for the wave polarization. It is shown that wave interference produces linear polarization. These observations emphasize that single point hodogram measurements are inadequate to determine the wave topology unless assuming plane waves. Observations of linear polarization indicate wave packets but not plane waves. A simple qualitative diagnostics for the wave polarization is the measurement of the magnetic field magnitude in time. Circular polarization has a constant amplitude; linear polarization results in amplitude modulations.

Hybrid NN/SVM Computational System for Optimizing Designs

NASA Technical Reports Server (NTRS)

Rai, Man Mohan

2009-01-01

A computational method and system based on a hybrid of an artificial neural network (NN) and a support vector machine (SVM) (see figure) has been conceived as a means of maximizing or minimizing an objective function, optionally subject to one or more constraints. Such maximization or minimization could be performed, for example, to optimize solve a data-regression or data-classification problem or to optimize a design associated with a response function. A response function can be considered as a subset of a response surface, which is a surface in a vector space of design and performance parameters. A typical example of a design problem that the method and system can be used to solve is that of an airfoil, for which a response function could be the spatial distribution of pressure over the airfoil. In this example, the response surface would describe the pressure distribution as a function of the operating conditions and the geometric parameters of the airfoil. The use of NNs to analyze physical objects in order to optimize their responses under specified physical conditions is well known. NN analysis is suitable for multidimensional interpolation of data that lack structure and enables the representation and optimization of a succession of numerical solutions of increasing complexity or increasing fidelity to the real world. NN analysis is especially useful in helping to satisfy multiple design objectives. Feedforward NNs can be used to make estimates based on nonlinear mathematical models. One difficulty associated with use of a feedforward NN arises from the need for nonlinear optimization to determine connection weights among input, intermediate, and output variables. It can be very expensive to train an NN in cases in which it is necessary to model large amounts of information. Less widely known (in comparison with NNs) are support vector machines (SVMs), which were originally applied in statistical learning theory. In terms that are necessarily oversimplified to fit the scope of this article, an SVM can be characterized as an algorithm that (1) effects a nonlinear mapping of input vectors into a higher-dimensional feature space and (2) involves a dual formulation of governing equations and constraints. One advantageous feature of the SVM approach is that an objective function (which one seeks to minimize to obtain coefficients that define an SVM mathematical model) is convex, so that unlike in the cases of many NN models, any local minimum of an SVM model is also a global minimum.

A Compendium of Wind Statistics and Models for the NASA Space Shuttle and Other Aerospace Vehicle Programs

NASA Technical Reports Server (NTRS)

Smith, O. E.; Adelfang, S. I.

1998-01-01

The wind profile with all of its variations with respect to altitude has been, is now, and will continue to be important for aerospace vehicle design and operations. Wind profile databases and models are used for the vehicle ascent flight design for structural wind loading, flight control systems, performance analysis, and launch operations. This report presents the evolution of wind statistics and wind models from the empirical scalar wind profile model established for the Saturn Program through the development of the vector wind profile model used for the Space Shuttle design to the variations of this wind modeling concept for the X-33 program. Because wind is a vector quantity, the vector wind models use the rigorous mathematical probability properties of the multivariate normal probability distribution. When the vehicle ascent steering commands (ascent guidance) are wind biased to the wind profile measured on the day-of-launch, ascent structural wind loads are reduced and launch probability is increased. This wind load alleviation technique is recommended in the initial phase of vehicle development. The vehicle must fly through the largest load allowable versus altitude to achieve its mission. The Gumbel extreme value probability distribution is used to obtain the probability of exceeding (or not exceeding) the load allowable. The time conditional probability function is derived from the Gumbel bivariate extreme value distribution. This time conditional function is used for calculation of wind loads persistence increments using 3.5-hour Jimsphere wind pairs. These increments are used to protect the commit-to-launch decision. Other topics presented include the Shuttle Shuttle load-response to smoothed wind profiles, a new gust model, and advancements in wind profile measuring systems. From the lessons learned and knowledge gained from past vehicle programs, the development of future launch vehicles can be accelerated. However, new vehicle programs by their very nature will require specialized support for new databases and analyses for wind, atmospheric parameters (pressure, temperature, and density versus altitude), and weather. It is for this reason that project managers are encouraged to collaborate with natural environment specialists early in the conceptual design phase. Such action will give the lead time necessary to meet the natural environment design and operational requirements, and thus, reduce development costs.

Left ventricular hypertrophy index based on a combination of frontal and transverse planes in the ECG and VCG: Diagnostic utility of cardiac vectors

NASA Astrophysics Data System (ADS)

Bonomini, Maria Paula; Juan Ingallina, Fernando; Barone, Valeria; Antonucci, Ricardo; Valentinuzzi, Max; Arini, Pedro David

2016-04-01

The changes that left ventricular hypertrophy (LVH) induces in depolarization and repolarization vectors are well known. We analyzed the performance of the electrocardiographic and vectorcardiographic transverse planes (TP in the ECG and XZ in the VCG) and frontal planes (FP in the ECG and XY in the VCG) to discriminate LVH patients from control subjects. In an age-balanced set of 58 patients, the directions and amplitudes of QRS-complexes and T-wave vectors were studied. The repolarization vector significantly decreased in modulus from controls to LVH in the transverse plane (TP: 0.45±0.17mV vs. 0.24±0.13mV, p<0.0005 XZ: 0.43±0.16mV vs. 0.26±0.11mV, p<0.005) while the depolarization vector significantly changed in angle in the electrocardiographic frontal plane (Controls vs. LVH, FP: 48.24±33.66° vs. 46.84±35.44°, p<0.005, XY: 20.28±35.20° vs. 19.35±12.31°, NS). Several LVH indexes were proposed combining such information in both ECG and VCG spaces. A subset of all those indexes with AUC values greater than 0.7 was further studied. This subset comprised four indexes, with three of them belonging to the ECG space. Two out of the four indexes presented the best ROC curves (AUC values: 0.78 and 0.75, respectively). One index belonged to the ECG space and the other one to the VCG space. Both indexes showed a sensitivity of 86% and a specificity of 70%. In conclusion, the proposed indexes can favorably complement LVH diagnosis

Covariantized vector Galileons

NASA Astrophysics Data System (ADS)

Hull, Matthew; Koyama, Kazuya; Tasinato, Gianmassimo

2016-03-01

Vector Galileons are ghost-free systems containing higher derivative interactions of vector fields. They break the vector gauge symmetry, and the dynamics of the longitudinal vector polarizations acquire a Galileon symmetry in an appropriate decoupling limit in Minkowski space. Using an Arnowitt-Deser-Misner approach, we carefully reconsider the coupling with gravity of vector Galileons, with the aim of studying the necessary conditions to avoid the propagation of ghosts. We develop arguments that put on a more solid footing the results previously obtained in the literature. Moreover, working in analogy with the scalar counterpart, we find indications for the existence of a "beyond Horndeski" theory involving vector degrees of freedom that avoids the propagation of ghosts thanks to secondary constraints. In addition, we analyze a Higgs mechanism for generating vector Galileons through spontaneous symmetry breaking, and we present its consistent covariantization.

A Spatio-temporal Model of African Animal Trypanosomosis Risk

PubMed Central

Dicko, Ahmadou H.; Percoma, Lassane; Sow, Adama; Adam, Yahaya; Mahama, Charles; Sidibé, Issa; Dayo, Guiguigbaza-Kossigan; Thévenon, Sophie; Fonta, William; Sanfo, Safietou; Djiteye, Aligui; Salou, Ernest; Djohan, Vincent; Cecchi, Giuliano; Bouyer, Jérémy

2015-01-01

Background African animal trypanosomosis (AAT) is a major constraint to sustainable development of cattle farming in sub-Saharan Africa. The habitat of the tsetse fly vector is increasingly fragmented owing to demographic pressure and shifts in climate, which leads to heterogeneous risk of cyclical transmission both in space and time. In Burkina Faso and Ghana, the most important vectors are riverine species, namely Glossina palpalis gambiensis and G. tachinoides, which are more resilient to human-induced changes than the savannah and forest species. Although many authors studied the distribution of AAT risk both in space and time, spatio-temporal models allowing predictions of it are lacking. Methodology/Principal Findings We used datasets generated by various projects, including two baseline surveys conducted in Burkina Faso and Ghana within PATTEC (Pan African Tsetse and Trypanosomosis Eradication Campaign) national initiatives. We computed the entomological inoculation rate (EIR) or tsetse challenge using a range of environmental data. The tsetse apparent density and their infection rate were separately estimated and subsequently combined to derive the EIR using a “one layer-one model” approach. The estimated EIR was then projected into suitable habitat. This risk index was finally validated against data on bovine trypanosomosis. It allowed a good prediction of the parasitological status (r2 = 67%), showed a positive correlation but less predictive power with serological status (r2 = 22%) aggregated at the village level but was not related to the illness status (r2 = 2%). Conclusions/Significance The presented spatio-temporal model provides a fine-scale picture of the dynamics of AAT risk in sub-humid areas of West Africa. The estimated EIR was high in the proximity of rivers during the dry season and more widespread during the rainy season. The present analysis is a first step in a broader framework for an efficient risk management of climate-sensitive vector-borne diseases. PMID:26154506

Hydrologic Process Parameterization of Electrical Resistivity Imaging of Solute Plumes Using POD McMC

NASA Astrophysics Data System (ADS)

Awatey, M. T.; Irving, J.; Oware, E. K.

2016-12-01

Markov chain Monte Carlo (McMC) inversion frameworks are becoming increasingly popular in geophysics due to their ability to recover multiple equally plausible geologic features that honor the limited noisy measurements. Standard McMC methods, however, become computationally intractable with increasing dimensionality of the problem, for example, when working with spatially distributed geophysical parameter fields. We present a McMC approach based on a sparse proper orthogonal decomposition (POD) model parameterization that implicitly incorporates the physics of the underlying process. First, we generate training images (TIs) via Monte Carlo simulations of the target process constrained to a conceptual model. We then apply POD to construct basis vectors from the TIs. A small number of basis vectors can represent most of the variability in the TIs, leading to dimensionality reduction. A projection of the starting model into the reduced basis space generates the starting POD coefficients. At each iteration, only coefficients within a specified sampling window are resimulated assuming a Gaussian prior. The sampling window grows at a specified rate as the number of iteration progresses starting from the coefficients corresponding to the highest ranked basis to those of the least informative basis. We found this gradual increment in the sampling window to be more stable compared to resampling all the coefficients right from the first iteration. We demonstrate the performance of the algorithm with both synthetic and lab-scale electrical resistivity imaging of saline tracer experiments, employing the same set of basis vectors for all inversions. We consider two scenarios of unimodal and bimodal plumes. The unimodal plume is consistent with the hypothesis underlying the generation of the TIs whereas bimodality in plume morphology was not theorized. We show that uncertainty quantification using McMC can proceed in the reduced dimensionality space while accounting for the physics of the underlying process.

Closedness of orbits in a space with SU(2) Poisson structure

NASA Astrophysics Data System (ADS)

Fatollahi, Amir H.; Shariati, Ahmad; Khorrami, Mohammad

2014-06-01

The closedness of orbits of central forces is addressed in a three-dimensional space in which the Poisson bracket among the coordinates is that of the SU(2) Lie algebra. In particular it is shown that among problems with spherically symmetric potential energies, it is only the Kepler problem for which all bounded orbits are closed. In analogy with the case of the ordinary space, a conserved vector (apart from the angular momentum) is explicitly constructed, which is responsible for the orbits being closed. This is the analog of the Laplace-Runge-Lenz vector. The algebra of the constants of the motion is also worked out.

