Tracking dynamics of two-dimensional continuous attractor neural networks
Fung, C. C. Alan; Wong, K. Y. Michael; Wu, Si
2009-12-01
We introduce an analytically solvable model of two-dimensional continuous attractor neural networks (CANNs). The synaptic input and the neuronal response form Gaussian bumps in the absence of external stimuli, and enable the network to track external stimuli by its translational displacement in the two-dimensional space. Basis functions of the two-dimensional quantum harmonic oscillator in polar coordinates are introduced to describe the distortion modes of the Gaussian bump. The perturbative method is applied to analyze its dynamics. Testing the method by considering the network behavior when the external stimulus abruptly changes its position, we obtain results of the reaction time and the amplitudes of various distortion modes, with excellent agreement with simulation results.
An investigation of two dimensional parallel and non-parallel steady mixing layers
Energy Technology Data Exchange (ETDEWEB)
Shabani, A. [Azad Islamic Univ., Faculty of Mechanical Engineering, School of Engineering, Research and Science Inst., Tehran (Iran, Islamic Republic of)]. E-mail: ario.shabani@cic.aut.ac.ir; Basirat Tabrizi, H. [Amirkabir Univ. of Technology, Dept. of Mechanical Engineering, Tehran (Iran, Islamic Republic of)
2004-07-01
A CFD code was generated to simulate the steady state behavior of two dimensional, parallel and nonparallel merging mixing layers. For the free stream velocity ratios of 0.7 and 0.9, the effect of the merging angle of free stream velocities of between 0.0 to 18.0 degrees on the mixing zone's velocity distribution, and on the physical spreading of the turbulent domain was numerically simulated and studied. The results were in good agreement with the available theoretical and experimental results, and indicated that increasing the angle of merging of the two free streams, or increasing their associated free stream velocity ratios increases the spatial growth rate and decreases the turbulent development distance. (author)
Two Dimensional Connectivity for Vehicular Ad-Hoc Networks
Farivar, Masoud; Ashtiani, Farid
2008-01-01
In this paper, we focus on two-dimensional connectivity in sparse vehicular ad hoc networks (VANETs). In this respect, we find thresholds for the arrival rates of vehicles at entrances of a block of streets such that the connectivity is guaranteed for any desired probability. To this end, we exploit a mobility model recently proposed for sparse VANETs, based on BCMP open queuing networks and solve the related traffic equations to find the traffic characteristics of each street and use the results to compute the exact probability of connectivity along these streets. Then, we use the results from percolation theory and the proposed fast algorithms for evaluation of bond percolation problem in a random graph corresponding to the block of the streets. We then find sufficiently accurate two dimensional connectivity-related parameters, such as the average number of intersections connected to each other and the size of the largest set of inter-connected intersections. We have also proposed lower bounds for the case ...
Intensity Coding in Two-Dimensional Excitable Neural Networks
Copelli, Mauro
2016-01-01
In the light of recent experimental findings that gap junctions are essential for low level intensity detection in the sensory periphery, the Greenberg-Hastings cellular automaton is employed to model the response of a two-dimensional sensory network to external stimuli. We show that excitable elements (sensory neurons) that have a small dynamical range are shown to give rise to a collective large dynamical range. Therefore the network transfer (gain) function (which is Hill or Stevens law-like) is an emergent property generated from a pool of small dynamical range cells, providing a basis for a "neural psychophysics". The growth of the dynamical range with the system size is approximately logarithmic, suggesting a functional role for electrical coupling. For a fixed number of neurons, the dynamical range displays a maximum as a function of the refractory period, which suggests experimental tests for the model. A biological application to ephaptic interactions in olfactory nerve fascicles is proposed.
Cellular neural network analysis for two-dimensional bioheat transfer equation.
Niu, J H; Wang, H Z; Zhang, H X; Yan, J Y; Zhu, Y S
2001-09-01
The cellular neural network (CNN) method is applied to solve the Pennes bioheat transfer equation, and its feasibility is demonstrated. Numerical solutions were obtained for a cellular neural network for a two-dimensional steady-state temperature field obtained from focused and unfocused ultrasound heat sources. Transient-state temperature fields were also studied and compared with experimental results obtained elsewhere. The cellular neural networks' key features of asynchronous parallel processing, continuous-time dynamics and local interaction enable real-time temperature field estimation for clinical hyperthermia.
Design of two-dimensional digital filters using neural networks
Institute of Scientific and Technical Information of China (English)
Wang Xiaohua; He Yigang
2005-01-01
A new approach for the design of two-dimensional (2-D) linear phase FIR digital filters based on a new neural networks algorithm (NNA) is provided. A compact expression for the transfer function of a 2-D linear phase FIR filter is derived based on its frequency response characteristic, and the NNA, based on minimizing the square-error in the frequency-domain, is established according to the compact expression. To illustrate the stability of the NNA, the convergence theorem is presented and proved. Design examples are also given, and the results show that the ripple is considerably small in passband and stopband, and the NNA-based method is of powerful stability and requires quite little amount of computations.
Estimating the hydraulic conductivity of two-dimensional fracture networks
Leung, C. T.; Zimmerman, R. W.
2010-12-01
Most oil and gas reservoirs, as well as most potential sites for nuclear waste disposal, are naturally fractured. In these sites, the network of fractures will provide the main path for fluid to flow through the rock mass. In many cases, the fracture density is so high as to make it impractical to model it with a discrete fracture network (DFN) approach. For such rock masses, it would be useful to have recourse to analytical, or semi-analytical, methods to estimate the macroscopic hydraulic conductivity of the fracture network. We have investigated single-phase fluid flow through stochastically generated two-dimensional fracture networks. The centres and orientations of the fractures are uniformly distributed, whereas their lengths follow either a lognormal distribution or a power law distribution. We have considered the case where the fractures in the network each have the same aperture, as well as the case where the aperture of each fracture is directly proportional to the fracture length. The discrete fracture network flow and transport simulator NAPSAC, developed by Serco (Didcot, UK), is used to establish the “true” macroscopic hydraulic conductivity of the network. We then attempt to match this conductivity using a simple estimation method that does not require extensive computation. For our calculations, fracture networks are represented as networks composed of conducting segments (bonds) between nodes. Each bond represents the region of a single fracture between two adjacent intersections with other fractures. We assume that the bonds are arranged on a kagome lattice, with some fraction of the bonds randomly missing. The conductance of each bond is then replaced with some effective conductance, Ceff, which we take to be the arithmetic mean of the individual conductances, averaged over each bond, rather than over each fracture. This is in contrast to the usual approximation used in effective medium theories, wherein the geometric mean is used. Our
Two-Dimensional Heat Transfer in a Heterogeneous Fracture Network
Gisladottir, V. R.; Roubinet, D.; Tartakovsky, D. M.
2015-12-01
Geothermal energy harvesting requires extraction and injection of geothermal fluid. Doing so in an optimal way requires a quantitative understanding of site-specific heat transfer between geothermal fluid and the ambient rock. We develop a heat transfer particle-tracking approach to model that interaction. Fracture-network models of heat transfer in fractured rock explicitly account for the presence of individual fractures, ambient rock matrix, and fracture-matrix interfaces. Computational domains of such models span the meter scale, whereas fracture apertures are on the millimeter scale. The computations needed to model these multi-scale phenomenon can be prohibitively expensive, even for methods using nonuniform meshes. Our approach appreciably decreases the computational costs. Current particle-tracking methods usually assume both infinite matrix and one-dimensional (1D) heat transfer in the matrix blocks. They rely on 1D analytical solutions for heat transfer in a single fracture, which can lead to large predictive errors. Our two-dimensional (2D) heat transfer simulation algorithm is mesh-free and takes into account both longitudinal and transversal heat conduction in the matrix. It uses a probabilistic model to transfer particle to the appropriate neighboring fracture unless it returns to the fracture of origin or remains in the matrix. We use this approach to look at the impact of a fracture-network topology (e.g. the importance of smaller scale fractures), as well as the matrix block distribution on the heat transport in heterogeneous fractured rocks.
TESHIMA, Koji; NAKATSUJI, Hiroyuki
1987-01-01
Flowfields resulted from interaction of two equivalent freejets issued from two parallel two-dimensional sonic nozzles at various nozzle distances and at various values of the stagnation to ambient pressure ratio are investigated numerically and by visualization. A strong shear flow region appears between the two jets, which is observed by visualization, is simulated well by the present calculation. Agreements of the parameters representing the whole structure of the flowfield, such as the lo...
Criticality in Two-Dimensional Quantum Systems: Tensor Network Approach
Ran, Shi-Ju; Li, Wei; Lewenstein, Maciej; Su, Gang
2016-01-01
Determination and characterization of criticality in two-dimensional (2D) quantum many-body systems belong to the most important challenges and problems of quantum physics. In this paper we propose an efficient scheme to solve this problem by utilizing the infinite projected entangled pair state (iPEPS), and tensor network (TN) representations. We show that the criticality of a 2D state is faithfully reproduced by the ground state (dubbed as boundary state) of a one-dimensional effective Hamiltonian constructed from its iPEPS representation. We demonstrate that for a critical state the correlation length and the entanglement spectrum of the boundary state are essentially different from those of a gapped iPEPS. This provides a solid indicator that allows to identify the criticality of the 2D state. Our scheme is verified on the resonating valence bond (RVB) states on kagom\\'e and square lattices, where the boundary state of the honeycomb RVB is found to be described by a $c=1$ conformal field theory. We apply ...
Parallel processing method for two-dimensional Sn transport code DOT3.5
Energy Technology Data Exchange (ETDEWEB)
Uematsu, Mikio [Toshiba Corp., Kawasaki, Kanagawa (Japan)
1998-03-01
A parallel processing method for the two-dimensional Sn transport code DOT3.5 has been developed to achieve drastic reduction of computation time. In the proposed method, parallelization is made with angular domain decomposition and/or space domain decomposition. Calculational speedup for parallel processing by angular domain decomposition is achieved by minimizing frequency of communications between processing elements. As for parallel processing by space domain decomposition, two-step rescaling method consisting of segmentwise rescaling and the ordinary pointwise rescaling have been developed to accelerate convergence, which will otherwise be degraded because of discontinuity at the segment boundaries. The developed method was examined with a Sun workstation using the PVM message-passing library, and sufficient speedup was observed. (author)
Gopinath, T; Kumar, Anil
2006-12-01
Hadamard spectroscopy has earlier been used to speed-up multi-dimensional NMR experiments. In this work, we speed-up the two-dimensional quantum computing scheme, by using Hadamard spectroscopy in the indirect dimension, resulting in a scheme which is faster and requires the Fourier transformation only in the direct dimension. Two and three qubit quantum gates are implemented with an extra observer qubit. We also use one-dimensional Hadamard spectroscopy for binary information storage by spatial encoding and implementation of a parallel search algorithm.
Directory of Open Access Journals (Sweden)
Chunye Gong
2014-01-01
Full Text Available It is very time consuming to solve fractional differential equations. The computational complexity of two-dimensional fractional differential equation (2D-TFDE with iterative implicit finite difference method is O(MxMyN2. In this paper, we present a parallel algorithm for 2D-TFDE and give an in-depth discussion about this algorithm. A task distribution model and data layout with virtual boundary are designed for this parallel algorithm. The experimental results show that the parallel algorithm compares well with the exact solution. The parallel algorithm on single Intel Xeon X5540 CPU runs 3.16–4.17 times faster than the serial algorithm on single CPU core. The parallel efficiency of 81 processes is up to 88.24% compared with 9 processes on a distributed memory cluster system. We do think that the parallel computing technology will become a very basic method for the computational intensive fractional applications in the near future.
A minimum action method for small random perturbations of two-dimensional parallel shear flows
Wan, Xiaoliang
2013-02-01
In this work, we develop a parallel minimum action method for small random perturbations of Navier-Stokes equations to solve the optimization problem given by the large deviation theory. The Freidlin-Wentzell action functional is discretized by hp finite elements in time direction and spectral methods in physical space. A simple diagonal preconditioner is constructed for the nonlinear conjugate gradient solver of the optimization problem. A hybrid parallel strategy based on MPI and OpenMP is developed to improve numerical efficiency. Both h- and p-convergence are obtained when the discretization error from physical space can be neglected. We also present preliminary results for the transition in two-dimensional Poiseuille flow from the base flow to a non-attenuated traveling wave.
Functional Parallel Factor Analysis for Functions of One- and Two-dimensional Arguments.
Choi, Ji Yeh; Hwang, Heungsun; Timmerman, Marieke E
2017-02-14
Parallel factor analysis (PARAFAC) is a useful multivariate method for decomposing three-way data that consist of three different types of entities simultaneously. This method estimates trilinear components, each of which is a low-dimensional representation of a set of entities, often called a mode, to explain the maximum variance of the data. Functional PARAFAC permits the entities in different modes to be smooth functions or curves, varying over a continuum, rather than a collection of unconnected responses. The existing functional PARAFAC methods handle functions of a one-dimensional argument (e.g., time) only. In this paper, we propose a new extension of functional PARAFAC for handling three-way data whose responses are sequenced along both a two-dimensional domain (e.g., a plane with x- and y-axis coordinates) and a one-dimensional argument. Technically, the proposed method combines PARAFAC with basis function expansion approximations, using a set of piecewise quadratic finite element basis functions for estimating two-dimensional smooth functions and a set of one-dimensional basis functions for estimating one-dimensional smooth functions. In a simulation study, the proposed method appeared to outperform the conventional PARAFAC. We apply the method to EEG data to demonstrate its empirical usefulness.
Interactions of a Charged Particle with Parallel Two-Dimensional Quantum Electron Gases
Institute of Scientific and Technical Information of China (English)
LI Chun-Zhi; SONG Yuan-Hong; WANG You-Nian
2008-01-01
@@ By using the linearized quantum hydrodynamic (QHD) theory, electronic excitations induced by a charged particle moving between or over two parallel two-dimensional quantum electron gases (2DQEG) are investigated. The calculation shows that the influence of the quantum effects on the interaction process should be taken into account. Including the quantum statistical and quantum diffraction effects, the general expressions of the induced potential and the stopping power are obtained. Our simulation results indicate that a V-shaped oscillatory wake potential exists in the electron gases during the test charge intrusion. Meanwhile, double peaks will occur in the stopping power when the distance of two surfaces is smaller and the test charge gets closer to any one of the two sheets.
Two-dimensional networks of lanthanide cubane-shaped dumbbells.
Savard, Didier; Lin, Po-Heng; Burchell, Tara J; Korobkov, Ilia; Wernsdorfer, Wolfgang; Clérac, Rodolphe; Murugesu, Muralee
2009-12-21
The syntheses, structures, and magnetic properties are reported for three new lanthanide complexes, [Ln(III)(4)(mu(3)-OH)(2)(mu(3)-O)(2)(cpt)(6)(MeOH)(6)(H(2)O)](2) (Ln = Dy (1.15MeOH), Ho (2.14MeOH), and Tb (3.18MeOH)), based on 4-(4-carboxyphenyl)-1,2,4-triazole ligand (Hcpt). The three complexes were confirmed to be isomorphous by infrared spectroscopy and single-crystal X-ray diffraction. The crystal structure of 1 reveals that the eight-coordinate metal centers are organized in two cubane-shaped moieties composed of four Dy(III) ions each. All metal centers in the cubane core are bridged by two mu(3)-oxide and two mu(3)-hydroxide asymmetrical units. Moreover, each cubane is linked to its neighbor by two externally coordinating ligands, forming the dumbbell {Dy(III)(4)}(2) moiety. Electrostatic interactions between the ligands of the triazole-bridged dimers form an extended supramolecular two-dimensional arrangement analogous to a metal-organic framework with quadrilateral spaces occupied by ligands from axial sheets and by four solvent molecules. The magnetic properties of the three compounds have been investigated using dc and ac susceptibility measurements. For 1, the static and dynamic data corroborate the fact that the {Dy(III)(4)} cubane-shaped core exhibits slow relaxation of its magnetization below 5 K associated with a single-molecule magnet behavior.
Institute of Scientific and Technical Information of China (English)
Zhang Zhi-Yong; Tan Han-Dong; Wang Kun-Peng; Lin Chang-Hong; Zhang Bin; Xie Mao-Bi
2016-01-01
Traditional two-dimensional (2D) complex resistivity forward modeling is based on Poisson’s equation but spectral induced polarization (SIP) data are the coprod-ucts of the induced polarization (IP) and the electromagnetic induction (EMI) effects. This is especially true under high frequencies, where the EMI effect can exceed the IP effect. 2D inversion that only considers the IP effect reduces the reliability of the inver-sion data. In this paper, we derive differential equations using Maxwell’s equations. With the introduction of the Cole–Cole model, we use thefi nite-element method to conduct 2D SIP forward modeling that considers the EMI and IP effects simultaneously. The data-space Occam method, in which different constraints to the model smoothness and parametric boundaries are introduced, is then used to simultaneously obtain the four parameters of the Cole–Cole model using multi-array electricfi eld data. This approach not only improves the stability of the inversion but also signifi cantly reduces the solution ambiguity. To improve the computational effi ciency, message passing interface program-ming was used to accelerate the 2D SIP forward modeling and inversion. Synthetic da-tasets were tested using both serial and parallel algorithms, and the tests suggest that the proposed parallel algorithm is robust and effi cient.
Zhang, Zhi-Yong; Tan, Han-Dong; Wang, Kun-Peng; Lin, Chang-Hong; Zhang, Bin; Xie, Mao-Bi
2016-03-01
Traditional two-dimensional (2D) complex resistivity forward modeling is based on Poisson's equation but spectral induced polarization (SIP) data are the coproducts of the induced polarization (IP) and the electromagnetic induction (EMI) effects. This is especially true under high frequencies, where the EMI effect can exceed the IP effect. 2D inversion that only considers the IP effect reduces the reliability of the inversion data. In this paper, we derive differential equations using Maxwell's equations. With the introduction of the Cole-Cole model, we use the finite-element method to conduct 2D SIP forward modeling that considers the EMI and IP effects simultaneously. The data-space Occam method, in which different constraints to the model smoothness and parametric boundaries are introduced, is then used to simultaneously obtain the four parameters of the Cole—Cole model using multi-array electric field data. This approach not only improves the stability of the inversion but also significantly reduces the solution ambiguity. To improve the computational efficiency, message passing interface programming was used to accelerate the 2D SIP forward modeling and inversion. Synthetic datasets were tested using both serial and parallel algorithms, and the tests suggest that the proposed parallel algorithm is robust and efficient.
Aprea, C.; Greco, A.; Maiorino, A.; Masselli, C.
2017-01-01
Magnetic Refrigeration (MR) is a novel refrigeration technique based on eco-friendly solid materials as refrigerants, whom react to the application of magnetic fields, with warming and cooling by magnetocaloric effect. The thermodynamical cycle which best suits the magnetic refrigeration is Active Magnetic Regenerator cycle (AMR). Regenerator is the core of a magnetic refrigerator, since that it plays a dual-role: it operates both as refrigerant and regenerator in an AMR cycle. An AMR cycle consists of two adiabatic stages and two isofield stage. In this paper an investigation is conducted about the magnetocaloric refrigerator design through two-dimensional multiphysics numerical models of two different magnetocaloric regenerators: (1) a packed bed and (2) a parallel plates magnetic regenerators made of gadolinium, operating at room temperature under a 1.5T magnetic field induction. Both models employ water as secondary fluid. The tests were performed with variable fluid flow rate at fixed AMR cycle frequency. The results obtained are presented in terms of temperature span, cooling power, coefficient of performance and mechanical power of the circulation pump, and they indicate under which operating conditions packed bed configuration is to be preferred to parallel plates and vice versa.
Chaotic neural network applied to two-dimensional motion control.
Yoshida, Hiroyuki; Kurata, Shuhei; Li, Yongtao; Nara, Shigetoshi
2010-03-01
Chaotic dynamics generated in a chaotic neural network model are applied to 2-dimensional (2-D) motion control. The change of position of a moving object in each control time step is determined by a motion function which is calculated from the firing activity of the chaotic neural network. Prototype attractors which correspond to simple motions of the object toward four directions in 2-D space are embedded in the neural network model by designing synaptic connection strengths. Chaotic dynamics introduced by changing system parameters sample intermediate points in the high-dimensional state space between the embedded attractors, resulting in motion in various directions. By means of adaptive switching of the system parameters between a chaotic regime and an attractor regime, the object is able to reach a target in a 2-D maze. In computer experiments, the success rate of this method over many trials not only shows better performance than that of stochastic random pattern generators but also shows that chaotic dynamics can be useful for realizing robust, adaptive and complex control function with simple rules.
Two-dimensional percolation threshold in confined Si nanoparticle networks
Energy Technology Data Exchange (ETDEWEB)
Laube, J., E-mail: laube@imtek.de; Gutsch, S.; Zacharias, M.; Hiller, D. [Laboratory for Nanotechnology, Department of Microsystems Engineering (IMTEK), University of Freiburg, Georges-Koehler-Allee 103, 79110 Freiburg im Breisgau (Germany); Wang, D.; Kübel, C. [Karlsruhe Nano and Micro Facility (KNMF) and Institute of Nanotechnology (INT), Karlsruhe Institute of Technology - KIT, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen (Germany)
2016-01-25
Non-percolating and percolating silicon quantum dot (QD) networks were investigated by plane-view energy filtered transmission electron microscopy (EF-TEM). The Si QD networks were prepared by plasma enhanced chemical vapor deposition on free standing 5 nm Si{sub 3}N{sub 4} membranes, followed by high temperature annealing. The percolation threshold from non-percolating to percolating networks is found to be in between a SiO{sub x} stoichiometry of SiO{sub 0.5} up to SiO{sub 0.7}. Using the EF-TEM images, key structural parameters of the Si QD ensemble were extracted and compared, i.e., their size distribution, nearest neighbor distance, and circularity. Increasing the silicon excess within the SiO{sub x} layer results in an ensemble of closer spaced, less size-controlled, and less circular Si QDs that give rise to coupling effects. Furthermore, the influence of the structural parameters on the optical and electrical Si QD ensemble properties is discussed.
Graph Grammar-Based Multi-Frontal Parallel Direct Solver for Two-Dimensional Isogeometric Analysis
Kuźnik, Krzysztof
2012-06-02
This paper introduces the graph grammar based model for developing multi-thread multi-frontal parallel direct solver for two dimensional isogeometric finite element method. Execution of the solver algorithm has been expressed as the sequence of graph grammar productions. At the beginning productions construct the elimination tree with leaves corresponding to finite elements. Following sequence of graph grammar productions generates element frontal matri-ces at leaf nodes, merges matrices at parent nodes and eliminates rows corresponding to fully assembled degrees of freedom. Finally, there are graph grammar productions responsible for root problem solution and recursive backward substitutions. Expressing the solver algorithm by graph grammar productions allows us to explore the concurrency of the algorithm. The graph grammar productions are grouped into sets of independent tasks that can be executed concurrently. The resulting concurrent multi-frontal solver algorithm is implemented and tested on NVIDIA GPU, providing O(NlogN) execution time complexity where N is the number of degrees of freedom. We have confirmed this complexity by solving up to 1 million of degrees of freedom with 448 cores GPU.
Mechanical transport in two-dimensional networks of fractures
Energy Technology Data Exchange (ETDEWEB)
Endo, H.K.
1984-04-01
The objectives of this research are to evaluate directional mechanical transport parameters for anisotropic fracture systems, and to determine if fracture systems behave like equivalent porous media. The tracer experiments used to measure directional tortuosity, longitudinal geometric dispersivity, and hydraulic effective porosity are conducted with a uniform flow field and measurements are made from the fluid flowing within a test section where linear length of travel is constant. Since fluid flow and mechanical transport are coupled processes, the directional variations of specific discharge and hydraulic effective porosity are measured in regions with constant hydraulic gradients to evaluate porous medium equivalence for the two processes, respectively. If the fracture region behaves like an equivalent porous medium, the system has the following stable properties: (1) specific discharge is uniform in any direction and can be predicted from a permeability tensor; and (2) hydraulic effective porosity is directionally stable. Fracture systems with two parallel sets of continuous fractures satisfy criterion 1. However, in these systems hydraulic effective porosity is directionally dependent, and thus, criterion 2 is violated. Thus, for some fracture systems, fluid flow can be predicted using porous media assumptions, but it may not be possible to predict transport using porous media assumptions. Two discontinuous fracture systems were studied which satisfied both criteria. Hydraulic effective porosity for both systems has a value between rock effective porosity and total porosity. A length-density analysis (LDS) of Canadian fracture data shows that porous media equivalence for fluid flow and transport is likely when systems have narrow aperture distributions. 54 references, 90 figures, 7 tables.
Flow of a two-dimensional aqueous foam in two parallel channels
Jones, S.; Cantat, I.; Dollet, B.; Meheust, Y.
2012-04-01
Flowing foams are used in many engineering and technical applications. A well-known application is oil recovery. Another one is the remediation of polluted soil: the foam is injected into the ground in order to mobilize chemical species that are initially present in the medium. Apart from potential interesting physico-chemical and biochemical properties, foams have pecular flow properties that might be used in order to reach regions of the medium that are normally the least permeable. We study here this physical aspect of the topic. As a precursor to the study of foam flow through a complex porous material, we study the behaviour of an aqueous two-dimensional foam flowing through a medium consisting of two parallel channels with different widths, at fixed medium porosity, that is, at fixed total combined width of the two channels. The flow velocity, and hence flux, in each channel is measured by analyzing images of the flowing foam. The corresponding pressure drop along each channel is calculated based on theoretical arguments involving both (i) a dynamic pressure drop, which is controlled by bubble-wall friction, and (ii) possibly a capillary pressure drop over the bubble films that emerge at the channel outlet, the latter pressure drop being controlled by the radius of curvature of the bubble film. The flow behaviour of the foam happens to not uniquely be determined by the channel width, as would be the case for a Newtonian fluid, but also to be highly dependent on the foam structure within the narrowest of the two channel, especially when a "bamboo" structure is obtained. Consequently, the flux in a channel is found to have a more complicated relation to the channel width than expected. We try to define a corresponding medium permeability and compare it to the permeability expected for the flow of a standard newtonian fluid in the same geometry.
Hoffmann, T.; Martínez-Salazar, J.; Herrero, P.; Petermann, J.
1997-01-01
In situ transport measurements during the growth of a thin layer of thermally evaporated tellurium onto an oriented polymer film are presented. The system, which resembles the characteristics of a two-dimensional anisotropic network, is analyzed in terms of the current percolation theory. Parameters such as the percolation threshold and the critical exponents are calculated for the perpendicular and the parallel orientation. Within the limits of the experiments the values of t∥ and t⊥ are estimated to be 1.15 and 1.46, respectively.
Institute of Scientific and Technical Information of China (English)
Chaojun Yan; Wenbiao Peng; Haijun Li
2007-01-01
@@ The alternate-direction implicit finite difference beam propagation method (FD-BPM) is used to analyze the two-dimensional (2D) symmetrical multimode interference (MMI) couplers. The positions of the images at the output plane and the length of multimode waveguide are accurately determined numerically. In order to reduce calculation time, the parallel processing of the arithmetic is implemented by the message passing interface and the simulation is accomplished by eight personal computers.
Truong, T. K.; Liu, K. Y.; Reed, I. S.
1983-01-01
It is pointed out that the two-dimensional cyclic convolution is a useful tool for many two-dimensional digital signal processing applications. Two important applications are related to spaceborne high-resolution synthetic aperture radar (SAR) processing and image processing. Nussbaumer and Quandalle (1978) showed that a radix-2 polynomial transform analogous to the conventional radix-2 FFT algorithm can be used to compute a two-dimensional cyclic convolution. On the basis of results reported by Arambepola and Rayner (1979), a radix-2 polynomial transform can be defined to compute a multidimensional cyclic convolution. Truong et al. (1981) used the considered ideas together with the Chinese Theorem to further reduce the complexity of the radix-2 fast polynomial transform (FPT). Reed et al. (1981) demonstrated that such a new FPT algorithm is significantly faster than the FFT algorithm for computing a two-dimensional convolution. In the present investigation, a parallel-pipeline architecture is considered for implementing the FPT developed by Truong et al.
Institute of Scientific and Technical Information of China (English)
Guangwei Yuan; Longjun Shen
2003-01-01
In this paper we are going to discuss the difference schemes with intrinsic parallelismfor the boundary value problem of the two dimensional semilinear parabolic systems. Theunconditional stability of the general finite difference schemes with intrinsic parallelismis justified in the sense of the continuous dependence of the discrete vector solution ofthe difference schemes on the discrete data of the original problems in the discrete W2(2,1)norms. Then the uniqueness of the discrete vector solution of this difference scheme followsas the consequence of the stability.
Functional scale-free networks in the two-dimensional Abelian sandpile model
Zarepour, M.; Niry, M. D.; Valizadeh, A.
2015-07-01
Recently, the similarity of the functional network of the brain and the Ising model was investigated by Chialvo [Nat. Phys. 6, 744 (2010), 10.1038/nphys1803]. This similarity supports the idea that the brain is a self-organized critical system. In this study we derive a functional network of the two-dimensional Bak-Tang-Wiesenfeld sandpile model as a self-organized critical model, and compare its characteristics with those of the functional network of the brain, obtained from functional magnetic resonance imaging.
Design of two-dimensional recursive filters by using neural networks.
Mladenov, V M; Mastorakis, N E
2001-01-01
A new design method for two-dimensional (2-D) recursive digital filters is investigated. The design of the 2-D filter is reduced to a constrained minimization problem the solution of which is achieved by the convergence of an appropriate neural network. The method is tested on a numerical example and compared with previously published methods when applied to the same example. Advantages of the proposed method over the existing ones are discussed as well.
Energy Technology Data Exchange (ETDEWEB)
Khanin, Yu. N.; Vdovin, E. E., E-mail: vdov62@yandex.ru [Russian Academy of Sciences, Institute of Microelectronics Technology and High Purity Materials (Russian Federation); Makarovsky, O. [University of Nottingham, School of Physics and Astronomy (United Kingdom); Henini, M. [University of Nottingham, School of Physics and Astronomy, Nottingham Nanotechnology and Nanoscience Center (United Kingdom)
2013-09-15
Magnetotunneling between two-dimensional GaAs/InAs electron systems in vertical resonant tunneling GaAs/InAs/AlAs heterostructures is studied. A new-type of singularity in the tunneling density of states, specifically a dip at the Fermi level, is found; this feature is drastically different from that observed previously for the case of tunneling between two-dimensional GaAs tunnel systems in terms of both the kind of functional dependence and the energy and temperature parameters. As before, this effect manifests itself in the suppression of resonant tunneling in a narrow range near zero bias voltage in a high magnetic field parallel to the current direction. Magnetic-field and temperature dependences of the effect's parameters are obtained; these dependences are compared with available theoretical and experimental data. The observed effect can be caused by a high degree of disorder in two-dimensional correlated electron systems as a result of the introduction of structurally imperfect strained InAs layers.
Directory of Open Access Journals (Sweden)
Mihai-Victor PRICOP
2010-09-01
Full Text Available The present paper introduces a numerical approach of static linear elasticity equations for anisotropic materials. The domain and boundary conditions are simple, to enhance an easy implementation of the finite difference scheme. SOR and gradient are used to solve the resulting linear system. The simplicity of the geometry is also useful for MPI parallelization of the code.
Mechanism of the jamming transition in the two-dimensional traffic networks
Ishibashi, Yoshihiro; Fukui, Minoru
2012-12-01
The mechanism of the jamming transition in two-dimensional traffic networks is discussed on the basis of several models, where the update rule is deterministic, though the initial car configuration is random. It has turned out that the introduced concept of the occupation probability, which depends upon time and the site, is useful. The fluctuation in the local car density plays an important role to give rise to small initial clusters of the cars. To examine the growth of such clusters a time-dependent function C is introduced, which is the number of the neighboring car pairs, and C increases to a certain maximum value, correlated with the total jamming. The critical car density in the symmetric two-dimensional N×N/N×N system is found to be 0.22-0.23 for each of the east-bound (x) and the north-bound (y) cars.
Parallel implementation of geometrical shock dynamics for two dimensional converging shock waves
Qiu, Shi; Liu, Kuang; Eliasson, Veronica
2016-10-01
Geometrical shock dynamics (GSD) theory is an appealing method to predict the shock motion in the sense that it is more computationally efficient than solving the traditional Euler equations, especially for converging shock waves. However, to solve and optimize large scale configurations, the main bottleneck is the computational cost. Among the existing numerical GSD schemes, there is only one that has been implemented on parallel computers, with the purpose to analyze detonation waves. To extend the computational advantage of the GSD theory to more general applications such as converging shock waves, a numerical implementation using a spatial decomposition method has been coupled with a front tracking approach on parallel computers. In addition, an efficient tridiagonal system solver for massively parallel computers has been applied to resolve the most expensive function in this implementation, resulting in an efficiency of 0.93 while using 32 HPCC cores. Moreover, symmetric boundary conditions have been developed to further reduce the computational cost, achieving a speedup of 19.26 for a 12-sided polygonal converging shock.
Integration of neuroblasts into a two-dimensional small world neuronal network
Schneider-Mizell, Casey; Zochowski, Michal; Sander, Leonard
2009-03-01
Neurogenesis in the adult brain has been suggested to be important for learning and functional robustness to the neuronal death. New neurons integrate themselves into existing neuronal networks by moving into a target destination, extending axonal and dendritic processes, and inducing synaptogenesis to connect to active neurons. We hypothesize that increased plasticity of the network to novel stimuli can arise from activity-dependent cell and process motility rules. In complement to a similar in vitro model, we investigate a computational model of a two-dimensional small world network of integrate and fire neurons. After steady-state activity is reached in the extant network, we introduce new neurons which move, stop, and connect themselves through rules governed by position and firing rate.
Directory of Open Access Journals (Sweden)
Mohammad Mehdi Rashidi
2008-01-01
Full Text Available The flow of a viscous incompressible fluid between two parallel plates due to the normal motion of the plates is investigated. The unsteady Navier-Stokes equations are reduced to a nonlinear fourth-order differential equation by using similarity solutions. Homotopy analysis method (HAM is used to solve this nonlinear equation analytically. The convergence of the obtained series solution is carefully analyzed. The validity of our solutions is verified by the numerical results obtained by fourth-order Runge-Kutta.
Thermal metal in network models of a disordered two-dimensional superconductor
Chalker, J. T.; Read, N.; Kagalovsky, V.; Horovitz, B.; Avishai, Y.; Ludwig, A. W.
2002-01-01
We study the symmetry class for localization which arises from models of noninteracting quasiparticles in disordered superconductors that have neither time-reversal nor spin-rotation invariance. Two-dimensional systems in this category, which is known as class D, can display phases with three different types of quasiparticle dynamics: metallic, localized, or with a quantized (thermal) Hall conductance. Correspondingly, they can show a variety of delocalization transitions. We illustrate this behavior by investigating numerically the phase diagrams of network models with the appropriate symmetry and show the appearance of the metallic phase.
Mechanism of the jamming transition in the two-dimensional traffic networks. II
Ishibashi, Yoshihiro; Fukui, Minoru
2014-01-01
The jamming transition in a two-dimensional traffic network is investigated based upon the cellular automaton simulations, where the update rule is deterministic, though the initial car configuration is randomly set. The lifetime of the system is defined as the time until when all cars in the system come to a stop, and it will increase with decreasing car density from a higher density side. The critical car density is defined as the car density, at which the corresponding lifetime diverges. The analytical expression for the critical car density is proposed.
A two dimensional thermal network model for a photovoltaic solar wall
Energy Technology Data Exchange (ETDEWEB)
Dehra, Himanshu [1-140 Avenue Windsor, Lachine, Quebec (Canada)
2009-11-15
A two dimensional thermal network model is proposed to predict the temperature distribution for a section of photovoltaic solar wall installed in an outdoor room laboratory in Concordia University, Montreal, Canada. The photovoltaic solar wall is constructed with a pair of glass coated photovoltaic modules and a polystyrene filled plywood board as back panel. The active solar ventilation through a photovoltaic solar wall is achieved with an exhaust fan fixed in the outdoor room laboratory. The steady state thermal network nodal equations are developed for conjugate heat exchange and heat transport for a section of a photovoltaic solar wall. The matrix solution procedure is adopted for formulation of conductance and heat source matrices for obtaining numerical solution of one dimensional heat conduction and heat transport equations by performing two dimensional thermal network analyses. The temperature distribution is predicted by the model with measurement data obtained from the section of a photovoltaic solar wall. The effect of conduction heat flow and multi-node radiation heat exchange between composite surfaces is useful for predicting a ventilation rate through a solar ventilation system. (author)
Synchronizability of Small-World Networks Generated from a Two-Dimensional Kleinberg Model
Directory of Open Access Journals (Sweden)
Yi Zhao
2013-01-01
Full Text Available This paper investigates the synchronizability of small-world networks generated from a two-dimensional Kleinberg model, which is more general than NW small-world network. The three parameters of the Kleinberg model, namely, the distance of neighbors, the number of edge-adding, and the edge-adding probability, are analyzed for their impacts on its synchronizability and average path length. It can be deduced that the synchronizability becomes stronger as the edge-adding probability increases, and the increasing edge-adding probability could make the average path length of the Kleinberg small-world network go smaller. Moreover, larger distance among neighbors and more edges to be added could play positive roles in enhancing the synchronizability of the Kleinberg model. The lorentz oscillators are employed to verify the conclusions numerically.
Chen, Xiao; Yang, Yang; Cai, Xiaoying; Auger, Daniel A; Meyer, Craig H; Salerno, Michael; Epstein, Frederick H
2016-06-14
Cine Displacement Encoding with Stimulated Echoes (DENSE) provides accurate quantitative imaging of cardiac mechanics with rapid displacement and strain analysis; however, image acquisition times are relatively long. Compressed sensing (CS) with parallel imaging (PI) can generally provide high-quality images recovered from data sampled below the Nyquist rate. The purposes of the present study were to develop CS-PI-accelerated acquisition and reconstruction methods for cine DENSE, to assess their accuracy for cardiac imaging using retrospective undersampling, and to demonstrate their feasibility for prospectively-accelerated 2D cine DENSE imaging in a single breathhold. An accelerated cine DENSE sequence with variable-density spiral k-space sampling and golden angle rotations through time was implemented. A CS method, Block LOw-rank Sparsity with Motion-guidance (BLOSM), was combined with sensitivity encoding (SENSE) for the reconstruction of under-sampled multi-coil spiral data. Seven healthy volunteers and 7 patients underwent 2D cine DENSE imaging with fully-sampled acquisitions (14-26 heartbeats in duration) and with prospectively rate-2 and rate-4 accelerated acquisitions (14 and 8 heartbeats in duration). Retrospectively- and prospectively-accelerated data were reconstructed using BLOSM-SENSE and SENSE. Image quality of retrospectively-undersampled data was quantified using the relative root mean square error (rRMSE). Myocardial displacement and circumferential strain were computed for functional assessment, and linear correlation and Bland-Altman analyses were used to compare accelerated acquisitions to fully-sampled reference datasets. For retrospectively-undersampled data, BLOSM-SENSE provided similar or lower rRMSE at rate-2 and lower rRMSE at rate-4 acceleration compared to SENSE (p cine DENSE provided good image quality and expected values of displacement and strain. BLOSM-SENSE-accelerated spiral cine DENSE imaging with 2D displacement encoding can be
Energy Technology Data Exchange (ETDEWEB)
Nickell, T.W.
1988-01-01
This study numerically analyzes combined radiative and natural or forced convective heat transfer between vertical parallel plates with two-dimensional discrete heat sources. The numerical method was verified by comparing its results with other published experimental data and the agreement was excellent. It is shown that radiative heat transfer is a significant and useful mode of heat transfer in combination with both natural and forced convection in this situation and cannot be neglected. Radiative heat transfer accounted for 50-60% or more of the total heat transfer in some cases, and usually approximately 30-35% on the top of a discrete heat source. This fact can be used to advantage in the thermal design of electronic circuit boards.
Bifurcations of large networks of two-dimensional integrate and fire neurons.
Nicola, Wilten; Campbell, Sue Ann
2013-08-01
Recently, a class of two-dimensional integrate and fire models has been used to faithfully model spiking neurons. This class includes the Izhikevich model, the adaptive exponential integrate and fire model, and the quartic integrate and fire model. The bifurcation types for the individual neurons have been thoroughly analyzed by Touboul (SIAM J Appl Math 68(4):1045-1079, 2008). However, when the models are coupled together to form networks, the networks can display bifurcations that an uncoupled oscillator cannot. For example, the networks can transition from firing with a constant rate to burst firing. This paper introduces a technique to reduce a full network of this class of neurons to a mean field model, in the form of a system of switching ordinary differential equations. The reduction uses population density methods and a quasi-steady state approximation to arrive at the mean field system. Reduced models are derived for networks with different topologies and different model neurons with biologically derived parameters. The mean field equations are able to qualitatively and quantitatively describe the bifurcations that the full networks display. Extensions and higher order approximations are discussed.
Robustness and breakup of the spiral wave in a two-dimensional lattice network of neurons
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
The robustness and breakup of spiral wave in a two-dimensional lattice networks of neurons are investigated. The effect of small- world type connection is often simplified with local regular connection and the long-range connection with certain probability. The network effect on the development of spiral wave can be better described by local regular connection and changeable long-range connection probability than fixed long-range connection probability because the long-range probability could be changeable in realistic biological system. The effect from the changeable probability for long-range connection is simplified by multiplicative noise. At first, a stable rotating spiral wave is developed by using appropriate initial values, parameters and no-flux boundary conditions, and then the effect of networks is investigated. Extensive numerical studies show that spiral wave keeps its alive and robust when the intensity of multiplicative noise is below a certain threshold, otherwise, the breakup of spiral wave occurs. A statistical factor of synchronization in two-dimensional array is defined to study the phase transition of spiral wave by checking the membrane potentials of all neurons corresponding to the critical parameters(the intensity of noise or forcing current)in the curve for factor of synchronization. The Hindmarsh-Rose model is investigated, the Hodgkin-Huxley neuron model in the presence of the channel noise is also studied to check the model independence of our conclusions. And it is found that breakup of spiral wave is easier to be induced by the multiplicative noise in presence of channel noise.
Size effect on brittle and ductile fracture of two-dimensional interlinked carbon nanotube network
Jing, Yuhang; Aluru, N. R.
2017-09-01
The mechanical properties of two-dimensional (2D) interlinked carbon nanotube (CNT) network are investigated using ab initio calculation and molecular dynamics simulations (MD) with Reaxff force field. The simulation results show that bulk 2D interlinked CNT network has good mechanical properties along the axial direction which can be comparable to that of single-walled CNT and graphene, but has better ductility along the radial direction than single-walled CNT and graphene. In addition, the mechanical properties of 2D interlinked CNT network ribbon along the radial direction depend strongly on the size of the ribbon. The Young's modulus and Poisson's ratio decrease as the size increases while the fracture strain increases with the size increasing. By analyzing the atomic structural (both bond length and atomic von Mises stress) evolution of the ribbons, the mechanism of a brittle-to-ductile transition is revealed. The exploration of the mechanical properties of the 2D interlinked CNT network paves the way for application of the relevant devices that can benefit from the high Young's modulus, high tensile strength, and good ductility.
Directory of Open Access Journals (Sweden)
M. Kakitani
2013-06-01
Full Text Available The energy efficiency of non-cooperative and cooperative transmissions are investigated in a two-dimensional wireless sensor network, considering a target outage probability and the same end-to-end throughput for all transmission schemes. The impact of the relay selection method in the cooperative schemes is also analyzed. We show that under non line-of-sight conditions the relay selection method has a greater impact in the energy efficiency than the availability of a return channel. By its turn, under line-of-sight conditions a return channel is more valuable to the energy efficiency of cooperative transmission than the specific relay selection method. Finally, we demonstrate that the energy efficiency advantage of the cooperative over the non-cooperative transmission increases with the distance among nodes and with the nodes density.
Surface-Induced Optimal Packing of Two-Dimensional Molecular Networks
Copie, Guillaume; Cleri, Fabrizio; Makoudi, Younes; Krzeminski, Christophe; Berthe, Maxime; Cherioux, Frédéric; Palmino, Frank; Grandidier, Bruno
2015-02-01
High-density packing in organic crystals is usually associated with an increase of the coordination between molecules. Such a concept is not necessarily extended to two-dimensional molecular networks self-assembled on a solid surface, for which we demonstrate the key role of the surface in inducing the optimal packing. By a combination of scanning tunneling microscopy experiments and multiscale computer simulations, we study the phase transition between two polymorphs. We find that, contrary to intuition, the structure with the lowest packing fraction corresponds to the highest molecular coordination number, due to the competition between surface and intermolecular forces. Having the lowest free energy, this structure spreads out as the most stable polymorph over a wide range of molecular concentrations.
Graphene-based field effect transistor in two-dimensional paper networks
Energy Technology Data Exchange (ETDEWEB)
Cagang, Aldrine Abenoja; Abidi, Irfan Haider; Tyagi, Abhishek [Department of Chemical and Biomolecular Engineering, Hong Kong University of Science and Technology, Clear Water Bay (Hong Kong); Hu, Jie; Xu, Feng [Bioinspired Engineering and Biomechanics Center (BEBC), Xi' an Jiaotong University, Xi' an 710049 (China); The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi' an Jiaotong University, Xi' an 710049 (China); Lu, Tian Jian [Bioinspired Engineering and Biomechanics Center (BEBC), Xi' an Jiaotong University, Xi' an 710049 (China); Luo, Zhengtang, E-mail: keztluo@ust.hk [Department of Chemical and Biomolecular Engineering, Hong Kong University of Science and Technology, Clear Water Bay (Hong Kong)
2016-04-21
We demonstrate the fabrication of a graphene-based field effect transistor (GFET) incorporated in a two-dimensional paper network format (2DPNs). Paper serves as both a gate dielectric and an easy-to-fabricate vessel for holding the solution with the target molecules in question. The choice of paper enables a simpler alternative approach to the construction of a GFET device. The fabricated device is shown to behave similarly to a solution-gated GFET device with electron and hole mobilities of ∼1256 cm{sup 2} V{sup −1} s{sup −1} and ∼2298 cm{sup 2} V{sup −1} s{sup −1} respectively and a Dirac point around ∼1 V. When using solutions of ssDNA and glucose it was found that the added molecules induce negative electrolytic gating effects shifting the conductance minimum to the right, concurrent with increasing carrier concentrations which results to an observed increase in current response correlated to the concentration of the solution used. - Highlights: • A graphene-based field effect transistor sensor was fabricated for two-dimensional paper network formats. • The constructed GFET on 2DPN was shown to behave similarly to solution-gated GFETs. • Electrolyte gating effects have more prominent effect over adsorption effects on the behavior of the device. • The GFET incorporated on 2DPN was shown to yield linear response to presence of glucose and ssDNA soaked inside the paper.
Czarnik, Piotr; Dziarmaga, Jacek; Oleś, Andrzej M.
2016-05-01
Progress in describing thermodynamic phase transitions in quantum systems is obtained by noticing that the Gibbs operator e-β H for a two-dimensional (2D) lattice system with a Hamiltonian H can be represented by a three-dimensional tensor network, the third dimension being the imaginary time (inverse temperature) β . Coarse graining the network along β results in a 2D projected entangled-pair operator (PEPO) with a finite bond dimension D . The coarse graining is performed by a tree tensor network of isometries. The isometries are optimized variationally, taking into account full tensor environment, to maximize the accuracy of the PEPO. The algorithm is applied to the isotropic quantum compass model on an infinite square lattice near a symmetry-breaking phase transition at finite temperature. From the linear susceptibility in the symmetric phase and the order parameter in the symmetry-broken phase, the critical temperature is estimated at Tc=0.0606 (4 ) J , where J is the isotropic coupling constant between S =1/2 pseudospins.
Kilpatrick, Zachary P.
2009-10-29
We study the spatiotemporal dynamics of a two-dimensional excitatory neuronal network with synaptic depression. Coupling between populations of neurons is taken to be nonlocal, while depression is taken to be local and presynaptic. We show that the network supports a wide range of spatially structured oscillations, which are suggestive of phenomena seen in cortical slice experiments and in vivo. The particular form of the oscillations depends on initial conditions and the level of background noise. Given an initial, spatially localized stimulus, activity evolves to a spatially localized oscillating core that periodically emits target waves. Low levels of noise can spontaneously generate several pockets of oscillatory activity that interact via their target patterns. Periodic activity in space can also organize into spiral waves, provided that there is some source of rotational symmetry breaking due to external stimuli or noise. In the high gain limit, no oscillatory behavior exists, but a transient stimulus can lead to a single, outward propagating target wave. © Springer Science + Business Media, LLC 2009.
Directory of Open Access Journals (Sweden)
Franceschini Barbara
2005-02-01
Full Text Available Abstract Background Modeling the complex development and growth of tumor angiogenesis using mathematics and biological data is a burgeoning area of cancer research. Architectural complexity is the main feature of every anatomical system, including organs, tissues, cells and sub-cellular entities. The vascular system is a complex network whose geometrical characteristics cannot be properly defined using the principles of Euclidean geometry, which is only capable of interpreting regular and smooth objects that are almost impossible to find in Nature. However, fractal geometry is a more powerful means of quantifying the spatial complexity of real objects. Methods This paper introduces the surface fractal dimension (Ds as a numerical index of the two-dimensional (2-D geometrical complexity of tumor vascular networks, and their behavior during computer-simulated changes in vessel density and distribution. Results We show that Ds significantly depends on the number of vessels and their pattern of distribution. This demonstrates that the quantitative evaluation of the 2-D geometrical complexity of tumor vascular systems can be useful not only to measure its complex architecture, but also to model its development and growth. Conclusions Studying the fractal properties of neovascularity induces reflections upon the real significance of the complex form of branched anatomical structures, in an attempt to define more appropriate methods of describing them quantitatively. This knowledge can be used to predict the aggressiveness of malignant tumors and design compounds that can halt the process of angiogenesis and influence tumor growth.
Kiefer, Thomas; Villanueva, Guillermo; Brugger, Jürgen
2009-08-01
In this study we investigate electrical conduction in finite rectangular random resistor networks in quasione and two dimensions far away from the percolation threshold p(c) by the use of a bond percolation model. Various topologies such as parallel linear chains in one dimension, as well as square and triangular lattices in two dimensions, are compared as a function of the geometrical aspect ratio. In particular we propose a linear approximation for conduction in two-dimensional systems far from p(c), which is useful for engineering purposes. We find that the same scaling function, which can be used for finite-size scaling of percolation thresholds, also applies to describe conduction away from p(c). This is in contrast to the quasi-one-dimensional case, which is highly nonlinear. The qualitative analysis of the range within which the linear approximation is legitimate is given. A brief link to real applications is made by taking into account a statistical distribution of the resistors in the network. Our results are of potential interest in fields such as nanostructured or composite materials and sensing applications.
Two-Dimensional High-Lift Aerodynamic Optimization Using Neural Networks
Greenman, Roxana M.
1998-01-01
The high-lift performance of a multi-element airfoil was optimized by using neural-net predictions that were trained using a computational data set. The numerical data was generated using a two-dimensional, incompressible, Navier-Stokes algorithm with the Spalart-Allmaras turbulence model. Because it is difficult to predict maximum lift for high-lift systems, an empirically-based maximum lift criteria was used in this study to determine both the maximum lift and the angle at which it occurs. The 'pressure difference rule,' which states that the maximum lift condition corresponds to a certain pressure difference between the peak suction pressure and the pressure at the trailing edge of the element, was applied and verified with experimental observations for this configuration. Multiple input, single output networks were trained using the NASA Ames variation of the Levenberg-Marquardt algorithm for each of the aerodynamic coefficients (lift, drag and moment). The artificial neural networks were integrated with a gradient-based optimizer. Using independent numerical simulations and experimental data for this high-lift configuration, it was shown that this design process successfully optimized flap deflection, gap, overlap, and angle of attack to maximize lift. Once the neural nets were trained and integrated with the optimizer, minimal additional computer resources were required to perform optimization runs with different initial conditions and parameters. Applying the neural networks within the high-lift rigging optimization process reduced the amount of computational time and resources by 44% compared with traditional gradient-based optimization procedures for multiple optimization runs.
