Bromidotetra-kis-(2-isopropyl-1H-imidazole-κN)copper(II) bromide.

PubMed

Godlewska, Sylwia; Socha, Joanna; Baranowska, Katarzyna; Dołęga, Anna

2011-10-01

The Cu(II) atom in the title salt, [CuBr(C(6)H(10)N(2))(4)]Br, is coordinated in a square-pyramidal geometry by four imidazole N atoms and one bromide anion that is located at the apex of the pyramid. The cations and the anions form a two-dimensional network parallel to (001) through N-H⋯Br hydrogen bonds.

Electromagnetic Design of a Magnetically-Coupled Spatial Power Combiner

NASA Technical Reports Server (NTRS)

Bulcha, B.; Cataldo, G.; Stevenson, T. R.; U-Yen, K.; Moseley, S. H.; Wollack, E. J.

2017-01-01

The design of a two-dimensional beam-combining network employing a parallel-plate superconducting waveguide with a mono-crystalline silicon dielectric is presented. This novel beam-combining network structure employs an array of magnetically coupled antenna elements to achieve high coupling efficiency and full sampling of the intensity distribution while avoiding diffractive losses in the multi-mode region defined by the parallel-plate waveguide. These attributes enable the structures use in realizing compact far-infrared spectrometers for astrophysical and instrumentation applications. When configured with a suitable corporate-feed power-combiner, this fully sampled array can be used to realize a low-sidelobe apodized response without incurring a reduction in coupling efficiency. To control undesired reflections over a wide range of angles in the finite-sized parallel-plate waveguide region, a wideband meta-material electromagnetic absorber structure is implemented. This adiabatic structure absorbs greater than 99 of the power over the 1.7:1 operational band at angles ranging from normal (0 degree) to near parallel (180 degree) incidence. Design, simulations, and application of the device will be presented.

A comparison between HMLP and HRBF for attitude control.

PubMed

Fortuna, L; Muscato, G; Xibilia, M G

2001-01-01

In this paper the problem of controlling the attitude of a rigid body, such as a Spacecraft, in three-dimensional space is approached by introducing two new control strategies developed in hypercomplex algebra. The proposed approaches are based on two parallel controllers, both derived in quaternion algebra. The first is a feedback controller of the proportional derivative (PD) type, while the second is a feedforward controller, which is implemented either by means of a hypercomplex multilayer perceptron (HMLP) neural network or by means of a hypercomplex radial basis function (HRBF) neural network. Several simulations show the performance of the two approaches. The results are also compared with a classical PD controller and with an adaptive controller, showing the improvements obtained by using neural networks, especially when an external disturbance acts on the rigid body. In particular the HMLP network gave better results when considering trajectories not presented during the learning phase.

Noncoherent parallel optical processor for discrete two-dimensional linear transformations.

PubMed

Glaser, I

1980-10-01

We describe a parallel optical processor, based on a lenslet array, that provides general linear two-dimensional transformations using noncoherent light. Such a processor could become useful in image- and signal-processing applications in which the throughput requirements cannot be adequately satisfied by state-of-the-art digital processors. Experimental results that illustrate the feasibility of the processor by demonstrating its use in parallel optical computation of the two-dimensional Walsh-Hadamard transformation are presented.

2-(4-Hy-droxy-phen-yl)-1H-benzimidazol-3-ium chloride monohydrate.

PubMed

González-Padilla, Jazmin E; Rosales-Hernández, Martha Cecila; Padilla-Martínez, Itzia I; García-Báez, Efren V; Rojas-Lima, Susana

2013-01-01

The title mol-ecular salt, C13H11N2O(+)·Cl(-)·H2O, crystallizes as a monohydrate. In the cation, the phenol and benzimidazole rings are almost coplanar, making a dihedral angle of 3.18 (4)°. The chloride anion and benzimidazole cation are linked by two N(+)-H⋯Cl(-) hydrogen bonds, forming chains propagating along [010]. These chains are linked through O-H⋯Cl hydrogen bonds involving the water mol-ecule and the chloride anion, which form a diamond core, giving rise to the formation of two-dimensional networks lying parallel to (10-2). Two π-π inter-actions involving the imidazolium ring with the benzene and phenol rings [centroid-centroid distances = 3.859 (3) and 3.602 (3) Å, respectively], contribute to this second dimension. A strong O-H⋯O hydrogen bond involving the water mol-ecule and the phenol substituent on the benzimidazole unit links the networks, forming a three-dimensional structure.

Bromidotetra­kis­(2-isopropyl-1H-imidazole-κN 3)copper(II) bromide

PubMed Central

Godlewska, Sylwia; Socha, Joanna; Baranowska, Katarzyna; Dołęga, Anna

2011-01-01

The CuII atom in the title salt, [CuBr(C6H10N2)4]Br, is coordinated in a square-pyramidal geometry by four imidazole N atoms and one bromide anion that is located at the apex of the pyramid. The cations and the anions form a two-dimensional network parallel to (001) through N—H⋯Br hydrogen bonds. PMID:22064905

Parallel numerical modeling of hybrid-dimensional compositional non-isothermal Darcy flows in fractured porous media

NASA Astrophysics Data System (ADS)

Xing, F.; Masson, R.; Lopez, S.

2017-09-01

This paper introduces a new discrete fracture model accounting for non-isothermal compositional multiphase Darcy flows and complex networks of fractures with intersecting, immersed and non-immersed fractures. The so called hybrid-dimensional model using a 2D model in the fractures coupled with a 3D model in the matrix is first derived rigorously starting from the equi-dimensional matrix fracture model. Then, it is discretized using a fully implicit time integration combined with the Vertex Approximate Gradient (VAG) finite volume scheme which is adapted to polyhedral meshes and anisotropic heterogeneous media. The fully coupled systems are assembled and solved in parallel using the Single Program Multiple Data (SPMD) paradigm with one layer of ghost cells. This strategy allows for a local assembly of the discrete systems. An efficient preconditioner is implemented to solve the linear systems at each time step and each Newton type iteration of the simulation. The numerical efficiency of our approach is assessed on different meshes, fracture networks, and physical settings in terms of parallel scalability, nonlinear convergence and linear convergence.

How to cluster in parallel with neural networks

NASA Technical Reports Server (NTRS)

Kamgar-Parsi, Behzad; Gualtieri, J. A.; Devaney, Judy E.; Kamgar-Parsi, Behrooz

1988-01-01

Partitioning a set of N patterns in a d-dimensional metric space into K clusters - in a way that those in a given cluster are more similar to each other than the rest - is a problem of interest in astrophysics, image analysis and other fields. As there are approximately K(N)/K (factorial) possible ways of partitioning the patterns among K clusters, finding the best solution is beyond exhaustive search when N is large. Researchers show that this problem can be formulated as an optimization problem for which very good, but not necessarily optimal solutions can be found by using a neural network. To do this the network must start from many randomly selected initial states. The network is simulated on the MPP (a 128 x 128 SIMD array machine), where researchers use the massive parallelism not only in solving the differential equations that govern the evolution of the network, but also by starting the network from many initial states at once, thus obtaining many solutions in one run. Researchers obtain speedups of two to three orders of magnitude over serial implementations and the promise through Analog VLSI implementations of speedups comensurate with human perceptual abilities.

Classification of 2-dimensional array patterns: assembling many small neural networks is better than using a large one.

PubMed

Chen, Liang; Xue, Wei; Tokuda, Naoyuki

2010-08-01

In many pattern classification/recognition applications of artificial neural networks, an object to be classified is represented by a fixed sized 2-dimensional array of uniform type, which corresponds to the cells of a 2-dimensional grid of the same size. A general neural network structure, called an undistricted neural network, which takes all the elements in the array as inputs could be used for problems such as these. However, a districted neural network can be used to reduce the training complexity. A districted neural network usually consists of two levels of sub-neural networks. Each of the lower level neural networks, called a regional sub-neural network, takes the elements in a region of the array as its inputs and is expected to output a temporary class label, called an individual opinion, based on the partial information of the entire array. The higher level neural network, called an assembling sub-neural network, uses the outputs (opinions) of regional sub-neural networks as inputs, and by consensus derives the label decision for the object. Each of the sub-neural networks can be trained separately and thus the training is less expensive. The regional sub-neural networks can be trained and performed in parallel and independently, therefore a high speed can be achieved. We prove theoretically in this paper, using a simple model, that a districted neural network is actually more stable than an undistricted neural network in noisy environments. We conjecture that the result is valid for all neural networks. This theory is verified by experiments involving gender classification and human face recognition. We conclude that a districted neural network is highly recommended for neural network applications in recognition or classification of 2-dimensional array patterns in highly noisy environments. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Two-dimensional self-organization of an ordered Au silicide nanowire network on a Si(110)-16 x 2 surface.

PubMed

Hong, Ie-Hong; Yen, Shang-Chieh; Lin, Fu-Shiang

2009-08-17

A well-ordered two-dimensional (2D) network consisting of two crossed Au silicide nanowire (NW) arrays is self-organized on a Si(110)-16 x 2 surface by the direct-current heating of approximately 1.5 monolayers of Au on the surface at 1100 K. Such a highly regular crossbar nanomesh exhibits both a perfect long-range spatial order and a high integration density over a mesoscopic area, and these two self-ordering crossed arrays of parallel-aligned NWs have distinctly different sizes and conductivities. NWs are fabricated with widths and pitches as small as approximately 2 and approximately 5 nm, respectively. The difference in the conductivities of two crossed-NW arrays opens up the possibility for their utilization in nanodevices of crossbar architecture. Scanning tunneling microscopy/spectroscopy studies show that the 2D self-organization of this perfect Au silicide nanomesh can be achieved through two different directional electromigrations of Au silicide NWs along different orientations of two nonorthogonal 16 x 2 domains, which are driven by the electrical field of direct-current heating. Prospects for this Au silicide nanomesh are also discussed.

2-Ferrocenyl-6-methyl­pyridin-3-ol

PubMed Central

Wang, Zhi-Qiang; Xu, Chen; Cen, Fei-Fei; Li, Ying-Fei; Ji, Bao-Ming

2008-01-01

In the title compound, [Fe(C5H5)(C11H10NO)], the dihedral angle between the pyridyl and substituted cyclo­penta­dienyl rings is 20.4 (3)°. The H atoms of the methyl group are disordered over two positions; their site-occupation factors were fixed at 0.5. The crystal structure is stabilized by well defined inter­molecular O—H⋯N and C—H⋯O hydrogen bonds, leading to the formation of a two-dimensional network parallel to (101). PMID:21581222

(4R*,5R*)-2-(4-Meth­oxy­phen­yl)-1,3-dioxolane-4,5-dicarboxamide

PubMed Central

Lv, Chun-Lei; Chen, Jian-Hui; Zhang, Yu-Zhe; Lu, Ding-Qiang; OuYang, Ping-Kai

2012-01-01

In the title compound, C12H14N2O5, the five-membered 1,3-dioxolane ring has a twisted conformation. In the crystal, N—H⋯O and C—H⋯O hydrogen bonds link the mol­ecules into a two-dimensional network lying parallel to the ab plane. There are also C—H⋯π inter­actions present in the crystal structure. PMID:22412479

Particle simulation on heterogeneous distributed supercomputers

NASA Technical Reports Server (NTRS)

Becker, Jeffrey C.; Dagum, Leonardo

1993-01-01

We describe the implementation and performance of a three dimensional particle simulation distributed between a Thinking Machines CM-2 and a Cray Y-MP. These are connected by a combination of two high-speed networks: a high-performance parallel interface (HIPPI) and an optical network (UltraNet). This is the first application to use this configuration at NASA Ames Research Center. We describe our experience implementing and using the application and report the results of several timing measurements. We show that the distribution of applications across disparate supercomputing platforms is feasible and has reasonable performance. In addition, several practical aspects of the computing environment are discussed.

2-(4-Hy­droxy­phen­yl)-1H-benzimidazol-3-ium chloride monohydrate

PubMed Central

González-Padilla, Jazmin E.; Rosales-Hernández, Martha Cecila; Padilla-Martínez, Itzia I.; García-Báez, Efren V.; Rojas-Lima, Susana

2013-01-01

The title mol­ecular salt, C13H11N2O+·Cl−·H2O, crystallizes as a monohydrate. In the cation, the phenol and benzimidazole rings are almost coplanar, making a dihedral angle of 3.18 (4)°. The chloride anion and benzimidazole cation are linked by two N+—H⋯Cl− hydrogen bonds, forming chains propagating along [010]. These chains are linked through O—H⋯Cl hydrogen bonds involving the water mol­ecule and the chloride anion, which form a diamond core, giving rise to the formation of two-dimensional networks lying parallel to (10-2). Two π–π inter­actions involving the imidazolium ring with the benzene and phenol rings [centroid–centroid distances = 3.859 (3) and 3.602 (3) Å, respectively], contribute to this second dimension. A strong O—H⋯O hydrogen bond involving the water mol­ecule and the phenol substituent on the benzimidazole unit links the networks, forming a three-dimensional structure. PMID:24427105

All-Optical Two-Dimensional Serial-to-Parallel Pulse Converter Using an Organic Film with Femtosecond Optical Response

NASA Astrophysics Data System (ADS)

Tatsuura, Satoshi; Wada, Osamu; Furuki, Makoto; Tian, Minquan; Sato, Yasuhiro; Iwasa, Izumi; Pu, Lyong Sun

2001-04-01

In this study, we introduce a new concept of all-optical two-dimensional serial-to-parallel pulse converters. Femtosecond optical pulses can be understood as thin plates of light traveling in space. When a femtosecond signal-pulse train and a single gate pulse were fed onto a material with a finite incident angle, each signal-pulse plate met the gate-pulse plate at different locations in the material due to the time-of-flight effect. Meeting points can be made two-dimensional by adding a partial time delay to the gate pulse. By placing a nonlinear optical material at an appropriate position, two-dimensional serial-to-parallel conversion of a signal-pulse train can be achieved with a single gate pulse. We demonstrated the detection of parallel outputs from a 1-Tb/s optical-pulse train through the use of a BaB2O4 crystal. We also succeeded in demonstrating 1-Tb/s serial-to-parallel operation through the use of a novel organic nonlinear optical material, squarylium-dye J-aggregate film, which exhibits ultrafast recovery of bleached absorption.

Crystal structure of catena-poly[[aquadi-n-propyl­tin(IV)]-μ-oxalato

PubMed Central

Reichelt, Martin; Reuter, Hans

2014-01-01

The title compound, [Sn(C3H7)2(H2O)(C2O4)]n, represents the first diorganotin(IV) oxalate hydrate to be structurally characterized. The tin(IV) atom of the one-dimensional coordination polymer is located on a twofold rotation axis and is coordinated by two chelating oxalate ligands with two slightly different Sn—O bond lengths of 2.290 (2) and 2.365 (2) Å, two symmetry-related n-propyl groups with a Sn—C bond lengths of 2.127 (3) Å, and a water mol­ecule with a Sn—O bond length of 2.262 (2) Å. The coordination polyhedron around the SnIV atom is a slightly distorted penta­gonal bipyramid with a nearly linear axis between the trans-oriented n-propyl groups [C—Sn—C = 176.8 (1)°]. The bond angles between the oxygen atoms of the equatorial plane range from 70.48 (6)° to 76.12 (8)°. A one-dimensional coordination polymer results from the less asymmetric bilateral coordination of the centrosymmetric oxalate anion, inter­nally reflected by two slightly different C—O bond lengths of 1.248 (3) and 1.254 (3) Å. The chains of the polymer propagate parallel to [001] and are held together by hydrogen bonds between water mol­ecules and oxalate anions of neighboring chains, leading to a two-dimensional network parallel to (100). PMID:25249862

Hadoop neural network for parallel and distributed feature selection.

PubMed

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.

N-(1H-Indazol-5-yl)-4-meth-oxy-benzene-sulfonamide.

PubMed

Chicha, Hakima; Rakib, El Mostapha; Bouissane, Latifa; Saadi, Mohamed; El Ammari, Lahcen

2013-10-26

In the title compound, C14H13N3O3S, the fused ring system is almost planar, the largest deviation from the mean plane being 0.023 (2) Å, and makes a dihedral angle of 47.92 (10)° with the benzene ring of the benzene-sulfonamide moiety. In the crystal, mol-ecules are connected through N-H⋯O hydrogen bonds and weak C-H⋯O contacts, forming a two-dimensional network which is parallel to (010).

N-(3-Chloro-1H-indazol-5-yl)-4-meth-oxy-benzene-sulfonamide.

PubMed

Chicha, Hakima; Rakib, El Mostapha; Bouissane, Latifa; Saadi, Mohamed; El Ammari, Lahcen

2013-10-12

In the title compound, C14H12ClN3O3S, the fused five- and six-membered rings are folded slightly along the common edge, forming a dihedral angle of 3.2 (1)°. The mean plane through the indazole system makes a dihedral angle of 30.75 (7)° with the distant benzene ring. In the crystal, N-H⋯O hydrogen bonds link the mol-ecules, forming a two-dimensional network parallel to (001).

Parallel Computation of Unsteady Flows on a Network of Workstations

NASA Technical Reports Server (NTRS)

1997-01-01

Parallel computation of unsteady flows requires significant computational resources. The utilization of a network of workstations seems an efficient solution to the problem where large problems can be treated at a reasonable cost. This approach requires the solution of several problems: 1) the partitioning and distribution of the problem over a network of workstation, 2) efficient communication tools, 3) managing the system efficiently for a given problem. Of course, there is the question of the efficiency of any given numerical algorithm to such a computing system. NPARC code was chosen as a sample for the application. For the explicit version of the NPARC code both two- and three-dimensional problems were studied. Again both steady and unsteady problems were investigated. The issues studied as a part of the research program were: 1) how to distribute the data between the workstations, 2) how to compute and how to communicate at each node efficiently, 3) how to balance the load distribution. In the following, a summary of these activities is presented. Details of the work have been presented and published as referenced.

Re-forming supercritical quasi-parallel shocks. I - One- and two-dimensional simulations

NASA Technical Reports Server (NTRS)

Thomas, V. A.; Winske, D.; Omidi, N.

1990-01-01

The process of reforming supercritical quasi-parallel shocks is investigated using one-dimensional and two-dimensional hybrid (particle ion, massless fluid electron) simulations both of shocks and of simpler two-stream interactions. It is found that the supercritical quasi-parallel shock is not steady. Instread of a well-defined shock ramp between upstream and downstream states that remains at a fixed position in the flow, the ramp periodically steepens, broadens, and then reforms upstream of its former position. It is concluded that the wave generation process is localized at the shock ramp and that the reformation process proceeds in the absence of upstream perturbations intersecting the shock.

Learning control system design based on 2-D theory - An application to parallel link manipulator

NASA Technical Reports Server (NTRS)

Geng, Z.; Carroll, R. L.; Lee, J. D.; Haynes, L. H.

1990-01-01

An approach to iterative learning control system design based on two-dimensional system theory is presented. A two-dimensional model for the iterative learning control system which reveals the connections between learning control systems and two-dimensional system theory is established. A learning control algorithm is proposed, and the convergence of learning using this algorithm is guaranteed by two-dimensional stability. The learning algorithm is applied successfully to the trajectory tracking control problem for a parallel link robot manipulator. The excellent performance of this learning algorithm is demonstrated by the computer simulation results.

The BlueGene/L supercomputer

NASA Astrophysics Data System (ADS)

Bhanota, Gyan; Chen, Dong; Gara, Alan; Vranas, Pavlos

2003-05-01

The architecture of the BlueGene/L massively parallel supercomputer is described. Each computing node consists of a single compute ASIC plus 256 MB of external memory. The compute ASIC integrates two 700 MHz PowerPC 440 integer CPU cores, two 2.8 Gflops floating point units, 4 MB of embedded DRAM as cache, a memory controller for external memory, six 1.4 Gbit/s bi-directional ports for a 3-dimensional torus network connection, three 2.8 Gbit/s bi-directional ports for connecting to a global tree network and a Gigabit Ethernet for I/O. 65,536 of such nodes are connected into a 3-d torus with a geometry of 32×32×64. The total peak performance of the system is 360 Teraflops and the total amount of memory is 16 TeraBytes.

Dissipation, Voltage Profile and Levy Dragon in a Special Ladder Network

ERIC Educational Resources Information Center

Ucak, C.

2009-01-01

A ladder network constructed by an elementary two-terminal network consisting of a parallel resistor-inductor block in series with a parallel resistor-capacitor block sometimes is said to have a non-dispersive dissipative response. This special ladder network is created iteratively by replacing the elementary two-terminal network in place of the…

Vision-Based Navigation and Parallel Computing

DTIC Science & Technology

1990-08-01

33 5.8. Behizad Kamgar-Parsi and Behrooz Karngar-Parsi,"On Problem 5- lving with Hopfield Neural Networks", CAR-TR-462, CS-TR...Second. the hypercube connections support logarithmic implementations of fundamental parallel algorithms. such as grid permutations and scan...the pose space. It also uses a set of virtual processors to represent an orthogonal projection grid , and projections of the six dimensional pose space

Bistatic scattering from a three-dimensional object above a two-dimensional randomly rough surface modeled with the parallel FDTD approach.

PubMed

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.

VLSI neuroprocessors

NASA Technical Reports Server (NTRS)

Kemeny, Sabrina E.

1994-01-01

Electronic and optoelectronic hardware implementations of highly parallel computing architectures address several ill-defined and/or computation-intensive problems not easily solved by conventional computing techniques. The concurrent processing architectures developed are derived from a variety of advanced computing paradigms including neural network models, fuzzy logic, and cellular automata. Hardware implementation technologies range from state-of-the-art digital/analog custom-VLSI to advanced optoelectronic devices such as computer-generated holograms and e-beam fabricated Dammann gratings. JPL's concurrent processing devices group has developed a broad technology base in hardware implementable parallel algorithms, low-power and high-speed VLSI designs and building block VLSI chips, leading to application-specific high-performance embeddable processors. Application areas include high throughput map-data classification using feedforward neural networks, terrain based tactical movement planner using cellular automata, resource optimization (weapon-target assignment) using a multidimensional feedback network with lateral inhibition, and classification of rocks using an inner-product scheme on thematic mapper data. In addition to addressing specific functional needs of DOD and NASA, the JPL-developed concurrent processing device technology is also being customized for a variety of commercial applications (in collaboration with industrial partners), and is being transferred to U.S. industries. This viewgraph p resentation focuses on two application-specific processors which solve the computation intensive tasks of resource allocation (weapon-target assignment) and terrain based tactical movement planning using two extremely different topologies. Resource allocation is implemented as an asynchronous analog competitive assignment architecture inspired by the Hopfield network. Hardware realization leads to a two to four order of magnitude speed-up over conventional techniques and enables multiple assignments, (many to many), not achievable with standard statistical approaches. Tactical movement planning (finding the best path from A to B) is accomplished with a digital two-dimensional concurrent processor array. By exploiting the natural parallel decomposition of the problem in silicon, a four order of magnitude speed-up over optimized software approaches has been demonstrated.

Using algebra for massively parallel processor design and utilization

NASA Technical Reports Server (NTRS)

Campbell, Lowell; Fellows, Michael R.

1990-01-01

This paper summarizes the author's advances in the design of dense processor networks. Within is reported a collection of recent constructions of dense symmetric networks that provide the largest know values for the number of nodes that can be placed in a network of a given degree and diameter. The constructions are in the range of current potential engineering significance and are based on groups of automorphisms of finite-dimensional vector spaces.

Two-dimensional displacement measurement based on two parallel gratings

NASA Astrophysics Data System (ADS)

Wei, Peipei; Lu, Xi; Qiao, Decheng; Zou, Limin; Huang, Xiangdong; Tan, Jiubin; Lu, Zhengang

2018-06-01

In this paper, a two-dimensional (2-D) planar encoder based on two parallel gratings, which includes a scanning grating and scale grating, is presented. The scanning grating is a combined transmission rectangular grating comprised of a 2-D grating located at the center and two one-dimensional (1-D) gratings located at the sides. The grating lines of the two 1-D gratings are perpendicular to each other and parallel with the 2-D grating lines. The scale grating is a 2-D reflective-type rectangular grating placed in parallel with the scanning grating, and there is an angular difference of 45° between the grating lines of the two 2-D gratings. With the special structural design of the scanning grating, the encoder can measure the 2-D displacement in the grating plane simultaneously, and the measured interference signals in the two directions are uncoupled. Moreover, by utilizing the scanning grating to modulate the phase of the interference signals instead of the prisms, the structure of the encoder is compact. Experiments were implemented, and the results demonstrate the validity of the 2-D planar grating encoder.

The AIS-5000 parallel processor

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

Schmitt, L.A.; Wilson, S.S.

1988-05-01

The AIS-5000 is a commercially available massively parallel processor which has been designed to operate in an industrial environment. It has fine-grained parallelism with up to 1024 processing elements arranged in a single-instruction multiple-data (SIMD) architecture. The processing elements are arranged in a one-dimensional chain that, for computer vision applications, can be as wide as the image itself. This architecture has superior cost/performance characteristics than two-dimensional mesh-connected systems. The design of the processing elements and their interconnections as well as the software used to program the system allow a wide variety of algorithms and applications to be implemented. In thismore » paper, the overall architecture of the system is described. Various components of the system are discussed, including details of the processing elements, data I/O pathways and parallel memory organization. A virtual two-dimensional model for programming image-based algorithms for the system is presented. This model is supported by the AIS-5000 hardware and software and allows the system to be treated as a full-image-size, two-dimensional, mesh-connected parallel processor. Performance bench marks are given for certain simple and complex functions.« less

Parallel processing data network of master and slave transputers controlled by a serial control network

DOEpatents

Crosetto, D.B.

1996-12-31

The present device provides for a dynamically configurable communication network having a multi-processor parallel processing system having a serial communication network and a high speed parallel communication network. The serial communication network is used to disseminate commands from a master processor to a plurality of slave processors to effect communication protocol, to control transmission of high density data among nodes and to monitor each slave processor`s status. The high speed parallel processing network is used to effect the transmission of high density data among nodes in the parallel processing system. Each node comprises a transputer, a digital signal processor, a parallel transfer controller, and two three-port memory devices. A communication switch within each node connects it to a fast parallel hardware channel through which all high density data arrives or leaves the node. 6 figs.

Parallel processing data network of master and slave transputers controlled by a serial control network

DOEpatents

Crosetto, Dario B.

1996-01-01

The present device provides for a dynamically configurable communication network having a multi-processor parallel processing system having a serial communication network and a high speed parallel communication network. The serial communication network is used to disseminate commands from a master processor (100) to a plurality of slave processors (200) to effect communication protocol, to control transmission of high density data among nodes and to monitor each slave processor's status. The high speed parallel processing network is used to effect the transmission of high density data among nodes in the parallel processing system. Each node comprises a transputer (104), a digital signal processor (114), a parallel transfer controller (106), and two three-port memory devices. A communication switch (108) within each node (100) connects it to a fast parallel hardware channel (70) through which all high density data arrives or leaves the node.

catena-Poly[[triphenyl-tin(IV)]-μ-phenyl-phosphinato-κO:O'].

PubMed

Diop, Tidiane; Diop, Libasse; Kociok-Köhn, Gabriele; Molloy, Kieran C; Stoeckli-Evans, Helen

2011-12-01

In the structure of the title coordination polymer, [Sn(C(6)H(5))(3)(C(6)H(6)O(2)P)](n) or [PhP(H)O(2)Sn(IV)(Ph)(3)](n), the Sn(IV) atom is five-coordinate, with the SnC(3)O(2) framework in a trans trigonal-bipyramidal arrangement having the PhP(H)O(2) (-) anions in apical positions. In the crystal, neighbouring polymer chains are linked via C-H⋯π inter-actions, forming a two-dimensional network lying parallel to (001).

Absolute Configuration of Andrographolide and Its Proliferation of Osteoblast Cell Lines

NASA Astrophysics Data System (ADS)

Chantrapromma, S.; Boonnak, N.; Pitakpornpreecha, T.; Yordthong, T.; Chidan Kumar, C. S.; Fun, H. K.

2018-05-01

Andrographolide, C20H30O5, is a labdane diterpenoid which was isolated from the leave of Andrographis paniculata. Its crystal structure is determined by single crystal X-ray diffraction: monoclinic, sp. gr. P21, Z = 2. Absolute configuration is determined by the refinement of the Flack parameter to 0.21(19). In the crystal, molecules are linked by O-H···O hydrogen bonds and C-H···O interactions into two dimensional network parallel to the (001) plane. Its proliferation of osteoblast cell lines is reported.

4-Methyl-N-(1-methyl-1H-indazol-5-yl)benzene-sulfonamide.

PubMed

Chicha, Hakima; Oulemda, Bassou; Rakib, El Mostapha; Saadi, Mohamed; El Ammari, Lahcen

2013-01-01

In the title compound, C15H15N3O2S, the fused ring system is close to planar, the largest deviation from the mean plane being 0.030 (2) Å, and makes a dihedral angle of 48.84 (9)° with the benzene ring belonging to the methyl-benzene-sulfonamide moiety. In the crystal, mol-ecules are -connected through N-H⋯N hydrogen bonds and weak C-H⋯O contacts, forming a two-dimensional network parallel to (001).

4-Methyl-N-(1-methyl-1H-indazol-5-yl)benzene­sulfonamide

PubMed Central

Chicha, Hakima; Oulemda, Bassou; Rakib, El Mostapha; Saadi, Mohamed; El Ammari, Lahcen

2013-01-01

In the title compound, C15H15N3O2S, the fused ring system is close to planar, the largest deviation from the mean plane being 0.030 (2) Å, and makes a dihedral angle of 48.84 (9)° with the benzene ring belonging to the methyl­benzene­sulfonamide moiety. In the crystal, mol­ecules are ­connected through N—H⋯N hydrogen bonds and weak C—H⋯O contacts, forming a two-dimensional network parallel to (001). PMID:24427093

N-(3-Chloro-1H-indazol-5-yl)-4-meth­oxy­benzene­sulfonamide

PubMed Central

Chicha, Hakima; Rakib, El Mostapha; Bouissane, Latifa; Saadi, Mohamed; El Ammari, Lahcen

2013-01-01

In the title compound, C14H12ClN3O3S, the fused five- and six-membered rings are folded slightly along the common edge, forming a dihedral angle of 3.2 (1)°. The mean plane through the indazole system makes a dihedral angle of 30.75 (7)° with the distant benzene ring. In the crystal, N—H⋯O hydrogen bonds link the mol­ecules, forming a two-dimensional network parallel to (001). PMID:24454078

N-(1H-Indazol-5-yl)-4-meth­oxy­benzene­sulfonamide

PubMed Central

Chicha, Hakima; Rakib, El Mostapha; Bouissane, Latifa; Saadi, Mohamed; El Ammari, Lahcen

2013-01-01

In the title compound, C14H13N3O3S, the fused ring system is almost planar, the largest deviation from the mean plane being 0.023 (2) Å, and makes a dihedral angle of 47.92 (10)° with the benzene ring of the benzene­sulfonamide moiety. In the crystal, mol­ecules are connected through N—H⋯O hydrogen bonds and weak C—H⋯O contacts, forming a two-dimensional network which is parallel to (010). PMID:24454128

High-speed all-optical DNA local sequence alignment based on a three-dimensional artificial neural network.

PubMed

Maleki, Ehsan; Babashah, Hossein; Koohi, Somayyeh; Kavehvash, Zahra

2017-07-01

This paper presents an optical processing approach for exploring a large number of genome sequences. Specifically, we propose an optical correlator for global alignment and an extended moiré matching technique for local analysis of spatially coded DNA, whose output is fed to a novel three-dimensional artificial neural network for local DNA alignment. All-optical implementation of the proposed 3D artificial neural network is developed and its accuracy is verified in Zemax. Thanks to its parallel processing capability, the proposed structure performs local alignment of 4 million sequences of 150 base pairs in a few seconds, which is much faster than its electrical counterparts, such as the basic local alignment search tool.

Parallel computation for biological sequence comparison: comparing a portable model to the native model for the Intel Hypercube.

PubMed

Nadkarni, P M; Miller, P L

1991-01-01

A parallel program for inter-database sequence comparison was developed on the Intel Hypercube using two models of parallel programming. One version was built using machine-specific Hypercube parallel programming commands. The other version was built using Linda, a machine-independent parallel programming language. The two versions of the program provide a case study comparing these two approaches to parallelization in an important biological application area. Benchmark tests with both programs gave comparable results with a small number of processors. As the number of processors was increased, the Linda version was somewhat less efficient. The Linda version was also run without change on Network Linda, a virtual parallel machine running on a network of desktop workstations.

SERODS optical data storage with parallel signal transfer

DOEpatents

Vo-Dinh, Tuan

2003-09-02

Surface-enhanced Raman optical data storage (SERODS) systems having increased reading and writing speeds, that is, increased data transfer rates, are disclosed. In the various SERODS read and write systems, the surface-enhanced Raman scattering (SERS) data is written and read using a two-dimensional process called parallel signal transfer (PST). The various embodiments utilize laser light beam excitation of the SERODS medium, optical filtering, beam imaging, and two-dimensional light detection. Two- and three-dimensional SERODS media are utilized. The SERODS write systems employ either a different laser or a different level of laser power.