A variable structure approach to robust control of VTOL aircraft

NASA Technical Reports Server (NTRS)

Calise, A. J.; Kramer, F.

1982-01-01

This paper examines the application of variable structure control theory to the design of a flight control system for the AV-8A Harrier in a hover mode. The objective in variable structure design is to confine the motion to a subspace of the total state space. The motion in this subspace is insensitive to system parameter variations and external disturbances that lie in the range space of the control. A switching type of control law results from the design procedure. The control system was designed to track a vector velocity command defined in the body frame. For comparison purposes, a proportional controller was designed using optimal linear regulator theory. Both control designs were first evaluated for transient response performance using a linearized model, then a nonlinear simulation study of a hovering approach to landing was conducted. Wind turbulence was modeled using a 1052 destroyer class air wake model.

Binary black hole spacetimes with a helical Killing vector

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

Klein, Christian

Binary black hole spacetimes with a helical Killing vector, which are discussed as an approximation for the early stage of a binary system, are studied in a projection formalism. In this setting the four-dimensional Einstein equations are equivalent to a three-dimensional gravitational theory with a SL(2,R)/SO(1,1) sigma model as the material source. The sigma model is determined by a complex Ernst equation. 2+1 decompositions of the three-metric are used to establish the field equations on the orbit space of the Killing vector. The two Killing horizons of spherical topology which characterize the black holes, the cylinder of light where themore » Killing vector changes from timelike to spacelike, and infinity are singular points of the equations. The horizon and the light cylinder are shown to be regular singularities, i.e., the metric functions can be expanded in a formal power series in the vicinity. The behavior of the metric at spatial infinity is studied in terms of formal series solutions to the linearized Einstein equations. It is shown that the spacetime is not asymptotically flat in the strong sense to have a smooth null infinity under the assumption that the metric tends asymptotically to the Minkowski metric. In this case the metric functions have an oscillatory behavior in the radial coordinate in a nonaxisymmetric setting, the asymptotic multipoles are not defined. The asymptotic behavior of the Weyl tensor near infinity shows that there is no smooth null infinity.« less

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.

Hydrologic variability and the dynamics of West Nile virus transmission

NASA Astrophysics Data System (ADS)

Shaman, J. L.

2011-12-01

West Nile virus (WNV) first emerged in North America in New York City during 1999 and since that time has spread throughout the continent and settled into a pattern of local endemicity in which outbreaks of variable size develop in some years but not others. Predicting where and when these outbreaks will develop is an issue of considerable public health importance. Spillover transmission of WNV to humans typically occurs when infection rates among vector mosquitoes are elevated. Mosquito infection rates are not constant through time but instead increase when newly emergent mosquitoes can more readily acquire WNV by blood-meal feeding on available, infected animal hosts. Such an increase of vector mosquito infection rates is termed amplification and is facilitated for WNV by intense zoonotic transmission of the virus among vector mosquitoes and avian hosts. Theory, observation and model simulations indicate that amplification is favored when mosquito breeding habitats and bird nesting and roosting habitats overlap. Both vector mosquitoes and vertebrate hosts depend on water resources; mosquitoes are critically dependent on the availability of standing water, as the first 3 stages of the mosquito life cycle, egg, larvae, pupae, are aquatic. Here it is shown that hydrologic variability often determines where and when vector mosquitoes and avian hosts congregate together, and when the amplification of WNV is more likely. Measures of land surface wetness and pooling, from ground observation, satellite observation, or numerical modeling, can provide reliable estimates of where and when WNV transmission hotspots will arise. Examples of this linkage between hydrology and WNV activity are given for Florida, Colorado and New York, and an operational system for monitoring and forecasting WNV risk in space and time is presented for Florida.

From elementary flux modes to elementary flux vectors: Metabolic pathway analysis with arbitrary linear flux constraints.

PubMed

Klamt, Steffen; Regensburger, Georg; Gerstl, Matthias P; Jungreuthmayer, Christian; Schuster, Stefan; Mahadevan, Radhakrishnan; Zanghellini, Jürgen; Müller, Stefan

2017-04-01

Elementary flux modes (EFMs) emerged as a formal concept to describe metabolic pathways and have become an established tool for constraint-based modeling and metabolic network analysis. EFMs are characteristic (support-minimal) vectors of the flux cone that contains all feasible steady-state flux vectors of a given metabolic network. EFMs account for (homogeneous) linear constraints arising from reaction irreversibilities and the assumption of steady state; however, other (inhomogeneous) linear constraints, such as minimal and maximal reaction rates frequently used by other constraint-based techniques (such as flux balance analysis [FBA]), cannot be directly integrated. These additional constraints further restrict the space of feasible flux vectors and turn the flux cone into a general flux polyhedron in which the concept of EFMs is not directly applicable anymore. For this reason, there has been a conceptual gap between EFM-based (pathway) analysis methods and linear optimization (FBA) techniques, as they operate on different geometric objects. One approach to overcome these limitations was proposed ten years ago and is based on the concept of elementary flux vectors (EFVs). Only recently has the community started to recognize the potential of EFVs for metabolic network analysis. In fact, EFVs exactly represent the conceptual development required to generalize the idea of EFMs from flux cones to flux polyhedra. This work aims to present a concise theoretical and practical introduction to EFVs that is accessible to a broad audience. We highlight the close relationship between EFMs and EFVs and demonstrate that almost all applications of EFMs (in flux cones) are possible for EFVs (in flux polyhedra) as well. In fact, certain properties can only be studied with EFVs. Thus, we conclude that EFVs provide a powerful and unifying framework for constraint-based modeling of metabolic networks.

From elementary flux modes to elementary flux vectors: Metabolic pathway analysis with arbitrary linear flux constraints

PubMed Central

Klamt, Steffen; Gerstl, Matthias P.; Jungreuthmayer, Christian; Mahadevan, Radhakrishnan; Müller, Stefan

2017-01-01

Elementary flux modes (EFMs) emerged as a formal concept to describe metabolic pathways and have become an established tool for constraint-based modeling and metabolic network analysis. EFMs are characteristic (support-minimal) vectors of the flux cone that contains all feasible steady-state flux vectors of a given metabolic network. EFMs account for (homogeneous) linear constraints arising from reaction irreversibilities and the assumption of steady state; however, other (inhomogeneous) linear constraints, such as minimal and maximal reaction rates frequently used by other constraint-based techniques (such as flux balance analysis [FBA]), cannot be directly integrated. These additional constraints further restrict the space of feasible flux vectors and turn the flux cone into a general flux polyhedron in which the concept of EFMs is not directly applicable anymore. For this reason, there has been a conceptual gap between EFM-based (pathway) analysis methods and linear optimization (FBA) techniques, as they operate on different geometric objects. One approach to overcome these limitations was proposed ten years ago and is based on the concept of elementary flux vectors (EFVs). Only recently has the community started to recognize the potential of EFVs for metabolic network analysis. In fact, EFVs exactly represent the conceptual development required to generalize the idea of EFMs from flux cones to flux polyhedra. This work aims to present a concise theoretical and practical introduction to EFVs that is accessible to a broad audience. We highlight the close relationship between EFMs and EFVs and demonstrate that almost all applications of EFMs (in flux cones) are possible for EFVs (in flux polyhedra) as well. In fact, certain properties can only be studied with EFVs. Thus, we conclude that EFVs provide a powerful and unifying framework for constraint-based modeling of metabolic networks. PMID:28406903

Derivation of formulas for root-mean-square errors in location, orientation, and shape in triangulation solution of an elongated object in space

NASA Technical Reports Server (NTRS)

Long, S. A. T.

1974-01-01

Formulas are derived for the root-mean-square (rms) displacement, slope, and curvature errors in an azimuth-elevation image trace of an elongated object in space, as functions of the number and spacing of the input data points and the rms elevation error in the individual input data points from a single observation station. Also, formulas are derived for the total rms displacement, slope, and curvature error vectors in the triangulation solution of an elongated object in space due to the rms displacement, slope, and curvature errors, respectively, in the azimuth-elevation image traces from different observation stations. The total rms displacement, slope, and curvature error vectors provide useful measure numbers for determining the relative merits of two or more different triangulation procedures applicable to elongated objects in space.

Covariance estimation in Terms of Stokes Parameters with Application to Vector Sensor Imaging

DTIC Science & Technology

2016-12-15

S. Klein, “HF Vector Sensor for Radio Astronomy : Ground Testing Results,” in AIAA SPACE 2016, ser. AIAA SPACE Forum, American Institute of... astronomy ,” in 2016 IEEE Aerospace Conference, Mar. 2016, pp. 1–17. doi: 10.1109/ AERO.2016.7500688. [4] K.-C. Ho, K.-C. Tan, and B. T. G. Tan, “Estimation of...Statistical Imaging in Radio Astronomy via an Expectation-Maximization Algorithm for Structured Covariance Estimation,” in Statistical Methods in Imaging: IN

Lie theory and control systems defined on spheres

NASA Technical Reports Server (NTRS)

Brockett, R. W.

1972-01-01

It is shown that in constructing a theory for the most elementary class of control problems defined on spheres, some results from the Lie theory play a natural role. To understand controllability, optimal control, and certain properties of stochastic equations, Lie theoretic ideas are needed. The framework considered here is the most natural departure from the usual linear system/vector space problems which have dominated control systems literature. For this reason results are compared with those previously available for the finite dimensional vector space case.

Space Object Classification Using Fused Features of Time Series Data

NASA Astrophysics Data System (ADS)

Jia, B.; Pham, K. D.; Blasch, E.; Shen, D.; Wang, Z.; Chen, G.

In this paper, a fused feature vector consisting of raw time series and texture feature information is proposed for space object classification. The time series data includes historical orbit trajectories and asteroid light curves. The texture feature is derived from recurrence plots using Gabor filters for both unsupervised learning and supervised learning algorithms. The simulation results show that the classification algorithms using the fused feature vector achieve better performance than those using raw time series or texture features only.

Using trees to compute approximate solutions to ordinary differential equations exactly

NASA Technical Reports Server (NTRS)

Grossman, Robert

1991-01-01

Some recent work is reviewed which relates families of trees to symbolic algorithms for the exact computation of series which approximate solutions of ordinary differential equations. It turns out that the vector space whose basis is the set of finite, rooted trees carries a natural multiplication related to the composition of differential operators, making the space of trees an algebra. This algebraic structure can be exploited to yield a variety of algorithms for manipulating vector fields and the series and algebras they generate.

Local Gram-Schmidt and covariant Lyapunov vectors and exponents for three harmonic oscillator problems

NASA Astrophysics Data System (ADS)

Hoover, Wm. G.; Hoover, Carol G.

2012-02-01

We compare the Gram-Schmidt and covariant phase-space-basis-vector descriptions for three time-reversible harmonic oscillator problems, in two, three, and four phase-space dimensions respectively. The two-dimensional problem can be solved analytically. The three-dimensional and four-dimensional problems studied here are simultaneously chaotic, time-reversible, and dissipative. Our treatment is intended to be pedagogical, for use in an updated version of our book on Time Reversibility, Computer Simulation, and Chaos. Comments are very welcome.