Landers, John; Chérioux, Frédéric; De Santis, Maurizio; Bendiab, Nedjma; Lamare, Simon; Magaud, Laurence; Coraux, Johann
2014-12-01
We report a convergent surface polymerization reaction scheme on Au(111), based on a triple aldol condensation, yielding a carbon-rich, covalent nanoporous two-dimensional network. The reaction is not self-poisoning and proceeds up to a full surface coverage. The deposited precursor molecules 1, 3, 5-tri(4’-acetylphenyl) first form supramolecular assemblies that are converted to the porous covalent network upon heating. The formation and structure of the network and of the intermediate steps are studied with scanning tunneling microscopy, Raman spectroscopy and density functional theory.
Guo, L-X; Li, J; Zeng, H
2009-11-01
We present an investigation of the electromagnetic scattering from a three-dimensional (3-D) object above a two-dimensional (2-D) randomly rough surface. A Message Passing Interface-based parallel finite-difference time-domain (FDTD) approach is used, and the uniaxial perfectly matched layer (UPML) medium is adopted for truncation of the FDTD lattices, in which the finite-difference equations can be used for the total computation domain by properly choosing the uniaxial parameters. This makes the parallel FDTD algorithm easier to implement. The parallel performance with different number of processors is illustrated for one rough surface realization and shows that the computation time of our parallel FDTD algorithm is dramatically reduced relative to a single-processor implementation. Finally, the composite scattering coefficients versus scattered and azimuthal angle are presented and analyzed for different conditions, including the surface roughness, the dielectric constants, the polarization, and the size of the 3-D object.
Tracer particles in two-dimensional elastic networks diffuse logarithmically slow
Lizana, Ludvig; Ambjörnsson, Tobias; Lomholt, Michael A.
2017-01-01
Several experiments on tagged molecules or particles in living systems suggest that they move anomalously slow—their mean squared displacement (MSD) increase slower than linearly with time. Leading models aimed at understanding these experiments predict that the MSD grows as a power law with a growth exponent that is smaller than unity. However, in some experiments the growth is so slow (fitted exponent ∼0.1–0.2) that they hint towards other mechanisms at play. In this paper, we theoretically demonstrate how in-plane collective modes excited by thermal fluctuations in a two dimensional membrane lead to logarithmic time dependence for the the tracer particle’s MSD.
Energy Technology Data Exchange (ETDEWEB)
Jost, G.; Tran, T.M.; Appert, K. [Ecole Polytechnique Federale, Lausanne (Switzerland). Centre de Recherche en Physique des Plasma (CRPP); Wuethrich, S. [CRAY Research, PATP/PSE, EPFL, Lausanne (Switzerland)
1996-12-01
A two-dimensional PIC code aimed at the investigation of electron-cyclotron beam instabilities in gyrotrons and their effects on the beam quality is presented. The code is based on recently developed techniques for handling charge conservation and open boundaries and uses an electromagnetic field which is decomposed in its transverse magnetic (TM) and electric (TE) components. The code has been implemented on the massively parallel computer CRAY T3D, and on the CRAY Y-MP. (author) figs., tabs., refs.
Institute of Scientific and Technical Information of China (English)
WANG Zhicong; ZHANG Qinghe; LI Tong; ZHAO Zhongyi; ZHANG Weibing
2006-01-01
A comprehensive two-dimensional liquid chromatographic system (2D SCX/RP) is constructed with a 10-port-2-way valve using strong cation exchange chromatography (Hypersil SCX, 100 mm×4.6 mm I.D.) followed by reversed phase chromatography (Hypersil BDS C18, 15 mm×4.6 mm I.D.) to separate the complex peptides from globin peptic hydrolysate. After the sample was loaded on the SCX column, the phosphate buffer (pH 4.0) was used to elute the peptides. Then, elutes flowed through the interface and the peptides focused on the head of the trapping columns (Hypersil BDS C18, 15 mm×4.6 mm I.D.) but salt passed into the waste. After the valve was switched, the samples were flushed with a backward flow into the RP analytical column. The peptides on the SCX were eluted with 12 discontinuous steps linearly increasing salt concentrations. The peptides enriched on the trapping column were desalted and separated by the RP columns. The resolution and the resolved peaks of the 2D SCX/RP system were greatly increased and the total peak capacity reached as high as 2280.
Two Dimensional Array Based Overlay Network for Balancing Load of Peer-to-Peer Live Video Streaming
Faruq Ibn Ibrahimy, Abdullah; Rafiqul, Islam Md; Anwar, Farhat; Ibn Ibrahimy, Muhammad
2013-12-01
The live video data is streaming usually in a tree-based overlay network or in a mesh-based overlay network. In case of departure of a peer with additional upload bandwidth, the overlay network becomes very vulnerable to churn. In this paper, a two dimensional array-based overlay network is proposed for streaming the live video stream data. As there is always a peer or a live video streaming server to upload the live video stream data, so the overlay network is very stable and very robust to churn. Peers are placed according to their upload and download bandwidth, which enhances the balance of load and performance. The overlay network utilizes the additional upload bandwidth of peers to minimize chunk delivery delay and to maximize balance of load. The procedure, which is used for distributing the additional upload bandwidth of the peers, distributes the additional upload bandwidth to the heterogeneous strength peers in a fair treat distribution approach and to the homogeneous strength peers in a uniform distribution approach. The proposed overlay network has been simulated by Qualnet from Scalable Network Technologies and results are presented in this paper.
Natale, Joseph; Hentschel, George
Firing-rate networks offer a coarse model of signal propagation in the brain. Here we analyze sparse, 2D planar firing-rate networks with no synapses beyond a certain cutoff distance. Additionally, we impose Dale's Principle to ensure that each neuron makes only or inhibitory outgoing connections. Using spectral methods, we find that the number of neurons participating in excitations of the network becomes insignificant whenever the connectivity cutoff is tuned to a value near or below the average interneuron separation. Further, neural activations exceeding a certain threshold stay confined to a small region of space. This behavior is an instance of Anderson localization, a disorder-induced phase transition by which an information channel is rendered unable to transmit signals. We discuss several potential implications of localization for both local and long-range computation in the brain. This work was supported in part by Grants JSMF/ 220020321 and NSF/IOS/1208126.
Ochiai, Tetsuyuki
2016-01-01
Synthetic gauge field and pseudospin-orbit interaction are implemented in the stacked two-dimensional ring network model proposed by the present author. The model was introduced to simulate light propagation in the corresponding ring-resonator network, and is thus completely bosonic. Without these two items, the system exhibits Floquet-Weyl and Floquet-topological-insulator phases with topologically gapless and gapped band structures, respectively. The synthetic magnetic field implemented in the model results in a three-dimensional Hofstadter-butterfly-type spectrum in a photonic platform. The resulting gaps are characterization by the winding number of relevant S-matrices together with the Chern number of the bulk bands. The pseudospin-orbit interaction is defined as the mixing term between two pseudospin degrees of freedom in the rings, namely, the clockwise and counter-clockwise modes in the rings. It destroys the Floquet-topological-insulator phases, while the Floquet-Weyl phase with multiple Weyl points ...
Institute of Scientific and Technical Information of China (English)
Hongxi Yin; Wei Liang; Le Ma; Liqiao Qin
2009-01-01
A new generation algorithm of two-dimensional triple-codeweight asymmetric optical orthogonal codes for optical code division multiple access (OCDMA) networks is proposed. The code cardinality is obtained and the error-probability performance for corresponding OCDMA system is analyzed. The codes with two constraints (i.e., auto- and cross-correlation properties) being unequal are taken into account. On the premise of fixed system resources, the code cardinality can be significantly improved. By analysis of the error-probability performance, it is shown that the codes with different parameters have different performances. Therefore, this type of codes can be applied to support diverse quality of service (QoS) and satisfy the quality requirement of different multimedia or distinct users, and simultaneously make the better use of bandwidth resources in optical networks.
Ensemble Distribution for Immiscible Two-Phase Flow in Two-Dimensional Networks
Savani, Isha; Kjelstrup, Signe; Vassvik, Morten; Sinha, Santanu; Hansen, Alex
2016-01-01
An ensemble distribution has been constructed to describe steady immiscible two-phase flow of two incompressible fluids in a network. The system is ergodic. The distribution relates the time that a bubble of the non-wetting fluid spends in a link to the local volume flow. The properties of the ensemble distribution are tested by two-phase flow simulations at the pore-scale for capillary numbers ranging from 0.1 to 0.001. It is shown that the distribution follows the postulated dependence on the local flow for Ca = 0.01 and 0.001. The distribution is used to compute the global flow performance of the network. In particular, we find the expression for the overall mobility of the system using the ensemble distribution. The entropy production at the scale of the network is shown to give the expected product of the average flow and its driving force, obtained from a black-box description. The distribution can be used to obtain macroscopic variables from local network information, for a practical range of capillary...
Curvature-induced cross-hatched order in two-dimensional semiflexible polymer networks
Vrusch, Cyril
2015-01-01
A recurring motif in the organization of biological tissues are networks of long, fibrillar protein strands effectively confined to cylindrical surfaces. Often, the fibers in such curved, quasi-2D geometries adopt a characteristic order: the fibers wrap around the central axis at an angle which varies with radius and, in several cases, is strongly bimodally distributed. In this Letter, we investigate the general problem of a 2D crosslinked network of semiflexible fibers confined to a cylindrical substrate, and demonstrate that in such systems the trade-off between bending and stretching energies, very generically, gives rise to cross-hatched order. We discuss its general dependency on the radius of the confining cylinder, and present an intuitive model that illustrates the basic physical principle of curvature-induced order. Our findings shed new light on the potential origin of some curiously universal fiber orientational distributions in tissue biology, and suggests novel ways in which synthetic polymeric s...
Le, Thai; Tran, Hai
2011-01-01
Facial expression classification is a kind of image classification and it has received much attention, in recent years. There are many approaches to solve these problems with aiming to increase efficient classification. One of famous suggestions is described as first step, project image to different spaces; second step, in each of these spaces, images are classified into responsive class and the last step, combine the above classified results into the final result. The advantages of this approach are to reflect fulfill and multiform of image classified. In this paper, we use 2D-PCA and its variants to project the pattern or image into different spaces with different grouping strategies. Then we develop a model which combines many Neural Networks applied for the last step. This model evaluates the reliability of each space and gives the final classification conclusion. Our model links many Neural Networks together, so we call it Multi Artificial Neural Network (MANN). We apply our proposal model for 6 basic fa...
A Study on Group Key Agreement in Sensor Network Environments Using Two-Dimensional Arrays
Directory of Open Access Journals (Sweden)
Moon-Seog Jun
2011-08-01
Full Text Available These days, with the emergence of the concept of ubiquitous computing, sensor networks that collect, analyze and process all the information through the sensors have become of huge interest. However, sensor network technology fundamentally has wireless communication infrastructure as its foundation and thus has security weakness and limitations such as low computing capacity, power supply limitations and price. In this paper, and considering the characteristics of the sensor network environment, we propose a group key agreement method using a keyset pre-distribution of two-dimension arrays that should minimize the exposure of key and personal information. The key collision problems are resolved by utilizing a polygonal shape’s center of gravity. The method shows that calculating a polygonal shape’s center of gravity only requires a very small amount of calculations from the users. The simple calculation not only increases the group key generation efficiency, but also enhances the sense of security by protecting information between nodes.
Directory of Open Access Journals (Sweden)
R. Daud
2013-06-01
Full Text Available Shielding interaction effects of two parallel edge cracks in finite thickness plates subjected to remote tension load is analyzed using a developed finite element analysis program. In the present study, the crack interaction limit is evaluated based on the fitness of service (FFS code, and focus is given to the weak crack interaction region as the crack interval exceeds the length of cracks (b > a. Crack interaction factors are evaluated based on stress intensity factors (SIFs for Mode I SIFs using a displacement extrapolation technique. Parametric studies involved a wide range of crack-to-width (0.05 ≤ a/W ≤ 0.5 and crack interval ratios (b/a > 1. For validation, crack interaction factors are compared with single edge crack SIFs as a state of zero interaction. Within the considered range of parameters, the proposed numerical evaluation used to predict the crack interaction factor reduces the error of existing analytical solution from 1.92% to 0.97% at higher a/W. In reference to FFS codes, the small discrepancy in the prediction of the crack interaction factor validates the reliability of the numerical model to predict crack interaction limits under shielding interaction effects. In conclusion, the numerical model gave a successful prediction in estimating the crack interaction limit, which can be used as a reference for the shielding orientation of other cracks.
BIFURCATION IN A TWO-DIMENSIONAL NEURAL NETWORK MODEL WITH DELAY
Institute of Scientific and Technical Information of China (English)
WEI Jun-jie; ZHANG Chun-rui; LI Xiu-ling
2005-01-01
A kind of 2-dimensional neural network model with delay is considered. By analyzing the distribution of the roots of the characteristic equation associated with the model, a bifurcation diagram was drawn in an appropriate parameter plane. It is found that a line is a pitchfork bifurcation curve. Further more, the stability of each fixed point and existence of Hopf bifurcation were obtained. Finally, the direction of the Hopf bifurcation and the stability of the bifurcating periodic solutions were determined by using the normal form method and centre manifold theory.
Energy Technology Data Exchange (ETDEWEB)
Cardelli, E.; Faba, A. [Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia (Italy); Laudani, A.; Lozito, G.M.; Riganti Fulginei, F.; Salvini, A. [Department of Engineering, Roma Tre University, Via V. Volterra 62, 00146 Rome (Italy)
2016-04-01
This paper presents a hybrid neural network approach to model magnetic hysteresis at macro-magnetic scale. That approach aims to be coupled together with numerical treatments of magnetic hysteresis such as FEM numerical solvers of the Maxwell's equations in time domain, as in case of the non-linear dynamic analysis of electrical machines, and other similar devices, allowing a complete computer simulation with acceptable run times. The proposed Hybrid Neural System consists of four inputs representing the magnetic induction and magnetic field components at each time step and it is trained by 2D and scalar measurements performed on the magnetic material to be modeled. The magnetic induction B is assumed as entry point and the output of the Hybrid Neural System returns the predicted value of the field H at the same time step. Within the Hybrid Neural System, a suitably trained neural network is used for predicting the hysteretic behavior of the material to be modeled. Validations with experimental tests and simulations for symmetric, non-symmetric and minor loops are presented.
Directory of Open Access Journals (Sweden)
Kentaro Inoue
Full Text Available BACKGROUND: For visualizing large-scale biochemical network maps, it is important to calculate the coordinates of molecular nodes quickly and to enhance the understanding or traceability of them. The grid layout is effective in drawing compact, orderly, balanced network maps with node label spaces, but existing grid layout algorithms often require a high computational cost because they have to consider complicated positional constraints through the entire optimization process. RESULTS: We propose a hybrid grid layout algorithm that consists of a non-grid, fast layout (preprocessor algorithm and an approximate pattern matching algorithm that distributes the resultant preprocessed nodes on square grid points. To demonstrate the feasibility of the hybrid layout algorithm, it is characterized in terms of the calculation time, numbers of edge-edge and node-edge crossings, relative edge lengths, and F-measures. The proposed algorithm achieves outstanding performances compared with other existing grid layouts. CONCLUSIONS: Use of an approximate pattern matching algorithm quickly redistributes the laid-out nodes by fast, non-grid algorithms on the square grid points, while preserving the topological relationships among the nodes. The proposed algorithm is a novel use of the pattern matching, thereby providing a breakthrough for grid layout. This application program can be freely downloaded from http://www.cadlive.jp/hybridlayout/hybridlayout.html.
Okada, Arifumi; Nakata, Yohei; Minou, Kosuke; Yoshimura, Masamichi; Kadono, Kohei
2016-12-01
By scanning tunneling microscopy (STM), we investigated two-dimensional (2D) structures of melamine formed on Au(111) surfaces by solvent evaporation. By increasing the evaporation temperature, the well-known ordered honeycomb 2D molecular phase, in which all molecules are linked by hydrogen bonding, changes to four coexisting phases, i.e., a 2D network consisting of linear segments, 1D molecular rows, and hexagonal and distorted hexagonal structures. The first two phases are sometimes observed in ultrahigh vacuum (UHV) on metallic substrates other than Au. The last two phases have lattice parameters close to those of the well-known honeycomb structure. The structural change observed in this study is attributed to local temperature and concentration distributions of the solution and substrate surface during solvent evaporation. From the results, we found that the molecular nanostructures can be tailored by the solvent evaporation method with small changes in temperature.
Ochiai, Tetsuyuki
2016-01-01
We show the presence of Floquet-Weyl and Floquet-topological-insulator phases in a stacked two-dimensional ring-network lattice. The Weyl points in the three-dimensional Brillouin zone and Fermi-arc surface states are clearly demonstrated in the quasienergy spectrum of the system in the Weyl phase. In addition, chiral surface states coexist in this phase. The Floquet-topological-insulator phase is characterized by the winding number of two in the reflection matrices of the semi-infinite system and resulting two gapless surface states in the quasienergy g ap of the bulk. The phase diagram of the system is derived in the two-parameter space of hopping S-matrices among the rings. We also discuss a possible optical realization of the system together with the introduction of synthetic gauge fields.
Wang, Yong; Yang, Zhuoshi; Zhang, Jianpei; Li, Feng; Wen, Hongkai; Shen, Yiran
2016-08-19
In this paper, we consider the problem of reconstructing the temporal and spatial profile of some physical phenomena monitored by large-scale Wireless Sensor Networks (WSNs) in an energy efficient manner. Compressive sensing is one of the popular choices to reduce the energy consumption of the data collection in WSNs. The existing solutions only consider sparsity of sensors' data from either temporal or spatial dimensions. In this paper, we propose a novel data collection strategy, CS²-collector, for WSNs based on the theory of Two Dimensional Compressive Sensing (2DCS). It exploits both temporal and spatial sparsity, i.e., 2D-sparsity of WSNs and achieves significant gain on the tradeoff between the compression ratio and reconstruction accuracy as the numerical simulations and evaluations on different types of sensors' data. More intuitively, with the same given energy budget, CS²-collector provides significantly more accurate reconstruction of the profile of the physical phenomena that are temporal-spatially sparse.
Ochiai, Tetsuyuki
2016-10-01
We show the presence of Floquet-Weyl and Floquet-topological-insulator phases in a stacked two-dimensional ring-network lattice. The Weyl points in the three-dimensional Brillouin zone and Fermi-arc surface states are clearly demonstrated in the quasienergy spectrum of the system in the Floquet-Weyl phase. In addition, chiral surface states coexist in this phase. The Floquet-topological-insulator phase is characterized by the winding number of two in the reflection matrices of the semi-infinite system and resulting two gapless surface states in the quasienergy gap of the bulk. The phase diagram of the system is derived in the two-parameter space of hopping S-matrices among the rings. We also discuss a possible optical realization of the system together with the introduction of synthetic gauge fields.
Two-dimensional shape classification using generalized Fourier representation and neural networks
Chodorowski, Artur; Gustavsson, Tomas; Mattsson, Ulf
2000-04-01
A shape-based classification method is developed based upon the Generalized Fourier Representation (GFR). GFR can be regarded as an extension of traditional polar Fourier descriptors, suitable for description of closed objects, both convex and concave, with or without holes. Explicit relations of GFR coefficients to regular moments, moment invariants and affine moment invariants are given in the paper. The dual linear relation between GFR coefficients and regular moments was used to compare shape features derive from GFR descriptors and Hu's moment invariants. the GFR was then applied to a clinical problem within oral medicine and used to represent the contours of the lesions in the oral cavity. The lesions studied were leukoplakia and different forms of lichenoid reactions. Shape features were extracted from GFR coefficients in order to classify potentially cancerous oral lesions. Alternative classifiers were investigated based on a multilayer perceptron with different architectures and extensions. The overall classification accuracy for recognition of potentially cancerous oral lesions when using neural network classifier was 85%, while the classification between leukoplakia and reticular lichenoid reactions gave 96% (5-fold cross-validated) recognition rate.
Parallel network simulations with NEURON.
Migliore, M; Cannia, C; Lytton, W W; Markram, Henry; Hines, M L
2006-10-01
The NEURON simulation environment has been extended to support parallel network simulations. Each processor integrates the equations for its subnet over an interval equal to the minimum (interprocessor) presynaptic spike generation to postsynaptic spike delivery connection delay. The performance of three published network models with very different spike patterns exhibits superlinear speedup on Beowulf clusters and demonstrates that spike communication overhead is often less than the benefit of an increased fraction of the entire problem fitting into high speed cache. On the EPFL IBM Blue Gene, almost linear speedup was obtained up to 100 processors. Increasing one model from 500 to 40,000 realistic cells exhibited almost linear speedup on 2,000 processors, with an integration time of 9.8 seconds and communication time of 1.3 seconds. The potential for speed-ups of several orders of magnitude makes practical the running of large network simulations that could otherwise not be explored.
Jameson, A. R.; Larsen, M. L.
2016-06-01
Microphysical understanding of the variability in rain requires a statistical characterization of different drop sizes both in time and in all dimensions of space. Temporally, there have been several statistical characterizations of raindrop counts. However, temporal and spatial structures are neither equivalent nor readily translatable. While there are recent reports of the one-dimensional spatial correlation functions in rain, they can only be assumed to represent the two-dimensional (2D) correlation function under the assumption of spatial isotropy. To date, however, there are no actual observations of the (2D) spatial correlation function in rain over areas. Two reasons for this deficiency are the fiscal and the physical impossibilities of assembling a dense network of instruments over even hundreds of meters much less over kilometers. Consequently, all measurements over areas will necessarily be sparsely sampled. A dense network of data must then be estimated using interpolations from the available observations. In this work, a network of 19 optical disdrometers over a 100 m by 71 m area yield observations of drop spectra every minute. These are then interpolated to a 1 m resolution grid. Fourier techniques then yield estimates of the 2D spatial correlation functions. Preliminary examples using this technique found that steadier, light rain decorrelates spatially faster than does the convective rain, but in both cases the 2D spatial correlation functions are anisotropic, reflecting an asymmetry in the physical processes influencing the rain reaching the ground not accounted for in numerical microphysical models.
Que, Ruiyi; Zhu, Rong
2013-12-31
This paper demonstrates a novel flow sensor with two-dimensional 360° direction sensitivity achieved with a simple structure and a novel data fusion algorithm. Four sensing elements with roundabout wires distributed in four quadrants of a circle compose the sensor probe, and work in constant temperature difference (CTD) mode as both Joule heaters and temperature detectors. The magnitude and direction of a fluid flow are measured by detecting flow-induced temperature differences among the four elements. The probe is made of Ti/Au thin-film with a diameter of 2 mm, and is fabricated using micromachining techniques. When a flow goes through the sensor, the flow-induced temperature differences are detected by the sensing elements that also serve as the heaters of the sensor. By measuring the temperature differences among the four sensing elements symmetrically distributed in the sensing area, a full 360° direction sensitivity can be obtained. By using a BP neural network to model the relationship between the readouts of the four sensor elements and flow parameters and execute data fusion, the magnitude and direction of the flow can be deduced. Validity of the sensor design was proven through both simulations and experiments. Wind tunnel experimental results show that the measurement accuracy of the airflow speed reaches 0.72 m/s in the range of 3 m/s-30 m/s and the measurement accuracy of flow direction angle reaches 1.9° in the range of 360°.
Directory of Open Access Journals (Sweden)
Ruiyi Que
2013-12-01
Full Text Available This paper demonstrates a novel flow sensor with two-dimensional 360° direction sensitivity achieved with a simple structure and a novel data fusion algorithm. Four sensing elements with roundabout wires distributed in four quadrants of a circle compose the sensor probe, and work in constant temperature difference (CTD mode as both Joule heaters and temperature detectors. The magnitude and direction of a fluid flow are measured by detecting flow-induced temperature differences among the four elements. The probe is made of Ti/Au thin-film with a diameter of 2 mm, and is fabricated using micromachining techniques. When a flow goes through the sensor, the flow-induced temperature differences are detected by the sensing elements that also serve as the heaters of the sensor. By measuring the temperature differences among the four sensing elements symmetrically distributed in the sensing area, a full 360° direction sensitivity can be obtained. By using a BP neural network to model the relationship between the readouts of the four sensor elements and flow parameters and execute data fusion, the magnitude and direction of the flow can be deduced. Validity of the sensor design was proven through both simulations and experiments. Wind tunnel experimental results show that the measurement accuracy of the airflow speed reaches 0.72 m/s in the range of 3 m/s–30 m/s and the measurement accuracy of flow direction angle reaches 1.9° in the range of 360°.
Wang, Yong; Yang, Zhuoshi; Zhang, Jianpei; Li, Feng; Wen, Hongkai; Shen, Yiran
2016-01-01
In this paper, we consider the problem of reconstructing the temporal and spatial profile of some physical phenomena monitored by large-scale Wireless Sensor Networks (WSNs) in an energy efficient manner. Compressive sensing is one of the popular choices to reduce the energy consumption of the data collection in WSNs. The existing solutions only consider sparsity of sensors’ data from either temporal or spatial dimensions. In this paper, we propose a novel data collection strategy, CS2-collector, for WSNs based on the theory of Two Dimensional Compressive Sensing (2DCS). It exploits both temporal and spatial sparsity, i.e., 2D-sparsity of WSNs and achieves significant gain on the tradeoff between the compression ratio and reconstruction accuracy as the numerical simulations and evaluations on different types of sensors’ data. More intuitively, with the same given energy budget, CS2-collector provides significantly more accurate reconstruction of the profile of the physical phenomena that are temporal-spatially sparse. PMID:27548180
Ochiai, Tetsuyuki
2017-02-01
We study the effects of a synthetic gauge field and pseudospin-orbit interaction in a stacked two-dimensional ring-network model. The model was introduced to simulate light propagation in the corresponding ring-resonator lattice, and is thus completely bosonic. Without these two items, the model exhibits Floquet-Weyl and Floquet-topological-insulator phases with topologically gapless and gapped band structures, respectively. The synthetic magnetic field implemented in the model results in a three-dimensional Hofstadter-butterfly-type spectrum in a photonic platform. The resulting gaps are characterized by the winding number of relevant S-matrices together with the Chern number of the bulk bands. The pseudospin-orbit interaction is defined as the mixing term between two pseudospin degrees of freedom in the rings, namely, the clockwise and counter-clockwise modes. It destroys the Floquet-topological-insulator phases, while the Floquet-Weyl phase with multiple Weyl points can be preserved by breaking the space-inversion symmetry. Implementing both the synthetic gauge field and pseudospin-orbit interaction requires a certain nonreciprocity.
Energy Technology Data Exchange (ETDEWEB)
Chair, Noureddine, E-mail: n.chair@ju.edu.jo
2014-02-15
We have recently developed methods for obtaining exact two-point resistance of the complete graph minus N edges. We use these methods to obtain closed formulas of certain trigonometrical sums that arise in connection with one-dimensional lattice, in proving Scott’s conjecture on permanent of Cauchy matrix, and in the perturbative chiral Potts model. The generalized trigonometrical sums of the chiral Potts model are shown to satisfy recursion formulas that are transparent and direct, and differ from those of Gervois and Mehta. By making a change of variables in these recursion formulas, the dimension of the space of conformal blocks of SU(2) and SO(3) WZW models may be computed recursively. Our methods are then extended to compute the corner-to-corner resistance, and the Kirchhoff index of the first non-trivial two-dimensional resistor network, 2×N. Finally, we obtain new closed formulas for variant of trigonometrical sums, some of which appear in connection with number theory. -- Highlights: • Alternative derivation of certain trigonometrical sums of the chiral Potts model are given. • Generalization of these trigonometrical sums satisfy recursion formulas. • The dimension of the space of conformal blocks may be computed from these recursions. • Exact corner-to-corner resistance, the Kirchhoff index of 2×N are given.
Energy Technology Data Exchange (ETDEWEB)
Shimada, Kotaro, E-mail: kotaro@kuhp.kyoto-u.ac.jp [Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University, Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507 (Japan); Isoda, Hiroyoshi, E-mail: sayuki@kuhp.kyoto-u.ac.jp [Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University, Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507 (Japan); Okada, Tomohisa, E-mail: tomokada@kuhp.kyoto-u.ac.jp [Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University, Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507 (Japan); Kamae, Toshikazu, E-mail: toshi13@kuhp.kyoto-u.ac.jp [Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University, Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507 (Japan); Arizono, Shigeki, E-mail: arizono@kuhp.kyoto-u.ac.jp [Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University, Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507 (Japan); Hirokawa, Yuusuke, E-mail: yuusuke@kuhp.kyoto-u.ac.jp [Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University, Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507 (Japan); Shibata, Toshiya, E-mail: ksj@kuhp.kyoto-u.ac.jp [Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University, Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507 (Japan); Togashi, Kaori, E-mail: ktogashi@kuhp.kyoto-u.ac.jp [Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University, Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507 (Japan)
2011-01-15
Objective: To study whether shortening the acquisition time for selective hepatic artery visualization is feasible without image quality deterioration by adopting two-dimensional (2D) parallel imaging (PI) and short tau inversion recovery (STIR) methods. Materials and methods: Twenty-four healthy volunteers were enrolled. 3D true steady-state free-precession imaging with a time spatial labeling inversion pulse was conducted using 1D or 2D-PI and fat suppression by chemical shift selective (CHESS) or STIR methods. Three groups of different scan conditions were assigned and compared: group A (1D-PI factor 2 and CHESS), group B (2D-PI factor 2 x 2 and CHESS), and group C (2D-PI factor 2 x 2 and STIR). The artery-to-liver contrast was quantified, and the quality of artery visualization and overall image quality were scored. Results: The mean scan time was 9.5 {+-} 1.0 min (mean {+-} standard deviation), 5.9 {+-} 0.8 min, and 5.8 {+-} 0.5 min in groups A, B, and C, respectively, and was significantly shorter in groups B and C than in group A (P < 0.01). The artery-to-liver contrast was significantly better in group C than in groups A and B (P < 0.01). The scores for artery visualization and overall image quality were worse in group B than in groups A and C. The differences were statistically significant (P < 0.05) regarding the arterial branches of segments 4 and 8. Between group A and group C, which had similar scores, there were no statistically significant differences. Conclusion: Shortening the acquisition time for selective hepatic artery visualization was feasible without deterioration of the image quality by the combination of 2D-PI and STIR methods. It will facilitate using non-contrast-enhanced MRA in clinical practice.
Parallel Graph Partitioning for Complex Networks
Meyerhenke, Henning; Schulz, Christian
2014-01-01
Processing large complex networks like social networks or web graphs has recently attracted considerable interest. In order to do this in parallel, we need to partition them into pieces of about equal size. Unfortunately, previous parallel graph partitioners originally developed for more regular mesh-like networks do not work well for these networks. This paper addresses this problem by parallelizing and adapting the label propagation technique originally developed for graph clustering. By introducing size constraints, label propagation becomes applicable for both the coarsening and the refinement phase of multilevel graph partitioning. We obtain very high quality by applying a highly parallel evolutionary algorithm to the coarsened graph. The resulting system is both more scalable and achieves higher quality than state-of-the-art systems like ParMetis or PT-Scotch. For large complex networks the performance differences are very big. For example, our algorithm can partition a web graph with 3.3 billion edges ...
Coupled One and Two Dimensional Model for River Network Flow and Sediment Transport%一二维耦合河网水沙模型研究
Institute of Scientific and Technical Information of China (English)
吕文丽; 张旭
2011-01-01
Based on previous research, a new one and two-dimensional coupled model of river water and sediment was proposed.With reference to the three-level solution for one-dimensional river network water mode, the two-dimensional river section will be generalized to river section within the river network.One and two dimensional coupled river network sediment model will be established with the balance of flow amount and sediment transport.The model sets up the chasing relationship between variables of water level and sediment content at the end and first section to further establish matrix equations of the whole one and two-dimensional river network node water level and sediment content.Though the verification and calculation for generalized river network from Datong to Zhenjiang in the lower reaches of the Yangtze River, it is found that the model is of great practical value.%借鉴河网水流的三级解法,将二维河段概化为河网内部河段,通过河网节点流量和输沙量的平衡,建立一二维耦合河网水沙模型.模型采用全隐式方法建立二维河段以首末断面的水位和含沙量为中间变量的矩阵追赶关系,进而建立整个一二维河网的节点水位及含沙量的矩阵方程组.对方程组的求解,可实现一二维水沙模型的耦合求解.通过对长江下游大通至镇江概化河网的验证计算,表明模型具有很好的实用价值.
Shevchenko, O. S.; Kopeliovich, A. I.
2016-03-01
The energy spectrum of a quasi-two-dimensional electron gas in an in-plane magnetic field is studied using the perturbation theory and quasiclassical approach in the presence of the Rashba and Dresselhaus spin-orbit coupling. The existence of the intersection of energy sublevels in electron spectrum is demonstrated. The reciprocal mass tensor of electrons is analyzed. The heat capacity of the degenerate electron gas is examined, and its relations with the key features of the spectrum are shown.
Parallel computing and networking; Heiretsu keisanki to network
Energy Technology Data Exchange (ETDEWEB)
Asakawa, E.; Tsuru, T. [Japan National Oil Corp., Tokyo (Japan); Matsuoka, T. [Japan Petroleum Exploration Co. Ltd., Tokyo (Japan)
1996-05-01
This paper describes the trend of parallel computers used in geophysical exploration. Around 1993 was the early days when the parallel computers began to be used for geophysical exploration. Classification of these computers those days was mainly MIMD (multiple instruction stream, multiple data stream), SIMD (single instruction stream, multiple data stream) and the like. Parallel computers were publicized in the 1994 meeting of the Geophysical Exploration Society as a `high precision imaging technology`. Concerning the library of parallel computers, there was a shift to PVM (parallel virtual machine) in 1993 and to MPI (message passing interface) in 1995. In addition, the compiler of FORTRAN90 was released with support implemented for data parallel and vector computers. In 1993, networks used were Ethernet, FDDI, CDDI and HIPPI. In 1995, the OC-3 products under ATM began to propagate. However, ATM remains to be an interoffice high speed network because the ATM service has not spread yet for the public network. 1 ref.
Institute of Scientific and Technical Information of China (English)
LI,Bao-Long(李宝龙); XU,Yan(徐艳); LIU,Qi(刘琦); WANG,Hua-Qin(王化勤); XU,Zheng(徐正)
2002-01-01
The copper(Ⅱ) complex [Cu3(nta)2(azpy)2(H2O)2] @6H2O(nta= nitrilotriacetate, azpy= 4,4'-azobispyridine) has been synthesized and characterized. The X-ray analysis reveals that there are two kinds of copper(Ⅱ) coordination environments.Cu(1) has a distorted square plane symmetry and Cu(2) has a distorted octahedral symmetry. Cu(1)is linked to Cu(2)through nta and bound to Cu(1C) by azpy, and Cu(2) islinked to Cu(2A) through azpy, which extends to two-dimensional network with large rhombus 1.2 nm× 1.7 nm.
Institute of Scientific and Technical Information of China (English)
WANG,Da-Qi(王大奇); YU,Qing-Jiang(于清江); DOU,Jian-Min(窦建民)
2002-01-01
The novel complex [K(18-C-6)]2[Cd(mnt)2] [18-C-6=18-crown-6, mnt= 1, 2-dicyanoethen-1, 2-dithiolate, C2S2-(CN)2- 2] was synthesized and characterized by elemental analysis,IR spectrum and X-ray diffraction analysis. The complex displays two-dimensional network structure of [ K(18-C-6)] complex segments and [Cd(mnt)2] complex segment bridged by S-K-S, S-K-N and N-K-N interactions between adjacent [K(18-C-6)] and [Cd(mnt)2] units.
Institute of Scientific and Technical Information of China (English)
ZHOU Ningyu; ZHAO Dongfeng; DING Hongwei
2008-01-01
A higher quality of service (QoS) is provided for ad hoc networks through a multi-channel and slotted random multi-access (MSRM) protocol with two-dimensional probability. For this protocol, the system time is slotted into a time slot with high channel utilization realized by the choice of two parameters p1 and p2, and the channel load equilibrium. The protocol analyzes the throughput of the MSRM protocol for a load equilibrium state and the throughput based on priority. Simulations agree with the theoretical analysis. The simulations also show that the slotted-time system is better than the continuous-time system.
Institute of Scientific and Technical Information of China (English)
董悫; 王江晴; 孙阳光
2015-01-01
The traditional two-dimensional Otsu thresholding segmentation algorithms do not think about human vision characteristics and the result of segmentation can not match up to the visual perception of human eye. In order to solve this problem,an algorithm based on the two-dimensional Otsu algorithm and the lateral inhibition network is proposed. In this algorithm, the lateral inhibition network of human visual system that has the features of enhancing center and inhibiting surroundings is fully used. The lateral inhibition network is utilized to process the original picture and obtains the lateral inhibition picture. A two-dimensional histogram based on the gray information and lateral inhibition information of pixels is established. The maximum between-cluster variance is chosen as the criterion to select the optimal threshold. Experimental results show that this algorithm not only is well adapted to the contrast and illumination intensity, but also has the capacity for fitting the breaks compared with the traditional Otsu algorithm and two-dimensional Otsu algorithm. It improves the robustness to image noise and obtains more perfect segmentation results.%传统二维Otsu阈值分割算法未考虑人类视觉特性，分割结果不符合人眼视觉感受。为此，提出一种二维Otsu算法与侧抑制网络相结合的分割算法。该算法从基于人类视觉系统的侧抑制网络出发，利用侧抑制网络增强中心，抑制周围的特性，通过侧抑制网络处理原始图像，得到侧抑制图像，构建基于像素的灰度信息和侧抑制信息的二维直方图，并采用类间最大方差作为最佳阈值的选取准则。实验结果表明，与传统的Otsu算法和二维Otsu算法等相比，该算法具有较好的对比度、光照强度适应性和间断拟合能力，并能提高对图像噪声的鲁棒性，获得更理想的分割结果。
Zhou, Jiang; Huang, Ying; Cao, Xiehong; Ouyang, Bo; Sun, Wenping; Tan, Chaoliang; Zhang, Yu; Ma, Qinglang; Liang, Shuquan; Yan, Qingyu; Zhang, Hua
2015-04-01
We report the synthesis of two-dimensional (2D) NiCo2O4 nanosheet-coated three-dimensional graphene network (3DGN), which is then used as an electrode for high-rate, long-cycle-life supercapacitors. Using the 3DGN and nanoporous nanosheets, an ultrahigh specific capacitance (2173 F g-1 at 6 A g-1), excellent rate capability (954 F g-1 at 200 A g-1) and superior long-term cycling performance (94% capacitance retention after 14 000 cycles at 100 A g-1) are achieved.We report the synthesis of two-dimensional (2D) NiCo2O4 nanosheet-coated three-dimensional graphene network (3DGN), which is then used as an electrode for high-rate, long-cycle-life supercapacitors. Using the 3DGN and nanoporous nanosheets, an ultrahigh specific capacitance (2173 F g-1 at 6 A g-1), excellent rate capability (954 F g-1 at 200 A g-1) and superior long-term cycling performance (94% capacitance retention after 14 000 cycles at 100 A g-1) are achieved. Electronic supplementary information (ESI) available: Experimental details, Fig. S1-S9, and Table S1. See DOI: 10.1039/c4nr06527a
Yari, Abdollah; Saeidikhah, Marzieh
2015-11-01
In this work, a gold electrode (GE) was modified by coating with two dimensional silica network/citrate capped gold nanoparticles-poly(diallyldimethylammonium chloride) (GE-TDSN-CGNP-PDDA) for ultra-sensitive determination of Bovine Serum Albumin (BSA). After covalently binding of a silica network (in two-dimensional form) on the surface of a gold electrode, via twice in situ hydrolysis of 3-mercaptopropyl-tri-ethoxysilane, citrate capped gold nanoparticles (CGNP) were chemically adsorbed on the silica cage. Subsequently, PDDA was bonded to CGNP via electrostatic interaction of positively charged polymer and negatively charged stabilizer of CGNP. Analytical properties of GE-TDSN-CGNP-PDDA were studied by Electrochemical Impedance Spectroscopy (EIS). The detection limit for measured BSA was found to be 8.4×10(-13) mol L(-1) and the measuring linear concentration range of the proposed sensor was 9.9×10(-12)-1.6×10(-10) mol L(-1) of BSA. In addition, GE-TDSN-CGNP-PDDA exhibited good stability with high selectivity and was applied for determination of BSA in some samples with satisfactory results.
Energy Technology Data Exchange (ETDEWEB)
Zhang, Yijing, E-mail: yzhng123@illinois.edu; Moore, Keegan J.; Vakakis, Alexander F. [Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States); McFarland, D. Michael [Department of Aerospace Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States)
2015-12-21
We study passive pulse redirection and nonlinear targeted energy transfer in a granular network composed of two semi-infinite, ordered homogeneous granular chains mounted on linear elastic foundations and coupled by weak linear stiffnesses. Periodic excitation in the form of repetitive half-sine pulses is applied to one of the chains, designated as the “excited chain,” whereas the other chain is initially at rest and is regarded as the “absorbing chain.” We show that passive pulse redirection and targeted energy transfer from the excited to the absorbing chain can be achieved by macro-scale realization of the spatial analog of the Landau-Zener quantum tunneling effect. This is realized by finite stratification of the elastic foundation of the excited chain and depends on the system parameters (e.g., the percentage of stratification) and on the parameters of the periodic excitation. Utilizing empirical mode decomposition and numerical Hilbert transforms, we detect the existence of two distinct nonlinear phenomena in the periodically forced network; namely, (i) energy localization in the absorbing chain due to sustained 1:1 resonance capture leading to irreversible pulse redirection from the excited chain, and (ii) continuous energy exchanges in the form of nonlinear beats between the two chains in the absence of resonance capture. Our results extend previous findings of transient passive energy redirection in impulsively excited granular networks and demonstrate that steady state passive pulse redirection in these networks can be robustly achieved under periodic excitation.
The mode of toxic action (MoA) has been recognized as a key determinant of chemical toxicity but MoA classification in aquatic toxicology has been limited. We developed a Bayesian network model to classify aquatic toxicity mode of action using a recently published dataset contain...
The mode of toxic action (MoA) has been recognized as a key determinant of chemical toxicity, but development of predictive MoA classification models in aquatic toxicology has been limited. We developed a Bayesian network model to classify aquatic toxicity MoA using a recently pu...
Zimmerman, R. W.; Leung, C. T.
2009-12-01
Most oil and gas reservoirs, as well as most potential sites for nuclear waste disposal, are naturally fractured. In these sites, the network of fractures will provide the main path for fluid to flow through the rock mass. In many cases, the fracture density is so high as to make it impractical to model it with a discrete fracture network (DFN) approach. For such rock masses, it would be useful to have recourse to analytical, or semi-analytical, methods to estimate the macroscopic hydraulic conductivity of the fracture network. We have investigated single-phase fluid flow through generated stochastically two-dimensional fracture networks. The centers and orientations of the fractures are uniformly distributed, whereas their lengths follow a lognormal distribution. The aperture of each fracture is correlated with its length, either through direct proportionality, or through a nonlinear relationship. The discrete fracture network flow and transport simulator NAPSAC, developed by Serco (Didcot, UK), is used to establish the “true” macroscopic hydraulic conductivity of the network. We then attempt to match this value by starting with the individual fracture conductances, and using various upscaling methods. Kirkpatrick’s effective medium approximation, which works well for pore networks on a core scale, generally underestimates the conductivity of the fracture networks. We attribute this to the fact that the conductances of individual fracture segments (between adjacent intersections with other fractures) are correlated with each other, whereas Kirkpatrick’s approximation assumes no correlation. The power-law averaging approach proposed by Desbarats for porous media is able to match the numerical value, using power-law exponents that generally lie between 0 (geometric mean) and 1 (harmonic mean). The appropriate exponent can be correlated with statistical parameters that characterize the fracture density.
DEFF Research Database (Denmark)
Zhang, Jingdong; Chi, Qijin; Nielsen, Jens Ulrik;
2000-01-01
Microscopic structures for molecular monolayers of L-cysteine and L-cystine assembled on Au(111) have been disclosed by employing electrochemistry and in situ scanning tunneling microscopy (STM). HighresolutionSTMimages show that the adlayers of both cyteine and cystine exhibit highly......-ordered networklike clusters with (3x3 6)R30° structure. By combining the surface coverage estimated from voltammetric data, each cluster is demonstrated to include six individual cysteine molecules or three cystine molecules. As a comparison, no cluster structure is observed for the 1-butanethiol adlayer prepared...... and examined under the same conditions as those for cysteine and cystine. This suggests that intermolecular and intramolecular hydrogen bonds among adsorbed cysteine or cystine molecules could be responsible for the origin of the cluster-network structures for the adlayers. Several models are proposed and used...
A TCAM-based Two-dimensional Prefix Packet Classification Algorithm
Institute of Scientific and Technical Information of China (English)
王志恒; 刘刚; 白英彩
2004-01-01
Packet classification (PC) has become the main method to support the quality of service and security of network application. And two-dimensional prefix packet classification (PPC) is the popular one. This paper analyzes the problem of ruler conflict, and then presents a TCAMbased two-dimensional PPC algorithm. This algorithm makes use of the parallelism of TCAM to lookup the longest prefix in one instruction cycle. Then it uses a memory image and associated data structures to eliminate the conflicts between rulers, and performs a fast two-dimensional PPC.Compared with other algorithms, this algorithm has the least time complexity and less space complexity.
Huang, Ching-Yu; Wei, Tzu-Chieh
2016-04-01
Symmetry-protected topological (SPT) phases exhibit nontrivial order if symmetry is respected but are adiabatically connected to the trivial product phase if symmetry is not respected. However, unlike the symmetry-breaking phase, there is no local order parameter for SPT phases. Here we employ a tensor-network method to compute the topological invariants characterized by the simulated modular S and T matrices to study transitions in a few families of two-dimensional (2D) wave functions which are ZN (N =2 and3 ) symmetric. We find that in addition to the topologically ordered phases, the modular matrices can be used to identify nontrivial SPT phases and detect transitions between different SPT phases as well as between symmetric and symmetry-breaking phases. Therefore modular matrices can be used to characterize various types of gapped phases in a unifying way.
Directory of Open Access Journals (Sweden)
Martin Alberto JM
2009-01-01
Full Text Available Abstract Background Prediction of protein structures from their sequences is still one of the open grand challenges of computational biology. Some approaches to protein structure prediction, especially ab initio ones, rely to some extent on the prediction of residue contact maps. Residue contact map predictions have been assessed at the CASP competition for several years now. Although it has been shown that exact contact maps generally yield correct three-dimensional structures, this is true only at a relatively low resolution (3–4 Å from the native structure. Another known weakness of contact maps is that they are generally predicted ab initio, that is not exploiting information about potential homologues of known structure. Results We introduce a new class of distance restraints for protein structures: multi-class distance maps. We show that Cα trace reconstructions based on 4-class native maps are significantly better than those from residue contact maps. We then build two predictors of 4-class maps based on recursive neural networks: one ab initio, or relying on the sequence and on evolutionary information; one template-based, or in which homology information to known structures is provided as a further input. We show that virtually any level of sequence similarity to structural templates (down to less than 10% yields more accurate 4-class maps than the ab initio predictor. We show that template-based predictions by recursive neural networks are consistently better than the best template and than a number of combinations of the best available templates. We also extract binary residue contact maps at an 8 Å threshold (as per CASP assessment from the 4-class predictors and show that the template-based version is also more accurate than the best template and consistently better than the ab initio one, down to very low levels of sequence identity to structural templates. Furthermore, we test both ab-initio and template-based 8
Cheng, Jianlin; Saigo, Hiroto; Baldi, Pierre
2006-03-15
The formation of disulphide bridges between cysteines plays an important role in protein folding, structure, function, and evolution. Here, we develop new methods for predicting disulphide bridges in proteins. We first build a large curated data set of proteins containing disulphide bridges to extract relevant statistics. We then use kernel methods to predict whether a given protein chain contains intrachain disulphide bridges or not, and recursive neural networks to predict the bonding probabilities of each pair of cysteines in the chain. These probabilities in turn lead to an accurate estimation of the total number of disulphide bridges and to a weighted graph matching problem that can be addressed efficiently to infer the global disulphide bridge connectivity pattern. This approach can be applied both in situations where the bonded state of each cysteine is known, or in ab initio mode where the state is unknown. Furthermore, it can easily cope with chains containing an arbitrary number of disulphide bridges, overcoming one of the major limitations of previous approaches. It can classify individual cysteine residues as bonded or nonbonded with 87% specificity and 89% sensitivity. The estimate for the total number of bridges in each chain is correct 71% of the times, and within one from the true value over 94% of the times. The prediction of the overall disulphide connectivity pattern is exact in about 51% of the chains. In addition to using profiles in the input to leverage evolutionary information, including true (but not predicted) secondary structure and solvent accessibility information yields small but noticeable improvements. Finally, once the system is trained, predictions can be computed rapidly on a proteomic or protein-engineering scale. The disulphide bridge prediction server (DIpro), software, and datasets are available through www.igb.uci.edu/servers/psss.html.
Two-dimensional quantum repeaters
Wallnöfer, J.; Zwerger, M.; Muschik, C.; Sangouard, N.; Dür, W.
2016-11-01
The endeavor to develop quantum networks gave rise to a rapidly developing field with far-reaching applications such as secure communication and the realization of distributed computing tasks. This ultimately calls for the creation of flexible multiuser structures that allow for quantum communication between arbitrary pairs of parties in the network and facilitate also multiuser applications. To address this challenge, we propose a two-dimensional quantum repeater architecture to establish long-distance entanglement shared between multiple communication partners in the presence of channel noise and imperfect local control operations. The scheme is based on the creation of self-similar multiqubit entanglement structures at growing scale, where variants of entanglement swapping and multiparty entanglement purification are combined to create high-fidelity entangled states. We show how such networks can be implemented using trapped ions in cavities.
Parallel Evolutionary Optimization for Neuromorphic Network Training
Energy Technology Data Exchange (ETDEWEB)
Schuman, Catherine D [ORNL; Disney, Adam [University of Tennessee (UT); Singh, Susheela [North Carolina State University (NCSU), Raleigh; Bruer, Grant [University of Tennessee (UT); Mitchell, John Parker [University of Tennessee (UT); Klibisz, Aleksander [University of Tennessee (UT); Plank, James [University of Tennessee (UT)
2016-01-01
One of the key impediments to the success of current neuromorphic computing architectures is the issue of how best to program them. Evolutionary optimization (EO) is one promising programming technique; in particular, its wide applicability makes it especially attractive for neuromorphic architectures, which can have many different characteristics. In this paper, we explore different facets of EO on a spiking neuromorphic computing model called DANNA. We focus on the performance of EO in the design of our DANNA simulator, and on how to structure EO on both multicore and massively parallel computing systems. We evaluate how our parallel methods impact the performance of EO on Titan, the U.S.'s largest open science supercomputer, and BOB, a Beowulf-style cluster of Raspberry Pi's. We also focus on how to improve the EO by evaluating commonality in higher performing neural networks, and present the result of a study that evaluates the EO performed by Titan.