SERODS optical data storage with parallel signal transfer

DOEpatents

Vo-Dinh, Tuan

2003-06-24

Surface-enhanced Raman optical data storage (SERODS) systems having increased reading and writing speeds, that is, increased data transfer rates, are disclosed. In the various SERODS read and write systems, the surface-enhanced Raman scattering (SERS) data is written and read using a two-dimensional process called parallel signal transfer (PST). The various embodiments utilize laser light beam excitation of the SERODS medium, optical filtering, beam imaging, and two-dimensional light detection. Two- and three-dimensional SERODS media are utilized. The SERODS write systems employ either a different laser or a different level of laser power.

Crystal structures of the three closely related compounds: bis-[(1H-tetra-zol-5-yl)meth-yl]nitramide, tri-amino-guanidinium 5-({[(1H-tetra-zol-5-yl)meth-yl](nitro)-amino}-meth-yl)tetra-zol-1-ide, and di-ammonium bis-[(tetra-zol-1-id-5-yl)meth-yl]nitramide monohydrate.

PubMed

Mitchell, Lauren A; Imler, Gregory H; Parrish, Damon A; Deschamps, Jeffrey R; Leonard, Philip W; Chavez, David E

2017-07-01

In the mol-ecule of neutral bis-[(1 H -tetra-zol-5-yl)meth-yl]nitramide, (I), C 4 H 6 N 10 O 2 , there are two intra-molecular N-H⋯O hydrogen bonds. In the crystal, N-H⋯N hydrogen bonds link mol-ecules, forming a two-dimensional network parallel to (-201) and weak C-H⋯O, C-H⋯N hydrogen bonds, and inter-molecular π-π stacking completes the three-dimensional network. The anion in the molecular salt, tri-amino-guanidinium 5-({[(1 H -tetra-zol-5-yl)meth-yl](nitro)-amino}-meth-yl)tetra-zol-1-ide, (II), CH 9 N 6 + ·C 4 H 5 N 10 O 2 - , displays intra-molecular π-π stacking and in the crystal, N-H⋯N and N-H⋯O hydrogen bonds link the components of the structure, forming a three-dimensional network. In the crystal of di-ammonium bis-[(tetra-zol-1-id-5-yl)meth-yl]nitramide monohydrate, (III), 2NH 4 + ·C 4 H 4 N 10 O 2 2- ·H 2 O, O-H⋯N, N-H⋯N, and N-H⋯O hydrogen bonds link the components of the structure into a three-dimensional network. In addition, there is inter-molecular π-π stacking. In all three structures, the central N atom of the nitramide is mainly sp 2 -hybridized. Bond lengths indicate delocalization of charges on the tetra-zole rings for all three compounds. Compound (II) was found to be a non-merohedral twin and was solved and refined in the major component.

Two-dimensional plasmons in the random impedance network model of disordered thin film nanocomposites

NASA Astrophysics Data System (ADS)

Olekhno, N. A.; Beltukov, Y. M.

2018-05-01

Random impedance networks are widely used as a model to describe plasmon resonances in disordered metal-dielectric nanocomposites. Two-dimensional networks are applied when considering thin films despite the fact that such networks correspond to the two-dimensional electrodynamics [Clerc et al., J. Phys. A 29, 4781 (1996), 10.1088/0305-4470/29/16/006]. In the present work, we propose a model of two-dimensional systems with the three-dimensional Coulomb interaction and show that this model is equivalent to the planar network with long-range capacitive links between distant sites. In the case of a metallic film, we obtain the well-known dispersion of two-dimensional plasmons ω ∝√{k } . We study the evolution of resonances with a decrease in the metal filling factor within the framework of the proposed model. In the subcritical region with the metal filling p lower than the percolation threshold pc, we observe a gap with Lifshitz tails in the spectral density of states (DOS). In the supercritical region p >pc , the DOS demonstrates a crossover between plane-wave two-dimensional plasmons and resonances of finite clusters.

Computer hardware fault administration

DOEpatents

Archer, Charles J.; Megerian, Mark G.; Ratterman, Joseph D.; Smith, Brian E.

2010-09-14

Computer hardware fault administration carried out in a parallel computer, where the parallel computer includes a plurality of compute nodes. The compute nodes are coupled for data communications by at least two independent data communications networks, where each data communications network includes data communications links connected to the compute nodes. Typical embodiments carry out hardware fault administration by identifying a location of a defective link in the first data communications network of the parallel computer and routing communications data around the defective link through the second data communications network of the parallel computer.

Bimodal wireless sensing with dual-channel wide bandgap heterostructure varactors

NASA Astrophysics Data System (ADS)

Deen, David A.; Osinsky, Andrei; Miller, Ross

2014-03-01

A capacitive wireless sensing scheme is developed that utilizes an AlN/GaN-based dual-channel varactor. The dual-channel heterostructure affords two capacitance plateaus within the capacitance-voltage (CV) characteristic, owing to the two parallel two-dimensional electron gases (2DEGs) located at respective AlN/GaN interfaces. The capacitance plateaus are leveraged for the definition of two resonant states of the sensor when implemented in an inductively-coupled resonant LRC network for wireless readout. The physics-based CV model is compared with published experimental results, which serve as a basis for the sensor embodiment. The bimodal resonant sensor is befitting for a broad application space ranging from gas, electrostatic, and piezoelectric sensors to biological and chemical detection.

Contribution of human skin topography to the characterization of dynamic skin tension during senescence: morpho-mechanical approach

NASA Astrophysics Data System (ADS)

Zahouani, H.; Djaghloul, M.; Vargiolu, R.; Mezghani, S.; Mansori, M. E. L.

2014-03-01

The structuring of the dermis with a network of collagen and elastic fibres gives a three-dimensional structure to the skin network with directions perpendicular and parallel to the skin surface. This three-dimensional morphology prints on the surface of the stratum corneum a three dimensional network of lines which express the mechanical tension of the skin at rest. To evaluate the changes of skin morphology, we used a three-dimensional confocal microscopy and characterization of skin imaging of volar forearm microrelief. We have accurately characterize the role of skin line network during chronological aging with the identification of depth scales on the network of lines (z <= 60μm) and the network of lines covering Langer's lines (z > 60 microns). During aging has been highlighted lower rows for elastic fibres, the decrease weakened the tension and results in enlargement of the plates of the microrelief, which gives us a geometric pertinent indicator to quantify the loss of skin tension and assess the stage of aging. The study of 120 Caucasian women shows that ageing in the volar forearm zone results in changes in the morphology of the line network organisation. The decrease in secondary lines (z <= 60 μm) is counterbalanced by an increase in the depth of the primary lines (z > 60 μm) and an accentuation of the anisotropy index.

trans-Bis[4-amino-3,5-bis­(2-pyrid­yl)-4H-1,2,4-triazole-κN 3]diaqua­cobalt(II) bis­(3-carb­oxy-5-nitro­benzoate)

PubMed Central

Wang, Xi; Shao, Chun-Fu; Li, Cheng-Peng

2011-01-01

The title complex, [Co(C12H10N6)2(H2O)2](C8H4NO6)2, is composed of a mononuclear cobalt(II) cation and two 3-carb­oxy-5-nitro­benzoate anions for charge balance. In the cation, the CoII atom is six-coordinated in a distorted octa­hedral geometry. It bonds to two O atoms of two water mol­ecules, and two pairs of N atoms from two 4-amino-3,5-bis­(2-pyrid­yl)-4H-1,2,4-triazole mol­ecules, which behave as bidentate chelating ligands. There are intra­molecular N—H⋯N hydrogen bonds in the cation. In the crystal, there are a number of inter­molecular N—H⋯O and O—H⋯O hydrogen bonds, as well as inter­molecular π–π stacking inter­actions [centroid–centroid distances = 3.657 (2) and 3.847 (2) Å], that link the mol­ecules into two-dimensional networks lying parallel to the ab plane. The presence of C—H⋯O inter­actions leads to the formation of a three-dimensional network. PMID:22058688

Parallel and Multivalued Logic by the Two-Dimensional Photon-Echo Response of a Rhodamine–DNA Complex

PubMed Central

2015-01-01

Implementing parallel and multivalued logic operations at the molecular scale has the potential to improve the miniaturization and efficiency of a new generation of nanoscale computing devices. Two-dimensional photon-echo spectroscopy is capable of resolving dynamical pathways on electronic and vibrational molecular states. We experimentally demonstrate the implementation of molecular decision trees, logic operations where all possible values of inputs are processed in parallel and the outputs are read simultaneously, by probing the laser-induced dynamics of populations and coherences in a rhodamine dye mounted on a short DNA duplex. The inputs are provided by the bilinear interactions between the molecule and the laser pulses, and the output values are read from the two-dimensional molecular response at specific frequencies. Our results highlights how ultrafast dynamics between multiple molecular states induced by light–matter interactions can be used as an advantage for performing complex logic operations in parallel, operations that are faster than electrical switching. PMID:25984269

Particle simulation of plasmas on the massively parallel processor

NASA Technical Reports Server (NTRS)

Gledhill, I. M. A.; Storey, L. R. O.

1987-01-01

Particle simulations, in which collective phenomena in plasmas are studied by following the self consistent motions of many discrete particles, involve several highly repetitive sets of calculations that are readily adaptable to SIMD parallel processing. A fully electromagnetic, relativistic plasma simulation for the massively parallel processor is described. The particle motions are followed in 2 1/2 dimensions on a 128 x 128 grid, with periodic boundary conditions. The two dimensional simulation space is mapped directly onto the processor network; a Fast Fourier Transform is used to solve the field equations. Particle data are stored according to an Eulerian scheme, i.e., the information associated with each particle is moved from one local memory to another as the particle moves across the spatial grid. The method is applied to the study of the nonlinear development of the whistler instability in a magnetospheric plasma model, with an anisotropic electron temperature. The wave distribution function is included as a new diagnostic to allow simulation results to be compared with satellite observations.

High-performance parallel analysis of coupled problems for aircraft propulsion

NASA Technical Reports Server (NTRS)

Felippa, C. A.; Farhat, C.; Chen, P.-S.; Gumaste, U.; Leoinne, M.; Stern, P.

1995-01-01

This research program deals with the application of high-performance computing methods to the numerical simulation of complete jet engines. The program was initiated in 1993 by applying two-dimensional parallel aeroelastic codes to the interior gas flow problem of a by-pass jet engine. The fluid mesh generation, domain decomposition and solution capabilities were successfully tested. Attention was then focused on methodology for the partitioned analysis of the interaction of the gas flow with a flexible structure and with the fluid mesh motion driven by these structural displacements. The latter is treated by an ALE technique that models the fluid mesh motion as that of a fictitious mechanical network laid along the edges of near-field fluid elements. New partitioned analysis procedures to treat this coupled 3-component problem were developed in 1994. These procedures involved delayed corrections and subcycling, and have been successfully tested on several massively parallel computers. For the global steady-state axisymmetric analysis of a complete engine we have decided to use the NASA-sponsored ENG10 program, which uses a regular FV-multiblock-grid discretization in conjunction with circumferential averaging to include effects of blade forces, loss, combustor heat addition, blockage, bleeds and convective mixing. A load-balancing preprocessor for parallel versions of ENG10 has been developed. It is planned to use the steady-state global solution provided by ENG10 as input to a localized three-dimensional FSI analysis for engine regions where aeroelastic effects may be important.

Extraction of drainage networks from large terrain datasets using high throughput computing

NASA Astrophysics Data System (ADS)

Gong, Jianya; Xie, Jibo

2009-02-01

Advanced digital photogrammetry and remote sensing technology produces large terrain datasets (LTD). How to process and use these LTD has become a big challenge for GIS users. Extracting drainage networks, which are basic for hydrological applications, from LTD is one of the typical applications of digital terrain analysis (DTA) in geographical information applications. Existing serial drainage algorithms cannot deal with large data volumes in a timely fashion, and few GIS platforms can process LTD beyond the GB size. High throughput computing (HTC), a distributed parallel computing mode, is proposed to improve the efficiency of drainage networks extraction from LTD. Drainage network extraction using HTC involves two key issues: (1) how to decompose the large DEM datasets into independent computing units and (2) how to merge the separate outputs into a final result. A new decomposition method is presented in which the large datasets are partitioned into independent computing units using natural watershed boundaries instead of using regular 1-dimensional (strip-wise) and 2-dimensional (block-wise) decomposition. Because the distribution of drainage networks is strongly related to watershed boundaries, the new decomposition method is more effective and natural. The method to extract natural watershed boundaries was improved by using multi-scale DEMs instead of single-scale DEMs. A HTC environment is employed to test the proposed methods with real datasets.

Parallel computation for biological sequence comparison: comparing a portable model to the native model for the Intel Hypercube.

PubMed Central

Nadkarni, P. M.; Miller, P. L.

1991-01-01

A parallel program for inter-database sequence comparison was developed on the Intel Hypercube using two models of parallel programming. One version was built using machine-specific Hypercube parallel programming commands. The other version was built using Linda, a machine-independent parallel programming language. The two versions of the program provide a case study comparing these two approaches to parallelization in an important biological application area. Benchmark tests with both programs gave comparable results with a small number of processors. As the number of processors was increased, the Linda version was somewhat less efficient. The Linda version was also run without change on Network Linda, a virtual parallel machine running on a network of desktop workstations. PMID:1807632

Poly[[[μ3-N′-(carboxymethyl)ethylene­di­amine-N,N,N′-triacetato]dysprosium(III)] trihydrate

PubMed Central

Zhuang, Xiaomei; Long, Qingping; Wang, Jun

2010-01-01

In the title coordination polymer, {[Dy(C10H13N2O8)]·3H2O}n, the dysprosium(III) ion is coordinated by two N atoms and six O atoms from three different (carb­oxy­meth­yl)ethyl­ene­diamine­triacetate ligands in a distorted square-anti­prismatic geometry. The ligands connect the metal atoms, forming layers parallel to the ab plane. O—H⋯O hydrogen bonds further assemble adjacent layers into a three-dimensional supra­molecular network. PMID:21588859

Massively parallel GPU-accelerated minimization of classical density functional theory

NASA Astrophysics Data System (ADS)

Stopper, Daniel; Roth, Roland

2017-08-01

In this paper, we discuss the ability to numerically minimize the grand potential of hard disks in two-dimensional and of hard spheres in three-dimensional space within the framework of classical density functional and fundamental measure theory on modern graphics cards. Our main finding is that a massively parallel minimization leads to an enormous performance gain in comparison to standard sequential minimization schemes. Furthermore, the results indicate that in complex multi-dimensional situations, a heavy parallel minimization of the grand potential seems to be mandatory in order to reach a reasonable balance between accuracy and computational cost.

Bis(μ-2-{[2-(1,3-benzothia­zol-2-yl)hydrazinyl­idene]meth­yl}-6-meth­oxy­phenolato)bis­[dinitratodysprosium(III)] methanol disolvate

PubMed Central

Xu, Xuebin; Ding, Shuai; Shen, Si; Tang, Jinkui; Liu, Zhiliang

2011-01-01

In the centrosymmetric dinuclear title compound, [Dy2(C15H12N3O2S)2(NO3)4]·2CH3OH, the two DyIII atoms are coordinated by two deprotonated 2-{[2-(1,3-benzothia­zol-2-yl)hydrazinyl­idene]meth­yl}-6-meth­oxy­phenol ligands and four nitrate ions, all of which are chelating. The crystal packing is stabilized by inter­molecular N—H⋯O hydrogen bonds and weak O—H⋯O inter­actions, forming a two-dimensional network parallel to (010). PMID:21754674

14-Meth­oxy-4,6-dimethyl-9-phenyl-8,12-dioxa-4,6-di­aza­tetra­cyclo­[8.8.0.02,7.013,18]octa­deca-2(7),13,15,17-tetra­ene-3,5,11-trione

PubMed Central

Jagadeesan, G; Jayashree, S.; Kannan, D.; Bakthadoss, M.; Aravindhan, S.

2013-01-01

The title compound, C23H20N2O6, crystallizes with two mol­ecules in the asymmetric unit in which the dihedral angles between the mean planes of the pyran and phenyl rings are 66.6 (1) and 61.9 (1) °. The fused pyrone and pyran rings each adopts a sofa conformation. In the crystal, C—H⋯O hydrogen bonds link the mol­ecules, forming a two-dimensional network parallel to [001]. PMID:24109298

14-Eth­oxy-4,6-dimethyl-9-phenyl-8,12-dioxa-4,6-diaza­tetra­cyclo­[8.8.0.02,7.013,18]octa­deca-2(7),13,15,17-tetra­ene-3,5,11-trione

PubMed Central

Jagadeesan, G.; Kannan, D.; Bakthadoss, M.; Aravindhan, S.

2013-01-01

In the title compound, C23H20N2O6, the fused pyrone and pyran rings each adopt a sofa conformation. The dihedral angle between the mean planes of the pyran and phenyl rings is 61.9 (1)°. In the crystal, mol­ecules are linked by two pairs of C—H⋯O hydrogen bonds, forming dimers. These dimers are linked via a third C—H⋯O hydrogen bond, forming a two-dimensional network parallel to (10-2). PMID:23476462

A three-dimensional spectral algorithm for simulations of transition and turbulence

NASA Technical Reports Server (NTRS)

Zang, T. A.; Hussaini, M. Y.

1985-01-01

A spectral algorithm for simulating three dimensional, incompressible, parallel shear flows is described. It applies to the channel, to the parallel boundary layer, and to other shear flows with one wall bounded and two periodic directions. Representative applications to the channel and to the heated boundary layer are presented.

Modified neural networks for rapid recovery of tokamak plasma parameters for real time control

NASA Astrophysics Data System (ADS)

Sengupta, A.; Ranjan, P.

2002-07-01

Two modified neural network techniques are used for the identification of the equilibrium plasma parameters of the Superconducting Steady State Tokamak I from external magnetic measurements. This is expected to ultimately assist in a real time plasma control. As different from the conventional network structure where a single network with the optimum number of processing elements calculates the outputs, a multinetwork system connected in parallel does the calculations here in one of the methods. This network is called the double neural network. The accuracy of the recovered parameters is clearly more than the conventional network. The other type of neural network used here is based on the statistical function parametrization combined with a neural network. The principal component transformation removes linear dependences from the measurements and a dimensional reduction process reduces the dimensionality of the input space. This reduced and transformed input set, rather than the entire set, is fed into the neural network input. This is known as the principal component transformation-based neural network. The accuracy of the recovered parameters in the latter type of modified network is found to be a further improvement over the accuracy of the double neural network. This result differs from that obtained in an earlier work where the double neural network showed better performance. The conventional network and the function parametrization methods have also been used for comparison. The conventional network has been used for an optimization of the set of magnetic diagnostics. The effective set of sensors, as assessed by this network, are compared with the principal component based network. Fault tolerance of the neural networks has been tested. The double neural network showed the maximum resistance to faults in the diagnostics, while the principal component based network performed poorly. Finally the processing times of the methods have been compared. The double network and the principal component network involve the minimum computation time, although the conventional network also performs well enough to be used in real time.

Parallel Algorithms for Switching Edges in Heterogeneous Graphs.

PubMed

Bhuiyan, Hasanuzzaman; Khan, Maleq; Chen, Jiangzhuo; Marathe, Madhav

2017-06-01

An edge switch is an operation on a graph (or network) where two edges are selected randomly and one of their end vertices are swapped with each other. Edge switch operations have important applications in graph theory and network analysis, such as in generating random networks with a given degree sequence, modeling and analyzing dynamic networks, and in studying various dynamic phenomena over a network. The recent growth of real-world networks motivates the need for efficient parallel algorithms. The dependencies among successive edge switch operations and the requirement to keep the graph simple (i.e., no self-loops or parallel edges) as the edges are switched lead to significant challenges in designing a parallel algorithm. Addressing these challenges requires complex synchronization and communication among the processors leading to difficulties in achieving a good speedup by parallelization. In this paper, we present distributed memory parallel algorithms for switching edges in massive networks. These algorithms provide good speedup and scale well to a large number of processors. A harmonic mean speedup of 73.25 is achieved on eight different networks with 1024 processors. One of the steps in our edge switch algorithms requires the computation of multinomial random variables in parallel. This paper presents the first non-trivial parallel algorithm for the problem, achieving a speedup of 925 using 1024 processors.

Parallel Algorithms for Switching Edges in Heterogeneous Graphs☆

PubMed Central

Khan, Maleq; Chen, Jiangzhuo; Marathe, Madhav

2017-01-01

An edge switch is an operation on a graph (or network) where two edges are selected randomly and one of their end vertices are swapped with each other. Edge switch operations have important applications in graph theory and network analysis, such as in generating random networks with a given degree sequence, modeling and analyzing dynamic networks, and in studying various dynamic phenomena over a network. The recent growth of real-world networks motivates the need for efficient parallel algorithms. The dependencies among successive edge switch operations and the requirement to keep the graph simple (i.e., no self-loops or parallel edges) as the edges are switched lead to significant challenges in designing a parallel algorithm. Addressing these challenges requires complex synchronization and communication among the processors leading to difficulties in achieving a good speedup by parallelization. In this paper, we present distributed memory parallel algorithms for switching edges in massive networks. These algorithms provide good speedup and scale well to a large number of processors. A harmonic mean speedup of 73.25 is achieved on eight different networks with 1024 processors. One of the steps in our edge switch algorithms requires the computation of multinomial random variables in parallel. This paper presents the first non-trivial parallel algorithm for the problem, achieving a speedup of 925 using 1024 processors. PMID:28757680

[Three-dimensional parallel collagen scaffold promotes tendon extracellular matrix formation].

PubMed

Zheng, Zefeng; Shen, Weiliang; Le, Huihui; Dai, Xuesong; Ouyang, Hongwei; Chen, Weishan

2016-03-01

To investigate the effects of three-dimensional parallel collagen scaffold on the cell shape, arrangement and extracellular matrix formation of tendon stem cells. Parallel collagen scaffold was fabricated by unidirectional freezing technique, while random collagen scaffold was fabricated by freeze-drying technique. The effects of two scaffolds on cell shape and extracellular matrix formation were investigated in vitro by seeding tendon stem/progenitor cells and in vivo by ectopic implantation. Parallel and random collagen scaffolds were produced successfully. Parallel collagen scaffold was more akin to tendon than random collagen scaffold. Tendon stem/progenitor cells were spindle-shaped and unified orientated in parallel collagen scaffold, while cells on random collagen scaffold had disorder orientation. Two weeks after ectopic implantation, cells had nearly the same orientation with the collagen substance. In parallel collagen scaffold, cells had parallel arrangement, and more spindly cells were observed. By contrast, cells in random collagen scaffold were disorder. Parallel collagen scaffold can induce cells to be in spindly and parallel arrangement, and promote parallel extracellular matrix formation; while random collagen scaffold can induce cells in random arrangement. The results indicate that parallel collagen scaffold is an ideal structure to promote tendon repairing.

A parallel algorithm for the two-dimensional time fractional diffusion equation with implicit difference method.

PubMed

Gong, Chunye; Bao, Weimin; Tang, Guojian; Jiang, Yuewen; Liu, Jie

2014-01-01

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(M(x)M(y)N(2)). 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.

Electromagnetic Design of a Magnetically Coupled Spatial Power Combiner

NASA Astrophysics Data System (ADS)

Bulcha, B. T.; Cataldo, G.; Stevenson, T. R.; U-Yen, K.; Moseley, S. H.; Wollack, E. J.

2018-04-01

The design of a two-dimensional spatial beam-combining network employing a parallel-plate superconducting waveguide filled with a monocrystalline silicon dielectric substrate is presented. This component uses arrays of magnetically coupled antenna elements to achieve high coupling efficiency and full sampling of the intensity distribution while avoiding diffractive losses in the multimode waveguide region. These attributes enable the structure's use in realizing compact far-infrared spectrometers for astrophysical and instrumentation applications. If unterminated, reflections within a finite-sized spatial beam combiner can potentially lead to spurious couplings between elements. A planar meta-material electromagnetic absorber is implemented to control this response within the device. This broadband termination absorbs greater than 0.99 of the power over the 1.7:1 operational band at angles ranging from normal to near-parallel incidence. The design approach, simulations and applications of the spatial power combiner and meta-material termination structure are presented.

High-performance parallel analysis of coupled problems for aircraft propulsion

NASA Technical Reports Server (NTRS)

Felippa, C. A.; Farhat, C.; Lanteri, S.; Maman, N.; Piperno, S.; Gumaste, U.

1994-01-01

This research program deals with the application of high-performance computing methods for the analysis of complete jet engines. We have entitled this program by applying the two dimensional parallel aeroelastic codes to the interior gas flow problem of a bypass jet engine. The fluid mesh generation, domain decomposition, and solution capabilities were successfully tested. We then focused attention on methodology for the partitioned analysis of the interaction of the gas flow with a flexible structure and with the fluid mesh motion that results from these structural displacements. This is treated by a new arbitrary Lagrangian-Eulerian (ALE) technique that models the fluid mesh motion as that of a fictitious mass-spring network. New partitioned analysis procedures to treat this coupled three-component problem are developed. These procedures involved delayed corrections and subcycling. Preliminary results on the stability, accuracy, and MPP computational efficiency are reported.

Reconfigurable microfluidic hanging drop network for multi-tissue interaction and analysis.

PubMed

Frey, Olivier; Misun, Patrick M; Fluri, David A; Hengstler, Jan G; Hierlemann, Andreas

2014-06-30

Integration of multiple three-dimensional microtissues into microfluidic networks enables new insights in how different organs or tissues of an organism interact. Here, we present a platform that extends the hanging-drop technology, used for multi-cellular spheroid formation, to multifunctional complex microfluidic networks. Engineered as completely open, 'hanging' microfluidic system at the bottom of a substrate, the platform features high flexibility in microtissue arrangements and interconnections, while fabrication is simple and operation robust. Multiple spheroids of different cell types are formed in parallel on the same platform; the different tissues are then connected in physiological order for multi-tissue experiments through reconfiguration of the fluidic network. Liquid flow is precisely controlled through the hanging drops, which enable nutrient supply, substance dosage and inter-organ metabolic communication. The possibility to perform parallelized microtissue formation on the same chip that is subsequently used for complex multi-tissue experiments renders the developed platform a promising technology for 'body-on-a-chip'-related research.

3D simulations of early blood vessel formation

NASA Astrophysics Data System (ADS)

Cavalli, F.; Gamba, A.; Naldi, G.; Semplice, M.; Valdembri, D.; Serini, G.

2007-08-01

Blood vessel networks form by spontaneous aggregation of individual cells migrating toward vascularization sites (vasculogenesis). A successful theoretical model of two-dimensional experimental vasculogenesis has been recently proposed, showing the relevance of percolation concepts and of cell cross-talk (chemotactic autocrine loop) to the understanding of this self-aggregation process. Here we study the natural 3D extension of the computational model proposed earlier, which is relevant for the investigation of the genuinely three-dimensional process of vasculogenesis in vertebrate embryos. The computational model is based on a multidimensional Burgers equation coupled with a reaction diffusion equation for a chemotactic factor and a mass conservation law. The numerical approximation of the computational model is obtained by high order relaxed schemes. Space and time discretization are performed by using TVD schemes and, respectively, IMEX schemes. Due to the computational costs of realistic simulations, we have implemented the numerical algorithm on a cluster for parallel computation. Starting from initial conditions mimicking the experimentally observed ones, numerical simulations produce network-like structures qualitatively similar to those observed in the early stages of in vivo vasculogenesis. We develop the computation of critical percolative indices as a robust measure of the network geometry as a first step towards the comparison of computational and experimental data.

Auto- and hetero-associative memory using a 2-D optical logic gate

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

1989-01-01

An optical associative memory system suitable for both auto- and hetero-associative recall is demonstrated. This system utilizes Hamming distance as the similarity measure between a binary input and a memory image with the aid of a two-dimensional optical EXCLUSIVE OR (XOR) gate and a parallel electronics comparator module. Based on the Hamming distance measurement, this optical associative memory performs a nearest neighbor search and the result is displayed in the output plane in real-time. This optical associative memory is fast and noniterative and produces no output spurious states as compared with that of the Hopfield neural network model.

Auto- and hetero-associative memory using a 2-D optical logic gate

NASA Astrophysics Data System (ADS)

Chao, Tien-Hsin

1989-06-01

An optical associative memory system suitable for both auto- and hetero-associative recall is demonstrated. This system utilizes Hamming distance as the similarity measure between a binary input and a memory image with the aid of a two-dimensional optical EXCLUSIVE OR (XOR) gate and a parallel electronics comparator module. Based on the Hamming distance measurement, this optical associative memory performs a nearest neighbor search and the result is displayed in the output plane in real-time. This optical associative memory is fast and noniterative and produces no output spurious states as compared with that of the Hopfield neural network model.

4-{[4-(Hy­droxy­meth­yl)piperidin-1-yl]meth­yl}phenol

PubMed Central

Simões, M. C. R.; Landre, I. M. R.; Moreira, M. S.; Viegas Jr, C.; Doriguetto, A. C.

2012-01-01

In the title compound, C13H19NO2, the piperidine ring has a chair conformation with the exocyclic N—C bond in an equatorial position. In the crystal, mol­ecules are linked head-to-tail by phenol O—H⋯O hydrogen bonds to hy­droxy­methyl­ene O-atom acceptors, forming chains which extend along [100]. These chains form two-dimensional networks lying parallel to (101) through cyclic hydrogen-bonding associations [graph set R 4 4(30)], involving hy­droxy O—H donors and piperidine N-atom acceptors. PMID:22798921

3-(4-Hy­droxy­phen­yl)-7-meth­oxy­chroman-4-one monohydrate

PubMed Central

Xiao, Zhu-Ping; Peng, Zhu-Yun; Luo, Qun; Wu, Ying; Yang, Ye-Ling

2011-01-01

In the title compound, C16H14O4·H2O, the dihedral angle betwen the benzene rings is 71.4 (6)°. The pyran ring is in a sofa conformation. In the crystal, O—H⋯O hydrogen bonds connect the components into a two-dimensional network parallel to (010), incorporating C 2 2(4) and C 2 2(11) chains. In addition, weak C—H⋯O, C—H⋯π and π–π stacking inter­actions [centroid–centroid distance = 3.768 (2) Å] are present. PMID:22199730

Supramolecular hydrogen-bonding networks in bis(adeninium) phthalate phthalic acid 1.45-hydrate.

PubMed

Sridhar, Balasubramanian; Ravikumar, Krishnan

2007-04-01

In the title compound, 2C(5)H(6)N(5)(+).C(8)H(4)O(4)(2-).C(8)H(6)O(4).1.45H(2)O, the asymmetric unit comprises two adeninium cations, two half phthalate anions with crystallographic C(2) symmetry, one neutral phthalic acid molecule, and one fully occupied and one partially occupied site (0.45) for water molecules. The adeninium cations form N-H...O hydrogen bonds with the phthalate anions. The cations also form infinite one-dimensional polymeric ribbons via N-H...N interactions. In the crystal packing, hydrogen-bonded columns of cations, anions and phthalate anions extend parallel to the c axis. The water molecules crosslink adjacent columns into hydrogen-bonded layers.

A parallel simulated annealing algorithm for standard cell placement on a hypercube computer

NASA Technical Reports Server (NTRS)

Jones, Mark Howard

1987-01-01

A parallel version of a simulated annealing algorithm is presented which is targeted to run on a hypercube computer. A strategy for mapping the cells in a two dimensional area of a chip onto processors in an n-dimensional hypercube is proposed such that both small and large distance moves can be applied. Two types of moves are allowed: cell exchanges and cell displacements. The computation of the cost function in parallel among all the processors in the hypercube is described along with a distributed data structure that needs to be stored in the hypercube to support parallel cost evaluation. A novel tree broadcasting strategy is used extensively in the algorithm for updating cell locations in the parallel environment. Studies on the performance of the algorithm on example industrial circuits show that it is faster and gives better final placement results than the uniprocessor simulated annealing algorithms. An improved uniprocessor algorithm is proposed which is based on the improved results obtained from parallelization of the simulated annealing algorithm.

A parallel finite-difference method for computational aerodynamics

NASA Technical Reports Server (NTRS)

Swisshelm, Julie M.

1989-01-01

A finite-difference scheme for solving complex three-dimensional aerodynamic flow on parallel-processing supercomputers is presented. The method consists of a basic flow solver with multigrid convergence acceleration, embedded grid refinements, and a zonal equation scheme. Multitasking and vectorization have been incorporated into the algorithm. Results obtained include multiprocessed flow simulations from the Cray X-MP and Cray-2. Speedups as high as 3.3 for the two-dimensional case and 3.5 for segments of the three-dimensional case have been achieved on the Cray-2. The entire solver attained a factor of 2.7 improvement over its unitasked version on the Cray-2. The performance of the parallel algorithm on each machine is analyzed.

Distributed run of a one-dimensional model in a regional application using SOAP-based web services

NASA Astrophysics Data System (ADS)

Smiatek, Gerhard

This article describes the setup of a distributed computing system in Perl. It facilitates the parallel run of a one-dimensional environmental model on a number of simple network PC hosts. The system uses Simple Object Access Protocol (SOAP) driven web services offering the model run on remote hosts and a multi-thread environment distributing the work and accessing the web services. Its application is demonstrated in a regional run of a process-oriented biogenic emission model for the area of Germany. Within a network consisting of up to seven web services implemented on Linux and MS-Windows hosts, a performance increase of approximately 400% has been reached compared to a model run on the fastest single host.

Capacity of Heterogeneous Mobile Wireless Networks with D-Delay Transmission Strategy.