SAX-VSM: Interpretable Time Series Classification Using SAX and Vector Space Model

DTIC Science & Technology

2013-01-01

points in the region 800-1900 cm−1. The two top-ranked by SAX- VSM subsequences in both datasets correpond to spectrogram intervals of Chlorogenic acid ...1600 1800 Wavenumbers Best class-characteristic subsequences - Chlorogenic acid Arabica Robusta 800 1000 1200 1400 1600 1800 Wavenumbers Second to best...correspond to chlorogenic acid (best subsequence) and to caffeine (second to best) regions of spectra. This result aligns with the original work based on

Current Simulation Methods in Military Systems Vulnerability Assessment

DTIC Science & Technology

1990-11-01

Weapons * 1990: JASON Review of the Army Approach to Vulnerability Testing Many of the suggestions and recommendations made by these committees concern...damage vectors. Ongoing work by the JASONs 29 is also targeted to developing statistical methods for LF-test/SQuASH-model comparisons in Space 2]. We...Technical Report BRL-TR-3113, June 1990. 28. L. Tonnessen, A. Fries , L. Starkey and A. Stein, Live Fire Testing in the Evaluation of the Vulnerability of

Robust Image Restoration for Ground-Based Space Surveillance

DTIC Science & Technology

2013-09-01

systems can be characterized by well-separated layers of frozen turbulence with different velocity vectors (the frozen flow model, FFM ) [5[. Studies...of the atmosphere at Mt. Haleakala have suggested that there are typically 2-3 such layers [6]. The FFM requires that we know the wind velocities...as a sum of independent static turbulent layers: where denotes the velocity of the ith layer. Using the FFM results in better sampling of the

Reducible boundary conditions in coupled channels

NASA Astrophysics Data System (ADS)

Pankrashkin, Konstantin

2005-10-01

We study Hamiltonians with point interactions in spaces of vector-valued functions. Using some information from the theory of quantum graphs, we describe a class of the operators which can be reduced to the direct sum of several one-dimensional problems. It shown that such a reduction is closely connected with the invariance under channel permutations. Examples are provided by some 'model' interactions, in particular, the so-called δ, δ' and the Kirchhoff couplings.

Revisiting the direct detection of dark matter in simplified models

NASA Astrophysics Data System (ADS)

Li, Tong

2018-07-01

In this work we numerically re-examine the loop-induced WIMP-nucleon scattering cross section for the simplified dark matter models and the constraint set by the latest direct detection experiment. We consider a fermion, scalar or vector dark matter component from five simplified models with leptophobic spin-0 mediators coupled only to Standard Model quarks and dark matter particles. The tree-level WIMP-nucleon cross sections in these models are all momentum-suppressed. We calculate the non-suppressed spin-independent WIMP-nucleon cross sections from loop diagrams and investigate the constrained space of dark matter mass and mediator mass by Xenon1T. The constraints from indirect detection and collider search are also discussed.

Vectorization of a penalty function algorithm for well scheduling

NASA Technical Reports Server (NTRS)

Absar, I.

1984-01-01

In petroleum engineering, the oil production profiles of a reservoir can be simulated by using a finite gridded model. This profile is affected by the number and choice of wells which in turn is a result of various production limits and constraints including, for example, the economic minimum well spacing, the number of drilling rigs available and the time required to drill and complete a well. After a well is available it may be shut in because of excessive water or gas productions. In order to optimize the field performance a penalty function algorithm was developed for scheduling wells. For an example with some 343 wells and 15 different constraints, the scheduling routine vectorized for the CYBER 205 averaged 560 times faster performance than the scalar version.

Cellular Mechanisms of Gravitropic Response in Higher Plants

NASA Astrophysics Data System (ADS)

Medvedev, Sergei; Smolikova, Galina; Pozhvanov, Gregory; Suslov, Dmitry

The evolutionary success of land plants in adaptation to the vectorial environmental factors was based mainly on the development of polarity systems. In result, normal plant ontogenesis is based on the positional information. Polarity is a tool by which the developing plant organs and tissues are mapped and the specific three-dimensional structure of the organism is created. It is due to their polar organization plants are able to orient themselves relative to the gravity vector and different vectorial cues, and to respond adequately to various stimuli. Gravitation is one of the most important polarized environmental factor that guides the development of plant organisms in space. Every plant can "estimate" its position relative to the gravity vector and correct it, if necessary, by means of polarized growth. The direction and the magnitude of gravitational stimulus are constant during the whole plant ontogenesis. The key plant response to the action of gravity is gravitropism, i.e. the directed growth of organs with respect to the gravity vector. This response is a very convenient model to study the mechanisms of plant orientation in space. The present report is focused on the main cellular mechanisms responsible for graviropic bending in higher plants. These mechanisms and structures include electric polarization of plant cells, Ca ({2+) }gradients, cytoskeleton, G-proteins, phosphoinositides and the machinery responsible for asymmetric auxin distribution. Those mechanisms tightly interact demonstrating some hierarchy and multiple feedbacks. The Ca (2+) gradients provide the primary physiological basis of polarity in plant cells. Calcium ions influence on the bioelectric potentials, the organization of actin cytoskeleton, the activity of Ca (2+) -binding proteins and Ca (2+) -dependent protein kinases. Protein kinases modulate transcription factors activity thereby regulating the gene expression and switching the developmental programs. Actin cytoskeleton affects the molecular machinery of polar auxin transport. It results in the changes of auxin gradients in plant organs and tissues, which modulate all cellular mechanisms of polarity via multiple feedback loops. The understanding of the mechanisms of plant organism orientation relative to the gravity vector will allow us to develop efficient technologies for plant growing in microgravity conditions at orbital space stations and during long piloted space flights. This work was supported by the grant of Russian Foundation for Basic Research (N 14-04-01-624) and by the grant of St.-Petersburg State University (N 1.38.233.2014).

Efficient computational methods for electromagnetic imaging with applications to 3D magnetotellurics

NASA Astrophysics Data System (ADS)

Kordy, Michal Adam

The motivation for this work is the forward and inverse problem for magnetotellurics, a frequency domain electromagnetic remote-sensing geophysical method used in mineral, geothermal, and groundwater exploration. The dissertation consists of four papers. In the first paper, we prove the existence and uniqueness of a representation of any vector field in H(curl) by a vector lying in H(curl) and H(div). It allows us to represent electric or magnetic fields by another vector field, for which nodal finite element approximation may be used in the case of non-constant electromagnetic properties. With this approach, the system matrix does not become ill-posed for low-frequency. In the second paper, we consider hexahedral finite element approximation of an electric field for the magnetotelluric forward problem. The near-null space of the system matrix for low frequencies makes the numerical solution unstable in the air. We show that the proper solution may obtained by applying a correction on the null space of the curl. It is done by solving a Poisson equation using discrete Helmholtz decomposition. We parallelize the forward code on multicore workstation with large RAM. In the next paper, we use the forward code in the inversion. Regularization of the inversion is done by using the second norm of the logarithm of conductivity. The data space Gauss-Newton approach allows for significant savings in memory and computational time. We show the efficiency of the method by considering a number of synthetic inversions and we apply it to real data collected in Cascade Mountains. The last paper considers a cross-frequency interpolation of the forward response as well as the Jacobian. We consider Pade approximation through model order reduction and rational Krylov subspace. The interpolating frequencies are chosen adaptively in order to minimize the maximum error of interpolation. Two error indicator functions are compared. We prove a theorem of almost always lucky failure in the case of the right hand analytically dependent on frequency. The operator's null space is treated by decomposing the solution into the part in the null space and orthogonal to it.

Which coordinate system for modelling path integration?

PubMed

Vickerstaff, Robert J; Cheung, Allen

2010-03-21

Path integration is a navigation strategy widely observed in nature where an animal maintains a running estimate, called the home vector, of its location during an excursion. Evidence suggests it is both ancient and ubiquitous in nature, and has been studied for over a century. In that time, canonical and neural network models have flourished, based on a wide range of assumptions, justifications and supporting data. Despite the importance of the phenomenon, consensus and unifying principles appear lacking. A fundamental issue is the neural representation of space needed for biological path integration. This paper presents a scheme to classify path integration systems on the basis of the way the home vector records and updates the spatial relationship between the animal and its home location. Four extended classes of coordinate systems are used to unify and review both canonical and neural network models of path integration, from the arthropod and mammalian literature. This scheme demonstrates analytical equivalence between models which may otherwise appear unrelated, and distinguishes between models which may superficially appear similar. A thorough analysis is carried out of the equational forms of important facets of path integration including updating, steering, searching and systematic errors, using each of the four coordinate systems. The type of available directional cue, namely allothetic or idiothetic, is also considered. It is shown that on balance, the class of home vectors which includes the geocentric Cartesian coordinate system, appears to be the most robust for biological systems. A key conclusion is that deducing computational structure from behavioural data alone will be difficult or impossible, at least in the absence of an analysis of random errors. Consequently it is likely that further theoretical insights into path integration will require an in-depth study of the effect of noise on the four classes of home vectors. Copyright 2009 Elsevier Ltd. All rights reserved.

A unified approach to χ2 discriminators for searches of gravitational waves from compact binary coalescences

NASA Astrophysics Data System (ADS)

Dhurandhar, Sanjeev; Gupta, Anuradha; Gadre, Bhooshan; Bose, Sukanta

2017-11-01

We describe a general mathematical framework for χ2 discriminators in the context of the compact binary coalescence (CBC) search. We show that with any χ2 is associated a vector bundle over the signal manifold, that is, the manifold traced out by the signal waveforms in the function space of data segments. The χ2 is then defined as the square of the L2 norm of the data vector projected onto a finite-dimensional subspace (the fibre) of the Hilbert space of data trains and orthogonal to the signal waveform. Any such fibre leads to a χ2 discriminator, and the full vector bundle comprising the subspaces and the base manifold constitute the χ2 discriminator. We show that the χ2 discriminators used so far in the CBC searches correspond to different fibre structures constituting different vector bundles on the same base manifold, namely, the parameter space. Several benefits accrue from this general formulation. It most importantly shows that there are a plethora of χ2's available and further gives useful insights into the vetoing procedure. It indicates procedures to formulate new χ2's that could be more effective in discriminating against commonly occurring glitches in the data. It also shows that no χ2 with a reasonable number of degrees of freedom is foolproof. It could also shed light on understanding why the traditional χ2 works so well. We show how to construct a generic χ2 given an arbitrary set of vectors in the function space of data segments. These vectors could be chosen such that glitches have maximum projection on them. Further, for glitches that can be modeled, we are able to quantify the efficiency of a given χ2 discriminator by a probability. Second, we propose a family of ambiguity χ2 discriminators that is an alternative to the traditional one [B. Allen, Phys. Rev. D 71, 062001 (2005), 10.1103/PhysRevD.71.062001, B. Allen et al., Phys. Rev. D 85, 122006 (2012)., 10.1103/PhysRevD.85.122006]. Any such ambiguity χ2 makes use of the filtered output of the template bank, thus adding negligible cost to the overall search. It is termed so because it makes significant use of the ambiguity function. We first describe the formulation with the help of the Newtonian waveform, apply the ambiguity χ2 to the spinless TaylorF2 waveforms, and test it on simulated data. We show that the ambiguity χ2 essentially gives a clean separation between glitches and signals. We indicate how the ambiguity χ2 can be generalized to detector networks for coherent observations. The effects of mismatch between signal and templates on a χ2 discriminator using general arguments and the geometrical framework are also investigated.