Li, Yang; Xiao, Jie; Shubina, Tatyana E; Chen, Min; Shi, Ziliang; Schmid, Martin; Steinrück, Hans-Peter; Gottfried, J Michael; Lin, Nian
2012-04-11
We investigated the coordination self-assembly and metalation reaction of Cu with 5,10,15,20-tetra(4-pyridyl)porphyrin (2HTPyP) on a Au(111) surface by means of scanning tunneling microscopy, X-ray photoelectron spectroscopy, and density functional theory calculations. 2HTPyP was found to interact with Cu through both the peripheral pyridyl groups and the porphyrin core. Pairs of pyridyl groups from neighboring molecules coordinate Cu(0) atoms, which leads to the formation of a supramolecular metal-organic coordination network. The network formation occurs at room temperature; annealing at 450 K enhances the process. The interaction of Cu with the porphyrin core is more complex. At room temperature, formation of an initial complex Cu(0)-2HTPyP is observed. Annealing at 450 K activates an intramolecular redox reaction, by which the coordinated Cu(0) is oxidized to Cu(II) and the complex Cu(II)TPyP is formed. The coordination network consists then of Cu(II) complexes linked by Cu(0) atoms; that is, it represents a mixed-valence two-dimensional coordination network consisting of an ordered array of Cu(II) and Cu(0) centers. Above 520 K, the network degrades and the Cu atoms in the linking positions diffuse into the substrate, while the Cu(II)TPyP complexes form a close-packed structure that is stabilized by weak intermolecular interactions. Density functional theory investigations show that the reaction with Cu(0) proceeds via formation of an initial complex between metal atom and porphyrin followed by formation of Cu(II) porphyrin within the course of the reaction. The activation barrier of the rate limiting step was found to be 24-37 kcal mol(-1) depending on the method used. In addition, linear coordination of a Cu atom by two CuTPyP molecules is favorable according to gas-phase calculations. © 2012 American Chemical Society
Osserman, Robert
2011-01-01
The basic component of several-variable calculus, two-dimensional calculus is vital to mastery of the broader field. This extensive treatment of the subject offers the advantage of a thorough integration of linear algebra and materials, which aids readers in the development of geometric intuition. An introductory chapter presents background information on vectors in the plane, plane curves, and functions of two variables. Subsequent chapters address differentiation, transformations, and integration. Each chapter concludes with problem sets, and answers to selected exercises appear at the end o
Juday, Richard D. (Inventor)
1992-01-01
A two-dimensional vernier scale is disclosed utilizing a cartesian grid on one plate member with a polar grid on an overlying transparent plate member. The polar grid has multiple concentric circles at a fractional spacing of the spacing of the cartesian grid lines. By locating the center of the polar grid on a location on the cartesian grid, interpolation can be made of both the X and Y fractional relationship to the cartesian grid by noting which circles coincide with a cartesian grid line for the X and Y direction.
二维映射神经元网络同步%Synchronization of Neuronal Networks Using Two-dimensional Map
Institute of Scientific and Technical Information of China (English)
刘勇
2013-01-01
Experimental results have confirmed that the electric activity of individual neuron has a steady state,a spike state and a spiking-bursting state.The synchronization of neuron is investi-gated in the regular network by a simple two-dimensional map model.The influence of coupling strength on the synchronization of neuronal networks is discussed by computing factor of syn-chronization.%实验研究发现神经元的电活动有静息态、激发态以及簇发态的特征。利用简单的二维映射神经元模型构造规则网络来研究神经元网络放电的同步机制。通过计算同步因子探讨神经元网络同步，分析了耦合强度对神经元网络同步的影响。
Directory of Open Access Journals (Sweden)
Haiyan Li
Full Text Available Angiogenesis is very important for vascularized tissue engineering. In this study, we found that a two-dimensional co-culture of human bone marrow stromal cell (HBMSC and human umbical vein endothelial cell (HUVEC is able to stimulate the migration of co-cultured HUVEC and induce self-assembled network formation. During this process, expression of vascular endothelial growth factor (VEGF₁₆₅ was upregulated in co-cultured HBMSC. Meanwhile, VEGF₁₆₅-receptor2 (KDR and urokinase-type plasminogen activator (uPA were upregulated in co-cultured HUVEC. Functional studies show that neutralization of VEGF₁₆₅ blocked the migration and the rearrangement of the cells and downregulated the expression of uPA and its receptor. Blocking of vascular endothelial-cadherin (VE-cad did not affect the migration of co-cultured HUVEC but suppressed the self-assembled network formation. In conclusion, co-cultures upregulated the expression of VEGF₁₆₅ in co-cultured HBMSC; VEGF₁₆₅ then activated uPA in co-cultured HUVEC, which might be responsible for initiating the migration and the self-assembled network formation with the participation of VE-cad. All of these results indicated that only the direct contact of HBMSC and HUVEC and their respective dialogue are sufficient to stimulate secretion of soluble factors and to activate molecules that are critical for self-assembled network formation which show a great application potential for vascularization in tissue engineering.
Parallelizing dynamic sequential programs using polyhedral process networks
Nadezhkin, Dmitry
2012-01-01
The Polyhedral Process Network (PPN) is a suitable parallel model of computation (MoC) used to specify embedded streaming applications in a parallel form facilitating the efficient mapping onto embedded parallel execution platforms. Unfortunately, specifying an application using a parallel MoC is a
Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J
2015-01-01
In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron.
Directory of Open Access Journals (Sweden)
Zhiqiang Guo
Full Text Available In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D2PCA and a Radial Basis Function Neural Network (RBFNN to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA and independent component analysis (ICA. The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron.
Two-dimensional optical spectroscopy
Cho, Minhaeng
2009-01-01
Discusses the principles and applications of two-dimensional vibrational and optical spectroscopy techniques. This book provides an account of basic theory required for an understanding of two-dimensional vibrational and electronic spectroscopy.
Larson, Elliot D; Groskreutz, Stephen R; Harmes, David C; Gibbs-Hall, Ian C; Trudo, Sabrina P; Allen, Robert C; Rutan, Sarah C; Stoll, Dwight R
2013-05-01
Various implementations of two-dimensional high-performance liquid chromatography are increasingly being developed and applied to the analysis of complex materials, including those encountered in the analysis of foods, beverages, and nutraceuticals. Previously, we introduced the concept of selective comprehensive two-dimensional liquid chromatography (sLC × LC) as a hybrid between the more conventional, but extreme opposite sampling modes of heartcutting (LC-LC) and fully comprehensive (LC × LC) 2D separation. The sLC × LC approach breaks the link between first dimension ((1)D) sampling time and second dimension ((2)D) analysis time that is faced in LC × LC and allows very rapid (as low as 1 s) sampling of highly efficient (1)D separations, while at the same time allowing efficient (2)D separations on the timescale of tens of seconds. In this paper, we improve upon our previous sLC × LC work by demonstrating the ability to perform the processes of (1)D sampling and (2)D separation in parallel. This significantly improves the flexibility of the technique and allows targeted analysis of analytes that elute close together in time in the (1)D separation. To demonstrate the value of this added capability, we have developed a sLC × LC method using multi-wavelength ultraviolet absorbance detection for the quantitative analysis of six target furanocoumarin compounds in extracts of celery, parsley, and parsnips. We show that (2)D separations of (1)D effluent containing the target compounds of interest reveal the presence of unanticipated interferent peaks that would otherwise compromise the quantitative accuracy of the method. We also demonstrate the application of the chemometric method iterative key set factor analysis with alternating least-squares to sLC × LC to mathematically resolve target compounds that are only slightly separated chromatographically but not sufficiently resolved for accurate quantitation.
Kalyanapu, A. J.; Dullo, T. T.; Thornton, J. C.; Auld, L. A.
2015-12-01
Obion River, is located in the northwestern Tennessee region, and discharges into the Mississippi River. In the past, the river system was largely channelized for agricultural purposes that resulted in increased erosion, loss of wildlife habitat and downstream flood risks. These impacts are now being slowly reversed mainly due to wetland restoration. The river system is characterized by a large network of "loops" around the main channels that hold water either from excess flows or due to flow diversions. Without data on each individual channel, levee, canal, or pond it is not known where the water flows from or to. In some segments along the river, the natural channel has been altered and rerouted by the farmers for their irrigation purposes. Satellite imagery can aid in identifying these features, but its spatial coverage is temporally sparse. All the alterations that have been done to the watershed make it difficult to develop hydraulic models, which could predict flooding and droughts. This is especially true when building one-dimensional (1D) hydraulic models compared to two-dimensional (2D) models, as the former cannot adequately simulate lateral flows in the floodplain and in complex terrains. The objective of this study therefore is to study the performance of 1D and 2D flood models in this complex river system, evaluate the limitations of 1D models and highlight the advantages of 2D models. The study presents the application of HEC-RAS and HEC-2D models developed by the Hydrologic Engineering Center (HEC), a division of the US Army Corps of Engineers. The broader impacts of this study is the development of best practices for developing flood models in channelized river systems and in agricultural watersheds.
A Network Model for Parallel Line Balancing Problem
Recep Benzer; Hadi Gökçen; Tahsin Çetinyokus; Hakan Çerçioglu
2007-01-01
Gökçen et al. (2006) have proposed several procedures and a mathematical model on single-model (product) assembly line balancing (ALB) problem with parallel lines. In parallel ALB problem, the goal is to balance more than one assembly line together. In this paper, a network model for parallel ALB problem has been proposed and illustrated on a numerical example. This model is a new approach for parallel ALB and it provides a different point of view for i...
DIRECT DISPLACEMENT OF PARALLEL MECHANISM WITH WAVELET NETWORK
Institute of Scientific and Technical Information of China (English)
CHEN Weishan; CHEN Hua; LIU Junkao
2007-01-01
A new method solution for the direct displacement of parallel mechanism, wavelet network method, is proposed. Comparing with the classical analytical and numerical methods, this method can be extended to any parallel mechanism with any selected degree of freedom and configuration. A wavelet network suiting to approach multi-input and multi-output system is constructed. The network is optimized by analyzing the sparseness of input data and selecting the fitting wavelets by orthogonalization method according to the output data. Then it is applied to solve the direct displacement of a general six-degree-of-freedom parallel mechanism as a numerical example. For comparison purposes, a BP neural network is also used for this problem. Simulation results show that the wavelet network performs better than BP neural network. In addition, the wavelet network learns much faster than BP network.
Towards two-dimensional search engines
Ermann, Leonardo; Chepelianskii, Alexei D.; Shepelyansky, Dima L.
2011-01-01
We study the statistical properties of various directed networks using ranking of their nodes based on the dominant vectors of the Google matrix known as PageRank and CheiRank. On average PageRank orders nodes proportionally to a number of ingoing links, while CheiRank orders nodes proportionally to a number of outgoing links. In this way the ranking of nodes becomes two-dimensional that paves the way for development of two-dimensional search engines of new type. Statistical properties of inf...
Toward two-dimensional search engines
Ermann, L.; Chepelianskii, A. D.; Shepelyansky, D. L.
2012-07-01
We study the statistical properties of various directed networks using ranking of their nodes based on the dominant vectors of the Google matrix known as PageRank and CheiRank. On average PageRank orders nodes proportionally to a number of ingoing links, while CheiRank orders nodes proportionally to a number of outgoing links. In this way, the ranking of nodes becomes two dimensional which paves the way for the development of two-dimensional search engines of a new type. Statistical properties of information flow on the PageRank-CheiRank plane are analyzed for networks of British, French and Italian universities, Wikipedia, Linux Kernel, gene regulation and other networks. A special emphasis is done for British universities networks using the large database publicly available in the UK. Methods of spam links control are also analyzed.
Parallel CFD design on network-based computer
Cheung, Samson
1995-01-01
Combining multiple engineering workstations into a network-based heterogeneous parallel computer allows application of aerodynamic optimization with advanced computational fluid dynamics codes, which can be computationally expensive on mainframe supercomputers. This paper introduces a nonlinear quasi-Newton optimizer designed for this network-based heterogeneous parallel computing environment utilizing a software called Parallel Virtual Machine. This paper will introduce the methodology behind coupling a Parabolized Navier-Stokes flow solver to the nonlinear optimizer. This parallel optimization package is applied to reduce the wave drag of a body of revolution and a wing/body configuration with results of 5% to 6% drag reduction.
Towards two-dimensional search engines
Ermann, Leonardo; Shepelyansky, Dima L
2011-01-01
We study the statistical properties of various directed networks using ranking of their nodes based on the dominant vectors of the Google matrix known as PageRank and CheiRank. On average PageRank orders nodes proportionally to a number of ingoing links, while CheiRank orders nodes proportionally to a number of outgoing links. In this way the ranking of nodes becomes two-dimensional that paves the way for development of two-dimensional search engines of new type. Information flow properties on PageRank-CheiRank plane are analyzed for networks of British, French and Italian Universities, Wikipedia, Linux Kernel, gene regulation and other networks. Methods of spam links control are also analyzed.
Liu, Shan-Shan; Yuan, Shuai; Lu, Hai-Feng; Xu, Meng-Zhen; Sun, Di
2013-06-01
The cation-templated self-assembly of 1,4-bis(2-methyl-1H-imidazol-1-yl)butane (bmimb) with CuSCN gives rise to a novel two-dimensional network, namely catena-poly[2,2'-dimethyl-1,1'-(butane-1,4-diyl)bis(1H-imidazol-3-ium) [tetra-μ2-thiocyanato-κ(4)S:S;κ(4)S:N-dicopper(I)
NEURAL NETWORK TRAINING WITH PARALLEL PARTICLE SWARM OPTIMIZER
Institute of Scientific and Technical Information of China (English)
Qin Zheng; Liu Yu; Wang Yu
2006-01-01
Objective To reduce the execution time of neural network training. Methods Parallel particle swarm optimization algorithm based on master-slave model is proposed to train radial basis function neural networks, which is implemented on a cluster using MPI libraries for inter-process communication. Results High speed-up factor is achieved and execution time is reduced greatly. On the other hand, the resulting neural network has good classification accuracy not only on training sets but also on test sets. Conclusion Since the fitness evaluation is intensive, parallel particle swarm optimization shows great advantages to speed up neural network training.
Gourgue, O.; Baeyens, W.; Chen, M. S.; de Brauwere, A.; de Brye, B.; Deleersnijder, E.; Elskens, M.; Legat, V.
2013-12-01
This paper presents the sediment module designed for the two-dimensional depth-averaged and one-dimensional section-averaged components of the finite-element model SLIM (Second-generation Louvain-la-Neuve Ice-ocean Model) in the framework of its application to the tidal part of the Scheldt Basin. This sediment transport module focuses on fine-grained, cohesive sediments. It is a necessary tool to undertake environmental biogeochemical studies, in which fine sediment dynamics play a crucial role.
A Network Model for Parallel Line Balancing Problem
Directory of Open Access Journals (Sweden)
Recep Benzer
2007-01-01
Full Text Available Gökçen et al. (2006 have proposed several procedures and a mathematical model on single-model (product assembly line balancing (ALB problem with parallel lines. In parallel ALB problem, the goal is to balance more than one assembly line together. In this paper, a network model for parallel ALB problem has been proposed and illustrated on a numerical example. This model is a new approach for parallel ALB and it provides a different point of view for interested researchers.
Liu, Ting; Pan, Yu-Peng; Wang, Suna; Dou, Jian-Min
2013-04-01
Reactions of 2-(hydroxymethyl)pyridine (Hhmp) with PbCl2 and Pb(NO3)2 at room temperature led to the formation of two novel compounds, namely tetrakis[μ3-(pyridin-2-yl)methanolato]-tetrahedro-tetrakis[chloridolead(II)], [Pb4(C6H6NO)4Cl4], (I), and poly[(μ2-nitrato)[μ2-(pyridin-2-yl)methanolato]lead(II)], [Pb(C6H6NO)(NO3)]n, (II). Compound (I) exhibits a tetranuclear Pb4O4 cubane structure, which is connected through π-π stacking interactions between the pyridine groups of the (pyridin-2-yl)methanolate (hmp(-)) ligands and through C-H···Cl interactions to form an interesting threefold diamondoid network. Compound (II) possesses two-dimensional (4,4)-sql topology based on a Pb2O2 unit, which is further extended into a three-dimensional supramolecular network through π-π stacking interactions between adjacent pyridine rings and through C-H···O interactions between the pyridine C atoms of the hmp(-) ligands and the nitrate anions.
Two-dimensional liquid chromatography
DEFF Research Database (Denmark)
Græsbøll, Rune
of this thesis is on online comprehensive two-dimensional liquid chromatography (online LC×LC) with reverse phase in both dimensions (online RP×RP). Since online RP×RP has not been attempted before within this research group, a significant part of this thesis consists of knowledge and experience gained...
Associative Networks on a Massively Parallel Computer.
1985-10-01
19 4.12 The Language Definition ....... ............... 21 4.1.3 Specialized Procedures and Functions... definition we give of associative networks eliminates words and meanings altogether in favor of numbers. It is assumed to be a function of a higher... lgbt (as a group of numbers, in this case), but this only leads to sensible queries when a statistical function is applied: "What is the largest salary
Gui, Daxiang; Zheng, Tao; Xie, Jian; Cai, Yawen; Wang, Yaxing; Chen, Lanhua; Diwu, Juan; Chai, Zhifang; Wang, Shuao
2016-12-19
A highly stable layered zirconium phosphate, (NH4)2[ZrF2(HPO4)2] (ZrP-1), was synthesized by an ionothermal method and contains an extremely dense two-dimensional hydrogen-bond network that is thermally stable up to 573 K, leading to combined ultrahigh water-assisted proton conductivities of 1.45 × 10(-2) S cm(-1) at 363 K/95% relative humidity and sustainable anhydrous proton conductivity of 1.1 × 10(-5) S cm(-1) at 503 K.
Hadoop neural network for parallel and distributed feature selection.
Hodge, Victoria J; O'Keefe, Simon; Austin, Jim
2016-06-01
In this paper, we introduce a theoretical basis for a Hadoop-based neural network for parallel and distributed feature selection in Big Data sets. It is underpinned by an associative memory (binary) neural network which is highly amenable to parallel and distributed processing and fits with the Hadoop paradigm. There are many feature selectors described in the literature which all have various strengths and weaknesses. We present the implementation details of five feature selection algorithms constructed using our artificial neural network framework embedded in Hadoop YARN. Hadoop allows parallel and distributed processing. Each feature selector can be divided into subtasks and the subtasks can then be processed in parallel. Multiple feature selectors can also be processed simultaneously (in parallel) allowing multiple feature selectors to be compared. We identify commonalities among the five features selectors. All can be processed in the framework using a single representation and the overall processing can also be greatly reduced by only processing the common aspects of the feature selectors once and propagating these aspects across all five feature selectors as necessary. This allows the best feature selector and the actual features to select to be identified for large and high dimensional data sets through exploiting the efficiency and flexibility of embedding the binary associative-memory neural network in Hadoop. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
Parallel optical logic operations on reversible networks
Shamir, Joseph
2013-03-01
A generic optical network architecture is proposed for the implementation of programmable logic operations. Based on reversible optical gate elements the processor is highly energy efficient and intrinsically fast. In this architecture the whole logic operation is executed by light propagating through the system with no energy dissipation. Energy must be spent only at the input interface and at discrete locations where the logic operation results are to be detected. As a consequence, the theoretical lower limit for energy dissipation in logic operations must be reconsidered. The strength of this approach is demonstrated by examples showing the implementation of various lossless logic operations, including Half Adder and Full Adder.
Two dimensional unstable scar statistics.
Energy Technology Data Exchange (ETDEWEB)
Warne, Larry Kevin; Jorgenson, Roy Eberhardt; Kotulski, Joseph Daniel; Lee, Kelvin S. H. (ITT Industries/AES Los Angeles, CA)
2006-12-01
This report examines the localization of time harmonic high frequency modal fields in two dimensional cavities along periodic paths between opposing sides of the cavity. The cases where these orbits lead to unstable localized modes are known as scars. This paper examines the enhancements for these unstable orbits when the opposing mirrors are both convex and concave. In the latter case the construction includes the treatment of interior foci.
Juday, Richard D.
1992-01-01
Modified vernier scale gives accurate two-dimensional coordinates from maps, drawings, or cathode-ray-tube displays. Movable circular overlay rests on fixed rectangular-grid overlay. Pitch of circles nine-tenths that of grid and, for greatest accuracy, radii of circles large compared with pitch of grid. Scale enables user to interpolate between finest divisions of regularly spaced rule simply by observing which mark on auxiliary vernier rule aligns with mark on primary rule.
Using the multistage cube network topology in parallel supercomputers
Energy Technology Data Exchange (ETDEWEB)
Siegel, H.J.; Nation, W.G. (Purdue Univ., Lafayette, IN (USA). School of Electrical Engineering); Kruskal, C.P. (Maryland Univ., College Park, MD (USA). Dept. of Computer Science); Napolitano, L.M. Jr. (Sandia National Labs., Livermore, CA (USA))
1989-12-01
A variety of approaches to designing the interconnection network to support communications among the processors and memories of supercomputers employing large-scale parallel processing have been proposed and/or implemented. These approaches are often based on the multistage cube topology. This topology is the subject of much ongoing research and study because of the ways in which the multistage cube can be used. The attributes of the topology that make it useful are described. These include O(N log{sub 2} N) cost for an N input/output network, decentralized control, a variety of implementation options, good data permuting capability to support single instruction stream/multiple data stream (SIMD) parallelism, good throughput to support multiple instruction stream/multiple data stream (MIMD) parallelism, and ability to be partitioned into independent subnetworks to support reconfigurable systems. Examples of existing systems that use multistage cube networks are overviewed. The multistage cube topology can be converted into a single-stage network by associating with each switch in the network a processor (and a memory). Properties of systems that use the multistage cube network in this way are also examined.
Niu, Jingyang; Zhao, Junwei; Wang, Jingping; Ma, Pengtao
2004-08-01
A novel two-dimensional infinite network organic-inorganic hybrid neodymium(III)-centered compound of formula (dmaH) 2[Nd(dmf) 4(H 2O)][α-BW 12O 40]·H 2O ( 1) [dma=dimethylamine and dmf= N, N-dimethylformamide] is obtained by the conventional self-assembly reaction of neodymium oxide, N, N-dimethylformamide and borotungstic acid (α-H 5BW 12O 40·30H 2O) in the mixed solvent of acetonitrile and water, and characterized by IR, UV-visible spectra and X-ray single crystal diffraction. Structural analysis indicates that every [α-BW 12O 40] 5- polyanion interconnects with three adjacent [Nd(dmf) 4(H 2O)] 3+ subunits by means of W-O-Nd bridges, meanwhile, every [Nd(dmf) 4(H 2O)] 3+ building block is surrounded by three neighboring [α-BW 12O 40] 5- polyanions by making use of which an unprecedented two-dimensional extended network structure can be constructed. Interestingly, this structure pattern may act as useful model for the design and assembly of functional molecule-based compounds, especially in the field of molecular sieve materials.
PARNEM-A PARALLEL DISCRETE EVENT NETWORK EMULATION SYSTEM
Institute of Scientific and Technical Information of China (English)
Li Yue; Qian Depei; He Ying
2006-01-01
Objective Network emulation system constructs a virtual network environment which has the characteristics of controllable and repeatable network conditions. This makes it possible to predict the availability and performance of new protocols and algorithms before deploying to Internet. Methods PARNEM, a parallel discrete event network emulation system described in this paper has the following characteristics: ① BREEN - a BSP based real-time event scheduling engine; ② application transparent flexible interactive mechanism; ③ legacy network model reuse. Conclusion PARNEM allows detailed and accurate study of application behavior. Comprehensive case studies covering bottleneck bandwidth measurement and distributed cooperative web caching system demonstrate that network emulation technology opens a wide range of new opportunities for examining the behavior of applications.
Efficient Heuristics for Simulating Population Overflow in Parallel Networks
Zaburnenko, T.S.; Nicola, V.F.
2006-01-01
In this paper we propose a state-dependent importance sampling heuristic to estimate the probability of population overflow in networks of parallel queues. This heuristic approximates the “optimal��? state-dependent change of measure without the need for costly optimization involved in other
An Image Database on a Parallel Processing Network.
Philip, G.; And Others
1991-01-01
Describes the design and development of an image database for photographs in the Ulster Museum (Northern Ireland) that used parallelism from a transputer network. Topics addressed include image processing techniques; documentation needed for the photographs, including indexing, classifying, and cataloging; problems; hardware and software aspects;…
Energy Technology Data Exchange (ETDEWEB)
Yan, Dongming [School of Civil and Architectural Engineering, Zhejiang University, Hangzhou 310058 (China); Hou, Peipei; Liu, Chang [State Key Laboratory of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou 310027 (China); Chai, Wenxiang [College of Materials Science and Engineering, China Jiliang University, Hangzhou 310018 (China); Zheng, Xuerong [State Key Laboratory of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou 310027 (China); Zhang, Luodong [School of Civil and Architectural Engineering, Zhejiang University, Hangzhou 310058 (China); Zhi, Mingjia; Zhou, Chunmei [State Key Laboratory of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou 310027 (China); Liu, Yi, E-mail: liuyimse@zju.edu.cn [State Key Laboratory of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou 310027 (China)
2016-09-15
Two new quaternary thioarsenates(III) NaAg{sub 2}AsS{sub 3}·H{sub 2}O (1) and KAg{sub 2}AsS{sub 3} (2) with high yields have been successfully prepared through a facile surfactant-thermal method. It is interesting that 2 can only be obtained with the aid of ethanediamine (en), which indicates that weak basicity of solvent is beneficial to the growth of 2 compared with 1. Both 1 and 2 feature the similar two-dimensional (2D) layer structures. However, the distortion of the primary honeycomb-like nets in 2 is more severe than that of 1, which demonstrates that Na{sup +} and K{sup +} cations have different structure directing effects on these two thioarsenates(III). Both experimental and theoretical studies confirm 1 and 2 are semiconductors with band gaps in the visible region. Our success in preparing these two quaternary thioarsenates(III) proves that surfactant-thermal technique is a powerful yet facile synthetic method to explore new complex chalcogenides. - Graphical abstract: Two new quaternary thioarsenates(III) NaAg{sub 2}AsS{sub 3}·H{sub 2}O (1) and KAg{sub 2}AsS{sub 3} (2) with high yields have been successfully prepared through a facile surfactant-thermal method. X-ray single crystal diffraction analyses demonstrate that Na{sup +} and K{sup +} cations have different structure directing effects on these two thioarsenates(III). Both experimental and theoretical studies confirm 1 and 2 are semiconductors with band gaps in the visible region. Display Omitted - Highlights: • NaAg{sub 2}AsS{sub 3}⋅H{sub 2}O (1) and KAg{sub 2}AsS{sub 3} (2) were prepared through surfactant-thermal method. • Crystal structures show Na{sup ±} and K{sup ±} have different structure directing effects. • The weak basicity of solvent is benefit to the growth of 2 compared with 1. • Experimental and theoretical studies confirm 1 and 2 are semiconductors.
Two-dimensional liquid chromatography
DEFF Research Database (Denmark)
Græsbøll, Rune
Two-dimensional liquid chromatography has received increasing interest due to the rise in demand for analysis of complex chemical mixtures. Separation of complex mixtures is hard to achieve as a simple consequence of the sheer number of analytes, as these samples might contain hundreds or even...... dimensions. As a consequence of the conclusions made within this thesis, the research group has, for the time being, decided against further development of online LC×LC systems, since it was not deemed ideal for the intended application, the analysis of the polar fraction of oil. Trap-and...
A Parallelism-Based Approach to Network Anonymization
Margasinski, Igor
2009-01-01
Considering topologies of anonymous networks we used to organizing anonymous communication into hard to trace paths hiding its origin or destination. In anonymity the company is crucial, however the serial transportation imposes a costly tradeoff between a level of privacy and a speed of communication. This paper introduces a framework of a novel architecture for anonymous networks that hides initiators of communications by parallelization of anonymous links. The new approach, which is based on the grounds of the anonymous P2P network called P2Priv, does not require content forwarding via a chain of proxy nodes to assure high degree of anonymity. Contrary to P2Priv, the new architecture can be suited to anonymization of various network communications, including anonymous access to distributed as well as client-server services. In particular, it can be considered as an anonymization platform for these network applications where both privacy and low delays are required.
Two-dimensional capillary origami
Energy Technology Data Exchange (ETDEWEB)
Brubaker, N.D., E-mail: nbrubaker@math.arizona.edu; Lega, J., E-mail: lega@math.arizona.edu
2016-01-08
We describe a global approach to the problem of capillary origami that captures all unfolded equilibrium configurations in the two-dimensional setting where the drop is not required to fully wet the flexible plate. We provide bifurcation diagrams showing the level of encapsulation of each equilibrium configuration as a function of the volume of liquid that it contains, as well as plots representing the energy of each equilibrium branch. These diagrams indicate at what volume level the liquid drop ceases to be attached to the endpoints of the plate, which depends on the value of the contact angle. As in the case of pinned contact points, three different parameter regimes are identified, one of which predicts instantaneous encapsulation for small initial volumes of liquid. - Highlights: • Full solution set of the two-dimensional capillary origami problem. • Fluid does not necessarily wet the entire plate. • Global energy approach provides exact differential equations satisfied by minimizers. • Bifurcation diagrams highlight three different regimes. • Conditions for spontaneous encapsulation are identified.
MASSIVE PARALLELISM WITH GPUS FOR CENTRALITY RANKING IN COMPLEX NETWORKS
Directory of Open Access Journals (Sweden)
Frederico L. Cabral
2014-10-01
Full Text Available Many problems in Computer Science can be modelled using graphs. Evaluating node centrality in complex networks, which can be considered equivalent to undirected graphs, provides an useful metric of the relative importance of each node inside the evaluated network. The knowledge on which the most central nodes are, has various applications, such as improving information spreading in diffusion networks. In this case, most central nodes can be considered to have higher influence rates over other nodes in the network. The main purpose in this work is developing a GPU based and massively parallel application so as to evaluate the node centrality in complex networks using the Nvidia CUDA programming model. The main contribution of this work is the strategies for the development of an algorithm to evaluate the node centrality in complex networks using Nvidia CUDA parallel programming model. We show that the strategies improves algorithm´s speed-up in two orders of magnitude on one NVIDIA Tesla k20 GPU cluster node, when compared to the hybrid OpenMP/MPI algorithm version, running in the same cluster, with 4 nodes 2 Intel(R Xeon(R CPU E5-2660 each, for radius zero.
Parallel routing in Mobile Ad-Hoc Networks
Day, Khaled; Arafeh, Bassel; Alzeidi, Nasser; 10.5121/ijcnc.2011.3506
2011-01-01
This paper proposes and evaluates a new position-based Parallel Routing Protocol (PRP) for simultaneously routing multiple data packets over disjoint paths in a mobile ad-hoc network (MANET) for higher reliability and reduced communication delays. PRP views the geographical region where the MANET is located as a virtual 2-dimensional grid of cells. Cell-disjoint (parallel) paths between grid cells are constructed and used for building pre-computed routing tables. A single gateway node in each grid cell handles routing through that grid cell reducing routing overheads. Each node maintains updated information about its own location in the virtual grid using GPS. Nodes also keep track of the location of other nodes using a new proposed cell-based broadcasting algorithm. Nodes exchange energy level information with neighbors allowing energy-aware selection of the gateway nodes. Performance evaluation results have been derived showing the attractiveness of the proposed parallel routing protocol from different resp...
Two-dimensional capillary origami
Brubaker, N. D.; Lega, J.
2016-01-01
We describe a global approach to the problem of capillary origami that captures all unfolded equilibrium configurations in the two-dimensional setting where the drop is not required to fully wet the flexible plate. We provide bifurcation diagrams showing the level of encapsulation of each equilibrium configuration as a function of the volume of liquid that it contains, as well as plots representing the energy of each equilibrium branch. These diagrams indicate at what volume level the liquid drop ceases to be attached to the endpoints of the plate, which depends on the value of the contact angle. As in the case of pinned contact points, three different parameter regimes are identified, one of which predicts instantaneous encapsulation for small initial volumes of liquid.
Two-dimensional cubic convolution.
Reichenbach, Stephen E; Geng, Frank
2003-01-01
The paper develops two-dimensional (2D), nonseparable, piecewise cubic convolution (PCC) for image interpolation. Traditionally, PCC has been implemented based on a one-dimensional (1D) derivation with a separable generalization to two dimensions. However, typical scenes and imaging systems are not separable, so the traditional approach is suboptimal. We develop a closed-form derivation for a two-parameter, 2D PCC kernel with support [-2,2] x [-2,2] that is constrained for continuity, smoothness, symmetry, and flat-field response. Our analyses, using several image models, including Markov random fields, demonstrate that the 2D PCC yields small improvements in interpolation fidelity over the traditional, separable approach. The constraints on the derivation can be relaxed to provide greater flexibility and performance.
Directory of Open Access Journals (Sweden)
Gyungse Park
2008-07-01
Full Text Available In the title compound, [Cd3(C16H10O43(C3H7NO2]n or [Cd3(SDA3(DMF2]n (H2SDA is trans-stilbene-4,4Ã¢Â€Â²-dicarboxylic acid and DMF is dimethylformamide, the linear dicarboxylate ligand forms a two-dimensionally layered metalÃ¢Â€Â“organic network with the relatively uncommon 36 topology. The structure reveals trinuclear secondary building units and has an octahedral geometry at a central metal ion (occupying a overline{3} symmetry site and tetrahedral geometries at two surrounding symmetrically equivalent metal ions lying on a threefold axis. The six-connected planar trinuclear CdII centers, Cd3(O2CR6, play a role as potential nodes in generation of the relatively uncommon 36 topology. The coordinated DMF unit is disordered around the threefold axis.
King, Philippa; Clérac, Rodolphe; Anson, Christopher E; Coulon, Claude; Powell, Annie K
2003-06-01
A new Cu(II) complex, [Cu(3)(dcp)(2)(H(2)O)(4)](n), with the ligand 3,5-pyrazoledicarboxylic acid monohydrate (H(3)dcp) has been prepared by hydrothermal synthesis, and it crystallizes in the monoclinic space group P2(1)/c with a = 11.633(2) A, b = 9.6005(14) A, c = 6.9230(17) A, beta = 106.01(2) degrees, and Z = 2. In the solid state structure of [Cu(3)(dcp)(2)(H(2)O)(4)](n), trinuclear [Cu(3)(dcp)(2)(H(2)O)(4)] repeating units in which two dcp(3-) ligands chelate the three Cu(II) ions with the central Cu(II) ion, Cu(1) (on an inversion center), link to form infinite 2D sheets via syn-anti equatorial-equatorial carboxylate bridges between Cu(2) atoms in adjacent trimers. These layers are further linked by syn-anti axial-equatorial carboxylate bridging between Cu(1) atoms in adjacent sheets resulting in the formation of a crystallographic 3D network. A detailed analysis of the magnetic properties of [Cu(3)(dcp)(2)(H(2)O)(4)](n) reveals that the dcp(3-) ligand acts to link Cu(II) centers in three different ways with coupling constants orders of magnitude apart in value. In the high temperature region above 50 K, the dominant interaction is strongly antiferromagnetic (J/k(B) = -32 K) within the trimer units mediated by the pyrazolate bridges. Below 20 K, the trimer motif can be modeled as an S = 1/2 unit. These units are coupled to their neighbors by a ferromagnetic interaction mediated by the syn-anti equatorial-equatorial carboxylate bridge. This interaction has been estimated at J(2D)/k(B) = +2.8 K on the basis of a 2D square lattice Heisenberg model. Finally, below 3.2 K a weak antiferromagnetic coupling (J(3D)/k(B) = -0.1 K) which is mediated by the syn-anti axial-equatorial carboxylate bridges between the 2D layers becomes relevant to describe the magnetic (T, H) phase diagram of this material.
Wang, Xijun; Zhang, Aihua; Sun, Hui; Wu, Gelin; Sun, Wenjun; Yan, Guangli
2012-10-21
Recent advances in proteomic technologies have enabled us to create detailed protein-protein interaction maps in diseases. As the size of the interaction dataset increases, powerful computational methods are required in order to effectively interpret network models from large scale interactome data. In this study, we carried out comparative proteomics to construct and identify the proteins networks associated with hepatic injury (HI) which are largely unknown, as a case study. All proteins expressed were separated and identified by two-dimensional gel electrophoresis (2-DE) and matrix-assisted laser desorption/ionization time-of-flight-time-of-flight mass spectrometry (MALDI-TOF/TOF MS). Protein-interacting networks and pathways were mapped using STRING analysis program. We have performed for the first time a comprehensive profiling of changes in protein expression of HI rats, to uncover the networks altered by treated with CCl(4). Identification of fifteen spots (seven over-expressed and eight under-expressed) were established by MALDI-TOF/TOF MS. These proteins were subjected to functional pathway analysis using STRING software for better understanding of the biological context of the identified proteins. It suggested that modulation of multiple vital physiological pathways including DNA repair process, cell apoptosis, oxidation reduction, signal transduction, metabolic process, intracellular signaling cascade, regulation of biological processes, cell communication, regulation of cellular process, and molecular transport. In summary, the present study provides the first protein-interacting network maps and novel insights into the biological responses and potential pathways of HI. The generation of protein interaction networks clearly enhances the interpretation of proteomic data, particularly in respect of understanding molecular mechanisms of panel protein biomarkers.
Reconfigurable and Parallelized Network Coding Decoder for VANETs
Directory of Open Access Journals (Sweden)
Sunwoo Kim
2012-01-01
Full Text Available Network coding is a promising technique for data communications in wired and wireless networks. However, it places an additional computing overhead on the receiving node in exchange for the improved bandwidth. This paper proposes an FPGA-based reconfigurable and parallelized network coding decoder for embedded systems especially for vehicular ad hoc networks. In our design, rapid decoding process can be achieved by exploiting parallelism in the coefficient vector operations. The proposed decoder is implemented by using a modern Xilinx Virtex-5 device and its performance is evaluated considering the performance of the software decoding on various embedded processors. The performance on four different sizes of the coefficient matrix is measured and the decoding throughput of 18.3 Mbps for the size 16 × 16 and 6.5 Mbps for 128 × 128 has been achieved at the operating frequency of 64.5 MHz. Compared to the recent TEGRA 250 processor, the result obtained with128 × 128 coefficient matrix reaches up to 5.06 in terms of speedup.
Classifying Two-dimensional Hyporeductive Triple Algebras
Issa, A Nourou
2010-01-01
Two-dimensional real hyporeductive triple algebras (h.t.a.) are investigated. A classification of such algebras is presented. As a consequence, a classification of two-dimensional real Lie triple algebras (i.e. generalized Lie triple systems) and two-dimensional real Bol algebras is given.
Locality-Driven Parallel Static Analysis for Power Delivery Networks
Zeng, Zhiyu
2011-06-01
Large VLSI on-chip Power Delivery Networks (PDNs) are challenging to analyze due to the sheer network complexity. In this article, a novel parallel partitioning-based PDN analysis approach is presented. We use the boundary circuit responses of each partition to divide the full grid simulation problem into a set of independent subgrid simulation problems. Instead of solving exact boundary circuit responses, a more efficient scheme is proposed to provide near-exact approximation to the boundary circuit responses by exploiting the spatial locality of the flip-chip-type power grids. This scheme is also used in a block-based iterative error reduction process to achieve fast convergence. Detailed computational cost analysis and performance modeling is carried out to determine the optimal (or near-optimal) number of partitions for parallel implementation. Through the analysis of several large power grids, the proposed approach is shown to have excellent parallel efficiency, fast convergence, and favorable scalability. Our approach can solve a 16-million-node power grid in 18 seconds on an IBM p5-575 processing node with 16 Power5+ processors, which is 18.8X faster than a state-of-the-art direct solver. © 2011 ACM.
Two-dimensional function photonic crystals
Wu, Xiang-Yao; Liu, Xiao-Jing; Liang, Yu
2016-01-01
In this paper, we have firstly proposed two-dimensional function photonic crystals, which the dielectric constants of medium columns are the functions of space coordinates $\\vec{r}$, it is different from the two-dimensional conventional photonic crystals constituting by the medium columns of dielectric constants are constants. We find the band gaps of two-dimensional function photonic crystals are different from the two-dimensional conventional photonic crystals, and when the functions form of dielectric constants are different, the band gaps structure should be changed, which can be designed into the appropriate band gaps structures by the two-dimensional function photonic crystals.
CX: A Scalable, Robust Network for Parallel Computing
Directory of Open Access Journals (Sweden)
Peter Cappello
2002-01-01
Full Text Available CX, a network-based computational exchange, is presented. The system's design integrates variations of ideas from other researchers, such as work stealing, non-blocking tasks, eager scheduling, and space-based coordination. The object-oriented API is simple, compact, and cleanly separates application logic from the logic that supports interprocess communication and fault tolerance. Computations, of course, run to completion in the presence of computational hosts that join and leave the ongoing computation. Such hosts, or producers, use task caching and prefetching to overlap computation with interprocessor communication. To break a potential task server bottleneck, a network of task servers is presented. Even though task servers are envisioned as reliable, the self-organizing, scalable network of n- servers, described as a sibling-connected height-balanced fat tree, tolerates a sequence of n-1 server failures. Tasks are distributed throughout the server network via a simple "diffusion" process. CX is intended as a test bed for research on automated silent auctions, reputation services, authentication services, and bonding services. CX also provides a test bed for algorithm research into network-based parallel computation.
Dopamine: A parallel pathway for modulation of locomotor networks
Directory of Open Access Journals (Sweden)
Simon eSharples
2014-06-01
Full Text Available The spinal cord contains networks of neurons that can produce locomotor patterns. To readily respond to environmental conditions, these networks must be flexible yet at the same time robust. Neuromodulators play a key role in contributing to network flexibility in a variety of invertebrate and vertebrate networks. For example, neuromodulators contribute to altering intrinsic properties and synaptic weights that, in extreme cases, can lead to neurons switching between networks. Here we focus on the role of dopamine in the control of stepping networks in the spinal cord. We first review the role of dopamine in modulating rhythmic activity in the stomatogastric ganglion and the leech, since work from these preparations provides a foundation to understand its role in vertebrate systems. We then move to a discussion of dopamine’s role in modulation of swimming in aquatic species such as the larval xenopus, lamprey and zebrafish. The control of terrestrial walking in vertebrates by dopamine is less studied and we review current evidence in mammals with a focus on rodent species. We discuss data suggesting that the source of dopamine within the spinal cord is mainly from the A11 area of the diencephalon, and then turn to a discussion of dopamine’s role in modulating walking patterns from both in vivo and in vitro preparations. Similar to the descending serotonergic system, the dopaminergic system may serve as a potential target to promote recovery of locomotor function following spinal cord injury; evidence suggests that dopaminergic agonists can promote recovery of function following spinal cord injury (SCI. We discuss pharmacogenetic and optogenetic approaches that could be deployed in SCI and their potential tractability. Throughout the review we draw parallels with both noradrenergic and serotonergic modulatory effects on spinal cord networks. In all likelihood, a complementary monoaminergic enhancement strategy should be deployed following
Identifying failure in a tree network of a parallel computer
Archer, Charles J.; Pinnow, Kurt W.; Wallenfelt, Brian P.
2010-08-24
Methods, parallel computers, and products are provided for identifying failure in a tree network of a parallel computer. The parallel computer includes one or more processing sets including an I/O node and a plurality of compute nodes. For each processing set embodiments include selecting a set of test compute nodes, the test compute nodes being a subset of the compute nodes of the processing set; measuring the performance of the I/O node of the processing set; measuring the performance of the selected set of test compute nodes; calculating a current test value in dependence upon the measured performance of the I/O node of the processing set, the measured performance of the set of test compute nodes, and a predetermined value for I/O node performance; and comparing the current test value with a predetermined tree performance threshold. If the current test value is below the predetermined tree performance threshold, embodiments include selecting another set of test compute nodes. If the current test value is not below the predetermined tree performance threshold, embodiments include selecting from the test compute nodes one or more potential problem nodes and testing individually potential problem nodes and links to potential problem nodes.
Efficient Parallel Statistical Model Checking of Biochemical Networks
Directory of Open Access Journals (Sweden)
Paolo Ballarini
2009-12-01
Full Text Available We consider the problem of verifying stochastic models of biochemical networks against behavioral properties expressed in temporal logic terms. Exact probabilistic verification approaches such as, for example, CSL/PCTL model checking, are undermined by a huge computational demand which rule them out for most real case studies. Less demanding approaches, such as statistical model checking, estimate the likelihood that a property is satisfied by sampling executions out of the stochastic model. We propose a methodology for efficiently estimating the likelihood that a LTL property P holds of a stochastic model of a biochemical network. As with other statistical verification techniques, the methodology we propose uses a stochastic simulation algorithm for generating execution samples, however there are three key aspects that improve the efficiency: first, the sample generation is driven by on-the-fly verification of P which results in optimal overall simulation time. Second, the confidence interval estimation for the probability of P to hold is based on an efficient variant of the Wilson method which ensures a faster convergence. Third, the whole methodology is designed according to a parallel fashion and a prototype software tool has been implemented that performs the sampling/verification process in parallel over an HPC architecture.
Hadamard States and Two-dimensional Gravity
Salehi, H
2001-01-01
We have used a two-dimensional analog of the Hadamard state-condition to study the local constraints on the two-point function of a linear quantum field conformally coupled to a two-dimensional gravitational background. We develop a dynamical model in which the determination of the state of the quantum field is essentially related to the determination of a conformal frame. A particular conformal frame is then introduced in which a two-dimensional gravitational equation is established.
Topological defects in two-dimensional crystals
Chen, Yong; Qi, Wei-Kai
2008-01-01
By using topological current theory, we study the inner topological structure of the topological defects in two-dimensional (2D) crystal. We find that there are two elementary point defects topological current in two-dimensional crystal, one for dislocations and the other for disclinations. The topological quantization and evolution of topological defects in two-dimensional crystals are discussed. Finally, We compare our theory with Brownian-dynamics simulations in 2D Yukawa systems.
Energy Technology Data Exchange (ETDEWEB)
Yoon, Jeong Hee [Department of Radiology, Seoul National University Hospital, Seoul 03080 (Korea, Republic of); Department of Radiology, Seoul National University College of Medicine, Seoul 03087 (Korea, Republic of); Lee, Jeong Min [Department of Radiology, Seoul National University Hospital, Seoul 03080 (Korea, Republic of); Department of Radiology, Seoul National University College of Medicine, Seoul 03087 (Korea, Republic of); Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul 03087 (Korea, Republic of); Yu, Mi Hye [Department of Radiology, Konkuk University Medical Center, Seoul 05030 (Korea, Republic of); Kim, Eun Ju [Philips Healthcare Korea, Seoul 04342 (Korea, Republic of); Han, Joon Koo [Department of Radiology, Seoul National University Hospital, Seoul 03080 (Korea, Republic of); Department of Radiology, Seoul National University College of Medicine, Seoul 03087 (Korea, Republic of); Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul 03087 (Korea, Republic of)
2016-11-01
To determine whether triple arterial phase acquisition via a combination of Contrast Enhanced Time Robust Angiography, keyhole, temporal viewsharing and parallel imaging can improve arterial phase acquisition with higher spatial resolution than single arterial phase gadoxetic-acid enhanced magnetic resonance imaging (MRI). Informed consent was waived for this retrospective study by our Institutional Review Board. In 752 consecutive patients who underwent gadoxetic acid-enhanced liver MRI, either single (n = 587) or triple (n = 165) arterial phases was obtained in a single breath-hold under MR fluoroscopy guidance. Arterial phase timing was assessed, and the degree of motion was rated on a four-point scale. The percentage of patients achieving the late arterial phase without significant motion was compared between the two methods using the χ{sup 2} test. The late arterial phase was captured at least once in 96.4% (159/165) of the triple arterial phase group and in 84.2% (494/587) of the single arterial phase group (p < 0.001). Significant motion artifacts (score ≤ 2) were observed in 13.3% (22/165), 1.2% (2/165), 4.8% (8/165) on 1st, 2nd, and 3rd scans of triple arterial phase acquisitions and 6.0% (35/587) of single phase acquisitions. Thus, the late arterial phase without significant motion artifacts was captured in 96.4% (159/165) of the triple arterial phase group and in 79.9% (469/587) of the single arterial phase group (p < 0.001). Triple arterial phase imaging may reliably provide adequate arterial phase imaging for gadoxetic acid-enhanced liver MRI.
Energy Technology Data Exchange (ETDEWEB)
Yoon, Jeong Hee; Lee, Jeong Min; Han, Joon Koo [Dept. of Radiology, Seoul National University Hospital, Seoul (Korea, Republic of); Yu, Mi Hye [Dept. of Radiology, Konkuk University Medical Center, Seoul (Korea, Republic of); Kim, Eun Ju [Philips Healthcare Korea, Seoul (Korea, Republic of)
2016-07-15
To determine whether triple arterial phase acquisition via a combination of Contrast Enhanced Time Robust Angiography, keyhole, temporal viewsharing and parallel imaging can improve arterial phase acquisition with higher spatial resolution than single arterial phase gadoxetic-acid enhanced magnetic resonance imaging (MRI). Informed consent was waived for this retrospective study by our Institutional Review Board. In 752 consecutive patients who underwent gadoxetic acid-enhanced liver MRI, either single (n = 587) or triple (n = 165) arterial phases was obtained in a single breath-hold under MR fluoroscopy guidance. Arterial phase timing was assessed, and the degree of motion was rated on a four-point scale. The percentage of patients achieving the late arterial phase without significant motion was compared between the two methods using the χ2 test. The late arterial phase was captured at least once in 96.4% (159/165) of the triple arterial phase group and in 84.2% (494/587) of the single arterial phase group (p < 0.001). Significant motion artifacts (score ≤ 2) were observed in 13.3% (22/165), 1.2% (2/165), 4.8% (8/165) on 1st, 2nd, and 3rd scans of triple arterial phase acquisitions and 6.0% (35/587) of single phase acquisitions. Thus, the late arterial phase without significant motion artifacts was captured in 96.4% (159/165) of the triple arterial phase group and in 79.9% (469/587) of the single arterial phase group (p < 0.001). Triple arterial phase imaging may reliably provide adequate arterial phase imaging for gadoxetic acid-enhanced liver MRI.
The parallel network dynamic DEA model with interval data
Directory of Open Access Journals (Sweden)
S. Keikha-Javan
2014-09-01
Full Text Available In original DEA models, data apply precisely for measuring the relative efficiency whereas in reality, we do not always deal with precise data, also, be noted that when data are non-precision, it is expected to attain non-precision efficiency due to these data. In this article, we apply the parallel network dynamic DEA model for non-precision data in which the carry-overs among periods are assumed as desired and undesired. Then Upper and lower efficiency bounds are obtained for overall-, periodical-, divisional and periodical efficiencies the part which is computed considering the subunits of DMU under evaluation. Finally, having exerted this model on data set of branches of several banks in Iran, we compute the efficiency interval.
Phase separation under two-dimensional Poiseuille flow.
Kiwata, H
2001-05-01
The spinodal decomposition of a two-dimensional binary fluid under Poiseuille flow is studied by numerical simulation. We investigated time dependence of domain sizes in directions parallel and perpendicular to the flow. In an effective region of the flow, the power-law growth of a characteristic length in the direction parallel to the flow changes from the diffusive regime with the growth exponent alpha=1/3 to a new regime. The scaling invariance of the growth in the perpendicular direction is destroyed after the diffusive regime. A recurrent prevalence of thick and thin domains which determines log-time periodic oscillations has not been observed in our model. The growth exponents in the infinite system under two-dimensional Poiseuille flow are obtained by the renormalization group.
Strongly interacting two-dimensional Dirac fermions
Lim, L.K.; Lazarides, A.; Hemmerich, Andreas; de Morais Smith, C.
2009-01-01
We show how strongly interacting two-dimensional Dirac fermions can be realized with ultracold atoms in a two-dimensional optical square lattice with an experimentally realistic, inherent gauge field, which breaks time reversal and inversion symmetries. We find remarkable phenomena in a temperature
Topology optimization of two-dimensional waveguides
DEFF Research Database (Denmark)
Jensen, Jakob Søndergaard; Sigmund, Ole
2003-01-01
In this work we use the method of topology optimization to design two-dimensional waveguides with low transmission loss.......In this work we use the method of topology optimization to design two-dimensional waveguides with low transmission loss....
Parallel calculation of multi-electrode array correlation networks.
Ribeiro, Pedro; Simonotto, Jennifer; Kaiser, Marcus; Silva, Fernando
2009-11-15
When calculating correlation networks from multi-electrode array (MEA) data, one works with extensive computations. Unfortunately, as the MEAs grow bigger, the time needed for the computation grows even more: calculating pair-wise correlations for current 60 channel systems can take hours on normal commodity computers whereas for future 1000 channel systems it would take almost 280 times as long, given that the number of pairs increases with the square of the number of channels. Even taking into account the increase of speed in processors, soon it can be unfeasible to compute correlations in a single computer. Parallel computing is a way to sustain reasonable calculation times in the future. We provide a general tool for rapid computation of correlation networks which was tested for: (a) a single computer cluster with 16 cores, (b) the Newcastle Condor System utilizing idle processors of university computers and (c) the inter-cluster, with 192 cores. Our reusable tool provides a simple interface for neuroscientists, automating data partition and job submission, and also allowing coding in any programming language. It is also sufficiently flexible to be used in other high-performance computing environments.