PubMed

Wu, Feng; Zhu, Jiang; Xi, Zhipeng; Gao, Kai

2016-03-25

This paper investigates the capacity problem of heterogeneous wireless networks in mobility scenarios. A heterogeneous network model which consists of n normal nodes and m helping nodes is proposed. Moreover, we propose a D-delay transmission strategy to ensure that every packet can be delivered to its destination nodes with limited delay. Different from most existing network schemes, our network model has a novel two-tier architecture. The existence of helping nodes greatly improves the network capacity. Four types of mobile networks are studied in this paper: i.i.d. fast mobility model and slow mobility model in two-dimensional space, i.i.d. fast mobility model and slow mobility model in three-dimensional space. Using the virtual channel model, we present an intuitive analysis of the capacity of two-dimensional mobile networks and three-dimensional mobile networks, respectively. Given a delay constraint D, we derive the asymptotic expressions for the capacity of the four types of mobile networks. Furthermore, the impact of D and m to the capacity of the whole network is analyzed. Our findings provide great guidance for the future design of the next generation of networks.

Electric Current Flow Through Two-Dimensional Networks

NASA Astrophysics Data System (ADS)

Gaspard, Mallory

In modern nanotechnology, two-dimensional atomic network structures boast promising applications as nanoscale circuit boards to serve as the building blocks of more sustainable and efficient, electronic devices. However, properties associated with the network connectivity can be beneficial or deleterious to the current flow. Taking a computational approach, we will study large uniform networks, as well as large random networks using Kirchhoff's Equations in conjunction with graph theoretical measures of network connectedness and flows, to understand how network connectivity affects overall ability for successful current flow throughout a network. By understanding how connectedness affects flow, we may develop new ways to design more efficient two-dimensional materials for the next generation of nanoscale electronic devices, and we will gain a deeper insight into the intricate balance between order and chaos in the universe. Rensselaer Polytechnic Institute, SURP Institutional Grant.

Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment.

PubMed

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 quality solutions can be obtained within relatively short time. This integrated approach is a promising way for inferring large networks.

Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment

PubMed Central

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 computational framework, high quality solutions can be obtained within relatively short time. This integrated approach is a promising way for inferring large networks. PMID:24428926

Efficient implementation of a 3-dimensional ADI method on the iPSC/860

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

Van der Wijngaart, R.F.

1993-12-31

A comparison is made between several domain decomposition strategies for the solution of three-dimensional partial differential equations on a MIMD distributed memory parallel computer. The grids used are structured, and the numerical algorithm is ADI. Important implementation issues regarding load balancing, storage requirements, network latency, and overlap of computations and communications are discussed. Results of the solution of the three-dimensional heat equation on the Intel iPSC/860 are presented for the three most viable methods. It is found that the Bruno-Cappello decomposition delivers optimal computational speed through an almost complete elimination of processor idle time, while providing good memory efficiency.

Functional Parallel Factor Analysis for Functions of One- and Two-dimensional Arguments.

PubMed

Choi, Ji Yeh; Hwang, Heungsun; Timmerman, Marieke E

2018-03-01

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.

Image matrix processor for fast multi-dimensional computations

DOEpatents

Roberson, George P.; Skeate, Michael F.

1996-01-01

An apparatus for multi-dimensional computation which comprises a computation engine, including a plurality of processing modules. The processing modules are configured in parallel and compute respective contributions to a computed multi-dimensional image of respective two dimensional data sets. A high-speed, parallel access storage system is provided which stores the multi-dimensional data sets, and a switching circuit routes the data among the processing modules in the computation engine and the storage system. A data acquisition port receives the two dimensional data sets representing projections through an image, for reconstruction algorithms such as encountered in computerized tomography. The processing modules include a programmable local host, by which they may be configured to execute a plurality of different types of multi-dimensional algorithms. The processing modules thus include an image manipulation processor, which includes a source cache, a target cache, a coefficient table, and control software for executing image transformation routines using data in the source cache and the coefficient table and loading resulting data in the target cache. The local host processor operates to load the source cache with a two dimensional data set, loads the coefficient table, and transfers resulting data out of the target cache to the storage system, or to another destination.

A class of parallel algorithms for computation of the manipulator inertia matrix

NASA Technical Reports Server (NTRS)

Fijany, Amir; Bejczy, Antal K.

1989-01-01

Parallel and parallel/pipeline algorithms for computation of the manipulator inertia matrix are presented. An algorithm based on composite rigid-body spatial inertia method, which provides better features for parallelization, is used for the computation of the inertia matrix. Two parallel algorithms are developed which achieve the time lower bound in computation. Also described is the mapping of these algorithms with topological variation on a two-dimensional processor array, with nearest-neighbor connection, and with cardinality variation on a linear processor array. An efficient parallel/pipeline algorithm for the linear array was also developed, but at significantly higher efficiency.

Competition of wormholes during the evolution of cave passages

NASA Astrophysics Data System (ADS)

Gabrovsek, Franci; Dreybrodt, Wolfgang

2017-04-01

Reactive fronts in two-dimensional plane parallel fractures, with constant head difference between input and output and with diffusion controlled first order reaction rates R = keff ṡ (Ceq - C), where keff = k ṡ (1 + ka/6D)-1, are instable to infinitesimal perturbations in fracture aperture width (1), causing spontaneous fingering of the reactive front resulting in the formation of wormholes. C is the actual concentration and Ceq the equilibrium concentration, a, is the actual aperture width of the fracture , and D the constant of molecular diffusion. Fingering happens also in plane-parallel rough fractures where it is triggered by the existence of statistically more favorable pathways. The same behavior is observed in rectangular two-dimensional networks of "one-dimensional" smooth fractures used in modeling the evolution of caves in soluble rock (2). Here the formation of caves can be regarded as the evolution of wormholes along the two-dimensional network. Once fingering has been triggered, either by instability or by roughness, many small fingers compete with each other and only a few survive. Here we investigate the competition between two seeded fingers in initially homogeneous fracture networks with identical aperture width of all fractures and also in inhomogeneous ones where the aperture widths are distributed log normally. In both cases our modeling reveals the rules of competition: By instability one of the fingers grows faster than its competitor therefore penetrating somewhat deeper. As a consequence the hydraulic head at its tip is higher than that close to the tip of the shorter finger. Therefore the fractures connecting the tip regions of both fingers carry flow from the deep finger to the tip region of its competitor. This cross-flow is replaced by increasing inflow of aggressive solution into the input of the winner, enhancing further dissolution and growth. On the other hand the cross-flow increases the head at the tip of the losing finger, and consequently decreases inflow of aggressive solution into it, thus inhibiting its further evolution. This mechanism supports further growth of the winner (wormhole) and stops the growth of its competitor. Similar competition happens in the case of several fingers competing. In any case we observe flow from the winning fingers to the loosing ones. The communication between the competitors is always established by cross flow between its tip regions. We will present various scenarios of wormhole formation, which demonstrate details of the competition of fingers arising from either the reactive instability or from the statistical distribution of fracture aperture widths. In conclusion we find that the initiation of wormholes results either from instability or from the statistical distribution of favorable pathways. Once growth of fingers has been initiated the evolution of the wormhole patterns becomes deterministic. (1) Szymczak, P., and A.J.C. Ladd (2011), The initial stages of cave formation: Beyond the one-dimensional paradigm, Earth Planet. Sci. Lett. 301, 424-432 (2) Dreybrodt, W., Gabrovšek, F., Romanov, D.(2005) Processes of Speleogenesis: A Modeling Approach. ZRC Publishing, Karst Research Institute at ZRC SAZU, Ljubljana

On the Transition from Two-Dimensional to Three-Dimensional MHD Turbulence

NASA Technical Reports Server (NTRS)

Thess, A.; Zikanov, Oleg

2004-01-01

We report a theoretical investigation of the robustness of two-dimensional inviscid MHD flows at low magnetic Reynolds numbers with respect to three-dimensional perturbations. We analyze three model problems, namely flow in the interior of a triaxial ellipsoid, an unbounded vortex with elliptical streamlines, and a vortex sheet parallel to the magnetic field. We demonstrate that motion perpendicular to the magnetic field with elliptical streamlines becomes unstable with respect to the elliptical instability once the velocity has reached a critical magnitude whose value tends to zero as the eccentricity of the streamlines becomes large. Furthermore, vortex sheets parallel to the magnetic field, which are unstable for any velocity and any magnetic field, are found to emit eddies with vorticity perpendicular to the magnetic field and with an aspect ratio proportional to N(sup 1/2). The results suggest that purely two-dimensional motion without Joule energy dissipation is a singular type of flow which does not represent the asymptotic behaviour of three-dimensional MHD turbulence in the limit of infinitely strong magnetic fields.

(2+1)-dimensional spacetimes containing closed timelike curves

NASA Astrophysics Data System (ADS)

Headrick, Matthew P.; Gott, J. Richard, III

1994-12-01

We investigate the global geometries of (2+1)-dimensional spacetimes as characterized by the transformations undergone by tangent spaces upon parallel transport around closed curves. We critically discuss the use of the term ``total energy-momentum'' as a label for such parallel-transport transformations, pointing out several problems with it. We then investigate parallel-transport transformations in the known (2+1)-dimensional spacetimes containing closed timelike curves (CTC's), and introduce a few new such spacetimes. Using the more specific concept of the holonomy of a closed curve, applicable in simply connected spacetimes, we emphasize that Gott's two-particle CTC-containing spacetime does not have a tachyonic geometry. Finally, we prove the following modified version of Kabat's conjecture: if a CTC is deformable to spacelike or null infinity while remaining a CTC, then its parallel-transport transformation cannot be a rotation; therefore its holonomy, if defined, cannot be a rotation other than through a multiple of 2π.

Statistical mechanics of complex neural systems and high dimensional data

NASA Astrophysics Data System (ADS)

Advani, Madhu; Lahiri, Subhaneil; Ganguli, Surya

2013-03-01

Recent experimental advances in neuroscience have opened new vistas into the immense complexity of neuronal networks. This proliferation of data challenges us on two parallel fronts. First, how can we form adequate theoretical frameworks for understanding how dynamical network processes cooperate across widely disparate spatiotemporal scales to solve important computational problems? Second, how can we extract meaningful models of neuronal systems from high dimensional datasets? To aid in these challenges, we give a pedagogical review of a collection of ideas and theoretical methods arising at the intersection of statistical physics, computer science and neurobiology. We introduce the interrelated replica and cavity methods, which originated in statistical physics as powerful ways to quantitatively analyze large highly heterogeneous systems of many interacting degrees of freedom. We also introduce the closely related notion of message passing in graphical models, which originated in computer science as a distributed algorithm capable of solving large inference and optimization problems involving many coupled variables. We then show how both the statistical physics and computer science perspectives can be applied in a wide diversity of contexts to problems arising in theoretical neuroscience and data analysis. Along the way we discuss spin glasses, learning theory, illusions of structure in noise, random matrices, dimensionality reduction and compressed sensing, all within the unified formalism of the replica method. Moreover, we review recent conceptual connections between message passing in graphical models, and neural computation and learning. Overall, these ideas illustrate how statistical physics and computer science might provide a lens through which we can uncover emergent computational functions buried deep within the dynamical complexities of neuronal networks.

Broadcasting a message in a parallel computer

DOEpatents

Berg, Jeremy E [Rochester, MN; Faraj, Ahmad A [Rochester, MN

2011-08-02

Methods, systems, and products are disclosed for broadcasting a message in a parallel computer. The parallel computer includes a plurality of compute nodes connected together using a data communications network. The data communications network optimized for point to point data communications and is characterized by at least two dimensions. The compute nodes are organized into at least one operational group of compute nodes for collective parallel operations of the parallel computer. One compute node of the operational group assigned to be a logical root. Broadcasting a message in a parallel computer includes: establishing a Hamiltonian path along all of the compute nodes in at least one plane of the data communications network and in the operational group; and broadcasting, by the logical root to the remaining compute nodes, the logical root's message along the established Hamiltonian path.

Water-network percolation transitions in hydrated yeast

NASA Astrophysics Data System (ADS)

Sokołowska, Dagmara; Król-Otwinowska, Agnieszka; Mościcki, Józef K.

2004-11-01

We discovered two percolation processes in succession in dc conductivity of bulk baker’s yeast in the course of dehydration. Critical exponents characteristic for the three-dimensional network for heavily hydrated system, and two dimensions in the light hydration limit, evidenced a dramatic change of the water network dimensionality in the dehydration process.

Highly Parallel Alternating Directions Algorithm for Time Dependent Problems

NASA Astrophysics Data System (ADS)

Ganzha, M.; Georgiev, K.; Lirkov, I.; Margenov, S.; Paprzycki, M.

2011-11-01

In our work, we consider the time dependent Stokes equation on a finite time interval and on a uniform rectangular mesh, written in terms of velocity and pressure. For this problem, a parallel algorithm based on a novel direction splitting approach is developed. Here, the pressure equation is derived from a perturbed form of the continuity equation, in which the incompressibility constraint is penalized in a negative norm induced by the direction splitting. The scheme used in the algorithm is composed of two parts: (i) velocity prediction, and (ii) pressure correction. This is a Crank-Nicolson-type two-stage time integration scheme for two and three dimensional parabolic problems in which the second-order derivative, with respect to each space variable, is treated implicitly while the other variable is made explicit at each time sub-step. In order to achieve a good parallel performance the solution of the Poison problem for the pressure correction is replaced by solving a sequence of one-dimensional second order elliptic boundary value problems in each spatial direction. The parallel code is implemented using the standard MPI functions and tested on two modern parallel computer systems. The performed numerical tests demonstrate good level of parallel efficiency and scalability of the studied direction-splitting-based algorithm.

Fencing network direct memory access data transfers in a parallel active messaging interface of a parallel computer

DOEpatents

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.

Fencing network direct memory access data transfers in a parallel active messaging interface of a parallel computer

DOEpatents

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.

A novel open-framework with non-crossing channels in the uranyl vanadates A(UO 2) 4(VO 4) 3 ( A=Li, Na)

NASA Astrophysics Data System (ADS)

Obbade, S.; Dion, C.; Rivenet, M.; Saadi, M.; Abraham, F.

2004-06-01

A new sodium uranyl vanadate Na(UO 2) 4(VO 4) 3 has been synthesized by solid-state reaction and its structure determined from single-crystal X-ray diffraction data. It crystallizes in the tetragonal symmetry with space group I4 1/ amd and following cell parameters: a=7.2267(4) Å and c=34.079(4) Å, V=1779.8(2) Å 3, Z=4 with ρmes=5.36(3) g/cm 3 and ρcal=5.40(2) g/cm 3. A full-matrix least-squares refinement on the basis of F2 yielded R1=0.028 and w R2=0.056 for 52 parameters with 474 independent reflections with I⩾2 σ( I) collected on a BRUKER AXS diffractometer with Mo Kα radiation and a CCD detector. The crystal structure is characterized by ∞2[(UO 2) 2(VO 4)] sheets parallel to (001) formed by corner-shared UO 6 distorted octahedra and V(2)O 4 tetrahedra, connected by V(1)O 4 tetrahedra to ∞1[UO 5] 4- chains of edge-shared UO 7 pentagonal bipyramids alternately parallel to the a- and b-axis. The resulting three-dimensional framework creates mono-dimensional channels running down the a- and b-axis formed by face-shared oxygen octahedra half occupied by Na. The powder of Li analog compound Li(UO 2) 4(VO 4) 3 has been synthesized by solid-state reaction. The two compounds exhibit high mobility of the alkaline ions within the two-dimensional network of non-intersecting channels.

Information engineering

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

Hunt, D.N.

1997-02-01

The Information Engineering thrust area develops information technology to support the programmatic needs of Lawrence Livermore National Laboratory`s Engineering Directorate. Progress in five programmatic areas are described in separate reports contained herein. These are entitled Three-dimensional Object Creation, Manipulation, and Transport, Zephyr:A Secure Internet-Based Process to Streamline Engineering Procurements, Subcarrier Multiplexing: Optical Network Demonstrations, Parallel Optical Interconnect Technology Demonstration, and Intelligent Automation Architecture.

(2E)-1-(4,4′′-Difluoro-5′-meth­oxy-1,1′:3′,1′′-terphenyl-4′-yl)-3-(2-fluoro­phen­yl)prop-2-en-1-one

PubMed Central

Fun, Hoong-Kun; Loh, Wan-Sin; Samshuddin, S.; Narayana, B.; Sarojini, B. K.

2012-01-01

In the title compound, C28H19F3O2, the central benzene ring forms dihedral angles of 48.69 (6), 60.93 (6) and 42.06 (6)° with the fluoro­benzene rings. In the crystal, inter­molecular C—H⋯O and C—H⋯F hydrogen bonds link the mol­ecules, forming an undulating two-dimensional network parallel to the bc plane. C—H⋯π inter­actions further consolidate the crystal packing. PMID:22807850

Spatial light modulators and applications III; Proceedings of the Meeting, San Diego, CA, Aug. 7, 8, 1989

NASA Astrophysics Data System (ADS)

Efron, Uzi

Recent advances in the technology and applications of spatial light modulators (SLMs) are discussed in review essays by leading experts. Topics addressed include materials for SLMs, SLM devices and device technology, applications to optical data processing, and applications to artificial neural networks. Particular attention is given to nonlinear optical polymers, liquid crystals, magnetooptic SLMs, multiple-quantum-well SLMs, deformable-mirror SLMs, three-dimensional optical memories, applications of photorefractive devices to optical computing, photonic neurocomputers and learning machines, holographic associative memories, SLMs as parallel memories for optoelectronic neural networks, and coherent-optics implementations of neural-network models.

Spatial light modulators and applications III; Proceedings of the Meeting, San Diego, CA, Aug. 7, 8, 1989

NASA Technical Reports Server (NTRS)

Efron, Uzi (Editor)

1990-01-01

Recent advances in the technology and applications of spatial light modulators (SLMs) are discussed in review essays by leading experts. Topics addressed include materials for SLMs, SLM devices and device technology, applications to optical data processing, and applications to artificial neural networks. Particular attention is given to nonlinear optical polymers, liquid crystals, magnetooptic SLMs, multiple-quantum-well SLMs, deformable-mirror SLMs, three-dimensional optical memories, applications of photorefractive devices to optical computing, photonic neurocomputers and learning machines, holographic associative memories, SLMs as parallel memories for optoelectronic neural networks, and coherent-optics implementations of neural-network models.

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

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

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

1989-03-01

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

A Chip-Capillary Hybrid Device for Automated Transfer of Sample Pre-Separated by Capillary Isoelectric Focusing to Parallel Capillary Gel Electrophoresis for Two-Dimensional Protein Separation

PubMed Central

Lu, Joann J.; Wang, Shili; Li, Guanbin; Wang, Wei; Pu, Qiaosheng; Liu, Shaorong

2012-01-01

In this report, we introduce a chip-capillary hybrid device to integrate capillary isoelectric focusing (CIEF) with parallel capillary sodium dodecyl sulfate – polyacrylamide gel electrophoresis (SDS-PAGE) or capillary gel electrophoresis (CGE) toward automating two-dimensional (2D) protein separations. The hybrid device consists of three chips that are butted together. The middle chip can be moved between two positions to re-route the fluidic paths, which enables the performance of CIEF and injection of proteins partially resolved by CIEF to CGE capillaries for parallel CGE separations in a continuous and automated fashion. Capillaries are attached to the other two chips to facilitate CIEF and CGE separations and to extend the effective lengths of CGE columns. Specifically, we illustrate the working principle of the hybrid device, develop protocols for producing and preparing the hybrid device, and demonstrate the feasibility of using this hybrid device for automated injection of CIEF-separated sample to parallel CGE for 2D protein separations. Potentials and problems associated with the hybrid device are also discussed. PMID:22830584

Image matrix processor for fast multi-dimensional computations

DOEpatents

Roberson, G.P.; Skeate, M.F.

1996-10-15

An apparatus for multi-dimensional computation is disclosed which comprises a computation engine, including a plurality of processing modules. The processing modules are configured in parallel and compute respective contributions to a computed multi-dimensional image of respective two dimensional data sets. A high-speed, parallel access storage system is provided which stores the multi-dimensional data sets, and a switching circuit routes the data among the processing modules in the computation engine and the storage system. A data acquisition port receives the two dimensional data sets representing projections through an image, for reconstruction algorithms such as encountered in computerized tomography. The processing modules include a programmable local host, by which they may be configured to execute a plurality of different types of multi-dimensional algorithms. The processing modules thus include an image manipulation processor, which includes a source cache, a target cache, a coefficient table, and control software for executing image transformation routines using data in the source cache and the coefficient table and loading resulting data in the target cache. The local host processor operates to load the source cache with a two dimensional data set, loads the coefficient table, and transfers resulting data out of the target cache to the storage system, or to another destination. 10 figs.

Metal-organic framework assembled from erbium and a tetrapodal polyphosphonic acid organic linker.

PubMed

Mendes, Ricardo F; Firmino, Ana D G; Tomé, João P C; Almeida Paz, Filipe A

2018-06-01

A three-dimensional metal-organic framework (MOF), poly[[μ 6 -5'-pentahydrogen [1,1'-biphenyl]-3,3',5,5'-tetrayltetrakis(phosphonato)]erbium(III)] 2.5-hydrate], formulated as [Er(C 12 H 11 O 12 P 4 )]·2.5H 2 O or [Er(H 5 btp)]·2.5H 2 O (I) and isotypical with a Y 3+ -based MOF reported previously by our research group [Firmino et al. (2017b). Inorg. Chem. 56, 1193-1208], was constructed based solely on Er 3+ and on the polyphosphonic organic linker [1,1'-biphenyl]-3,3',5,5'-tetrakis(phosphonic acid) (H 8 btp). The present work describes our efforts to introduce lanthanide cations into the flexible network, demonstrating that, on the one hand, the compound can be obtained using three distinct experimental methods, i.e. hydro(solvo)thermal (Hy), microwave-assisted (MW) and one-pot (Op), and, on the other hand, that crystallite size can be approximately fine-tuned according to the method employed. MOF I contains hexacoordinated Er 3+ cations which are distributed in a zigzag inorganic chain running parallel to the [100] direction of the unit cell. The chains are, in turn, bridged by the anionic organic linker to form a three-dimensional 6,6-connected binodal network. This connectivity leads to the existence of one-dimensional channels (also running parallel to the [100] direction) filled with disordered and partially occupied water molecules of crystalization which are engaged in O-H...O hydrogen-bonding interactions with the [Er(H 5 btp)] framework. Additional weak π-π interactions [intercentroid distance = 3.957 (7) Å] exist between aromatic rings, which help to maintain the structural integrity of the network.

Optimization of Turbine Blade Design for Reusable Launch Vehicles

NASA Technical Reports Server (NTRS)

Shyy, Wei

1998-01-01

To facilitate design optimization of turbine blade shape for reusable launching vehicles, appropriate techniques need to be developed to process and estimate the characteristics of the design variables and the response of the output with respect to the variations of the design variables. The purpose of this report is to offer insight into developing appropriate techniques for supporting such design and optimization needs. Neural network and polynomial-based techniques are applied to process aerodynamic data obtained from computational simulations for flows around a two-dimensional airfoil and a generic three- dimensional wing/blade. For the two-dimensional airfoil, a two-layered radial-basis network is designed and trained. The performances of two different design functions for radial-basis networks, one based on the accuracy requirement, whereas the other one based on the limit on the network size. While the number of neurons needed to satisfactorily reproduce the information depends on the size of the data, the neural network technique is shown to be more accurate for large data set (up to 765 simulations have been used) than the polynomial-based response surface method. For the three-dimensional wing/blade case, smaller aerodynamic data sets (between 9 to 25 simulations) are considered, and both the neural network and the polynomial-based response surface techniques improve their performance as the data size increases. It is found while the relative performance of two different network types, a radial-basis network and a back-propagation network, depends on the number of input data, the number of iterations required for radial-basis network is less than that for the back-propagation network.

A solution for two-dimensional mazes with use of chaotic dynamics in a recurrent neural network model.

PubMed

Suemitsu, Yoshikazu; Nara, Shigetoshi

2004-09-01

Chaotic dynamics introduced into a neural network model is applied to solving two-dimensional mazes, which are ill-posed problems. A moving object moves from the position at t to t + 1 by simply defined motion function calculated from firing patterns of the neural network model at each time step t. We have embedded several prototype attractors that correspond to the simple motion of the object orienting toward several directions in two-dimensional space in our neural network model. Introducing chaotic dynamics into the network gives outputs sampled from intermediate state points between embedded attractors in a state space, and these dynamics enable the object to move in various directions. System parameter switching between a chaotic and an attractor regime in the state space of the neural network enables the object to move to a set target in a two-dimensional maze. Results of computer simulations show that the success rate for this method over 300 trials is higher than that of random walk. To investigate why the proposed method gives better performance, we calculate and discuss statistical data with respect to dynamical structure.

Neural networks for dimensionality reduction of fluorescence spectra and prediction of drinking water disinfection by-products.

PubMed

Peleato, Nicolas M; Legge, Raymond L; Andrews, Robert C

2018-06-01

The use of fluorescence data coupled with neural networks for improved predictability of drinking water disinfection by-products (DBPs) was investigated. Novel application of autoencoders to process high-dimensional fluorescence data was related to common dimensionality reduction techniques of parallel factors analysis (PARAFAC) and principal component analysis (PCA). The proposed method was assessed based on component interpretability as well as for prediction of organic matter reactivity to formation of DBPs. Optimal prediction accuracies on a validation dataset were observed with an autoencoder-neural network approach or by utilizing the full spectrum without pre-processing. Latent representation by an autoencoder appeared to mitigate overfitting when compared to other methods. Although DBP prediction error was minimized by other pre-processing techniques, PARAFAC yielded interpretable components which resemble fluorescence expected from individual organic fluorophores. Through analysis of the network weights, fluorescence regions associated with DBP formation can be identified, representing a potential method to distinguish reactivity between fluorophore groupings. However, distinct results due to the applied dimensionality reduction approaches were observed, dictating a need for considering the role of data pre-processing in the interpretability of the results. In comparison to common organic measures currently used for DBP formation prediction, fluorescence was shown to improve prediction accuracies, with improvements to DBP prediction best realized when appropriate pre-processing and regression techniques were applied. The results of this study show promise for the potential application of neural networks to best utilize fluorescence EEM data for prediction of organic matter reactivity. Copyright © 2018 Elsevier Ltd. All rights reserved.

Fault detection for hydraulic pump based on chaotic parallel RBF network

NASA Astrophysics Data System (ADS)

Lu, Chen; Ma, Ning; Wang, Zhipeng

2011-12-01

In this article, a parallel radial basis function network in conjunction with chaos theory (CPRBF network) is presented, and applied to practical fault detection for hydraulic pump, which is a critical component in aircraft. The CPRBF network consists of a number of radial basis function (RBF) subnets connected in parallel. The number of input nodes for each RBF subnet is determined by different embedding dimension based on chaotic phase-space reconstruction. The output of CPRBF is a weighted sum of all RBF subnets. It was first trained using the dataset from normal state without fault, and then a residual error generator was designed to detect failures based on the trained CPRBF network. Then, failure detection can be achieved by the analysis of the residual error. Finally, two case studies are introduced to compare the proposed CPRBF network with traditional RBF networks, in terms of prediction and detection accuracy.

A two-dimensional Zn coordination polymer with a three-dimensional supra-molecular architecture.

PubMed

Liu, Fuhong; Ding, Yan; Li, Qiuyu; Zhang, Liping

2017-10-01

The title compound, poly[bis-{μ 2 -4,4'-bis-[(1,2,4-triazol-1-yl)meth-yl]biphenyl-κ 2 N 4 : N 4' }bis-(nitrato-κ O )zinc(II)], [Zn(NO 3 ) 2 (C 18 H 16 N 6 ) 2 ] n , is a two-dimensional zinc coordination polymer constructed from 4,4'-bis-[(1 H -1,2,4-triazol-1-yl)meth-yl]-1,1'-biphenyl units. It was synthesized and characterized by elemental analysis and single-crystal X-ray diffraction. The Zn II cation is located on an inversion centre and is coordinated by two O atoms from two symmetry-related nitrate groups and four N atoms from four symmetry-related 4,4'-bis-[(1 H -1,2,4-triazol-1-yl)meth-yl]-1,1'-biphenyl ligands, forming a distorted octa-hedral {ZnN 4 O 2 } coordination geometry. The linear 4,4'-bis-[(1 H -1,2,4-triazol-1-yl)meth-yl]-1,1'-biphenyl ligand links two Zn II cations, generating two-dimensional layers parallel to the crystallographic (132) plane. The parallel layers are connected by C-H⋯O, C-H⋯N, C-H⋯π and π-π stacking inter-actions, resulting in a three-dimensional supra-molecular architecture.

Synchrotron radiation CT from the micro to nanoscale for the investigation of bone tissue

NASA Astrophysics Data System (ADS)

Peyrin, Francoise; Dong, Pei; Pacureanu, Alexandra; Zuluaga, Maria; Olivier, Cécile; Langer, Max; Cloetens, Peter

2012-10-01

During the last decade, X-ray micro Computerized Tomography (CT) has become a conventional technique for the three-dimensional (3D) investigation of trabecular bone micro-architecture. Coupling micro-CT to synchrotron sources possesses significant advantages in terms of image quality and gives access to information on bone mineralization which is an important factor of bone quality. We present an overview of the investigation of bone using Synchrotron Radiation (SR) CT from the micro to the nano scale. We introduce two synchrotron CT systems developed at the ESRF based on SR parallel-beam micro-CT and magnified phase CT respectively, achieving down to submicrometric and nanometric spatial resolution. In the latter, by using phase retrieval prior to tomographic reconstruction, the system provides maps of the 3D refractive index distribution. Parallel-beam SR micro-CT has extensively been used for the analysis of trabecular or cortical bone in human or small animals with spatial resolution in the range [3-10] μm. However, the characterization of the bone properties at the cellular scale is also of major interest. At the micrometric scale, the shape, density and morphology of osteocyte lacunae can be studied on statistically representative volumes. At the nanometric scale, unprecedented 3D displays of the canaliculi network have been obtained on fields of views including a large number of interconnected osteocyte lacunae. Finally SR magnified phase CT provides a detailed analysis of the lacuno-canalicular network and in addition information on the organization of the collagen fibers. These findings open new perspectives for three-dimensional quantitative assessment of bone tissue at the cellular scale.

Function approximation using combined unsupervised and supervised learning.

PubMed

Andras, Peter

2014-03-01

Function approximation is one of the core tasks that are solved using neural networks in the context of many engineering problems. However, good approximation results need good sampling of the data space, which usually requires exponentially increasing volume of data as the dimensionality of the data increases. At the same time, often the high-dimensional data is arranged around a much lower dimensional manifold. Here we propose the breaking of the function approximation task for high-dimensional data into two steps: (1) the mapping of the high-dimensional data onto a lower dimensional space corresponding to the manifold on which the data resides and (2) the approximation of the function using the mapped lower dimensional data. We use over-complete self-organizing maps (SOMs) for the mapping through unsupervised learning, and single hidden layer neural networks for the function approximation through supervised learning. We also extend the two-step procedure by considering support vector machines and Bayesian SOMs for the determination of the best parameters for the nonlinear neurons in the hidden layer of the neural networks used for the function approximation. We compare the approximation performance of the proposed neural networks using a set of functions and show that indeed the neural networks using combined unsupervised and supervised learning outperform in most cases the neural networks that learn the function approximation using the original high-dimensional data.

Kubo conductivity of a strongly magnetized two-dimensional plasma.

NASA Technical Reports Server (NTRS)

Montgomery, D.; Tappert, F.

1971-01-01

The Kubo formula is used to evaluate the bulk electrical conductivity of a two-dimensional guiding-center plasma in a strong dc magnetic field. The particles interact only electrostatically. An ?anomalous' electrical conductivity is derived for this system, which parallels a recent result of Taylor and McNamara for the coefficient of spatial diffusion.

Two-dimensional optoelectronic interconnect-processor and its operational bit error rate

NASA Astrophysics Data System (ADS)

Liu, J. Jiang; Gollsneider, Brian; Chang, Wayne H.; Carhart, Gary W.; Vorontsov, Mikhail A.; Simonis, George J.; Shoop, Barry L.

2004-10-01

Two-dimensional (2-D) multi-channel 8x8 optical interconnect and processor system were designed and developed using complementary metal-oxide-semiconductor (CMOS) driven 850-nm vertical-cavity surface-emitting laser (VCSEL) arrays and the photodetector (PD) arrays with corresponding wavelengths. We performed operation and bit-error-rate (BER) analysis on this free-space integrated 8x8 VCSEL optical interconnects driven by silicon-on-sapphire (SOS) circuits. Pseudo-random bit stream (PRBS) data sequence was used in operation of the interconnects. Eye diagrams were measured from individual channels and analyzed using a digital oscilloscope at data rates from 155 Mb/s to 1.5 Gb/s. Using a statistical model of Gaussian distribution for the random noise in the transmission, we developed a method to compute the BER instantaneously with the digital eye-diagrams. Direct measurements on this interconnects were also taken on a standard BER tester for verification. We found that the results of two methods were in the same order and within 50% accuracy. The integrated interconnects were investigated in an optoelectronic processing architecture of digital halftoning image processor. Error diffusion networks implemented by the inherently parallel nature of photonics promise to provide high quality digital halftoned images.

Influence of a parallel magnetic field on the microwave photoconductivity in a high-mobility two-dimensional electron system

NASA Astrophysics Data System (ADS)

Yang, C. L.; Du, R. R.; Pfeiffer, L. N.; West, K. W.