Toward (finally!) ruling out Z and Higgs mediated dark matter models

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

Escudero, Miguel; Berlin, Asher; Hooper, Dan

2016-12-01

In recent years, direct detection, indirect detection, and collider experiments have placed increasingly stringent constraints on particle dark matter, exploring much of the parameter space associated with the WIMP paradigm. In this paper, we focus on the subset of WIMP models in which the dark matter annihilates in the early universe through couplings to either the Standard Model Z or the Standard Model Higgs boson. Considering fermionic, scalar, and vector dark matter candidates within a model-independent context, we find that the overwhelming majority of these dark matter candidates are already ruled out by existing experiments. In the case of Zmore » mediated dark matter, the only scenarios that are not currently excluded are those in which the dark matter is a fermion with an axial coupling and with a mass either within a few GeV of the Z resonance ( m {sub DM} ≅ m {sub Z} /2) or greater than 200 GeV, or with a vector coupling and with m {sub DM} > 6 TeV . Several Higgs mediated scenarios are currently viable if the mass of the dark matter is near the Higgs pole ( m {sub DM} ≅ m {sub H} /2). Otherwise, the only scenarios that are not excluded are those in which the dark matter is a scalar (vector) heavier than 400 GeV (1160 GeV) with a Higgs portal coupling, or a fermion with a pseudoscalar (CP violating) coupling to the Standard Model Higgs boson. With the exception of dark matter with a purely pseudoscalar coupling to the Higgs, it is anticipated that planned direct detection experiments will probe nearly the entire range of models considered in this study.« less

Toward (finally!) ruling out Z and Higgs mediated dark matter models

DOE PAGES

Escudero, Miguel; Fermi National Accelerator Lab.; Berlin, Asher; ...

2016-12-15

In recent years, direct detection, indirect detection, and collider experiments have placed increasingly stringent constraints on particle dark matter, exploring much of the parameter space associated with the WIMP paradigm. In this paper, we focus on the subset of WIMP models in which the dark matter annihilates in the early universe through couplings to either the Standard Model Z or the Standard Model Higgs boson. Considering fermionic, scalar, and vector dark matter candidates within a model-independent context, we find that the overwhelming majority of these dark matter candidates are already ruled out by existing experiments. In the case of Zmore » mediated dark matter, the only scenarios that are not currently excluded are those in which the dark matter is a fermion with an axial coupling and with a mass either within a few GeV of the Z resonance (m DM ≃ m Z/2) or greater than 200 GeV, or with a vector coupling and with m DM > 6 TeV . Several Higgs mediated scenarios are currently viable if the mass of the dark matter is near the Higgs pole (m DM ≃ m H/2). Otherwise, the only scenarios that are not excluded are those in which the dark matter is a scalar (vector) heavier than 400 GeV (1160 GeV) with a Higgs portal coupling, or a fermion with a pseudoscalar (CP violating) coupling to the Standard Model Higgs boson. Furthermore, with the exception of dark matter with a purely pseudoscalar coupling to the Higgs, it is anticipated that planned direct detection experiments will probe nearly the entire range of models considered in this study.« less

Toward (finally!) ruling out Z and Higgs mediated dark matter models

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

Escudero, Miguel; Fermi National Accelerator Lab.; Berlin, Asher

In recent years, direct detection, indirect detection, and collider experiments have placed increasingly stringent constraints on particle dark matter, exploring much of the parameter space associated with the WIMP paradigm. In this paper, we focus on the subset of WIMP models in which the dark matter annihilates in the early universe through couplings to either the Standard Model Z or the Standard Model Higgs boson. Considering fermionic, scalar, and vector dark matter candidates within a model-independent context, we find that the overwhelming majority of these dark matter candidates are already ruled out by existing experiments. In the case of Zmore » mediated dark matter, the only scenarios that are not currently excluded are those in which the dark matter is a fermion with an axial coupling and with a mass either within a few GeV of the Z resonance (m DM ≃ m Z/2) or greater than 200 GeV, or with a vector coupling and with m DM > 6 TeV . Several Higgs mediated scenarios are currently viable if the mass of the dark matter is near the Higgs pole (m DM ≃ m H/2). Otherwise, the only scenarios that are not excluded are those in which the dark matter is a scalar (vector) heavier than 400 GeV (1160 GeV) with a Higgs portal coupling, or a fermion with a pseudoscalar (CP violating) coupling to the Standard Model Higgs boson. Furthermore, with the exception of dark matter with a purely pseudoscalar coupling to the Higgs, it is anticipated that planned direct detection experiments will probe nearly the entire range of models considered in this study.« less

An Optimization Principle for Deriving Nonequilibrium Statistical Models of Hamiltonian Dynamics

NASA Astrophysics Data System (ADS)

Turkington, Bruce

2013-08-01

A general method for deriving closed reduced models of Hamiltonian dynamical systems is developed using techniques from optimization and statistical estimation. Given a vector of resolved variables, selected to describe the macroscopic state of the system, a family of quasi-equilibrium probability densities on phase space corresponding to the resolved variables is employed as a statistical model, and the evolution of the mean resolved vector is estimated by optimizing over paths of these densities. Specifically, a cost function is constructed to quantify the lack-of-fit to the microscopic dynamics of any feasible path of densities from the statistical model; it is an ensemble-averaged, weighted, squared-norm of the residual that results from submitting the path of densities to the Liouville equation. The path that minimizes the time integral of the cost function determines the best-fit evolution of the mean resolved vector. The closed reduced equations satisfied by the optimal path are derived by Hamilton-Jacobi theory. When expressed in terms of the macroscopic variables, these equations have the generic structure of governing equations for nonequilibrium thermodynamics. In particular, the value function for the optimization principle coincides with the dissipation potential that defines the relation between thermodynamic forces and fluxes. The adjustable closure parameters in the best-fit reduced equations depend explicitly on the arbitrary weights that enter into the lack-of-fit cost function. Two particular model reductions are outlined to illustrate the general method. In each example the set of weights in the optimization principle contracts into a single effective closure parameter.

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.

Markov random field model-based edge-directed image interpolation.

PubMed

Li, Min; Nguyen, Truong Q

2008-07-01

This paper presents an edge-directed image interpolation algorithm. In the proposed algorithm, the edge directions are implicitly estimated with a statistical-based approach. In opposite to explicit edge directions, the local edge directions are indicated by length-16 weighting vectors. Implicitly, the weighting vectors are used to formulate geometric regularity (GR) constraint (smoothness along edges and sharpness across edges) and the GR constraint is imposed on the interpolated image through the Markov random field (MRF) model. Furthermore, under the maximum a posteriori-MRF framework, the desired interpolated image corresponds to the minimal energy state of a 2-D random field given the low-resolution image. Simulated annealing methods are used to search for the minimal energy state from the state space. To lower the computational complexity of MRF, a single-pass implementation is designed, which performs nearly as well as the iterative optimization. Simulation results show that the proposed MRF model-based edge-directed interpolation method produces edges with strong geometric regularity. Compared to traditional methods and other edge-directed interpolation methods, the proposed method improves the subjective quality of the interpolated edges while maintaining a high PSNR level.

EEG Characteristic Extraction Method of Listening Music and Objective Estimation Method Based on Latency Structure Model in Individual Characteristics

NASA Astrophysics Data System (ADS)

Ito, Shin-Ichi; Mitsukura, Yasue; Nakamura Miyamura, Hiroko; Saito, Takafumi; Fukumi, Minoru

EEG is characterized by the unique and individual characteristics. Little research has been done to take into account the individual characteristics when analyzing EEG signals. Often the EEG has frequency components which can describe most of the significant characteristics. Then there is the difference of importance between the analyzed frequency components of the EEG. We think that the importance difference shows the individual characteristics. In this paper, we propose a new EEG extraction method of characteristic vector by a latency structure model in individual characteristics (LSMIC). The LSMIC is the latency structure model, which has personal error as the individual characteristics, based on normal distribution. The real-coded genetic algorithms (RGA) are used for specifying the personal error that is unknown parameter. Moreover we propose an objective estimation method that plots the EEG characteristic vector on a visualization space. Finally, the performance of the proposed method is evaluated using a realistic simulation and applied to a real EEG data. The result of our experiment shows the effectiveness of the proposed method.

Exotic Leptons. Higgs, Flavor and Collider Phenomenology

DOE PAGES

Altmannshofer, Wolfgang; Bauer, Martin; Carena, Marcela

2014-01-15

We study extensions of the standard model by one generation of vector-like leptons with non-standard hypercharges, which allow for a sizable modification of the h → γγ decay rate for new lepton masses in the 300 GeV-1 TeV range. We also analyze vacuum stability implications for different hypercharges. Effects in h → Zγ are typically much smaller than in h → γγ, but distinct among the considered hypercharge assignments. Non-standard hypercharges constrain or entirely forbid possible mixing operators with standard model leptons. As a consequence, the leading contributions to the experimentally strongly constrained electric dipole moments of standard model fermionsmore » are only generated at the two loop level by the new CP violating sources of the considered setups. Furthermore, we derive the bounds from dipole moments, electro-weak precision observables and lepton flavor violating processes, and discuss their implications. Finally, we examine the production and decay channels of the vector-like leptons at the LHC, and find that signatures with multiple light leptons or taus are already probing interesting regions of parameter space.« less

Studies of the Three-Nucleon System Dynamics in the Deuteron-Proton Breakup Reaction

NASA Astrophysics Data System (ADS)

Ciepał, I.; Kłos, B.; Stephan, E.; Kistryn, St.; Biegun, A.; Bodek, K.; Deltuva, A.; Epelbaum, E.; Eslami-Kalantari, M.; Fonseca, A. C.; Golak, J.; Jha, V.; Kalantar-Nayestanaki, N.; Kamada, H.; Khatri, G.; Kirillov, Da.; Kirillov, Di.; Kliczewski, St.; Kozela, A.; Kravcikova, M.; Machner, H.; Magiera, A.; Martinska, G.; Messchendorp, J.; Nogga, A.; Parol, W.; Ramazani-Moghaddam-Arani, A.; Roy, B. J.; Sakai, H.; Sekiguchi, K.; Sitnik, I.; Siudak, R.; Skibiński, R.; Sworst, R.; Urban, J.; Witała, H.; Zejma, J.

2014-03-01

One of the most important goals of modern nuclear physics is to contruct nuclear force model which properly describes the experimental data. To develop and test predictions of current models the breakup 1H(overrightarrow d, pp)n reaction was investigated experimentally at 100 and 130 MeV deuteron beam energies. Rich set of data for cross section, vector and tensor analyzing powers was obtained with the use of the SALAD and BINA detectors at KVI and Germanium Wall setup at FZ-Jülich. Results are compared with various theoretical approaches which describe the three-nucleon (3N) system dynamics. For correct description of the cross section data both, three-nucleon force (3NF) and Coulomb force, have to be included into calculations and influence of those ingredients is seizable at specific parts of the phase space. In case of the vector analyzing powers very low sensitivity to any effects beyond nucleon-nucleon interaction was found. At 130 MeV, the Axy data are not correctly described when 3NF models are included into calculations.

Spatial orientation of caloric nystagmus in semicircular canal-plugged monkeys.