Parallel multilayer perceptron neural network used for hyperspectral image classification
Garcia-Salgado, Beatriz P.; Ponomaryov, Volodymyr I.; Robles-Gonzalez, Marco A.
2016-04-01
This study is focused on time optimization for the classification problem presenting a comparison of five Artificial Neural Network Multilayer Perceptron (ANN-MLP) architectures. We use the Artificial Neural Network (ANN) because it allows to recognize patterns in data in a lower time rate. Time and classification accuracy are taken into account together for the comparison. According to time comparison, two paradigms in the computational field for each ANN-MLP architecture are analysed with three schemes. Firstly, sequential programming is applied by using a single CPU core. Secondly, parallel programming is employed over a multi-core CPU architecture. Finally, a programming model running on GPU architecture is implemented. Furthermore, the classification accuracy is compared between the proposed five ANN-MLP architectures and a state-of.the-art Support Vector Machine (SVM) with three classification frames: 50%,60% and 70% of the data set's observations are randomly selected to train the classifiers. Also, a visual comparison of the classified results is presented. The Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) criteria are also calculated to characterise visual perception. The images employed were acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), the Reflective Optics System Imaging Spectrometer (ROSIS) and the Hyperion sensor.
Architecture of the parallel hierarchical network for fast image recognition
Timchenko, Leonid; Wójcik, Waldemar; Kokriatskaia, Natalia; Kutaev, Yuriy; Ivasyuk, Igor; Kotyra, Andrzej; Smailova, Saule
2016-09-01
Multistage integration of visual information in the brain allows humans to respond quickly to most significant stimuli while maintaining their ability to recognize small details in the image. Implementation of this principle in technical systems can lead to more efficient processing procedures. The multistage approach to image processing includes main types of cortical multistage convergence. The input images are mapped into a flexible hierarchy that reflects complexity of image data. Procedures of the temporal image decomposition and hierarchy formation are described in mathematical expressions. The multistage system highlights spatial regularities, which are passed through a number of transformational levels to generate a coded representation of the image that encapsulates a structure on different hierarchical levels in the image. At each processing stage a single output result is computed to allow a quick response of the system. The result is presented as an activity pattern, which can be compared with previously computed patterns on the basis of the closest match. With regard to the forecasting method, its idea lies in the following. In the results synchronization block, network-processed data arrive to the database where a sample of most correlated data is drawn using service parameters of the parallel-hierarchical network.
Institute of Scientific and Technical Information of China (English)
DU，Miao(杜淼); DU,Miao; XU，Qiang(徐强); XU,Qiang; GUO，Ya-Mei (郭亚梅); GUO,Ya-Mei; WENG，Lin-Hong(翁林红); WENG,Lin-Hong; BU，Xian-He (卜显和); BU,Xian-He
2001-01-01
A penta-coordinated Ni(II) complex with a 1,5-diazacyclooctane (DACO) ligand functionazed by two imidazole donor pendants, [NiiL1Cl] (ClO4)'HH2O (1) (where L1 = 1,5-bis (imidazol-4-ylmethyl)-1,S-diazacyclooctane) has been synthesized and characterized by X-ray diffraction, infrared spectra, elemental analyses, conductance, thermal analyses and UV-Vis techniques. Complex 1 crystallizes in triclinic crystal system, P-1 space group with a = 0.74782(7), b = 1.15082(10), c = 1.237s1(11) nm, a=82.090(2), β=73.011(2), γ=83.462(2)°, V= 1.00603(16) nn3, Mr = 486.00, Z=2,Dc=1.604 g/cm3, final R＝0.0435, and wR=0.1244. The structures of 1 and its related complexes show that in all the three mononuclear complexes, each Ni(Ⅱ) center is penta-coordinated with a near regular square pyranid (RSP) to distorted square-pyramidal (DSP) coordination environment due to the boat/chair configuration of DACO ring in these complexes, and the degree of distortion increases with the augment of the size of the heterocyclic pendants. In addition, the most striking feature of complex 1 resides in the formation of a two-dimensional network structure through hydrogen bonds and stabilized by π-π stacking. The solution behaviors of the Ni(ⅡI) complexes are also discussed in detail.
Interaction of two-dimensional magnetoexcitons
Dumanov, E. V.; Podlesny, I. V.; Moskalenko, S. A.; Liberman, M. A.
2017-04-01
We study interaction of the two-dimensional magnetoexcitons with in-plane wave vector k→∥ = 0 , taking into account the influence of the excited Landau levels (ELLs) and of the external electric field perpendicular to the surface of the quantum well and parallel to the external magnetic field. It is shown that the account of the ELLs gives rise to the repulsion between the spinless magnetoexcitons with k→∥ = 0 in the Fock approximation, with the interaction constant g decreasing inverse proportional to the magnetic field strength B (g (0) ∼ 1 / B) . In the presence of the perpendicular electric field the Rashba spin-orbit coupling (RSOC), Zeeman splitting (ZS) and nonparabolicity of the heavy-hole dispersion law affect the Landau quantization of the electrons and holes. They move along the new cyclotron orbits, change their Coulomb interactions and cause the interaction between 2D magnetoexcitons with k→∥ = 0 . The changes of the Coulomb interactions caused by the electrons and by the holes moving with new cyclotron orbits are characterized by some coefficients, which in the absence of the electric field turn to be unity. The differences between these coefficients of the electron-hole pairs forming the magnetoexcitons determine their affinities to the interactions. The interactions between the homogeneous, semihomogeneous and heterogeneous magnetoexcitons forming the symmetric states with the same signs of their affinities are attractive whereas in the case of different sign affinities are repulsive. In the heterogeneous asymmetric states the interactions have opposite signs in comparison with the symmetric states. In all these cases the interaction constant g have the dependence g (0) 1 /√{ B} .
Two Dimensional Plasmonic Cavities on Moire Surfaces
Balci, Sinan; Kocabas, Askin; Karabiyik, Mustafa; Kocabas, Coskun; Aydinli, Atilla
2010-03-01
We investigate surface plasmon polariton (SPP) cavitiy modes on two dimensional Moire surfaces in the visible spectrum. Two dimensional hexagonal Moire surface can be recorded on a photoresist layer using Interference lithography (IL). Two sequential exposures at slightly different angles in IL generate one dimensional Moire surfaces. Further sequential exposure for the same sample at slightly different angles after turning the sample 60 degrees around its own axis generates two dimensional hexagonal Moire cavity. Spectroscopic reflection measurements have shown plasmonic band gaps and cavity states at all the azimuthal angles (omnidirectional cavity and band gap formation) investigated. The plasmonic band gap edge and the cavity states energies show six fold symmetry on the two dimensional Moire surface as measured in reflection measurements.
Two-dimensional function photonic crystals
Liu, Xiao-Jing; Liang, Yu; Ma, Ji; Zhang, Si-Qi; Li, Hong; Wu, Xiang-Yao; Wu, Yi-Heng
2017-01-01
In this paper, we have studied two-dimensional function photonic crystals, in which the dielectric constants of medium columns are the functions of space coordinates , that can become true easily by electro-optical effect and optical kerr effect. We calculated the band gap structures of TE and TM waves, and found the TE (TM) wave band gaps of function photonic crystals are wider (narrower) than the conventional photonic crystals. For the two-dimensional function photonic crystals, when the dielectric constant functions change, the band gaps numbers, width and position should be changed, and the band gap structures of two-dimensional function photonic crystals can be adjusted flexibly, the needed band gap structures can be designed by the two-dimensional function photonic crystals, and it can be of help to design optical devices.
Two-Dimensional Planetary Surface Lander
Hemmati, H.; Sengupta, A.; Castillo, J.; McElrath, T.; Roberts, T.; Willis, P.
2014-06-01
A systems engineering study was conducted to leverage a new two-dimensional (2D) lander concept with a low per unit cost to enable scientific study at multiple locations with a single entry system as the delivery vehicle.
Parallel logic gates in synthetic gene networks induced by non-Gaussian noise.
Xu, Yong; Jin, Xiaoqin; Zhang, Huiqing
2013-11-01
The recent idea of logical stochastic resonance is verified in synthetic gene networks induced by non-Gaussian noise. We realize the switching between two kinds of logic gates under optimal moderate noise intensity by varying two different tunable parameters in a single gene network. Furthermore, in order to obtain more logic operations, thus providing additional information processing capacity, we obtain in a two-dimensional toggle switch model two complementary logic gates and realize the transformation between two logic gates via the methods of changing different parameters. These simulated results contribute to improve the computational power and functionality of the networks.
Speeding up parallel GROMACS on high-latency networks.
Kutzner, Carsten; van der Spoel, David; Fechner, Martin; Lindahl, Erik; Schmitt, Udo W; de Groot, Bert L; Grubmüller, Helmut
2007-09-01
We investigate the parallel scaling of the GROMACS molecular dynamics code on Ethernet Beowulf clusters and what prerequisites are necessary for decent scaling even on such clusters with only limited bandwidth and high latency. GROMACS 3.3 scales well on supercomputers like the IBM p690 (Regatta) and on Linux clusters with a special interconnect like Myrinet or Infiniband. Because of the high single-node performance of GROMACS, however, on the widely used Ethernet switched clusters, the scaling typically breaks down when more than two computer nodes are involved, limiting the absolute speedup that can be gained to about 3 relative to a single-CPU run. With the LAM MPI implementation, the main scaling bottleneck is here identified to be the all-to-all communication which is required every time step. During such an all-to-all communication step, a huge amount of messages floods the network, and as a result many TCP packets are lost. We show that Ethernet flow control prevents network congestion and leads to substantial scaling improvements. For 16 CPUs, e.g., a speedup of 11 has been achieved. However, for more nodes this mechanism also fails. Having optimized an all-to-all routine, which sends the data in an ordered fashion, we show that it is possible to completely prevent packet loss for any number of multi-CPU nodes. Thus, the GROMACS scaling dramatically improves, even for switches that lack flow control. In addition, for the common HP ProCurve 2848 switch we find that for optimum all-to-all performance it is essential how the nodes are connected to the switch's ports. This is also demonstrated for the example of the Car-Parinello MD code.
Institute of Scientific and Technical Information of China (English)
Zhao Feng; Li Qinghua
2005-01-01
A new real-time model based on parallel time-series mining is proposed to improve the accuracy and efficiency of the network intrusion detection systems. In this model, multidimensional dataset is constructed to describe network events, and sliding window updating algorithm is used to maintain network stream. Moreover, parallel frequent patterns and frequent episodes mining algorithms are applied to implement parallel time-series mining engineer which can intelligently generate rules to distinguish intrusions from normal activities. Analysis and study on the basis of DAWNING 3000 indicate that this parallel time-series mining-based model provides a more accurate and efficient way to building real-time NIDS.
Vuurpijl, L.G.
1998-01-01
In this thesis, two platforms for simulating artificial neural networks are discussed: MIMD-parallel processor systems as an execution platform and neurosimulators as a research and development platform. Because of the parallelism encountered in neural networks, distributed processor systems seem to
Vuurpijl, L.G.
1998-01-01
In this thesis, two platforms for simulating artificial neural networks are discussed: MIMD-parallel processor systems as an execution platform and neurosimulators as a research and development platform. Because of the parallelism encountered in neural networks, distributed processor systems seem to
Cooperative Transmission for a Vector Gaussian Parallel Relay Network
Kim, Muryong
2009-01-01
In this paper, we consider a parallel relay network where two relays cooperatively help a source transmit to a destination. We assume the source and the destination nodes are equipped with multiple antennas. Three basic schemes and their achievable rates are studied: Decode-and-Forward (DF), Amplify-and-Forward (AF), and Compress-and-Forward (CF). For the DF scheme, the source transmits two private signals, one for each relay, where dirty paper coding (DPC) is used between the two private streams, and a common signal for both relays. The relays make efficient use of the common information to introduce a proper amount of correlation in the transmission to the destination. We show that the DF scheme achieves the capacity under certain conditions. We also show that the CF scheme is asymptotically optimal in the high relay power limit, regardless of channel ranks. It turns out that the AF scheme also achieves the asymptotic optimality but only when the relays-to-destination channel is full rank. The relative adva...
Institute of Scientific and Technical Information of China (English)
徐速
2011-01-01
Taking Beijing Yizhuang economic development area as example, the MIKE Flood integrated simulation model was used for one- and two-dimensional integrated simulation of storm pipe network and surface flow for the existing condition and constructed wetland built in the future in 1, 5, and 10 year storm return periods. The results show that under the existing condition, there are flooded areas in all 3 storm return periods, especially in more than 5 year return periods, the flooded area exceeds 10％ of the total area. The constructed wetland built in the future can reduce about 20％ flooded area,which locates at the upstream of the wetland, than the existing condition. The results can be utilized to do further research including risk assessment and comparison among emergency response plans to find an optimal way to reduce loss from storm.%采用MTKE n00d集成模型,以北京市亦庄经济技术开发区为案例,针对现状和未来建设人工湿地两种情景,对1年、5年、10年暴雨重现期下的淹没特性进行了雨水管网和地面流的一、二维集成模拟.模拟结果表明,在现状条件下,3种暴雨重现期都会产生淹没区域,尤其是在5年以上重现期时整个区域的10%都会被淹没;未来建设人工湿地可比现状减少20%左右的淹没面积,但其作用范围是人工湿地上游区域,对其他区域则没有明显作用.利用这些结果可进行暴雨危害的风险评估,并对各种工程方案进行比较分析,以寻找减轻暴雨淹没损失的最佳途径.
Interpolation by two-dimensional cubic convolution
Shi, Jiazheng; Reichenbach, Stephen E.
2003-08-01
This paper presents results of image interpolation with an improved method for two-dimensional cubic convolution. Convolution with a piecewise cubic is one of the most popular methods for image reconstruction, but the traditional approach uses a separable two-dimensional convolution kernel that is based on a one-dimensional derivation. The traditional, separable method is sub-optimal for the usual case of non-separable images. The improved method in this paper implements the most general non-separable, two-dimensional, piecewise-cubic interpolator with constraints for symmetry, continuity, and smoothness. The improved method of two-dimensional cubic convolution has three parameters that can be tuned to yield maximal fidelity for specific scene ensembles characterized by autocorrelation or power-spectrum. This paper illustrates examples for several scene models (a circular disk of parametric size, a square pulse with parametric rotation, and a Markov random field with parametric spatial detail) and actual images -- presenting the optimal parameters and the resulting fidelity for each model. In these examples, improved two-dimensional cubic convolution is superior to several other popular small-kernel interpolation methods.
Lee, Wei-Po; Hsiao, Yu-Ting; Hwang, Wei-Che
2014-01-16
To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high
2014-01-01
Background To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. Results This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Conclusions Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel
TWO-DIMENSIONAL TOPOLOGY OF COSMOLOGICAL REIONIZATION
Energy Technology Data Exchange (ETDEWEB)
Wang, Yougang; Xu, Yidong; Chen, Xuelei [Key Laboratory of Computational Astrophysics, National Astronomical Observatories, Chinese Academy of Sciences, Beijing, 100012 China (China); Park, Changbom [School of Physics, Korea Institute for Advanced Study, 85 Hoegiro, Dongdaemun-gu, Seoul 130-722 (Korea, Republic of); Kim, Juhan, E-mail: wangyg@bao.ac.cn, E-mail: cbp@kias.re.kr [Center for Advanced Computation, Korea Institute for Advanced Study, 85 Hoegiro, Dongdaemun-gu, Seoul 130-722 (Korea, Republic of)
2015-11-20
We study the two-dimensional topology of the 21-cm differential brightness temperature for two hydrodynamic radiative transfer simulations and two semi-numerical models. In each model, we calculate the two-dimensional genus curve for the early, middle, and late epochs of reionization. It is found that the genus curve depends strongly on the ionized fraction of hydrogen in each model. The genus curves are significantly different for different reionization scenarios even when the ionized faction is the same. We find that the two-dimensional topology analysis method is a useful tool to constrain the reionization models. Our method can be applied to the future observations such as those of the Square Kilometre Array.
Two dimensional topology of cosmological reionization
Wang, Yougang; Xu, Yidong; Chen, Xuelei; Kim, Juhan
2015-01-01
We study the two-dimensional topology of the 21-cm differential brightness temperature for two hydrodynamic radiative transfer simulations and two semi-numerical models. In each model, we calculate the two dimensional genus curve for the early, middle and late epochs of reionization. It is found that the genus curve depends strongly on the ionized fraction of hydrogen in each model. The genus curves are significantly different for different reionization scenarios even when the ionized faction is the same. We find that the two-dimensional topology analysis method is a useful tool to constrain the reionization models. Our method can be applied to the future observations such as those of the Square Kilometer Array.
Two-dimensional x-ray diffraction
He, Bob B
2009-01-01
Written by one of the pioneers of 2D X-Ray Diffraction, this useful guide covers the fundamentals, experimental methods and applications of two-dimensional x-ray diffraction, including geometry convention, x-ray source and optics, two-dimensional detectors, diffraction data interpretation, and configurations for various applications, such as phase identification, texture, stress, microstructure analysis, crystallinity, thin film analysis and combinatorial screening. Experimental examples in materials research, pharmaceuticals, and forensics are also given. This presents a key resource to resea
Matching Two-dimensional Gel Electrophoresis' Spots
DEFF Research Database (Denmark)
Dos Anjos, António; AL-Tam, Faroq; Shahbazkia, Hamid Reza
2012-01-01
This paper describes an approach for matching Two-Dimensional Electrophoresis (2-DE) gels' spots, involving the use of image registration. The number of false positive matches produced by the proposed approach is small, when compared to academic and commercial state-of-the-art approaches. This ar......This paper describes an approach for matching Two-Dimensional Electrophoresis (2-DE) gels' spots, involving the use of image registration. The number of false positive matches produced by the proposed approach is small, when compared to academic and commercial state-of-the-art approaches...
Mobility anisotropy of two-dimensional semiconductors
Lang, Haifeng; Zhang, Shuqing; Liu, Zhirong
2016-12-01
The carrier mobility of anisotropic two-dimensional semiconductors under longitudinal acoustic phonon scattering was theoretically studied using deformation potential theory. Based on the Boltzmann equation with the relaxation time approximation, an analytic formula of intrinsic anisotropic mobility was derived, showing that the influence of effective mass on mobility anisotropy is larger than those of deformation potential constant or elastic modulus. Parameters were collected for various anisotropic two-dimensional materials (black phosphorus, Hittorf's phosphorus, BC2N , MXene, TiS3, and GeCH3) to calculate their mobility anisotropy. It was revealed that the anisotropic ratio is overestimated by the previously described method.
Two-dimensional transport study of scrape off layer plasmas
Energy Technology Data Exchange (ETDEWEB)
Yamamoto, Nobuyuki [Interdisciplinary Graduate School of Advanced Energy Engineering Sciences, Kyushu University, Fukuoka (Japan); Yagi, Masatoshi; Itoh, Sanae-I. [Kyushu Univ., Fukuoka (Japan). Research Inst. for Applied Mechanics
1999-09-01
Two-dimensional transport code is developed to analyzed the heat pulse propagation in the scrape-off layer plasma. The classical and anomalous transport models are considered as a thermal diffusivity perpendicular to the magnetic field. On the other hand, the classical transport model is chosen as a thermal diffusivity parallel to the magnetic field. The heat deposition profiles are evaluated for various kinds of transport models. It is found that the heat pulse which arrives at the divertor plate due to the classical transport is largest compared with other models. The steady state temperate profiles of the electron and ion are also discussed. (author)
Experimental realization of two-dimensional boron sheets.
Feng, Baojie; Zhang, Jin; Zhong, Qing; Li, Wenbin; Li, Shuai; Li, Hui; Cheng, Peng; Meng, Sheng; Chen, Lan; Wu, Kehui
2016-06-01
A variety of two-dimensional materials have been reported in recent years, yet single-element systems such as graphene and black phosphorus have remained rare. Boron analogues have been predicted, as boron atoms possess a short covalent radius and the flexibility to adopt sp(2) hybridization, features that favour the formation of two-dimensional allotropes, and one example of such a borophene material has been reported recently. Here, we present a parallel experimental work showing that two-dimensional boron sheets can be grown epitaxially on a Ag(111) substrate. Two types of boron sheet, a β12 sheet and a χ3 sheet, both exhibiting a triangular lattice but with different arrangements of periodic holes, are observed by scanning tunnelling microscopy. Density functional theory simulations agree well with experiments, and indicate that both sheets are planar without obvious vertical undulations. The boron sheets are quite inert to oxidization and interact only weakly with their substrate. We envisage that such boron sheets may find applications in electronic devices in the future.
Institute of Scientific and Technical Information of China (English)
吉建华; 范戈
2002-01-01
A new one-dimensional optical orthogonal codes(1-D OOC) named extended hyperbolic line congruence codes(EHLC) is constructed,and its performance is analyzed.Compared with extended quadratic congruence codes(EQC),EHLC has large code cardinality,but has a little poor performances of auto-correlation and cross-correlation.Then,using EHLC for time spreading and prime sequence(PC) for wavelength hopping,a new two-dimensional optical orthogonal codes(2-D OOC)named EHLC/PC is constructed.Because the code weight of EHLC equals(p-1) and the code weight of PC equals p,selection function f(i) should be used to pick out(p-1)wavelengths from each prime sequence.At last,the performance of EHLC/PC is analyzed,and is also compared with EQC/PC.Because each wavelength within a code is different,auto-correlation of EHLC/PC equals zero.When examining the cross-correlation of EHLC/PC,authors should consider four different modes:same time spreading pattern/same wavelength hopping pattern(different sk),same time spreading pattern/different wavelength hopping pattern,different time spreading pattern/same wavelength hopping pattern,different time spreading pattern/different wavelenght hopping pattern.By using difference function and wavelength hopping pattern,it is not difficult to get the cross-correlation performances of EHLC/PC.It is shown that the cross-correlation performance of EHLC/PC is a little worse than EQC/PC,but EHLC/PC has much larger code cardinality.Moreover,EHLC/PC has shorter code length and smaller code weight,which can enhance user data rate and also can reduce the complexity of optical encoders/decoders.Therefore,EHLC/PC is suitable for massive optical code-division multiple-access(OCDMA) networks.%构造了一种扩展的双曲线性同余码(EHLC)并分析了其码字性能.用该码作为时间扩频伪随机序列和以素数码(PC)作为波长跳频伪随机序列,再构成一种新的二维光正交码EHLC/PC.然后分析了EHLC/PC码字的性能,并与EQC/PC
Piezoelectricity in Two-Dimensional Materials
Wu, Tao
2015-02-25
Powering up 2D materials: Recent experimental studies confirmed the existence of piezoelectricity - the conversion of mechanical stress into electricity - in two-dimensional single-layer MoS2 nanosheets. The results represent a milestone towards embedding low-dimensional materials into future disruptive technologies. © 2015 Wiley-VCH Verlag GmbH & Co. KGaA.
Kronecker Product of Two-dimensional Arrays
Institute of Scientific and Technical Information of China (English)
Lei Hu
2006-01-01
Kronecker sequences constructed from short sequences are good sequences for spread spectrum communication systems. In this paper we study a similar problem for two-dimensional arrays, and we determine the linear complexity of the Kronecker product of two arrays. Our result shows that similar good property on linear complexity holds for Kronecker product of arrays.
Two-Dimensional Toda-Heisenberg Lattice
Directory of Open Access Journals (Sweden)
Vadim E. Vekslerchik
2013-06-01
Full Text Available We consider a nonlinear model that is a combination of the anisotropic two-dimensional classical Heisenberg and Toda-like lattices. In the framework of the Hirota direct approach, we present the field equations of this model as a bilinear system, which is closely related to the Ablowitz-Ladik hierarchy, and derive its N-soliton solutions.
A novel two dimensional particle velocity sensor
Pjetri, Olti; Wiegerink, Remco J.; Lammerink, Theo S.; Krijnen, Gijs J.
2013-01-01
In this paper we present a two wire, two-dimensional particle velocity sensor. The miniature sensor of size 1.0x2.5x0.525 mm, consisting of only two crossed wires, shows excellent directional sensitivity in both directions, thus requiring no directivity calibration, and is relatively easy to fabrica
Two-dimensional microstrip detector for neutrons
Energy Technology Data Exchange (ETDEWEB)
Oed, A. [Institut Max von Laue - Paul Langevin (ILL), 38 - Grenoble (France)
1997-04-01
Because of their robust design, gas microstrip detectors, which were developed at ILL, can be assembled relatively quickly, provided the prefabricated components are available. At the beginning of 1996, orders were received for the construction of three two-dimensional neutron detectors. These detectors have been completed. The detectors are outlined below. (author). 2 refs.
Two-dimensional magma-repository interactions
Bokhove, O.
2001-01-01
Two-dimensional simulations of magma-repository interactions reveal that the three phases --a shock tube, shock reflection and amplification, and shock attenuation and decay phase-- in a one-dimensional flow tube model have a precursor. This newly identified phase ``zero'' consists of the impact of
Two-dimensional subwavelength plasmonic lattice solitons
Ye, F; Hu, B; Panoiu, N C
2010-01-01
We present a theoretical study of plasmonic lattice solitons (PLSs) formed in two-dimensional (2D) arrays of metallic nanowires embedded into a nonlinear medium with Kerr nonlinearity. We analyze two classes of 2D PLSs families, namely, fundamental and vortical PLSs in both focusing and defocusing media. Their existence, stability, and subwavelength spatial confinement are studied in detai
A two-dimensional Dirac fermion microscope
DEFF Research Database (Denmark)
Bøggild, Peter; Caridad, Jose; Stampfer, Christoph
2017-01-01
in the solid state. Here we provide a perspective view on how a two-dimensional (2D) Dirac fermion-based microscope can be realistically implemented and operated, using graphene as a vacuum chamber for ballistic electrons. We use semiclassical simulations to propose concrete architectures and design rules of 2...
An evaluation of parallel optimization for OpenSolaris Network Stack
Energy Technology Data Exchange (ETDEWEB)
Zou, Hongbo; Wu, Wenji; /Fermilab; Sun, Xian-He; /IIT, Chicago; DeMar, Phil; Crawford, Matt; /Fermilab
2010-10-01
Computing is now shifting towards multiprocessing. The fundamental goal of multiprocessing is improved performance through the introduction of additional hardware threads or cores (referred to as 'cores' for simplicity). Modern network stacks can exploit parallel cores to allow either message-based parallelism or connection-based parallelism as a means to enhance performance. OpenSolaris has redesigned and parallelized to better utilize additional cores. Three special technologies, named Softring Set, Soft ring and Squeue are introduced in OpenSolaris for stack parallelization. In this paper, we study the OpenSolaris packet receiving process and its core parallelism optimization techniques. Experiment results show that these techniques allow OpenSolaris to achieve better network I/O performance in multiprocessing environments; however, network stack parallelization has also brought extra overheads for system. An effective and efficient network I/O optimization in multiprocessing environments is required to cross all levers of the network stack from network interface to application.
Energy Technology Data Exchange (ETDEWEB)
Blocksome, Michael A.; Mamidala, Amith R.
2015-07-14
Fencing direct memory access (`DMA`) data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint including specifications of a client, a context, and a task, the endpoints coupled for data communications through the PAMI and through DMA controllers operatively coupled to a deterministic data communications network through which the DMA controllers deliver data communications deterministically, including initiating execution through the PAMI of an ordered sequence of active DMA instructions for DMA data transfers between two endpoints, effecting deterministic DMA data transfers through a DMA controller and the deterministic data communications network; and executing through the PAMI, with no FENCE accounting for DMA data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all DMA instructions initiated prior to execution of the FENCE instruction for DMA data transfers between the two endpoints.
Energy Technology Data Exchange (ETDEWEB)
Blocksome, Michael A.; Mamidala, Amith R.
2015-07-07
Fencing direct memory access (`DMA`) data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint including specifications of a client, a context, and a task, the endpoints coupled for data communications through the PAMI and through DMA controllers operatively coupled to a deterministic data communications network through which the DMA controllers deliver data communications deterministically, including initiating execution through the PAMI of an ordered sequence of active DMA instructions for DMA data transfers between two endpoints, effecting deterministic DMA data transfers through a DMA controller and the deterministic data communications network; and executing through the PAMI, with no FENCE accounting for DMA data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all DMA instructions initiated prior to execution of the FENCE instruction for DMA data transfers between the two endpoints.
Tetanic stimulation of cortical networks induces parallel memory
Veenendaal, van Tamar; Witteveen, Tim; Feber, le Joost; Akay, M
2013-01-01
The mechanisms behind memory have been studied mainly in artificial neural networks. Several mechanisms have been proposed, but it remains unclear yet if and how these findings can be translated to biological networks. Here we unravel part of the mechanism by showing that cultured neuronal networks
Parallel unstructured AMR and gigabit networking for Beowulf-class clusters
Norton, C. D.; Cwik, T. A.
2001-01-01
The impact of gigabit networking with Myrinet 2000 hardware and MPICH-GM software on a 2-way SMP Beowulf-class cluster for parallel unstructured adaptive mesh refinement using the PYRAMID library is described.
From devil to angel, transmission lines boost parallel computing of linear resistor networks
Wei, Fei
2009-01-01
Transmission line is always big trouble for integrated circuits designers; however, it could be of great help to the parallel computing of extremely large linear resistor networks. In this paper, we introduce the virtual transmission method (VTM), which brings virtual transmission lines into linear resistor networks to achieve distributed and asynchronous parallel computing in the virtual time domain. Numerical experiments show that VTM could be efficiently running on the 2D or 3D microprocessor with arbitrary number of cores.
Jiang, Hayang; Xie, Gaogang; Salamatian, Kavé; Mathy, Laurent
2013-01-01
Network Intrusion Detection Systems (NIDSes) face significant challenges coming from the relentless network link speed growth and increasing complexity of threats. Both hardware accelerated and parallel software-based NIDS solutions, based on commodity multi-core and GPU processors, have been proposed to overcome these challenges. Network Intrusion Detection Systems (NIDSes) face significant challenges coming from the relentless network link speed growth and increasing complexity of threats. ...
Electronics based on two-dimensional materials.
Fiori, Gianluca; Bonaccorso, Francesco; Iannaccone, Giuseppe; Palacios, Tomás; Neumaier, Daniel; Seabaugh, Alan; Banerjee, Sanjay K; Colombo, Luigi
2014-10-01
The compelling demand for higher performance and lower power consumption in electronic systems is the main driving force of the electronics industry's quest for devices and/or architectures based on new materials. Here, we provide a review of electronic devices based on two-dimensional materials, outlining their potential as a technological option beyond scaled complementary metal-oxide-semiconductor switches. We focus on the performance limits and advantages of these materials and associated technologies, when exploited for both digital and analog applications, focusing on the main figures of merit needed to meet industry requirements. We also discuss the use of two-dimensional materials as an enabling factor for flexible electronics and provide our perspectives on future developments.
Two-dimensional ranking of Wikipedia articles
Zhirov, A. O.; Zhirov, O. V.; Shepelyansky, D. L.
2010-10-01
The Library of Babel, described by Jorge Luis Borges, stores an enormous amount of information. The Library exists ab aeterno. Wikipedia, a free online encyclopaedia, becomes a modern analogue of such a Library. Information retrieval and ranking of Wikipedia articles become the challenge of modern society. While PageRank highlights very well known nodes with many ingoing links, CheiRank highlights very communicative nodes with many outgoing links. In this way the ranking becomes two-dimensional. Using CheiRank and PageRank we analyze the properties of two-dimensional ranking of all Wikipedia English articles and show that it gives their reliable classification with rich and nontrivial features. Detailed studies are done for countries, universities, personalities, physicists, chess players, Dow-Jones companies and other categories.
Two-Dimensional NMR Lineshape Analysis
Waudby, Christopher A.; Ramos, Andres; Cabrita, Lisa D.; Christodoulou, John
2016-04-01
NMR titration experiments are a rich source of structural, mechanistic, thermodynamic and kinetic information on biomolecular interactions, which can be extracted through the quantitative analysis of resonance lineshapes. However, applications of such analyses are frequently limited by peak overlap inherent to complex biomolecular systems. Moreover, systematic errors may arise due to the analysis of two-dimensional data using theoretical frameworks developed for one-dimensional experiments. Here we introduce a more accurate and convenient method for the analysis of such data, based on the direct quantum mechanical simulation and fitting of entire two-dimensional experiments, which we implement in a new software tool, TITAN (TITration ANalysis). We expect the approach, which we demonstrate for a variety of protein-protein and protein-ligand interactions, to be particularly useful in providing information on multi-step or multi-component interactions.
A two-dimensional Dirac fermion microscope
Bøggild, Peter; Caridad, José M.; Stampfer, Christoph; Calogero, Gaetano; Papior, Nick Rübner; Brandbyge, Mads
2017-06-01
The electron microscope has been a powerful, highly versatile workhorse in the fields of material and surface science, micro and nanotechnology, biology and geology, for nearly 80 years. The advent of two-dimensional materials opens new possibilities for realizing an analogy to electron microscopy in the solid state. Here we provide a perspective view on how a two-dimensional (2D) Dirac fermion-based microscope can be realistically implemented and operated, using graphene as a vacuum chamber for ballistic electrons. We use semiclassical simulations to propose concrete architectures and design rules of 2D electron guns, deflectors, tunable lenses and various detectors. The simulations show how simple objects can be imaged with well-controlled and collimated in-plane beams consisting of relativistic charge carriers. Finally, we discuss the potential of such microscopes for investigating edges, terminations and defects, as well as interfaces, including external nanoscale structures such as adsorbed molecules, nanoparticles or quantum dots.
A two-dimensional Dirac fermion microscope.
Bøggild, Peter; Caridad, José M; Stampfer, Christoph; Calogero, Gaetano; Papior, Nick Rübner; Brandbyge, Mads
2017-06-09
The electron microscope has been a powerful, highly versatile workhorse in the fields of material and surface science, micro and nanotechnology, biology and geology, for nearly 80 years. The advent of two-dimensional materials opens new possibilities for realizing an analogy to electron microscopy in the solid state. Here we provide a perspective view on how a two-dimensional (2D) Dirac fermion-based microscope can be realistically implemented and operated, using graphene as a vacuum chamber for ballistic electrons. We use semiclassical simulations to propose concrete architectures and design rules of 2D electron guns, deflectors, tunable lenses and various detectors. The simulations show how simple objects can be imaged with well-controlled and collimated in-plane beams consisting of relativistic charge carriers. Finally, we discuss the potential of such microscopes for investigating edges, terminations and defects, as well as interfaces, including external nanoscale structures such as adsorbed molecules, nanoparticles or quantum dots.
Two-Dimensional Scheduling: A Review
Directory of Open Access Journals (Sweden)
Zhuolei Xiao
2013-07-01
Full Text Available In this study, we present a literature review, classification schemes and analysis of methodology for scheduling problems on Batch Processing machine (BP with both processing time and job size constraints which is also regarded as Two-Dimensional (TD scheduling. Special attention is given to scheduling problems with non-identical job sizes and processing times, with details of the basic algorithms and other significant results.
Two dimensional fermions in four dimensional YM
Narayanan, R
2009-01-01
Dirac fermions in the fundamental representation of SU(N) live on a two dimensional torus flatly embedded in $R^4$. They interact with a four dimensional SU(N) Yang Mills vector potential preserving a global chiral symmetry at finite $N$. As the size of the torus in units of $\\frac{1}{\\Lambda_{SU(N)}}$ is varied from small to large, the chiral symmetry gets spontaneously broken in the infinite $N$ limit.
Two-dimensional Kagome photonic bandgap waveguide
DEFF Research Database (Denmark)
Nielsen, Jens Bo; Søndergaard, Thomas; Libori, Stig E. Barkou;
2000-01-01
The transverse-magnetic photonic-bandgap-guidance properties are investigated for a planar two-dimensional (2-D) Kagome waveguide configuration using a full-vectorial plane-wave-expansion method. Single-moded well-localized low-index guided modes are found. The localization of the optical modes...... is investigated with respect to the width of the 2-D Kagome waveguide, and the number of modes existing for specific frequencies and waveguide widths is mapped out....
String breaking in two-dimensional QCD
Hornbostel, K J
1999-01-01
I present results of a numerical calculation of the effects of light quark-antiquark pairs on the linear heavy-quark potential in light-cone quantized two-dimensional QCD. I extract the potential from the Q-Qbar component of the ground-state wavefunction, and observe string breaking at the heavy-light meson pair threshold. I briefly comment on the states responsible for the breaking.
Two-dimensional supramolecular electron spin arrays.
Wäckerlin, Christian; Nowakowski, Jan; Liu, Shi-Xia; Jaggi, Michael; Siewert, Dorota; Girovsky, Jan; Shchyrba, Aneliia; Hählen, Tatjana; Kleibert, Armin; Oppeneer, Peter M; Nolting, Frithjof; Decurtins, Silvio; Jung, Thomas A; Ballav, Nirmalya
2013-05-07
A bottom-up approach is introduced to fabricate two-dimensional self-assembled layers of molecular spin-systems containing Mn and Fe ions arranged in a chessboard lattice. We demonstrate that the Mn and Fe spin states can be reversibly operated by their selective response to coordination/decoordination of volatile ligands like ammonia (NH3). Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Two dimensional echocardiographic detection of intraatrial masses.
DePace, N L; Soulen, R L; Kotler, M N; Mintz, G S
1981-11-01
With two dimensional echocardiography, a left atrial mass was detected in 19 patients. Of these, 10 patients with rheumatic mitral stenosis had a left atrial thrombus. The distinctive two dimensional echocardiographic features of left atrial thrombus included a mass of irregular nonmobile laminated echos within an enlarged atrial cavity, usually with a broad base of attachment to the posterior left atrial wall. Seven patients had a left atrial myxoma. Usually, the myxoma appeared as a mottled ovoid, sharply demarcated mobile mass attached to the interatrial septum. One patient had a right atrial angiosarcoma that appeared as a nonmobile mass extending from the inferior vena caval-right atrial junction into the right atrial cavity. One patient had a left atrial leiomyosarcoma producing a highly mobile mass attached to the lateral wall of the left atrium. M mode echocardiography detected six of the seven myxomas, one thrombus and neither of the other tumors. Thus, two dimensional echocardiography appears to be the technique of choice in the detection, localization and differentiation of intraatrial masses.
A Parallel Adaboost-Backpropagation Neural Network for Massive Image Dataset Classification
Cao, Jianfang; Chen, Lichao; Wang, Min; Shi, Hao; Tian, Yun
2016-12-01
Image classification uses computers to simulate human understanding and cognition of images by automatically categorizing images. This study proposes a faster image classification approach that parallelizes the traditional Adaboost-Backpropagation (BP) neural network using the MapReduce parallel programming model. First, we construct a strong classifier by assembling the outputs of 15 BP neural networks (which are individually regarded as weak classifiers) based on the Adaboost algorithm. Second, we design Map and Reduce tasks for both the parallel Adaboost-BP neural network and the feature extraction algorithm. Finally, we establish an automated classification model by building a Hadoop cluster. We use the Pascal VOC2007 and Caltech256 datasets to train and test the classification model. The results are superior to those obtained using traditional Adaboost-BP neural network or parallel BP neural network approaches. Our approach increased the average classification accuracy rate by approximately 14.5% and 26.0% compared to the traditional Adaboost-BP neural network and parallel BP neural network, respectively. Furthermore, the proposed approach requires less computation time and scales very well as evaluated by speedup, sizeup and scaleup. The proposed approach may provide a foundation for automated large-scale image classification and demonstrates practical value.
A Parallel Adaboost-Backpropagation Neural Network for Massive Image Dataset Classification.
Cao, Jianfang; Chen, Lichao; Wang, Min; Shi, Hao; Tian, Yun
2016-12-01
Image classification uses computers to simulate human understanding and cognition of images by automatically categorizing images. This study proposes a faster image classification approach that parallelizes the traditional Adaboost-Backpropagation (BP) neural network using the MapReduce parallel programming model. First, we construct a strong classifier by assembling the outputs of 15 BP neural networks (which are individually regarded as weak classifiers) based on the Adaboost algorithm. Second, we design Map and Reduce tasks for both the parallel Adaboost-BP neural network and the feature extraction algorithm. Finally, we establish an automated classification model by building a Hadoop cluster. We use the Pascal VOC2007 and Caltech256 datasets to train and test the classification model. The results are superior to those obtained using traditional Adaboost-BP neural network or parallel BP neural network approaches. Our approach increased the average classification accuracy rate by approximately 14.5% and 26.0% compared to the traditional Adaboost-BP neural network and parallel BP neural network, respectively. Furthermore, the proposed approach requires less computation time and scales very well as evaluated by speedup, sizeup and scaleup. The proposed approach may provide a foundation for automated large-scale image classification and demonstrates practical value.
Electromagnetically induced two-dimensional grating assisted by incoherent pump
Energy Technology Data Exchange (ETDEWEB)
Chen, Yu-Yuan; Liu, Zhuan-Zhuan; Wan, Ren-Gang, E-mail: wrg@snnu.edu.cn
2017-04-25
We propose a scheme for realizing electromagnetically induced two-dimensional grating in a double-Λ system driven simultaneously by a coherent field and an incoherent pump field. In such an atomic configuration, the absorption is suppressed owing to the incoherent pumping process and the probe can be even amplified, while the refractivity is mainly attributed to the dynamically induced coherence. With the help of a standing-wave pattern coherent field, we obtain periodically modulated refractive index without or with gain, and therefore phase grating or gain-phase grating which diffracts a probe light into high-order direction efficiently can be formed in the medium via appropriate manipulation of the system parameters. The diffraction efficiency attainable by the present gratings can be controlled by tuning the coherent field intensity or the interaction length. Hence, the two-dimensional grating can be utilized as all-optical splitter or router in optical networking and communication. - Highlights: • Two-dimensional grating is coherently induced in four-level atoms. • Phase and gain-phase gratings are obtained assisted by incoherent pump. • The diffraction power is improved due to the enhanced refraction modulation. • The gratings can be utilized as multi-channel all-optical splitter and router.
MEDUSA - An overset grid flow solver for network-based parallel computer systems
Smith, Merritt H.; Pallis, Jani M.
1993-01-01
Continuing improvement in processing speed has made it feasible to solve the Reynolds-Averaged Navier-Stokes equations for simple three-dimensional flows on advanced workstations. Combining multiple workstations into a network-based heterogeneous parallel computer allows the application of programming principles learned on MIMD (Multiple Instruction Multiple Data) distributed memory parallel computers to the solution of larger problems. An overset-grid flow solution code has been developed which uses a cluster of workstations as a network-based parallel computer. Inter-process communication is provided by the Parallel Virtual Machine (PVM) software. Solution speed equivalent to one-third of a Cray-YMP processor has been achieved from a cluster of nine commonly used engineering workstation processors. Load imbalance and communication overhead are the principal impediments to parallel efficiency in this application.
Liu, Jun; Han, Jiuqiang; Lv, Hongqiang; Li, Bing
2015-04-16
With the continuing growth of highway construction and vehicle use expansion all over the world, highway vehicle traffic rule violation (TRV) detection has become more and more important so as to avoid traffic accidents and injuries in intelligent transportation systems (ITS) and vehicular ad hoc networks (VANETs). Since very few works have contributed to solve the TRV detection problem by moving vehicle measurements and surveillance devices, this paper develops a novel parallel ultrasonic sensor system that can be used to identify the TRV behavior of a host vehicle in real-time. Then a two-dimensional state method is proposed, utilizing the spacial state and time sequential states from the data of two parallel ultrasonic sensors to detect and count the highway vehicle violations. Finally, the theoretical TRV identification probability is analyzed, and actual experiments are conducted on different highway segments with various driving speeds, which indicates that the identification accuracy of the proposed method can reach about 90.97%.
Representing and computing regular languages on massively parallel networks
Energy Technology Data Exchange (ETDEWEB)
Miller, M.I.; O' Sullivan, J.A. (Electronic Systems and Research Lab., of Electrical Engineering, Washington Univ., St. Louis, MO (US)); Boysam, B. (Dept. of Electrical, Computer and Systems Engineering, Rensselaer Polytechnic Inst., Troy, NY (US)); Smith, K.R. (Dept. of Electrical Engineering, Southern Illinois Univ., Edwardsville, IL (US))
1991-01-01
This paper proposes a general method for incorporating rule-based constraints corresponding to regular languages into stochastic inference problems, thereby allowing for a unified representation of stochastic and syntactic pattern constraints. The authors' approach first established the formal connection of rules to Chomsky grammars, and generalizes the original work of Shannon on the encoding of rule-based channel sequences to Markov chains of maximum entropy. This maximum entropy probabilistic view leads to Gibb's representations with potentials which have their number of minima growing at precisely the exponential rate that the language of deterministically constrained sequences grow. These representations are coupled to stochastic diffusion algorithms, which sample the language-constrained sequences by visiting the energy minima according to the underlying Gibbs' probability law. The coupling to stochastic search methods yields the all-important practical result that fully parallel stochastic cellular automata may be derived to generate samples from the rule-based constraint sets. The production rules and neighborhood state structure of the language of sequences directly determines the necessary connection structures of the required parallel computing surface. Representations of this type have been mapped to the DAP-510 massively-parallel processor consisting of 1024 mesh-connected bit-serial processing elements for performing automated segmentation of electron-micrograph images.
Wired and Wireless Parallel Simulation of Fluid Flow Problem on Heterogeneous Network Cluster
Directory of Open Access Journals (Sweden)
Fariha Quratulain Baloch
2012-09-01
Full Text Available In this research Homogeneous and Heterogeneous networks will be analyzed using parallel processing technique for highly sophisticated research problem. During the analysis sample networks will be considered and QoS parameters will be observed using simulation for end-to-end services. Analysis of the wireless LAN system is carried out and its efficiency is measured compared to the wired systems, for the purpose of designing and implementing the parallel processing techniques used to solve general purpose engineering problems. The basic purpose for this research is to provide improved QoS in networks for research and academic learning.
MapReduce Based Parallel Neural Networks in Enabling Large Scale Machine Learning.
Liu, Yang; Yang, Jie; Huang, Yuan; Xu, Lixiong; Li, Siguang; Qi, Man
2015-01-01
Artificial neural networks (ANNs) have been widely used in pattern recognition and classification applications. However, ANNs are notably slow in computation especially when the size of data is large. Nowadays, big data has received a momentum from both industry and academia. To fulfill the potentials of ANNs for big data applications, the computation process must be speeded up. For this purpose, this paper parallelizes neural networks based on MapReduce, which has become a major computing model to facilitate data intensive applications. Three data intensive scenarios are considered in the parallelization process in terms of the volume of classification data, the size of the training data, and the number of neurons in the neural network. The performance of the parallelized neural networks is evaluated in an experimental MapReduce computer cluster from the aspects of accuracy in classification and efficiency in computation.
Line-plane broadcasting in a data communications network of a parallel computer
Archer, Charles J.; Berg, Jeremy E.; Blocksome, Michael A.; Smith, Brian E.
2010-11-23
Methods, apparatus, and products are disclosed for line-plane broadcasting in a data communications network of a parallel computer, the parallel computer comprising a plurality of compute nodes connected together through the network, the network optimized for point to point data communications and characterized by at least a first dimension, a second dimension, and a third dimension, that include: initiating, by a broadcasting compute node, a broadcast operation, including sending a message to all of the compute nodes along an axis of the first dimension for the network; sending, by each compute node along the axis of the first dimension, the message to all of the compute nodes along an axis of the second dimension for the network; and sending, by each compute node along the axis of the second dimension, the message to all of the compute nodes along an axis of the third dimension for the network.
Line-plane broadcasting in a data communications network of a parallel computer
Archer, Charles J.; Berg, Jeremy E.; Blocksome, Michael A.; Smith, Brian E.
2010-06-08
Methods, apparatus, and products are disclosed for line-plane broadcasting in a data communications network of a parallel computer, the parallel computer comprising a plurality of compute nodes connected together through the network, the network optimized for point to point data communications and characterized by at least a first dimension, a second dimension, and a third dimension, that include: initiating, by a broadcasting compute node, a broadcast operation, including sending a message to all of the compute nodes along an axis of the first dimension for the network; sending, by each compute node along the axis of the first dimension, the message to all of the compute nodes along an axis of the second dimension for the network; and sending, by each compute node along the axis of the second dimension, the message to all of the compute nodes along an axis of the third dimension for the network.
Weakly disordered two-dimensional Frenkel excitons
Boukahil, A.; Zettili, Nouredine
2004-03-01
We report the results of studies of the optical properties of weakly disordered two- dimensional Frenkel excitons in the Coherent Potential Approximation (CPA). An approximate complex Green's function for a square lattice with nearest neighbor interactions is used in the self-consistent equation to determine the coherent potential. It is shown that the Density of States is very much affected by the logarithmic singularities in the Green's function. Our CPA results are in excellent agreement with previous investigations by Schreiber and Toyozawa using the Monte Carlo simulation.
Two-dimensional photonic crystal surfactant detection.
Zhang, Jian-Tao; Smith, Natasha; Asher, Sanford A
2012-08-07
We developed a novel two-dimensional (2-D) crystalline colloidal array photonic crystal sensing material for the visual detection of amphiphilic molecules in water. A close-packed polystyrene 2-D array monolayer was embedded in a poly(N-isopropylacrylamide) (PNIPAAm)-based hydrogel film. These 2-D photonic crystals placed on a mirror show intense diffraction that enables them to be used for visual determination of analytes. Binding of surfactant molecules attaches ions to the sensor that swells the PNIPAAm-based hydrogel. The resulting increase in particle spacing red shifts the 2-D diffracted light. Incorporation of more hydrophobic monomers increases the sensitivity to surfactants.
Theory of two-dimensional transformations
Kanayama, Yutaka J.; Krahn, Gary W.
1998-01-01
The article of record may be found at http://dx.doi.org/10.1109/70.720359 Robotics and Automation, IEEE Transactions on This paper proposes a new "heterogeneous" two-dimensional (2D) transformation group ___ to solve motion analysis/planning problems in robotics. In this theory, we use a 3×1 matrix to represent a transformation as opposed to a 3×3 matrix in the homogeneous formulation. First, this theory is as capable as the homogeneous theory, Because of the minimal size, its implement...
Two-dimensional ranking of Wikipedia articles
Zhirov, A O; Shepelyansky, D L
2010-01-01
The Library of Babel, described by Jorge Luis Borges, stores an enormous amount of information. The Library exists {\\it ab aeterno}. Wikipedia, a free online encyclopaedia, becomes a modern analogue of such a Library. Information retrieval and ranking of Wikipedia articles become the challenge of modern society. We analyze the properties of two-dimensional ranking of all Wikipedia English articles and show that it gives their reliable classification with rich and nontrivial features. Detailed studies are done for countries, universities, personalities, physicists, chess players, Dow-Jones companies and other categories.
Mobility anisotropy of two-dimensional semiconductors
Lang, Haifeng; Liu, Zhirong
2016-01-01
The carrier mobility of anisotropic two-dimensional (2D) semiconductors under longitudinal acoustic (LA) phonon scattering was theoretically studied with the deformation potential theory. Based on Boltzmann equation with relaxation time approximation, an analytic formula of intrinsic anisotropic mobility was deduced, which shows that the influence of effective mass to the mobility anisotropy is larger than that of deformation potential constant and elastic modulus. Parameters were collected for various anisotropic 2D materials (black phosphorus, Hittorf's phosphorus, BC$_2$N, MXene, TiS$_3$, GeCH$_3$) to calculate their mobility anisotropy. It was revealed that the anisotropic ratio was overestimated in the past.
Sums of two-dimensional spectral triples
DEFF Research Database (Denmark)
Christensen, Erik; Ivan, Cristina
2007-01-01
construct a sum of two dimensional modules which reflects some aspects of the topological dimensions of the compact metric space, but this will only give the metric back approximately. At the end we make an explicit computation of the last module for the unit interval in. The metric is recovered exactly......, the Dixmier trace induces a multiple of the Lebesgue integral but the growth of the number of eigenvalues is different from the one found for the standard differential operator on the unit interval....