2006-07-01

Using a two-axis magnet, we have studied experimentally the influence of a parallel magnetic field (B//) on microwave-induced resistance oscillations (MIROs) and zero-resistance states (ZRS) previously discovered in a high-mobility two-dimensional electron system. We have observed a strong suppression of MIRO/ZRS by a modest B//˜1T . In Hall bar samples, magnetoplasmon resonance (MPR) has also been observed concurrently with the MIRO/ZRS. In contrast to the suppression of MIRO/ZRS, the MPR peak is apparently enhanced by B// . These findings cannot be explained by a simple modification of single-particle energy spectrum and/or scattering parameters by B// .

Fast parallel approach for 2-D DHT-based real-valued discrete Gabor transform.

PubMed

Tao, Liang; Kwan, Hon Keung

2009-12-01

Two-dimensional fast Gabor transform algorithms are useful for real-time applications due to the high computational complexity of the traditional 2-D complex-valued discrete Gabor transform (CDGT). This paper presents two block time-recursive algorithms for 2-D DHT-based real-valued discrete Gabor transform (RDGT) and its inverse transform and develops a fast parallel approach for the implementation of the two algorithms. The computational complexity of the proposed parallel approach is analyzed and compared with that of the existing 2-D CDGT algorithms. The results indicate that the proposed parallel approach is attractive for real time image processing.

Crystal structure of the cis and trans polymorphs of bis-[μ-2-(1,3-benzo-thia-zol-2-yl)phenolato]-κ3N,O:O;κ3O:N,O-bis-[fac-tri-carbonyl-rhenium(I)].

PubMed

Priyatharsini, Maruthupandiyan; Shankar, Bhaskaran; Sathiyendiran, Malaichamy; Srinivasan, Navaneethakrishnan; Krishnakumar, Rajaputi Venkatraman

2017-02-01

The title dinuclear complex, [Re 2 (C 13 H 8 NOS) 2 (CO) 6 ], crystallizes in two polymorphs where the 2-(1,3-benzo-thia-zol-2-yl)phenolate ligands and two carbonyl groups are trans - ( I ) or cis -arranged ( II ) with respect to the [Re 2 O 2 (CO) 4 ] core. Polymorphs I and II exhibit a crystallographically imposed centre of symmetry and a twofold rotation axis, respectively. The structures may be described as being formed by two octa-hedrally distorted metal-coordinating units fused through μ-oxido bridges, leading to edge-sharing dimers. The crystal packing is governed by C-H⋯O hydrogen-bonding inter-actions, forming chains parallel to the c axis in I and a three-dimensional network in II .

Parallel Implementation of a High Order Implicit Collocation Method for the Heat Equation

NASA Technical Reports Server (NTRS)

Kouatchou, Jules; Halem, Milton (Technical Monitor)

2000-01-01

We combine a high order compact finite difference approximation and collocation techniques to numerically solve the two dimensional heat equation. The resulting method is implicit arid can be parallelized with a strategy that allows parallelization across both time and space. We compare the parallel implementation of the new method with a classical implicit method, namely the Crank-Nicolson method, where the parallelization is done across space only. Numerical experiments are carried out on the SGI Origin 2000.

Improving the scalability of hyperspectral imaging applications on heterogeneous platforms using adaptive run-time data compression

NASA Astrophysics Data System (ADS)

Plaza, Antonio; Plaza, Javier; Paz, Abel

2010-10-01

Latest generation remote sensing instruments (called hyperspectral imagers) are now able to generate hundreds of images, corresponding to different wavelength channels, for the same area on the surface of the Earth. In previous work, we have reported that the scalability of parallel processing algorithms dealing with these high-dimensional data volumes is affected by the amount of data to be exchanged through the communication network of the system. However, large messages are common in hyperspectral imaging applications since processing algorithms are pixel-based, and each pixel vector to be exchanged through the communication network is made up of hundreds of spectral values. Thus, decreasing the amount of data to be exchanged could improve the scalability and parallel performance. In this paper, we propose a new framework based on intelligent utilization of wavelet-based data compression techniques for improving the scalability of a standard hyperspectral image processing chain on heterogeneous networks of workstations. This type of parallel platform is quickly becoming a standard in hyperspectral image processing due to the distributed nature of collected hyperspectral data as well as its flexibility and low cost. Our experimental results indicate that adaptive lossy compression can lead to improvements in the scalability of the hyperspectral processing chain without sacrificing analysis accuracy, even at sub-pixel precision levels.

Muscle networks: Connectivity analysis of EMG activity during postural control

NASA Astrophysics Data System (ADS)

Boonstra, Tjeerd W.; Danna-Dos-Santos, Alessander; Xie, Hong-Bo; Roerdink, Melvyn; Stins, John F.; Breakspear, Michael

2015-12-01

Understanding the mechanisms that reduce the many degrees of freedom in the musculoskeletal system remains an outstanding challenge. Muscle synergies reduce the dimensionality and hence simplify the control problem. How this is achieved is not yet known. Here we use network theory to assess the coordination between multiple muscles and to elucidate the neural implementation of muscle synergies. We performed connectivity analysis of surface EMG from ten leg muscles to extract the muscle networks while human participants were standing upright in four different conditions. We observed widespread connectivity between muscles at multiple distinct frequency bands. The network topology differed significantly between frequencies and between conditions. These findings demonstrate how muscle networks can be used to investigate the neural circuitry of motor coordination. The presence of disparate muscle networks across frequencies suggests that the neuromuscular system is organized into a multiplex network allowing for parallel and hierarchical control structures.

Flow of a Gas Turbine Engine Low-Pressure Subsystem Simulated

NASA Technical Reports Server (NTRS)

Veres, Joseph P.

1997-01-01

The NASA Lewis Research Center is managing a task to numerically simulate overnight, on a parallel computing testbed, the aerodynamic flow in the complete low-pressure subsystem (LPS) of a gas turbine engine. The model solves the three-dimensional Navier- Stokes flow equations through all the components within the LPS, as well as the external flow around the engine nacelle. The LPS modeling task is being performed by Allison Engine Company under the Small Engine Technology contract. The large computer simulation was evaluated on networked computer systems using 8, 16, and 32 processors, with the parallel computing efficiency reaching 75 percent when 16 processors were used.

Formation of Gd coordination polymer with 1D chains mediated by Bronsted acidic ionic liquids

NASA Astrophysics Data System (ADS)

Luo, Qianqian; Han, Ying; Lin, Hechun; Zhang, Yuanyuan; Duan, Chungang; Peng, Hui

2017-03-01

One dimensional coordination polymer Gd[(SO4)(NO3)(C2H6SO)2] (1) is prepared through the mediation of Bronsted acid ionic liquid, which crystallized in the monoclinic space of C2/c. In this polymer, adjacent Gd atoms are linked by two SO42- ions to generate a 1-D chain, and all oxygen atoms in SO42- groups are connected to three nearest Gd atoms in μ3:η1:η1:η2 fashion. Gd, S and N from SO42- and NO3- are precisely coplanar. The planar is coordinated by a pair of DMSO molecules, which is parallel and linked by hydrogen bonding to form a three-dimensional supramolecular network. Magnetic susceptibility measurement of 1 reveals weak antiferromagnetic interactions between the Gd (III) ions. It exhibits relatively large magneto-caloric effect with -ΔSm=28.8 J Kg-1 K-1 for ΔH=7 T.

Performing a local reduction operation on a parallel computer

DOEpatents

Blocksome, Michael A; Faraj, Daniel A

2013-06-04

A parallel computer including compute nodes, each including two reduction processing cores, a network write processing core, and a network read processing core, each processing core assigned an input buffer. Copying, in interleaved chunks by the reduction processing cores, contents of the reduction processing cores' input buffers to an interleaved buffer in shared memory; copying, by one of the reduction processing cores, contents of the network write processing core's input buffer to shared memory; copying, by another of the reduction processing cores, contents of the network read processing core's input buffer to shared memory; and locally reducing in parallel by the reduction processing cores: the contents of the reduction processing core's input buffer; every other interleaved chunk of the interleaved buffer; the copied contents of the network write processing core's input buffer; and the copied contents of the network read processing core's input buffer.

Performing a local reduction operation on a parallel computer

DOEpatents

Blocksome, Michael A.; Faraj, Daniel A.

2012-12-11

A parallel computer including compute nodes, each including two reduction processing cores, a network write processing core, and a network read processing core, each processing core assigned an input buffer. Copying, in interleaved chunks by the reduction processing cores, contents of the reduction processing cores' input buffers to an interleaved buffer in shared memory; copying, by one of the reduction processing cores, contents of the network write processing core's input buffer to shared memory; copying, by another of the reduction processing cores, contents of the network read processing core's input buffer to shared memory; and locally reducing in parallel by the reduction processing cores: the contents of the reduction processing core's input buffer; every other interleaved chunk of the interleaved buffer; the copied contents of the network write processing core's input buffer; and the copied contents of the network read processing core's input buffer.

Multistability in bidirectional associative memory neural networks

NASA Astrophysics Data System (ADS)

Huang, Gan; Cao, Jinde

2008-04-01

In this Letter, the multistability issue is studied for Bidirectional Associative Memory (BAM) neural networks. Based on the existence and stability analysis of the neural networks with or without delay, it is found that the 2 n-dimensional networks can have 3 equilibria and 2 equilibria of them are locally exponentially stable, where each layer of the BAM network has n neurons. Furthermore, the results has been extended to (n+m)-dimensional BAM neural networks, where there are n and m neurons on the two layers respectively. Finally, two numerical examples are presented to illustrate the validity of our results.

Sequential Feedback Scheme Outperforms the Parallel Scheme for Hamiltonian Parameter Estimation.

PubMed

Yuan, Haidong

2016-10-14

Measurement and estimation of parameters are essential for science and engineering, where the main quest is to find the highest achievable precision with the given resources and design schemes to attain it. Two schemes, the sequential feedback scheme and the parallel scheme, are usually studied in the quantum parameter estimation. While the sequential feedback scheme represents the most general scheme, it remains unknown whether it can outperform the parallel scheme for any quantum estimation tasks. In this Letter, we show that the sequential feedback scheme has a threefold improvement over the parallel scheme for Hamiltonian parameter estimations on two-dimensional systems, and an order of O(d+1) improvement for Hamiltonian parameter estimation on d-dimensional systems. We also show that, contrary to the conventional belief, it is possible to simultaneously achieve the highest precision for estimating all three components of a magnetic field, which sets a benchmark on the local precision limit for the estimation of a magnetic field.

Toward two-dimensional search engines

NASA Astrophysics Data System (ADS)

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.

Metal-superconductor transition in low-dimensional superconducting clusters embedded in two-dimensional electron systems

NASA Astrophysics Data System (ADS)

Bucheli, D.; Caprara, S.; Castellani, C.; Grilli, M.

2013-02-01

Motivated by recent experimental data on thin film superconductors and oxide interfaces, we propose a random-resistor network apt to describe the occurrence of a metal-superconductor transition in a two-dimensional electron system with disorder on the mesoscopic scale. We consider low-dimensional (e.g. filamentary) structures of a superconducting cluster embedded in the two-dimensional network and we explore the separate effects and the interplay of the superconducting structure and of the statistical distribution of local critical temperatures. The thermal evolution of the resistivity is determined by a numerical calculation of the random-resistor network and, for comparison, a mean-field approach called effective medium theory (EMT). Our calculations reveal the relevance of the distribution of critical temperatures for clusters with low connectivity. In addition, we show that the presence of spatial correlations requires a modification of standard EMT to give qualitative agreement with the numerical results. Applying the present approach to an LaTiO3/SrTiO3 oxide interface, we find that the measured resistivity curves are compatible with a network of spatially dense but loosely connected superconducting islands.

Crystal structure of 2-amino-pyridinium 6-chloro-nicotinate.

PubMed

Jasmine, N Jeeva; Rajam, A; Muthiah, P Thomas; Stanley, N; Razak, I Abdul; Rosli, M Mustaqim

2015-09-01

In the title salt, C5H7N(+)·C6H3ClNO(-), the 2-amino-pyri-din-ium cation inter-acts with the carboxyl-ate group of the 6-chloro-nicotinate anion through a pair of independent N-H⋯O hydrogen bonds, forming an R 2 (2)(8) ring motif. In the crystal, these dimeric units are connected further via N-H⋯O hydrogen bonds, forming chains along [001]. In addition, weak C-H⋯N and C-H⋯O hydrogen bonds, together with weak π-π inter-actions, with centroid-centroid distances of 3.6560 (5) and 3.6295 (5) Å, connect the chains, forming a two-dimensional network parallel to (100).

Di-μ-chlorido-bis­[(2-amino­benzamide-κ2 N 2,O)chlorido­copper(II)

PubMed Central

Damous, Maamar; Dénès, George; Bouacida, Sofiane; Hamlaoui, Meriem; Merazig, Hocine; Daran, Jean-Claude

2013-01-01

The title compound, [Cu2Cl4(C7H8N2O)2], crystallizes as discrete [CuLCl2]2 (L = 2-amino­benzamide) dimers with inversion symmetry. Each CuII ion is five-coordinated and is bound to two bridging chloride ligands, a terminal chloride ligand and a bidentate 2-amino­benzamide ligand. The crystal structure exhibits alternating layers parallel to (010) along the b-axis direction. In the crystal, the components are linked via N—H⋯Cl hydrogen bonds, forming a three-dimensional network. These inter­actions link the mol­ecules within the layers and also link the layers together and reinforce the cohesion of the structure. PMID:24426988

Neural-Network Object-Recognition Program

NASA Technical Reports Server (NTRS)

Spirkovska, L.; Reid, M. B.

1993-01-01

HONTIOR computer program implements third-order neural network exhibiting invariance under translation, change of scale, and in-plane rotation. Invariance incorporated directly into architecture of network. Only one view of each object needed to train network for two-dimensional-translation-invariant recognition of object. Also used for three-dimensional-transformation-invariant recognition by training network on only set of out-of-plane rotated views. Written in C language.

Music Signal Processing Using Vector Product Neural Networks

NASA Astrophysics Data System (ADS)

Fan, Z. C.; Chan, T. S.; Yang, Y. H.; Jang, J. S. R.

2017-05-01

We propose a novel neural network model for music signal processing using vector product neurons and dimensionality transformations. Here, the inputs are first mapped from real values into three-dimensional vectors then fed into a three-dimensional vector product neural network where the inputs, outputs, and weights are all three-dimensional values. Next, the final outputs are mapped back to the reals. Two methods for dimensionality transformation are proposed, one via context windows and the other via spectral coloring. Experimental results on the iKala dataset for blind singing voice separation confirm the efficacy of our model.

Ballistic Deficits for Ionization Chamber Pulses in Pulse Shaping Amplifiers

NASA Astrophysics Data System (ADS)

Kumar, G. Anil; Sharma, S. L.; Choudhury, R. K.

2007-04-01

In order to understand the dependence of the ballistic deficit on the shape of rising portion of the voltage pulse at the input of a pulse shaping amplifier, we have estimated the ballistic deficits for the pulses from a two-electrode parallel plate ionization chamber as well as for the pulses from a gridded parallel plate ionization chamber. These estimations have been made using numerical integration method when the pulses are processed through the CR-RCn (n=1-6) shaping network as well as when the pulses are processed through the complex shaping network of the ORTEC Model 472 spectroscopic amplifier. Further, we have made simulations to see the effect of ballistic deficit on the pulse-height spectra under different conditions. We have also carried out measurements of the ballistic deficits for the pulses from a two-electrode parallel plate ionization chamber as well as for the pulses from a gridded parallel plate ionization chamber when these pulses are processed through the ORTEC 572 linear amplifier having a simple CR-RC shaping network. The reasonable matching of the simulated ballistic deficits with the experimental ballistic deficits for the CR-RC shaping network clearly establishes the validity of the simulation technique

Characterizing information propagation through inter-vehicle communication on a simple network of two parallel roads

DOT National Transportation Integrated Search

2010-10-01

In this report, we study information propagation via inter-vehicle communication along two parallel : roads. By identifying an inherent Bernoulli process, we are able to derive the mean and variance of : propagation distance. A road separation distan...

Ullmann-type coupling of brominated tetrathienoanthracene on copper and silver

NASA Astrophysics Data System (ADS)

Gutzler, Rico; Cardenas, Luis; Lipton-Duffin, Josh; El Garah, Mohamed; Dinca, Laurentiu E.; Szakacs, Csaba E.; Fu, Chaoying; Gallagher, Mark; Vondráček, Martin; Rybachuk, Maksym; Perepichka, Dmitrii F.; Rosei, Federico

2014-02-01

We report the synthesis of extended two-dimensional organic networks on Cu(111), Ag(111), Cu(110), and Ag(110) from thiophene-based molecules. A combination of scanning tunnelling microscopy and X-ray photoemission spectroscopy yields insight into the reaction pathways from single molecules towards the formation of two-dimensional organometallic and polymeric structures via Ullmann reaction dehalogenation and C-C coupling. The thermal stability of the molecular networks is probed by annealing at elevated temperatures of up to 500 °C. On Cu(111) only organometallic structures are formed, while on Ag(111) both organometallic and covalent polymeric networks were found to coexist. The ratio between organometallic and covalent bonds could be controlled by means of the annealing temperature. The thiophene moieties start degrading at 200 °C on the copper surface, whereas on silver the degradation process becomes significant only at 400 °C. Our work reveals how the interplay of a specific surface type and temperature steers the formation of organometallic and polymeric networks and describes how these factors influence the structural integrity of two-dimensional organic networks.We report the synthesis of extended two-dimensional organic networks on Cu(111), Ag(111), Cu(110), and Ag(110) from thiophene-based molecules. A combination of scanning tunnelling microscopy and X-ray photoemission spectroscopy yields insight into the reaction pathways from single molecules towards the formation of two-dimensional organometallic and polymeric structures via Ullmann reaction dehalogenation and C-C coupling. The thermal stability of the molecular networks is probed by annealing at elevated temperatures of up to 500 °C. On Cu(111) only organometallic structures are formed, while on Ag(111) both organometallic and covalent polymeric networks were found to coexist. The ratio between organometallic and covalent bonds could be controlled by means of the annealing temperature. The thiophene moieties start degrading at 200 °C on the copper surface, whereas on silver the degradation process becomes significant only at 400 °C. Our work reveals how the interplay of a specific surface type and temperature steers the formation of organometallic and polymeric networks and describes how these factors influence the structural integrity of two-dimensional organic networks. Electronic supplementary information (ESI) available: Additional STM data and DFT results. See DOI: 10.1039/c3nr05710k

The openGL visualization of the 2D parallel FDTD algorithm

NASA Astrophysics Data System (ADS)

Walendziuk, Wojciech

2005-02-01

This paper presents a way of visualization of a two-dimensional version of a parallel algorithm of the FDTD method. The visualization module was created on the basis of the OpenGL graphic standard with the use of the GLUT interface. In addition, the work includes the results of the efficiency of the parallel algorithm in the form of speedup charts.

NASA high performance computing, communications, image processing, and data visualization-potential applications to medicine.

PubMed

Kukkonen, C A

1995-06-01

High-speed information processing technologies being developed and applied by the Jet Propulsion Laboratory for NASA and Department of Defense mission needs have potential dual-uses in telemedicine and other medical applications. Fiber optic ground networks connected with microwave satellite links allow NASA to communicate with its astronauts in Earth orbit or on the moon, and with its deep space probes billions of miles away. These networks monitor the health of astronauts and or robotic spacecraft. Similar communications technology will also allow patients to communicate with doctors anywhere on Earth. NASA space missions have science as a major objective. Science sensors have become so sophisticated that they can take more data than our scientists can analyze by hand. High performance computers--workstations, supercomputer and massively parallel computers are being used to transform this data into knowledge. This is done using image processing, data visualization and other techniques to present the data--one's and zero's in forms that a human analyst can readily relate to and understand. Medical sensors have also explored in the in data output--witness CT scans, MRI, and ultrasound. This data must be presented in visual form and computers will allow routine combination of many two dimensional MRI images into three dimensional reconstructions of organs that then can be fully examined by physicians. Emerging technologies such as neural networks that are being "trained" to detect craters on planets or incoming missiles amongst decoys can be used to identify microcalcification in mammograms.

Probing energy transfer events in the light harvesting complex 2 (LH2) of Rhodobacter sphaeroides with two-dimensional spectroscopy.

PubMed

Fidler, Andrew F; Singh, Ved P; Long, Phillip D; Dahlberg, Peter D; Engel, Gregory S

2013-10-21

Excitation energy transfer events in the photosynthetic light harvesting complex 2 (LH2) of Rhodobacter sphaeroides are investigated with polarization controlled two-dimensional electronic spectroscopy. A spectrally broadened pulse allows simultaneous measurement of the energy transfer within and between the two absorption bands at 800 nm and 850 nm. The phased all-parallel polarization two-dimensional spectra resolve the initial events of energy transfer by separating the intra-band and inter-band relaxation processes across the two-dimensional map. The internal dynamics of the 800 nm region of the spectra are resolved as a cross peak that grows in on an ultrafast time scale, reflecting energy transfer between higher lying excitations of the B850 chromophores into the B800 states. We utilize a polarization sequence designed to highlight the initial excited state dynamics which uncovers an ultrafast transfer component between the two bands that was not observed in the all-parallel polarization data. We attribute the ultrafast transfer component to energy transfer from higher energy exciton states to lower energy states of the strongly coupled B850 chromophores. Connecting the spectroscopic signature to the molecular structure, we reveal multiple relaxation pathways including a cyclic transfer of energy between the two rings of the complex.

Three-Dimensional Arrangement of Human Bone Marrow Microvessels Revealed by Immunohistology in Undecalcified Sections

PubMed Central

Wilhelmi, Verena; Seiler, Anja; Lampp, Katrin; Neff, Andreas; Guthe, Michael; Lobachev, Oleg

2016-01-01

The arrangement of microvessels in human bone marrow is so far unknown. We combined monoclonal antibodies against CD34 and against CD141 to visualise all microvessel endothelia in 21 serial sections of about 1 cm2 size derived from a human iliac crest. The specimen was not decalcified and embedded in Technovit® 9100. In different regions of interest, the microvasculature was reconstructed in three dimensions using automatic methods. The three-dimensional models were subject to a rigid semiautomatic and manual quality control. In iliac crest bone marrow, the adipose tissue harbours irregularly distributed haematopoietic areas. These are fed by networks of large sinuses, which are loosely connected to networks of small capillaries prevailing in areas of pure adipose tissue. Our findings are compatible with the hypothesis that capillaries and sinuses in human iliac crest bone marrow are partially arranged in parallel. PMID:27997569

Resistance and Security Index of Networks: Structural Information Perspective of Network Security

NASA Astrophysics Data System (ADS)

Li, Angsheng; Hu, Qifu; Liu, Jun; Pan, Yicheng

2016-06-01

Recently, Li and Pan defined the metric of the K-dimensional structure entropy of a structured noisy dataset G to be the information that controls the formation of the K-dimensional structure of G that is evolved by the rules, order and laws of G, excluding the random variations that occur in G. Here, we propose the notion of resistance of networks based on the one- and two-dimensional structural information of graphs. Given a graph G, we define the resistance of G, written , as the greatest overall number of bits required to determine the code of the module that is accessible via random walks with stationary distribution in G, from which the random walks cannot escape. We show that the resistance of networks follows the resistance law of networks, that is, for a network G, the resistance of G is , where and are the one- and two-dimensional structure entropies of G, respectively. Based on the resistance law, we define the security index of a network G to be the normalised resistance of G, that is, . We show that the resistance and security index are both well-defined measures for the security of the networks.

Resistance and Security Index of Networks: Structural Information Perspective of Network Security.

PubMed

Li, Angsheng; Hu, Qifu; Liu, Jun; Pan, Yicheng

2016-06-03

Recently, Li and Pan defined the metric of the K-dimensional structure entropy of a structured noisy dataset G to be the information that controls the formation of the K-dimensional structure of G that is evolved by the rules, order and laws of G, excluding the random variations that occur in G. Here, we propose the notion of resistance of networks based on the one- and two-dimensional structural information of graphs. Given a graph G, we define the resistance of G, written , as the greatest overall number of bits required to determine the code of the module that is accessible via random walks with stationary distribution in G, from which the random walks cannot escape. We show that the resistance of networks follows the resistance law of networks, that is, for a network G, the resistance of G is , where and are the one- and two-dimensional structure entropies of G, respectively. Based on the resistance law, we define the security index of a network G to be the normalised resistance of G, that is, . We show that the resistance and security index are both well-defined measures for the security of the networks.

Resistance and Security Index of Networks: Structural Information Perspective of Network Security

PubMed Central

Li, Angsheng; Hu, Qifu; Liu, Jun; Pan, Yicheng

2016-01-01

Recently, Li and Pan defined the metric of the K-dimensional structure entropy of a structured noisy dataset G to be the information that controls the formation of the K-dimensional structure of G that is evolved by the rules, order and laws of G, excluding the random variations that occur in G. Here, we propose the notion of resistance of networks based on the one- and two-dimensional structural information of graphs. Given a graph G, we define the resistance of G, written , as the greatest overall number of bits required to determine the code of the module that is accessible via random walks with stationary distribution in G, from which the random walks cannot escape. We show that the resistance of networks follows the resistance law of networks, that is, for a network G, the resistance of G is , where and are the one- and two-dimensional structure entropies of G, respectively. Based on the resistance law, we define the security index of a network G to be the normalised resistance of G, that is, . We show that the resistance and security index are both well-defined measures for the security of the networks. PMID:27255783

Hierarchical Artificial Bee Colony Algorithm for RFID Network Planning Optimization

PubMed Central

Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong

2014-01-01

This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness. PMID:24592200

Hierarchical artificial bee colony algorithm for RFID network planning optimization.

PubMed

Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong

2014-01-01

This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness.

On the dimensionally correct kinetic theory of turbulence for parallel propagation

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

Gaelzer, R., E-mail: rudi.gaelzer@ufrgs.br, E-mail: yoonp@umd.edu, E-mail: 007gasun@khu.ac.kr, E-mail: luiz.ziebell@ufrgs.br; Ziebell, L. F., E-mail: rudi.gaelzer@ufrgs.br, E-mail: yoonp@umd.edu, E-mail: 007gasun@khu.ac.kr, E-mail: luiz.ziebell@ufrgs.br; Yoon, P. H., E-mail: rudi.gaelzer@ufrgs.br, E-mail: yoonp@umd.edu, E-mail: 007gasun@khu.ac.kr, E-mail: luiz.ziebell@ufrgs.br

2015-03-15

Yoon and Fang [Phys. Plasmas 15, 122312 (2008)] formulated a second-order nonlinear kinetic theory that describes the turbulence propagating in directions parallel/anti-parallel to the ambient magnetic field. Their theory also includes discrete-particle effects, or the effects due to spontaneously emitted thermal fluctuations. However, terms associated with the spontaneous fluctuations in particle and wave kinetic equations in their theory contain proper dimensionality only for an artificial one-dimensional situation. The present paper extends the analysis and re-derives the dimensionally correct kinetic equations for three-dimensional case. The new formalism properly describes the effects of spontaneous fluctuations emitted in three-dimensional space, while the collectivelymore » emitted turbulence propagates predominantly in directions parallel/anti-parallel to the ambient magnetic field. As a first step, the present investigation focuses on linear wave-particle interaction terms only. A subsequent paper will include the dimensionally correct nonlinear wave-particle interaction terms.« less

Chimera patterns in two-dimensional networks of coupled neurons.

PubMed

Schmidt, Alexander; Kasimatis, Theodoros; Hizanidis, Johanne; Provata, Astero; Hövel, Philipp

2017-03-01

We discuss synchronization patterns in networks of FitzHugh-Nagumo and leaky integrate-and-fire oscillators coupled in a two-dimensional toroidal geometry. A common feature between the two models is the presence of fast and slow dynamics, a typical characteristic of neurons. Earlier studies have demonstrated that both models when coupled nonlocally in one-dimensional ring networks produce chimera states for a large range of parameter values. In this study, we give evidence of a plethora of two-dimensional chimera patterns of various shapes, including spots, rings, stripes, and grids, observed in both models, as well as additional patterns found mainly in the FitzHugh-Nagumo system. Both systems exhibit multistability: For the same parameter values, different initial conditions give rise to different dynamical states. Transitions occur between various patterns when the parameters (coupling range, coupling strength, refractory period, and coupling phase) are varied. Many patterns observed in the two models follow similar rules. For example, the diameter of the rings grows linearly with the coupling radius.

Chimera patterns in two-dimensional networks of coupled neurons

NASA Astrophysics Data System (ADS)

Schmidt, Alexander; Kasimatis, Theodoros; Hizanidis, Johanne; Provata, Astero; Hövel, Philipp

2017-03-01

We discuss synchronization patterns in networks of FitzHugh-Nagumo and leaky integrate-and-fire oscillators coupled in a two-dimensional toroidal geometry. A common feature between the two models is the presence of fast and slow dynamics, a typical characteristic of neurons. Earlier studies have demonstrated that both models when coupled nonlocally in one-dimensional ring networks produce chimera states for a large range of parameter values. In this study, we give evidence of a plethora of two-dimensional chimera patterns of various shapes, including spots, rings, stripes, and grids, observed in both models, as well as additional patterns found mainly in the FitzHugh-Nagumo system. Both systems exhibit multistability: For the same parameter values, different initial conditions give rise to different dynamical states. Transitions occur between various patterns when the parameters (coupling range, coupling strength, refractory period, and coupling phase) are varied. Many patterns observed in the two models follow similar rules. For example, the diameter of the rings grows linearly with the coupling radius.

Exploratory tests of two strut fuel injectors for supersonic combustion

NASA Technical Reports Server (NTRS)

Anderson, G. Y.; Gooderum, P. B.

1974-01-01

Results of supersonic mixing and combustion tests performed with two simple strut injector configurations, one with parallel injectors and one with perpendicular injectors, are presented and analyzed. Good agreement is obtained between static pressure measured on the duct wall downstream of the strut injectors and distributions obtained from one-dimensional calculations. Measured duct heat load agrees with results of the one-dimensional calculations for moderate amounts of reaction, but is underestimated when large separated regions occur near the injection location. For the parallel injection strut, good agreement is obtained between the shape of the injected fuel distribution inferred from gas sample measurements at the duct exit and the distribution calculated with a multiple-jet mixing theory. The overall fraction of injected fuel reacted in the multiple-jet calculation closely matches the amount of fuel reaction necessary to match static pressure with the one-dimensional calculation. Gas sample measurements with the perpendicular injection strut also give results consistent with the amount of fuel reaction in the one-dimensional calculation.

Influence of the extrinsic curvature on two-dimensional nematic films.

PubMed

Napoli, Gaetano; Vergori, Luigi

2018-05-01

Nematic films are thin fluid structures, ideally two dimensional, endowed with an in-plane degenerate nematic order. In this paper we examine a generalization of the classical Plateau problem to an axisymmetric nematic film bounded by two coaxial parallel rings. At equilibrium, the shape of the nematic film results from the competition between surface tension, which favors the minimization of the area, and the nematic elasticity, which instead promotes the alignment of the molecules along a common direction. We find two classes of equilibrium solutions in which the molecules are uniformly aligned along the meridians or parallels. Depending on two dimensionless parameters, one related to the geometry of the film and the other to the constitutive moduli, the Gaussian curvature of the equilibrium shape may be everywhere negative, vanishing, or positive. The stability of these equilibrium configurations is investigated.

Influence of the extrinsic curvature on two-dimensional nematic films

NASA Astrophysics Data System (ADS)

Napoli, Gaetano; Vergori, Luigi

2018-05-01

Nematic films are thin fluid structures, ideally two dimensional, endowed with an in-plane degenerate nematic order. In this paper we examine a generalization of the classical Plateau problem to an axisymmetric nematic film bounded by two coaxial parallel rings. At equilibrium, the shape of the nematic film results from the competition between surface tension, which favors the minimization of the area, and the nematic elasticity, which instead promotes the alignment of the molecules along a common direction. We find two classes of equilibrium solutions in which the molecules are uniformly aligned along the meridians or parallels. Depending on two dimensionless parameters, one related to the geometry of the film and the other to the constitutive moduli, the Gaussian curvature of the equilibrium shape may be everywhere negative, vanishing, or positive. The stability of these equilibrium configurations is investigated.

Locating hardware faults in a parallel computer

DOEpatents

Archer, Charles J.; Megerian, Mark G.; Ratterman, Joseph D.; Smith, Brian E.

2010-04-13

Locating hardware faults in a parallel computer, including defining within a tree network of the parallel computer two or more sets of non-overlapping test levels of compute nodes of the network that together include all the data communications links of the network, each non-overlapping test level comprising two or more adjacent tiers of the tree; defining test cells within each non-overlapping test level, each test cell comprising a subtree of the tree including a subtree root compute node and all descendant compute nodes of the subtree root compute node within a non-overlapping test level; performing, separately on each set of non-overlapping test levels, an uplink test on all test cells in a set of non-overlapping test levels; and performing, separately from the uplink tests and separately on each set of non-overlapping test levels, a downlink test on all test cells in a set of non-overlapping test levels.

An efficient three-dimensional Poisson solver for SIMD high-performance-computing architectures

NASA Technical Reports Server (NTRS)

Cohl, H.

1994-01-01

We present an algorithm that solves the three-dimensional Poisson equation on a cylindrical grid. The technique uses a finite-difference scheme with operator splitting. This splitting maps the banded structure of the operator matrix into a two-dimensional set of tridiagonal matrices, which are then solved in parallel. Our algorithm couples FFT techniques with the well-known ADI (Alternating Direction Implicit) method for solving Elliptic PDE's, and the implementation is extremely well suited for a massively parallel environment like the SIMD architecture of the MasPar MP-1. Due to the highly recursive nature of our problem, we believe that our method is highly efficient, as it avoids excessive interprocessor communication.