PubMed

Arai, Yasuko; Yakushin, Sergei B; Cohen, Bernard; Suzuki, Jun-Ichi; Raphan, Theodore

2002-08-01

We studied caloric nystagmus before and after plugging all six semicircular canals to determine whether velocity storage contributed to the spatial orientation of caloric nystagmus. Monkeys were stimulated unilaterally with cold ( approximately 20 degrees C) water while upright, supine, prone, right-side down, and left-side down. The decline in the slow phase velocity vector was determined over the last 37% of the nystagmus, at a time when the response was largely due to activation of velocity storage. Before plugging, yaw components varied with the convective flow of endolymph in the lateral canals in all head orientations. Plugging blocked endolymph flow, eliminating convection currents. Despite this, caloric nystagmus was readily elicited, but the horizontal component was always toward the stimulated (ipsilateral) side, regardless of head position relative to gravity. When upright, the slow phase velocity vector was close to the yaw and spatial vertical axes. Roll components became stronger in supine and prone positions, and vertical components were enhanced in side down positions. In each case, this brought the velocity vectors toward alignment with the spatial vertical. Consistent with principles governing the orientation of velocity storage, when the yaw component of the velocity vector was positive, the cross-coupled pitch or roll components brought the vector upward in space. Conversely, when yaw eye velocity vector was downward in the head coordinate frame, i.e., negative, pitch and roll were downward in space. The data could not be modeled simply by a reduction in activity in the ipsilateral vestibular nerve, which would direct the velocity vector along the roll direction. Since there is no cross coupling from roll to yaw, velocity storage alone could not rotate the vector to fit the data. We postulated, therefore, that cooling had caused contraction of the endolymph in the plugged canals. This contraction would deflect the cupula toward the plug, simulating ampullofugal flow of endolymph. Inhibition and excitation induced by such cupula deflection fit the data well in the upright position but not in lateral or prone/supine conditions. Data fits in these positions required the addition of a spatially orientated, velocity storage component. We conclude, therefore, that three factors produce cold caloric nystagmus after canal plugging: inhibition of activity in ampullary nerves, contraction of endolymph in the stimulated canals, and orientation of eye velocity to gravity through velocity storage. Although the response to convection currents dominates the normal response to caloric stimulation, velocity storage probably also contributes to the orientation of eye velocity.

Robust Kalman filtering cooperated Elman neural network learning for vision-sensing-based robotic manipulation with global stability.

PubMed

Zhong, Xungao; Zhong, Xunyu; Peng, Xiafu

2013-10-08

In this paper, a global-state-space visual servoing scheme is proposed for uncalibrated model-independent robotic manipulation. The scheme is based on robust Kalman filtering (KF), in conjunction with Elman neural network (ENN) learning techniques. The global map relationship between the vision space and the robotic workspace is learned using an ENN. This learned mapping is shown to be an approximate estimate of the Jacobian in global space. In the testing phase, the desired Jacobian is arrived at using a robust KF to improve the ENN learning result so as to achieve robotic precise convergence of the desired pose. Meanwhile, the ENN weights are updated (re-trained) using a new input-output data pair vector (obtained from the KF cycle) to ensure robot global stability manipulation. Thus, our method, without requiring either camera or model parameters, avoids the corrupted performances caused by camera calibration and modeling errors. To demonstrate the proposed scheme's performance, various simulation and experimental results have been presented using a six-degree-of-freedom robotic manipulator with eye-in-hand configurations.

Searching for transcription factor binding sites in vector spaces

PubMed Central

2012-01-01

Background Computational approaches to transcription factor binding site identification have been actively researched in the past decade. Learning from known binding sites, new binding sites of a transcription factor in unannotated sequences can be identified. A number of search methods have been introduced over the years. However, one can rarely find one single method that performs the best on all the transcription factors. Instead, to identify the best method for a particular transcription factor, one usually has to compare a handful of methods. Hence, it is highly desirable for a method to perform automatic optimization for individual transcription factors. Results We proposed to search for transcription factor binding sites in vector spaces. This framework allows us to identify the best method for each individual transcription factor. We further introduced two novel methods, the negative-to-positive vector (NPV) and optimal discriminating vector (ODV) methods, to construct query vectors to search for binding sites in vector spaces. Extensive cross-validation experiments showed that the proposed methods significantly outperformed the ungapped likelihood under positional background method, a state-of-the-art method, and the widely-used position-specific scoring matrix method. We further demonstrated that motif subtypes of a TF can be readily identified in this framework and two variants called the k NPV and k ODV methods benefited significantly from motif subtype identification. Finally, independent validation on ChIP-seq data showed that the ODV and NPV methods significantly outperformed the other compared methods. Conclusions We conclude that the proposed framework is highly flexible. It enables the two novel methods to automatically identify a TF-specific subspace to search for binding sites. Implementations are available as source code at: http://biogrid.engr.uconn.edu/tfbs_search/. PMID:23244338

SVPWM Technique with Varying DC-Link Voltage for Common Mode Voltage Reduction in a Matrix Converter and Analytical Estimation of its Output Voltage Distortion

NASA Astrophysics Data System (ADS)

Padhee, Varsha

Common Mode Voltage (CMV) in any power converter has been the major contributor to premature motor failures, bearing deterioration, shaft voltage build up and electromagnetic interference. Intelligent control methods like Space Vector Pulse Width Modulation (SVPWM) techniques provide immense potential and flexibility to reduce CMV, thereby targeting all the afore mentioned problems. Other solutions like passive filters, shielded cables and EMI filters add to the volume and cost metrics of the entire system. Smart SVPWM techniques therefore, come with a very important advantage of being an economical solution. This thesis discusses a modified space vector technique applied to an Indirect Matrix Converter (IMC) which results in the reduction of common mode voltages and other advanced features. The conventional indirect space vector pulse-width modulation (SVPWM) method of controlling matrix converters involves the usage of two adjacent active vectors and one zero vector for both rectifying and inverting stages of the converter. By suitable selection of space vectors, the rectifying stage of the matrix converter can generate different levels of virtual DC-link voltage. This capability can be exploited for operation of the converter in different ranges of modulation indices for varying machine speeds. This results in lower common mode voltage and improves the harmonic spectrum of the output voltage, without increasing the number of switching transitions as compared to conventional modulation. To summarize it can be said that the responsibility of formulating output voltages with a particular magnitude and frequency has been transferred solely to the rectifying stage of the IMC. Estimation of degree of distortion in the three phase output voltage is another facet discussed in this thesis. An understanding of the SVPWM technique and the switching sequence of the space vectors in detail gives the potential to estimate the RMS value of the switched output voltage of any converter. This conceivably aids the sizing and design of output passive filters. An analytical estimation method has been presented to achieve this purpose for am IMC. Knowledge of the fundamental component in output voltage can be utilized to calculate its Total Harmonic Distortion (THD). The effectiveness of the proposed SVPWM algorithms and the analytical estimation technique is substantiated by simulations in MATLAB / Simulink and experiments on a laboratory prototype of the IMC. Proper comparison plots have been provided to contrast the performance of the proposed methods with the conventional SVPWM method. The behavior of output voltage distortion and CMV with variation in operating parameters like modulation index and output frequency has also been analyzed.

Ambitwistor Strings in Four Dimensions

NASA Astrophysics Data System (ADS)

Geyer, Yvonne; Lipstein, Arthur E.; Mason, Lionel

2014-08-01

We develop ambitwistor string theories for four dimensions to obtain new formulas for tree-level gauge and gravity amplitudes with arbitrary amounts of supersymmetry. Ambitwistor space is the space of complex null geodesics in complexified Minkowski space, and in contrast to earlier ambitwistor strings, we use twistors rather than vectors to represent this space. Although superficially similar to the original twistor string theories of Witten, Berkovits, and Skinner, these theories differ in the assignment of world sheet spins of the fields, rely on both twistor and dual twistor representatives for the vertex operators, and use the ambitwistor procedure for calculating correlation functions. Our models are much more flexible, no longer requiring maximal supersymmetry, and the resulting formulas for amplitudes are simpler, having substantially reduced moduli. These are supported on the solutions to the scattering equations refined according to helicity and can be checked by comparison with corresponding formulas of Witten and of Cachazo and Skinner.

ICRF Development for the Variable Specific Impulse Magnetoplasma Rocket

NASA Astrophysics Data System (ADS)

Ryan, P. M.; Baity, F. W.; Barber, G. C.; Carter, M. D.; Hoffman, D. J.; Jaeger, E. F.; Taylor, D. J.; Chang-Diaz, F. R.; Squire, J. P.; McCaskill, G.

1997-11-01

The feasibility of using magnetically vectored and rf-heated plasmas for space propulsion (F. R. Chang-Diaz, et al., Bull. Am. Phys. Soc., 41, 1541 (1996)) is being investigated experimentally on an asymmetric magnetic mirror device at the Advanced Space Propulsion Laboratory (ASPL), Johnson Space Center, NASA. Analysis of the antenna interaction with and the wave propagation through the dense plasma propulsion system is being studied at ORNL(Oak Ridge National Laboratory, managed by Lockheed Martin Energy Research Corp. for the U.S. Department of Energy under contract number DE-AC05-96OR22464.), using antenna design codes developed for ICH systems and mirror codes developed for the EBT experiment at ORNL. The present modeling effort is directed toward the ASPL experimental device. Antenna optimization and performance, as well as the design considerations for space-qualified rf components and systems (minimizing weight while maximizing reliability) will be presented.

Photovoltaic array space power plus diagnostics experiment

NASA Technical Reports Server (NTRS)

Guidice, Donald A.

1990-01-01

The objective of the Photovoltaic Array Space Power Plus Diagnostics (PASP Plus) experiment is to measure the effects of the interaction of the low- to mid-altitude space environment on the performance of a diverse set of small solar-cell arrays (planar and concentrator, representative of present and future military technologies) under differing conditions of velocity-vector orientation and simulated (by biasing) high-voltage operation. Solar arrays to be tested include Si and GaAs planar arrays and several types of GaAs concentrator arrays. Diagnostics (a Langmuir probe and a pressure gauge) and a transient pulse monitor (to measure radiated and conducted EMI during arcing) will be used to determine the impact of the environment on array operation to help verify various interactions models. Results from a successful PASP Plus flight will furnish answers to important interactions questions and provide inputs for design and test standards for photovoltaic space-power subsystems.

Meson effective mass in the isospin medium in hard-wall AdS/QCD model

NASA Astrophysics Data System (ADS)

Mamedov, Shahin

2016-02-01

We study a mass splitting of the light vector, axial-vector, and pseudoscalar mesons in the isospin medium in the framework of the hard-wall model. We write an effective mass definition for the interacting gauge fields and scalar field introduced in gauge field theory in the bulk of AdS space-time. Relying on holographic duality we obtain a formula for the effective mass of a boundary meson in terms of derivative operator over the extra bulk coordinate. The effective mass found in this way coincides with the one obtained from finding of poles of the two-point correlation function. In order to avoid introducing distinguished infrared boundaries in the quantization formula for the different mesons from the same isotriplet we introduce extra action terms at this boundary, which reduces distinguished values of this boundary to the same value. Profile function solutions and effective mass expressions were found for the in-medium ρ , a_1, and π mesons.