Binding energy of two-dimensional biexcitons
DEFF Research Database (Denmark)
Singh, Jai; Birkedal, Dan; Vadim, Lyssenko;
1996-01-01
Using a model structure for a two-dimensional (2D) biexciton confined in a quantum well, it is shown that the form of the Hamiltonian of the 2D biexciton reduces into that of an exciton. The binding energies and Bohr radii of a 2D biexciton in its various internal energy states are derived...... analytically using the fractional dimension approach. The ratio of the binding energy of a 2D biexciton to that of a 2D exciton is found to be 0.228, which agrees very well with the recent experimental value. The results of our approach are compared with those of earlier theories....
Dynamics of film. [two dimensional continua theory
Zak, M.
1979-01-01
The general theory of films as two-dimensional continua are elaborated upon. As physical realizations of such a model this paper examines: inextensible films, elastic films, and nets. The suggested dynamic equations have enabled us to find out the characteristic speeds of wave propagation of the invariants of external and internal geometry and formulate the criteria of instability of their shape. Also included herein is a detailed account of the equation describing the film motions beyond the limits of the shape stability accompanied by the formation of wrinkles. The theory is illustrated by examples.
Parallel importance sampling in conditional linear Gaussian networks
DEFF Research Database (Denmark)
Salmerón, Antonio; Ramos-López, Darío; Borchani, Hanen
2015-01-01
In this paper we analyse the problem of probabilistic inference in CLG networks when evidence comes in streams. In such situations, fast and scalable algorithms, able to provide accurate responses in a short time are required. We consider the instantiation of variational inference and importance ...
Two-dimensional gauge theoretic supergravities
Cangemi, D.; Leblanc, M.
1994-05-01
We investigate two-dimensional supergravity theories, which can be built from a topological and gauge invariant action defined on an ordinary surface. One is the N = 1 supersymmetric extension of the Jackiw-Teitelboim model presented by Chamseddine in a superspace formalism. We complement the proof of Montano, Aoaki and Sonnenschein that this extension is topological and gauge invariant, based on the graded de Sitter algebra. Not only do the equations of motion correspond to the supergravity ones and do gauge transformations encompass local supersymmetries, but we also identify the ∫-theory with the superfield formalism action written by Chamseddine. Next, we show that the N = 1 supersymmetric extension of string-inspired two-dimensional dilaton gravity put forward by Park and Strominger cannot be written as a ∫-theory. As an alternative, we propose two topological and gauge theories that are based on a graded extension of the extended Poincaré algebra and satisfy a vanishing-curvature condition. Both models are supersymmetric extensions of the string-inspired dilaton gravity.
Two-Dimensional Theory of Scientific Representation
Directory of Open Access Journals (Sweden)
A Yaghmaie
2013-03-01
Full Text Available Scientific representation is an interesting topic for philosophers of science, many of whom have recently explored it from different points of view. There are currently two competing approaches to the issue: cognitive and non-cognitive, and each of them claims its own merits over the other. This article tries to provide a hybrid theory of scientific representation, called Two-Dimensional Theory of Scientific Representation, which has the merits of the two accounts and is free of their shortcomings. To do this, we will argue that although scientific representation needs to use the notion of intentionality, such a notion is defined and realized in a simply structural form contrary to what cognitive approach says about intentionality. After a short introduction, the second part of the paper is devoted to introducing theories of scientific representation briefly. In the third part, the structural accounts of representation will be criticized. The next step is to introduce the two-dimensional theory which involves two key components: fixing and structural fitness. It will be argued that fitness is an objective and non-intentional relation, while fixing is intentional.
Two-dimensional shape memory graphene oxide
Chang, Zhenyue; Deng, Junkai; Chandrakumara, Ganaka G.; Yan, Wenyi; Liu, Jefferson Zhe
2016-06-01
Driven by the increasing demand for micro-/nano-technologies, stimuli-responsive shape memory materials at nanoscale have recently attracted great research interests. However, by reducing the size of conventional shape memory materials down to approximately nanometre range, the shape memory effect diminishes. Here, using density functional theory calculations, we report the discovery of a shape memory effect in a two-dimensional atomically thin graphene oxide crystal with ordered epoxy groups, namely C8O. A maximum recoverable strain of 14.5% is achieved as a result of reversible phase transition between two intrinsically stable phases. Our calculations conclude co-existence of the two stable phases in a coherent crystal lattice, giving rise to the possibility of constructing multiple temporary shapes in a single material, thus, enabling highly desirable programmability. With an atomic thickness, excellent shape memory mechanical properties and electric field stimulus, the discovery of a two-dimensional shape memory graphene oxide opens a path for the development of exceptional micro-/nano-electromechanical devices.
Directory of Open Access Journals (Sweden)
Wensheng Guo
Full Text Available In biological systems, the dynamic analysis method has gained increasing attention in the past decade. The Boolean network is the most common model of a genetic regulatory network. The interactions of activation and inhibition in the genetic regulatory network are modeled as a set of functions of the Boolean network, while the state transitions in the Boolean network reflect the dynamic property of a genetic regulatory network. A difficult problem for state transition analysis is the finding of attractors. In this paper, we modeled the genetic regulatory network as a Boolean network and proposed a solving algorithm to tackle the attractor finding problem. In the proposed algorithm, we partitioned the Boolean network into several blocks consisting of the strongly connected components according to their gradients, and defined the connection between blocks as decision node. Based on the solutions calculated on the decision nodes and using a satisfiability solving algorithm, we identified the attractors in the state transition graph of each block. The proposed algorithm is benchmarked on a variety of genetic regulatory networks. Compared with existing algorithms, it achieved similar performance on small test cases, and outperformed it on larger and more complex ones, which happens to be the trend of the modern genetic regulatory network. Furthermore, while the existing satisfiability-based algorithms cannot be parallelized due to their inherent algorithm design, the proposed algorithm exhibits a good scalability on parallel computing architectures.
Guo, Wensheng; Yang, Guowu; Wu, Wei; He, Lei; Sun, Mingyu
2014-01-01
In biological systems, the dynamic analysis method has gained increasing attention in the past decade. The Boolean network is the most common model of a genetic regulatory network. The interactions of activation and inhibition in the genetic regulatory network are modeled as a set of functions of the Boolean network, while the state transitions in the Boolean network reflect the dynamic property of a genetic regulatory network. A difficult problem for state transition analysis is the finding of attractors. In this paper, we modeled the genetic regulatory network as a Boolean network and proposed a solving algorithm to tackle the attractor finding problem. In the proposed algorithm, we partitioned the Boolean network into several blocks consisting of the strongly connected components according to their gradients, and defined the connection between blocks as decision node. Based on the solutions calculated on the decision nodes and using a satisfiability solving algorithm, we identified the attractors in the state transition graph of each block. The proposed algorithm is benchmarked on a variety of genetic regulatory networks. Compared with existing algorithms, it achieved similar performance on small test cases, and outperformed it on larger and more complex ones, which happens to be the trend of the modern genetic regulatory network. Furthermore, while the existing satisfiability-based algorithms cannot be parallelized due to their inherent algorithm design, the proposed algorithm exhibits a good scalability on parallel computing architectures.
Institute of Scientific and Technical Information of China (English)
XU Quan; TIAN Qiang
2007-01-01
Two-dimensional compact-like discrete breathers in discrete two-dimensional monatomic square lattices are investigated by discussing a generafized discrete two-dimensional monatomic model.It is proven that the twodimensional compact-like discrete breathers exist not only in two-dimensional soft Ф4 potentials but also in hard two-dimensional Ф4 potentials and pure two-dimensional K4 lattices.The measurements of the two-dimensional compact-like discrete breather cores in soft and hard two-dimensional Ф4 potential are determined by coupling parameter K4,while those in pure two-dimensional K4 lattices have no coupling with parameter K4.The stabilities of the two-dimensional compact-like discrete breathers correlate closely to the coupling parameter K4 and the boundary condition of lattices.
Lo, James Ting-Ho
2009-11-01
By a fundamental neural filtering theorem, a recurrent neural network with fixed weights is known to be capable of adapting to an uncertain environment. This letter reports some mathematical results on the performance of such adaptation for series-parallel identification of a dynamical system as compared with the performance of the best series-parallel identifier possible under the assumption that the precise value of the uncertain environmental process is given. In short, if an uncertain environmental process is observable (not necessarily constant) from the output of a dynamical system or constant (not necessarily observable), then a recurrent neural network exists as a series-parallel identifier of the dynamical system whose output approaches the output of an optimal series-parallel identifier using the environmental process as an additional input.
Energy Technology Data Exchange (ETDEWEB)
Kerr, J.P.
1992-01-01
The objective of this study was to determine the feasibility of using an Artificial Neural Network (ANN), in particular a backpropagation ANN, to improve the speed and quality of the reconstruction of three-dimensional SPECT (single photon emission computed tomography) images. In addition, since the processing elements (PE)s in each layer of an ANN are independent of each other, the speed and efficiency of the neural network architecture could be better optimized by implementing the ANN on a massively parallel computer. The specific goals of this research were: to implement a fully interconnected backpropagation neural network on a serial computer and a SIMD parallel computer, to identify any reduction in the time required to train these networks on the parallel machine versus the serial machine, to determine if these neural networks can learn to recognize SPECT data by training them on a section of an actual SPECT image, and to determine from the knowledge obtained in this research if full SPECT image reconstruction by an ANN implemented on a parallel computer is feasible both in time required to train the network, and in quality of the images reconstructed.
Energy Technology Data Exchange (ETDEWEB)
Kerr, J.P.
1992-12-31
The objective of this study was to determine the feasibility of using an Artificial Neural Network (ANN), in particular a backpropagation ANN, to improve the speed and quality of the reconstruction of three-dimensional SPECT (single photon emission computed tomography) images. In addition, since the processing elements (PE)s in each layer of an ANN are independent of each other, the speed and efficiency of the neural network architecture could be better optimized by implementing the ANN on a massively parallel computer. The specific goals of this research were: to implement a fully interconnected backpropagation neural network on a serial computer and a SIMD parallel computer, to identify any reduction in the time required to train these networks on the parallel machine versus the serial machine, to determine if these neural networks can learn to recognize SPECT data by training them on a section of an actual SPECT image, and to determine from the knowledge obtained in this research if full SPECT image reconstruction by an ANN implemented on a parallel computer is feasible both in time required to train the network, and in quality of the images reconstructed.
Fast Regular Circuits for Network-based Parallel Data Processing
Directory of Open Access Journals (Sweden)
SKLIAROVA, I.
2013-11-01
Full Text Available This paper is dedicated to the design, implementation, and evaluation of fast circuits executing operations that are frequently required in data processing which are: 1 discovering the maximum and minimum values in a given set of data; and 2 sorting data items. We found that minimizing the number of circuit components does not guarantee minimal hardware resources. This is because interconnections also influence the complexity significantly. Network-based circuits are often considered to be combinational. However, this does not mean that they are faster than sequential circuits solving the same problem because propagation delays can be considerable. We revised the existing network-based solutions and proposed regular circuits which provide a good compromise between hardware resources and performance.
Network Coding Parallelization Based on Matrix Operations for Multicore Architectures
DEFF Research Database (Denmark)
Wunderlich, Simon; Cabrera, Juan; Fitzek, Frank
2015-01-01
. Despite the fact that single core implementations show already comparable coding speeds with standard coding approaches, this paper pushes network coding to the next level by exploiting multicore architectures. The disruptive idea presented in the paper is to break with current software implementations...... and coding approaches and to adopt highly optimized dense matrix operations from the high performance computation field for network coding in order to increase the coding speed. The paper presents the novel coding approach for multicore architectures and shows coding speed gains on a commercial platform...... such as the Raspberry Pi2 with four cores in the order of up to one full magnitude. The speed increase gain is even higher than the number of cores of the Raspberry Pi2 since the newly introduced approach exploits the cache architecture way better than by-the-book matrix operations. Copyright © 2015 by the Institute...
Directory of Open Access Journals (Sweden)
Jilin Zhang
2017-01-01
Full Text Available With the development of the mobile systems, we gain a lot of benefits and convenience by leveraging mobile devices; at the same time, the information gathered by smartphones, such as location and environment, is also valuable for business to provide more intelligent services for customers. More and more machine learning methods have been used in the field of mobile information systems to study user behavior and classify usage patterns, especially convolutional neural network. With the increasing of model training parameters and data scale, the traditional single machine training method cannot meet the requirements of time complexity in practical application scenarios. The current training framework often uses simple data parallel or model parallel method to speed up the training process, which is why heterogeneous computing resources have not been fully utilized. To solve these problems, our paper proposes a delay synchronization convolutional neural network parallel strategy, which leverages the heterogeneous system. The strategy is based on both synchronous parallel and asynchronous parallel approaches; the model training process can reduce the dependence on the heterogeneous architecture in the premise of ensuring the model convergence, so the convolution neural network framework is more adaptive to different heterogeneous system environments. The experimental results show that the proposed delay synchronization strategy can achieve at least three times the speedup compared to the traditional data parallelism.
Two-dimensional random arrays for real time volumetric imaging
DEFF Research Database (Denmark)
Davidsen, Richard E.; Jensen, Jørgen Arendt; Smith, Stephen W.
1994-01-01
Two-dimensional arrays are necessary for a variety of ultrasonic imaging techniques, including elevation focusing, 2-D phase aberration correction, and real time volumetric imaging. In order to reduce system cost and complexity, sparse 2-D arrays have been considered with element geometries...... real time volumetric imaging system, which employs a wide transmit beam and receive mode parallel processing to increase image frame rate. Depth-of-field comparisons were made from simulated on-axis and off-axis beamplots at ranges from 30 to 160 mm for both coaxial and offset transmit and receive...... selected ad hoc, by algorithm, or by random process. Two random sparse array geometries and a sparse array with a Mills cross receive pattern were simulated and compared to a fully sampled aperture with the same overall dimensions. The sparse arrays were designed to the constraints of the Duke University...
Spin from defects in two-dimensional quantum field theory
Novak, Sebastian
2015-01-01
We build two-dimensional quantum field theories on spin surfaces starting from theories on oriented surfaces with networks of topological defect lines and junctions. The construction uses a combinatorial description of the spin structure in terms of a triangulation equipped with extra data. The amplitude for the spin surfaces is defined to be the amplitude for the underlying oriented surface together with a defect network dual to the triangulation. Independence of the triangulation and of the other choices follows if the line defect and junctions are obtained from a Delta-separable Frobenius algebra with involutive Nakayama automorphism in the monoidal category of topological defects. For rational conformal field theory we can give a more explicit description of the defect category, and we work out two examples related to free fermions in detail: the Ising model and the so(n) WZW model at level 1.
Integer-encoded massively parallel processing of fast-learning fuzzy ARTMAP neural networks
Bahr, Hubert A.; DeMara, Ronald F.; Georgiopoulos, Michael
1997-04-01
In this paper we develop techniques that are suitable for the parallel implementation of Fuzzy ARTMAP networks. Speedup and learning performance results are provided for execution on a DECmpp/Sx-1208 parallel processor consisting of a DEC RISC Workstation Front-End and MasPar MP-1 Back-End with 8,192 processors. Experiments of the parallel implementation were conducted on the Letters benchmark database developed by Frey and Slate. The results indicate a speedup on the order of 1000-fold which allows combined training and testing time of under four minutes.
Optimal excitation of two dimensional Holmboe instabilities
Constantinou, Navid C
2010-01-01
Highly stratified shear layers are rendered unstable even at high stratifications by Holmboe instabilities when the density stratification is concentrated in a small region of the shear layer. These instabilities may cause mixing in highly stratified environments. However these instabilities occur in tongues for a limited range of parameters. We perform Generalized Stability analysis of the two dimensional perturbation dynamics of an inviscid Boussinesq stratified shear layer and show that Holmboe instabilities at high Richardson numbers can be excited by their adjoints at amplitudes that are orders of magnitude larger than by introducing initially the unstable mode itself. We also determine the optimal growth that obtains for parameters for which there is no instability. We find that there is potential for large transient growth regardless of whether the background flow is exponentially stable or not and that the characteristic structure of the Holmboe instability asymptotically emerges for parameter values ...
Phonon hydrodynamics in two-dimensional materials.
Cepellotti, Andrea; Fugallo, Giorgia; Paulatto, Lorenzo; Lazzeri, Michele; Mauri, Francesco; Marzari, Nicola
2015-03-06
The conduction of heat in two dimensions displays a wealth of fascinating phenomena of key relevance to the scientific understanding and technological applications of graphene and related materials. Here, we use density-functional perturbation theory and an exact, variational solution of the Boltzmann transport equation to study fully from first-principles phonon transport and heat conductivity in graphene, boron nitride, molybdenum disulphide and the functionalized derivatives graphane and fluorographene. In all these materials, and at variance with typical three-dimensional solids, normal processes keep dominating over Umklapp scattering well-above cryogenic conditions, extending to room temperature and more. As a result, novel regimes emerge, with Poiseuille and Ziman hydrodynamics, hitherto typically confined to ultra-low temperatures, characterizing transport at ordinary conditions. Most remarkably, several of these two-dimensional materials admit wave-like heat diffusion, with second sound present at room temperature and above in graphene, boron nitride and graphane.
Probabilistic Universality in two-dimensional Dynamics
Lyubich, Mikhail
2011-01-01
In this paper we continue to explore infinitely renormalizable H\\'enon maps with small Jacobian. It was shown in [CLM] that contrary to the one-dimensional intuition, the Cantor attractor of such a map is non-rigid and the conjugacy with the one-dimensional Cantor attractor is at most 1/2-H\\"older. Another formulation of this phenomenon is that the scaling structure of the H\\'enon Cantor attractor differs from its one-dimensional counterpart. However, in this paper we prove that the weight assigned by the canonical invariant measure to these bad spots tends to zero on microscopic scales. This phenomenon is called {\\it Probabilistic Universality}. It implies, in particular, that the Hausdorff dimension of the canonical measure is universal. In this way, universality and rigidity phenomena of one-dimensional dynamics assume a probabilistic nature in the two-dimensional world.
Two-dimensional position sensitive neutron detector
Indian Academy of Sciences (India)
A M Shaikh; S S Desai; A K Patra
2004-08-01
A two-dimensional position sensitive neutron detector has been developed. The detector is a 3He + Kr filled multiwire proportional counter with charge division position readout and has a sensitive area of 345 mm × 345 mm, pixel size 5 mm × 5 mm, active depth 25 mm and is designed for efficiency of 70% for 4 Å neutrons. The detector is tested with 0.5 bar 3He + 1.5 bar krypton gas mixture in active chamber and 2 bar 4He in compensating chamber. The pulse height spectrum recorded at an anode potential of 2000 V shows energy resolution of ∼ 25% for the 764 keV peak. A spatial resolution of 8 mm × 6 mm is achieved. The detector is suitable for SANS studies in the range of 0.02–0.25 Å-1.
Two-dimensional heterostructures for energy storage
Pomerantseva, Ekaterina; Gogotsi, Yury
2017-07-01
Two-dimensional (2D) materials provide slit-shaped ion diffusion channels that enable fast movement of lithium and other ions. However, electronic conductivity, the number of intercalation sites, and stability during extended cycling are also crucial for building high-performance energy storage devices. While individual 2D materials, such as graphene, show some of the required properties, none of them can offer all properties needed to maximize energy density, power density, and cycle life. Here we argue that stacking different 2D materials into heterostructured architectures opens an opportunity to construct electrodes that would combine the advantages of the individual building blocks while eliminating the associated shortcomings. We discuss characteristics of common 2D materials and provide examples of 2D heterostructured electrodes that showed new phenomena leading to superior electrochemical performance. We also consider electrode fabrication approaches and finally outline future steps to create 2D heterostructured electrodes that could greatly expand current energy storage technologies.
Rationally synthesized two-dimensional polymers.
Colson, John W; Dichtel, William R
2013-06-01
Synthetic polymers exhibit diverse and useful properties and influence most aspects of modern life. Many polymerization methods provide linear or branched macromolecules, frequently with outstanding functional-group tolerance and molecular weight control. In contrast, extending polymerization strategies to two-dimensional periodic structures is in its infancy, and successful examples have emerged only recently through molecular framework, surface science and crystal engineering approaches. In this Review, we describe successful 2D polymerization strategies, as well as seminal research that inspired their development. These methods include the synthesis of 2D covalent organic frameworks as layered crystals and thin films, surface-mediated polymerization of polyfunctional monomers, and solid-state topochemical polymerizations. Early application targets of 2D polymers include gas separation and storage, optoelectronic devices and membranes, each of which might benefit from predictable long-range molecular organization inherent to this macromolecular architecture.
Janus Spectra in Two-Dimensional Flows
Liu, Chien-Chia; Cerbus, Rory T.; Chakraborty, Pinaki
2016-09-01
In large-scale atmospheric flows, soap-film flows, and other two-dimensional flows, the exponent of the turbulent energy spectra, α , may theoretically take either of two distinct values, 3 or 5 /3 , but measurements downstream of obstacles have invariably revealed α =3 . Here we report experiments on soap-film flows where downstream of obstacles there exists a sizable interval in which α transitions from 3 to 5 /3 for the streamwise fluctuations but remains equal to 3 for the transverse fluctuations, as if two mutually independent turbulent fields of disparate dynamics were concurrently active within the flow. This species of turbulent energy spectra, which we term the Janus spectra, has never been observed or predicted theoretically. Our results may open up new vistas in the study of turbulence and geophysical flows.
Local doping of two-dimensional materials
Wong, Dillon; Velasco, Jr, Jairo; Ju, Long; Kahn, Salman; Lee, Juwon; Germany, Chad E.; Zettl, Alexander K.; Wang, Feng; Crommie, Michael F.
2016-09-20
This disclosure provides systems, methods, and apparatus related to locally doping two-dimensional (2D) materials. In one aspect, an assembly including a substrate, a first insulator disposed on the substrate, a second insulator disposed on the first insulator, and a 2D material disposed on the second insulator is formed. A first voltage is applied between the 2D material and the substrate. With the first voltage applied between the 2D material and the substrate, a second voltage is applied between the 2D material and a probe positioned proximate the 2D material. The second voltage between the 2D material and the probe is removed. The first voltage between the 2D material and the substrate is removed. A portion of the 2D material proximate the probe when the second voltage was applied has a different electron density compared to a remainder of the 2D material.
Two-dimensional fourier transform spectrometer
Energy Technology Data Exchange (ETDEWEB)
DeFlores, Lauren; Tokmakoff, Andrei
2016-10-25
The present invention relates to a system and methods for acquiring two-dimensional Fourier transform (2D FT) spectra. Overlap of a collinear pulse pair and probe induce a molecular response which is collected by spectral dispersion of the signal modulated probe beam. Simultaneous collection of the molecular response, pulse timing and characteristics permit real time phasing and rapid acquisition of spectra. Full spectra are acquired as a function of pulse pair timings and numerically transformed to achieve the full frequency-frequency spectrum. This method demonstrates the ability to acquire information on molecular dynamics, couplings and structure in a simple apparatus. Multi-dimensional methods can be used for diagnostic and analytical measurements in the biological, biomedical, and chemical fields.
Two-dimensional fourier transform spectrometer
DeFlores, Lauren; Tokmakoff, Andrei
2013-09-03
The present invention relates to a system and methods for acquiring two-dimensional Fourier transform (2D FT) spectra. Overlap of a collinear pulse pair and probe induce a molecular response which is collected by spectral dispersion of the signal modulated probe beam. Simultaneous collection of the molecular response, pulse timing and characteristics permit real time phasing and rapid acquisition of spectra. Full spectra are acquired as a function of pulse pair timings and numerically transformed to achieve the full frequency-frequency spectrum. This method demonstrates the ability to acquire information on molecular dynamics, couplings and structure in a simple apparatus. Multi-dimensional methods can be used for diagnostic and analytical measurements in the biological, biomedical, and chemical fields.
FACE RECOGNITION USING TWO DIMENSIONAL LAPLACIAN EIGENMAP
Institute of Scientific and Technical Information of China (English)
Chen Jiangfeng; Yuan Baozong; Pei Bingnan
2008-01-01
Recently,some research efforts have shown that face images possibly reside on a nonlinear sub-manifold. Though Laplacianfaces method considered the manifold structures of the face images,it has limits to solve face recognition problem. This paper proposes a new feature extraction method,Two Dimensional Laplacian EigenMap (2DLEM),which especially considers the manifold structures of the face images,and extracts the proper features from face image matrix directly by using a linear transformation. As opposed to Laplacianfaces,2DLEM extracts features directly from 2D images without a vectorization preprocessing. To test 2DLEM and evaluate its performance,a series of ex-periments are performed on the ORL database and the Yale database. Moreover,several experiments are performed to compare the performance of three 2D methods. The experiments show that 2DLEM achieves the best performance.
Mourelle, L.; Ferreira, R. E.; Nedjah, N.
2010-10-01
The aim of the work described in this article is to investigate migration strategies for the execution of parallel genetic algorithms in a multi-processor system-on-chip (MPSoC). Some multimedia and internet applications for wireless communications are using genetic algorithms and can benefit from the advantages provided by parallel processing on MPSoCs. In order to run such algorithms, we use a network-on-chip platform, which provides the interconnection network required for the communication between processors. Two migration strategies are employed in order to analyse the speedup and efficiency each one can provide, considering the communication costs they require.
Equivalency of two-dimensional algebras
Energy Technology Data Exchange (ETDEWEB)
Santos, Gildemar Carneiro dos; Pomponet Filho, Balbino Jose S. [Universidade Federal da Bahia (UFBA), BA (Brazil). Inst. de Fisica
2011-07-01
Full text: Let us consider a vector z = xi + yj over the field of real numbers, whose basis (i,j) satisfy a given algebra. Any property of this algebra will be reflected in any function of z, so we can state that the knowledge of the properties of an algebra leads to more general conclusions than the knowledge of the properties of a function. However structural properties of an algebra do not change when this algebra suffers a linear transformation, though the structural constants defining this algebra do change. We say that two algebras are equivalent to each other whenever they are related by a linear transformation. In this case, we have found that some relations between the structural constants are sufficient to recognize whether or not an algebra is equivalent to another. In spite that the basis transform linearly, the structural constants change like a third order tensor, but some combinations of these tensors result in a linear transformation, allowing to write the entries of the transformation matrix as function of the structural constants. Eventually, a systematic way to find the transformation matrix between these equivalent algebras is obtained. In this sense, we have performed the thorough classification of associative commutative two-dimensional algebras, and find that even non-division algebra may be helpful in solving non-linear dynamic systems. The Mandelbrot set was used to have a pictorial view of each algebra, since equivalent algebras result in the same pattern. Presently we have succeeded in classifying some non-associative two-dimensional algebras, a task more difficult than for associative one. (author)
de Ladurantaye, Vincent; Lavoie, Jean; Bergeron, Jocelyn; Parenteau, Maxime; Lu, Huizhong; Pichevar, Ramin; Rouat, Jean
2012-02-01
A parallel implementation of a large spiking neural network is proposed and evaluated. The neural network implements the binding by synchrony process using the Oscillatory Dynamic Link Matcher (ODLM). Scalability, speed and performance are compared for 2 implementations: Message Passing Interface (MPI) and Compute Unified Device Architecture (CUDA) running on clusters of multicore supercomputers and NVIDIA graphical processing units respectively. A global spiking list that represents at each instant the state of the neural network is described. This list indexes each neuron that fires during the current simulation time so that the influence of their spikes are simultaneously processed on all computing units. Our implementation shows a good scalability for very large networks. A complex and large spiking neural network has been implemented in parallel with success, thus paving the road towards real-life applications based on networks of spiking neurons. MPI offers a better scalability than CUDA, while the CUDA implementation on a GeForce GTX 285 gives the best cost to performance ratio. When running the neural network on the GTX 285, the processing speed is comparable to the MPI implementation on RQCHP's Mammouth parallel with 64 notes (128 cores).
Energy Technology Data Exchange (ETDEWEB)
Madduri, Kamesh; Bader, David A.
2009-02-15
Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data streams from socioeconomic interactions, social networking web sites, communication traffic, and scientific computing can be intuitively modeled as graphs. We present the first study of novel high-performance combinatorial techniques for analyzing large-scale information networks, encapsulating dynamic interaction data in the order of billions of entities. We present new data structures to represent dynamic interaction networks, and discuss algorithms for processing parallel insertions and deletions of edges in small-world networks. With these new approaches, we achieve an average performance rate of 25 million structural updates per second and a parallel speedup of nearly28 on a 64-way Sun UltraSPARC T2 multicore processor, for insertions and deletions to a small-world network of 33.5 million vertices and 268 million edges. We also design parallel implementations of fundamental dynamic graph kernels related to connectivity and centrality queries. Our implementations are freely distributed as part of the open-source SNAP (Small-world Network Analysis and Partitioning) complex network analysis framework.
Networked Just-in-time Control of a Parallel Mechanism with Pneumatic Linear Drives
Directory of Open Access Journals (Sweden)
Takahiro Kosaki
2014-01-01
Full Text Available Parallel mechanisms have advantages such as high power, high stiffness, and high precision due to the parallel arrangement of actuators, in comparison with typical serial mechanisms. In the present study, we used pneumatic linear drives to develop a linearly actuated parallel mechanism, in which the actuators fixed on a base enable high degrees of freedom of motion of an end-effector. Using pneumatic linear drives in the realization of such a parallel mechanism leads to lightweight, compact, and low-cost construction. For the parallel mechanism prototype, we construct a control system based on our previously proposed networked Just-In-Time (JIT control strategy, which is based on client-server architecture. In this system, the parallel mechanism is connected to a client computer, and a server computer has a database that stores the control data for all the pneumatic actuators to drive the parallel mechanism. The client online accesses the database, receives data from the server, and feeds control commands to the pneumatic actuators. Experiments were performed to investigate the performance of the developed parallel mechanism system.
MapReduce Based Parallel Neural Networks in Enabling Large Scale Machine Learning
Yang Liu; Jie Yang; Yuan Huang; Lixiong Xu; Siguang Li; Man Qi
2015-01-01
Artificial neural networks (ANNs) have been widely used in pattern recognition and classification applications. However, ANNs are notably slow in computation especially when the size of data is large. Nowadays, big data has received a momentum from both industry and academia. To fulfill the potentials of ANNs for big data applications, the computation process must be speeded up. For this purpose, this paper parallelizes neural networks based on MapReduce, which has become a major computing mo...
Modulator and VCSEL-MSM smart pixels for parallel pipeline networking and signal processing
Chen, C.-H.; Hoanca, Bogdan; Kuznia, C. B.; Pansatiankul, Dhawat E.; Zhang, Liping; Sawchuk, Alexander A.
1999-07-01
TRANslucent Smart Pixel Array (TRANSPAR) systems perform high performance parallel pipeline networking and signal processing based on optical propagation of 3D data packets. The TRANSPAR smart pixel devices use either self-electro- optic effect GaAs multiple quantum well modulators or CMOS- VCSEL-MSM (CMOS-Vertical Cavity Surface Emitting Laser- Metal-Semiconductor-Metal) technology. The data packets transfer among high throughput photonic network nodes using multiple access/collision detection or token-ring protocols.
Negative Dispersion of Lattice Waves in a Two-Dimensional Yukawa System
Institute of Scientific and Technical Information of China (English)
刘艳红; 刘斌; 杨思泽; 王龙
2002-01-01
Collective motion modes existing in a two-dimensional Yukawa system are investigated by molecular dynamics simulation. The dispersion relations of transverse and longitudinal lattice waves obtained for hexagonal lattice are in agreement with the theoretical results. The negative dispersion of the parallel longitudinal wave is demonstrated by the simulation, and is explained by a physical model.
Two-dimensional acoustic particle velocity sensors based on a crossing wires topology
Pjetri, O.
2016-01-01
This thesis describes the design and realization of two-dimensional acoustic particle velocity sensors based on thermal convection. The sensors are of the order of 1 mm×1 mm and consist of two crossing wires with each wire sensing the acoustic particle velocity in the direction parallel to it. Their
Signatures of beta-sheet secondary structures in linear and two-dimensional infrared spectroscopy
Cheatum, CM; Tokmakoff, A; Knoester, J
2004-01-01
Using idealized models for parallel and antiparallel beta sheets, we calculate the linear and two-dimensional infrared spectra of the amide I vibration as a function of size and secondary structure. The model assumes transition-dipole coupling between the amide I oscillators in the sheet and account
Visualizing Network Traffic to Understand the Performance of Massively Parallel Simulations
Landge, A. G.
2012-12-01
The performance of massively parallel applications is often heavily impacted by the cost of communication among compute nodes. However, determining how to best use the network is a formidable task, made challenging by the ever increasing size and complexity of modern supercomputers. This paper applies visualization techniques to aid parallel application developers in understanding the network activity by enabling a detailed exploration of the flow of packets through the hardware interconnect. In order to visualize this large and complex data, we employ two linked views of the hardware network. The first is a 2D view, that represents the network structure as one of several simplified planar projections. This view is designed to allow a user to easily identify trends and patterns in the network traffic. The second is a 3D view that augments the 2D view by preserving the physical network topology and providing a context that is familiar to the application developers. Using the massively parallel multi-physics code pF3D as a case study, we demonstrate that our tool provides valuable insight that we use to explain and optimize pF3D-s performance on an IBM Blue Gene/P system. © 1995-2012 IEEE.
On numerical evaluation of two-dimensional phase integrals
DEFF Research Database (Denmark)
Lessow, H.; Rusch, W.; Schjær-Jacobsen, Hans
1975-01-01
The relative advantages of several common numerical integration algorithms used in computing two-dimensional phase integrals are evaluated.......The relative advantages of several common numerical integration algorithms used in computing two-dimensional phase integrals are evaluated....
Two-Dimensional Impact Reconstruction Method for Rail Defect Inspection
Directory of Open Access Journals (Sweden)
Jie Zhao
2014-01-01
Full Text Available The safety of train operating is seriously menaced by the rail defects, so it is of great significance to inspect rail defects dynamically while the train is operating. This paper presents a two-dimensional impact reconstruction method to realize the on-line inspection of rail defects. The proposed method utilizes preprocessing technology to convert time domain vertical vibration signals acquired by wireless sensor network to space signals. The modern time-frequency analysis method is improved to reconstruct the obtained multisensor information. Then, the image fusion processing technology based on spectrum threshold processing and node color labeling is proposed to reduce the noise, and blank the periodic impact signal caused by rail joints and locomotive running gear. This method can convert the aperiodic impact signals caused by rail defects to partial periodic impact signals, and locate the rail defects. An application indicates that the two-dimensional impact reconstruction method could display the impact caused by rail defects obviously, and is an effective on-line rail defects inspection method.
Shifman, M A; Windemuth, A; Schulten, K; Miller, P L
1992-04-01
Molecular dynamics simulations investigate local and global motion in molecules. Several parallel computing approaches have been taken to attack the most computationally expensive phase of molecular simulations, the evaluation of long range interactions. This paper reviews these approaches and develops a straightforward but effective algorithm using the machine-independent parallel programming language, Linda. The algorithm was run both on a shared memory parallel computer and on a network of high performance Unix workstations. Performance benchmarks were performed on both systems using two proteins. This algorithm offers a portable cost-effective alternative for molecular dynamics simulations. In view of the increasing numbers of networked workstations, this approach could help make molecular dynamics simulations more easily accessible to the research community.
Par@Graph - a parallel toolbox for the construction and analysis of large complex climate networks
Tantet, A.J.J.
2015-01-01
In this paper, we present Par@Graph, a software toolbox to reconstruct and analyze complex climate networks having a large number of nodes (up to at least 106) and edges (up to at least 1012). The key innovation is an efficient set of parallel software tools designed to leverage the inherited hybrid
DEFF Research Database (Denmark)
Jacobsen, Susanne; Nesic, Ljiljana; Petersen, Marianne Kjerstine;
2001-01-01
Analyzing a gliadin extract by matrix assisted laser desorption/ionization-time of flight-mass spectrometry (MALDI- TOF-MS) combined with an artificial neural network (ANN) is a suitable method for identification of wheat varieties. However, the ANN can not distinguish between all different wheat...
Adaptive control of parallel manipulators via fuzzy-neural network algorithm
Institute of Scientific and Technical Information of China (English)
Dachang ZHU; Yuefa FANG
2007-01-01
This paper considers adaptive control of parallel manipulators combined with fuzzy-neural network algorithms (FNNA). With this algorithm, the robustness is guaranteed by the adaptive control law and the parametric uncertainties are eliminated. FNNA is used to handle model uncertainties and external disturbances. In the proposed control scheme,we consider modifying the weight of fuzzy rules and present these rules to a MIMO system of parallel manipulators with more than three degrees-of-freedom (DoF). The algorithm has the advantage of not requiring the inverse of the Jacobian matrix especially for the low DoF parallel manipulators. The validity of the control scheme is shown through numerical simulations of a 6-RPS parallel manipulator with three DoF.
Optimization on a Network-based Parallel Computer System for Supersonic Laminar Wing Design
Garcia, Joseph A.; Cheung, Samson; Holst, Terry L. (Technical Monitor)
1995-01-01
A set of Computational Fluid Dynamics (CFD) routines and flow transition prediction tools are integrated into a network based parallel numerical optimization routine. Through this optimization routine, the design of a 2-D airfoil and an infinitely swept wing will be studied in order to advance the design cycle capability of supersonic laminar flow wings. The goal of advancing supersonic laminar flow wing design is achieved by wisely choosing the design variables used in the optimization routine. The design variables are represented by the theory of Fourier series and potential theory. These theories, combined with the parallel CFD flow routines and flow transition prediction tools, provide a design space for a global optimal point to be searched. Finally, the parallel optimization routine enables gradient evaluations to be performed in a fast and parallel fashion.
Perspective: Two-dimensional resonance Raman spectroscopy
Molesky, Brian P.; Guo, Zhenkun; Cheshire, Thomas P.; Moran, Andrew M.
2016-11-01
Two-dimensional resonance Raman (2DRR) spectroscopy has been developed for studies of photochemical reaction mechanisms and structural heterogeneity in complex systems. The 2DRR method can leverage electronic resonance enhancement to selectively probe chromophores embedded in complex environments (e.g., a cofactor in a protein). In addition, correlations between the two dimensions of the 2DRR spectrum reveal information that is not available in traditional Raman techniques. For example, distributions of reactant and product geometries can be correlated in systems that undergo chemical reactions on the femtosecond time scale. Structural heterogeneity in an ensemble may also be reflected in the 2D spectroscopic line shapes of both reactive and non-reactive systems. In this perspective article, these capabilities of 2DRR spectroscopy are discussed in the context of recent applications to the photodissociation reactions of triiodide and myoglobin. We also address key differences between the signal generation mechanisms for 2DRR and off-resonant 2D Raman spectroscopies. Most notably, it has been shown that these two techniques are subject to a tradeoff between sensitivity to anharmonicity and susceptibility to artifacts. Overall, recent experimental developments and applications of the 2DRR method suggest great potential for the future of the technique.
Janus spectra in two-dimensional flows
Liu, Chien-Chia; Chakraborty, Pinaki
2016-01-01
In theory, large-scale atmospheric flows, soap-film flows and other two-dimensional flows may host two distinct types of turbulent energy spectra---in one, $\\alpha$, the spectral exponent of velocity fluctuations, equals $3$ and the fluctuations are dissipated at the small scales, and in the other, $\\alpha=5/3$ and the fluctuations are dissipated at the large scales---but measurements downstream of obstacles have invariably revealed $\\alpha = 3$. Here we report experiments on soap-film flows where downstream of obstacles there exists a sizable interval in which $\\alpha$ has transitioned from $3$ to $5/3$ for the streamwise fluctuations but remains equal to $3$ for the transverse fluctuations, as if two mutually independent turbulent fields of disparate dynamics were concurrently active within the flow. This species of turbulent energy spectra, which we term the Janus spectra, has never been observed or predicted theoretically. Our results may open up new vistas in the study of turbulence and geophysical flows...
Comparative Two-Dimensional Fluorescence Gel Electrophoresis.
Ackermann, Doreen; König, Simone
2018-01-01
Two-dimensional comparative fluorescence gel electrophoresis (CoFGE) uses an internal standard to increase the reproducibility of coordinate assignment for protein spots visualized on 2D polyacrylamide gels. This is particularly important for samples, which need to be compared without the availability of replicates and thus cannot be studied using differential gel electrophoresis (DIGE). CoFGE corrects for gel-to-gel variability by co-running with the sample proteome a standardized marker grid of 80-100 nodes, which is formed by a set of purified proteins. Differentiation of reference and analyte is possible by the use of two fluorescent dyes. Variations in the y-dimension (molecular weight) are corrected by the marker grid. For the optional control of the x-dimension (pI), azo dyes can be used. Experiments are possible in both vertical and horizontal (h) electrophoresis devices, but hCoFGE is much easier to perform. For data analysis, commercial software capable of warping can be adapted.
Two-dimensional hexagonal semiconductors beyond graphene
Nguyen, Bich Ha; Hieu Nguyen, Van
2016-12-01
The rapid and successful development of the research on graphene and graphene-based nanostructures has been substantially enlarged to include many other two-dimensional hexagonal semiconductors (THS): phosphorene, silicene, germanene, hexagonal boron nitride (h-BN) and transition metal dichalcogenides (TMDCs) such as MoS2, MoSe2, WS2, WSe2 as well as the van der Waals heterostructures of various THSs (including graphene). The present article is a review of recent works on THSs beyond graphene and van der Waals heterostructures composed of different pairs of all THSs. One among the priorities of new THSs compared to graphene is the presence of a non-vanishing energy bandgap which opened up the ability to fabricate a large number of electronic, optoelectronic and photonic devices on the basis of these new materials and their van der Waals heterostructures. Moreover, a significant progress in the research on TMDCs was the discovery of valley degree of freedom. The results of research on valley degree of freedom and the development of a new technology based on valley degree of freedom-valleytronics are also presented. Thus the scientific contents of the basic research and practical applications os THSs are very rich and extremely promising.
Two-Dimensional Phononic Crystals: Disorder Matters.
Wagner, Markus R; Graczykowski, Bartlomiej; Reparaz, Juan Sebastian; El Sachat, Alexandros; Sledzinska, Marianna; Alzina, Francesc; Sotomayor Torres, Clivia M
2016-09-14
The design and fabrication of phononic crystals (PnCs) hold the key to control the propagation of heat and sound at the nanoscale. However, there is a lack of experimental studies addressing the impact of order/disorder on the phononic properties of PnCs. Here, we present a comparative investigation of the influence of disorder on the hypersonic and thermal properties of two-dimensional PnCs. PnCs of ordered and disordered lattices are fabricated of circular holes with equal filling fractions in free-standing Si membranes. Ultrafast pump and probe spectroscopy (asynchronous optical sampling) and Raman thermometry based on a novel two-laser approach are used to study the phononic properties in the gigahertz (GHz) and terahertz (THz) regime, respectively. Finite element method simulations of the phonon dispersion relation and three-dimensional displacement fields furthermore enable the unique identification of the different hypersonic vibrations. The increase of surface roughness and the introduction of short-range disorder are shown to modify the phonon dispersion and phonon coherence in the hypersonic (GHz) range without affecting the room-temperature thermal conductivity. On the basis of these findings, we suggest a criteria for predicting phonon coherence as a function of roughness and disorder.
Two-dimensional topological photonic systems
Sun, Xiao-Chen; He, Cheng; Liu, Xiao-Ping; Lu, Ming-Hui; Zhu, Shi-Ning; Chen, Yan-Feng
2017-09-01
The topological phase of matter, originally proposed and first demonstrated in fermionic electronic systems, has drawn considerable research attention in the past decades due to its robust transport of edge states and its potential with respect to future quantum information, communication, and computation. Recently, searching for such a unique material phase in bosonic systems has become a hot research topic worldwide. So far, many bosonic topological models and methods for realizing them have been discovered in photonic systems, acoustic systems, mechanical systems, etc. These discoveries have certainly yielded vast opportunities in designing material phases and related properties in the topological domain. In this review, we first focus on some of the representative photonic topological models and employ the underlying Dirac model to analyze the edge states and geometric phase. On the basis of these models, three common types of two-dimensional topological photonic systems are discussed: 1) photonic quantum Hall effect with broken time-reversal symmetry; 2) photonic topological insulator and the associated pseudo-time-reversal symmetry-protected mechanism; 3) time/space periodically modulated photonic Floquet topological insulator. Finally, we provide a summary and extension of this emerging field, including a brief introduction to the Weyl point in three-dimensional systems.
Radiation effects on two-dimensional materials
Energy Technology Data Exchange (ETDEWEB)
Walker, R.C. II; Robinson, J.A. [Department of Materials Science, Penn State, University Park, PA (United States); Center for Two-Dimensional Layered Materials, Penn State, University Park, PA (United States); Shi, T. [Department of Mechanical and Nuclear Engineering, Penn State, University Park, PA (United States); Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, MI (United States); Silva, E.C. [GlobalFoundries, Malta, NY (United States); Jovanovic, I. [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, MI (United States)
2016-12-15
The effects of electromagnetic and particle irradiation on two-dimensional materials (2DMs) are discussed in this review. Radiation creates defects that impact the structure and electronic performance of materials. Determining the impact of these defects is important for developing 2DM-based devices for use in high-radiation environments, such as space or nuclear reactors. As such, most experimental studies have been focused on determining total ionizing dose damage to 2DMs and devices. Total dose experiments using X-rays, gamma rays, electrons, protons, and heavy ions are summarized in this review. We briefly discuss the possibility of investigating single event effects in 2DMs based on initial ion beam irradiation experiments and the development of 2DM-based integrated circuits. Additionally, beneficial uses of irradiation such as ion implantation to dope materials or electron-beam and helium-beam etching to shape materials have begun to be used on 2DMs and are reviewed as well. For non-ionizing radiation, such as low-energy photons, we review the literature on 2DM-based photo-detection from terahertz to UV. The majority of photo-detecting devices operate in the visible and UV range, and for this reason they are the focus of this review. However, we review the progress in developing 2DMs for detecting infrared and terahertz radiation. (copyright 2016 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
Photodetectors based on two dimensional materials
Zheng, Lou; Zhongzhu, Liang; Guozhen, Shen
2016-09-01
Two-dimensional (2D) materials with unique properties have received a great deal of attention in recent years. This family of materials has rapidly established themselves as intriguing building blocks for versatile nanoelectronic devices that offer promising potential for use in next generation optoelectronics, such as photodetectors. Furthermore, their optoelectronic performance can be adjusted by varying the number of layers. They have demonstrated excellent light absorption, enabling ultrafast and ultrasensitive detection of light in photodetectors, especially in their single-layer structure. Moreover, due to their atomic thickness, outstanding mechanical flexibility, and large breaking strength, these materials have been of great interest for use in flexible devices and strain engineering. Toward that end, several kinds of photodetectors based on 2D materials have been reported. Here, we present a review of the state-of-the-art in photodetectors based on graphene and other 2D materials, such as the graphene, transition metal dichalcogenides, and so on. Project supported by the National Natural Science Foundation of China (Nos. 61377033, 61574132, 61504136) and the State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences.
Asymptotics for Two-dimensional Atoms
DEFF Research Database (Denmark)
Nam, Phan Thanh; Portmann, Fabian; Solovej, Jan Philip
2012-01-01
We prove that the ground state energy of an atom confined to two dimensions with an infinitely heavy nucleus of charge $Z>0$ and $N$ quantum electrons of charge -1 is $E(N,Z)=-{1/2}Z^2\\ln Z+(E^{\\TF}(\\lambda)+{1/2}c^{\\rm H})Z^2+o(Z^2)$ when $Z\\to \\infty$ and $N/Z\\to \\lambda$, where $E^{\\TF}(\\lambd......We prove that the ground state energy of an atom confined to two dimensions with an infinitely heavy nucleus of charge $Z>0$ and $N$ quantum electrons of charge -1 is $E(N,Z)=-{1/2}Z^2\\ln Z+(E^{\\TF}(\\lambda)+{1/2}c^{\\rm H})Z^2+o(Z^2)$ when $Z\\to \\infty$ and $N/Z\\to \\lambda$, where $E......^{\\TF}(\\lambda)$ is given by a Thomas-Fermi type variational problem and $c^{\\rm H}\\approx -2.2339$ is an explicit constant. We also show that the radius of a two-dimensional neutral atom is unbounded when $Z\\to \\infty$, which is contrary to the expected behavior of three-dimensional atoms....
Predicting Two-Dimensional Silicon Carbide Monolayers.
Shi, Zhiming; Zhang, Zhuhua; Kutana, Alex; Yakobson, Boris I
2015-10-27
Intrinsic semimetallicity of graphene and silicene largely limits their applications in functional devices. Mixing carbon and silicon atoms to form two-dimensional (2D) silicon carbide (SixC1-x) sheets is promising to overcome this issue. Using first-principles calculations combined with the cluster expansion method, we perform a comprehensive study on the thermodynamic stability and electronic properties of 2D SixC1-x monolayers with 0 ≤ x ≤ 1. Upon varying the silicon concentration, the 2D SixC1-x presents two distinct structural phases, a homogeneous phase with well dispersed Si (or C) atoms and an in-plane hybrid phase rich in SiC domains. While the in-plane hybrid structure shows uniform semiconducting properties with widely tunable band gap from 0 to 2.87 eV due to quantum confinement effect imposed by the SiC domains, the homogeneous structures can be semiconducting or remain semimetallic depending on a superlattice vector which dictates whether the sublattice symmetry is topologically broken. Moreover, we reveal a universal rule for describing the electronic properties of the homogeneous SixC1-x structures. These findings suggest that the 2D SixC1-x monolayers may present a new "family" of 2D materials, with a rich variety of properties for applications in electronics and optoelectronics.
Parallel NGO networks for HIV control: risks and opportunities for NGO contracting.
Zaidi, Shehla; Gul, Xaher; Nishtar, Noureen Aleem
2012-12-27
Policy measures for preventive and promotive services are increasingly reliant on contracting of NGOs. Contracting is a neo-liberal response relying on open market competition for service delivery tenders. In contracting of health services a common assumption is a monolithic NGO market. A case study of HIV control in Pakistan shows that in reality the NGO market comprises of parallel NGO networks having widely different service packages, approaches and agendas. These parallel networks had evolved over time due to vertical policy agendas. Contracting of NGOs for provision of HIV services was faced with uneven capacities and turf rivalries across both NGO networks. At the same time contracting helped NGO providers belonging to different clusters to move towards standardized service delivery for HIV prevention. Market based measures such as contracting need to be accompanied with wider policy measures that facilitate in bringing NGOs groups to a shared understanding of health issues and responses.
Compact triplexer in two-dimensional hexagonal lattice photonic crystals
Institute of Scientific and Technical Information of China (English)
Hongliang Ren; Jianping Ma; Hao Wen; Yali Qin; Zhefu Wu; Weisheng Hu; Chun Jiang; Yaohui Jin
2011-01-01
We design a contpact triplexer based on two-dimensional (2D) hexagonal lattice photonic crystals (PCs). A folded directional coupler (FDC) is introduced in the triplexer beside the point-defect micro-cavities and line-defect waveguides. Because of the reflection feedback of the FDC, high channel drop efficiency can be realized and a compact size with the order of micrometers can be maintained. The proposed device is analyzed using the plane wave expansion method, and its transmission characteristics are calculated using the finites-difference time-domain method. The footprint of the triplexer is about 12× 9 μm, and its extinction ratios are less than -20 dB for 1310 nm, approximately -20 dB for 1490 nm, and under -4O dB for 1550 nm, making it a potentially essential device ii future fiber-to-the-home networks.%@@ We design a compact triplexer based on two-dimensional (2D) hexagonal lattice photonic crystals (PCs).A folded directional coupler (FDC) is introduced in the triplexer beside the point-defect micro-cavities and line-defect waveguides.Because of the reflection feedback of the FDC, high channel drop efficiency can be realized and a compact size with the order of micrometers can be maintained.The proposed device is analyzed using the plane wave expansion method, and its transmission characteristics are calculated using the finite-difference time-domain method.The footprint of the triplexer is about 12×9 μm, and its extinction ratios are less than -20 dB for 1310 nm, approximately -20 dB for 1490 nm, and under -40 dB for 1550 nm, making it a potentially essential device in future fiber-to-the-home networks.