Mechanical Behavior of Collagen-Fibrin Co-Gels Reflects Transition From Series to Parallel Interactions With Increasing Collagen Content

PubMed Central

Lai, Victor K.; Lake, Spencer P.; Frey, Christina R.; Tranquillo, Robert T.; Barocas, Victor H.

2012-01-01

Fibrin and collagen, biopolymers occurring naturally in the body, are biomaterials commonly-used as scaffolds for tissue engineering. How collagen and fibrin interact to confer macroscopic mechanical properties in collagen-fibrin composite systems remains poorly understood. In this study, we formulated collagen-fibrin co-gels at different collagen-tofibrin ratios to observe changes in the overall mechanical behavior and microstructure. A modeling framework of a two-network system was developed by modifying our micro-scale model, considering two forms of interaction between the networks: (a) two interpenetrating but noninteracting networks (“parallel”), and (b) a single network consisting of randomly alternating collagen and fibrin fibrils (“series”). Mechanical testing of our gels show that collagen-fibrin co-gels exhibit intermediate properties (UTS, strain at failure, tangent modulus) compared to those of pure collagen and fibrin. The comparison with model predictions show that the parallel and series model cases provide upper and lower bounds, respectively, for the experimental data, suggesting that a combination of such interactions exists between the collagen and fibrin in co-gels. A transition from the series model to the parallel model occurs with increasing collagen content, with the series model best describing predominantly fibrin co-gels, and the parallel model best describing predominantly collagen co-gels. PMID:22482659

Scaling Properties of Dimensionality Reduction for Neural Populations and Network Models

PubMed Central

Cowley, Benjamin R.; Doiron, Brent; Kohn, Adam

2016-01-01

Recent studies have applied dimensionality reduction methods to understand how the multi-dimensional structure of neural population activity gives rise to brain function. It is unclear, however, how the results obtained from dimensionality reduction generalize to recordings with larger numbers of neurons and trials or how these results relate to the underlying network structure. We address these questions by applying factor analysis to recordings in the visual cortex of non-human primates and to spiking network models that self-generate irregular activity through a balance of excitation and inhibition. We compared the scaling trends of two key outputs of dimensionality reduction—shared dimensionality and percent shared variance—with neuron and trial count. We found that the scaling properties of networks with non-clustered and clustered connectivity differed, and that the in vivo recordings were more consistent with the clustered network. Furthermore, recordings from tens of neurons were sufficient to identify the dominant modes of shared variability that generalize to larger portions of the network. These findings can help guide the interpretation of dimensionality reduction outputs in regimes of limited neuron and trial sampling and help relate these outputs to the underlying network structure. PMID:27926936

A WENO-Limited, ADER-DT, Finite-Volume Scheme for Efficient, Robust, and Communication-Avoiding Multi-Dimensional Transport

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

Norman, Matthew R

2014-01-01

The novel ADER-DT time discretization is applied to two-dimensional transport in a quadrature-free, WENO- and FCT-limited, Finite-Volume context. Emphasis is placed on (1) the serial and parallel computational properties of ADER-DT and this framework and (2) the flexibility of ADER-DT and this framework in efficiently balancing accuracy with other constraints important to transport applications. This study demonstrates a range of choices for the user when approaching their specific application while maintaining good parallel properties. In this method, genuine multi-dimensionality, single-step and single-stage time stepping, strict positivity, and a flexible range of limiting are all achieved with only one parallel synchronizationmore » and data exchange per time step. In terms of parallel data transfers per simulated time interval, this improves upon multi-stage time stepping and post-hoc filtering techniques such as hyperdiffusion. This method is evaluated with standard transport test cases over a range of limiting options to demonstrate quantitatively and qualitatively what a user should expect when employing this method in their application.« less

Analysis of bacterial fatty acids by flow modulated comprehensive two-dimensional gas chromatography with parallel flame ionization detector/mass spectrometry.

PubMed

Gu, Qun; David, Frank; Lynen, Frédéric; Rumpel, Klaus; Xu, Guowang; De Vos, Paul; Sandra, Pat

2010-06-25

Comprehensive two-dimensional gas chromatography (GCxGC) offers an interesting tool for profiling bacterial fatty acids. Flow modulated GCxGC using a commercially available system was evaluated, different parameters such as column flows and modulation time were optimized. The method was tested on bacterial fatty acid methyl esters (BAMEs) from Stenotrophomonas maltophilia LMG 958T by using parallel flame ionization detector (FID)/mass spectrometry (MS). The results are compared to data obtained using a thermal modulated GCxGC system. The data show that flow modulated GCxGC-FID/MS method can be applied in a routine environment and offers interesting perspectives for chemotaxonomy of bacteria.

Research on two-port network of wavelet transform processor using surface acoustic wavelet devices and its application.

PubMed

Liu, Shoubing; Lu, Wenke; Zhu, Changchun

2017-11-01

The goal of this research is to study two-port network of wavelet transform processor (WTP) using surface acoustic wave (SAW) devices and its application. The motive was prompted by the inconvenience of the long research and design cycle and the huge research funding involved with traditional method in this field, which were caused by the lack of the simulation and emulation method of WTP using SAW devices. For this reason, we introduce the two-port network analysis tool, which has been widely used in the design and analysis of SAW devices with uniform interdigital transducers (IDTs). Because the admittance parameters calculation formula of the two-port network can only be used for the SAW devices with uniform IDTs, this analysis tool cannot be directly applied into the design and analysis of the processor using SAW devices, whose input interdigital transducer (IDT) is apodized weighting. Therefore, in this paper, we propose the channel segmentation method, which can convert the WTP using SAW devices into parallel channels, and also provide with the calculation formula of the number of channels, the number of finger pairs and the static capacitance of an interdigital period in each parallel channel firstly. From the parameters given above, we can calculate the admittance parameters of the two port network for each channel, so that we can obtain the admittance parameter of the two-port network of the WTP using SAW devices on the basis of the simplification rule of parallel two-port network. Through this analysis tool, not only can we get the impulse response function of the WTP using SAW devices but we can also get the matching circuit of it. Large numbers of studies show that the parameters of the two-port network obtained by this paper are consistent with those measured by network analyzer E5061A, and the impulse response function obtained by the two-port network analysis tool is also consistent with that measured by network analyzer E5061A, which can meet the accuracy requirements of the analysis of the WTP using SAW devices. Therefore the two-port network analysis tool discussed in this paper has comparatively higher theoretical and practical value. Copyright © 2017 Elsevier B.V. All rights reserved.

From biological neural networks to thinking machines: Transitioning biological organizational principles to computer technology

NASA Technical Reports Server (NTRS)

Ross, Muriel D.

1991-01-01

The three-dimensional organization of the vestibular macula is under study by computer assisted reconstruction and simulation methods as a model for more complex neural systems. One goal of this research is to transition knowledge of biological neural network architecture and functioning to computer technology, to contribute to the development of thinking computers. Maculas are organized as weighted neural networks for parallel distributed processing of information. The network is characterized by non-linearity of its terminal/receptive fields. Wiring appears to develop through constrained randomness. A further property is the presence of two main circuits, highly channeled and distributed modifying, that are connected through feedforward-feedback collaterals and biasing subcircuit. Computer simulations demonstrate that differences in geometry of the feedback (afferent) collaterals affects the timing and the magnitude of voltage changes delivered to the spike initiation zone. Feedforward (efferent) collaterals act as voltage followers and likely inhibit neurons of the distributed modifying circuit. These results illustrate the importance of feedforward-feedback loops, of timing, and of inhibition in refining neural network output. They also suggest that it is the distributed modifying network that is most involved in adaptation, memory, and learning. Tests of macular adaptation, through hyper- and microgravitational studies, support this hypothesis since synapses in the distributed modifying circuit, but not the channeled circuit, are altered. Transitioning knowledge of biological systems to computer technology, however, remains problematical.

Parallel Implementation of Triangular Cellular Automata for Computing Two-Dimensional Elastodynamic Response on Arbitrary Domains

NASA Astrophysics Data System (ADS)

Leamy, Michael J.; Springer, Adam C.

In this research we report parallel implementation of a Cellular Automata-based simulation tool for computing elastodynamic response on complex, two-dimensional domains. Elastodynamic simulation using Cellular Automata (CA) has recently been presented as an alternative, inherently object-oriented technique for accurately and efficiently computing linear and nonlinear wave propagation in arbitrarily-shaped geometries. The local, autonomous nature of the method should lead to straight-forward and efficient parallelization. We address this notion on symmetric multiprocessor (SMP) hardware using a Java-based object-oriented CA code implementing triangular state machines (i.e., automata) and the MPI bindings written in Java (MPJ Express). We use MPJ Express to reconfigure our existing CA code to distribute a domain's automata to cores present on a dual quad-core shared-memory system (eight total processors). We note that this message passing parallelization strategy is directly applicable to computer clustered computing, which will be the focus of follow-on research. Results on the shared memory platform indicate nearly-ideal, linear speed-up. We conclude that the CA-based elastodynamic simulator is easily configured to run in parallel, and yields excellent speed-up on SMP hardware.

Longitudinal Dynamics of 3-Dimensional Components of Selfhood After Severe Traumatic Brain Injury: A qEEG Case Study.

PubMed

Fingelkurts, Andrew A; Fingelkurts, Alexander A

2017-09-01

In this report, we describe the case of a patient who sustained extremely severe traumatic brain damage with diffuse axonal injury in a traffic accident and whose recovery was monitored during 6 years. Specifically, we were interested in the recovery dynamics of 3-dimensional components of selfhood (a 3-dimensional construct model for the complex experiential selfhood has been recently proposed based on the empirical findings on the functional-topographical specialization of 3 operational modules of brain functional network responsible for the self-consciousness processing) derived from the electroencephalographic (EEG) signal. The analysis revealed progressive (though not monotonous) restoration of EEG functional connectivity of 3 modules of brain functional network responsible for the self-consciousness processing, which was also paralleled by the clinically significant functional recovery. We propose that restoration of normal integrity of the operational modules of the self-referential brain network may underlie the positive dynamics of 3 aspects of selfhood and provide a neurobiological mechanism for their recovery. The results are discussed in the context of recent experimental studies that support this inference. Studies of ongoing recovery after severe brain injury utilizing knowledge about each separate aspect of complex selfhood will likely help to develop more efficient and targeted rehabilitation programs for patients with brain trauma.

Implementation of a Parallel Kalman Filter for Stratospheric Chemical Tracer Assimilation

NASA Technical Reports Server (NTRS)

Chang, Lang-Ping; Lyster, Peter M.; Menard, R.; Cohn, S. E.

1998-01-01

A Kalman filter for the assimilation of long-lived atmospheric chemical constituents has been developed for two-dimensional transport models on isentropic surfaces over the globe. An important attribute of the Kalman filter is that it calculates error covariances of the constituent fields using the tracer dynamics. Consequently, the current Kalman-filter assimilation is a five-dimensional problem (coordinates of two points and time), and it can only be handled on computers with large memory and high floating point speed. In this paper, an implementation of the Kalman filter for distributed-memory, message-passing parallel computers is discussed. Two approaches were studied: an operator decomposition and a covariance decomposition. The latter was found to be more scalable than the former, and it possesses the property that the dynamical model does not need to be parallelized, which is of considerable practical advantage. This code is currently used to assimilate constituent data retrieved by limb sounders on the Upper Atmosphere Research Satellite. Tests of the code examined the variance transport and observability properties. Aspects of the parallel implementation, some timing results, and a brief discussion of the physical results will be presented.

Parallel replica dynamics method for bistable stochastic reaction networks: Simulation and sensitivity analysis

NASA Astrophysics Data System (ADS)

Wang, Ting; Plecháč, Petr

2017-12-01

Stochastic reaction networks that exhibit bistable behavior are common in systems biology, materials science, and catalysis. Sampling of stationary distributions is crucial for understanding and characterizing the long-time dynamics of bistable stochastic dynamical systems. However, simulations are often hindered by the insufficient sampling of rare transitions between the two metastable regions. In this paper, we apply the parallel replica method for a continuous time Markov chain in order to improve sampling of the stationary distribution in bistable stochastic reaction networks. The proposed method uses parallel computing to accelerate the sampling of rare transitions. Furthermore, it can be combined with the path-space information bounds for parametric sensitivity analysis. With the proposed methodology, we study three bistable biological networks: the Schlögl model, the genetic switch network, and the enzymatic futile cycle network. We demonstrate the algorithmic speedup achieved in these numerical benchmarks. More significant acceleration is expected when multi-core or graphics processing unit computer architectures and programming tools such as CUDA are employed.

Preparation and crystal structure of K/sub 2/Nb/sub 2/As/sub 2/O/sub 11/

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

Faouzi Zid, M.; Jouini, T.; Juoini, N.

1988-06-01

K/sup 2/Nb/sub 2/As/sub 2/O/sub 11/ crystallizes in the monoclinic system, space group P21/a, with a = 10.342(6), b = 10.446(5), c = 9.971(4) A, ..beta.. = 96.72(4)/sup 0/, M = 589.86, V = 1069.8(5) A/sup 3/, Z = 4, rho = 3.67 g cm/sup -1/. The crystal structure was refined (105 variables) from 1782 independent reflections collected on a Philips PW 1100 automatic diffractometer with AgK anti ..cap alpha.. radiation. The final R index and weighted R/sub w/ index are 0.058 and 0.056, respectively. The structure consists of NbO/sub 6/ octahedra and AsO/sub 4/ tetrahedra sharing vertices, forming infinite chainsmore » (NbO/sub 6/-AsO/sub 4/)infinity parallel to the a axis. Two chains are linked together by Nb-O-Nb and Nb-O-As bonds. These double chains are connected by vertices, forming a three-dimensional network. The potassium atoms are located in tunnels parallel to the a axis.« less

Crystal structures of Ca(ClO4)2·4H2O and Ca(ClO4)2·6H2O

PubMed Central

Hennings, Erik; Schmidt, Horst; Voigt, Wolfgang

2014-01-01

The title compounds, calcium perchlorate tetra­hydrate and calcium perchlorate hexa­hydrate, were crystallized at low temperatures according to the solid–liquid phase diagram. The structure of the tetra­hydrate consists of one Ca2+ cation eightfold coordinated in a square-anti­prismatic fashion by four water mol­ecules and four O atoms of four perchlorate tetra­hedra, forming chains parallel to [01-1] by sharing corners of the ClO4 tetra­hedra. The structure of the hexa­hydrate contains two different Ca2+ cations, each coordinated by six water mol­ecules and two O atoms of two perchlorate tetra­hedra, forming [Ca(H2O)6(ClO4)]2 dimers by sharing two ClO4 tetra­hedra. The dimers are arranged in sheets parallel (001) and alternate with layers of non-coordinating ClO4 tetra­hedra. O—H⋯O hydrogen bonds between the water mol­ecules as donor and ClO4 tetra­hedra and water mol­ecules as acceptor groups lead to the formation of a three-dimensional network in the two structures. Ca(ClO4)2·6H2O was refined as a two-component inversion twin, with an approximate twin component ratio of 1:1 in each of the two structures. PMID:25552974

Efficient implementation of parallel three-dimensional FFT on clusters of PCs

NASA Astrophysics Data System (ADS)

Takahashi, Daisuke

2003-05-01

In this paper, we propose a high-performance parallel three-dimensional fast Fourier transform (FFT) algorithm on clusters of PCs. The three-dimensional FFT algorithm can be altered into a block three-dimensional FFT algorithm to reduce the number of cache misses. We show that the block three-dimensional FFT algorithm improves performance by utilizing the cache memory effectively. We use the block three-dimensional FFT algorithm to implement the parallel three-dimensional FFT algorithm. We succeeded in obtaining performance of over 1.3 GFLOPS on an 8-node dual Pentium III 1 GHz PC SMP cluster.

Two- to three-dimensional crossover in a dense electron liquid in silicon

NASA Astrophysics Data System (ADS)

Matmon, Guy; Ginossar, Eran; Villis, Byron J.; Kölker, Alex; Lim, Tingbin; Solanki, Hari; Schofield, Steven R.; Curson, Neil J.; Li, Juerong; Murdin, Ben N.; Fisher, Andrew J.; Aeppli, Gabriel

2018-04-01

Doping of silicon via phosphine exposures alternating with molecular beam epitaxy overgrowth is a path to Si:P substrates for conventional microelectronics and quantum information technologies. The technique also provides a well-controlled material for systematic studies of two-dimensional lattices with a half-filled band. We show here that for a dense (ns=2.8 ×1014 cm-2) disordered two-dimensional array of P atoms, the full field magnitude and angle-dependent magnetotransport is remarkably well described by classic weak localization theory with no corrections due to interaction. The two- to three-dimensional crossover seen upon warming can also be interpreted using scaling concepts developed for anistropic three-dimensional materials, which work remarkably except when the applied fields are nearly parallel to the conducting planes.

Decoupling Principle Analysis and Development of a Parallel Three-Dimensional Force Sensor

PubMed Central

Zhao, Yanzhi; Jiao, Leihao; Weng, Dacheng; Zhang, Dan; Zheng, Rencheng

2016-01-01

In the development of the multi-dimensional force sensor, dimension coupling is the ubiquitous factor restricting the improvement of the measurement accuracy. To effectively reduce the influence of dimension coupling on the parallel multi-dimensional force sensor, a novel parallel three-dimensional force sensor is proposed using a mechanical decoupling principle, and the influence of the friction on dimension coupling is effectively reduced by making the friction rolling instead of sliding friction. In this paper, the mathematical model is established by combining with the structure model of the parallel three-dimensional force sensor, and the modeling and analysis of mechanical decoupling are carried out. The coupling degree (ε) of the designed sensor is defined and calculated, and the calculation results show that the mechanical decoupling parallel structure of the sensor possesses good decoupling performance. A prototype of the parallel three-dimensional force sensor was developed, and FEM analysis was carried out. The load calibration and data acquisition experiment system are built, and then calibration experiments were done. According to the calibration experiments, the measurement accuracy is less than 2.86% and the coupling accuracy is less than 3.02%. The experimental results show that the sensor system possesses high measuring accuracy, which provides a basis for the applied research of the parallel multi-dimensional force sensor. PMID:27649194

Dimethyl 4-[3-(4-meth­oxy­phen­yl)-1-phenyl-1H-pyrazol-4-yl]-2,6-dimethyl-1,4-dihydro­pyridine-3,5-dicarboxyl­ate dihydrate

PubMed Central

Fun, Hoong-Kun; Ooi, Chin Wei; Garudachari, B.; Shivananda, Kammasandra Nanjunda; Isloor, Arun M.

2012-01-01

In the title compound, C27H27N3O5·2H2O, the dihydro­pyridine ring adopts a flattened boat conformation. The central pyrazole ring is essentially planar [maximum deviation of 0.003 (1) Å] and makes dihedral angles of 50.42 (6) and 26.44 (6)° with the benzene rings. In the crystal, mol­ecules are linked via N—H⋯O, O—H⋯O, O—H⋯N and C—H⋯O hydrogen bonds into two-dimensional networks parallel to the bc plane. The crystal structure is further consolidated by weak C—H⋯π inter­actions. PMID:22798871

Crystal structure of (±)-1-({[4-(all­yloxy)phen­yl]sulfan­yl}meth­yl)-2-(di­phenyl­thio­phosphor­yl)ferrocene

PubMed Central

Michelot, Audric; Sarda, Stéphanie; Daran, Jean-Claude; Deydier, Eric; Manoury, Eric

2015-01-01

The title compound, [Fe(C5H5)(C27H24OPS2)], is built up from a ferrocene moiety substituted in the 1- and 2-positions by {[4-(all­yloxy)phen­yl]sulfan­yl}methyl and di­phenyl­thio­phosphoryl groups, respectively. The two S atoms lie on opposite sides of the cyclo­penta­dienyl ring plane to which they are attached. In the crystal, C—H⋯S hydrogen bonds link the mol­ecules into a ribbon running parallel to the (-110) plane. C—H⋯π inter­actions link the ribbons to form a three-dimensional network. PMID:26396768

Crystal structures of two mixed-valence copper cyanide complexes with N-methyl­ethylenedi­amine

PubMed Central

Sabatino, Alexander

2017-01-01

The crystal structures of two mixed-valence copper cyanide compounds involving N-methyl­ethylenedi­amine (meen), are described. In compound (I), poly[bis(μ3-cyanido-κ3 C:C:N)tris(μ2-cyanido-κ2 C:N)bis(N-methylethane-1,2-di­amine-κ2 N,N′)tricopper(I)copper(II)], [Cu4(CN)5(C3H10N2)2] or Cu4(CN)5meen2, cyanide groups link CuI atoms into a three-dimensional network containing open channels parallel to the b axis. In the network, two tetra­hedrally bound CuI atoms are bonded by the C atoms of two end-on bridging CN groups to form Cu2(CN)6 moieties with the Cu atoms in close contact at 2.560 (1) Å. Other trigonally bound CuI atoms link these units together to form the network. The CuII atoms, coordinated by two meen units, are covalently linked to the network via a cyanide bridge, and project into the open network channels. In the mol­ecular compound (II), [(N-methylethylenediamine-κ2 N,N′)copper(II)]-μ2-cyanido-κ2 C:N-[bis(cyanido-κC)copper(I)] monohydrate, [Cu2(CN)3(C3H10N2)2]·H2O or Cu2(CN)3meen2·H2O, a CN group connects a CuII atom coordinated by two meen groups with a trigonal–planar CuI atom coordinated by CN groups. The mol­ecules are linked into centrosymmetric dimers via hydrogen bonds to two water mol­ecules. In both compounds, the bridging cyanide between the CuII and CuI atoms has the N atom bonded to CuII and the C atom bonded to CuI, and the CuII atoms are in a square-pyramidal coordination. PMID:28217329

Parallel computing of a climate model on the dawn 1000 by domain decomposition method

NASA Astrophysics Data System (ADS)

Bi, Xunqiang

1997-12-01

In this paper the parallel computing of a grid-point nine-level atmospheric general circulation model on the Dawn 1000 is introduced. The model was developed by the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS). The Dawn 1000 is a MIMD massive parallel computer made by National Research Center for Intelligent Computer (NCIC), CAS. A two-dimensional domain decomposition method is adopted to perform the parallel computing. The potential ways to increase the speed-up ratio and exploit more resources of future massively parallel supercomputation are also discussed.

Network marketing on a small-world network

NASA Astrophysics Data System (ADS)

Kim, Beom Jun; Jun, Tackseung; Kim, Jeong-Yoo; Choi, M. Y.

2006-02-01

We investigate a dynamic model of network marketing in a small-world network structure artificially constructed similarly to the Watts-Strogatz network model. Different from the traditional marketing, consumers can also play the role of the manufacturer's selling agents in network marketing, which is stimulated by the referral fee the manufacturer offers. As the wiring probability α is increased from zero to unity, the network changes from the one-dimensional regular directed network to the star network where all but one player are connected to one consumer. The price p of the product and the referral fee r are used as free parameters to maximize the profit of the manufacturer. It is observed that at α=0 the maximized profit is constant independent of the network size N while at α≠0, it increases linearly with N. This is in parallel to the small-world transition. It is also revealed that while the optimal value of p stays at an almost constant level in a broad range of α, that of r is sensitive to a change in the network structure. The consumer surplus is also studied and discussed.

Parallel Distributed Processing Theory in the Age of Deep Networks.

PubMed

Bowers, Jeffrey S

2017-12-01

Parallel distributed processing (PDP) models in psychology are the precursors of deep networks used in computer science. However, only PDP models are associated with two core psychological claims, namely that all knowledge is coded in a distributed format and cognition is mediated by non-symbolic computations. These claims have long been debated in cognitive science, and recent work with deep networks speaks to this debate. Specifically, single-unit recordings show that deep networks learn units that respond selectively to meaningful categories, and researchers are finding that deep networks need to be supplemented with symbolic systems to perform some tasks. Given the close links between PDP and deep networks, it is surprising that research with deep networks is challenging PDP theory. Copyright © 2017. Published by Elsevier Ltd.

Reliability of a Parallel Pipe Network

NASA Technical Reports Server (NTRS)

Herrera, Edgar; Chamis, Christopher (Technical Monitor)

2001-01-01

The goal of this NASA-funded research is to advance research and education objectives in theoretical and computational probabilistic structural analysis, reliability, and life prediction methods for improved aerospace and aircraft propulsion system components. Reliability methods are used to quantify response uncertainties due to inherent uncertainties in design variables. In this report, several reliability methods are applied to a parallel pipe network. The observed responses are the head delivered by a main pump and the head values of two parallel lines at certain flow rates. The probability that the flow rates in the lines will be less than their specified minimums will be discussed.

Further two-dimensional code development for Stirling space engine components

NASA Technical Reports Server (NTRS)

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.

Error estimation and adaptive mesh refinement for parallel analysis of shell structures

NASA Technical Reports Server (NTRS)

Keating, Scott C.; Felippa, Carlos A.; Park, K. C.

1994-01-01

The formulation and application of element-level, element-independent error indicators is investigated. This research culminates in the development of an error indicator formulation which is derived based on the projection of element deformation onto the intrinsic element displacement modes. The qualifier 'element-level' means that no information from adjacent elements is used for error estimation. This property is ideally suited for obtaining error values and driving adaptive mesh refinements on parallel computers where access to neighboring elements residing on different processors may incur significant overhead. In addition such estimators are insensitive to the presence of physical interfaces and junctures. An error indicator qualifies as 'element-independent' when only visible quantities such as element stiffness and nodal displacements are used to quantify error. Error evaluation at the element level and element independence for the error indicator are highly desired properties for computing error in production-level finite element codes. Four element-level error indicators have been constructed. Two of the indicators are based on variational formulation of the element stiffness and are element-dependent. Their derivations are retained for developmental purposes. The second two indicators mimic and exceed the first two in performance but require no special formulation of the element stiffness mesh refinement which we demonstrate for two dimensional plane stress problems. The parallelizing of substructures and adaptive mesh refinement is discussed and the final error indicator using two-dimensional plane-stress and three-dimensional shell problems is demonstrated.

Fast Two-Dimensional Bubble Analysis of Biopolymer Filamentous Networks Pore Size from Confocal Microscopy Thin Data Stacks

PubMed Central

Molteni, Matteo; Magatti, Davide; Cardinali, Barbara; Rocco, Mattia; Ferri, Fabio

2013-01-01

The average pore size ξ0 of filamentous networks assembled from biological macromolecules is one of the most important physical parameters affecting their biological functions. Modern optical methods, such as confocal microscopy, can noninvasively image such networks, but extracting a quantitative estimate of ξ0 is a nontrivial task. We present here a fast and simple method based on a two-dimensional bubble approach, which works by analyzing one by one the (thresholded) images of a series of three-dimensional thin data stacks. No skeletonization or reconstruction of the full geometry of the entire network is required. The method was validated by using many isotropic in silico generated networks of different structures, morphologies, and concentrations. For each type of network, the method provides accurate estimates (a few percent) of the average and the standard deviation of the three-dimensional distribution of the pore sizes, defined as the diameters of the largest spheres that can be fit into the pore zones of the entire gel volume. When applied to the analysis of real confocal microscopy images taken on fibrin gels, the method provides an estimate of ξ0 consistent with results from elastic light scattering data. PMID:23473499

catena-Poly[[[4,6-bis-(2-pyrid-yl)-1,3,5-triazin-2-olato]copper(II)]-μ-chlorido].

PubMed

Cao, Man-Li

2011-06-01

The title compound, [Cu(C(13)H(8)N(5)O)Cl](n), has a chain structure parallel to [100] with Cu(2+) cations in a trigonal-bipyramidal coordination environment. The ligand adopts a tridentate tripyridyl coordination mode and a chloride ion acts as a bridge. The chains are linked via weak C-H⋯O and C-H⋯Cl hydrogen bonds into a three-dimensional supra-molecular network.

Orbital effect for the Fulde-Ferrell-Larkin-Ovchinnikov phase in a quasi-two-dimensional superconductor in a parallel magnetic field

NASA Astrophysics Data System (ADS)

Lebed, A. G.

2018-04-01

We theoretically study the orbital destructive effect against superconductivity in a parallel magnetic field in the Fulde-Ferrell-Larkin-Ovchinnikov (FFLO or LOFF) phase at zero temperature in a quasi-two-dimensional (Q2D) conductor. We demonstrate that at zero temperature a special parameter, λ =l⊥(H ) /d , is responsible for strength of the orbital effect, where l⊥(H ) is a typical "size" of the quasiclassical electron orbit in a magnetic field and d is the interplane distance. We discuss applications of our results to the existing experiments on the FFLO phase in the organic Q2D conductors κ -(ET) 2Cu (NCS) 2 and κ -(ET) 2Cu [N (CN) 2] Cl .

Three-dimensional neural cultures produce networks that mimic native brain activity.

PubMed

Bourke, Justin L; Quigley, Anita F; Duchi, Serena; O'Connell, Cathal D; Crook, Jeremy M; Wallace, Gordon G; Cook, Mark J; Kapsa, Robert M I

2018-02-01

Development of brain function is critically dependent on neuronal networks organized through three dimensions. Culture of central nervous system neurons has traditionally been limited to two dimensions, restricting growth patterns and network formation to a single plane. Here, with the use of multichannel extracellular microelectrode arrays, we demonstrate that neurons cultured in a true three-dimensional environment recapitulate native neuronal network formation and produce functional outcomes more akin to in vivo neuronal network activity. Copyright © 2017 John Wiley & Sons, Ltd.

A parallel program for numerical simulation of discrete fracture network and groundwater flow

NASA Astrophysics Data System (ADS)

Huang, Ting-Wei; Liou, Tai-Sheng; Kalatehjari, Roohollah

2017-04-01

The ability of modeling fluid flow in Discrete Fracture Network (DFN) is critical to various applications such as exploration of reserves in geothermal and petroleum reservoirs, geological sequestration of carbon dioxide and final disposal of spent nuclear fuels. Although several commerical or acdametic DFN flow simulators are already available (e.g., FracMan and DFNWORKS), challenges in terms of computational efficiency and three-dimensional visualization still remain, which therefore motivates this study for developing a new DFN and flow simulator. A new DFN and flow simulator, DFNbox, was written in C++ under a cross-platform software development framework provided by Qt. DFNBox integrates the following capabilities into a user-friendly drop-down menu interface: DFN simulation and clipping, 3D mesh generation, fracture data analysis, connectivity analysis, flow path analysis and steady-state grounwater flow simulation. All three-dimensional visualization graphics were developed using the free OpenGL API. Similar to other DFN simulators, fractures are conceptualized as random point process in space, with stochastic characteristics represented by orientation, size, transmissivity and aperture. Fracture meshing was implemented by Delaunay triangulation for visualization but not flow simulation purposes. Boundary element method was used for flow simulations such that only unknown head or flux along exterior and interection bounaries are needed for solving the flow field in the DFN. Parallel compuation concept was taken into account in developing DFNbox for calculations that such concept is possible. For example, the time-consuming seqential code for fracture clipping calculations has been completely replaced by a highly efficient parallel one. This can greatly enhance compuational efficiency especially on multi-thread platforms. Furthermore, DFNbox have been successfully tested in Windows and Linux systems with equally-well performance.

Flow distribution in parallel microfluidic networks and its effect on concentration gradient

PubMed Central

Guermonprez, Cyprien; Michelin, Sébastien; Baroud, Charles N.

2015-01-01

The architecture of microfluidic networks can significantly impact the flow distribution within its different branches and thereby influence tracer transport within the network. In this paper, we study the flow rate distribution within a network of parallel microfluidic channels with a single input and single output, using a combination of theoretical modeling and microfluidic experiments. Within the ladder network, the flow rate distribution follows a U-shaped profile, with the highest flow rate occurring in the initial and final branches. The contrast with the central branches is controlled by a single dimensionless parameter, namely, the ratio of hydrodynamic resistance between the distribution channel and the side branches. This contrast in flow rates decreases when the resistance of the side branches increases relative to the resistance of the distribution channel. When the inlet flow is composed of two parallel streams, one of which transporting a diffusing species, a concentration variation is produced within the side branches of the network. The shape of this concentration gradient is fully determined by two dimensionless parameters: the ratio of resistances, which determines the flow rate distribution, and the Péclet number, which characterizes the relative speed of diffusion and advection. Depending on the values of these two control parameters, different distribution profiles can be obtained ranging from a flat profile to a step distribution of solute, with well-distributed gradients between these two limits. Our experimental results are in agreement with our numerical model predictions, based on a simplified 2D advection-diffusion problem. Finally, two possible applications of this work are presented: the first one combines the present design with self-digitization principle to encapsulate the controlled concentration in nanoliter chambers, while the second one extends the present design to create a continuous concentration gradient within an open flow chamber. PMID:26487905

Human-level control through deep reinforcement learning.

PubMed

Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A; Veness, Joel; Bellemare, Marc G; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis

2015-02-26

The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.

Human-level control through deep reinforcement learning

NASA Astrophysics Data System (ADS)

Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A.; Veness, Joel; Bellemare, Marc G.; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K.; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis

2015-02-01

The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.

Implementation of a parallel unstructured Euler solver on shared and distributed memory architectures

NASA Technical Reports Server (NTRS)

Mavriplis, D. J.; Das, Raja; Saltz, Joel; Vermeland, R. E.