Dynamical Causal Modeling from a Quantum Dynamical Perspective

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

Demiralp, Emre; Demiralp, Metin

Recent research suggests that any set of first order linear vector ODEs can be converted to a set of specific vector ODEs adhering to what we have called ''Quantum Harmonical Form (QHF)''. QHF has been developed using a virtual quantum multi harmonic oscillator system where mass and force constants are considered to be time variant and the Hamiltonian is defined as a conic structure over positions and momenta to conserve the Hermiticity. As described in previous works, the conversion to QHF requires the matrix coefficient of the first set of ODEs to be a normal matrix. In this paper, thismore » limitation is circumvented using a space extension approach expanding the potential applicability of this method. Overall, conversion to QHF allows the investigation of a set of ODEs using mathematical tools available to the investigation of the physical concepts underlying quantum harmonic oscillators. The utility of QHF in the context of dynamical systems and dynamical causal modeling in behavioral and cognitive neuroscience is briefly discussed.« less

A Bag of Concepts Approach for Biomedical Document Classification Using Wikipedia Knowledge.

PubMed

Mouriño-García, Marcos A; Pérez-Rodríguez, Roberto; Anido-Rifón, Luis E

2017-01-01

The ability to efficiently review the existing literature is essential for the rapid progress of research. This paper describes a classifier of text documents, represented as vectors in spaces of Wikipedia concepts, and analyses its suitability for classification of Spanish biomedical documents when only English documents are available for training. We propose the cross-language concept matching (CLCM) technique, which relies on Wikipedia interlanguage links to convert concept vectors from the Spanish to the English space. The performance of the classifier is compared to several baselines: a classifier based on machine translation, a classifier that represents documents after performing Explicit Semantic Analysis (ESA), and a classifier that uses a domain-specific semantic an- notator (MetaMap). The corpus used for the experiments (Cross-Language UVigoMED) was purpose-built for this study, and it is composed of 12,832 English and 2,184 Spanish MEDLINE abstracts. The performance of our approach is superior to any other state-of-the art classifier in the benchmark, with performance increases up to: 124% over classical machine translation, 332% over MetaMap, and 60 times over the classifier based on ESA. The results have statistical significance, showing p-values < 0.0001. Using knowledge mined from Wikipedia to represent documents as vectors in a space of Wikipedia concepts and translating vectors between language-specific concept spaces, a cross-language classifier can be built, and it performs better than several state-of-the-art classifiers. Schattauer GmbH.

A Bag of Concepts Approach for Biomedical Document Classification Using Wikipedia Knowledge*. Spanish-English Cross-language Case Study.

PubMed

Mouriño-García, Marcos A; Pérez-Rodríguez, Roberto; Anido-Rifón, Luis E

2017-10-26

The ability to efficiently review the existing literature is essential for the rapid progress of research. This paper describes a classifier of text documents, represented as vectors in spaces of Wikipedia concepts, and analyses its suitability for classification of Spanish biomedical documents when only English documents are available for training. We propose the cross-language concept matching (CLCM) technique, which relies on Wikipedia interlanguage links to convert concept vectors from the Spanish to the English space. The performance of the classifier is compared to several baselines: a classifier based on machine translation, a classifier that represents documents after performing Explicit Semantic Analysis (ESA), and a classifier that uses a domain-specific semantic annotator (MetaMap). The corpus used for the experiments (Cross-Language UVigoMED) was purpose-built for this study, and it is composed of 12,832 English and 2,184 Spanish MEDLINE abstracts. The performance of our approach is superior to any other state-of-the art classifier in the benchmark, with performance increases up to: 124% over classical machine translation, 332% over MetaMap, and 60 times over the classifier based on ESA. The results have statistical significance, showing p-values < 0.0001. Using knowledge mined from Wikipedia to represent documents as vectors in a space of Wikipedia concepts and translating vectors between language-specific concept spaces, a cross-language classifier can be built, and it performs better than several state-of-the-art classifiers.

Implementation of the Orbital Maneuvering Systems Engine and Thrust Vector Control for the European Service Module

NASA Technical Reports Server (NTRS)

Millard, Jon

2014-01-01

The European Space Agency (ESA) has entered into a partnership with the National Aeronautics and Space Administration (NASA) to develop and provide the Service Module (SM) for the Orion Multipurpose Crew Vehicle (MPCV) Program. The European Service Module (ESM) will provide main engine thrust by utilizing the Space Shuttle Program Orbital Maneuvering System Engine (OMS-E). Thrust Vector Control (TVC) of the OMS-E will be provided by the Orbital Maneuvering System (OMS) TVC, also used during the Space Shuttle Program. NASA will be providing the OMS-E and OMS TVC to ESA as Government Furnished Equipment (GFE) to integrate into the ESM. This presentation will describe the OMS-E and OMS TVC and discuss the implementation of the hardware for the ESM.

Modal vector estimation for closely spaced frequency modes

NASA Technical Reports Server (NTRS)

Craig, R. R., Jr.; Chung, Y. T.; Blair, M.

1982-01-01

Techniques for obtaining improved modal vector estimates for systems with closely spaced frequency modes are discussed. In describing the dynamical behavior of a complex structure modal parameters are often analyzed: undamped natural frequency, mode shape, modal mass, modal stiffness and modal damping. From both an analytical standpoint and an experimental standpoint, identification of modal parameters is more difficult if the system has repeated frequencies or even closely spaced frequencies. The more complex the structure, the more likely it is to have closely spaced frequencies. This makes it difficult to determine valid mode shapes using single shaker test methods. By employing band selectable analysis (zoom) techniques and by employing Kennedy-Pancu circle fitting or some multiple degree of freedom (MDOF) curve fit procedure, the usefulness of the single shaker approach can be extended.

Discrete- vs. Continuous-Time Modeling of Unequally Spaced Experience Sampling Method Data.

PubMed

de Haan-Rietdijk, Silvia; Voelkle, Manuel C; Keijsers, Loes; Hamaker, Ellen L

2017-01-01

The Experience Sampling Method is a common approach in psychological research for collecting intensive longitudinal data with high ecological validity. One characteristic of ESM data is that it is often unequally spaced, because the measurement intervals within a day are deliberately varied, and measurement continues over several days. This poses a problem for discrete-time (DT) modeling approaches, which are based on the assumption that all measurements are equally spaced. Nevertheless, DT approaches such as (vector) autoregressive modeling are often used to analyze ESM data, for instance in the context of affective dynamics research. There are equivalent continuous-time (CT) models, but they are more difficult to implement. In this paper we take a pragmatic approach and evaluate the practical relevance of the violated model assumption in DT AR(1) and VAR(1) models, for the N = 1 case. We use simulated data under an ESM measurement design to investigate the bias in the parameters of interest under four different model implementations, ranging from the true CT model that accounts for all the exact measurement times, to the crudest possible DT model implementation, where even the nighttime is treated as a regular interval. An analysis of empirical affect data illustrates how the differences between DT and CT modeling can play out in practice. We find that the size and the direction of the bias in DT (V)AR models for unequally spaced ESM data depend quite strongly on the true parameter in addition to data characteristics. Our recommendation is to use CT modeling whenever possible, especially now that new software implementations have become available.

Discrete- vs. Continuous-Time Modeling of Unequally Spaced Experience Sampling Method Data

PubMed Central

de Haan-Rietdijk, Silvia; Voelkle, Manuel C.; Keijsers, Loes; Hamaker, Ellen L.

2017-01-01

The Experience Sampling Method is a common approach in psychological research for collecting intensive longitudinal data with high ecological validity. One characteristic of ESM data is that it is often unequally spaced, because the measurement intervals within a day are deliberately varied, and measurement continues over several days. This poses a problem for discrete-time (DT) modeling approaches, which are based on the assumption that all measurements are equally spaced. Nevertheless, DT approaches such as (vector) autoregressive modeling are often used to analyze ESM data, for instance in the context of affective dynamics research. There are equivalent continuous-time (CT) models, but they are more difficult to implement. In this paper we take a pragmatic approach and evaluate the practical relevance of the violated model assumption in DT AR(1) and VAR(1) models, for the N = 1 case. We use simulated data under an ESM measurement design to investigate the bias in the parameters of interest under four different model implementations, ranging from the true CT model that accounts for all the exact measurement times, to the crudest possible DT model implementation, where even the nighttime is treated as a regular interval. An analysis of empirical affect data illustrates how the differences between DT and CT modeling can play out in practice. We find that the size and the direction of the bias in DT (V)AR models for unequally spaced ESM data depend quite strongly on the true parameter in addition to data characteristics. Our recommendation is to use CT modeling whenever possible, especially now that new software implementations have become available. PMID:29104554

Odor Impression Prediction from Mass Spectra.

PubMed

Nozaki, Yuji; Nakamoto, Takamichi

2016-01-01

The sense of smell arises from the perception of odors from chemicals. However, the relationship between the impression of odor and the numerous physicochemical parameters has yet to be understood owing to its complexity. As such, there is no established general method for predicting the impression of odor of a chemical only from its physicochemical properties. In this study, we designed a novel predictive model based on an artificial neural network with a deep structure for predicting odor impression utilizing the mass spectra of chemicals, and we conducted a series of computational analyses to evaluate its performance. Feature vectors extracted from the original high-dimensional space using two autoencoders equipped with both input and output layers in the model are used to build a mapping function from the feature space of mass spectra to the feature space of sensory data. The results of predictions obtained by the proposed new method have notable accuracy (R≅0.76) in comparison with a conventional method (R≅0.61).

Towards causal patch physics in dS/CFT

NASA Astrophysics Data System (ADS)

Neiman, Yasha

2018-01-01

This contribution is a status report on a research program aimed at obtaining quantum-gravitational physics inside a cosmological horizon through dS/CFT, i.e. through a holographic description at past/future infinity of de Sitter space. The program aims to bring together two main elements. The first is the observation by Anninos, Hartman and Strominger that Vasiliev's higher-spin gravity provides a working model for dS/CFT in 3+1 dimensions. The second is the proposal by Parikh, Savonije and Verlinde that dS/CFT may prove more tractable if one works in so-called "elliptic" de Sitter space - a folded-in-half version of global de Sitter where antipodal points have been identified. We review some relevant progress concerning quantum field theory on elliptic de Sitter space, higher-spin gravity and its holographic duality with a free vector model. We present our reasons for optimism that the approach outlined here will lead to a full holographic description of quantum (higher-spin) gravity in the causal patch of a de Sitter observer.

A robust variant of block Jacobi-Davidson for extracting a large number of eigenpairs: Application to grid-based real-space density functional theory

NASA Astrophysics Data System (ADS)

Lee, M.; Leiter, K.; Eisner, C.; Breuer, A.; Wang, X.

2017-09-01

In this work, we investigate a block Jacobi-Davidson (J-D) variant suitable for sparse symmetric eigenproblems where a substantial number of extremal eigenvalues are desired (e.g., ground-state real-space quantum chemistry). Most J-D algorithm variations tend to slow down as the number of desired eigenpairs increases due to frequent orthogonalization against a growing list of solved eigenvectors. In our specification of block J-D, all of the steps of the algorithm are performed in clusters, including the linear solves, which allows us to greatly reduce computational effort with blocked matrix-vector multiplies. In addition, we move orthogonalization against locked eigenvectors and working eigenvectors outside of the inner loop but retain the single Ritz vector projection corresponding to the index of the correction vector. Furthermore, we minimize the computational effort by constraining the working subspace to the current vectors being updated and the latest set of corresponding correction vectors. Finally, we incorporate accuracy thresholds based on the precision required by the Fermi-Dirac distribution. The net result is a significant reduction in the computational effort against most previous block J-D implementations, especially as the number of wanted eigenpairs grows. We compare our approach with another robust implementation of block J-D (JDQMR) and the state-of-the-art Chebyshev filter subspace (CheFSI) method for various real-space density functional theory systems. Versus CheFSI, for first-row elements, our method yields competitive timings for valence-only systems and 4-6× speedups for all-electron systems with up to 10× reduced matrix-vector multiplies. For all-electron calculations on larger elements (e.g., gold) where the wanted spectrum is quite narrow compared to the full spectrum, we observe 60× speedup with 200× fewer matrix-vector multiples vs. CheFSI.