Two-dimensional materials and their prospects in transistor electronics.
Schwierz, F; Pezoldt, J; Granzner, R
2015-05-14
During the past decade, two-dimensional materials have attracted incredible interest from the electronic device community. The first two-dimensional material studied in detail was graphene and, since 2007, it has intensively been explored as a material for electronic devices, in particular, transistors. While graphene transistors are still on the agenda, researchers have extended their work to two-dimensional materials beyond graphene and the number of two-dimensional materials under examination has literally exploded recently. Meanwhile several hundreds of different two-dimensional materials are known, a substantial part of them is considered useful for transistors, and experimental transistors with channels of different two-dimensional materials have been demonstrated. In spite of the rapid progress in the field, the prospects of two-dimensional transistors still remain vague and optimistic opinions face rather reserved assessments. The intention of the present paper is to shed more light on the merits and drawbacks of two-dimensional materials for transistor electronics and to add a few more facets to the ongoing discussion on the prospects of two-dimensional transistors. To this end, we compose a wish list of properties for a good transistor channel material and examine to what extent the two-dimensional materials fulfill the criteria of the list. The state-of-the-art two-dimensional transistors are reviewed and a balanced view of both the pros and cons of these devices is provided.
Dispatching packets on a global combining network of a parallel computer
Almasi, Gheorghe; Archer, Charles J.
2011-07-19
Methods, apparatus, and products are disclosed for dispatching packets on a global combining network of a parallel computer comprising a plurality of nodes connected for data communications using the network capable of performing collective operations and point to point operations that include: receiving, by an origin system messaging module on an origin node from an origin application messaging module on the origin node, a storage identifier and an operation identifier, the storage identifier specifying storage containing an application message for transmission to a target node, and the operation identifier specifying a message passing operation; packetizing, by the origin system messaging module, the application message into network packets for transmission to the target node, each network packet specifying the operation identifier and an operation type for the message passing operation specified by the operation identifier; and transmitting, by the origin system messaging module, the network packets to the target node.
Parallelizing Backpropagation Neural Network Using MapReduce and Cascading Model.
Liu, Yang; Jing, Weizhe; Xu, Lixiong
2016-01-01
Artificial Neural Network (ANN) is a widely used algorithm in pattern recognition, classification, and prediction fields. Among a number of neural networks, backpropagation neural network (BPNN) has become the most famous one due to its remarkable function approximation ability. However, a standard BPNN frequently employs a large number of sum and sigmoid calculations, which may result in low efficiency in dealing with large volume of data. Therefore to parallelize BPNN using distributed computing technologies is an effective way to improve the algorithm performance in terms of efficiency. However, traditional parallelization may lead to accuracy loss. Although several complements have been done, it is still difficult to find out a compromise between efficiency and precision. This paper presents a parallelized BPNN based on MapReduce computing model which supplies advanced features including fault tolerance, data replication, and load balancing. And also to improve the algorithm performance in terms of precision, this paper creates a cascading model based classification approach, which helps to refine the classification results. The experimental results indicate that the presented parallelized BPNN is able to offer high efficiency whilst maintaining excellent precision in enabling large-scale machine learning.
Parallelizing Backpropagation Neural Network Using MapReduce and Cascading Model
Directory of Open Access Journals (Sweden)
Yang Liu
2016-01-01
Full Text Available Artificial Neural Network (ANN is a widely used algorithm in pattern recognition, classification, and prediction fields. Among a number of neural networks, backpropagation neural network (BPNN has become the most famous one due to its remarkable function approximation ability. However, a standard BPNN frequently employs a large number of sum and sigmoid calculations, which may result in low efficiency in dealing with large volume of data. Therefore to parallelize BPNN using distributed computing technologies is an effective way to improve the algorithm performance in terms of efficiency. However, traditional parallelization may lead to accuracy loss. Although several complements have been done, it is still difficult to find out a compromise between efficiency and precision. This paper presents a parallelized BPNN based on MapReduce computing model which supplies advanced features including fault tolerance, data replication, and load balancing. And also to improve the algorithm performance in terms of precision, this paper creates a cascading model based classification approach, which helps to refine the classification results. The experimental results indicate that the presented parallelized BPNN is able to offer high efficiency whilst maintaining excellent precision in enabling large-scale machine learning.
Further two-dimensional code development for Stirling space engine components
Ibrahim, Mounir; Tew, Roy C.; Dudenhoefer, James E.
1990-01-01
The development of multidimensional models of Stirling engine components is described. Two-dimensional parallel plate models of an engine regenerator and a cooler were used to study heat transfer under conditions of laminar, incompressible oscillating flow. Substantial differences in the nature of the temperature variations in time over the cycle were observed for the cooler as contrasted with the regenerator. When the two-dimensional cooler model was used to calculate a heat transfer coefficient, it yields a very different result from that calculated using steady-flow correlations. Simulation results for the regenerator and the cooler are presented.
Directory of Open Access Journals (Sweden)
Francesco Gregoretti
Full Text Available The reverse engineering of gene regulatory networks using gene expression profile data has become crucial to gain novel biological knowledge. Large amounts of data that need to be analyzed are currently being produced due to advances in microarray technologies. Using current reverse engineering algorithms to analyze large data sets can be very computational-intensive. These emerging computational requirements can be met using parallel computing techniques. It has been shown that the Network Identification by multiple Regression (NIR algorithm performs better than the other ready-to-use reverse engineering software. However it cannot be used with large networks with thousands of nodes--as is the case in biological networks--due to the high time and space complexity. In this work we overcome this limitation by designing and developing a parallel version of the NIR algorithm. The new implementation of the algorithm reaches a very good accuracy even for large gene networks, improving our understanding of the gene regulatory networks that is crucial for a wide range of biomedical applications.
Minimum-Cost Node-Disjoint Steiner Trees in Series-Parallel Networks
Directory of Open Access Journals (Sweden)
Sunil Chopra
1996-01-01
, is a Steiner tree spanning Ni for i = 1, ..., r and VNi ∩ VNj = for i ≠ j. The edge-disjoint version of this problem is known to be NP-hard for t. series-parallel graphs (see Rlchey and Parker [5]. In this paper we give a O(n5 algorithm for finding a minimum-cost node-disjoint family of Steiner trees in series-parallel networks. Our algorithm can be extended to k-trees and is polynomial for fixed k.
Parallel Distributed Implementation of Truss Optimization on a Local Area Network
Institute of Scientific and Technical Information of China (English)
唐天兵; 韦凌云; 严毅; 韦日钰
2004-01-01
A two-level optimization method for the design of complex truss and parallel distributed implementation on a LAN is presented using parallel virtual machine (PVM) for Win 32 as message passing between PCs. The volumes of truss are minimized by decomposing the original optimization problem into a number of bar optimization problems executed concurrently and a coordinate optimization problem, subject to constraints on nodal displacements, and stresses, buckling and crippling of bars, etc. The system sensitivity analysis that derives the partial derivatives of displacements and stresses with respect to areas are also performed in parallel so as to shorten the analysis time. The convergence and the speedup performances as well as parallel computing efficiency of the method are investigated by the optimization examples of a 52-bar planar truss and a 3 126-bar three-dimensional truss. The results show that the ideal speedup is obtained in the cases of 2 PCs for the 3 126-bar space truss optimization, while no speedup is observed for the 52-bar truss. It is concluded that ( 1 ) the parallel distributed algorithm proposed is efficient on the PC-based LAN for the coarsegrained large optimization problem; (2) to get a high speedup, the problem granularity should match with the network granularity;and (3) the larger the problem size is, the higher the parallel efficiency is.
Parallel implementation of backpropagation neural networks on a heterogeneous array of transputers.
Foo, S K; Saratchandran, P; Sundararajan, N
1997-01-01
This paper analyzes parallel implementation of the backpropagation training algorithm on a heterogeneous transputer network (i.e., transputers of different speed and memory) connected in a pipelined ring topology. Training-set parallelism is employed as the parallelizing paradigm for the backpropagation algorithm. It is shown through analysis that finding the optimal allocation of the training patterns amongst the processors to minimize the time for a training epoch is a mixed integer programming problem. Using mixed integer programming optimal pattern allocations for heterogeneous processor networks having a mixture of T805-20 (20 MHz) and T805-25 (25 MHz) transputers are theoretically found for two benchmark problems. The time for an epoch corresponding to the optimal pattern allocations is then obtained experimentally for the benchmark problems from the T805-20, TS805-25 heterogeneous networks. A Monte Carlo simulation study is carried out to statistically verify the optimality of the epoch time obtained from the mixed integer programming based allocations. In this study pattern allocations are randomly generated and the corresponding time for an epoch is experimentally obtained from the heterogeneous network. The mean and standard deviation for the epoch times from the random allocations are then compared with the optimal epoch time. The results show the optimal epoch time to be always lower than the mean epoch times by more than three standard deviations (3sigma) for all the sample sizes used in the study thus giving validity to the theoretical analysis.
Ultrafast two dimensional infrared chemical exchange spectroscopy
Fayer, Michael
2011-03-01
The method of ultrafast two dimensional infrared (2D IR) vibrational echo spectroscopy is described. Three ultrashort IR pulses tuned to the frequencies of the vibrational transitions of interest are directed into the sample. The interaction of these pulses with the molecular vibrational oscillators produces a polarization that gives rise to a fourth pulse, the vibrational echo. The vibrational echo pulse is combined with another pulse, the local oscillator, for heterodyne detection of the signal. For fixed time between the second and third pulses, the waiting time, the first pulse is scanned. Two Fourier transforms of the data yield a 2D IR spectrum. The waiting time is increased, and another spectrum is obtained. The change in the 2D IR spectra with increased waiting time provides information on the time evolution of the structure of the molecular system under observation. In a 2D IR chemical exchange experiment, two species A and B, are undergoing chemical exchange. A's are turning into B's, and B's are turning into A's, but the overall concentrations of the species are not changing. The kinetics of the chemical exchange on the ground electronic state under thermal equilibrium conditions can be obtained 2D IR spectroscopy. A vibration that has a different frequency for the two species is monitored. At very short time, there will be two peaks on the diagonal of the 2D IR spectrum, one for A and one for B. As the waiting time is increased, chemical exchange causes off-diagonal peaks to grow in. The time dependence of the growth of these off-diagonal peaks gives the chemical exchange rate. The method is applied to organic solute-solvent complex formation, orientational isomerization about a carbon-carbon single bond, migration of a hydrogen bond from one position on a molecule to another, protein structural substate interconversion, and water hydrogen bond switching between ions and water molecules. This work was supported by the Air Force Office of Scientific
Molecular assembly on two-dimensional materials
Kumar, Avijit; Banerjee, Kaustuv; Liljeroth, Peter
2017-02-01
Molecular self-assembly is a well-known technique to create highly functional nanostructures on surfaces. Self-assembly on two-dimensional (2D) materials is a developing field driven by the interest in functionalization of 2D materials in order to tune their electronic properties. This has resulted in the discovery of several rich and interesting phenomena. Here, we review this progress with an emphasis on the electronic properties of the adsorbates and the substrate in well-defined systems, as unveiled by scanning tunneling microscopy. The review covers three aspects of the self-assembly. The first one focuses on non-covalent self-assembly dealing with site-selectivity due to inherent moiré pattern present on 2D materials grown on substrates. We also see that modification of intermolecular interactions and molecule–substrate interactions influences the assembly drastically and that 2D materials can also be used as a platform to carry out covalent and metal-coordinated assembly. The second part deals with the electronic properties of molecules adsorbed on 2D materials. By virtue of being inert and possessing low density of states near the Fermi level, 2D materials decouple molecules electronically from the underlying metal substrate and allow high-resolution spectroscopy and imaging of molecular orbitals. The moiré pattern on the 2D materials causes site-selective gating and charging of molecules in some cases. The last section covers the effects of self-assembled, acceptor and donor type, organic molecules on the electronic properties of graphene as revealed by spectroscopy and electrical transport measurements. Non-covalent functionalization of 2D materials has already been applied for their application as catalysts and sensors. With the current surge of activity on building van der Waals heterostructures from atomically thin crystals, molecular self-assembly has the potential to add an extra level of flexibility and functionality for applications ranging
A nanoporous two-dimensional polymer by single-crystal-to-single-crystal photopolymerization.
Kissel, Patrick; Murray, Daniel J; Wulftange, William J; Catalano, Vincent J; King, Benjamin T
2014-09-01
In contrast to the wide number and variety of available synthetic routes to conventional linear polymers, the synthesis of two-dimensional polymers and unambiguous proof of their structure remains a challenge. Two-dimensional polymers-single-layered polymers that form a tiling network in exactly two dimensions-have potential for use in nanoporous membranes and other applications. Here, we report the preparation of a fluorinated hydrocarbon two-dimensional polymer that can be exfoliated into single sheets, and its characterization by high-resolution single-crystal X-ray diffraction analysis. The procedure involves three steps: preorganization in a lamellar crystal of a rigid monomer bearing three photoreactive arms, photopolymerization of the crystalline monomers by [4 + 4] cycloaddition, and isolation of individual two-dimensional polymer sheets. This polymer is a molecularly thin (~1 nm) material that combines precisely defined monodisperse pores of ~9 Å with a high pore density of 3.3 × 10(13) pores cm(-2). Atomic-resolution single-crystal X-ray structures of the monomer, an intermediate dimer and the final crystalline two-dimensional polymer were obtained and prove the single-crystal-to-single-crystal nature and molecular precision of the two-dimensional photopolymerization.
Parallel Approach for Time Series Analysis with General Regression Neural Networks
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J.C. Cuevas-Tello
2012-04-01
Full Text Available The accuracy on time delay estimation given pairs of irregularly sampled time series is of great relevance in astrophysics. However the computational time is also important because the study of large data sets is needed. Besides introducing a new approach for time delay estimation, this paper presents a parallel approach to obtain a fast algorithm for time delay estimation. The neural network architecture that we use is general Regression Neural Network (GRNN. For the parallel approach, we use Message Passing Interface (MPI on a beowulf-type cluster and on a Cray supercomputer and we also use the Compute Unified Device Architecture (CUDA™ language on Graphics Processing Units (GPUs. We demonstrate that, with our approach, fast algorithms can be obtained for time delay estimation on large data sets with the same accuracy as state-of-the-art methods.
Locating hardware faults in a data communications network of a parallel computer
Archer, Charles J.; Megerian, Mark G.; Ratterman, Joseph D.; Smith, Brian E.
2010-01-12
Hardware faults location in a data communications network of a parallel computer. Such a parallel computer includes a plurality of compute nodes and a data communications network that couples the compute nodes for data communications and organizes the compute node as a tree. Locating hardware faults includes identifying a next compute node as a parent node and a root of a parent test tree, identifying for each child compute node of the parent node a child test tree having the child compute node as root, running a same test suite on the parent test tree and each child test tree, and identifying the parent compute node as having a defective link connected from the parent compute node to a child compute node if the test suite fails on the parent test tree and succeeds on all the child test trees.
Real-Time Control Strategy of Elman Neural Network for the Parallel Hybrid Electric Vehicle
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Ruijun Liu
2014-01-01
Full Text Available Through researching the instantaneous control strategy and Elman neural network, the paper established equivalent fuel consumption functions under the charging and discharging conditions of power batteries, deduced the optimal control objective function of instantaneous equivalent consumption, established the instantaneous optimal control model, and designs the Elman neural network controller. Based on the ADVISOR 2002 platform, the instantaneous optimal control strategy and the Elman neural network control strategy were simulated on a parallel HEV. The simulation results were analyzed in the end. The contribution of the paper is that the trained Elman neural network control strategy can reduce the simulation time by 96% and improve the real-time performance of energy control, which also ensures the good performance of power and fuel economy.
Parallel sub-neural network system for hand vein pattern recognition
Institute of Scientific and Technical Information of China (English)
Xue Yuan; Yongduan Song; Xueye Wei
2011-01-01
@@ A hand vein authentication system in which the identity of an individual can be readily confirmed upon gripping a handle is proposed.This recognition method incorporates infrared light-emitting diode (LED) onto a door handle and sets a charge-coupled device (CCD) camera on the other side of the hand.It builds on fuzzy c-means clustering and parallel neural networks (NNs); moreover, it is expected to solve the pattern recognition problem in large-scale databases using NNs due to its self-learning and parallel processing capabilities and by effectively incorporating training patterns.The experimental results validate the efficiency of the proposed algorithm.%A hand vein authentication system in which the identity of an individual can be readily confirmed upon gripping a handle is proposed. This recognition method incorporates infrared light-emitting diode (LED)onto a door handle and sets a charge-coupled device (CCD) camera on the other side of the hand. It builds on fuzzy c-means clustering and parallel neural networks (NNs); moreover, it is expected to solve the pattern recognition problem in large-scale databases using NNs due to its self-learning and parallel processing capabilities and by effectively incorporating training patterns. The experimental results validatethe efficiency of the proposed algorithm.
Parallel computation with molecular-motor-propelled agents in nanofabricated networks.
Nicolau, Dan V; Lard, Mercy; Korten, Till; van Delft, Falco C M J M; Persson, Malin; Bengtsson, Elina; Månsson, Alf; Diez, Stefan; Linke, Heiner; Nicolau, Dan V
2016-03-01
The combinatorial nature of many important mathematical problems, including nondeterministic-polynomial-time (NP)-complete problems, places a severe limitation on the problem size that can be solved with conventional, sequentially operating electronic computers. There have been significant efforts in conceiving parallel-computation approaches in the past, for example: DNA computation, quantum computation, and microfluidics-based computation. However, these approaches have not proven, so far, to be scalable and practical from a fabrication and operational perspective. Here, we report the foundations of an alternative parallel-computation system in which a given combinatorial problem is encoded into a graphical, modular network that is embedded in a nanofabricated planar device. Exploring the network in a parallel fashion using a large number of independent, molecular-motor-propelled agents then solves the mathematical problem. This approach uses orders of magnitude less energy than conventional computers, thus addressing issues related to power consumption and heat dissipation. We provide a proof-of-concept demonstration of such a device by solving, in a parallel fashion, the small instance {2, 5, 9} of the subset sum problem, which is a benchmark NP-complete problem. Finally, we discuss the technical advances necessary to make our system scalable with presently available technology.
An SPN analysis method for parallel scheduling in Ad Hoc networks
Institute of Scientific and Technical Information of China (English)
盛琳阳; 徐文超; 贾世楼
2004-01-01
In this paper, a new analytic method for modeling and evaluating mobile ad hoc networks (MANET)is proposed. Petri nets technique is introduced into MANET and a packet-flow parallel scheduling scheme is presented using Stochastic Petri Nets (SPN). The flowing of tokens is used in graphics mode to characterize dynamical features of sharing a single wireless channel. Through SPN reachability analysis and isomorphic continuous time Markov process equations, some network parameters, such as channel efficiency, one-hop transmission delay etc. , can be obtained. Compared with conventional performance evaluation methods, the above parameters are mathematical expressions instead of test results from a simulator.
Parallel and Mixed Hardware Implementation of Artificial Neuron Network on the FPGA Platform
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ATIBI Mohamed
2014-10-01
Full Text Available Most applications in different fields (automotive, robotics, medical… take advantage of the proven performance by artificial neural networks to solve their most complex problems. The architecture chosen for implementation is the multilayer perceptron that uses retro propagation as a learning algorithm. This article presents modular hardware implementation of multilayer perceptron architecture of artificial neuron network ‘ANN’, in the FPGA platform according to two models (parallel and mixed hardware implementation, and the comparison between these two implementations in terms of hardware resources and execution time. The two implementations are based on the proposed module of a formal neuron with the sigmoid activation function.
Parallel Processing for Large-scale Fault Tree in Wireless Sensor Networks
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Xinyan Wang
2013-05-01
Full Text Available Wireless sensor networks (WSN covers many kinds of technologies, such as technology of sensor, embedded system, wireless communication, etc. WSN is different from the traditional networks in size, communication distance and energy-constrained so as to develop new topology, protocol, quality of service (QoS, and so on. In order to solve the problem of self-organizing in the topology, this paper proposes a novel strategy which is based on communication delay between sensors. Firstly, the gateway selects some boundary nodes to connect. Secondly, the boundary nodes choose inner nodes. The rest may be deduced by analogy. Finally, a net-tree topology with multi-path routing is developed. The analyses of the topology show that net-tree has strong ability in self-organizing and extensible. However, the scale of system is usually very large and complexity so that it is hard to detect the failure nodes when the nodes fail. To solve the greater challenge, the paper proposes to adopt fault tree analysis. Fault tree is a commonly used method to analyze the reliability of a network or system. Based on the fault tree analysis, a parallel computing algorithm is represented to these faults in the net-tree. Firstly, two models for parallel processing are came up and we focus on the parallel processing algorithm based on the cut sets. Then, the speedup ratio is studied. Compare with the serial algorithm, the results of the experiment shows that the efficiency has been greatly improved.
The convolution theorem for two-dimensional continuous wavelet transform
Institute of Scientific and Technical Information of China (English)
ZHANG CHI
2013-01-01
In this paper , application of two -dimensional continuous wavelet transform to image processes is studied. We first show that the convolution and correlation of two continuous wavelets satisfy the required admissibility and regularity conditions ,and then we derive the convolution and correlation theorem for two-dimensional continuous wavelet transform. Finally, we present numerical example showing the usefulness of applying the convolution theorem for two -dimensional continuous wavelet transform to perform image restoration in the presence of additive noise.
Tilted Two-Dimensional Array Multifocus Confocal Raman Microspectroscopy.
Yabumoto, Sohshi; Hamaguchi, Hiro-O
2017-07-18
A simple and efficient two-dimensional multifocus confocal Raman microspectroscopy featuring the tilted-array technique is demonstrated. Raman scattering from a 4 × 4 square foci array passing through a 4 × 4 confocal pinhole array is tilted with a periscope. The tilted array of Raman scattering signals is dispersed by an imaging spectrograph onto a CCD detector, giving 16 independent Raman spectra formed as 16 bands with different heights on the sensor. Use of a state-of-the-art imaging spectrograph enables high-precision wavenumber duplicability of the 16 spectra. This high duplicability makes the simultaneously obtained spectra endurable for multivariate spectral analyses, which is demonstrated by a singular value decomposition analysis for Raman spectra of liquid indene. Although the present implementation attains only 16 measurement points, the number of points can be extended to larger than 100 without any technical leaps. Limit of parallelization depends on the interval of measurement points as well as the performance of the optical system. Criteria for finding the maximum feasible number are discussed.
Lattice gas dynamics: application to driven vortices in two dimensional superconductors.
Gotcheva, Violeta; Wang, Albert T J; Teitel, S
2004-06-18
A continuous time Monte Carlo lattice gas dynamics is developed to model driven steady states of vortices in two dimensional superconducting networks. Dramatic differences are found when compared to a simpler Metropolis dynamics. Subtle finite size effects are found at low temperature, with a moving smectic that becomes unstable to an anisotropic liquid on sufficiently large length scales.
A new asynchronous parallel algorithm for inferring large-scale gene regulatory networks.
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Xiangyun Xiao
Full Text Available The reconstruction of gene regulatory networks (GRNs from high-throughput experimental data has been considered one of the most important issues in systems biology research. With the development of high-throughput technology and the complexity of biological problems, we need to reconstruct GRNs that contain thousands of genes. However, when many existing algorithms are used to handle these large-scale problems, they will encounter two important issues: low accuracy and high computational cost. To overcome these difficulties, the main goal of this study is to design an effective parallel algorithm to infer large-scale GRNs based on high-performance parallel computing environments. In this study, we proposed a novel asynchronous parallel framework to improve the accuracy and lower the time complexity of large-scale GRN inference by combining splitting technology and ordinary differential equation (ODE-based optimization. The presented algorithm uses the sparsity and modularity of GRNs to split whole large-scale GRNs into many small-scale modular subnetworks. Through the ODE-based optimization of all subnetworks in parallel and their asynchronous communications, we can easily obtain the parameters of the whole network. To test the performance of the proposed approach, we used well-known benchmark datasets from Dialogue for Reverse Engineering Assessments and Methods challenge (DREAM, experimentally determined GRN of Escherichia coli and one published dataset that contains more than 10 thousand genes to compare the proposed approach with several popular algorithms on the same high-performance computing environments in terms of both accuracy and time complexity. The numerical results demonstrate that our parallel algorithm exhibits obvious superiority in inferring large-scale GRNs.
MapReduce Based Parallel Bayesian Network for Manufacturing Quality Control
Zheng, Mao-Kuan; Ming, Xin-Guo; Zhang, Xian-Yu; Li, Guo-Ming
2017-09-01
Increasing complexity of industrial products and manufacturing processes have challenged conventional statistics based quality management approaches in the circumstances of dynamic production. A Bayesian network and big data analytics integrated approach for manufacturing process quality analysis and control is proposed. Based on Hadoop distributed architecture and MapReduce parallel computing model, big volume and variety quality related data generated during the manufacturing process could be dealt with. Artificial intelligent algorithms, including Bayesian network learning, classification and reasoning, are embedded into the Reduce process. Relying on the ability of the Bayesian network in dealing with dynamic and uncertain problem and the parallel computing power of MapReduce, Bayesian network of impact factors on quality are built based on prior probability distribution and modified with posterior probability distribution. A case study on hull segment manufacturing precision management for ship and offshore platform building shows that computing speed accelerates almost directly proportionally to the increase of computing nodes. It is also proved that the proposed model is feasible for locating and reasoning of root causes, forecasting of manufacturing outcome, and intelligent decision for precision problem solving. The integration of bigdata analytics and BN method offers a whole new perspective in manufacturing quality control.
A two-dimensional mathematical model of percutaneous drug absorption
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Kubota K
2004-06-01
Full Text Available Abstract Background When a drug is applied on the skin surface, the concentration of the drug accumulated in the skin and the amount of the drug eliminated into the blood vessel depend on the value of a parameter, r. The values of r depend on the amount of diffusion and the normalized skin-capillary clearence. It is defined as the ratio of the steady-state drug concentration at the skin-capillary boundary to that at the skin-surface in one-dimensional models. The present paper studies the effect of the parameter values, when the region of contact of the skin with the drug, is a line segment on the skin surface. Methods Though a simple one-dimensional model is often useful to describe percutaneous drug absorption, it may be better represented by multi-dimensional models. A two-dimensional mathematical model is developed for percutaneous absorption of a drug, which may be used when the diffusion of the drug in the direction parallel to the skin surface must be examined, as well as in the direction into the skin, examined in one-dimensional models. This model consists of a linear second-order parabolic equation with appropriate initial conditions and boundary conditions. These boundary conditions are of Dirichlet type, Neumann type or Robin type. A finite-difference method which maintains second-order accuracy in space along the boundary, is developed to solve the parabolic equation. Extrapolation in time is applied to improve the accuracy in time. Solution of the parabolic equation gives the concentration of the drug in the skin at a given time. Results Simulation of the numerical methods described is carried out with various values of the parameter r. The illustrations are given in the form of figures. Conclusion Based on the values of r, conclusions are drawn about (1 the flow rate of the drug, (2 the flux and the cumulative amount of drug eliminated into the receptor cell, (3 the steady-state value of the flux, (4 the time to reach the steady
Cao, Jianfang; Cui, Hongyan; Shi, Hao; Jiao, Lijuan
2016-01-01
A back-propagation (BP) neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To improve the classification accuracy and runtime efficiency of the BP neural network algorithm, we proposed a parallel design and realization method for a particle swarm optimization (PSO)-optimized BP neural network based on MapReduce on the Hadoop platform using both the PSO algorithm and a parallel design. The PSO algorithm was used to optimize the BP neural network's initial weights and thresholds and improve the accuracy of the classification algorithm. The MapReduce parallel programming model was utilized to achieve parallel processing of the BP algorithm, thereby solving the problems of hardware and communication overhead when the BP neural network addresses big data. Datasets on 5 different scales were constructed using the scene image library from the SUN Database. The classification accuracy of the parallel PSO-BP neural network algorithm is approximately 92%, and the system efficiency is approximately 0.85, which presents obvious advantages when processing big data. The algorithm proposed in this study demonstrated both higher classification accuracy and improved time efficiency, which represents a significant improvement obtained from applying parallel processing to an intelligent algorithm on big data.
Directory of Open Access Journals (Sweden)
Jianfang Cao
Full Text Available A back-propagation (BP neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To improve the classification accuracy and runtime efficiency of the BP neural network algorithm, we proposed a parallel design and realization method for a particle swarm optimization (PSO-optimized BP neural network based on MapReduce on the Hadoop platform using both the PSO algorithm and a parallel design. The PSO algorithm was used to optimize the BP neural network's initial weights and thresholds and improve the accuracy of the classification algorithm. The MapReduce parallel programming model was utilized to achieve parallel processing of the BP algorithm, thereby solving the problems of hardware and communication overhead when the BP neural network addresses big data. Datasets on 5 different scales were constructed using the scene image library from the SUN Database. The classification accuracy of the parallel PSO-BP neural network algorithm is approximately 92%, and the system efficiency is approximately 0.85, which presents obvious advantages when processing big data. The algorithm proposed in this study demonstrated both higher classification accuracy and improved time efficiency, which represents a significant improvement obtained from applying parallel processing to an intelligent algorithm on big data.
Au, Jennifer; Choi, Jungik; Jones, Shawn W; Venkataramanan, Keerthi P; Antoniewicz, Maciek R
2014-11-01
In this work, we provide new insights into the metabolism of Clostridium acetobutylicum ATCC 824 obtained using a systematic approach for quantifying fluxes based on parallel labeling experiments and (13)C-metabolic flux analysis ((13)C-MFA). Here, cells were grown in parallel cultures with [1-(13)C]glucose and [U-(13)C]glucose as tracers and (13)C-MFA was used to quantify intracellular metabolic fluxes. Several metabolic network models were compared: an initial model based on current knowledge, and extended network models that included additional reactions that improved the fits of experimental data. While the initial network model did not produce a statistically acceptable fit of (13)C-labeling data, an extended network model with five additional reactions was able to fit all data with 292 redundant measurements. The model was subsequently trimmed to produce a minimal network model of C. acetobutylicum for (13)C-MFA, which could still reproduce all of the experimental data. The flux results provided valuable new insights into the metabolism of C. acetobutylicum. First, we found that TCA cycle was effectively incomplete, as there was no measurable flux between α-ketoglutarate and succinyl-CoA, succinate and fumarate, and malate and oxaloacetate. Second, an active pathway was identified from pyruvate to fumarate via aspartate. Third, we found that isoleucine was produced exclusively through the citramalate synthase pathway in C. acetobutylicum and that CAC3174 was likely responsible for citramalate synthase activity. These model predictions were confirmed in several follow-up tracer experiments. The validated metabolic network model established in this study can be used in future investigations for unbiased (13)C-flux measurements in C. acetobutylicum. Copyright © 2014 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.
The Chandrasekhar's Equation for Two-Dimensional Hypothetical White Dwarfs
De, Sanchari
2014-01-01
In this article we have extended the original work of Chandrasekhar on the structure of white dwarfs to the two-dimensional case. Although such two-dimensional stellar objects are hypothetical in nature, we strongly believe that the work presented in this article may be prescribed as Master of Science level class problem for the students in physics.
Beginning Introductory Physics with Two-Dimensional Motion
Huggins, Elisha
2009-01-01
During the session on "Introductory College Physics Textbooks" at the 2007 Summer Meeting of the AAPT, there was a brief discussion about whether introductory physics should begin with one-dimensional motion or two-dimensional motion. Here we present the case that by starting with two-dimensional motion, we are able to introduce a considerable…
Spatiotemporal surface solitons in two-dimensional photonic lattices.
Mihalache, Dumitru; Mazilu, Dumitru; Lederer, Falk; Kivshar, Yuri S
2007-11-01
We analyze spatiotemporal light localization in truncated two-dimensional photonic lattices and demonstrate the existence of two-dimensional surface light bullets localized in the lattice corners or the edges. We study the families of the spatiotemporal surface solitons and their properties such as bistability and compare them with the modes located deep inside the photonic lattice.
Explorative data analysis of two-dimensional electrophoresis gels
DEFF Research Database (Denmark)
Schultz, J.; Gottlieb, D.M.; Petersen, Marianne Kjerstine;
2004-01-01
Methods for classification of two-dimensional (2-DE) electrophoresis gels based on multivariate data analysis are demonstrated. Two-dimensional gels of ten wheat varieties are analyzed and it is demonstrated how to classify the wheat varieties in two qualities and a method for initial screening...
Mechanics of Apparent Horizon in Two Dimensional Dilaton Gravity
Cai, Rong-Gen
2016-01-01
In this article, we give a definition of apparent horizon in a two dimensional general dilaton gravity theory. With this definition, we construct the mechanics of the apparent horizon by introducing a quasi-local energy of the theory. Our discussion generalizes the apparent horizons mechanics in general spherically symmetric spactimes in four or higher dimensions to the two dimensional dilaton gravity case.
Topological aspect of disclinations in two-dimensional crystals
Institute of Scientific and Technical Information of China (English)
Qi Wei-Kai; Zhu Tao; Chen Yong; Ren Ji-Rong
2009-01-01
By using topological current theory, this paper studies the inner topological structure of disclinations during the melting of two-dimensional systems. From two-dimensional elasticity theory, it finds that there are topological currents for topological defects in homogeneous equation. The evolution of disclinations is studied, and the branch conditions for generating, annihilating, crossing, splitting and merging of disclinations are given.
Parallel ICA identifies sub-components of resting state networks that covary with behavioral indices
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Timothy eMeier
2012-10-01
Full Text Available Parallel Independent Component Analysis (para-ICA is a multivariate method that can identify complex relationships between different data modalities by simultaneously performing Independent Component Analysis on each data set while finding mutual information between the two data sets. We use para-ICA to test the hypothesis that spatial sub-components of common resting state networks (RSNs covary with specific behavioral measures. Resting state scans and a battery of behavioral indices were collected from 24 younger adults. Group ICA was performed and common RSNs were identified by spatial correlation to publically available templates. Nine RSNs were identified and para-ICA was run on each network with a matrix of behavioral measures serving as the second data type. Five networks had spatial sub-components that significantly correlated with behavioral components. These included a sub-component of the temporo-parietal attention network that differentially covaried with different trial-types of a sustained attention task, sub-components of default mode networks that covaried with attention and working memory tasks, and a sub-component of the bilateral frontal network that split the left inferior frontal gyrus into three clusters according to its cytoarchitecture that differentially covaried with working memory performance. Additionally, we demonstrate the validity of para-ICA in cases with unbalanced dimensions using simulated data.
National Aeronautics and Space Administration — Remote Sensing Solutions proposes to develop the Network-based Parallel Retrieval Onboard Computing Environment for Sensor Systems (nPROCESS) for deployment on...
Invariant Subspaces of the Two-Dimensional Nonlinear Evolution Equations
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Chunrong Zhu
2016-11-01
Full Text Available In this paper, we develop the symmetry-related methods to study invariant subspaces of the two-dimensional nonlinear differential operators. The conditional Lie–Bäcklund symmetry and Lie point symmetry methods are used to construct invariant subspaces of two-dimensional differential operators. We first apply the multiple conditional Lie–Bäcklund symmetries to derive invariant subspaces of the two-dimensional operators. As an application, the invariant subspaces for a class of two-dimensional nonlinear quadratic operators are provided. Furthermore, the invariant subspace method in one-dimensional space combined with the Lie symmetry reduction method and the change of variables is used to obtain invariant subspaces of the two-dimensional nonlinear operators.
Mungal, Angus Shiva
2016-01-01
In New York City, a partnership between Teach For America (TFA), the New York City Department of Education (NYCDOE), the Relay Graduate School of Education (Relay), and three charter school networks produced a "parallel education structure" within the public school system. Driving the partnership and the parallel education structure are…
Two-dimensional gain cross-grating based on spatial modulation of active Raman gain
Wang, Li; Zhou, Feng-Xue; Guo, Hong-Ju; Niu, Yue-Ping; Gong, Shang-Qing
2016-11-01
Based on the spatial modulation of active Raman gain, a two-dimensional gain cross-grating is theoretically proposed. As the probe field propagates along the z direction and passes through the intersectant region of the two orthogonal standing-wave fields in the x-y plane, it can be effectively diffracted into the high-order directions, and the zero-order diffraction intensity is amplified at the same time. In comparison with the two-dimensional electromagnetically induced cross-grating based on electromagnetically induced transparency, the two-dimensional gain cross-grating has much higher diffraction intensities in the first-order and the high-order directions. Hence, it is more suitable to be utilized as all-optical switching and routing in optical networking and communication. Project supported by the National Natural Science Foundation of China (Grant Nos. 11274112 and 11347133).
Peker, Musa; Şen, Baha; Gürüler, Hüseyin
2015-02-01
The effect of anesthesia on the patient is referred to as depth of anesthesia. Rapid classification of appropriate depth level of anesthesia is a matter of great importance in surgical operations. Similarly, accelerating classification algorithms is important for the rapid solution of problems in the field of biomedical signal processing. However numerous, time-consuming mathematical operations are required when training and testing stages of the classification algorithms, especially in neural networks. In this study, to accelerate the process, parallel programming and computing platform (Nvidia CUDA) facilitates dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU) was utilized. The system was employed to detect anesthetic depth level on related electroencephalogram (EEG) data set. This dataset is rather complex and large. Moreover, the achieving more anesthetic levels with rapid response is critical in anesthesia. The proposed parallelization method yielded high accurate classification results in a faster time.
Zheng, Yan
2015-03-01
Internet of things (IoT), focusing on providing users with information exchange and intelligent control, attracts a lot of attention of researchers from all over the world since the beginning of this century. IoT is consisted of large scale of sensor nodes and data processing units, and the most important features of IoT can be illustrated as energy confinement, efficient communication and high redundancy. With the sensor nodes increment, the communication efficiency and the available communication band width become bottle necks. Many research work is based on the instance which the number of joins is less. However, it is not proper to the increasing multi-join query in whole internet of things. To improve the communication efficiency between parallel units in the distributed sensor network, this paper proposed parallel query optimization algorithm based on distribution attributes cost graph. The storage information relations and the network communication cost are considered in this algorithm, and an optimized information changing rule is established. The experimental result shows that the algorithm has good performance, and it would effectively use the resource of each node in the distributed sensor network. Therefore, executive efficiency of multi-join query between different nodes could be improved.
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Ramazan Aygün
2007-11-01
Full Text Available The assumption of TCP-based protocols that packet error (lost or damaged is due to network congestion is not true for wireless networks. For wireless networks, it is important to reduce the number of retransmissions to improve the effectiveness of TCP-based protocols. In this paper, we consider improvement at the data link layer for systems that use stop-and-wait ARQ as in IEEE 802.11 standard. We show that increasing the buffer size will not solve the actual problem and moreover it is likely to degrade the quality of delivery (QoD. We firstly study a wireless router system model with a sequential convolutional decoder for error detection and correction in order to investigate QoD of flow and error control. To overcome the problems along with high packet error rate, we propose a wireless router system with parallel sequential decoders. We simulate our systems and provide performance in terms of average buffer occupancy, blocking probability, probability of decoding failure, system throughput, and channel throughput. We have studied these performance metrics for different channel conditions, packet arrival rates, decoding time-out limits, system capacities, and the number of sequential decoders. Our results show that parallel sequential decoders have great impact on the system performance and increase QoD significantly.
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Aygün Ramazan
2007-01-01
Full Text Available The assumption of TCP-based protocols that packet error (lost or damaged is due to network congestion is not true for wireless networks. For wireless networks, it is important to reduce the number of retransmissions to improve the effectiveness of TCP-based protocols. In this paper, we consider improvement at the data link layer for systems that use stop-and-wait ARQ as in IEEE 802.11 standard. We show that increasing the buffer size will not solve the actual problem and moreover it is likely to degrade the quality of delivery (QoD. We firstly study a wireless router system model with a sequential convolutional decoder for error detection and correction in order to investigate QoD of flow and error control. To overcome the problems along with high packet error rate, we propose a wireless router system with parallel sequential decoders. We simulate our systems and provide performance in terms of average buffer occupancy, blocking probability, probability of decoding failure, system throughput, and channel throughput. We have studied these performance metrics for different channel conditions, packet arrival rates, decoding time-out limits, system capacities, and the number of sequential decoders. Our results show that parallel sequential decoders have great impact on the system performance and increase QoD significantly.
Cao, Jianfang; Cui, Hongyan; Shi, Hao; Jiao, Lijuan
2016-01-01
A back-propagation (BP) neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To improve the classification accuracy and runtime efficiency of the BP neural network algorithm, we proposed a parallel design and realization method for a particle swarm optimization (PSO)-optimized BP neural network based on MapReduce on the Hadoop platform using both the PSO algorithm and a parallel design. The PSO algorithm was used to optimize the BP neural network’s initial weights and thresholds and improve the accuracy of the classification algorithm. The MapReduce parallel programming model was utilized to achieve parallel processing of the BP algorithm, thereby solving the problems of hardware and communication overhead when the BP neural network addresses big data. Datasets on 5 different scales were constructed using the scene image library from the SUN Database. The classification accuracy of the parallel PSO-BP neural network algorithm is approximately 92%, and the system efficiency is approximately 0.85, which presents obvious advantages when processing big data. The algorithm proposed in this study demonstrated both higher classification accuracy and improved time efficiency, which represents a significant improvement obtained from applying parallel processing to an intelligent algorithm on big data. PMID:27304987
Image encryption using the two-dimensional logistic chaotic map
Wu, Yue; Yang, Gelan; Jin, Huixia; Noonan, Joseph P.
2012-01-01
Chaos maps and chaotic systems have been proved to be useful and effective for cryptography. In our study, the two-dimensional logistic map with complicated basin structures and attractors are first used for image encryption. The proposed method adopts the classic framework of the permutation-substitution network in cryptography and thus ensures both confusion and diffusion properties for a secure cipher. The proposed method is able to encrypt an intelligible image into a random-like one from the statistical point of view and the human visual system point of view. Extensive simulation results using test images from the USC-SIPI image database demonstrate the effectiveness and robustness of the proposed method. Security analysis results of using both the conventional and the most recent tests show that the encryption quality of the proposed method reaches or excels the current state-of-the-art methods. Similar encryption ideas can be applied to digital data in other formats (e.g., digital audio and video). We also publish the cipher MATLAB open-source-code under the web page https://sites.google.com/site/tuftsyuewu/source-code.
Quantifying leaf venation patterns: two-dimensional maps.
Rolland-Lagan, Anne-Gaëlle; Amin, Mira; Pakulska, Malgosia
2009-01-01
The leaf vasculature plays crucial roles in transport and mechanical support. Understanding how vein patterns develop and what underlies pattern variation between species has many implications from both physiological and evolutionary perspectives. We developed a method for extracting spatial vein pattern data from leaf images, such as vein densities and also the sizes and shapes of the vein reticulations. We used this method to quantify leaf venation patterns of the first rosette leaf of Arabidopsis thaliana throughout a series of developmental stages. In particular, we characterized the size and shape of vein network areoles (loops), which enlarge and are split by new veins as a leaf develops. Pattern parameters varied in time and space. In particular, we observed a distal to proximal gradient in loop shape (length/width ratio) which varied over time, and a margin-to-center gradient in loop sizes. Quantitative analyses of vein patterns at the tissue level provide a two-way link between theoretical models of patterning and molecular experimental work to further explore patterning mechanisms during development. Such analyses could also be used to investigate the effect of environmental factors on vein patterns, or to compare venation patterns from different species for evolutionary studies. The method also provides a framework for gathering and overlaying two-dimensional maps of point, line and surface morphological data.
Two-dimensional discrete gap breathers in a two-dimensional discrete diatomic Klein-Gordon lattice
Institute of Scientific and Technical Information of China (English)
XU Quan; QIANG Tian
2009-01-01
We study the existence and stability of two-dimensional discrete breathers in a two-dimensional discrete diatomic Klein-Gordon lattice consisting of alternating light and heavy atoms, with nearest-neighbor harmonic coupling.Localized solutions to the corresponding nonlinear differential equations with frequencies inside the gap of the linear wave spectrum, i.e. two-dimensional gap breathers, are investigated numerically. The numerical results of the corresponding algebraic equations demonstrate the possibility of the existence of two-dimensional gap breathers with three types of symmetries, i.e., symmetric, twin-antisymmetric and single-antisymmetric. Their stability depends on the nonlinear on-site potential (soft or hard), the interaction potential (attractive or repulsive)and the center of the two-dimensional gap breather (on a light or a heavy atom).
Parallel Neural Network-Based Motion Controller for Autonomous Underwater Vehicles
Institute of Scientific and Technical Information of China (English)
GAN Yong; WANG Li-rong; WAN Lei; XU Yu-ru
2005-01-01
A parallel neural network-based controller (PNNC) is presented for the motion control of underwater vehicles in this paper. It consists of a real-time part, a self-learning part and a desired-state programmer, and it is different from normal adaptive neural network controller in structure. Owing to the introduction of the self-learning part, on-line learning can be performed without sample data in several sample periods, resulting in high learning speed of the controller and good control performance. The desired-state programmer is utilized to obtain better learning samples of the neural network to keep the stability of the controller. The developed controller is applied to the 4-degree of freedom control of the AUV "IUV-IV" and is successful on the simulation platform. The control performance is also compared with that of neural network controller with different structures such as normal adaptive neural network and different learning methods. Current effects and surge velocity control are also included to demonstrate the controller's performance. It is shown that the PNNC has a great possibility to solve the problems in the control system design of underwater vehicles.
Parallel fixed point implementation of a radial basis function network in an FPGA.
de Souza, Alisson C D; Fernandes, Marcelo A C
2014-09-29
This paper proposes a parallel fixed point radial basis function (RBF) artificial neural network (ANN), implemented in a field programmable gate array (FPGA) trained online with a least mean square (LMS) algorithm. The processing time and occupied area were analyzed for various fixed point formats. The problems of precision of the ANN response for nonlinear classification using the XOR gate and interpolation using the sine function were also analyzed in a hardware implementation. The entire project was developed using the System Generator platform (Xilinx), with a Virtex-6 xc6vcx240t-1ff1156 as the target FPGA.
Parallel Fixed Point Implementation of a Radial Basis Function Network in an FPGA
Directory of Open Access Journals (Sweden)
Alisson C. D. de Souza
2014-09-01
Full Text Available This paper proposes a parallel fixed point radial basis function (RBF artificial neural network (ANN, implemented in a field programmable gate array (FPGA trained online with a least mean square (LMS algorithm. The processing time and occupied area were analyzed for various fixed point formats. The problems of precision of the ANN response for nonlinear classification using the XOR gate and interpolation using the sine function were also analyzed in a hardware implementation. The entire project was developed using the System Generator platform (Xilinx, with a Virtex-6 xc6vcx240t-1ff1156 as the target FPGA.
El-Bahaie, Ebtehal H.; Al-Hussaini, Emad K.
2010-12-01
In this paper analytical and simulation results for the decentralized detection of unknown signals are introduced. Parallel sensor network scheme is assumed. Additive White Gaussian Noise (AWGN) and Nakagami fading are assumed in both links, that is, from the source to the decentralized local sensors and from the sensors to the fusion center. Furthermore, diversity employing Square Law Combining (SLC) or Square Law Selection (SLS) is considered at each sensor, for both independent and correlated branches. Appreciable improvements are obtained with the increase of the number of sensors and the diversity employment.
A Novel Method for Iris Recognition Using BP Neural Network and Parallel Computing
Directory of Open Access Journals (Sweden)
Hamid Reza Sahebi
2016-04-01
Full Text Available In this paper, we seek a new method in designing an iris recognition system. In this method, first the Haar wavelet features are extracted from iris images. The advantage of using these features is the high-speed extraction, as well as being unique to each iris. Then the back propagation neural network (BPNN is used as a classifier. In this system, the BPNN parallel algorithms and their implementation on GPUs have been used by the aid of CUDA in order to speed up the learning process. Finally, the system performance and the speeding outcomes in a way that this algorithm is done in series are presented.
Parallel dynamics of the fully connected Blume-Emery-Griffiths neural network
Bollé, D.; Blanco, J. Busquets; Shim, G. M.
2003-02-01
The parallel dynamics of the fully connected Blume-Emery-Griffiths neural network model is studied at zero temperature using a probabilistic approach. A recursive scheme is found determining the complete time evolution of the order parameters, taking into account all feedback correlations. It is based upon the evolution of the distribution of the local field, the structure of which is determined in detail. As an illustrative example explicit analytic formula are given for the first few time steps of the dynamics. Furthermore, equilibrium fixed-point equations are derived and compared with the thermodynamic approach. The analytic results find excellent confirmation in extensive numerical simulations.
Two dimensional NMR of liquids and oriented molecules
Energy Technology Data Exchange (ETDEWEB)
Gochin, M.
1987-02-01
Chapter 1 discusses the quantum mechanical formalism used for describing the interaction between magnetic dipoles that dictates the appearance of a spectrum. The NMR characteristics of liquids and liquid crystals are stressed. Chapter 2 reviews the theory of multiple quantum and two dimensional NMR. Properties of typical spectra and phase cycling procedures are discussed. Chapter 3 describes a specific application of heteronuclear double quantum coherence to the removal of inhomogeneous broadening in liquids. Pulse sequences have been devised which cancel out any contribution from this inhomogeneity to the final spectrum. An interpretation of various pulse sequences for the case of /sup 13/C and /sup 1/H is given, together with methods of spectral editing by removal or retention of the homo- or heteronuclear J coupling. The technique is applied to a demonstration of high resolution in both frequency and spatial dimensions with a surface coil. In Chapter 4, multiple quantum filtered 2-D spectroscopy is demonstrated as an effective means of studying randomly deuterated molecules dissolved in a nematic liquid crystal. Magnitudes of dipole coupling constants have been determined for benzene and hexane, and their signs and assignments found from high order multiple quantum spectra. For the first time, a realistic impression of the conformation of hexane can be estimated from these results. Chapter 5 is a technical description of the MDB DCHIB-DR11W parallel interface which has been set up to transfer data between the Data General Nova 820 minicomputer, interfaced to the 360 MHz spectrometer, and the Vax 11/730. It covers operation of the boards, physical specifications and installation, and programs for testing and running the interface.
Two Dimensional Hydrodynamic Analysis of the Moose Creek Floodway
2012-09-01
ER D C/ CH L TR -1 2 -2 0 Two Dimensional Hydrodynamic Analysis of the Moose Creek Floodway C oa st al a n d H yd ra u lic s La b or at...distribution is unlimited. ERDC/CHL TR-12-20 September 2012 Two Dimensional Hydrodynamic Analysis of the Moose Creek Floodway Stephen H. Scott, Jeremy A...A two-dimensional Adaptive Hydraulics (AdH) hydrodynamic model was developed to simulate the Moose Creek Floodway. The Floodway is located
RESEARCH ON TWO-DIMENSIONAL LDA FOR FACE RECOGNITION
Institute of Scientific and Technical Information of China (English)
Han Ke; Zhu Xiuchang
2006-01-01
The letter presents an improved two-dimensional linear discriminant analysis method for feature extraction. Compared with the current two-dimensional methods for feature extraction, the improved two-dimensional linear discriminant analysis method makes full use of not only the row and the column direction information of face images but also the discriminant information among different classes. The method is evaluated using the Nanjing University of Science and Technology (NUST) 603 face database and the Aleix Martinez and Robert Benavente (AR) face database. Experimental results show that the method in the letter is feasible and effective.
ONE-DIMENSIONAL AND TWO-DIMENSIONAL LEADERSHIP STYLES
Directory of Open Access Journals (Sweden)
Nikola Stefanović
2007-06-01
Full Text Available In order to motivate their group members to perform certain tasks, leaders use different leadership styles. These styles are based on leaders' backgrounds, knowledge, values, experiences, and expectations. The one-dimensional styles, used by many world leaders, are autocratic and democratic styles. These styles lie on the two opposite sides of the leadership spectrum. In order to precisely define the leadership styles on the spectrum between the autocratic leadership style and the democratic leadership style, leadership theory researchers use two dimensional matrices. The two-dimensional matrices define leadership styles on the basis of different parameters. By using these parameters, one can identify two-dimensional styles.