1992-01-01

An efficient three dimensional unstructured Euler solver is parallelized on a Cray Y-MP C90 shared memory computer and on an Intel Touchstone Delta distributed memory computer. This paper relates the experiences gained and describes the software tools and hardware used in this study. Performance comparisons between two differing architectures are made.

Implementation and Characterization of Three-Dimensional Particle-in-Cell Codes on Multiple-Instruction-Multiple-Data Massively Parallel Supercomputers

NASA Technical Reports Server (NTRS)

Lyster, P. M.; Liewer, P. C.; Decyk, V. K.; Ferraro, R. D.

1995-01-01

A three-dimensional electrostatic particle-in-cell (PIC) plasma simulation code has been developed on coarse-grain distributed-memory massively parallel computers with message passing communications. Our implementation is the generalization to three-dimensions of the general concurrent particle-in-cell (GCPIC) algorithm. In the GCPIC algorithm, the particle computation is divided among the processors using a domain decomposition of the simulation domain. In a three-dimensional simulation, the domain can be partitioned into one-, two-, or three-dimensional subdomains ("slabs," "rods," or "cubes") and we investigate the efficiency of the parallel implementation of the push for all three choices. The present implementation runs on the Intel Touchstone Delta machine at Caltech; a multiple-instruction-multiple-data (MIMD) parallel computer with 512 nodes. We find that the parallel efficiency of the push is very high, with the ratio of communication to computation time in the range 0.3%-10.0%. The highest efficiency (> 99%) occurs for a large, scaled problem with 64(sup 3) particles per processing node (approximately 134 million particles of 512 nodes) which has a push time of about 250 ns per particle per time step. We have also developed expressions for the timing of the code which are a function of both code parameters (number of grid points, particles, etc.) and machine-dependent parameters (effective FLOP rate, and the effective interprocessor bandwidths for the communication of particles and grid points). These expressions can be used to estimate the performance of scaled problems--including those with inhomogeneous plasmas--to other parallel machines once the machine-dependent parameters are known.

Parallel image-acquisition in continuous-wave electron paramagnetic resonance imaging with a surface coil array: Proof-of-concept experiments

NASA Astrophysics Data System (ADS)

Enomoto, Ayano; Hirata, Hiroshi

2014-02-01

This article describes a feasibility study of parallel image-acquisition using a two-channel surface coil array in continuous-wave electron paramagnetic resonance (CW-EPR) imaging. Parallel EPR imaging was performed by multiplexing of EPR detection in the frequency domain. The parallel acquisition system consists of two surface coil resonators and radiofrequency (RF) bridges for EPR detection. To demonstrate the feasibility of this method of parallel image-acquisition with a surface coil array, three-dimensional EPR imaging was carried out using a tube phantom. Technical issues in the multiplexing method of EPR detection were also clarified. We found that degradation in the signal-to-noise ratio due to the interference of RF carriers is a key problem to be solved.

Identifying messaging completion in a parallel computer by checking for change in message received and transmitted count at each node

DOEpatents

Archer, Charles J [Rochester, MN; Hardwick, Camesha R [Fayetteville, NC; McCarthy, Patrick J [Rochester, MN; Wallenfelt, Brian P [Eden Prairie, MN

2009-06-23

Methods, parallel computers, and products are provided for identifying messaging completion on a parallel computer. The parallel computer includes a plurality of compute nodes, the compute nodes coupled for data communications by at least two independent data communications networks including a binary tree data communications network optimal for collective operations that organizes the nodes as a tree and a torus data communications network optimal for point to point operations that organizes the nodes as a torus. Embodiments include reading all counters at each node of the torus data communications network; calculating at each node a current node value in dependence upon the values read from the counters at each node; and determining for all nodes whether the current node value for each node is the same as a previously calculated node value for each node. If the current node is the same as the previously calculated node value for all nodes of the torus data communications network, embodiments include determining that messaging is complete and if the current node is not the same as the previously calculated node value for all nodes of the torus data communications network, embodiments include determining that messaging is currently incomplete.

On the effect of memory in one-dimensional K=4 automata on networks

NASA Astrophysics Data System (ADS)

Alonso-Sanz, Ramón; Cárdenas, Juan Pablo

2008-12-01

The effect of implementing memory in cells of one-dimensional CA, and on nodes of various types of automata on networks with increasing degrees of random rewiring is studied in this article, paying particular attention to the case of four inputs. As a rule, memory induces a moderation in the rate of changing nodes and in the damage spreading, albeit in the latter case memory turns out to be ineffective in the control of the damage as the wiring network moves away from the ordered structure that features proper one-dimensional CA. This article complements the previous work done in the two-dimensional context.

Macroscopic Lagrangian description of warm plasmas. II Nonlinear wave interactions

NASA Technical Reports Server (NTRS)

Kim, H.; Crawford, F. W.

1983-01-01

A macroscopic Lagrangian is simplified to the adiabatic limit and expanded about equilibrium, to third order in perturbation, for three illustrative cases: one-dimensional compression parallel to the static magnetic field, two-dimensional compression perpendicular to the static magnetic field, and three-dimensional compression. As examples of the averaged-Lagrangian method applied to nonlinear wave interactions, coupling coefficients are derived for interactions between two electron plasma waves and an ion acoustic wave, and between an ordinary wave, an electron plasma wave, and an ion acoustic wave.

Dynamic grid refinement for partial differential equations on parallel computers

NASA Technical Reports Server (NTRS)

Mccormick, S.; Quinlan, D.

1989-01-01

The fast adaptive composite grid method (FAC) is an algorithm that uses various levels of uniform grids to provide adaptive resolution and fast solution of PDEs. An asynchronous version of FAC, called AFAC, that completely eliminates the bottleneck to parallelism is presented. This paper describes the advantage that this algorithm has in adaptive refinement for moving singularities on multiprocessor computers. This work is applicable to the parallel solution of two- and three-dimensional shock tracking problems.

Multitasking the three-dimensional transport code TORT on CRAY platforms

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

Azmy, Y.Y.; Barnett, D.A.; Burre, C.A.

1996-04-01

The multitasking options in the three-dimensional neutral particle transport code TORT originally implemented for Cray`s CTSS operating system are revived and extended to run on Cray Y/MP and C90 computers using the UNICOS operating system. These include two coarse-grained domain decompositions; across octants, and across directions within an octant, termed Octant Parallel (OP), and Direction Parallel (DP), respectively. Parallel performance of the DP is significantly enhanced by increasing the task grain size and reducing load imbalance via dynamic scheduling of the discrete angles among the participating tasks. Substantial Wall Clock speedup factors, approaching 4.5 using 8 tasks, have been measuredmore » in a time-sharing environment, and generally depend on the test problem specifications, number of tasks, and machine loading during execution.« less

Parallel and orthogonal stimulus in ultradiluted neural networks

NASA Astrophysics Data System (ADS)

Sobral, G. A., Jr.; Vieira, V. M.; Lyra, M. L.; da Silva, C. R.

2006-10-01

Extending a model due to Derrida, Gardner, and Zippelius, we have studied the recognition ability of an extreme and asymmetrically diluted version of the Hopfield model for associative memory by including the effect of a stimulus in the dynamics of the system. We obtain exact results for the dynamic evolution of the average network superposition. The stimulus field was considered as proportional to the overlapping of the state of the system with a particular stimulated pattern. Two situations were analyzed, namely, the external stimulus acting on the initialization pattern (parallel stimulus) and the external stimulus acting on a pattern orthogonal to the initialization one (orthogonal stimulus). In both cases, we obtained the complete phase diagram in the parameter space composed of the stimulus field, thermal noise, and network capacity. Our results show that the system improves its recognition ability for parallel stimulus. For orthogonal stimulus two recognition phases emerge with the system locking at the initialization or stimulated pattern. We confront our analytical results with numerical simulations for the noiseless case T=0 .

Electronic Structure of Two-Dimensional Hydrocarbon Networks of sp2 and sp3 C Atoms

NASA Astrophysics Data System (ADS)

Fujii, Yasumaru; Maruyama, Mina; Wakabayashi, Katsunori; Nakada, Kyoko; Okada, Susumu

2018-03-01

Based on density functional theory with the generalized gradient approximation, we have investigated the geometric and electronic structures of two-dimensional hexagonal covalent networks consisting of oligoacenes and fourfold coordinated hydrocarbon atoms, which are alternately arranged in a hexagonal manner. All networks were semiconductors with a finite energy gap at the Γ point, which monotonically decreased with the increase of the oligoacene length. As a result of a Kagome network of oligoacene connected through sp3 C atoms, the networks possess peculiar electron states in their valence and conduction bands, which consist of a flat dispersion band and a Dirac cone. The total energy of the networks depends on the oligoacene length and has a minimum for the network comprising naphthalene.

Massively parallel processor networks with optical express channels

DOEpatents

Deri, R.J.; Brooks, E.D. III; Haigh, R.E.; DeGroot, A.J.

1999-08-24

An optical method for separating and routing local and express channel data comprises interconnecting the nodes in a network with fiber optic cables. A single fiber optic cable carries both express channel traffic and local channel traffic, e.g., in a massively parallel processor (MPP) network. Express channel traffic is placed on, or filtered from, the fiber optic cable at a light frequency or a color different from that of the local channel traffic. The express channel traffic is thus placed on a light carrier that skips over the local intermediate nodes one-by-one by reflecting off of selective mirrors placed at each local node. The local-channel-traffic light carriers pass through the selective mirrors and are not reflected. A single fiber optic cable can thus be threaded throughout a three-dimensional matrix of nodes with the x,y,z directions of propagation encoded by the color of the respective light carriers for both local and express channel traffic. Thus frequency division multiple access is used to hierarchically separate the local and express channels to eliminate the bucket brigade latencies that would otherwise result if the express traffic had to hop between every local node to reach its ultimate destination. 3 figs.

An Airway Network Flow Assignment Approach Based on an Efficient Multiobjective Optimization Framework

PubMed Central

Zhang, Xuejun; Lei, Jiaxing

2015-01-01

Considering reducing the airspace congestion and the flight delay simultaneously, this paper formulates the airway network flow assignment (ANFA) problem as a multiobjective optimization model and presents a new multiobjective optimization framework to solve it. Firstly, an effective multi-island parallel evolution algorithm with multiple evolution populations is employed to improve the optimization capability. Secondly, the nondominated sorting genetic algorithm II is applied for each population. In addition, a cooperative coevolution algorithm is adapted to divide the ANFA problem into several low-dimensional biobjective optimization problems which are easier to deal with. Finally, in order to maintain the diversity of solutions and to avoid prematurity, a dynamic adjustment operator based on solution congestion degree is specifically designed for the ANFA problem. Simulation results using the real traffic data from China air route network and daily flight plans demonstrate that the proposed approach can improve the solution quality effectively, showing superiority to the existing approaches such as the multiobjective genetic algorithm, the well-known multiobjective evolutionary algorithm based on decomposition, and a cooperative coevolution multiobjective algorithm as well as other parallel evolution algorithms with different migration topology. PMID:26180840

Massively parallel processor networks with optical express channels

DOEpatents

Deri, Robert J.; Brooks, III, Eugene D.; Haigh, Ronald E.; DeGroot, Anthony J.

1999-01-01

An optical method for separating and routing local and express channel data comprises interconnecting the nodes in a network with fiber optic cables. A single fiber optic cable carries both express channel traffic and local channel traffic, e.g., in a massively parallel processor (MPP) network. Express channel traffic is placed on, or filtered from, the fiber optic cable at a light frequency or a color different from that of the local channel traffic. The express channel traffic is thus placed on a light carrier that skips over the local intermediate nodes one-by-one by reflecting off of selective mirrors placed at each local node. The local-channel-traffic light carriers pass through the selective mirrors and are not reflected. A single fiber optic cable can thus be threaded throughout a three-dimensional matrix of nodes with the x,y,z directions of propagation encoded by the color of the respective light carriers for both local and express channel traffic. Thus frequency division multiple access is used to hierarchically separate the local and express channels to eliminate the bucket brigade latencies that would otherwise result if the express traffic had to hop between every local node to reach its ultimate destination.

Aerodynamic simulation on massively parallel systems

NASA Technical Reports Server (NTRS)

Haeuser, Jochem; Simon, Horst D.

1992-01-01

This paper briefly addresses the computational requirements for the analysis of complete configurations of aircraft and spacecraft currently under design to be used for advanced transportation in commercial applications as well as in space flight. The discussion clearly shows that massively parallel systems are the only alternative which is both cost effective and on the other hand can provide the necessary TeraFlops, needed to satisfy the narrow design margins of modern vehicles. It is assumed that the solution of the governing physical equations, i.e., the Navier-Stokes equations which may be complemented by chemistry and turbulence models, is done on multiblock grids. This technique is situated between the fully structured approach of classical boundary fitted grids and the fully unstructured tetrahedra grids. A fully structured grid best represents the flow physics, while the unstructured grid gives best geometrical flexibility. The multiblock grid employed is structured within a block, but completely unstructured on the block level. While a completely unstructured grid is not straightforward to parallelize, the above mentioned multiblock grid is inherently parallel, in particular for multiple instruction multiple datastream (MIMD) machines. In this paper guidelines are provided for setting up or modifying an existing sequential code so that a direct parallelization on a massively parallel system is possible. Results are presented for three parallel systems, namely the Intel hypercube, the Ncube hypercube, and the FPS 500 system. Some preliminary results for an 8K CM2 machine will also be mentioned. The code run is the two dimensional grid generation module of Grid, which is a general two dimensional and three dimensional grid generation code for complex geometries. A system of nonlinear Poisson equations is solved. This code is also a good testcase for complex fluid dynamics codes, since the same datastructures are used. All systems provided good speedups, but message passing MIMD systems seem to be best suited for large miltiblock applications.

ParBiBit: Parallel tool for binary biclustering on modern distributed-memory systems

PubMed Central

Expósito, Roberto R.

2018-01-01

Biclustering techniques are gaining attention in the analysis of large-scale datasets as they identify two-dimensional submatrices where both rows and columns are correlated. In this work we present ParBiBit, a parallel tool to accelerate the search of interesting biclusters on binary datasets, which are very popular on different fields such as genetics, marketing or text mining. It is based on the state-of-the-art sequential Java tool BiBit, which has been proved accurate by several studies, especially on scenarios that result on many large biclusters. ParBiBit uses the same methodology as BiBit (grouping the binary information into patterns) and provides the same results. Nevertheless, our tool significantly improves performance thanks to an efficient implementation based on C++11 that includes support for threads and MPI processes in order to exploit the compute capabilities of modern distributed-memory systems, which provide several multicore CPU nodes interconnected through a network. Our performance evaluation with 18 representative input datasets on two different eight-node systems shows that our tool is significantly faster than the original BiBit. Source code in C++ and MPI running on Linux systems as well as a reference manual are available at https://sourceforge.net/projects/parbibit/. PMID:29608567

ParBiBit: Parallel tool for binary biclustering on modern distributed-memory systems.

PubMed

González-Domínguez, Jorge; Expósito, Roberto R

2018-01-01

Biclustering techniques are gaining attention in the analysis of large-scale datasets as they identify two-dimensional submatrices where both rows and columns are correlated. In this work we present ParBiBit, a parallel tool to accelerate the search of interesting biclusters on binary datasets, which are very popular on different fields such as genetics, marketing or text mining. It is based on the state-of-the-art sequential Java tool BiBit, which has been proved accurate by several studies, especially on scenarios that result on many large biclusters. ParBiBit uses the same methodology as BiBit (grouping the binary information into patterns) and provides the same results. Nevertheless, our tool significantly improves performance thanks to an efficient implementation based on C++11 that includes support for threads and MPI processes in order to exploit the compute capabilities of modern distributed-memory systems, which provide several multicore CPU nodes interconnected through a network. Our performance evaluation with 18 representative input datasets on two different eight-node systems shows that our tool is significantly faster than the original BiBit. Source code in C++ and MPI running on Linux systems as well as a reference manual are available at https://sourceforge.net/projects/parbibit/.

Exploiting parallel computing with limited program changes using a network of microcomputers

NASA Technical Reports Server (NTRS)

Rogers, J. L., Jr.; Sobieszczanski-Sobieski, J.

1985-01-01

Network computing and multiprocessor computers are two discernible trends in parallel processing. The computational behavior of an iterative distributed process in which some subtasks are completed later than others because of an imbalance in computational requirements is of significant interest. The effects of asynchronus processing was studied. A small existing program was converted to perform finite element analysis by distributing substructure analysis over a network of four Apple IIe microcomputers connected to a shared disk, simulating a parallel computer. The substructure analysis uses an iterative, fully stressed, structural resizing procedure. A framework of beams divided into three substructures is used as the finite element model. The effects of asynchronous processing on the convergence of the design variables are determined by not resizing particular substructures on various iterations.

A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks.

PubMed

Jiang, Peng; Liu, Shuai; Liu, Jun; Wu, Feng; Zhang, Le

2016-07-14

Most of the existing node depth-adjustment deployment algorithms for underwater wireless sensor networks (UWSNs) just consider how to optimize network coverage and connectivity rate. However, these literatures don't discuss full network connectivity, while optimization of network energy efficiency and network reliability are vital topics for UWSN deployment. Therefore, in this study, a depth-adjustment deployment algorithm based on two-dimensional (2D) convex hull and spanning tree (NDACS) for UWSNs is proposed. First, the proposed algorithm uses the geometric characteristics of a 2D convex hull and empty circle to find the optimal location of a sleep node and activate it, minimizes the network coverage overlaps of the 2D plane, and then increases the coverage rate until the first layer coverage threshold is reached. Second, the sink node acts as a root node of all active nodes on the 2D convex hull and then forms a small spanning tree gradually. Finally, the depth-adjustment strategy based on time marker is used to achieve the three-dimensional overall network deployment. Compared with existing depth-adjustment deployment algorithms, the simulation results show that the NDACS algorithm can maintain full network connectivity with high network coverage rate, as well as improved network average node degree, thus increasing network reliability.

A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks

PubMed Central

Jiang, Peng; Liu, Shuai; Liu, Jun; Wu, Feng; Zhang, Le

2016-01-01

Most of the existing node depth-adjustment deployment algorithms for underwater wireless sensor networks (UWSNs) just consider how to optimize network coverage and connectivity rate. However, these literatures don’t discuss full network connectivity, while optimization of network energy efficiency and network reliability are vital topics for UWSN deployment. Therefore, in this study, a depth-adjustment deployment algorithm based on two-dimensional (2D) convex hull and spanning tree (NDACS) for UWSNs is proposed. First, the proposed algorithm uses the geometric characteristics of a 2D convex hull and empty circle to find the optimal location of a sleep node and activate it, minimizes the network coverage overlaps of the 2D plane, and then increases the coverage rate until the first layer coverage threshold is reached. Second, the sink node acts as a root node of all active nodes on the 2D convex hull and then forms a small spanning tree gradually. Finally, the depth-adjustment strategy based on time marker is used to achieve the three-dimensional overall network deployment. Compared with existing depth-adjustment deployment algorithms, the simulation results show that the NDACS algorithm can maintain full network connectivity with high network coverage rate, as well as improved network average node degree, thus increasing network reliability. PMID:27428970

Parallel Computation and Visualization of Three-dimensional, Time-dependent, Thermal Convective Flows

NASA Technical Reports Server (NTRS)

Wang, P.; Li, P.

1998-01-01

A high-resolution numerical study on parallel systems is reported on three-dimensional, time-dependent, thermal convective flows. A parallel implentation on the finite volume method with a multigrid scheme is discussed, and a parallel visualization systemm is developed on distributed systems for visualizing the flow.

Crystal structure of bis-(μ-3-nitro-benzoato)-κ3O,O':O;κ3O:O,O'-bis-[bis-(3-cyano-pyridine-κN1)(3-nitro-benzoato-κ2O,O')cadmium].

PubMed

Hökelek, Tuncer; Akduran, Nurcan; Özen, Azer; Uğurlu, Güventürk; Necefoğlu, Hacali

2017-03-01

The asymmetric unit of the title compound, [Cd 2 (C 7 H 4 NO 4 ) 4 (C 6 H 4 N 2 ) 4 ], contains one Cd II atom, two 3-nitro-benzoate (NB) anions and two 3-cyano-pyridine (CPy) ligands. The two CPy ligands act as monodentate N(pyridine)-bonding ligands, while the two NB anions act as bidentate ligands through the carboxyl-ate O atoms. The centrosymmetric dinuclear complex is generated by application of inversion symmetry, whereby the Cd II atoms are bridged by the carboxyl-ate O atoms of two symmetry-related NB anions, thus completing the distorted N 2 O 5 penta-gonal-bipyramidal coordination sphere of each Cd II atom. The benzene and pyridine rings are oriented at dihedral angles of 10.02 (7) and 5.76 (9)°, respectively. In the crystal, C-H⋯N hydrogen bonds link the mol-ecules, enclosing R 2 2 (26) ring motifs, in which they are further linked via C-H⋯O hydrogen bonds, resulting in a three-dimensional network. In addition, π-π stacking inter-actions between parallel benzene rings and between parallel pyridine rings of adjacent mol-ecules [shortest centroid-to-centroid distances = 3.885 (1) and 3.712 (1) Å, respectively], as well as a weak C-H⋯π inter-action, may further stabilize the crystal structure.

On adaptive learning rate that guarantees convergence in feedforward networks.

PubMed

Behera, Laxmidhar; Kumar, Swagat; Patnaik, Awhan

2006-09-01

This paper investigates new learning algorithms (LF I and LF II) based on Lyapunov function for the training of feedforward neural networks. It is observed that such algorithms have interesting parallel with the popular backpropagation (BP) algorithm where the fixed learning rate is replaced by an adaptive learning rate computed using convergence theorem based on Lyapunov stability theory. LF II, a modified version of LF I, has been introduced with an aim to avoid local minima. This modification also helps in improving the convergence speed in some cases. Conditions for achieving global minimum for these kind of algorithms have been studied in detail. The performances of the proposed algorithms are compared with BP algorithm and extended Kalman filtering (EKF) on three bench-mark function approximation problems: XOR, 3-bit parity, and 8-3 encoder. The comparisons are made in terms of number of learning iterations and computational time required for convergence. It is found that the proposed algorithms (LF I and II) are much faster in convergence than other two algorithms to attain same accuracy. Finally, the comparison is made on a complex two-dimensional (2-D) Gabor function and effect of adaptive learning rate for faster convergence is verified. In a nutshell, the investigations made in this paper help us better understand the learning procedure of feedforward neural networks in terms of adaptive learning rate, convergence speed, and local minima.

Cell Migration in 1D and 2D Nanofiber Microenvironments.

PubMed

Estabridis, Horacio M; Jana, Aniket; Nain, Amrinder; Odde, David J

2018-03-01

Understanding how cells migrate in fibrous environments is important in wound healing, immune function, and cancer progression. A key question is how fiber orientation and network geometry influence cell movement. Here we describe a quantitative, modeling-based approach toward identifying the mechanisms by which cells migrate in fibrous geometries having well controlled orientation. Specifically, U251 glioblastoma cells were seeded onto non-electrospinning Spinneret based tunable engineering parameters fiber substrates that consist of networks of suspended 400 nm diameter nanofibers. Cells were classified based on the local fiber geometry and cell migration dynamics observed by light microscopy. Cells were found in three distinct geometries: adhering two a single fiber, adhering to two parallel fibers, and adhering to a network of orthogonal fibers. Cells adhering to a single fiber or two parallel fibers can only move in one dimension along the fiber axis, whereas cells on a network of orthogonal fibers can move in two dimensions. We found that cells move faster and more persistently in 1D geometries than in 2D, with cell migration being faster on parallel fibers than on single fibers. To explain these behaviors mechanistically, we simulated cell migration in the three different geometries using a motor-clutch based model for cell traction forces. Using nearly identical parameter sets for each of the three cases, we found that the simulated cells naturally replicated the reduced migration in 2D relative to 1D geometries. In addition, the modestly faster 1D migration on parallel fibers relative to single fibers was captured using a correspondingly modest increase in the number of clutches to reflect increased surface area of adhesion on parallel fibers. Overall, the integrated modeling and experimental analysis shows that cell migration in response to varying fibrous geometries can be explained by a simple mechanical readout of geometry via a motor-clutch mechanism.

The high performance parallel algorithm for Unified Gas-Kinetic Scheme

NASA Astrophysics Data System (ADS)

Li, Shiyi; Li, Qibing; Fu, Song; Xu, Jinxiu

2016-11-01

A high performance parallel algorithm for UGKS is developed to simulate three-dimensional flows internal and external on arbitrary grid system. The physical domain and velocity domain are divided into different blocks and distributed according to the two-dimensional Cartesian topology with intra-communicators in physical domain for data exchange and other intra-communicators in velocity domain for sum reduction to moment integrals. Numerical results of three-dimensional cavity flow and flow past a sphere agree well with the results from the existing studies and validate the applicability of the algorithm. The scalability of the algorithm is tested both on small (1-16) and large (729-5832) scale processors. The tested speed-up ratio is near linear ashind thus the efficiency is around 1, which reveals the good scalability of the present algorithm.

Two-Dimensional Nanoporous Networks Formed by Liquid-to-Solid Transfer of Hydrogen-Bonded Macrocycles Built from DNA Bases.

PubMed

Bilbao, Nerea; Destoop, Iris; De Feyter, Steven; González-Rodríguez, David

2016-01-11

We present an approach that makes use of DNA base pairing to produce hydrogen-bonded macrocycles whose supramolecular structure can be transferred from solution to a solid substrate. A hierarchical assembly process ultimately leads to two-dimensional nanostructured porous networks that are able to host size-complementary guests. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

System and method for representing and manipulating three-dimensional objects on massively parallel architectures

DOEpatents

Karasick, Michael S.; Strip, David R.

1996-01-01

A parallel computing system is described that comprises a plurality of uniquely labeled, parallel processors, each processor capable of modelling a three-dimensional object that includes a plurality of vertices, faces and edges. The system comprises a front-end processor for issuing a modelling command to the parallel processors, relating to a three-dimensional object. Each parallel processor, in response to the command and through the use of its own unique label, creates a directed-edge (d-edge) data structure that uniquely relates an edge of the three-dimensional object to one face of the object. Each d-edge data structure at least includes vertex descriptions of the edge and a description of the one face. As a result, each processor, in response to the modelling command, operates upon a small component of the model and generates results, in parallel with all other processors, without the need for processor-to-processor intercommunication.

Recursive inverse factorization.

PubMed

Rubensson, Emanuel H; Bock, Nicolas; Holmström, Erik; Niklasson, Anders M N

2008-03-14

A recursive algorithm for the inverse factorization S(-1)=ZZ(*) of Hermitian positive definite matrices S is proposed. The inverse factorization is based on iterative refinement [A.M.N. Niklasson, Phys. Rev. B 70, 193102 (2004)] combined with a recursive decomposition of S. As the computational kernel is matrix-matrix multiplication, the algorithm can be parallelized and the computational effort increases linearly with system size for systems with sufficiently sparse matrices. Recent advances in network theory are used to find appropriate recursive decompositions. We show that optimization of the so-called network modularity results in an improved partitioning compared to other approaches. In particular, when the recursive inverse factorization is applied to overlap matrices of irregularly structured three-dimensional molecules.

MPIGeneNet: Parallel Calculation of Gene Co-Expression Networks on Multicore Clusters.

PubMed

Gonzalez-Dominguez, Jorge; Martin, Maria J

2017-10-10

In this work we present MPIGeneNet, a parallel tool that applies Pearson's correlation and Random Matrix Theory to construct gene co-expression networks. It is based on the state-of-the-art sequential tool RMTGeneNet, which provides networks with high robustness and sensitivity at the expenses of relatively long runtimes for large scale input datasets. MPIGeneNet returns the same results as RMTGeneNet but improves the memory management, reduces the I/O cost, and accelerates the two most computationally demanding steps of co-expression network construction by exploiting the compute capabilities of common multicore CPU clusters. Our performance evaluation on two different systems using three typical input datasets shows that MPIGeneNet is significantly faster than RMTGeneNet. As an example, our tool is up to 175.41 times faster on a cluster with eight nodes, each one containing two 12-core Intel Haswell processors. Source code of MPIGeneNet, as well as a reference manual, are available at https://sourceforge.net/projects/mpigenenet/.

Experimental implementation of array-compressed parallel transmission at 7 tesla.

PubMed

Yan, Xinqiang; Cao, Zhipeng; Grissom, William A

2016-06-01

To implement and validate a hardware-based array-compressed parallel transmission (acpTx) system. In array-compressed parallel transmission, a small number of transmit channels drive a larger number of transmit coils, which are connected via an array compression network that implements optimized coil-to-channel combinations. A two channel-to-eight coil array compression network was developed using power splitters, attenuators and phase shifters, and a simulation was performed to investigate the effects of coil coupling on power dissipation in a simplified network. An eight coil transmit array was constructed using induced current elimination decoupling, and the coil and network were validated in benchtop measurements, B1+ mapping scans, and an accelerated spiral excitation experiment. The developed attenuators came within 0.08 dB of the desired attenuations, and reflection coefficients were -22 dB or better. The simulation demonstrated that up to 3× more power was dissipated in the network when coils were poorly isolated (-9.6 dB), versus well-isolated (-31 dB). Compared to split circularly-polarized coil combinations, the additional degrees of freedom provided by the array compression network led to 54% lower squared excitation error in the spiral experiment. Array-compressed parallel transmission was successfully implemented in a hardware system. Further work is needed to develop remote network tuning and to minimize network power dissipation. Magn Reson Med 75:2545-2552, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Chimera states in two-dimensional networks of locally coupled oscillators

NASA Astrophysics Data System (ADS)

Kundu, Srilena; Majhi, Soumen; Bera, Bidesh K.; Ghosh, Dibakar; Lakshmanan, M.

2018-02-01

Chimera state is defined as a mixed type of collective state in which synchronized and desynchronized subpopulations of a network of coupled oscillators coexist and the appearance of such anomalous behavior has strong connection to diverse neuronal developments. Most of the previous studies on chimera states are not extensively done in two-dimensional ensembles of coupled oscillators by taking neuronal systems with nonlinear coupling function into account while such ensembles of oscillators are more realistic from a neurobiological point of view. In this paper, we report the emergence and existence of chimera states by considering locally coupled two-dimensional networks of identical oscillators where each node is interacting through nonlinear coupling function. This is in contrast with the existence of chimera states in two-dimensional nonlocally coupled oscillators with rectangular kernel in the coupling function. We find that the presence of nonlinearity in the coupling function plays a key role to produce chimera states in two-dimensional locally coupled oscillators. We analytically verify explicitly in the case of a network of coupled Stuart-Landau oscillators in two dimensions that the obtained results using Ott-Antonsen approach and our analytical finding very well matches with the numerical results. Next, we consider another type of important nonlinear coupling function which exists in neuronal systems, namely chemical synaptic function, through which the nearest-neighbor (locally coupled) neurons interact with each other. It is shown that such synaptic interacting function promotes the emergence of chimera states in two-dimensional lattices of locally coupled neuronal oscillators. In numerical simulations, we consider two paradigmatic neuronal oscillators, namely Hindmarsh-Rose neuron model and Rulkov map for each node which exhibit bursting dynamics. By associating various spatiotemporal behaviors and snapshots at particular times, we study the chimera states in detail over a large range of coupling parameter. The existence of chimera states is confirmed by instantaneous angular frequency, order parameter and strength of incoherence.

Chimera states in two-dimensional networks of locally coupled oscillators.

PubMed

Kundu, Srilena; Majhi, Soumen; Bera, Bidesh K; Ghosh, Dibakar; Lakshmanan, M

2018-02-01

Chimera state is defined as a mixed type of collective state in which synchronized and desynchronized subpopulations of a network of coupled oscillators coexist and the appearance of such anomalous behavior has strong connection to diverse neuronal developments. Most of the previous studies on chimera states are not extensively done in two-dimensional ensembles of coupled oscillators by taking neuronal systems with nonlinear coupling function into account while such ensembles of oscillators are more realistic from a neurobiological point of view. In this paper, we report the emergence and existence of chimera states by considering locally coupled two-dimensional networks of identical oscillators where each node is interacting through nonlinear coupling function. This is in contrast with the existence of chimera states in two-dimensional nonlocally coupled oscillators with rectangular kernel in the coupling function. We find that the presence of nonlinearity in the coupling function plays a key role to produce chimera states in two-dimensional locally coupled oscillators. We analytically verify explicitly in the case of a network of coupled Stuart-Landau oscillators in two dimensions that the obtained results using Ott-Antonsen approach and our analytical finding very well matches with the numerical results. Next, we consider another type of important nonlinear coupling function which exists in neuronal systems, namely chemical synaptic function, through which the nearest-neighbor (locally coupled) neurons interact with each other. It is shown that such synaptic interacting function promotes the emergence of chimera states in two-dimensional lattices of locally coupled neuronal oscillators. In numerical simulations, we consider two paradigmatic neuronal oscillators, namely Hindmarsh-Rose neuron model and Rulkov map for each node which exhibit bursting dynamics. By associating various spatiotemporal behaviors and snapshots at particular times, we study the chimera states in detail over a large range of coupling parameter. The existence of chimera states is confirmed by instantaneous angular frequency, order parameter and strength of incoherence.