A robust variant of block Jacobi-Davidson for extracting a large number of eigenpairs: Application to grid-based real-space density functional theory.

PubMed

Lee, M; Leiter, K; Eisner, C; Breuer, A; Wang, X

2017-09-21

In this work, we investigate a block Jacobi-Davidson (J-D) variant suitable for sparse symmetric eigenproblems where a substantial number of extremal eigenvalues are desired (e.g., ground-state real-space quantum chemistry). Most J-D algorithm variations tend to slow down as the number of desired eigenpairs increases due to frequent orthogonalization against a growing list of solved eigenvectors. In our specification of block J-D, all of the steps of the algorithm are performed in clusters, including the linear solves, which allows us to greatly reduce computational effort with blocked matrix-vector multiplies. In addition, we move orthogonalization against locked eigenvectors and working eigenvectors outside of the inner loop but retain the single Ritz vector projection corresponding to the index of the correction vector. Furthermore, we minimize the computational effort by constraining the working subspace to the current vectors being updated and the latest set of corresponding correction vectors. Finally, we incorporate accuracy thresholds based on the precision required by the Fermi-Dirac distribution. The net result is a significant reduction in the computational effort against most previous block J-D implementations, especially as the number of wanted eigenpairs grows. We compare our approach with another robust implementation of block J-D (JDQMR) and the state-of-the-art Chebyshev filter subspace (CheFSI) method for various real-space density functional theory systems. Versus CheFSI, for first-row elements, our method yields competitive timings for valence-only systems and 4-6× speedups for all-electron systems with up to 10× reduced matrix-vector multiplies. For all-electron calculations on larger elements (e.g., gold) where the wanted spectrum is quite narrow compared to the full spectrum, we observe 60× speedup with 200× fewer matrix-vector multiples vs. CheFSI.

Cosmology in generalized Proca theories

NASA Astrophysics Data System (ADS)

De Felice, Antonio; Heisenberg, Lavinia; Kase, Ryotaro; Mukohyama, Shinji; Tsujikawa, Shinji; Zhang, Ying-li

2016-06-01

We consider a massive vector field with derivative interactions that propagates only the 3 desired polarizations (besides two tensor polarizations from gravity) with second-order equations of motion in curved space-time. The cosmological implications of such generalized Proca theories are investigated for both the background and the linear perturbation by taking into account the Lagrangian up to quintic order. In the presence of a matter fluid with a temporal component of the vector field, we derive the background equations of motion and show the existence of de Sitter solutions relevant to the late-time cosmic acceleration. We also obtain conditions for the absence of ghosts and Laplacian instabilities of tensor, vector, and scalar perturbations in the small-scale limit. Our results are applied to concrete examples of the general functions in the theory, which encompass vector Galileons as a specific case. In such examples, we show that the de Sitter fixed point is always a stable attractor and study viable parameter spaces in which the no-ghost and stability conditions are satisfied during the cosmic expansion history.

GNSS Single Frequency, Single Epoch Reliable Attitude Determination Method with Baseline Vector Constraint.

PubMed

Gong, Ang; Zhao, Xiubin; Pang, Chunlei; Duan, Rong; Wang, Yong

2015-12-02

For Global Navigation Satellite System (GNSS) single frequency, single epoch attitude determination, this paper proposes a new reliable method with baseline vector constraint. First, prior knowledge of baseline length, heading, and pitch obtained from other navigation equipment or sensors are used to reconstruct objective function rigorously. Then, searching strategy is improved. It substitutes gradually Enlarged ellipsoidal search space for non-ellipsoidal search space to ensure correct ambiguity candidates are within it and make the searching process directly be carried out by least squares ambiguity decorrelation algorithm (LAMBDA) method. For all vector candidates, some ones are further eliminated by derived approximate inequality, which accelerates the searching process. Experimental results show that compared to traditional method with only baseline length constraint, this new method can utilize a priori baseline three-dimensional knowledge to fix ambiguity reliably and achieve a high success rate. Experimental tests also verify it is not very sensitive to baseline vector error and can perform robustly when angular error is not great.

The application of SVR model in the improvement of QbD: a case study of the extraction of podophyllotoxin.

PubMed

Zhai, Chun-Hui; Xuan, Jian-Bang; Fan, Hai-Liu; Zhao, Teng-Fei; Jiang, Jian-Lan

2018-05-03

In order to make a further optimization of process design via increasing the stability of design space, we brought in the model of Support Vector Regression (SVR). In this work, the extraction of podophyllotoxin was researched as a case study based on Quality by Design (QbD). We compared the fitting effect of SVR and the most used quadratic polynomial model (QPM) in QbD, and an analysis was made between the two design spaces obtained by SVR and QPM. As a result, the SVR stayed ahead of QPM in prediction accuracy, the stability of model and the generalization ability. The introduction of SVR into QbD made the extraction process of podophyllotoxin well designed and easier to control. The better fitting effect of SVR improved the application effect of QbD and the universal applicability of SVR, especially for non-linear, complicated and weak-regularity problems, widened the application field of QbD.

Use of digital control theory state space formalism for feedback at SLC

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

Himel, T.; Hendrickson, L.; Rouse, F.

The algorithms used in the database-driven SLC fast-feedback system are based on the state space formalism of digital control theory. These are implemented as a set of matrix equations which use a Kalman filter to estimate a vector of states from a vector of measurements, and then apply a gain matrix to determine the actuator settings from the state vector. The matrices used in the calculation are derived offline using Linear Quadratic Gaussian minimization. For a given noise spectrum, this procedure minimizes the rms of the states (e.g., the position or energy of the beam). The offline program also allowsmore » simulation of the loop's response to arbitrary inputs, and calculates its frequency response. 3 refs., 3 figs.« less

A novel double fine guide sensor design on space telescope

NASA Astrophysics Data System (ADS)

Zhang, Xu-xu; Yin, Da-yi

2018-02-01

To get high precision attitude for space telescope, a double marginal FOV (field of view) FGS (Fine Guide Sensor) is proposed. It is composed of two large area APS CMOS sensors and both share the same lens in main light of sight. More star vectors can be get by two FGS and be used for high precision attitude determination. To improve star identification speed, the vector cross product in inter-star angles for small marginal FOV different from traditional way is elaborated and parallel processing method is applied to pyramid algorithm. The star vectors from two sensors are then used to attitude fusion with traditional QUEST algorithm. The simulation results show that the system can get high accuracy three axis attitudes and the scheme is feasibility.

Constraining new physics models with isotope shift spectroscopy

NASA Astrophysics Data System (ADS)

Frugiuele, Claudia; Fuchs, Elina; Perez, Gilad; Schlaffer, Matthias

2017-07-01

Isotope shifts of transition frequencies in atoms constrain generic long- and intermediate-range interactions. We focus on new physics scenarios that can be most strongly constrained by King linearity violation such as models with B -L vector bosons, the Higgs portal, and chameleon models. With the anticipated precision, King linearity violation has the potential to set the strongest laboratory bounds on these models in some regions of parameter space. Furthermore, we show that this method can probe the couplings relevant for the protophobic interpretation of the recently reported Be anomaly. We extend the formalism to include an arbitrary number of transitions and isotope pairs and fit the new physics coupling to the currently available isotope shift measurements.

Age- and bite-structured models for vector-borne diseases.

PubMed

Rock, K S; Wood, D A; Keeling, M J

2015-09-01

The biology and behaviour of biting insects is a vitally important aspect in the spread of vector-borne diseases. This paper aims to determine, through the use of mathematical models, what effect incorporating vector senescence and realistic feeding patterns has on disease. A novel model is developed to enable the effects of age- and bite-structure to be examined in detail. This original PDE framework extends previous age-structured models into a further dimension to give a new insight into the role of vector biting and its interaction with vector mortality and spread of disease. Through the PDE model, the roles of the vector death and bite rates are examined in a way which is impossible under the traditional ODE formulation. It is demonstrated that incorporating more realistic functions for vector biting and mortality in a model may give rise to different dynamics than those seen under a more simple ODE formulation. The numerical results indicate that the efficacy of control methods that increase vector mortality may not be as great as predicted under a standard host-vector model, whereas other controls including treatment of humans may be more effective than previously thought. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Real-time optical laboratory solution of parabolic differential equations

NASA Technical Reports Server (NTRS)

Casasent, David; Jackson, James

1988-01-01

An optical laboratory matrix-vector processor is used to solve parabolic differential equations (the transient diffusion equation with two space variables and time) by an explicit algorithm. This includes optical matrix-vector nonbase-2 encoded laboratory data, the combination of nonbase-2 and frequency-multiplexed data on such processors, a high-accuracy optical laboratory solution of a partial differential equation, new data partitioning techniques, and a discussion of a multiprocessor optical matrix-vector architecture.

A Deep Similarity Metric Learning Model for Matching Text Chunks to Spatial Entities

NASA Astrophysics Data System (ADS)

Ma, K.; Wu, L.; Tao, L.; Li, W.; Xie, Z.

2017-12-01

The matching of spatial entities with related text is a long-standing research topic that has received considerable attention over the years. This task aims at enrich the contents of spatial entity, and attach the spatial location information to the text chunk. In the data fusion field, matching spatial entities with the corresponding describing text chunks has a big range of significance. However, the most traditional matching methods often rely fully on manually designed, task-specific linguistic features. This work proposes a Deep Similarity Metric Learning Model (DSMLM) based on Siamese Neural Network to learn similarity metric directly from the textural attributes of spatial entity and text chunk. The low-dimensional feature representation of the space entity and the text chunk can be learned separately. By employing the Cosine distance to measure the matching degree between the vectors, the model can make the matching pair vectors as close as possible. Mearnwhile, it makes the mismatching as far apart as possible through supervised learning. In addition, extensive experiments and analysis on geological survey data sets show that our DSMLM model can effectively capture the matching characteristics between the text chunk and the spatial entity, and achieve state-of-the-art performance.

Predicting and Mitigating Outbreaks of Vector-Borne Disease Utilizing Satellite Remote Sensing Technology and Models

NASA Technical Reports Server (NTRS)

Estes, Sue; Haynes, John; Kiang, Richard; Brown, Molly; Reisen, William

2008-01-01

Satellite earth observations present a unique vantage point of the earth's environment from space which offers a wealth of health applications for the imaginative investigator. The session will present research results of the remote sensing environmental observations of earth and health applications. This session will an overview of many of the NASA public health applications using Remote Sensing Data and will also discuss opportunities to become a research collaborator with NASA.

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.