Institute of Scientific and Technical Information of China (English)
季学武; 王健; 赵又群; 刘亚辉; 臧利国; 李波
2015-01-01
In order to diminish the impacts of external disturbance such as parking speed fluctuation and model un-certainty existing in steering kinematics, this paper presents a parallel path tracking method for vehicle based on pre-view back propagation (BP) neural network PID controller. The forward BP neural network can adjust the parameters of PID controller in real time. The preview time is optimized by considering path curvature, change in curvature and road boundaries. A fuzzy controller considering barriers and different road conditions is built to select the starting po-sition. In addition, a kind of path planning technology satisfying the requirement of obstacle avoidance is introduced. In order to solve the problem of discontinuous curvature, cubic B spline curve is used for curve fitting. The simulation results and real vehicle tests validate the effectiveness of the proposed path planning and tracking methods.
Institute of Scientific and Technical Information of China (English)
WANG Zhao-Ming; SHAO Bin; ZOU Jian
2007-01-01
We investigate the entanglement transfer in two parallel 1D spin chains of a quantum spin network,and show that the perfect entanglement transfer can be realized at some special times.In addition,the so-called 'sudden death' phenomenon of entanglement is found in the spin network system.
An Efficient Medium Access Control Protocol with Parallel Transmission for Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Mitsuji Matsumoto
2012-08-01
Full Text Available In this paper, we present a novel low power medium access control protocol for wireless sensor networks (WSNs. The proposed protocol, EP-MAC (Efficient MAC with Parallel Transmission achieves high energy efficiency and high packet delivery ratio under different traffic load. EP-MAC protocol is basically based on the Time Division Multiple Access (TDMA approach. The power of Carrier Sense Multiple Access (CSMA is used in order to offset the fundamental problems that the stand-alone TDMA method suffers from, i.e., problems such as lack of scalability, adaptability to varying situations, etc. The novel idea behind the EP-MAC is that it uses the parallel transmission concept with the TDMA link scheduling. EP-MAC uses the methods for the transmission power adjustment, i.e., uses the minimum level power necessary to reach the intended neighbor within a specified bit error rate [BER] target. This reduces energy consumption, as well as further enhances the scope of parallel transmission of the protocol. The simulation studies support the theoretical results, and validate the efficiency of our proposed EP-MAC protocol.
A study of two-dimensional magnetic polaron
Institute of Scientific and Technical Information of China (English)
LIU; Tao; ZHANG; Huaihong; FENG; Mang; WANG; Kelin
2006-01-01
By using the variational method and anneal simulation, we study in this paper the self-trapped magnetic polaron (STMP) in two-dimensional anti-ferromagnetic material and the bound magnetic polaron (BMP) in ferromagnetic material. Schwinger angular momentum theory is applied to changing the problem into a coupling problem of carriers and two types of Bosons. Our calculation shows that there are single-peak and multi-peak structures in the two-dimensional STMP. For the ferromagnetic material, the properties of the two-dimensional BMP are almost the same as that in one-dimensional case; but for the anti-ferromagnetic material, the two-dimensional STMP structure is much richer than the one-dimensional case.
UPWIND DISCONTINUOUS GALERKIN METHODS FOR TWO DIMENSIONAL NEUTRON TRANSPORT EQUATIONS
Institute of Scientific and Technical Information of China (English)
袁光伟; 沈智军; 闫伟
2003-01-01
In this paper the upwind discontinuous Galerkin methods with triangle meshes for two dimensional neutron transport equations will be studied.The stability for both of the semi-discrete and full-discrete method will be proved.
Two-Dimensionally-Modulated, Magnetic Structure of Neodymium Metal
DEFF Research Database (Denmark)
Lebech, Bente; Bak, P.
1979-01-01
The incipient magnetic order of dhcp Nd is described by a two-dimensional, incommensurably modulated structure ("triple-q" structure). The ordering is accompanied by a lattice distortion that forms a similar pattern....
Entanglement Entropy for time dependent two dimensional holographic superconductor
Mazhari, N S; Myrzakulov, Kairat; Myrzakulov, R
2016-01-01
We studied entanglement entropy for a time dependent two dimensional holographic superconductor. We showed that the conserved charge of the system plays the role of the critical parameter to have condensation.
Decoherence in a Landau Quantized Two Dimensional Electron Gas
Directory of Open Access Journals (Sweden)
McGill Stephen A.
2013-03-01
Full Text Available We have studied the dynamics of a high mobility two-dimensional electron gas as a function of temperature. The presence of satellite reflections in the sample and magnet can be modeled in the time-domain.
Quantization of Two-Dimensional Gravity with Dynamical Torsion
Lavrov, P M
1999-01-01
We consider two-dimensional gravity with dynamical torsion in the Batalin - Vilkovisky and Batalin - Lavrov - Tyutin formalisms of gauge theories quantization as well as in the background field method.
Spatiotemporal dissipative solitons in two-dimensional photonic lattices.
Mihalache, Dumitru; Mazilu, Dumitru; Lederer, Falk; Kivshar, Yuri S
2008-11-01
We analyze spatiotemporal dissipative solitons in two-dimensional photonic lattices in the presence of gain and loss. In the framework of the continuous-discrete cubic-quintic Ginzburg-Landau model, we demonstrate the existence of novel classes of two-dimensional spatiotemporal dissipative lattice solitons, which also include surface solitons located in the corners or at the edges of the truncated two-dimensional photonic lattice. We find the domains of existence and stability of such spatiotemporal dissipative solitons in the relevant parameter space, for both on-site and intersite lattice solitons. We show that the on-site solitons are stable in the whole domain of their existence, whereas most of the intersite solitons are unstable. We describe the scenarios of the instability-induced dynamics of dissipative solitons in two-dimensional lattices.
Bound states of two-dimensional relativistic harmonic oscillators
Institute of Scientific and Technical Information of China (English)
Qiang Wen-Chao
2004-01-01
We give the exact normalized bound state wavefunctions and energy expressions of the Klein-Gordon and Dirac equations with equal scalar and vector harmonic oscillator potentials in the two-dimensional space.
A two-dimensional polymer prepared by organic synthesis.
Kissel, Patrick; Erni, Rolf; Schweizer, W Bernd; Rossell, Marta D; King, Benjamin T; Bauer, Thomas; Götzinger, Stephan; Schlüter, A Dieter; Sakamoto, Junji
2012-02-05
Synthetic polymers are widely used materials, as attested by a production of more than 200 millions of tons per year, and are typically composed of linear repeat units. They may also be branched or irregularly crosslinked. Here, we introduce a two-dimensional polymer with internal periodicity composed of areal repeat units. This is an extension of Staudinger's polymerization concept (to form macromolecules by covalently linking repeat units together), but in two dimensions. A well-known example of such a two-dimensional polymer is graphene, but its thermolytic synthesis precludes molecular design on demand. Here, we have rationally synthesized an ordered, non-equilibrium two-dimensional polymer far beyond molecular dimensions. The procedure includes the crystallization of a specifically designed photoreactive monomer into a layered structure, a photo-polymerization step within the crystal and a solvent-induced delamination step that isolates individual two-dimensional polymers as free-standing, monolayered molecular sheets.
Second invariant for two-dimensional classical super systems
Indian Academy of Sciences (India)
S C Mishra; Roshan Lal; Veena Mishra
2003-10-01
Construction of superpotentials for two-dimensional classical super systems (for ≥ 2) is carried out. Some interesting potentials have been studied in their super form and also their integrability.
Directory of Open Access Journals (Sweden)
Jun Liu
2015-04-01
Full Text Available With the continuing growth of highway construction and vehicle use expansion all over the world, highway vehicle traffic rule violation (TRV detection has become more and more important so as to avoid traffic accidents and injuries in intelligent transportation systems (ITS and vehicular ad hoc networks (VANETs. Since very few works have contributed to solve the TRV detection problem by moving vehicle measurements and surveillance devices, this paper develops a novel parallel ultrasonic sensor system that can be used to identify the TRV behavior of a host vehicle in real-time. Then a two-dimensional state method is proposed, utilizing the spacial state and time sequential states from the data of two parallel ultrasonic sensors to detect and count the highway vehicle violations. Finally, the theoretical TRV identification probability is analyzed, and actual experiments are conducted on different highway segments with various driving speeds, which indicates that the identification accuracy of the proposed method can reach about 90.97%.
SiGN-SSM: open source parallel software for estimating gene networks with state space models.
Tamada, Yoshinori; Yamaguchi, Rui; Imoto, Seiya; Hirose, Osamu; Yoshida, Ryo; Nagasaki, Masao; Miyano, Satoru
2011-04-15
SiGN-SSM is an open-source gene network estimation software able to run in parallel on PCs and massively parallel supercomputers. The software estimates a state space model (SSM), that is a statistical dynamic model suitable for analyzing short time and/or replicated time series gene expression profiles. SiGN-SSM implements a novel parameter constraint effective to stabilize the estimated models. Also, by using a supercomputer, it is able to determine the gene network structure by a statistical permutation test in a practical time. SiGN-SSM is applicable not only to analyzing temporal regulatory dependencies between genes, but also to extracting the differentially regulated genes from time series expression profiles. SiGN-SSM is distributed under GNU Affero General Public Licence (GNU AGPL) version 3 and can be downloaded at http://sign.hgc.jp/signssm/. The pre-compiled binaries for some architectures are available in addition to the source code. The pre-installed binaries are also available on the Human Genome Center supercomputer system. The online manual and the supplementary information of SiGN-SSM is available on our web site. tamada@ims.u-tokyo.ac.jp.
Directory of Open Access Journals (Sweden)
Lorenzo L. Pesce
2013-01-01
Full Text Available Our limited understanding of the relationship between the behavior of individual neurons and large neuronal networks is an important limitation in current epilepsy research and may be one of the main causes of our inadequate ability to treat it. Addressing this problem directly via experiments is impossibly complex; thus, we have been developing and studying medium-large-scale simulations of detailed neuronal networks to guide us. Flexibility in the connection schemas and a complete description of the cortical tissue seem necessary for this purpose. In this paper we examine some of the basic issues encountered in these multiscale simulations. We have determined the detailed behavior of two such simulators on parallel computer systems. The observed memory and computation-time scaling behavior for a distributed memory implementation were very good over the range studied, both in terms of network sizes (2,000 to 400,000 neurons and processor pool sizes (1 to 256 processors. Our simulations required between a few megabytes and about 150 gigabytes of RAM and lasted between a few minutes and about a week, well within the capability of most multinode clusters. Therefore, simulations of epileptic seizures on networks with millions of cells should be feasible on current supercomputers.
Distributed Parallel Network Data Storage Technology%分布式并行网络数据存储技术
Institute of Scientific and Technical Information of China (English)
杨峰; 刘心松; 罗朝劲
2002-01-01
The bases of distributed parallel network data storage technology(DPNDS) are high speed network tech-nology, database technology, artificial intelligence and multimedia technology. It will become the foundation of mod-ern information society because of the excellent management efficiency, reliability, availability, expansibility and lowcost. In this paper, we discuss the key technology of DPNDS which includes data distributing, parallel data process-ing, data network storage, object-oriented data storage and then give some suggestions about the new research direc-tion.
Extreme paths in oriented two-dimensional percolation
Andjel, E. D.; Gray, L. F.
2016-01-01
International audience; A useful result about leftmost and rightmost paths in two dimensional bond percolation is proved. This result was introduced without proof in \\cite{G} in the context of the contact process in continuous time. As discussed here, it also holds for several related models, including the discrete time contact process and two dimensional site percolation. Among the consequences are a natural monotonicity in the probability of percolation between different sites and a somewha...
Two Dimensional Nucleation Process by Monte Carlo Simulation
T., Irisawa; K., Matsumoto; Y., Arima; T., Kan; Computer Center, Gakushuin University; Department of Physics, Gakushuin University
1997-01-01
Two dimensional nucleation process on substrate is investigated by Monte Carlo simulation, and the critical nucleus size and its waiting time are measured with a high accuracy. In order to measure the critical nucleus with a high accuracy, we calculate the attachment and the detachment rate to the nucleus directly, and define the critical nucleus size when both rate are equal. Using the kinematical nucleation theory by Nishioka, it is found that, our obtained kinematical two dimensional criti...
Controlled Interactions between Two Dimensional Layered Inorganic Nanosheets and Polymers
2016-06-15
polymers . 2. Introduction . Research objectives: This research aims to study the physical (van der Waals forces: crystal epitaxy and π-π...AFRL-AFOSR-JP-TR-2016-0071 Controlled Interactions between Two Dimensional Layered Inorganic Nanosheets and Polymers Cheolmin Park YONSEI UNIVERSITY...Interactions between Two Dimensional Layered Inorganic Nanosheets and Polymers 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA2386-14-1-4054 5c. PROGRAM ELEMENT
Two-Dimensional Weak Pseudomanifolds on Eight Vertices
Indian Academy of Sciences (India)
Basudeb Datta; Nandini Nilakantan
2002-05-01
We explicitly determine all the two-dimensional weak pseudomanifolds on 8 vertices. We prove that there are (up to isomorphism) exactly 95 such weak pseudomanifolds, 44 of which are combinatorial 2-manifolds. These 95 weak pseudomanifolds triangulate 16 topological spaces. As a consequence, we prove that there are exactly three 8-vertex two-dimensional orientable pseudomanifolds which allow degree three maps to the 4-vertex 2-sphere.
Two-Dimensional Materials for Sensing: Graphene and Beyond
Directory of Open Access Journals (Sweden)
Seba Sara Varghese
2015-09-01
Full Text Available Two-dimensional materials have attracted great scientific attention due to their unusual and fascinating properties for use in electronics, spintronics, photovoltaics, medicine, composites, etc. Graphene, transition metal dichalcogenides such as MoS2, phosphorene, etc., which belong to the family of two-dimensional materials, have shown great promise for gas sensing applications due to their high surface-to-volume ratio, low noise and sensitivity of electronic properties to the changes in the surroundings. Two-dimensional nanostructured semiconducting metal oxide based gas sensors have also been recognized as successful gas detection devices. This review aims to provide the latest advancements in the field of gas sensors based on various two-dimensional materials with the main focus on sensor performance metrics such as sensitivity, specificity, detection limit, response time, and reversibility. Both experimental and theoretical studies on the gas sensing properties of graphene and other two-dimensional materials beyond graphene are also discussed. The article concludes with the current challenges and future prospects for two-dimensional materials in gas sensor applications.
Institute of Scientific and Technical Information of China (English)
Lihui WANG; Dayu LIU; Bo WANG; Jie SUN; Lianhong LI
2008-01-01
A microfluidic chip featuring laminar flow-based parallel gradient-generating networks was designed and fabricated. The microchip contains 5 gradient genera-tors and 30 cell chambers where the resulting concentra-tion gradients of drugs are delivered to stimulate on-chip cultured cells. The microfluidics exploits the advantage of lab-on-a-chip technology by integrating the generation of drug concentration gradients and a series of cell opera-tions including seeding, culture, stimulation and staining into a chip. The microfluidic network was patterned on a glass wafer, which was further bonded to a PDMS film. A series of weir structures were fabricated on the cell culture reservoir to facilitate cell positioning and seeding. Cell injection and fluid delivery were controlled by a syringe pump. Steady parallel concentration gradients were gen-erated by flowing two fluids in each network. Over time observation shows that the microchip was suitable for cell seeding and culture. The microchip described above was applied in studying the role of reduced glutathione (GSH) in mediating chemotherapy sensitivity of MCF-7 cells. MCF-7 cells were treated with concentration gradients of As2O3 and N-acetyl cysteine (NAC) for GSH modu-lation, followed by exposure to adriamycin. GSH levels were down-regulated upon As203 treatment and up-regu-lated upon NAC treatment. Suppression of intracellular GSH by treatment with As2O3 has been shown to increase sensitivity to adriamycin. Conversely, elevation of intra-cellular GSH by treatment with NAC leads to increased drug resistance. The integrated microfluidic chip is able to perform multiparametric pharmacological profiling with easy operation, and thus holds great potential for extra-polation to the cell based high-content drug screening.
Rychlewska, Urszula; Warzajtis, Beata; Djuran, Milos I; Radanović, Dusanka D; Dimitrijević, Mirjana Dj; Rajković, Sneaeana
2008-06-01
The title compound, {[CoLi2(C11H14N2O8)(H2O)3].2H2O}n, constitutes the first example of a salt of the [M(II)(1,3-pdta)](2-) complex (1,3-pdta is propane-1,3-diyldinitrilotetraacetate) with a monopositive cation as counter-ion. Insertion of the Li+ cation could only be achieved through application of the ion-exchange column technique which, however, appeared unsuccessful with other alkali metals and the ammonium cation. The structure contains two tetrahedrally coordinated Li+ cations, an octahedral [Co(1,3-pdta)](2-) anion and five water molecules, two of which are uncoordinated, and is built of two-dimensional layers extending parallel to the (010) lattice plane, the constituents of which are connected by the coordinate bonds. O-H(water)...O hydrogen bonds operate both within and between these layers. The crystal investigated belongs to the enantiomeric space group P2(1) with only one (Lambda) of two possible optical isomers of the [Co(1,3-pdta)](2-) complex. A possible cause of enantiomer separation during crystallization might be the rigidification and polarization of the [M(1,3-pdta)](2-) core, resulting from direct coordination of Li+ cations to three out of four carboxylate groups constituting the 1,3-pdta ligand. The structure of (I) differs considerably from those of the other [M(II)(1,3-pdta)](2-) complexes, in which the charge compensation is realized by means of divalent hexaaqua complex cations. This finding demonstrates a significant structure-determining role of the counter-ions.
Multiscale Methods, Parallel Computation, and Neural Networks for Real-Time Computer Vision.
Battiti, Roberto
1990-01-01
This thesis presents new algorithms for low and intermediate level computer vision. The guiding ideas in the presented approach are those of hierarchical and adaptive processing, concurrent computation, and supervised learning. Processing of the visual data at different resolutions is used not only to reduce the amount of computation necessary to reach the fixed point, but also to produce a more accurate estimation of the desired parameters. The presented adaptive multiple scale technique is applied to the problem of motion field estimation. Different parts of the image are analyzed at a resolution that is chosen in order to minimize the error in the coefficients of the differential equations to be solved. Tests with video-acquired images show that velocity estimation is more accurate over a wide range of motion with respect to the homogeneous scheme. In some cases introduction of explicit discontinuities coupled to the continuous variables can be used to avoid propagation of visual information from areas corresponding to objects with different physical and/or kinematic properties. The human visual system uses concurrent computation in order to process the vast amount of visual data in "real -time." Although with different technological constraints, parallel computation can be used efficiently for computer vision. All the presented algorithms have been implemented on medium grain distributed memory multicomputers with a speed-up approximately proportional to the number of processors used. A simple two-dimensional domain decomposition assigns regions of the multiresolution pyramid to the different processors. The inter-processor communication needed during the solution process is proportional to the linear dimension of the assigned domain, so that efficiency is close to 100% if a large region is assigned to each processor. Finally, learning algorithms are shown to be a viable technique to engineer computer vision systems for different applications starting from
Sun, Zhiwei; Zhi, Ya'nan; Liu, Liren; Sun, Jianfeng; Zhou, Yu; Hou, Peipei
2013-09-01
The synthetic aperture imaging ladar (SAIL) systems typically generate large amounts of data difficult to compress with digital method. This paper presents an optical SAIL processor based on compensation of quadratic phase of echo in azimuth direction and two dimensional Fourier transform. The optical processor mainly consists of one phase-only liquid crystal spatial modulator(LCSLM) to load the phase data of target echo and one cylindrical lens to compensate the quadratic phase and one spherical lens to fulfill the task of two dimensional Fourier transform. We show the imaging processing result of practical target echo obtained by a synthetic aperture imaging ladar demonstrator. The optical processor is compact and lightweight and could provide inherent parallel and the speed-of-light computing capability, it has a promising application future especially in onboard and satellite borne SAIL systems.
Two-dimensional analysis of gold nanoparticle effects on dye molecule system
Energy Technology Data Exchange (ETDEWEB)
Qaradaghi, Vahid [School of Electrical and Computer Engineering, Tarbiat Modares University (TMU), P.O. Box 14115-194, Tehran (Iran, Islamic Republic of); Fathi, Davood, E-mail: davfathi@modares.ac.ir [School of Electrical and Computer Engineering, Tarbiat Modares University (TMU), P.O. Box 14115-194, Tehran (Iran, Islamic Republic of)
2013-01-15
This paper presents a two-dimensional analysis of a dye molecule system in the presence of a gold nanoparticle (AuNP). This configuration has been used widely for the practical applications such as optoelectronics and also the biomedical applications such as cancer. The effects of coupling between the nanoparticle (AuNP) and dye molecules around it are simulated and studied in a two-dimensional plane. The three relative momentum polarizations of dye molecule near the AuNP (perpendicular, parallel and random) are considered. With the change of nanoparticle radius and its distances from the dye molecules, the output fluorescence signal will be changed. The obtained results show that, the perpendicular polarized dye w.r.t. the AuNP surface leads to the increase of output fluorescence signal nearly 1.5 times the input intensity.
Two-dimensional simulations of nonlinear beam-plasma interaction in isotropic and magnetized plasmas
Timofeev, I V
2012-01-01
Nonlinear interaction of a low density electron beam with a uniform plasma is studied using two-dimensional particle-in-cell (PIC) simulations. We focus on formation of coherent phase space structures in the case, when a wide two-dimensional wave spectrum is driven unstable, and we also study how nonlinear evolution of these structures is affected by the external magnetic field. In the case of isotropic plasma, nonlinear buildup of filamentation modes due to the combined effects of two-stream and oblique instabilities is found to exist and growth mechanisms of secondary instabilities destroying the BGK--type nonlinear wave are identified. In the weak magnetic field, the energy of beam-excited plasma waves at the nonlinear stage of beam-plasma interaction goes predominantly to the short-wavelength upper-hybrid waves propagating parallel to the magnetic field, whereas in the strong magnetic field the spectral energy is transferred to the electrostatic whistlers with oblique propagation.
Two-Dimensional Rotating Stall Analysis in a Wide Vaneless Diffuser
Directory of Open Access Journals (Sweden)
2006-01-01
Full Text Available We report a numerical study on the vaneless diffuser core flow instability in centrifugal compressors. The analysis is performed for the purpose of better understanding of the rotating stall flow mechanism in radial vaneless diffusers. Since the analysis is restricted to the two-dimensional core flow, the effect of the wall boundary layers is neglected. A commercial code with the standard incompressible viscous flow solver is applied to model the vaneless diffuser core flow in the plane parallel to the diffuser walls. At the diffuser inlet, rotating jet-wake velocity pattern is prescribed and at the diffuser outlet constant static pressure is assumed. Under these circumstances, two-dimensional rotating flow instability similar to rotating stall is found to exist. Performed parameter analysis reveals that this instability is strongly influenced by the diffuser geometry and the inlet and outlet flow conditions.
Scalable loading of a two-dimensional trapped-ion array
Bruzewicz, Colin D.; McConnell, Robert; Chiaverini, John; Sage, Jeremy M.
2016-09-01
Two-dimensional arrays of trapped-ion qubits are attractive platforms for scalable quantum information processing. Sufficiently rapid reloading capable of sustaining a large array, however, remains a significant challenge. Here with the use of a continuous flux of pre-cooled neutral atoms from a remotely located source, we achieve fast loading of a single ion per site while maintaining long trap lifetimes and without disturbing the coherence of an ion quantum bit in an adjacent site. This demonstration satisfies all major criteria necessary for loading and reloading extensive two-dimensional arrays, as will be required for large-scale quantum information processing. Moreover, the already high loading rate can be increased by loading ions in parallel with only a concomitant increase in photo-ionization laser power and no need for additional atomic flux.
Institute of Scientific and Technical Information of China (English)
魏关锋; 姚平经; LUOXing; ROETZELWilfried
2004-01-01
The multi-stream heat exchanger network synthesis (HENS) problem can be formulated as a mixed integer nonlinear programming model according to Yee et al. Its nonconvexity nature leads to existence of more than one optimum and computational difficulty for traditional algorithms to find the global optimum. Compared with deterministic algorithms, evolutionary computation provides a promising approach to tackle this problem. In this paper, a mathematical model of multi-stream heat exchangers network synthesis problem is setup. Different from the assumption of isothermal mixing of stream splits and thus linearity constraints of Yee et al., non-isothermal mixing is supported. As a consequence, nonlinear constraints are resulted and nonconvexity of the objective function is added. To solve the mathematical model, an algorithm named GA/SA (parallel genetic/simulated annealing algorithm) is detailed for application to the multi-stream heat exchanger network synthesis problem. The performance of the proposed approach is demonstrated with three examples and the obtained solutions indicate the presented approach is effective for multi-stream HENS.
Foulkes, Stephen B.; Booth, David M.
1997-07-01
Object segmentation is the process by which a mask is generated which identifies the area of an image which is occupied by an object. Many object recognition techniques depend on the quality of such masks for shape and underlying brightness information, however, segmentation remains notoriously unreliable. This paper considers how the image restoration technique of Geman and Geman can be applied to the improvement of object segmentations generated by a locally adaptive background subtraction technique. Also presented is how an artificial neural network hybrid, consisting of a single layer Kohonen network with each of its nodes connected to a different multi-layer perceptron, can be used to approximate the image restoration process. It is shown that the restoration techniques are very well suited for parallel processing and in particular the artificial neural network hybrid has the potential for near real time image processing. Results are presented for the detection of ships in SPOT panchromatic imagery and the detection of vehicles in infrared linescan images, these being a fair representation of the wider class of problem.
Two dimensional soft material: new faces of graphene oxide.
Kim, Jaemyung; Cote, Laura J; Huang, Jiaxing
2012-08-21
Graphite oxide sheets, now called graphene oxide (GO), can be made from chemical exfoliation of graphite by reactions that have been known for 150 years. Because GO is a promising solution-processable precursor for the bulk production of graphene, interest in this old material has resurged. The reactions to produce GO add oxygenated functional groups to the graphene sheets on their basal plane and edges, and this derivatization breaks the π-conjugated network, resulting in electrically insulating but highly water-dispersible sheets. Apart from making graphene, GO itself has many intriguing properties. Like graphene, GO is a two-dimensional (2D) sheet with feature sizes at two abruptly different length scales. The apparent thickness of the functionalized carbon sheet is approximately 1 nm, but the lateral dimensions can range from a few nanometers to hundreds of micrometers. Therefore, researchers can think of GO as either a single molecule or a particle, depending on which length scale is of greater interest. At the same time, GO can be viewed as an unconventional soft material, such as a 2D polymer, highly anisotropic colloid, membrane, liquid crystal, or amphiphile. In this Account, we highlight the soft material characteristics of GO. GO consists of nanographitic patches surrounded by largely disordered, oxygenated domains. Such structural characteristics effectively make GO a 2D amphiphile with a hydrophilic periphery and largely hydrophobic center. This insight has led to better understanding of the solution properties of GO for making thin films and new applications of GO as a surfactant. Changes in pH and sheet size can tune the amphiphilicity of GO, leading to intriguing interfacial activities. In addition, new all-carbon composites made of only graphitic nanostructures using GO as a dispersing agent have potential applications in photovoltaics and energy storage. On the other hand, GO can function as a 2D random diblock copolymer, one block graphitic and
Zhong, Cheng; Liu, Lei; Zhao, Jing
2014-01-01
An efficient location-based query algorithm of protecting the privacy of the user in the distributed networks is given. This algorithm utilizes the location indexes of the users and multiple parallel threads to search and select quickly all the candidate anonymous sets with more users and their location information with more uniform distribution to accelerate the execution of the temporal-spatial anonymous operations, and it allows the users to configure their custom-made privacy-preserving location query requests. The simulated experiment results show that the proposed algorithm can offer simultaneously the location query services for more users and improve the performance of the anonymous server and satisfy the anonymous location requests of the users.
Electronics and optoelectronics of two-dimensional transition metal dichalcogenides.
Wang, Qing Hua; Kalantar-Zadeh, Kourosh; Kis, Andras; Coleman, Jonathan N; Strano, Michael S
2012-11-01
The remarkable properties of graphene have renewed interest in inorganic, two-dimensional materials with unique electronic and optical attributes. Transition metal dichalcogenides (TMDCs) are layered materials with strong in-plane bonding and weak out-of-plane interactions enabling exfoliation into two-dimensional layers of single unit cell thickness. Although TMDCs have been studied for decades, recent advances in nanoscale materials characterization and device fabrication have opened up new opportunities for two-dimensional layers of thin TMDCs in nanoelectronics and optoelectronics. TMDCs such as MoS(2), MoSe(2), WS(2) and WSe(2) have sizable bandgaps that change from indirect to direct in single layers, allowing applications such as transistors, photodetectors and electroluminescent devices. We review the historical development of TMDCs, methods for preparing atomically thin layers, their electronic and optical properties, and prospects for future advances in electronics and optoelectronics.
Hamiltonian formalism of two-dimensional Vlasov kinetic equation.
Pavlov, Maxim V
2014-12-08
In this paper, the two-dimensional Benney system describing long wave propagation of a finite depth fluid motion and the multi-dimensional Russo-Smereka kinetic equation describing a bubbly flow are considered. The Hamiltonian approach established by J. Gibbons for the one-dimensional Vlasov kinetic equation is extended to a multi-dimensional case. A local Hamiltonian structure associated with the hydrodynamic lattice of moments derived by D. J. Benney is constructed. A relationship between this hydrodynamic lattice of moments and the two-dimensional Vlasov kinetic equation is found. In the two-dimensional case, a Hamiltonian hydrodynamic lattice for the Russo-Smereka kinetic model is constructed. Simple hydrodynamic reductions are presented.
Control Operator for the Two-Dimensional Energized Wave Equation
Directory of Open Access Journals (Sweden)
Sunday Augustus REJU
2006-07-01
Full Text Available This paper studies the analytical model for the construction of the two-dimensional Energized wave equation. The control operator is given in term of space and time t independent variables. The integral quadratic objective cost functional is subject to the constraint of two-dimensional Energized diffusion, Heat and a source. The operator that shall be obtained extends the Conjugate Gradient method (ECGM as developed by Hestenes et al (1952, [1]. The new operator enables the computation of the penalty cost, optimal controls and state trajectories of the two-dimensional energized wave equation when apply to the Conjugate Gradient methods in (Waziri & Reju, LEJPT & LJS, Issues 9, 2006, [2-4] to appear in this series.
Two-Dimensional Electronic Spectroscopy Using Incoherent Light: Theoretical Analysis
Turner, Daniel B; Sutor, Erika J; Hendrickson, Rebecca A; Gealy, M W; Ulness, Darin J
2012-01-01
Electronic energy transfer in photosynthesis occurs over a range of time scales and under a variety of intermolecular coupling conditions. Recent work has shown that electronic coupling between chromophores can lead to coherent oscillations in two-dimensional electronic spectroscopy measurements of pigment-protein complexes measured with femtosecond laser pulses. A persistent issue in the field is to reconcile the results of measurements performed using femtosecond laser pulses with physiological illumination conditions. Noisy-light spectroscopy can begin to address this question. In this work we present the theoretical analysis of incoherent two-dimensional electronic spectroscopy, I(4) 2D ES. Simulations reveal diagonal peaks, cross peaks, and coherent oscillations similar to those observed in femtosecond two-dimensional electronic spectroscopy experiments. The results also expose fundamental differences between the femtosecond-pulse and noisy-light techniques; the differences lead to new challenges and opp...
A two-dimensional spin liquid in quantum kagome ice.
Carrasquilla, Juan; Hao, Zhihao; Melko, Roger G
2015-06-22
Actively sought since the turn of the century, two-dimensional quantum spin liquids (QSLs) are exotic phases of matter where magnetic moments remain disordered even at zero temperature. Despite ongoing searches, QSLs remain elusive, due to a lack of concrete knowledge of the microscopic mechanisms that inhibit magnetic order in materials. Here we study a model for a broad class of frustrated magnetic rare-earth pyrochlore materials called quantum spin ices. When subject to an external magnetic field along the [111] crystallographic direction, the resulting interactions contain a mix of geometric frustration and quantum fluctuations in decoupled two-dimensional kagome planes. Using quantum Monte Carlo simulations, we identify a set of interactions sufficient to promote a groundstate with no magnetic long-range order, and a gap to excitations, consistent with a Z2 spin liquid phase. This suggests an experimental procedure to search for two-dimensional QSLs within a class of pyrochlore quantum spin ice materials.
Spectral Radiative Properties of Two-Dimensional Rough Surfaces
Xuan, Yimin; Han, Yuge; Zhou, Yue
2012-12-01
Spectral radiative properties of two-dimensional rough surfaces are important for both academic research and practical applications. Besides material properties, surface structures have impact on the spectral radiative properties of rough surfaces. Based on the finite difference time domain algorithm, this paper studies the spectral energy propagation process on a two-dimensional rough surface and analyzes the effect of different factors such as the surface structure, angle, and polarization state of the incident wave on the spectral radiative properties of the two-dimensional rough surface. To quantitatively investigate the spatial distribution of energy reflected from the rough surface, the concept of the bidirectional reflectance distribution function is introduced. Correlation analysis between the reflectance and different impact factors is conducted to evaluate the influence degree. Comparison between the theoretical and experimental data is given to elucidate the accuracy of the computational code. This study is beneficial to optimizing the surface structures of optoelectronic devices such as solar cells.
Two dimensional convolute integers for machine vision and image recognition
Edwards, Thomas R.
1988-01-01
Machine vision and image recognition require sophisticated image processing prior to the application of Artificial Intelligence. Two Dimensional Convolute Integer Technology is an innovative mathematical approach for addressing machine vision and image recognition. This new technology generates a family of digital operators for addressing optical images and related two dimensional data sets. The operators are regression generated, integer valued, zero phase shifting, convoluting, frequency sensitive, two dimensional low pass, high pass and band pass filters that are mathematically equivalent to surface fitted partial derivatives. These operators are applied non-recursively either as classical convolutions (replacement point values), interstitial point generators (bandwidth broadening or resolution enhancement), or as missing value calculators (compensation for dead array element values). These operators show frequency sensitive feature selection scale invariant properties. Such tasks as boundary/edge enhancement and noise or small size pixel disturbance removal can readily be accomplished. For feature selection tight band pass operators are essential. Results from test cases are given.
Optical modulators with two-dimensional layered materials
Sun, Zhipei; Wang, Feng
2016-01-01
Light modulation is an essential operation in photonics and optoelectronics. With existing and emerging technologies increasingly demanding compact, efficient, fast and broadband optical modulators, high-performance light modulation solutions are becoming indispensable. The recent realization that two-dimensional layered materials could modulate light with superior performance has prompted intense research and significant advances, paving the way for realistic applications. In this review, we cover the state-of-the-art of optical modulators based on two-dimensional layered materials including graphene, transition metal dichalcogenides and black phosphorus. We discuss recent advances employing hybrid structures, such as two-dimensional heterostructures, plasmonic structures, and silicon/fibre integrated structures. We also take a look at future perspectives and discuss the potential of yet relatively unexplored mechanisms such as magneto-optic and acousto-optic modulation.
Directory of Open Access Journals (Sweden)
TIMCHENKO, L.
2012-11-01
Full Text Available Propositions necessary for development of parallel-hierarchical (PH network training methods are discussed in this article. Unlike already known structures of the artificial neural network, where non-normalized (absolute similarity criteria are used for comparison, the suggested structure uses a normalized criterion. Based on the analysis of training rules, a conclusion is made that application of two training methods with a teacher is optimal for PH network training: error correction-based training and memory-based training. Mathematical models of training and a combined method of PH network training for recognition of static and dynamic patterns are developed.
Kuznia, C. B.; Sawchuk, Alexander A.; Zhang, Liping; Hoanca, Bogdan; Hong, Sunkwang; Min, Chris; Pansatiankul, Dhawat E.; Alpaslan, Zahir Y.
2000-05-01
We present a networking and signal processing architecture called Transpar-TR (Translucent Smart Pixel Array-Token- Ring) that utilizes smart pixel technology to perform 2D parallel optical data transfer between digital processing nodes. Transpar-TR moves data through the network in the form of 3D packets (2D spatial and 1D time). By utilizing many spatial parallel channels, Transpar-TR can achieve high throughput, low latency communication between nodes, even with each channel operating at moderate data rates. The 2D array of optical channels is created by an array of smart pixels, each with an optical input and optical output. Each smart pixel consists of two sections, an optical network interface and ALU-based processor with local memory. The optical network interface is responsible for transmitting and receiving optical data packets using a slotted token ring network protocol. The smart pixel array operates as a single-instruction multiple-data processor when processing data. The Transpar-TR network, consisting of networked smart pixel arrays, can perform pipelined parallel processing very efficiently on 2D data structures such as images and video. This paper discusses the Transpar-TR implementation in which each node is the printed circuit board integration of a VCSEL-MSM chip, a transimpedance receiver array chip and an FPGA chip.
Two-dimensional superconductors with atomic-scale thickness
Uchihashi, Takashi
2017-01-01
Recent progress in two-dimensional superconductors with atomic-scale thickness is reviewed mainly from the experimental point of view. The superconducting systems treated here involve a variety of materials and forms: elemental metal ultrathin films and atomic layers on semiconductor surfaces; interfaces and superlattices of heterostructures made of cuprates, perovskite oxides, and rare-earth metal heavy-fermion compounds; interfaces of electric-double-layer transistors; graphene and atomic sheets of transition metal dichalcogenide; iron selenide and organic conductors on oxide and metal surfaces, respectively. Unique phenomena arising from the ultimate two dimensionality of the system and the physics behind them are discussed.
TreePM Method for Two-Dimensional Cosmological Simulations
Indian Academy of Sciences (India)
Suryadeep Ray
2004-09-01
We describe the two-dimensional TreePM method in this paper. The 2d TreePM code is an accurate and efficient technique to carry out large two-dimensional N-body simulations in cosmology. This hybrid code combines the 2d Barnes and Hut Tree method and the 2d Particle–Mesh method. We describe the splitting of force between the PM and the Tree parts. We also estimate error in force for a realistic configuration. Finally, we discuss some tests of the code.
Singular analysis of two-dimensional bifurcation system
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
Bifurcation properties of two-dimensional bifurcation system are studied in this paper.Universal unfolding and transition sets of the bifurcation equations are obtained.The whole parametric plane is divided into several different persistent regions according to the type of motion,and the different qualitative bifurcation diagrams in different persistent regions are given.The bifurcation properties of the two-dimensional bifurcation system are compared with its reduced one-dimensional system.It is found that the system which is reduced to one dimension has lost many bifurcation properties.
Critical Behaviour of a Two-Dimensional Random Antiferromagnet
DEFF Research Database (Denmark)
Als-Nielsen, Jens Aage; Birgeneau, R. J.; Guggenheim, H. J.
1976-01-01
A neutron scattering study of the order parameter, correlation length and staggered susceptibility of the two-dimensional random antiferromagnet Rb2Mn0.5Ni0.5F4 is reported. The system is found to exhibit a well-defined phase transition with critical exponents identical to those of the isomorphou...... pure materials K2NiF4 and K2MnF4. Thus, in these systems, which have the asymptotic critical behaviour of the two-dimensional Ising model, randomness has no measurable effect on the phase-transition behaviour....
Nonlinear excitations in two-dimensional molecular structures with impurities
DEFF Research Database (Denmark)
Gaididei, Yuri Borisovich; Rasmussen, Kim; Christiansen, Peter Leth
1995-01-01
We study the nonlinear dynamics of electronic excitations interacting with acoustic phonons in two-dimensional molecular structures with impurities. We show that the problem is reduced to the nonlinear Schrodinger equation with a varying coefficient. The latter represents the influence of the imp......We study the nonlinear dynamics of electronic excitations interacting with acoustic phonons in two-dimensional molecular structures with impurities. We show that the problem is reduced to the nonlinear Schrodinger equation with a varying coefficient. The latter represents the influence...... excitations. Analytical results are in good agreement with numerical simulations of the nonlinear Schrodinger equation....
Vortices in the Two-Dimensional Simple Exclusion Process
Bodineau, T.; Derrida, B.; Lebowitz, Joel L.
2008-06-01
We show that the fluctuations of the partial current in two dimensional diffusive systems are dominated by vortices leading to a different scaling from the one predicted by the hydrodynamic large deviation theory. This is supported by exact computations of the variance of partial current fluctuations for the symmetric simple exclusion process on general graphs. On a two-dimensional torus, our exact expressions are compared to the results of numerical simulations. They confirm the logarithmic dependence on the system size of the fluctuations of the partial flux. The impact of the vortices on the validity of the fluctuation relation for partial currents is also discussed in an Appendix.
Two-dimensional hazard estimation for longevity analysis
DEFF Research Database (Denmark)
Fledelius, Peter; Guillen, M.; Nielsen, J.P.
2004-01-01
the two-dimensional mortality surface. Furthermore we look at aggregated synthetic population metrics as 'population life expectancy' and 'population survival probability'. For Danish women these metrics indicate decreasing mortality with respect to chronological time. The metrics can not directly be used......We investigate developments in Danish mortality based on data from 1974-1998 working in a two-dimensional model with chronological time and age as the two dimensions. The analyses are done with non-parametric kernel hazard estimation techniques. The only assumption is that the mortality surface...... for analysis of economic implications arising from mortality changes....
Field analysis of two-dimensional focusing grating couplers
Borsboom, P.-P.; Frankena, H. J.
1995-05-01
A different technique was developed by which several two-dimensional dielectric optical gratings, consisting 100 or more corrugations, were treated in a numerical reliable approach. The numerical examples that were presented were restricted to gratings made up of sequences of waveguide sections symmetric about the x = 0 plane. The newly developed method was effectively used to investigate the field produced by a two-dimensional focusing grating coupler. Focal-region fields were determined for three symmetrical gratings with 19, 50, and 124 corrugations. For focusing grating coupler with limited length, high-frequency intensity variations were noted in the focal region.
Self-assembly of two-dimensional DNA crystals
Institute of Scientific and Technical Information of China (English)
SONG Cheng; CHEN Yaqing; WEI Shuai; YOU Xiaozeng; XIAO Shoujun
2004-01-01
Self-assembly of synthetic oligonucleotides into two-dimensional lattices presents a 'bottom-up' approach to the fabrication of devices on nanometer scale. We report the design and observation of two-dimensional crystalline forms of DNAs that are composed of twenty-one plane oligonucleotides and one phosphate-modified oligonucleotide. These synthetic sequences are designed to self-assemble into four double-crossover (DX) DNA tiles. The 'sticky ends' of these tiles that associate according to Watson-Crick's base pairing are programmed to build up specific periodic patterns upto tens of microns. The patterned crystals are visualized by the transmission electron microscopy.
Dynamics of vortex interactions in two-dimensional flows
DEFF Research Database (Denmark)
Juul Rasmussen, J.; Nielsen, A.H.; Naulin, V.
2002-01-01
a critical value, a(c). Using the Weiss-field, a(c) is estimated for vortex patches. Introducing an effective radius for vortices with distributed vorticity, we find that 3.3 a(c) ...The dynamics and interaction of like-signed vortex structures in two dimensional flows are investigated by means of direct numerical solutions of the two-dimensional Navier-Stokes equations. Two vortices with distributed vorticity merge when their distance relative to their radius, d/R-0l. is below...
Two-dimensional assignment with merged measurements using Langrangrian relaxation
Briers, Mark; Maskell, Simon; Philpott, Mark
2004-01-01
Closely spaced targets can result in merged measurements, which complicate data association. Such merged measurements violate any assumption that each measurement relates to a single target. As a result, it is not possible to use the auction algorithm in its simplest form (or other two-dimensional assignment algorithms) to solve the two-dimensional target-to-measurement assignment problem. We propose an approach that uses the auction algorithm together with Lagrangian relaxation to incorporate the additional constraints resulting from the presence of merged measurements. We conclude with some simulated results displaying the concepts introduced, and discuss the application of this research within a particle filter context.
Two-dimensional lattice Boltzmann model for magnetohydrodynamics.
Schaffenberger, Werner; Hanslmeier, Arnold
2002-10-01
We present a lattice Boltzmann model for the simulation of two-dimensional magnetohydro dynamic (MHD) flows. The model is an extension of a hydrodynamic lattice Boltzman model with 9 velocities on a square lattice resulting in a model with 17 velocities. Earlier lattice Boltzmann models for two-dimensional MHD used a bidirectional streaming rule. However, the use of such a bidirectional streaming rule is not necessary. In our model, the standard streaming rule is used, allowing smaller viscosities. To control the viscosity and the resistivity independently, a matrix collision operator is used. The model is then applied to the Hartmann flow, giving reasonable results.
Quasinormal frequencies of asymptotically flat two-dimensional black holes
Lopez-Ortega, A
2011-01-01
We discuss whether the minimally coupled massless Klein-Gordon and Dirac fields have well defined quasinormal modes in single horizon, asymptotically flat two-dimensional black holes. To get the result we solve the equations of motion in the massless limit and we also calculate the effective potentials of Schrodinger type equations. Furthermore we calculate exactly the quasinormal frequencies of the Dirac field propagating in the two-dimensional uncharged Witten black hole. We compare our results on its quasinormal frequencies with other already published.
Spin dynamics in a two-dimensional quantum gas
DEFF Research Database (Denmark)
Pedersen, Poul Lindholm; Gajdacz, Miroslav; Deuretzbacher, Frank
2014-01-01
We have investigated spin dynamics in a two-dimensional quantum gas. Through spin-changing collisions, two clouds with opposite spin orientations are spontaneously created in a Bose-Einstein condensate. After ballistic expansion, both clouds acquire ring-shaped density distributions with superimp......We have investigated spin dynamics in a two-dimensional quantum gas. Through spin-changing collisions, two clouds with opposite spin orientations are spontaneously created in a Bose-Einstein condensate. After ballistic expansion, both clouds acquire ring-shaped density distributions...
Comparison of GPU- and CPU-implementations of mean-firing rate neural networks on parallel hardware.
Dinkelbach, Helge Ülo; Vitay, Julien; Beuth, Frederik; Hamker, Fred H
2012-01-01
Modern parallel hardware such as multi-core processors (CPUs) and graphics processing units (GPUs) have a high computational power which can be greatly beneficial to the simulation of large-scale neural networks. Over the past years, a number of efforts have focused on developing parallel algorithms and simulators best suited for the simulation of spiking neural models. In this article, we aim at investigating the advantages and drawbacks of the CPU and GPU parallelization of mean-firing rate neurons, widely used in systems-level computational neuroscience. By comparing OpenMP, CUDA and OpenCL implementations towards a serial CPU implementation, we show that GPUs are better suited than CPUs for the simulation of very large networks, but that smaller networks would benefit more from an OpenMP implementation. As this performance strongly depends on data organization, we analyze the impact of various factors such as data structure, memory alignment and floating precision. We then discuss the suitability of the different hardware depending on the networks' size and connectivity, as random or sparse connectivities in mean-firing rate networks tend to break parallel performance on GPUs due to the violation of coalescence.
Directory of Open Access Journals (Sweden)
Narayanan Manikandan
2016-01-01
Full Text Available Software development life cycle has been characterized by destructive disconnects between activities like planning, analysis, design, and programming. Particularly software developed with prediction based results is always a big challenge for designers. Time series data forecasting like currency exchange, stock prices, and weather report are some of the areas where an extensive research is going on for the last three decades. In the initial days, the problems with financial analysis and prediction were solved by statistical models and methods. For the last two decades, a large number of Artificial Neural Networks based learning models have been proposed to solve the problems of financial data and get accurate results in prediction of the future trends and prices. This paper addressed some architectural design related issues for performance improvement through vectorising the strengths of multivariate econometric time series models and Artificial Neural Networks. It provides an adaptive approach for predicting exchange rates and it can be called hybrid methodology for predicting exchange rates. This framework is tested for finding the accuracy and performance of parallel algorithms used.
Manikandan, Narayanan; Subha, Srinivasan
2016-01-01
Software development life cycle has been characterized by destructive disconnects between activities like planning, analysis, design, and programming. Particularly software developed with prediction based results is always a big challenge for designers. Time series data forecasting like currency exchange, stock prices, and weather report are some of the areas where an extensive research is going on for the last three decades. In the initial days, the problems with financial analysis and prediction were solved by statistical models and methods. For the last two decades, a large number of Artificial Neural Networks based learning models have been proposed to solve the problems of financial data and get accurate results in prediction of the future trends and prices. This paper addressed some architectural design related issues for performance improvement through vectorising the strengths of multivariate econometric time series models and Artificial Neural Networks. It provides an adaptive approach for predicting exchange rates and it can be called hybrid methodology for predicting exchange rates. This framework is tested for finding the accuracy and performance of parallel algorithms used. PMID:26881271
Manikandan, Narayanan; Subha, Srinivasan
2016-01-01
Software development life cycle has been characterized by destructive disconnects between activities like planning, analysis, design, and programming. Particularly software developed with prediction based results is always a big challenge for designers. Time series data forecasting like currency exchange, stock prices, and weather report are some of the areas where an extensive research is going on for the last three decades. In the initial days, the problems with financial analysis and prediction were solved by statistical models and methods. For the last two decades, a large number of Artificial Neural Networks based learning models have been proposed to solve the problems of financial data and get accurate results in prediction of the future trends and prices. This paper addressed some architectural design related issues for performance improvement through vectorising the strengths of multivariate econometric time series models and Artificial Neural Networks. It provides an adaptive approach for predicting exchange rates and it can be called hybrid methodology for predicting exchange rates. This framework is tested for finding the accuracy and performance of parallel algorithms used.
Parallel Void Thread in Long-Reach Ethernet Passive Optical Networks
Elrasad, Amr
2015-06-25
This work investigates void filling (idle periods) in long-reach Ethernet passive optical networks. We focus on reducing grant delays and hence reducing the average packet delay. We introduce a novel approach called parallel void thread (PVT), which allocates bandwidth grants during voids baseless of bandwidth requests. We introduce three different grant sizing schemes for PVT, namely void extension, count controlled batch void filling, and size controlled batch void filling. The proposed approaches canbe integrated with almost all of the previously reported dynamic bandwidth allocation schemes. Unlike other void filling schemes, PVT is less sensitive to the differential distance between optical network units and can work very well in the case of limited differential distances. We have analytically investigated the packet delay and derived a bound condition for PVT to outperform the other competitors. We support our work with extensive simulation study considering bursty traffic with long range dependence for both the single-class and differentiated services (DiffServ) scenarios. Numerical results show delay reduction up to 35% compared with the non-void filling scheme for the single-class scenario. For DiffServ traffic, PVT achieves delay reduction up to 80% for expedited forward traffic, 52% for assured forward traffic, and 56% for best effort traffic. © 2015 OSA.
Directory of Open Access Journals (Sweden)
H. L. Sneha
2013-01-01
Full Text Available The current focus in defense arena is towards the stealth technology with an emphasis to control the radar cross-section (RCS. The scattering from the antennas mounted over the platform is of prime importance especially for a low-observable aerospace vehicle. This paper presents the analysis of the scattering cross section of a uniformly spaced linear dipole array. Two types of feed networks, that is, series and parallel feed networks, are considered. The total RCS of phased array with either kind of feed network is obtained by following the signal as it enters through the aperture and travels through the feed network. The RCS estimation of array is done including the mutual coupling effect between the dipole elements in three configurations, that is, side-by-side, collinear, and parallel-in-echelon. The results presented can be useful while designing a phased array with optimum performance towards low observability.
Institute of Scientific and Technical Information of China (English)
Xu Quan; Tian Qiang
2009-01-01
This paper discusses the two-dimensional discrete monatomic Fermi-Pasta-Ulam lattice, by using the method of multiple-scale and the quasi-discreteness approach. By taking into account the interaction between the atoms in the lattice and their nearest neighbours, it obtains some classes of two-dimensional local models as follows: two-dimensional bright and dark discrete soliton trains, two-dimensional bright and dark line discrete breathers, and two-dimensional bright and dark discrete breather.
Unconventional critical activated scaling of two-dimensional quantum spin glasses
Matoz-Fernandez, D. A.; Romá, F.