Computer-aided mechanogenesis of skeletal muscle organs from single cells in vitro

NASA Technical Reports Server (NTRS)

Vanderburgh, Herman H.; Swasdison, Somporn; Karlisch, Patricia

1991-01-01

Complex mechanical forces generated in the growing embryo play an important role in organogenesis. Computerized application of similar forces to differentiating skeletal muscle myoblasts in vitro generate three dimensional artificial muscle organs. These organs contain parallel networks of long unbranched myofibers organized into fascicle-like structures. Tendon development is initiated and the muscles are capable of performing directed, functional work. Kinetically engineered organs provide a new method for studying the growth and development of normal and diseased skeletal muscle.

Computer aided mechanogenesis of skeletal muscle organs from single cells in vitro

NASA Technical Reports Server (NTRS)

Vandenburgh, Herman H.; Swasdison, Somporn; Karlisch, Patricia

1990-01-01

Complex mechanical forces generated in the growing embryo play an important role in organogenesis. Computerized application of similar forces to differentiating skeletal muscle myoblasts in vitro generate three dimensional artificial muscle organs. These organs contain parallel networks of long unbranched myofibers organized into fascicle-like structures. Tendon development is initiated and the muscles are capable of performing directed, functional work. Kinetically engineered organs provide a new method for studying the growth and development of normal and diseased skeletal muscle.

catena-Poly[[[4,6-bis­(2-pyrid­yl)-1,3,5-triazin-2-olato]copper(II)]-μ-chlorido

PubMed Central

Cao, Man-Li

2011-01-01

The title compound, [Cu(C13H8N5O)Cl]n, has a chain structure parallel to [100] with Cu2+ cations in a trigonal–bipyramidal coordination environment. The ligand adopts a tridentate tripyridyl coordination mode and a chloride ion acts as a bridge. The chains are linked via weak C—H⋯O and C—H⋯Cl hydrogen bonds into a three-dimensional supra­molecular network. PMID:21754632

Observation of the Chiral and Achiral Hexatic Phases of Self-assembled Micellar polymers

PubMed Central

Pal, Antara; Kamal, Md. Arif; Raghunathan, V. A.

2016-01-01

We report the discovery of a thermodynamically stable line hexatic (N + 6) phase in a three-dimensional (3D) system made up of self-assembled polymer-like micelles of amphiphilic molecules. The experimentally observed phase transition sequence nematic (N)  N + 6  two-dimensional hexagonal (2D-H) is in good agreement with the theoretical predictions. Further, the present study also brings to light the effect of chirality on the N + 6 phase. In the chiral N + 6 phase the bond-orientational order within each “polymer” bundle is found to be twisted about an axis parallel to the average polymer direction. This structure is consistent with the theoretically envisaged Moiré state, thereby providing the first experimental demonstration of the Moiré structure. In addition to confirming the predictions of fundamental theories of two-dimensional melting, these results are relevant in a variety of situations in chemistry, physics and biology, where parallel packing of polymer-like objects are encountered. PMID:27577927

A development of two-dimensional birefringence distribution measurement system with a sampling rate of 1.3 MHz

NASA Astrophysics Data System (ADS)

Onuma, Takashi; Otani, Yukitoshi

2014-03-01

A two-dimensional birefringence distribution measurement system with a sampling rate of 1.3 MHz is proposed. A polarization image sensor is developed as core device of the system. It is composed of a pixelated polarizer array made from photonic crystal and a parallel read out circuit with a multi-channel analog to digital converter specialized for two-dimensional polarization detection. By applying phase shifting algorism with circularly-polarized incident light, birefringence phase difference and azimuthal angle can be measured. The performance of the system is demonstrated experimentally by measuring actual birefringence distribution and polarization device such as Babinet-Soleil compensator.

Electrical Conductivity in Transparent Silver Nanowire Networks: Simulations and Experiments

NASA Astrophysics Data System (ADS)

Sherrott, Michelle; Mutiso, Rose; Rathmell, Aaron; Wiley, Benjamin; Winey, Karen

2012-02-01

We model and experimentally measure the electrical conductivity of two-dimensional networks containing finite, conductive cylinders with aspect ratio ranging from 33 to 333. We have previously used our simulations to explore the effects of cylinder orientation and aspect ratio in three-dimensional composites, and now extend the simulation to consider two-dimensional silver nanowire networks. Preliminary results suggest that increasing the aspect ratio and area fraction of these rods significantly decreases the sheet resistance of the film. For all simulated aspect ratios, this sheet resistance approaches a constant value for high area fractions of rods. This implies that regardless of aspect ratio, there is a limiting minimum sheet resistance that is characteristic of the properties of the nanowires. Experimental data from silver nanowire networks will be incorporated into the simulations to define the contact resistance and corroborate experimentally measured sheet resistances of transparent thin films.

Application of Two-Dimensional AWE Algorithm in Training Multi-Dimensional Neural Network Model

DTIC Science & Technology

2003-07-01

hybrid scheme . the general neural network method (Table 3.1). The training process of the software- ACKNOWLEDGMENT "Neuralmodeler" is shown in Fig. 3.2...engineering. Artificial neural networks (ANNs) have emerged Training a neural network model is the key of as a powerful technique for modeling general neural...coefficients am, the derivatives method of moments (MoM). The variables in the of matrix I have to be generated . A closed form model are frequency

All-optical bidirectional neural interfacing using hybrid multiphoton holographic optogenetic stimulation.

PubMed

Paluch-Siegler, Shir; Mayblum, Tom; Dana, Hod; Brosh, Inbar; Gefen, Inna; Shoham, Shy

2015-07-01

Our understanding of neural information processing could potentially be advanced by combining flexible three-dimensional (3-D) neuroimaging and stimulation. Recent developments in optogenetics suggest that neurophotonic approaches are in principle highly suited for noncontact stimulation of network activity patterns. In particular, two-photon holographic optical neural stimulation (2P-HONS) has emerged as a leading approach for multisite 3-D excitation, and combining it with temporal focusing (TF) further enables axially confined yet spatially extended light patterns. Here, we study key steps toward bidirectional cell-targeted 3-D interfacing by introducing and testing a hybrid new 2P-TF-HONS stimulation path for accurate parallel optogenetic excitation into a recently developed hybrid multiphoton 3-D imaging system. The system is shown to allow targeted all-optical probing of in vitro cortical networks expressing channelrhodopsin-2 using a regeneratively amplified femtosecond laser source tuned to 905 nm. These developments further advance a prospective new tool for studying and achieving distributed control over 3-D neuronal circuits both in vitro and in vivo.

Kolmogorov-Kraichnan Scaling in the Inverse Energy Cascade of Two-Dimensional Plasma Turbulence

NASA Astrophysics Data System (ADS)

Antar, G. Y.

2003-08-01

Turbulence in plasmas that are magnetically confined, such as tokamaks or linear devices, is two dimensional or at least quasi two dimensional due to the strong magnetic field, which leads to extreme elongation of the fluctuations, if any, in the direction parallel to the magnetic field. These plasmas are also compressible fluid flows obeying the compressible Navier-Stokes equations. This Letter presents the first comprehensive scaling of the structure functions of the density and velocity fields up to 10th order in the PISCES linear plasma device and up to 6th order in the Mega-Ampère Spherical Tokamak (MAST). In the two devices, it is found that the scaling of the turbulent fields is in good agreement with the prediction of the Kolmogorov-Kraichnan theory for two-dimensional turbulence in the energy cascade subrange.

Dielectric monitoring of carbon nanotube network formation in curing thermosetting nanocomposites

NASA Astrophysics Data System (ADS)

Battisti, A.; Skordos, A. A.; Partridge, I. K.

2009-08-01

This paper focuses on monitoring of carbon nanotube (CNT) network development during the cure of unsaturated polyester nanocomposites by means of electrical impedance spectroscopy. A phenomenological model of the dielectric response is developed using equivalent circuit analysis. The model comprises two parallel RC elements connected in series, each of them giving rise to a semicircular arc in impedance complex plane plots. An established inverse modelling methodology is utilized for the estimation of the parameters of the corresponding equivalent circuit. This allows a quantification of the evolution of two separate processes corresponding to the two parallel RC elements. The high frequency process, which is attributed to CNT aggregates, shows a monotonic decrease in characteristic time during the cure. In contrast, the low frequency process, which corresponds to inter-aggregate phenomena, shows a more complex behaviour explained by the interplay between conductive network development and the cross-linking of the polymer.

Neural Network Machine Learning and Dimension Reduction for Data Visualization

NASA Technical Reports Server (NTRS)

Liles, Charles A.

2014-01-01

Neural network machine learning in computer science is a continuously developing field of study. Although neural network models have been developed which can accurately predict a numeric value or nominal classification, a general purpose method for constructing neural network architecture has yet to be developed. Computer scientists are often forced to rely on a trial-and-error process of developing and improving accurate neural network models. In many cases, models are constructed from a large number of input parameters. Understanding which input parameters have the greatest impact on the prediction of the model is often difficult to surmise, especially when the number of input variables is very high. This challenge is often labeled the "curse of dimensionality" in scientific fields. However, techniques exist for reducing the dimensionality of problems to just two dimensions. Once a problem's dimensions have been mapped to two dimensions, it can be easily plotted and understood by humans. The ability to visualize a multi-dimensional dataset can provide a means of identifying which input variables have the highest effect on determining a nominal or numeric output. Identifying these variables can provide a better means of training neural network models; models can be more easily and quickly trained using only input variables which appear to affect the outcome variable. The purpose of this project is to explore varying means of training neural networks and to utilize dimensional reduction for visualizing and understanding complex datasets.

Spatial structure of ion beams in an expanding plasma

NASA Astrophysics Data System (ADS)

Aguirre, E. M.; Scime, E. E.; Thompson, D. S.; Good, T. N.

2017-12-01

We report spatially resolved perpendicular and parallel, to the magnetic field, ion velocity distribution function (IVDF) measurements in an expanding argon helicon plasma. The parallel IVDFs, obtained through laser induced fluorescence (LIF), show an ion beam with v ≈ 8000 m/s flowing downstream and confined to the center of the discharge. The ion beam is measurable for tens of centimeters along the expansion axis before the LIF signal fades, likely a result of metastable quenching of the beam ions. The parallel ion beam velocity slows in agreement with expectations for the measured parallel electric field. The perpendicular IVDFs show an ion population with a radially outward flow that increases with distance from the plasma axis. Structures aligned to the expanding magnetic field appear in the DC electric field, the electron temperature, and the plasma density in the plasma plume. These measurements demonstrate that at least two-dimensional and perhaps fully three-dimensional models are needed to accurately describe the spontaneous acceleration of ion beams in expanding plasmas.

First experiments probing the collision of parallel magnetic fields using laser-produced plasmas

DOE PAGES

Rosenberg, M. J.; Li, C. K.; Fox, W.; ...

2015-04-08

Novel experiments to study the strongly-driven collision of parallel magnetic fields in β~10, laser-produced plasmas have been conducted using monoenergetic proton radiography. These experiments were designed to probe the process of magnetic flux pileup, which has been identified in prior laser-plasma experiments as a key physical mechanism in the reconnection of anti-parallel magnetic fields when the reconnection inflow is dominated by strong plasma flows. In the present experiments using colliding plasmas carrying parallel magnetic fields, the magnetic flux is found to be conserved and slightly compressed in the collision region. Two-dimensional (2D) particle-in-cell (PIC) simulations predict a stronger flux compressionmore » and amplification of the magnetic field strength, and this discrepancy is attributed to the three-dimensional (3D) collision geometry. Future experiments may drive a stronger collision and further explore flux pileup in the context of the strongly-driven interaction of magnetic fields.« less

Parallel asynchronous systems and image processing algorithms

NASA Technical Reports Server (NTRS)

Coon, D. D.; Perera, A. G. U.

1989-01-01

A new hardware approach to implementation of image processing algorithms is described. The approach is based on silicon devices which would permit an independent analog processing channel to be dedicated to evey pixel. A laminar architecture consisting of a stack of planar arrays of the device would form a two-dimensional array processor with a 2-D array of inputs located directly behind a focal plane detector array. A 2-D image data stream would propagate in neuronlike asynchronous pulse coded form through the laminar processor. Such systems would integrate image acquisition and image processing. Acquisition and processing would be performed concurrently as in natural vision systems. The research is aimed at implementation of algorithms, such as the intensity dependent summation algorithm and pyramid processing structures, which are motivated by the operation of natural vision systems. Implementation of natural vision algorithms would benefit from the use of neuronlike information coding and the laminar, 2-D parallel, vision system type architecture. Besides providing a neural network framework for implementation of natural vision algorithms, a 2-D parallel approach could eliminate the serial bottleneck of conventional processing systems. Conversion to serial format would occur only after raw intensity data has been substantially processed. An interesting challenge arises from the fact that the mathematical formulation of natural vision algorithms does not specify the means of implementation, so that hardware implementation poses intriguing questions involving vision science.

2D-HB-Network at the air-water interface: A structural and dynamical characterization by means of ab initio and classical molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Pezzotti, Simone; Serva, Alessandra; Gaigeot, Marie-Pierre

2018-05-01

Following our previous work where the existence of a special 2-Dimensional H-Bond (2D-HB)-Network was revealed at the air-water interface [S. Pezzotti et al., J. Phys. Chem. Lett. 8, 3133 (2017)], we provide here a full structural and dynamical characterization of this specific arrangement by means of both Density Functional Theory based and Force Field based molecular dynamics simulations. We show in particular that water at the interface with air reconstructs to maximize H-Bonds formed between interfacial molecules, which leads to the formation of an extended and non-interrupted 2-Dimensional H-Bond structure involving on average ˜90% of water molecules at the interface. We also show that the existence of such an extended structure, composed of H-Bonds all oriented parallel to the surface, constrains the reorientional dynamics of water that is hence slower at the interface than in the bulk. The structure and dynamics of the 2D-HB-Network provide new elements to possibly rationalize several specific properties of the air-water interface, such as water surface tension, anisotropic reorientation of interfacial water under an external field, and proton hopping.

Percolation of spatially constraint networks

NASA Astrophysics Data System (ADS)

Li, Daqing; Li, Guanliang; Kosmidis, Kosmas; Stanley, H. E.; Bunde, Armin; Havlin, Shlomo

2011-03-01

We study how spatial constraints are reflected in the percolation properties of networks embedded in one-dimensional chains and two-dimensional lattices. We assume long-range connections between sites on the lattice where two sites at distance r are chosen to be linked with probability p(r)~r-δ. Similar distributions have been found in spatially embedded real networks such as social and airline networks. We find that for networks embedded in two dimensions, with 2<δ<4, the percolation properties show new intermediate behavior different from mean field, with critical exponents that depend on δ. For δ<2, the percolation transition belongs to the universality class of percolation in Erdös-Rényi networks (mean field), while for δ>4 it belongs to the universality class of percolation in regular lattices. For networks embedded in one dimension, we find that, for δ<1, the percolation transition is mean field. For 1<δ<2, the critical exponents depend on δ, while for δ>2 there is no percolation transition as in regular linear chains.

Brain plasticity and functionality explored by nonlinear optical microscopy

NASA Astrophysics Data System (ADS)

Sacconi, L.; Allegra, L.; Buffelli, M.; Cesare, P.; D'Angelo, E.; Gandolfi, D.; Grasselli, G.; Lotti, J.; Mapelli, J.; Strata, P.; Pavone, F. S.

2010-02-01

In combination with fluorescent protein (XFP) expression techniques, two-photon microscopy has become an indispensable tool to image cortical plasticity in living mice. In parallel to its application in imaging, multi-photon absorption has also been used as a tool for the dissection of single neurites with submicrometric precision without causing any visible collateral damage to the surrounding neuronal structures. In this work, multi-photon nanosurgery is applied to dissect single climbing fibers expressing GFP in the cerebellar cortex. The morphological consequences are then characterized with time lapse 3-dimensional two-photon imaging over a period of minutes to days after the procedure. Preliminary investigations show that the laser induced fiber dissection recalls a regenerative process in the fiber itself over a period of days. These results show the possibility of this innovative technique to investigate regenerative processes in adult brain. In parallel with imaging and manipulation technique, non-linear microscopy offers the opportunity to optically record electrical activity in intact neuronal networks. In this work, we combined the advantages of second-harmonic generation (SHG) with a random access (RA) excitation scheme to realize a new microscope (RASH) capable of optically recording fast membrane potential events occurring in a wide-field of view. The RASH microscope, in combination with bulk loading of tissue with FM4-64 dye, was used to simultaneously record electrical activity from clusters of Purkinje cells in acute cerebellar slices. Complex spikes, both synchronous and asynchronous, were optically recorded simultaneously across a given population of neurons. Spontaneous electrical activity was also monitored simultaneously in pairs of neurons, where action potentials were recorded without averaging across trials. These results show the strength of this technique in describing the temporal dynamics of neuronal assemblies, opening promising perspectives in understanding the computations of neuronal networks.

Three is much more than two in coarsening dynamics of cyclic competitions

NASA Astrophysics Data System (ADS)

Mitarai, Namiko; Gunnarson, Ivar; Pedersen, Buster Niels; Rosiek, Christian Anker; Sneppen, Kim

2016-04-01

The classical game of rock-paper-scissors has inspired experiments and spatial model systems that address the robustness of biological diversity. In particular, the game nicely illustrates that cyclic interactions allow multiple strategies to coexist for long-time intervals. When formulated in terms of a one-dimensional cellular automata, the spatial distribution of strategies exhibits coarsening with algebraically growing domain size over time, while the two-dimensional version allows domains to break and thereby opens the possibility for long-time coexistence. We consider a quasi-one-dimensional implementation of the cyclic competition, and study the long-term dynamics as a function of rare invasions between parallel linear ecosystems. We find that increasing the complexity from two to three parallel subsystems allows a transition from complete coarsening to an active steady state where the domain size stays finite. We further find that this transition happens irrespective of whether the update is done in parallel for all sites simultaneously or done randomly in sequential order. In both cases, the active state is characterized by localized bursts of dislocations, followed by longer periods of coarsening. In the case of the parallel dynamics, we find that there is another phase transition between the active steady state and the coarsening state within the three-line system when the invasion rate between the subsystems is varied. We identify the critical parameter for this transition and show that the density of active boundaries has critical exponents that are consistent with the directed percolation universality class. On the other hand, numerical simulations with the random sequential dynamics suggest that the system may exhibit an active steady state as long as the invasion rate is finite.

High-Performance Parallel Analysis of Coupled Problems for Aircraft Propulsion

NASA Technical Reports Server (NTRS)

Felippa, C. A.; Farhat, C.; Park, K. C.; Gumaste, U.; Chen, P.-S.; Lesoinne, M.; Stern, P.

1996-01-01

This research program dealt with the application of high-performance computing methods to the numerical simulation of complete jet engines. The program was initiated in January 1993 by applying two-dimensional parallel aeroelastic codes to the interior gas flow problem of a bypass jet engine. The fluid mesh generation, domain decomposition and solution capabilities were successfully tested. Attention was then focused on methodology for the partitioned analysis of the interaction of the gas flow with a flexible structure and with the fluid mesh motion driven by these structural displacements. The latter is treated by a ALE technique that models the fluid mesh motion as that of a fictitious mechanical network laid along the edges of near-field fluid elements. New partitioned analysis procedures to treat this coupled three-component problem were developed during 1994 and 1995. These procedures involved delayed corrections and subcycling, and have been successfully tested on several massively parallel computers, including the iPSC-860, Paragon XP/S and the IBM SP2. For the global steady-state axisymmetric analysis of a complete engine we have decided to use the NASA-sponsored ENG10 program, which uses a regular FV-multiblock-grid discretization in conjunction with circumferential averaging to include effects of blade forces, loss, combustor heat addition, blockage, bleeds and convective mixing. A load-balancing preprocessor tor parallel versions of ENG10 was developed. During 1995 and 1996 we developed the capability tor the first full 3D aeroelastic simulation of a multirow engine stage. This capability was tested on the IBM SP2 parallel supercomputer at NASA Ames. Benchmark results were presented at the 1196 Computational Aeroscience meeting.

Parallel Computing for Probabilistic Response Analysis of High Temperature Composites

NASA Technical Reports Server (NTRS)

Sues, R. H.; Lua, Y. J.; Smith, M. D.

1994-01-01

The objective of this Phase I research was to establish the required software and hardware strategies to achieve large scale parallelism in solving PCM problems. To meet this objective, several investigations were conducted. First, we identified the multiple levels of parallelism in PCM and the computational strategies to exploit these parallelisms. Next, several software and hardware efficiency investigations were conducted. These involved the use of three different parallel programming paradigms and solution of two example problems on both a shared-memory multiprocessor and a distributed-memory network of workstations.

High-speed parallel implementation of a modified PBR algorithm on DSP-based EH topology

NASA Astrophysics Data System (ADS)

Rajan, K.; Patnaik, L. M.; Ramakrishna, J.

1997-08-01

Algebraic Reconstruction Technique (ART) is an age-old method used for solving the problem of three-dimensional (3-D) reconstruction from projections in electron microscopy and radiology. In medical applications, direct 3-D reconstruction is at the forefront of investigation. The simultaneous iterative reconstruction technique (SIRT) is an ART-type algorithm with the potential of generating in a few iterations tomographic images of a quality comparable to that of convolution backprojection (CBP) methods. Pixel-based reconstruction (PBR) is similar to SIRT reconstruction, and it has been shown that PBR algorithms give better quality pictures compared to those produced by SIRT algorithms. In this work, we propose a few modifications to the PBR algorithms. The modified algorithms are shown to give better quality pictures compared to PBR algorithms. The PBR algorithm and the modified PBR algorithms are highly compute intensive, Not many attempts have been made to reconstruct objects in the true 3-D sense because of the high computational overhead. In this study, we have developed parallel two-dimensional (2-D) and 3-D reconstruction algorithms based on modified PBR. We attempt to solve the two problems encountered by the PBR and modified PBR algorithms, i.e., the long computational time and the large memory requirements, by parallelizing the algorithm on a multiprocessor system. We investigate the possible task and data partitioning schemes by exploiting the potential parallelism in the PBR algorithm subject to minimizing the memory requirement. We have implemented an extended hypercube (EH) architecture for the high-speed execution of the 3-D reconstruction algorithm using the commercially available fast floating point digital signal processor (DSP) chips as the processing elements (PEs) and dual-port random access memories (DPR) as channels between the PEs. We discuss and compare the performances of the PBR algorithm on an IBM 6000 RISC workstation, on a Silicon Graphics Indigo 2 workstation, and on an EH system. The results show that an EH(3,1) using DSP chips as PEs executes the modified PBR algorithm about 100 times faster than an LBM 6000 RISC workstation. We have executed the algorithms on a 4-node IBM SP2 parallel computer. The results show that execution time of the algorithm on an EH(3,1) is better than that of a 4-node IBM SP2 system. The speed-up of an EH(3,1) system with eight PEs and one network controller is approximately 7.85.

Energy efficiency analysis of two-sided feed scheme of DC traction network with high asymmetry of feeders parameters

NASA Astrophysics Data System (ADS)

Abramov, E. Y.; Sopov, V. I.

2017-10-01

In a given research using the example of traction network area with high asymmetry of power supply parameters, the sequence of comparative assessment of power losses in DC traction network with parallel and traditional separated operating modes of traction substation feeders was shown. Experimental measurements were carried out under these modes of operation. The calculation data results based on statistic processing showed the power losses decrease in contact network and the increase in feeders. The changes proved to be critical ones and this demonstrates the significance of potential effects when converting traction network areas into parallel feeder operation. An analytical method of calculation the average power losses for different feed schemes of the traction network was developed. On its basis, the dependences of the relative losses were obtained by varying the difference in feeder voltages. The calculation results showed unreasonableness transition to a two-sided feed scheme for the considered traction network area. A larger reduction in the total power loss can be obtained with a smaller difference of the feeders’ resistance and / or a more symmetrical sectioning scheme of contact network.

Ca(5)Zr(3)F(22).

PubMed

Oudahmane, Abdelghani; El-Ghozzi, Malika; Avignant, Daniel

2012-04-01

Single crystals of Ca(5)Zr(3)F(22), penta-calcium trizirconium docosafluoride, were obtained unexpectedly by solid-state reaction between CaF(2) and ZrF(4) in the presence of AgF. The structure of the title compound is isotypic with that of Sr(5)Zr(3)F(22) and can be described as being composed of layers with composition [Zr(3)F(20)](8-) made up from two different [ZrF(8)](4-) square anti-prisms (one with site symmetry 2) by corner-sharing. The layers extending parallel to the (001) plane are further linked by Ca(2+) cations, forming a three-dimensional network. Amongst the four crystallographically different Ca(2+) ions, three are located on twofold rotation axes. The Ca(2+) ions exhibit coordination numbers ranging from 8 to 12, depending on the cut off, with very distorted fluorine environments. Two of the Ca(2+) ions occupy inter-stices between the layers whereas the other two are located in void spaces of the [Zr(3)F(20)](8-) layer and alternate with the two Zr atoms along [010]. The crystal under investigation was an inversion twin.

Quasi-2D Unsteady Flow Solver Module for Rocket Engine and Propulsion System Simulations

DTIC Science & Technology

2006-06-14

Conference, Sacramento, CA, 9-12 July 2006. 14. ABSTRACT A new quasi-two-dimensional procedure is presented for the transient solution of real-fluid flows...solution procedures is being developed in parallel to provide verification test cases. The solution procedure for both codes is coupled with a state-of...Davis, Davis, CA, 95616 A new quasi-two-dimensional procedure is presented for the transient solution of real- fluid flows in lines and volumes

Parallel solution of sparse one-dimensional dynamic programming problems

NASA Technical Reports Server (NTRS)

Nicol, David M.

1989-01-01

Parallel computation offers the potential for quickly solving large computational problems. However, it is often a non-trivial task to effectively use parallel computers. Solution methods must sometimes be reformulated to exploit parallelism; the reformulations are often more complex than their slower serial counterparts. We illustrate these points by studying the parallelization of sparse one-dimensional dynamic programming problems, those which do not obviously admit substantial parallelization. We propose a new method for parallelizing such problems, develop analytic models which help us to identify problems which parallelize well, and compare the performance of our algorithm with existing algorithms on a multiprocessor.

A Two Colorable Fourth Order Compact Difference Scheme and Parallel Iterative Solution of the 3D Convection Diffusion Equation

NASA Technical Reports Server (NTRS)

Zhang, Jun; Ge, Lixin; Kouatchou, Jules

2000-01-01

A new fourth order compact difference scheme for the three dimensional convection diffusion equation with variable coefficients is presented. The novelty of this new difference scheme is that it Only requires 15 grid points and that it can be decoupled with two colors. The entire computational grid can be updated in two parallel subsweeps with the Gauss-Seidel type iterative method. This is compared with the known 19 point fourth order compact differenCe scheme which requires four colors to decouple the computational grid. Numerical results, with multigrid methods implemented on a shared memory parallel computer, are presented to compare the 15 point and the 19 point fourth order compact schemes.

Modeling evolution of crosstalk in noisy signal transduction networks

NASA Astrophysics Data System (ADS)

Tareen, Ammar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

2018-02-01

Signal transduction networks can form highly interconnected systems within cells due to crosstalk between constituent pathways. To better understand the evolutionary design principles underlying such networks, we study the evolution of crosstalk for two parallel signaling pathways that arise via gene duplication. We use a sequence-based evolutionary algorithm and evolve the network based on two physically motivated fitness functions related to information transmission. We find that one fitness function leads to a high degree of crosstalk while the other leads to pathway specificity. Our results offer insights on the relationship between network architecture and information transmission for noisy biomolecular networks.

High Performance Parallel Analysis of Coupled Problems for Aircraft Propulsion

NASA Technical Reports Server (NTRS)

Felippa, C. A.; Farhat, C.; Lanteri, S.; Maman, N.; Piperno, S.; Gumaste, U.

1994-01-01

In order to predict the dynamic response of a flexible structure in a fluid flow, the equations of motion of the structure and the fluid must be solved simultaneously. In this paper, we present several partitioned procedures for time-integrating this focus coupled problem and discuss their merits in terms of accuracy, stability, heterogeneous computing, I/O transfers, subcycling, and parallel processing. All theoretical results are derived for a one-dimensional piston model problem with a compressible flow, because the complete three-dimensional aeroelastic problem is difficult to analyze mathematically. However, the insight gained from the analysis of the coupled piston problem and the conclusions drawn from its numerical investigation are confirmed with the numerical simulation of the two-dimensional transient aeroelastic response of a flexible panel in a transonic nonlinear Euler flow regime.

Approach and separation of quantum vortices with balanced cores

NASA Astrophysics Data System (ADS)

Kerr, Robert M.; Rorai, C.; Skipper, J.; Sreenivasan, K. R.

2014-11-01

Using two innovations, smooth but different, scaling laws for the reconnection of pairs of initially orthogonal and anti-parallel quantum vortices are obtained using the three-dimensional Gross-Pitaevskii equations. For the anti-parallel case, the scaling laws just before and after reconnection obey the dimensional δ ~ | t - tr| 1 / 2 prediction with temporal symmetry about the reconnection time tr and physical space symmetry about xr, the mid-point between the vortices, with extensions forming the edges of an equilateral pyramid. For all of the orthogonal cases, before reconnection δin ~(t -tr) 1 / 3 and after reconnection δout ~(tr - t) 2 / 3 , which are respectively slower and faster than the dimensional prediction. In these cases, the reconnection takes place in a plane defined by the directions of the curvature and vorticity. Robert.Kerr@warwick.ac.uk.

The UPSF code: a metaprogramming-based high-performance automatically parallelized plasma simulation framework

NASA Astrophysics Data System (ADS)

Gao, Xiatian; Wang, Xiaogang; Jiang, Binhao

2017-10-01

UPSF (Universal Plasma Simulation Framework) is a new plasma simulation code designed for maximum flexibility by using edge-cutting techniques supported by C++17 standard. Through use of metaprogramming technique, UPSF provides arbitrary dimensional data structures and methods to support various kinds of plasma simulation models, like, Vlasov, particle in cell (PIC), fluid, Fokker-Planck, and their variants and hybrid methods. Through C++ metaprogramming technique, a single code can be used to arbitrary dimensional systems with no loss of performance. UPSF can also automatically parallelize the distributed data structure and accelerate matrix and tensor operations by BLAS. A three-dimensional particle in cell code is developed based on UPSF. Two test cases, Landau damping and Weibel instability for electrostatic and electromagnetic situation respectively, are presented to show the validation and performance of the UPSF code.

Analysis of multigrid methods on massively parallel computers: Architectural implications

NASA Technical Reports Server (NTRS)

Matheson, Lesley R.; Tarjan, Robert E.

1993-01-01

We study the potential performance of multigrid algorithms running on massively parallel computers with the intent of discovering whether presently envisioned machines will provide an efficient platform for such algorithms. We consider the domain parallel version of the standard V cycle algorithm on model problems, discretized using finite difference techniques in two and three dimensions on block structured grids of size 10(exp 6) and 10(exp 9), respectively. Our models of parallel computation were developed to reflect the computing characteristics of the current generation of massively parallel multicomputers. These models are based on an interconnection network of 256 to 16,384 message passing, 'workstation size' processors executing in an SPMD mode. The first model accomplishes interprocessor communications through a multistage permutation network. The communication cost is a logarithmic function which is similar to the costs in a variety of different topologies. The second model allows single stage communication costs only. Both models were designed with information provided by machine developers and utilize implementation derived parameters. With the medium grain parallelism of the current generation and the high fixed cost of an interprocessor communication, our analysis suggests an efficient implementation requires the machine to support the efficient transmission of long messages, (up to 1000 words) or the high initiation cost of a communication must be significantly reduced through an alternative optimization technique. Furthermore, with variable length message capability, our analysis suggests the low diameter multistage networks provide little or no advantage over a simple single stage communications network.

Linear Vector Quantisation and Uniform Circular Arrays based decoupled two-dimensional angle of arrival estimation

NASA Astrophysics Data System (ADS)

Ndaw, Joseph D.; Faye, Andre; Maïga, Amadou S.

2017-05-01

Artificial neural networks (ANN)-based models are efficient ways of source localisation. However very large training sets are needed to precisely estimate two-dimensional Direction of arrival (2D-DOA) with ANN models. In this paper we present a fast artificial neural network approach for 2D-DOA estimation with reduced training sets sizes. We exploit the symmetry properties of Uniform Circular Arrays (UCA) to build two different datasets for elevation and azimuth angles. Linear Vector Quantisation (LVQ) neural networks are then sequentially trained on each dataset to separately estimate elevation and azimuth angles. A multilevel training process is applied to further reduce the training sets sizes.

System and method for representing and manipulating three-dimensional objects on massively parallel architectures

DOEpatents

Karasick, M.S.; Strip, D.R.

1996-01-30

A parallel computing system is described that comprises a plurality of uniquely labeled, parallel processors, each processor capable of modeling a three-dimensional object that includes a plurality of vertices, faces and edges. The system comprises a front-end processor for issuing a modeling command to the parallel processors, relating to a three-dimensional object. Each parallel processor, in response to the command and through the use of its own unique label, creates a directed-edge (d-edge) data structure that uniquely relates an edge of the three-dimensional object to one face of the object. Each d-edge data structure at least includes vertex descriptions of the edge and a description of the one face. As a result, each processor, in response to the modeling command, operates upon a small component of the model and generates results, in parallel with all other processors, without the need for processor-to-processor intercommunication. 8 figs.

Guidance of dorsal root ganglion neurites and Schwann cells by isolated Schwann cell topography on poly(dimethyl siloxane) conduits and films

NASA Astrophysics Data System (ADS)

Richardson, J. A.; Rementer, C. W.; Bruder, Jan M.; Hoffman-Kim, D.