Large Animal Models for Foamy Virus Vector Gene Therapy

PubMed Central

Trobridge, Grant D.; Horn, Peter A.; Beard, Brian C.; Kiem, Hans-Peter

2012-01-01

Foamy virus (FV) vectors have shown great promise for hematopoietic stem cell (HSC) gene therapy. Their ability to efficiently deliver transgenes to multi-lineage long-term repopulating cells in large animal models suggests they will be effective for several human hematopoietic diseases. Here, we review FV vector studies in large animal models, including the use of FV vectors with the mutant O6-methylguanine-DNA methyltransferase, MGMTP140K to increase the number of genetically modified cells after transplantation. In these studies, FV vectors have mediated efficient gene transfer to polyclonal repopulating cells using short ex vivo transduction protocols designed to minimize the negative effects of ex vivo culture on stem cell engraftment. In this regard, FV vectors appear superior to gammaretroviral vectors, which require longer ex vivo culture to effect efficient transduction. FV vectors have also compared favorably with lentiviral vectors when directly compared in the dog model. FV vectors have corrected leukocyte adhesion deficiency and pyruvate kinase deficiency in the dog large animal model. FV vectors also appear safer than gammaretroviral vectors based on a reduced frequency of integrants near promoters and also near proto-oncogenes in canine repopulating cells. Together, these studies suggest that FV vectors should be highly effective for several human hematopoietic diseases, including those that will require relatively high percentages of gene-modified cells to achieve clinical benefit. PMID:23223198

Uniqueness of thermodynamic projector and kinetic basis of molecular individualism

NASA Astrophysics Data System (ADS)

Gorban, Alexander N.; Karlin, Iliya V.

2004-05-01

Three results are presented: First, we solve the problem of persistence of dissipation for reduction of kinetic models. Kinetic equations with thermodynamic Lyapunov functions are studied. Uniqueness of the thermodynamic projector is proven: There exists only one projector which transforms any vector field equipped with the given Lyapunov function into a vector field with the same Lyapunov function for a given anzatz manifold which is not tangent to the Lyapunov function levels. Second, we use the thermodynamic projector for developing the short memory approximation and coarse-graining for general nonlinear dynamic systems. We prove that in this approximation the entropy production increases. ( The theorem about entropy overproduction.) In example, we apply the thermodynamic projector to derive the equations of reduced kinetics for the Fokker-Planck equation. A new class of closures is developed, the kinetic multipeak polyhedra. Distributions of this type are expected in kinetic models with multidimensional instability as universally as the Gaussian distribution appears for stable systems. The number of possible relatively stable states of a nonequilibrium system grows as 2 m, and the number of macroscopic parameters is in order mn, where n is the dimension of configuration space, and m is the number of independent unstable directions in this space. The elaborated class of closures and equations pretends to describe the effects of “molecular individualism”. This is the third result.

Mapping the Indonesian territory, based on pollution, social demography and geographical data, using self organizing feature map

NASA Astrophysics Data System (ADS)

Hernawati, Kuswari; Insani, Nur; Bambang S. H., M.; Nur Hadi, W.; Sahid

2017-08-01

This research aims to mapping the 33 (thirty-three) provinces in Indonesia, based on the data on air, water and soil pollution, as well as social demography and geography data, into a clustered model. The method used in this study was unsupervised method that combines the basic concept of Kohonen or Self-Organizing Feature Maps (SOFM). The method is done by providing the design parameters for the model based on data related directly/ indirectly to pollution, which are the demographic and social data, pollution levels of air, water and soil, as well as the geographical situation of each province. The parameters used consists of 19 features/characteristics, including the human development index, the number of vehicles, the availability of the plant's water absorption and flood prevention, as well as geographic and demographic situation. The data used were secondary data from the Central Statistics Agency (BPS), Indonesia. The data are mapped into SOFM from a high-dimensional vector space into two-dimensional vector space according to the closeness of location in term of Euclidean distance. The resulting outputs are represented in clustered grouping. Thirty-three provinces are grouped into five clusters, where each cluster has different features/characteristics and level of pollution. The result can used to help the efforts on prevention and resolution of pollution problems on each cluster in an effective and efficient way.

A diagram for evaluating multiple aspects of model performance in simulating vector fields

NASA Astrophysics Data System (ADS)

Xu, Zhongfeng; Hou, Zhaolu; Han, Ying; Guo, Weidong

2016-12-01

Vector quantities, e.g., vector winds, play an extremely important role in climate systems. The energy and water exchanges between different regions are strongly dominated by wind, which in turn shapes the regional climate. Thus, how well climate models can simulate vector fields directly affects model performance in reproducing the nature of a regional climate. This paper devises a new diagram, termed the vector field evaluation (VFE) diagram, which is a generalized Taylor diagram and able to provide a concise evaluation of model performance in simulating vector fields. The diagram can measure how well two vector fields match each other in terms of three statistical variables, i.e., the vector similarity coefficient, root mean square length (RMSL), and root mean square vector difference (RMSVD). Similar to the Taylor diagram, the VFE diagram is especially useful for evaluating climate models. The pattern similarity of two vector fields is measured by a vector similarity coefficient (VSC) that is defined by the arithmetic mean of the inner product of normalized vector pairs. Examples are provided, showing that VSC can identify how close one vector field resembles another. Note that VSC can only describe the pattern similarity, and it does not reflect the systematic difference in the mean vector length between two vector fields. To measure the vector length, RMSL is included in the diagram. The third variable, RMSVD, is used to identify the magnitude of the overall difference between two vector fields. Examples show that the VFE diagram can clearly illustrate the extent to which the overall RMSVD is attributed to the systematic difference in RMSL and how much is due to the poor pattern similarity.

String-inspired special grand unification

NASA Astrophysics Data System (ADS)

Yamatsu, Naoki

2017-10-01

We discuss a grand unified theory (GUT) based on an SO(32) GUT gauge group broken to its subgroups including a special subgroup. In the SO(32) GUT on the six-dimensional (6D) orbifold space M^4× T^2/\\mathbb{Z}_2, one generation of the standard model fermions can be embedded into a 6D bulk Weyl fermion in the SO(32) vector representation. We show that for a three-generation model, all the 6D and 4D gauge anomalies in the bulk and on the fixed points are canceled out without exotic chiral fermions at low energies.

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.

Non-lightlike ruled surfaces with constant curvatures in Minkowski 3-space

NASA Astrophysics Data System (ADS)

Ali, Ahmad Tawfik

We study the non-lightlike ruled surfaces in Minkowski 3-space with non-lightlike base curve c(s) =∫(αt + βn + γb)ds, where t, n, b are the tangent, principal normal and binormal vectors of an arbitrary timelike curve Γ(s). Some important results of flat, minimal, II-minimal and II-flat non-lightlike ruled surfaces are studied. Finally, the following interesting theorem is proved: the only non-zero constant mean curvature (CMC) non-lightlike ruled surface is developable timelike ruled surface generated by binormal vector.

Dual-scale topology optoelectronic processor.

PubMed

Marsden, G C; Krishnamoorthy, A V; Esener, S C; Lee, S H

1991-12-15

The dual-scale topology optoelectronic processor (D-STOP) is a parallel optoelectronic architecture for matrix algebraic processing. The architecture can be used for matrix-vector multiplication and two types of vector outer product. The computations are performed electronically, which allows multiplication and summation concepts in linear algebra to be generalized to various nonlinear or symbolic operations. This generalization permits the application of D-STOP to many computational problems. The architecture uses a minimum number of optical transmitters, which thereby reduces fabrication requirements while maintaining area-efficient electronics. The necessary optical interconnections are space invariant, minimizing space-bandwidth requirements.

SpacePy - a Python-based library of tools for the space sciences

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

Morley, Steven K; Welling, Daniel T; Koller, Josef

Space science deals with the bodies within the solar system and the interplanetary medium; the primary focus is on atmospheres and above - at Earth the short timescale variation in the the geomagnetic field, the Van Allen radiation belts and the deposition of energy into the upper atmosphere are key areas of investigation. SpacePy is a package for Python, targeted at the space sciences, that aims to make basic data analysis, modeling and visualization easier. It builds on the capabilities of the well-known NumPy and MatPlotLib packages. Publication quality output direct from analyses is emphasized. The SpacePy project seeks tomore » promote accurate and open research standards by providing an open environment for code development. In the space physics community there has long been a significant reliance on proprietary languages that restrict free transfer of data and reproducibility of results. By providing a comprehensive, open-source library of widely used analysis and visualization tools in a free, modern and intuitive language, we hope that this reliance will be diminished. SpacePy includes implementations of widely used empirical models, statistical techniques used frequently in space science (e.g. superposed epoch analysis), and interfaces to advanced tools such as electron drift shell calculations for radiation belt studies. SpacePy also provides analysis and visualization tools for components of the Space Weather Modeling Framework - currently this only includes the BATS-R-US 3-D magnetohydrodynamic model and the RAM ring current model - including streamline tracing in vector fields. Further development is currently underway. External libraries, which include well-known magnetic field models, high-precision time conversions and coordinate transformations are wrapped for access from Python using SWIG and f2py. The rest of the tools have been implemented directly in Python. The provision of open-source tools to perform common tasks will provide openness in the analysis methods employed in scientific studies and will give access to advanced tools to all space scientists regardless of affiliation or circumstance.« less

Protein folding: complex potential for the driving force in a two-dimensional space of collective variables.

PubMed

Chekmarev, Sergei F

2013-10-14

Using the Helmholtz decomposition of the vector field of folding fluxes in a two-dimensional space of collective variables, a potential of the driving force for protein folding is introduced. The potential has two components. One component is responsible for the source and sink of the folding flows, which represent respectively, the unfolded states and the native state of the protein, and the other, which accounts for the flow vorticity inherently generated at the periphery of the flow field, is responsible for the canalization of the flow between the source and sink. The theoretical consideration is illustrated by calculations for a model β-hairpin protein.

Exact Solution of Klein-Gordon and Dirac Equations with Snyder-de Sitter Algebra

NASA Astrophysics Data System (ADS)

Merad, M.; Hadj Moussa, M.

2018-01-01

In this paper, we present the exact solution of the (1+1)-dimensional relativistic Klein-Gordon and Dirac equations with linear vector and scalar potentials in the framework of deformed Snyder-de Sitter model. We introduce some changes of variables, we show that a one-dimensional linear potential for the relativistic system in a space deformed can be equivalent to the trigonometric Rosen-Morse potential in a regular space. In both cases, we determine explicitly the energy eigenvalues and their corresponding eigenfunctions expressed in terms of Romonovski polynomials. The limiting cases are analyzed for α 1 and α 2 → 0 and are compared with those of literature.

Perturbative matching of lattice and continuum heavy-light currents with NRQCD heavy quarks

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

Morningstar, C.J.; Shigemitsu, J.

1999-05-01

The temporal and spatial components of the heavy-light vector current and the spatial components of the axial-vector current are expressed in terms of lattice-regulated operators suitable for simulations of {ital B} and {ital D} mesons. The currents are constructed by matching the appropriate scattering amplitudes in continuum QCD and a lattice model to one-loop order in perturbation theory. In the lattice theory, the heavy quarks are treated using the nonrelativistic (NRQCD) formulation and the light quarks are described by the tadpole-improved clover action. The light quarks are treated as massless. Our currents include relativistic and discretization corrections through O({alpha}{sub s}/M,a{alpha}{submore » s}), where {ital M} is the heavy-quark mass, {ital a} is the lattice spacing, and {alpha}{sub s} is the QCD coupling. As in our previous construction of the temporal component of the heavy-light axial-vector current, mixing between several lattice operators is encountered at one-loop order, and O(a{alpha}{sub s}) dimension-four improvement terms are identified. {copyright} {ital 1999} {ital The American Physical Society}« less