2016-07-01
We study the critical behavior of two-dimensional short-range quantum spin glasses by numerical simulations. Using a parallel tempering algorithm, we calculate the Binder cumulant for the Ising spin glass in a transverse magnetic field with two different short-range bond distributions, the bimodal and the Gaussian ones. Through an exhaustive finite-size analysis, we show that the cumulant probably follows an unconventional activated scaling, which we interpret as new evidence supporting the hypothesis that the quantum critical behavior is governed by an infinite randomness fixed point.
Photon-assisted spin transport in a two-dimensional electron gas
Fistul, M. V.; Efetov, K. B.
2007-01-01
We study spin-dependent transport in a two-dimensional electron gas subject to an external step-like potential $V(x)$ and irradiated by an electromagnetic field (EF). In the absence of EF the electronic spectrum splits into spin sub-bands originating from the "Rashba" spin-orbit coupling. We show that the resonant interaction of propagating electrons with the component EF parallel to the barrier induces a \\textit{% non-equilibrium dynamic gap} $(2\\Delta_{R})$ between the spin sub-bands. Exist...
Optical matrix for clock distribution and synchronous operation in two-dimensional array devices
Lee, K. S.; Shu, C.
1996-06-01
A scheme to generate an optical matrix from a mode-locked Nd:YAG laser has been theoretically explored and experimentally demonstrated. The matrix consists of highly synchronized and sequentially delayed optical pulses suitable for use with two-dimensional array optoelectronic devices and clock distribution system. The output pulses have the same state of polarization and no timing jitter is produced among the elements. Encoded outputs have been generated from the matrix using a set of photomasks. This technique can be applied to high-speed optical parallel processing.
Spectroscopy of charge transfer complexes of four amino acids as organic two-dimensional conductors
Energy Technology Data Exchange (ETDEWEB)
Padhiyar, Ashvin; Patel, A J; Oza, A T [Department of Physics, Sardar Patel University, Vallabh Vidyanagar-388 120, Gujarat (India)
2007-12-05
It is found in this study that four amino acids, namely asparagine, arginine, histidine and glutamine form two-dimensional conducting systems which are charge transfer complexes (CTCs) with organic acceptors like TCNQ, TCNE, chloranil, DDQ, TNF and iodine. It is verified using optical absorption edges that these are 2d conductors like transition metal dichalcogenides obeying absorption functions different from 1d and 3d conductors. This 2d nature is related to the network of intermolecular H-bonding in these complexes, which leads to a global H-bonded network resulting in the absence of local deformation due to the relaxation of strain.
Spectroscopy of charge transfer complexes of four amino acids as organic two-dimensional conductors
Padhiyar, Ashvin; Patel, A. J.; Oza, A. T.
2007-12-01
It is found in this study that four amino acids, namely asparagine, arginine, histidine and glutamine form two-dimensional conducting systems which are charge transfer complexes (CTCs) with organic acceptors like TCNQ, TCNE, chloranil, DDQ, TNF and iodine. It is verified using optical absorption edges that these are 2d conductors like transition metal dichalcogenides obeying absorption functions different from 1d and 3d conductors. This 2d nature is related to the network of intermolecular H-bonding in these complexes, which leads to a global H-bonded network resulting in the absence of local deformation due to the relaxation of strain.
Mapping two-dimensional polar active fluids to two-dimensional soap and one-dimensional sandblasting
Chen, Leiming; Lee, Chiu Fan; Toner, John
2016-07-01
Active fluids and growing interfaces are two well-studied but very different non-equilibrium systems. Each exhibits non-equilibrium behaviour distinct from that of their equilibrium counterparts. Here we demonstrate a surprising connection between these two: the ordered phase of incompressible polar active fluids in two spatial dimensions without momentum conservation, and growing one-dimensional interfaces (that is, the 1+1-dimensional Kardar-Parisi-Zhang equation), in fact belong to the same universality class. This universality class also includes two equilibrium systems: two-dimensional smectic liquid crystals, and a peculiar kind of constrained two-dimensional ferromagnet. We use these connections to show that two-dimensional incompressible flocks are robust against fluctuations, and exhibit universal long-ranged, anisotropic spatio-temporal correlations of those fluctuations. We also thereby determine the exact values of the anisotropy exponent ζ and the roughness exponents χx,y that characterize these correlations.
Kinetic Theory of a Confined Quasi-Two-Dimensional Gas of Hard Spheres
Directory of Open Access Journals (Sweden)
J. Javier Brey
2017-02-01
Full Text Available The dynamics of a system of hard spheres enclosed between two parallel plates separated a distance smaller than two particle diameters is described at the level of kinetic theory. The interest focuses on the behavior of the quasi-two-dimensional fluid seen when looking at the system from above or below. In the first part, a collisional model for the effective two-dimensional dynamics is analyzed. Although it is able to describe quite well the homogeneous evolution observed in the experiments, it is shown that it fails to predict the existence of non-equilibrium phase transitions, and in particular, the bimodal regime exhibited by the real system. A critical revision analysis of the model is presented , and as a starting point to get a more accurate description, the Boltzmann equation for the quasi-two-dimensional gas has been derived. In the elastic case, the solutions of the equation verify an H-theorem implying a monotonic tendency to a non-uniform steady state. As an example of application of the kinetic equation, here the evolution equations for the vertical and horizontal temperatures of the system are derived in the homogeneous approximation, and the results compared with molecular dynamics simulation results.
Waiting Time Dynamics in Two-Dimensional Infrared Spectroscopy
Jansen, Thomas L. C.; Knoester, Jasper
We review recent work on the waiting time dynamics of coherent two-dimensional infrared (2DIR) spectroscopy. This dynamics can reveal chemical and physical processes that take place on the femto- and picosecond time scale, which is faster than the time scale that may be probed by, for example,
The partition function of two-dimensional string theory
Dijkgraaf, Robbert; Moore, Gregory; Plesser, Ronen
1993-04-01
We derive a compact and explicit expression for the generating functional of all correlation functions of tachyon operators in two-dimensional string theory. This expression makes manifest relations of the c = 1 system to KP flow nd W 1 + ∞ constraints. Moreover we derive a Kontsevich-Penner integral representation of this generating functional.
The partition function of two-dimensional string theory
Energy Technology Data Exchange (ETDEWEB)
Dijkgraaf, R. (School of Natural Sciences, Inst. for Advanced Study, Princeton, NJ (United States) Dept. of Mathematics, Univ. Amsterdam (Netherlands)); Moore, G.; Plesser, R. (Dept. of Physics, Yale Univ., New Haven, CT (United States))
1993-04-12
We derive a compact and explicit expression for the generating functional of all correlation functions of tachyon operators in two-dimensional string theory. This expression makes manifest relations of the c=1 system to KP flow and W[sub 1+[infinity
Two-Dimensional Electronic Spectroscopy of a Model Dimer System
Directory of Open Access Journals (Sweden)
Prokhorenko V.I.
2013-03-01
Full Text Available Two-dimensional spectra of a dimer were measured to determine the timescale for electronic decoherence at room temperature. Anti-correlated beats in the crosspeaks were observed only during the period corresponding to the measured homogeneous lifetime.
Torque magnetometry studies of two-dimensional electron systems
Schaapman, Maaike Ruth
2004-01-01
This thesis describes a study of the magnetization two-dimensional electron gases (2DEGs). To detect the typically small magnetization, a sensitive magnetometer with optical angular detection was developed. The magnetometer uses a quadrant detector to measure the rotation of the sample. By mounting
Low-frequency scattering from two-dimensional perfect conductors
DEFF Research Database (Denmark)
Hansen, Thorkild; Yaghjian, A.D
1991-01-01
Exact expressions have been obtained for the leading terms in the low-frequency expansions of the far fields scattered from three different types of two-dimensional perfect conductors: a cylinder with finite cross section, a cylindrical bump on an infinite ground plane, and a cylindrical dent...
Two-Dimensional Mesoscale-Ordered Conducting Polymers
Liu, Shaohua; Zhang, Jian; Dong, Renhao; Gordiichuk, Pavlo; Zhang, Tao; Zhuang, Xiaodong; Mai, Yiyong; Liu, Feng; Herrmann, Andreas; Feng, Xinliang
2016-01-01
Despite the availability of numerous two-dimensional (2D) materials with structural ordering at the atomic or molecular level, direct construction of mesoscale-ordered superstructures within a 2D monolayer remains an enormous challenge. Here, we report the synergic manipulation of two types of assem
Piezoelectricity and Piezomagnetism: Duality in two-dimensional checkerboards
Fel, Leonid G.
2002-05-01
The duality approach in two-dimensional two-component regular checkerboards is extended to piezoelectricity and piezomagnetism. The relation between the effective piezoelectric and piezomagnetic moduli is found for a checkerboard with the p6'mm'-plane symmetry group (dichromatic triangle).
Specification of a Two-Dimensional Test Case
DEFF Research Database (Denmark)
Nielsen, Peter Vilhelm
This paper describes the geometry and other boundary conditions for a test case which can be used to test different two-dimensional CFD codes in the lEA Annex 20 work. The given supply opening is large compared with practical openings. Therefore, this geometry will reduce the need for a high number...... of grid points in the wall jet region....
Operator splitting for two-dimensional incompressible fluid equations
Holden, Helge; Karper, Trygve K
2011-01-01
We analyze splitting algorithms for a class of two-dimensional fluid equations, which includes the incompressible Navier-Stokes equations and the surface quasi-geostrophic equation. Our main result is that the Godunov and Strang splitting methods converge with the expected rates provided the initial data are sufficiently regular.
Chaotic dynamics for two-dimensional tent maps
Pumariño, Antonio; Ángel Rodríguez, José; Carles Tatjer, Joan; Vigil, Enrique
2015-02-01
For a two-dimensional extension of the classical one-dimensional family of tent maps, we prove the existence of an open set of parameters for which the respective transformation presents a strange attractor with two positive Lyapounov exponents. Moreover, periodic orbits are dense on this attractor and the attractor supports a unique ergodic invariant probability measure.
Divorticity and dihelicity in two-dimensional hydrodynamics
DEFF Research Database (Denmark)
Shivamoggi, B.K.; van Heijst, G.J.F.; Juul Rasmussen, Jens
2010-01-01
A framework is developed based on the concepts of divorticity B (≡×ω, ω being the vorticity) and dihelicity g (≡vB) for discussing the theoretical structure underlying two-dimensional (2D) hydrodynamics. This formulation leads to the global and Lagrange invariants that could impose significant...
Spin-orbit torques in two-dimensional Rashba ferromagnets
Qaiumzadeh, A.; Duine, R. A.|info:eu-repo/dai/nl/304830127; Titov, M.
2015-01-01
Magnetization dynamics in single-domain ferromagnets can be triggered by a charge current if the spin-orbit coupling is sufficiently strong. We apply functional Keldysh theory to investigate spin-orbit torques in metallic two-dimensional Rashba ferromagnets in the presence of spin-dependent
Numerical blowup in two-dimensional Boussinesq equations
Yin, Zhaohua
2009-01-01
In this paper, we perform a three-stage numerical relay to investigate the finite time singularity in the two-dimensional Boussinesq approximation equations. The initial asymmetric condition is the middle-stage output of a $2048^2$ run, the highest resolution in our study is $40960^2$, and some signals of numerical blowup are observed.
Exact two-dimensional superconformal R symmetry and c extremization.
Benini, Francesco; Bobev, Nikolay
2013-02-08
We uncover a general principle dubbed c extremization, which determines the exact R symmetry of a two-dimensional unitary superconformal field theory with N=(0,2) supersymmetry. To illustrate its utility, we study superconformal theories obtained by twisted compactifications of four-dimensional N=4 super-Yang-Mills theory on Riemann surfaces and construct their gravity duals.
Zero sound in a two-dimensional dipolar Fermi gas
Lu, Z.K.; Matveenko, S.I.; Shlyapnikov, G.V.
2013-01-01
We study zero sound in a weakly interacting two-dimensional (2D) gas of single-component fermionic dipoles (polar molecules or atoms with a large magnetic moment) tilted with respect to the plane of their translational motion. It is shown that the propagation of zero sound is provided by both mean-f
Topology optimization of two-dimensional elastic wave barriers
DEFF Research Database (Denmark)
Van Hoorickx, C.; Sigmund, Ole; Schevenels, M.
2016-01-01
Topology optimization is a method that optimally distributes material in a given design domain. In this paper, topology optimization is used to design two-dimensional wave barriers embedded in an elastic halfspace. First, harmonic vibration sources are considered, and stiffened material is insert...
Non perturbative methods in two dimensional quantum field theory
Abdalla, Elcio; Rothe, Klaus D
1991-01-01
This book is a survey of methods used in the study of two-dimensional models in quantum field theory as well as applications of these theories in physics. It covers the subject since the first model, studied in the fifties, up to modern developments in string theories, and includes exact solutions, non-perturbative methods of study, and nonlinear sigma models.
Thermodynamics of Two-Dimensional Black-Holes
Nappi, Chiara R.; Pasquinucci, Andrea
1992-01-01
We explore the thermodynamics of a general class of two dimensional dilatonic black-holes. A simple prescription is given that allows us to compute the mass, entropy and thermodynamic potentials, with results in agreement with those obtained by other methods, when available.
Influence of index contrast in two dimensional photonic crystal lasers
DEFF Research Database (Denmark)
Jørgensen, Mette Marie; Petersen, Sidsel Rübner; Christiansen, Mads Brøkner;
2010-01-01
The influence of index contrast variations for obtaining single-mode operation and low threshold in dye doped polymer two dimensional photonic crystal (PhC) lasers is investigated. We consider lasers made from Pyrromethene 597 doped Ormocore imprinted with a rectangular lattice PhC having a cavit...
Magnetic order in two-dimensional nanoparticle assemblies
Georgescu, M
2008-01-01
This thesis involves a fundamental study of two-dimensional arrays of magnetic nanoparticles using non-contact Atomic Force Microscopy, Magnetic Force Microscopy, and Atomic Force Spectroscopy. The goal is to acquire a better understanding of the interactions between magnetic nanoparticles and the
Dynamical phase transitions in the two-dimensional ANNNI model
Energy Technology Data Exchange (ETDEWEB)
Barber, M.N.; Derrida, B.
1988-06-01
We study the phase diagram of the two-dimensional anisotropic next-nearest neighbor Ising (ANNNI) model by comparing the time evolution of two distinct spin configurations submitted to the same thermal noise. We clearly se several dynamical transitions between ferromagnetic, paramagnetic, antiphase, and floating phases. These dynamical transitions seem to occur rather close to the transition lines determined previously in the literature.
Two-dimensional static black holes with pointlike sources
Melis, M
2004-01-01
We study the static black hole solutions of generalized two-dimensional dilaton-gravity theories generated by pointlike mass sources, in the hypothesis that the matter is conformally coupled. We also discuss the motion of test particles. Due to conformal coupling, these follow the geodesics of a metric obtained by rescaling the canonical metric with the dilaton.
Magnetic order in two-dimensional nanoparticle assemblies
Georgescu, M
2008-01-01
This thesis involves a fundamental study of two-dimensional arrays of magnetic nanoparticles using non-contact Atomic Force Microscopy, Magnetic Force Microscopy, and Atomic Force Spectroscopy. The goal is to acquire a better understanding of the interactions between magnetic nanoparticles and the r
Two-Dimensional Chirality in Three-Dimensional Chemistry.
Wintner, Claude E.
1983-01-01
The concept of two-dimensional chirality is used to enhance students' understanding of three-dimensional stereochemistry. This chirality is used as a key to teaching/understanding such concepts as enaniotropism, diastereotopism, pseudoasymmetry, retention/inversion of configuration, and stereochemical results of addition to double bonds. (JN)
Field analysis of two-dimensional focusing grating
Borsboom, P.P.; Frankena, H.J.
1995-01-01
The method that we have developed [P-P. Borsboom, Ph.D. dissertation (Delft University of Technology, Delft, The Netherlands); P-P. Borsboom and H. J. Frankena, J. Opt. Soc. Am. A 12, 1134–1141 (1995)] is successfully applied to a two-dimensional focusing grating coupler. The field in the focal regi
Torque magnetometry studies of two-dimensional electron systems
Schaapman, Maaike Ruth
2004-01-01
This thesis describes a study of the magnetization two-dimensional electron gases (2DEGs). To detect the typically small magnetization, a sensitive magnetometer with optical angular detection was developed. The magnetometer uses a quadrant detector to measure the rotation of the sample. By mounting
Two-Dimensional Mesoscale-Ordered Conducting Polymers
Liu, Shaohua; Zhang, Jian; Dong, Renhao; Gordiichuk, Pavlo; Zhang, Tao; Zhuang, Xiaodong; Mai, Yiyong; Liu, Feng; Herrmann, Andreas; Feng, Xinliang
2016-01-01
Despite the availability of numerous two-dimensional (2D) materials with structural ordering at the atomic or molecular level, direct construction of mesoscale-ordered superstructures within a 2D monolayer remains an enormous challenge. Here, we report the synergic manipulation of two types of
Vibrations of Thin Piezoelectric Shallow Shells: Two-Dimensional Approximation
Indian Academy of Sciences (India)
N Sabu
2003-08-01
In this paper we consider the eigenvalue problem for piezoelectric shallow shells and we show that, as the thickness of the shell goes to zero, the eigensolutions of the three-dimensional piezoelectric shells converge to the eigensolutions of a two-dimensional eigenvalue problem.
Two-dimensional effects in nonlinear Kronig-Penney models
DEFF Research Database (Denmark)
Gaididei, Yuri Borisovich; Christiansen, Peter Leth; Rasmussen, Kim
1997-01-01
An analysis of two-dimensional (2D) effects in the nonlinear Kronig-Penney model is presented. We establish an effective one-dimensional description of the 2D effects, resulting in a set of pseudodifferential equations. The stationary states of the 2D system and their stability is studied...
Forensic potential of comprehensive two-dimensional gas chromatography
Sampat, A.; Lopatka, M.; Sjerps, M.; Vivo-Truyols, G.; Schoenmakers, P.; van Asten, A.
2016-01-01
In this study, the application of comprehensive two-dimensional (2D) gas chromatography (GC × GC) in forensic science is reviewed. The peer-reviewed publications on the forensic use of GC × GC and 2D gas chromatography with mass spectrometric detection (GC × GC-MS) have been studied in detail, not o
Easy interpretation of optical two-dimensional correlation spectra
Lazonder, K.; Pshenichnikov, M.S.; Wiersma, D.A.
2006-01-01
We demonstrate that the value of the underlying frequency-frequency correlation function can be retrieved from a two-dimensional optical correlation spectrum through a simple relationship. The proposed method yields both intuitive clues and a quantitative measure of the dynamics of the system. The t
Two Dimensional F(R) Horava-Lifshitz Gravity
Kluson, J
2016-01-01
We study two-dimensional F(R) Horava-Lifshitz gravity from the Hamiltonian point of view. We determine constraints structure with emphasis on the careful separation of the second class constraints and global first class constraints. We determine number of physical degrees of freedom and also discuss gauge fixing of the global first class constraints.
Localization of Tight Closure in Two-Dimensional Rings
Indian Academy of Sciences (India)
Kamran Divaani-Aazar; Massoud Tousi
2005-02-01
It is shown that tight closure commutes with localization in any two-dimensional ring of prime characteristic if either is a Nagata ring or possesses a weak test element. Moreover, it is proved that tight closure commutes with localization at height one prime ideals in any ring of prime characteristic.
Cryptanalysis of the Two-Dimensional Circulation Encryption Algorithm
Directory of Open Access Journals (Sweden)
Bart Preneel
2005-07-01
Full Text Available We analyze the security of the two-dimensional circulation encryption algorithm (TDCEA, recently published by Chen et al. in this journal. We show that there are several flaws in the algorithm and describe some attacks. We also address performance issues in current cryptographic designs.
New directions in science and technology: two-dimensional crystals
Energy Technology Data Exchange (ETDEWEB)
Neto, A H Castro [Graphene Research Centre, National University of Singapore, 2 Science Drive 3, Singapore 117542 (Singapore); Novoselov, K, E-mail: phycastr@nus.edu.sg, E-mail: konstantin.novoselov@manchester.ac.uk [School of Physics and Astronomy, University of Manchester, Oxford Road, Manchester, M13 9PL (United Kingdom)
2011-08-15
Graphene is possibly one of the largest and fastest growing fields in condensed matter research. However, graphene is only one example in a large class of two-dimensional crystals with unusual properties. In this paper we briefly review the properties of graphene and look at the exciting possibilities that lie ahead.
Boundary-value problems for two-dimensional canonical systems
Hassi, Seppo; De Snoo, H; Winkler, Henrik
2000-01-01
The two-dimensional canonical system Jy' = -lHy where the nonnegative Hamiltonian matrix function H(x) is trace-normed on (0,∞) has been studied in a function-theoretic way by L. de Branges. We show that the Hamiltonian system induces a closed symmetric relation which can be reduced to a, not necess
On the continua in two-dimensional nonadiabatic magnetohydrodynamic spectra
De Ploey, A.; Van der Linden, R. A. M.; Belien, A. J. C.
2000-01-01
The equations for the continuous subspectra of the linear magnetohydrodynamic (MHD) normal modes spectrum of two-dimensional (2D) plasmas are derived in general curvilinear coordinates, taking nonadiabatic effects in the energy equation into account. Previously published derivations of continuous sp
Dislocation climb in two-dimensional discrete dislocation dynamics
Davoudi, K.M.; Nicola, L.; Vlassak, J.J.
2012-01-01
In this paper, dislocation climb is incorporated in a two-dimensional discrete dislocation dynamics model. Calculations are carried out for polycrystalline thin films, passivated on one or both surfaces. Climb allows dislocations to escape from dislocation pile-ups and reduces the strain-hardening r
SAR Processing Based On Two-Dimensional Transfer Function
Chang, Chi-Yung; Jin, Michael Y.; Curlander, John C.
1994-01-01
Exact transfer function, ETF, is two-dimensional transfer function that constitutes basis of improved frequency-domain-convolution algorithm for processing synthetic-aperture-radar, SAR data. ETF incorporates terms that account for Doppler effect of motion of radar relative to scanned ground area and for antenna squint angle. Algorithm based on ETF outperforms others.
Sound waves in two-dimensional ducts with sinusoidal walls
Nayfeh, A. H.
1974-01-01
The method of multiple scales is used to analyze the wave propagation in two-dimensional hard-walled ducts with sinusoidal walls. For traveling waves, resonance occurs whenever the wall wavenumber is equal to the difference of the wavenumbers of any two duct acoustic modes. The results show that neither of these resonating modes could occur without strongly generating the other.
Confined two-dimensional fermions at finite density
De Francia, M; Loewe, M; Santangelo, E M; De Francia, M; Falomir, H; Loewe, M; Santangelo, E M
1995-01-01
We introduce the chemical potential in a system of two-dimensional massless fermions, confined to a finite region, by imposing twisted boundary conditions in the Euclidean time direction. We explore in this simple model the application of functional techniques which could be used in more complicated situations.
Imperfect two-dimensional topological insulator field-effect transistors
Vandenberghe, William G.; Fischetti, Massimo V.
2017-01-01
To overcome the challenge of using two-dimensional materials for nanoelectronic devices, we propose two-dimensional topological insulator field-effect transistors that switch based on the modulation of scattering. We model transistors made of two-dimensional topological insulator ribbons accounting for scattering with phonons and imperfections. In the on-state, the Fermi level lies in the bulk bandgap and the electrons travel ballistically through the topologically protected edge states even in the presence of imperfections. In the off-state the Fermi level moves into the bandgap and electrons suffer from severe back-scattering. An off-current more than two-orders below the on-current is demonstrated and a high on-current is maintained even in the presence of imperfections. At low drain-source bias, the output characteristics are like those of conventional field-effect transistors, at large drain-source bias negative differential resistance is revealed. Complementary n- and p-type devices can be made enabling high-performance and low-power electronic circuits using imperfect two-dimensional topological insulators. PMID:28106059
Bounds on the capacity of constrained two-dimensional codes
DEFF Research Database (Denmark)
Forchhammer, Søren; Justesen, Jørn
2000-01-01
Bounds on the capacity of constrained two-dimensional (2-D) codes are presented. The bounds of Calkin and Wilf apply to first-order symmetric constraints. The bounds are generalized in a weaker form to higher order and nonsymmetric constraints. Results are given for constraints specified by run...
Miniature sensor for two-dimensional magnetic field distributions
Fluitman, J.H.J.; Krabbe, H.W.
1972-01-01
Describes a simple method of production of a sensor for two-dimensional magnetic field distributions. The sensor consists of a strip of Ni-Fe(81-19), of which the magnetoresistance is utilized. Typical dimensions of the strip, placed at the edge of a glass substrate, are: length 100 mu m, width 2 or
Forensic potential of comprehensive two-dimensional gas chromatography
Sampat, A.; Lopatka, M.; Sjerps, M.; Vivo-Truyols, G.; Schoenmakers, P.; van Asten, A.
2016-01-01
In this study, the application of comprehensive two-dimensional (2D) gas chromatography (GC × GC) in forensic science is reviewed. The peer-reviewed publications on the forensic use of GC × GC and 2D gas chromatography with mass spectrometric detection (GC × GC-MS) have been studied in detail, not o
Spontaneous emission in two-dimensional photonic crystal microcavities
DEFF Research Database (Denmark)
Søndergaard, Thomas
2000-01-01
The properties of the radiation field in a two-dimensional photonic crystal with and without a microcavity introduced are investigated through the concept of the position-dependent photon density of states. The position-dependent rate of spontaneous radiative decay for a two-level atom with random...
Linkage analysis by two-dimensional DNA typing
te Meerman, G J; Mullaart, E; van der Meulen, M A; den Daas, J H; Morolli, B; Uitterlinden, A G; Vijg, J
1993-01-01
In two-dimensional (2-D) DNA typing, genomic DNA fragments are separated, first according to size by electrophoresis in a neutral polyacrylamide gel and second according to sequence by denaturing gradient gel electrophoresis, followed by hybridization analysis using micro- and minisatellite core pro
Phase conjugated Andreev backscattering in two-dimensional ballistic cavities
Morpurgo, A.F.; Holl, S.; Wees, B.J.van; Klapwijk, T.M; Borghs, G.
1997-01-01
We have experimentally investigated transport in two-dimensional ballistic cavities connected to a point contact and to two superconducting electrodes with a tunable macroscopic phase difference. The point contact resistance oscillates as a function of the phase difference in a way which reflects
Two-dimensional manifold with point-like defects
Gani, Vakhid A; Rubin, Sergei G
2014-01-01
We study a class of two-dimensional extra spaces isomorphic to the $S^2$ sphere in the framework of the multidimensional gravitation. We show that there exists a family of stationary metrics that depend on the initial (boundary) conditions. All these geometries have a singular point. We also discuss the possibility for these deformed extra spaces to be considered as dark matter candidates.
Instability of two-dimensional heterotic stringy black holes
Azreg-Ainou, M
1999-01-01
We solve the eigenvalue problem of general relativity for the case of charged black holes in two-dimensional heterotic string theory, derived by McGuigan et al. For the case of $m^{2}>q^{2}$, we find a physically acceptable time-dependent growing mode; thus the black hole is unstable. The extremal case $m^{2}=q^{2}$ is stable.
Institute of Scientific and Technical Information of China (English)
XIONG Lei; LI haijiao; ZHANG Lewen
2008-01-01
The fourth-order B spline wavelet scaling functions are used to solve the two-dimensional unsteady diffusion equation. The calculations from a case history indicate that the method provides high accuracy and the computational efficiency is enhanced due to the small matrix derived from this method.The respective features of 3-spline wavelet scaling functions, 4-spline wavelet scaling functions and quasi-wavelet used to solve the two-dimensional unsteady diffusion equation are compared. The proposed method has potential applications in many fields including marine science.
Facile Synthesis and Characterization of Two Dimensional Layered Tin Disulfide Nanowalls
Mutlu, Zafer; Shahrezaei, Sina; Temiz, Selcuk; Ozkan, Mihrimah; Ozkan, Cengiz S.
2016-04-01
Two dimensional layered metal chalcogenides, especially tin sulfides, have recently received great interest due to their enticing physical and chemical properties and hold promise for various applications. We report on synthesis of phase-pure two dimensional tin disulfide nanowalls by a facile vapor-phase synthesis method on insulator substrates such as silicon dioxide and magnesium oxide using tin dioxide and sulfur powders as precursors. The synthesized tin disulfide nanowalls have been characterized to study their fundamental properties by using various techniques such as scanning electron microscopy, x-ray diffraction, Raman spectroscopy, x-ray photoelectron spectroscopy, and ultraviolet photoelectron spectroscopy. The synthesized films have an open network structure constituted of very uniform interconnected nanowalls with high crystallinity.
Ullmann-like reactions for the synthesis of complex two-dimensional materials
Quardokus, Rebecca C.; Tewary, V. K.; DelRio, Frank W.
2016-11-01
Engineering two-dimensional materials through surface-confined synthetic techniques is a promising avenue for designing new materials with tailored properties. Developing and understanding reaction mechanisms for surface-confined synthesis of two-dimensional materials requires atomic-level characterization and chemical analysis. Beggan et al (2015 Nanotechnology 26 365602) used scanning tunneling microscopy and x-ray photoelectron spectroscopy to elucidate the formation mechanism of surface-confined Ullmann-like coupling of thiophene substituted porphyrins on Ag(111). Upon surface deposition, bromine is dissociated and the porphyrins couple with surface adatoms to create linear strands and hexagonally packed molecules. Annealing the sample results in covalently-bonded networks of thienylporphyrin derivatives. A deeper understanding of surface-confined Ullmann-like coupling has the potential to lead to precision-engineered nano-structures through synthetic techniques. Contribution of the National Institute of Standards and Technology, not subject to copyright in the United States of America.
Gow, David W., Jr.; Keller, Corey J.; Eskandar, Emad; Meng, Nate; Cash, Sydney S.
2009-01-01
In this work, we apply Granger causality analysis to high spatiotemporal resolution intracranial EEG (iEEG) data to examine how different components of the left perisylvian language network interact during spoken language perception. The specific focus is on the characterization of serial versus parallel processing dependencies in the dominant…
Misra, Sanchit; Pamnany, Kiran; Aluru, Srinivas
2015-01-01
Construction of whole-genome networks from large-scale gene expression data is an important problem in systems biology. While several techniques have been developed, most cannot handle network reconstruction at the whole-genome scale, and the few that can, require large clusters. In this paper, we present a solution on the Intel Xeon Phi coprocessor, taking advantage of its multi-level parallelism including many x86-based cores, multiple threads per core, and vector processing units. We also present a solution on the Intel® Xeon® processor. Our solution is based on TINGe, a fast parallel network reconstruction technique that uses mutual information and permutation testing for assessing statistical significance. We demonstrate the first ever inference of a plant whole genome regulatory network on a single chip by constructing a 15,575 gene network of the plant Arabidopsis thaliana from 3,137 microarray experiments in only 22 minutes. In addition, our optimization for parallelizing mutual information computation on the Intel Xeon Phi coprocessor holds out lessons that are applicable to other domains.
Par@Graph – a parallel toolbox for the construction and analysis of large complex climate networks
Directory of Open Access Journals (Sweden)
H. Ihshaish
2015-01-01
Full Text Available In this paper, we present Par@Graph, a software toolbox to reconstruct and analyze complex climate networks having a large number of nodes (up to at least O (106 and of edges (up to at least O (1012. The key innovation is an efficient set of parallel software tools designed to leverage the inherited hybrid parallelism in distributed-memory clusters of multi-core machines. The performance of the toolbox is illustrated through networks derived from sea surface height (SSH data of a global high-resolution ocean model. Less than 8 min are needed on 90 Intel Xeon E5-4650 processors to construct a climate network including the preprocessing and the correlation of 3 × 105 SSH time series, resulting in a weighted graph with the same number of vertices and about 3 × 106 edges. In less than 5 min on 30 processors, the resulted graph's degree centrality, strength, connected components, eigenvector centrality, entropy and clustering coefficient metrics were obtained. These results indicate that a complete cycle to construct and analyze a large-scale climate network is available under 13 min. Par@Graph therefore facilitates the application of climate network analysis on high-resolution observations and model results, by enabling fast network construction from the calculation of statistical similarities between climate time series. It also enables network analysis at unprecedented scales on a variety of different sizes of input data sets.
Magnetoelectronic transport of the two-dimensional electron gas in CdSe single quantum wells
Indian Academy of Sciences (India)
P K Ghosh; A Ghosal; D Chattopadhyay
2009-02-01
Hall mobility and magnetoresistance coefficient for the two-dimensional (2D) electron transport parallel to the heterojunction interfaces in a single quantum well of CdSe are calculated with a numerical iterative technique in the framework of Fermi–Dirac statistics. Lattice scatterings due to polar-mode longitudinal optic (LO) phonons, and acoustic phonons via deformation potential and piezoelectric couplings, are considered together with background and remote ionized impurity interactions. The parallel mode of piezoelectric scattering is found to contribute more than the perpendicular mode. We observe that the Hall mobility decreases with increasing temperature but increases with increasing channel width. The magnetoresistance coefficient is found to decrease with increasing temperature and increase with increasing magnetic field in the classical region.
Two-dimensional behavior of three-dimensional magnetohydrodynamic flow with a strong guiding field.
Alexakis, Alexandros
2011-11-01
The magnetohydrodynamic (MHD) equations in the presence of a guiding magnetic field are investigated by means of direct numerical simulations. The basis of the investigation consists of nine runs forced at the small scales. The results demonstrate that for a large enough uniform magnetic field the large scale flow behaves as a two-dimensional (2D) (non-MHD) fluid exhibiting an inverse cascade of energy in the direction perpendicular to the magnetic field, while the small scales behave like a three-dimensional (3D) MHD fluid cascading the energy forwards. The amplitude of the inverse cascade is sensitive to the magnetic field amplitude, the domain size, the forcing mechanism, and the forcing scale. All these dependences are demonstrated by the varying parameters of the simulations. Furthermore, in the case that the system is forced anisotropically in the small parallel scales an inverse cascade in the parallel direction is observed that is feeding the 2D modes k(//)=0.
Radar cross section of dipole phased arrays with parallel feed network
Singh, Hema; Jha, Rakesh Mohan
2016-01-01
This book presents the detailed analytical formulation for the RCS of parallel-fed linear dipole array in the presence of mutual coupling. The radar cross section (RCS) of an object represents its electromagnetic (EM) scattering properties for a given incident wave. The analysis of scattered field is critical in military and defence arenas, especially while designing low-observable platforms. It is well-known that the presence of an antenna/array on the target influences its echo area significantly. The primary cause for such scattering of the incident signals is reflection that occurs within the antenna aperture and its feed network. In this book, the RCS estimation is done based on the signal path within the antenna system. The scattered field is expressed in terms of array design parameters including the reflection and transmission coefficients. The computed results show the variation in the RCS pattern with and without mutual coupling. The effect of finite dipole-length, inter-element spacing, scan angle,...
A Parallel and Incremental Approach for Data-Intensive Learning of Bayesian Networks.
Yue, Kun; Fang, Qiyu; Wang, Xiaoling; Li, Jin; Liu, Weiyi
2015-12-01
Bayesian network (BN) has been adopted as the underlying model for representing and inferring uncertain knowledge. As the basis of realistic applications centered on probabilistic inferences, learning a BN from data is a critical subject of machine learning, artificial intelligence, and big data paradigms. Currently, it is necessary to extend the classical methods for learning BNs with respect to data-intensive computing or in cloud environments. In this paper, we propose a parallel and incremental approach for data-intensive learning of BNs from massive, distributed, and dynamically changing data by extending the classical scoring and search algorithm and using MapReduce. First, we adopt the minimum description length as the scoring metric and give the two-pass MapReduce-based algorithms for computing the required marginal probabilities and scoring the candidate graphical model from sample data. Then, we give the corresponding strategy for extending the classical hill-climbing algorithm to obtain the optimal structure, as well as that for storing a BN by pairs. Further, in view of the dynamic characteristics of the changing data, we give the concept of influence degree to measure the coincidence of the current BN with new data, and then propose the corresponding two-pass MapReduce-based algorithms for BNs incremental learning. Experimental results show the efficiency, scalability, and effectiveness of our methods.
Formation of parallel joint sets and shear band/fracture networks in physical models
Jorand, C.; Chemenda, A. I.; Petit, J.-P.
2012-12-01
Both oedometric and plane-strain tests were performed with parallelepipedic samples made of synthetic granular, cohesive, frictional and dilatant rock analogue material GRAM2. For the first time parallel sets of fractures that have all the characteristics of natural joints were reproduced in the laboratory. The fractures are regularly spaced, normal to σ3, and have plumose morphology very similar to that of natural joints. These fractures can form at tensile stress σ3 much smaller in magnitude than the tensile strength of material and even at slightly compressive σ3. When mean stress σ exceeds a certain value, the fractures become oblique to σ1 (the obliquity increases with σ), forming networks of conjugate shear bands/fractures. These results of plane-strain experiments are in good agreement with those of better controlled conventional axisymmetric tests on a similar material in Chemenda et al. (2011b) and are closer to real geological situations. Both types of experiments are complementary. Their results lead to the conclusion that at least certain categories of natural fractures (including joints, and conjugate shear fractures/bands) were initiated as deformation localization bands. The band orientation is defined by the constitutive properties/parameters (notably the dilatancy factor) that are sensitive to σ.
Parallel mutual information estimation for inferring gene regulatory networks on GPUs
Directory of Open Access Journals (Sweden)
Liu Weiguo
2011-06-01
Full Text Available Abstract Background Mutual information is a measure of similarity between two variables. It has been widely used in various application domains including computational biology, machine learning, statistics, image processing, and financial computing. Previously used simple histogram based mutual information estimators lack the precision in quality compared to kernel based methods. The recently introduced B-spline function based mutual information estimation method is competitive to the kernel based methods in terms of quality but at a lower computational complexity. Results We present a new approach to accelerate the B-spline function based mutual information estimation algorithm with commodity graphics hardware. To derive an efficient mapping onto this type of architecture, we have used the Compute Unified Device Architecture (CUDA programming model to design and implement a new parallel algorithm. Our implementation, called CUDA-MI, can achieve speedups of up to 82 using double precision on a single GPU compared to a multi-threaded implementation on a quad-core CPU for large microarray datasets. We have used the results obtained by CUDA-MI to infer gene regulatory networks (GRNs from microarray data. The comparisons to existing methods including ARACNE and TINGe show that CUDA-MI produces GRNs of higher quality in less time. Conclusions CUDA-MI is publicly available open-source software, written in CUDA and C++ programming languages. It obtains significant speedup over sequential multi-threaded implementation by fully exploiting the compute capability of commonly used CUDA-enabled low-cost GPUs.
Decentralized Cooperation Strategies in Two-Dimensional Traffic of Cellular Automata
Institute of Scientific and Technical Information of China (English)
方峻; 覃征; 陈喜群; 冷彪; 徐朝晖; 江子能
2012-01-01
We study the two-dimensional traffic of cellular automata using computer simulation. We propose two type of decentralized cooperation strategies, which are called stepping aside (CS-SA) and choosing alternative routes (CS-CAR) respectively. We introduce them into an existing two-dimensional cellular automata (CA) model. CS-SA is designed to prohibit a kind of ping-pong jump when two objects standing together try to move in opposite directions. CS-CAR is designed to change the solution of conflict in parallel update. CS-CAR encourages the objects involved in parallel conflicts choose their alternative routes instead of waiting. We also combine the two cooperation strategies (CS-SA-CAR) to test their combined effects. It is found that the system keeps on a partial jam phase with nonzero velocity and flow until the density reaches one. The ratios of the ping-pong jump and the waiting objects involved in conflict are decreased obviously, especially at the free phase. And the average flow is improved by the three cooperation strategies. Although the average travel time is lengthened a bit by CS-CAR, it is shorten by CS-SA and CS-SA-CAR. In addition, we discuss the advantage and applicability of decentralized cooperation modeling.
Decentralized Cooperation Strategies in Two-Dimensional Traffic of Cellular Automata
Fang, Jun; Qin, Zheng; Chen, Xi-Qun; Leng, Biao; Xu, Zhao-Hui; Jiang, Zi-Neng
2012-12-01
We study the two-dimensional traffic of cellular automata using computer simulation. We propose two type of decentralized cooperation strategies, which are called stepping aside (CS-SA) and choosing alternative routes (CS-CAR) respectively. We introduce them into an existing two-dimensional cellular automata (CA) model. CS-SA is designed to prohibit a kind of ping-pong jump when two objects standing together try to move in opposite directions. CS-CAR is designed to change the solution of conflict in parallel update. CS-CAR encourages the objects involved in parallel conflicts choose their alternative routes instead of waiting. We also combine the two cooperation strategies (CS-SA-CAR) to test their combined effects. It is found that the system keeps on a partial jam phase with nonzero velocity and flow until the density reaches one. The ratios of the ping-pong jump and the waiting objects involved in conflict are decreased obviously, especially at the free phase. And the average flow is improved by the three cooperation strategies. Although the average travel time is lengthened a bit by CS-CAR, it is shorten by CS-SA and CS-SA-CAR. In addition, we discuss the advantage and applicability of decentralized cooperation modeling.
Institute of Scientific and Technical Information of China (English)
苗静; 曹玉珍; 杨仁杰; 刘蓉; 孙惠丽; 徐可欣
2013-01-01
Discriminant models of adulterated milk and pure milk were established using BP neural network combined with two-dimensional (2D) correlation near-infrared spectra parameterization .Forty pure milk samples ,40 adulterated milk samples with urea (1~20 g · L -1 ) and 40 adulterated milk samples with melamine (0.01~3 g · L -1 ) were prepared respectively .Based on the characteristics of 2D correlation near-infrared spectra of pure milk and adulterated milk ,5 apparent statistic parameters were calculated based on the parameterization theory .Using 5 characteristic parameters ,discriminant models of urea adulterated milk , melamine adulterated milk and two types of adulterated milk were built by BP neural network .The prediction rate of unknown samples were 95% ,100% and 96.7% ,respectively .The results show that this method can extract effectively feature informa-tion of adulterant ,reduce the input dimensions of BP neural network ,and better realize qualitative analysis of adulterant in milk .%将二维相关近红外谱参数化方法与BP神经网络结合，建立掺杂牛奶与纯牛奶的判别模型。分别配制含有尿素牛奶（1～20g·L -1）和三聚氰胺牛奶（0.01～3g·L -1）样品各40个。研究了纯牛奶、掺杂牛奶的二维相关近红外谱特性，在此基础上，分别提取了各样品二维相关同步谱的5个特征参数。将这5个特征参数作为BP神经网络的输入，分别建立掺杂尿素、掺杂三聚氰胺、两种掺杂牛奶与纯牛奶的判别模型，采用这些模型对未知样品进行预测，其预测正确率分别为95％，100％和96.7％。研究结果表明：该方法有效地提取了牛奶中掺杂目标物的特征光谱信息，同时又减少了BP神经网络输入变量的维数，实现了掺杂牛奶与纯牛奶的鉴别。
Stress Wave Propagation in Two-dimensional Buckyball Lattice
Xu, Jun; Zheng, Bowen
2016-11-01
Orderly arrayed granular crystals exhibit extraordinary capability to tune stress wave propagation. Granular system of higher dimension renders many more stress wave patterns, showing its great potential for physical and engineering applications. At nanoscale, one-dimensionally arranged buckyball (C60) system has shown the ability to support solitary wave. In this paper, stress wave behaviors of two-dimensional buckyball (C60) lattice are investigated based on square close packing and hexagonal close packing. We show that the square close packed system supports highly directional Nesterenko solitary waves along initially excited chains and hexagonal close packed system tends to distribute the impulse and dissipates impact exponentially. Results of numerical calculations based on a two-dimensional nonlinear spring model are in a good agreement with the results of molecular dynamics simulations. This work enhances the understanding of wave properties and allows manipulations of nanoscale lattice and novel design of shock mitigation and nanoscale energy harvesting devices.
The separation of whale myoglobins with two-dimensional electrophoresis.
Spicer, G S
1988-10-01
Five myoglobins (sperm whale, Sei whale, Hubbs' beaked whale, pilot whale, and Amazon River dolphin) were examined using two-dimensional electrophoresis. Previous reports indicated that none of these proteins could be separated by using denaturing (in the presence of 8-9 M urea) isoelectric focusing. This result is confirmed in the present study. However, all the proteins could be separated by using denaturing nonequilibrium pH-gradient electrophoresis in the first dimension. Additionally, all the myoglobins have characteristic mobilities in the second dimension (sodium dodecyl sulfate), but these mobilities do not correspond to the molecular weights of the proteins. We conclude that two-dimensional electrophoresis can be more sensitive to differences in primary protein structure than previous studies indicate and that the assessment seems to be incorrect that this technique can separate only proteins that have a unit charge difference.
Entanglement Entropy in Two-Dimensional String Theory.
Hartnoll, Sean A; Mazenc, Edward A
2015-09-18
To understand an emergent spacetime is to understand the emergence of locality. Entanglement entropy is a powerful diagnostic of locality, because locality leads to a large amount of short distance entanglement. Two-dimensional string theory is among the very simplest instances of an emergent spatial dimension. We compute the entanglement entropy in the large-N matrix quantum mechanics dual to two-dimensional string theory in the semiclassical limit of weak string coupling. We isolate a logarithmically large, but finite, contribution that corresponds to the short distance entanglement of the tachyon field in the emergent spacetime. From the spacetime point of view, the entanglement is regulated by a nonperturbative "graininess" of space.
Topological defect motifs in two-dimensional Coulomb clusters
Radzvilavičius, A; 10.1088/0953-8984/23/38/385301
2012-01-01
The most energetically favourable arrangement of low-density electrons in an infinite two-dimensional plane is the ordered triangular Wigner lattice. However, in most instances of contemporary interest one deals instead with finite clusters of strongly interacting particles localized in potential traps, for example, in complex plasmas. In the current contribution we study distribution of topological defects in two-dimensional Coulomb clusters with parabolic lateral confinement. The minima hopping algorithm based on molecular dynamics is used to efficiently locate the ground- and low-energy metastable states, and their structure is analyzed by means of the Delaunay triangulation. The size, structure and distribution of geometry-induced lattice imperfections strongly depends on the system size and the energetic state. Besides isolated disclinations and dislocations, classification of defect motifs includes defect compounds --- grain boundaries, rosette defects, vacancies and interstitial particles. Proliferatio...
The Persistence Problem in Two-Dimensional Fluid Turbulence
Perlekar, Prasad; Mitra, Dhrubaditya; Pandit, Rahul
2010-01-01
We present a natural framework for studying the persistence problem in two-dimensional fluid turbulence by using the Okubo-Weiss parameter {\\Lambda} to distinguish between vortical and extensional regions. We then use a direct numerical simulation (DNS) of the two-dimensional, incompressible Navier-Stokes equation with Ekman friction to study probability distribution functions (PDFs) of the persistence times of vortical and extensional regions by employing both Eulerian and Lagrangian measurements. We find that, in the Eulerian case, the persistence-time PDFs have exponential tails; by contrast, this PDF for Lagrangian particles, in vortical regions, has a power-law tail with a universal exponent {\\theta} = 3.1 \\pm 0.2.
On Dirichlet eigenvectors for neutral two-dimensional Markov chains
Champagnat, Nicolas; Miclo, Laurent
2012-01-01
We consider a general class of discrete, two-dimensional Markov chains modeling the dynamics of a population with two types, without mutation or immigration, and neutral in the sense that type has no influence on each individual's birth or death parameters. We prove that all the eigenvectors of the corresponding transition matrix or infinitesimal generator \\Pi\\ can be expressed as the product of "universal" polynomials of two variables, depending on each type's size but not on the specific transitions of the dynamics, and functions depending only on the total population size. These eigenvectors appear to be Dirichlet eigenvectors for \\Pi\\ on the complement of triangular subdomains, and as a consequence the corresponding eigenvalues are ordered in a specific way. As an application, we study the quasistationary behavior of finite, nearly neutral, two-dimensional Markov chains, absorbed in the sense that 0 is an absorbing state for each component of the process.
Statistical mechanics of two-dimensional and geophysical flows
Bouchet, Freddy
2011-01-01
The theoretical study of the self-organization of two-dimensional and geophysical turbulent flows is addressed based on statistical mechanics methods. This review is a self-contained presentation of classical and recent works on this subject; from the statistical mechanics basis of the theory up to applications to Jupiter's troposphere and ocean vortices and jets. Emphasize has been placed on examples with available analytical treatment in order to favor better understanding of the physics and dynamics. The equilibrium microcanonical measure is built from the Liouville theorem. On this theoretical basis, we predict the output of the long time evolution of complex turbulent flows as statistical equilibria. This is applied to make quantitative models of two-dimensional turbulence, the Great Red Spot and other Jovian vortices, ocean jets like the Gulf-Stream, and ocean vortices. We also present recent results for non-equilibrium situations, for the studies of either the relaxation towards equilibrium or non-equi...
Two-dimensional hazard estimation for longevity analysis
DEFF Research Database (Denmark)
Fledelius, Peter; Guillen, M.; Nielsen, J.P.
2004-01-01
We investigate developments in Danish mortality based on data from 1974-1998 working in a two-dimensional model with chronological time and age as the two dimensions. The analyses are done with non-parametric kernel hazard estimation techniques. The only assumption is that the mortality surface...... the two-dimensional mortality surface. Furthermore we look at aggregated synthetic population metrics as 'population life expectancy' and 'population survival probability'. For Danish women these metrics indicate decreasing mortality with respect to chronological time. The metrics can not directly be used...... for prediction purposes. However, we suggest that life insurance companies use the estimation technique and the cross-validation for bandwidth selection when analyzing their portfolio mortality. The non-parametric approach may give valuable information prior to developing more sophisticated prediction models...
Analysis of one dimensional and two dimensional fuzzy controllers
Institute of Scientific and Technical Information of China (English)
Ban Xiaojun; Gao Xiaozhi; Huang Xianlin; Wu Tianbao
2006-01-01
The analytical structures and the corresponding mathematical properties of the one dimensional and two dimensional fuzzy controllers are first investigated in detail.The nature of these two kinds of fuzzy controllers is next probed from the perspective of control engineering. For the one dimensional fuzzy controller, it is concluded that this controller is a combination of a saturation element and a nonlinear proportional controller, and the system that employs the one dimensional fuzzy controller is the combination of an open-loop control system and a closedloop control system. For the latter case, it is concluded that it is a hybrid controller, which comprises the saturation part, zero-output part, nonlinear derivative part, nonlinear proportional part, as well as nonlinear proportional-derivative part, and the two dimensional fuzzy controller-based control system is a loop-varying system with varying number of control loops.
Extension of modified power method to two-dimensional problems
Zhang, Peng; Lee, Hyunsuk; Lee, Deokjung
2016-09-01
In this study, the generalized modified power method was extended to two-dimensional problems. A direct application of the method to two-dimensional problems was shown to be unstable when the number of requested eigenmodes is larger than a certain problem dependent number. The root cause of this instability has been identified as the degeneracy of the transfer matrix. In order to resolve this instability, the number of sub-regions for the transfer matrix was increased to be larger than the number of requested eigenmodes; and a new transfer matrix was introduced accordingly which can be calculated by the least square method. The stability of the new method has been successfully demonstrated with a neutron diffusion eigenvalue problem and the 2D C5G7 benchmark problem.
Two Dimensional Lattice Boltzmann Method for Cavity Flow Simulation
Directory of Open Access Journals (Sweden)
Panjit MUSIK
2004-01-01
Full Text Available This paper presents a simulation of incompressible viscous flow within a two-dimensional square cavity. The objective is to develop a method originated from Lattice Gas (cellular Automata (LGA, which utilises discrete lattice as well as discrete time and can be parallelised easily. Lattice Boltzmann Method (LBM, known as discrete Lattice kinetics which provide an alternative for solving the Navier–Stokes equations and are generally used for fluid simulation, is chosen for the study. A specific two-dimensional nine-velocity square Lattice model (D2Q9 Model is used in the simulation with the velocity at the top of the cavity kept fixed. LBM is an efficient method for reproducing the dynamics of cavity flow and the results which are comparable to those of previous work.