2011-08-01

Biomimetic replicas of cellular topography have been utilized to direct neurite outgrowth. Here, we cultured postnatal rat dorsal root ganglion (DRG) explants in the presence of Schwann cell (SC) topography to determine the influence of SC topography on neurite outgrowth. Four distinct poly(dimethyl siloxane) conduits were fabricated within which DRG explants were cultured. To determine the contribution of SC topographical features to neurite guidance, the extent of neurite outgrowth into unpatterned conduits, conduits with randomly oriented SC replicas, and conduits with SC replicas parallel or perpendicular to the conduit long axis was measured. Neurite directionality and outgrowth from DRG were also quantified on two-dimensional SC replicas with orientations corresponding to the four conduit conditions. Additionally, live SC migration and neurite extension from DRG on SC replicas were examined as a first step toward quantification of the interactions between live SC and navigating neurites on SC replicas. DRG neurite outgrowth and morphology within conduits and on two-dimensional SC replicas were directed by the underlying SC topographical features. Maximal neurite outgrowth and alignment to the underlying features were observed into parallel conduits and on parallel two-dimensional substrates, whereas the least extent of outgrowth was observed into perpendicular conduits and on perpendicular two-dimensional replica conditions. Additionally, neurites on perpendicular conditions turned to extend along the direction of underlying SC topography. Neurite outgrowth exceeded SC migration in the direction of the underlying anisotropic SC replica after two days in culture. This finding confirms the critical role that SC have in guiding neurite outgrowth and suggests that the mechanism of neurite alignment to SC replicas depends on direct contact with cellular topography. These results suggest that SC topographical replicas may be used to direct and optimize neurite alignment, and emphasize the importance of SC features in neurite guidance.

NASA Tech Briefs, February 2008

NASA Technical Reports Server (NTRS)

2008-01-01

Topics discussed include: Optical Measurement of Mass Flow of a Two-Phase Fluid; Selectable-Tip Corrosion-Testing Electrochemical Cell; Piezoelectric Bolt Breakers and Bolt Fatigue Testers; Improved Measurement of B(sub 22) of Macromolecules in a Flow Cell; Measurements by a Vector Network Analyzer at 325 to 508 GHz; Using Light to Treat Mucositis and Help Wounds Heal; Increasing Discharge Capacities of Li-(CF)(sub n) Cells; Dot-in-Well Quantum-Dot Infrared Photodetectors; Integrated Microbatteries for Implantable Medical Devices; Oxidation Behavior of Carbon Fiber-Reinforced Composites; GIDEP Batching Tool; Generic Spacecraft Model for Real-Time Simulation; Parallel-Processing Software for Creating Mosaic Images; Software for Verifying Image-Correlation Tie Points; Flexcam Image Capture Viewing and Spot Tracking; Low-Pt-Content Anode Catalyst for Direct Methanol Fuel Cells; Graphite/Cyanate Ester Face Sheets for Adaptive Optics; Atomized BaF2-CaF7 for Better-Flowing Plasma-Spray Feedstock; Nanophase Nickel-Zirconium Alloys for Fuel Cells; Vacuum Packaging of MEMS With Multiple Internal Seal Rings; Compact Two-Dimensional Spectrometer Optics; and Fault-Tolerant Coding for State Machines.

A three-dimensional carbon nano-network for high performance lithium ion batteries

DOE PAGES

Tian, Miao; Wang, Wei; Liu, Yang; ...

2014-11-20

Three-dimensional (3D) network structure has been envisioned as a superior architecture for lithium ion battery (LIB) electrodes, which enhances both ion and electron transport to significantly improve battery performance. Herein, a 3D carbon nano-network is fabricated through chemical vapor deposition of carbon on a scalably manufactured 3D porous anodic alumina (PAA) template. As a demonstration on the applicability of 3D carbon nano-network for LIB electrodes, the low conductivity active material, TiO 2, is then uniformly coated on the 3D carbon nano-network using atomic layer deposition. High power performance is demonstrated in the 3D C/TiO 2 electrodes, where the parallel tubesmore » and gaps in the 3D carbon nano-network facilitates fast Li ion transport. A large areal capacity of ~0.37 mAh·cm –2 is achieved due to the large TiO 2 mass loading in the 60 µm-thick 3D C/TiO 2 electrodes. At a test rate of C/5, the 3D C/TiO 2 electrode with 18 nm-thick TiO 2 delivers a high gravimetric capacity of ~240 mAh g –1, calculated with the mass of the whole electrode. A long cycle life of over 1000 cycles with a capacity retention of 91% is demonstrated at 1C. In this study, the effects of the electrical conductivity of carbon nano-network, ion diffusion, and the electrolyte permeability on the rate performance of these 3D C/TiO 2 electrodes are systematically studied.« less

cellGPU: Massively parallel simulations of dynamic vertex models

NASA Astrophysics Data System (ADS)

Sussman, Daniel M.

2017-10-01

Vertex models represent confluent tissue by polygonal or polyhedral tilings of space, with the individual cells interacting via force laws that depend on both the geometry of the cells and the topology of the tessellation. This dependence on the connectivity of the cellular network introduces several complications to performing molecular-dynamics-like simulations of vertex models, and in particular makes parallelizing the simulations difficult. cellGPU addresses this difficulty and lays the foundation for massively parallelized, GPU-based simulations of these models. This article discusses its implementation for a pair of two-dimensional models, and compares the typical performance that can be expected between running cellGPU entirely on the CPU versus its performance when running on a range of commercial and server-grade graphics cards. By implementing the calculation of topological changes and forces on cells in a highly parallelizable fashion, cellGPU enables researchers to simulate time- and length-scales previously inaccessible via existing single-threaded CPU implementations. Program Files doi:http://dx.doi.org/10.17632/6j2cj29t3r.1 Licensing provisions: MIT Programming language: CUDA/C++ Nature of problem: Simulations of off-lattice "vertex models" of cells, in which the interaction forces depend on both the geometry and the topology of the cellular aggregate. Solution method: Highly parallelized GPU-accelerated dynamical simulations in which the force calculations and the topological features can be handled on either the CPU or GPU. Additional comments: The code is hosted at https://gitlab.com/dmsussman/cellGPU, with documentation additionally maintained at http://dmsussman.gitlab.io/cellGPUdocumentation

Nonlinear dimensionality reduction of electroencephalogram (EEG) for Brain Computer interfaces.

PubMed

Teli, Mohammad Nayeem; Anderson, Charles

2009-01-01

Patterns in electroencephalogram (EEG) signals are analyzed for a Brain Computer Interface (BCI). An important aspect of this analysis is the work on transformations of high dimensional EEG data to low dimensional spaces in which we can classify the data according to mental tasks being performed. In this research we investigate how a Neural Network (NN) in an auto-encoder with bottleneck configuration can find such a transformation. We implemented two approximate second-order methods to optimize the weights of these networks, because the more common first-order methods are very slow to converge for networks like these with more than three layers of computational units. The resulting non-linear projections of time embedded EEG signals show interesting separations that are related to tasks. The bottleneck networks do indeed discover nonlinear transformations to low-dimensional spaces that capture much of the information present in EEG signals. However, the resulting low-dimensional representations do not improve classification rates beyond what is possible using Quadratic Discriminant Analysis (QDA) on the original time-lagged EEG.

Domain decomposition methods in aerodynamics

NASA Technical Reports Server (NTRS)

Venkatakrishnan, V.; Saltz, Joel

1990-01-01

Compressible Euler equations are solved for two-dimensional problems by a preconditioned conjugate gradient-like technique. An approximate Riemann solver is used to compute the numerical fluxes to second order accuracy in space. Two ways to achieve parallelism are tested, one which makes use of parallelism inherent in triangular solves and the other which employs domain decomposition techniques. The vectorization/parallelism in triangular solves is realized by the use of a recording technique called wavefront ordering. This process involves the interpretation of the triangular matrix as a directed graph and the analysis of the data dependencies. It is noted that the factorization can also be done in parallel with the wave front ordering. The performances of two ways of partitioning the domain, strips and slabs, are compared. Results on Cray YMP are reported for an inviscid transonic test case. The performances of linear algebra kernels are also reported.

The Use of Modelling for Improving Pupils' Learning about Cells.

ERIC Educational Resources Information Center

Tregidgo, David; Ratcliffe, Mary

2000-01-01

Outlines the use of modeling in science teaching. Describes a study in which two parallel groups of year seven pupils modeled concepts of cell structure and function as they produced two- or three-dimensional representations of plant and animal cells. (Author/CCM)

Beyond the single-file fluid limit using transfer matrix method: Exact results for confined parallel hard squares

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

Gurin, Péter; Varga, Szabolcs

2015-06-14

We extend the transfer matrix method of one-dimensional hard core fluids placed between confining walls for that case where the particles can pass each other and at most two layers can form. We derive an eigenvalue equation for a quasi-one-dimensional system of hard squares confined between two parallel walls, where the pore width is between σ and 3σ (σ is the side length of the square). The exact equation of state and the nearest neighbor distribution functions show three different structures: a fluid phase with one layer, a fluid phase with two layers, and a solid-like structure where the fluidmore » layers are strongly correlated. The structural transition between differently ordered fluids develops continuously with increasing density, i.e., no thermodynamic phase transition occurs. The high density structure of the system consists of clusters with two layers which are broken with particles staying in the middle of the pore.« less

Novel 16-channel receive coil array for accelerated upper airway MRI at 3 Tesla.

PubMed

Kim, Yoon-Chul; Hayes, Cecil E; Narayanan, Shrikanth S; Nayak, Krishna S

2011-06-01

Upper airway MRI can provide a noninvasive assessment of speech and swallowing disorders and sleep apnea. Recent work has demonstrated the value of high-resolution three-dimensional imaging and dynamic two-dimensional imaging and the importance of further improvements in spatio-temporal resolution. The purpose of the study was to describe a novel 16-channel 3 Tesla receive coil that is highly sensitive to the human upper airway and investigate the performance of accelerated upper airway MRI with the coil. In three-dimensional imaging of the upper airway during static posture, 6-fold acceleration is demonstrated using parallel imaging, potentially leading to capturing a whole three-dimensional vocal tract with 1.25 mm isotropic resolution within 9 sec of sustained sound production. Midsagittal spiral parallel imaging of vocal tract dynamics during natural speech production is demonstrated with 2 × 2 mm(2) in-plane spatial and 84 ms temporal resolution. Copyright © 2010 Wiley-Liss, Inc.

Multispectral embedding-based deep neural network for three-dimensional human pose recovery

NASA Astrophysics Data System (ADS)

Yu, Jialin; Sun, Jifeng

2018-01-01

Monocular image-based three-dimensional (3-D) human pose recovery aims to retrieve 3-D poses using the corresponding two-dimensional image features. Therefore, the pose recovery performance highly depends on the image representations. We propose a multispectral embedding-based deep neural network (MSEDNN) to automatically obtain the most discriminative features from multiple deep convolutional neural networks and then embed their penultimate fully connected layers into a low-dimensional manifold. This compact manifold can explore not only the optimum output from multiple deep networks but also the complementary properties of them. Furthermore, the distribution of each hierarchy discriminative manifold is sufficiently smooth so that the training process of our MSEDNN can be effectively implemented only using few labeled data. Our proposed network contains a body joint detector and a human pose regressor that are jointly trained. Extensive experiments conducted on four databases show that our proposed MSEDNN can achieve the best recovery performance compared with the state-of-the-art methods.

Cellular automata with object-oriented features for parallel molecular network modeling.

PubMed

Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan

2005-06-01

Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented.

Performance of parallel computation using CUDA for solving the one-dimensional elasticity equations

NASA Astrophysics Data System (ADS)

Darmawan, J. B. B.; Mungkasi, S.

2017-01-01

In this paper, we investigate the performance of parallel computation in solving the one-dimensional elasticity equations. Elasticity equations are usually implemented in engineering science. Solving these equations fast and efficiently is desired. Therefore, we propose the use of parallel computation. Our parallel computation uses CUDA of the NVIDIA. Our research results show that parallel computation using CUDA has a great advantage and is powerful when the computation is of large scale.

Fast data reconstructed method of Fourier transform imaging spectrometer based on multi-core CPU

NASA Astrophysics Data System (ADS)

Yu, Chunchao; Du, Debiao; Xia, Zongze; Song, Li; Zheng, Weijian; Yan, Min; Lei, Zhenggang

2017-10-01

Imaging spectrometer can gain two-dimensional space image and one-dimensional spectrum at the same time, which shows high utility in color and spectral measurements, the true color image synthesis, military reconnaissance and so on. In order to realize the fast reconstructed processing of the Fourier transform imaging spectrometer data, the paper designed the optimization reconstructed algorithm with OpenMP parallel calculating technology, which was further used for the optimization process for the HyperSpectral Imager of `HJ-1' Chinese satellite. The results show that the method based on multi-core parallel computing technology can control the multi-core CPU hardware resources competently and significantly enhance the calculation of the spectrum reconstruction processing efficiency. If the technology is applied to more cores workstation in parallel computing, it will be possible to complete Fourier transform imaging spectrometer real-time data processing with a single computer.

Three-dimensional Finite Element Formulation and Scalable Domain Decomposition for High Fidelity Rotor Dynamic Analysis

NASA Technical Reports Server (NTRS)

Datta, Anubhav; Johnson, Wayne R.

2009-01-01

This paper has two objectives. The first objective is to formulate a 3-dimensional Finite Element Model for the dynamic analysis of helicopter rotor blades. The second objective is to implement and analyze a dual-primal iterative substructuring based Krylov solver, that is parallel and scalable, for the solution of the 3-D FEM analysis. The numerical and parallel scalability of the solver is studied using two prototype problems - one for ideal hover (symmetric) and one for a transient forward flight (non-symmetric) - both carried out on up to 48 processors. In both hover and forward flight conditions, a perfect linear speed-up is observed, for a given problem size, up to the point of substructure optimality. Substructure optimality and the linear parallel speed-up range are both shown to depend on the problem size as well as on the selection of the coarse problem. With a larger problem size, linear speed-up is restored up to the new substructure optimality. The solver also scales with problem size - even though this conclusion is premature given the small prototype grids considered in this study.

Simulation Exploration through Immersive Parallel Planes

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

Brunhart-Lupo, Nicholas J; Bush, Brian W; Gruchalla, Kenny M

We present a visualization-driven simulation system that tightly couples systems dynamics simulations with an immersive virtual environment to allow analysts to rapidly develop and test hypotheses in a high-dimensional parameter space. To accomplish this, we generalize the two-dimensional parallel-coordinates statistical graphic as an immersive 'parallel-planes' visualization for multivariate time series emitted by simulations running in parallel with the visualization. In contrast to traditional parallel coordinate's mapping the multivariate dimensions onto coordinate axes represented by a series of parallel lines, we map pairs of the multivariate dimensions onto a series of parallel rectangles. As in the case of parallel coordinates, eachmore » individual observation in the dataset is mapped to a polyline whose vertices coincide with its coordinate values. Regions of the rectangles can be 'brushed' to highlight and select observations of interest: a 'slider' control allows the user to filter the observations by their time coordinate. In an immersive virtual environment, users interact with the parallel planes using a joystick that can select regions on the planes, manipulate selection, and filter time. The brushing and selection actions are used to both explore existing data as well as to launch additional simulations corresponding to the visually selected portions of the input parameter space. As soon as the new simulations complete, their resulting observations are displayed in the virtual environment. This tight feedback loop between simulation and immersive analytics accelerates users' realization of insights about the simulation and its output.« less

Simulation Exploration through Immersive Parallel Planes: Preprint

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

Brunhart-Lupo, Nicholas; Bush, Brian W.; Gruchalla, Kenny

We present a visualization-driven simulation system that tightly couples systems dynamics simulations with an immersive virtual environment to allow analysts to rapidly develop and test hypotheses in a high-dimensional parameter space. To accomplish this, we generalize the two-dimensional parallel-coordinates statistical graphic as an immersive 'parallel-planes' visualization for multivariate time series emitted by simulations running in parallel with the visualization. In contrast to traditional parallel coordinate's mapping the multivariate dimensions onto coordinate axes represented by a series of parallel lines, we map pairs of the multivariate dimensions onto a series of parallel rectangles. As in the case of parallel coordinates, eachmore » individual observation in the dataset is mapped to a polyline whose vertices coincide with its coordinate values. Regions of the rectangles can be 'brushed' to highlight and select observations of interest: a 'slider' control allows the user to filter the observations by their time coordinate. In an immersive virtual environment, users interact with the parallel planes using a joystick that can select regions on the planes, manipulate selection, and filter time. The brushing and selection actions are used to both explore existing data as well as to launch additional simulations corresponding to the visually selected portions of the input parameter space. As soon as the new simulations complete, their resulting observations are displayed in the virtual environment. This tight feedback loop between simulation and immersive analytics accelerates users' realization of insights about the simulation and its output.« less

Unusual two-dimensional behavior of iron-based superconductors with low anisotropy

NASA Astrophysics Data System (ADS)

Kalenyuk, A. A.; Pagliero, A.; Borodianskyi, E. A.; Aswartham, S.; Wurmehl, S.; Büchner, B.; Chareev, D. A.; Kordyuk, A. A.; Krasnov, V. M.

2017-10-01

We study angular-dependent magnetoresistance in iron-based superconductors Ba1 -xNaxFe2As2 and FeTe1 -xSex . Both superconductors have relatively small anisotropies γ ˜2 and exhibit a three-dimensional (3D) behavior at low temperatures. However, we observe that they start to exhibit a profound two-dimensional behavior at elevated temperatures and in applied magnetic field parallel to the surface. We conclude that the unexpected two-dimensional (2D) behavior of the studied low-anisotropic superconductors is not related to layeredness of the materials, but is caused by appearance of surface superconductivity when magnetic field exceeds the upper critical field Hc 2(T ) for destruction of bulk superconductivity. We argue that the corresponding 3D-2D bulk-to-surface dimensional transition can be used for accurate determination of the upper critical field.

Parallel consensual neural networks.

PubMed

Benediktsson, J A; Sveinsson, J R; Ersoy, O K; Swain, P H

1997-01-01

A new type of a neural-network architecture, the parallel consensual neural network (PCNN), is introduced and applied in classification/data fusion of multisource remote sensing and geographic data. The PCNN architecture is based on statistical consensus theory and involves using stage neural networks with transformed input data. The input data are transformed several times and the different transformed data are used as if they were independent inputs. The independent inputs are first classified using the stage neural networks. The output responses from the stage networks are then weighted and combined to make a consensual decision. In this paper, optimization methods are used in order to weight the outputs from the stage networks. Two approaches are proposed to compute the data transforms for the PCNN, one for binary data and another for analog data. The analog approach uses wavelet packets. The experimental results obtained with the proposed approach show that the PCNN outperforms both a conjugate-gradient backpropagation neural network and conventional statistical methods in terms of overall classification accuracy of test data.

Coaxial microreactor for particle synthesis

DOEpatents

Bartsch, Michael; Kanouff, Michael P; Ferko, Scott M; Crocker, Robert W; Wally, Karl

2013-10-22

A coaxial fluid flow microreactor system disposed on a microfluidic chip utilizing laminar flow for synthesizing particles from solution. Flow geometries produced by the mixing system make use of hydrodynamic focusing to confine a core flow to a small axially-symmetric, centrally positioned and spatially well-defined portion of a flow channel cross-section to provide highly uniform diffusional mixing between a reactant core and sheath flow streams. The microreactor is fabricated in such a way that a substantially planar two-dimensional arrangement of microfluidic channels will produce a three-dimensional core/sheath flow geometry. The microreactor system can comprise one or more coaxial mixing stages that can be arranged singly, in series, in parallel or nested concentrically in parallel.

Parsing Flowcharts and Series-Parallel Graphs

DTIC Science & Technology

1978-11-01

descriptions of the graph. This possible multiplicity is undesirable in most practical applications, a fact that makes parti%:ularly useful reduction...to parse TT networks, some of the features that make this parsing method useful in other cases are more natually introduced in the context of this...as Figure 4.5 shows. This multiplicity is due to the associativity of consecutive Two Terminal Series and Two Terminal Parallel compositions. In spite

Transient Finite Element Computations on a Variable Transputer System

NASA Technical Reports Server (NTRS)

Smolinski, Patrick J.; Lapczyk, Ireneusz

1993-01-01

A parallel program to analyze transient finite element problems was written and implemented on a system of transputer processors. The program uses the explicit time integration algorithm which eliminates the need for equation solving, making it more suitable for parallel computations. An interprocessor communication scheme was developed for arbitrary two dimensional grid processor configurations. Several 3-D problems were analyzed on a system with a small number of processors.

Parallelized Stochastic Cutoff Method for Long-Range Interacting Systems

NASA Astrophysics Data System (ADS)

Endo, Eishin; Toga, Yuta; Sasaki, Munetaka

2015-07-01

We present a method of parallelizing the stochastic cutoff (SCO) method, which is a Monte-Carlo method for long-range interacting systems. After interactions are eliminated by the SCO method, we subdivide a lattice into noninteracting interpenetrating sublattices. This subdivision enables us to parallelize the Monte-Carlo calculation in the SCO method. Such subdivision is found by numerically solving the vertex coloring of a graph created by the SCO method. We use an algorithm proposed by Kuhn and Wattenhofer to solve the vertex coloring by parallel computation. This method was applied to a two-dimensional magnetic dipolar system on an L × L square lattice to examine its parallelization efficiency. The result showed that, in the case of L = 2304, the speed of computation increased about 102 times by parallel computation with 288 processors.

Spectrin tetramer-dimer equilibrium and the stability of erythrocyte membrane skeletons

NASA Astrophysics Data System (ADS)

Liu, Shih-Chun; Palek, Jiri

1980-06-01

The inner side of the red-cell membrane is laminated by a two-dimensional network of membrane proteins which include spectrin, actin and some other components1-4. After extraction of lipids and integral proteins from the membrane, this membrane skeleton can be visualized as a ball-shaped network consisting of twisted fibres1-4 and globular protrusions4; however, the assembly of the individual proteins in the membrane skeleton is not well understood. Spectrin can be eluted from the membrane in the form of dimers and tetramers5-8. Electron microscopic study with low-angle shadowing technique shows that spectrin dimers are two parallel strands of twisted fibres presumably representing bands 1 and 2 of spectrin9. Spectrin tetramers presumably formed by head-to-head associations of two dimers are twice as long9. In solution, the spectrin dimer-tetramer equilibrium depends on temperature and salt concentration7,8; however, it is not known whether the same equilibrium exists in the membrane and whether it affects the physical properties of the membrane, such as its structural stability and deformability. We now demonstrate that spectrin dimers and tetramers are in a reversible equilibrium in the membrane and that in physiological conditions this equilibrium favours spectrin tetramers. Furthermore, we show that transformation of spectrin tetramers to dimers, as induced by ghost incubation in hypotonic conditions, diminishes the structural stability of the Triton-insoluble membrane skeletons.

Poly-dimensional network comparative analysis reveals the pure pharmacological mechanism of baicalin in the targeted network of mouse cerebral ischemia.

PubMed

Liu, Qiong; Liu, Jun; Wang, Pengqian; Zhang, Yingying; Li, Bing; Yu, Yanan; Dang, Haixia; Li, Haixia; Zhang, Xiaoxu; Wang, Zhong

2017-07-01

This study aimed to investigate the pure pharmacological mechanisms of baicalin/baicalein (BA) in the targeted network of mouse cerebral ischemia using a poly-dimensional network comparative analysis. Eighty mice with induced focal cerebral ischemia were randomly divided into four groups: BA, Concha Margaritifera (CM), vehicle and sham group. A poly-dimensional comparative analysis of the expression levels of 374 stroke-related genes in each of the four groups was performed using MetaCore. BA significantly reduced the ischemic infarct volume (P<0.05), whereas CM was ineffective. Two processes and 10 network nodes were shared between "BA vs CM" and vehicle, but there were no overlapping pathways. Two pathways, three processes and 12 network nodes overlapped in "BA vs CM" and BA. The pure pharmacological mechanism of BA resulted in targeting of pathways related to development, G-protein signaling, apoptosis, signal transduction and immunity. The biological processes affected by BA were primarily found to correlate with apoptotic, anti-apoptotic and neurophysiological processes. Three network nodes changed from up-regulation to down-regulation, while mitogen-activated protein kinase kinase 6 (MAP2K6, also known as MEK6) changed from down-regulation to up-regulation in "BA vs CM" and vehicle. The changed nodes were all related to cell death and development. The pure pharmacological mechanism of BA is related to immunity, apoptosis, development, cytoskeletal remodeling, transduction and neurophysiology, as ascertained using a poly-dimensional network comparative analysis. Copyright © 2017. Published by Elsevier B.V.

Characterization of low thermal conductivity PAN-based carbon fibers

NASA Technical Reports Server (NTRS)

Katzman, Howard A.; Adams, P. M.; Le, T. D.; Hemminger, Carl S.

1992-01-01

The microstructure and surface chemistry of eight low thermal conductivity (LTC) PAN-based carbon fibers were determined and compared with PAN-based fibers heat treated to higher temperatures. Based on wide-angle x ray diffraction, the LTC PAN fibers all appear to have a similar turbostratic structure with large 002 d-spacings, small crystallite sizes, and moderate preferred orientation. Limited small-angle x ray scattering (SAXS) results indicate that, with the exception of LTC fibers made by BASF, the LTC fibers do not have well developed pores. Transmission electron microscopy shows that the texture of the two LTC PAN-based fibers studied (Amoco T350/23X and /25X) consists of multiple sets of parallel, wavy, bent layers that interweave with each other forming a complex three dimensional network oriented randomly around the fiber axis. X ray photoelectron spectroscopy (XPS) analysis finds correlations between heat treated temperatures and the surface composition chemistry of the carbon fiber samples.

Parallel Distributed Processing at 25: Further Explorations in the Microstructure of Cognition

ERIC Educational Resources Information Center

Rogers, Timothy T.; McClelland, James L.

2014-01-01

This paper introduces a special issue of "Cognitive Science" initiated on the 25th anniversary of the publication of "Parallel Distributed Processing" (PDP), a two-volume work that introduced the use of neural network models as vehicles for understanding cognition. The collection surveys the core commitments of the PDP…

EFDC1D - A ONE DIMENSIONAL HYDRODYNAMIC AND SEDIMENT TRANSPORT MODEL FOR RIVER AND STREAM NETWORKS: MODEL THEORY AND USERS GUIDE

EPA Science Inventory

This technical report describes the new one-dimensional (1D) hydrodynamic and sediment transport model EFDC1D. This model that can be applied to stream networks. The model code and two sample data sets are included on the distribution CD. EFDC1D can simulate bi-directional unstea...

Dimensionality Assessment of Ordered Polytomous Items with Parallel Analysis

ERIC Educational Resources Information Center

Timmerman, Marieke E.; Lorenzo-Seva, Urbano

2011-01-01

Parallel analysis (PA) is an often-recommended approach for assessment of the dimensionality of a variable set. PA is known in different variants, which may yield different dimensionality indications. In this article, the authors considered the most appropriate PA procedure to assess the number of common factors underlying ordered polytomously…

Implementation of Finite Volume based Navier Stokes Algorithm Within General Purpose Flow Network Code

NASA Technical Reports Server (NTRS)

Schallhorn, Paul; Majumdar, Alok

2012-01-01

This paper describes a finite volume based numerical algorithm that allows multi-dimensional computation of fluid flow within a system level network flow analysis. There are several thermo-fluid engineering problems where higher fidelity solutions are needed that are not within the capacity of system level codes. The proposed algorithm will allow NASA's Generalized Fluid System Simulation Program (GFSSP) to perform multi-dimensional flow calculation within the framework of GFSSP s typical system level flow network consisting of fluid nodes and branches. The paper presents several classical two-dimensional fluid dynamics problems that have been solved by GFSSP's multi-dimensional flow solver. The numerical solutions are compared with the analytical and benchmark solution of Poiseulle, Couette and flow in a driven cavity.

Spatio-temporal organization of dynamics in a two-dimensional periodically driven vortex flow: A Lagrangian flow network perspective.

PubMed

Lindner, Michael; Donner, Reik V

2017-03-01

We study the Lagrangian dynamics of passive tracers in a simple model of a driven two-dimensional vortex resembling real-world geophysical flow patterns. Using a discrete approximation of the system's transfer operator, we construct a directed network that describes the exchange of mass between distinct regions of the flow domain. By studying different measures characterizing flow network connectivity at different time-scales, we are able to identify the location of dynamically invariant structures and regions of maximum dispersion. Specifically, our approach allows us to delimit co-existing flow regimes with different dynamics. To validate our findings, we compare several network characteristics to the well-established finite-time Lyapunov exponents and apply a receiver operating characteristic analysis to identify network measures that are particularly useful for unveiling the skeleton of Lagrangian chaos.

Rarefied gas flow through two-dimensional nozzles

NASA Technical Reports Server (NTRS)

De Witt, Kenneth J.; Jeng, Duen-Ren; Keith, Theo G., Jr.; Chung, Chan-Hong

1989-01-01

A kinetic theory analysis is made of the flow of a rarefied gas from one reservoir to another through two-dimensional nozzles with arbitrary curvature. The Boltzmann equation simplified by a model collision integral is solved by means of finite-difference approximations with the discrete ordinate method. The physical space is transformed by a general grid generation technique and the velocity space is transformed to a polar coordinate system. A numerical code is developed which can be applied to any two-dimensional passage of complicated geometry for the flow regimes from free-molecular to slip. Numerical values of flow quantities can be calculated for the entire physical space including both inside the nozzle and in the outside plume. Predictions are made for the case of parallel slots and compared with existing literature data. Also, results for the cases of convergent or divergent slots and two-dimensional nozzles with arbitrary curvature at arbitrary knudsen number are presented.

Computer-generated 3D ultrasound images of the carotid artery

NASA Technical Reports Server (NTRS)

Selzer, Robert H.; Lee, Paul L.; Lai, June Y.; Frieden, Howard J.; Blankenhorn, David H.

1989-01-01

A method is under development to measure carotid artery lesions from a computer-generated three-dimensional ultrasound image. For each image, the position of the transducer in six coordinates (x, y, z, azimuth, elevation, and roll) is recorded and used to position each B-mode picture element in its proper spatial position in a three-dimensional memory array. After all B-mode images have been assembled in the memory, the three-dimensional image is filtered and resampled to produce a new series of parallel-plane two-dimensional images from which arterial boundaries are determined using edge tracking methods.

Computer-generated 3D ultrasound images of the carotid artery

NASA Astrophysics Data System (ADS)

Selzer, Robert H.; Lee, Paul L.; Lai, June Y.; Frieden, Howard J.; Blankenhorn, David H.

A method is under development to measure carotid artery lesions from a computer-generated three-dimensional ultrasound image. For each image, the position of the transducer in six coordinates (x, y, z, azimuth, elevation, and roll) is recorded and used to position each B-mode picture element in its proper spatial position in a three-dimensional memory array. After all B-mode images have been assembled in the memory, the three-dimensional image is filtered and resampled to produce a new series of parallel-plane two-dimensional images from which arterial boundaries are determined using edge tracking methods.

Commensurate Superstructure of the {Cu(NO3)(H2O)}(HTae)(Bpy) Coordination Polymer: An Example of 2D Hydrogen-Bonding Networks as Magnetic Exchange Pathway.

PubMed

Fernández de Luis, Roberto; Larrea, Edurne S; Orive, Joseba; Lezama, Luis; Arriortua, María I

2016-11-21

The average and commensurate superstructures of the one-dimensional coordination polymer {Cu(NO 3 )(H 2 O)}(HTae)(Bpy) (H 2 Tae = 1,1,2,2-tetraacetylethane, Bpy = 4,4'-bipyridine) were determined by single-crystal X-ray diffraction, and the possible symmetry relations between the space group of the average structure and the superstructure were checked. The crystal structure consists in parallel and oblique {Cu(HTae)(Bpy)} zigzag metal-organic chains stacked along the [100] crystallographic direction. The origin of the fivefold c axis in the commensurate superstructure is ascribed to a commensurate modulation of the coordination environment of the copper atoms. The commensurately ordered nitrate groups and coordinated water molecules establish a two-dimensional hydrogen-bonding network. Moreover, the crystal structure shows a commensurate to incommensurate transition at room temperature. The release of the coordination water molecules destabilizes the crystal framework, and the compound shows an irreversible structure transformation above 100 °C. Despite the loss of crystallinity, the spectroscopic studies indicate that the main building blocks of the crystal framework are retained after the transformation. The hydrogen-bonding network not only plays a crucial role stabilizing the crystal structure but also is an important pathway for magnetic exchange transmission. In fact, the magnetic susceptibility curves indicate that after the loss of coordinated water molecules, and hence the collapse of the hydrogen-bonding network, the weak anti-ferromagnetic coupling observed in the initial compound is broken. The electron paramagnetic resonance spectra are the consequence of the average signals from Cu(II) with different orientations, indicating that the magnetic coupling is effective between them. In fact, X- and Q-band data are reflecting different situations; the X-band spectra show the characteristics of an exchange g-tensor, while the Q-band signals are coming from both the exchange and the molecular g-tensors.

Multirate parallel distributed compensation of a cluster in wireless sensor and actor networks

NASA Astrophysics Data System (ADS)

Yang, Chun-xi; Huang, Ling-yun; Zhang, Hao; Hua, Wang

2016-01-01

The stabilisation problem for one of the clusters with bounded multiple random time delays and packet dropouts in wireless sensor and actor networks is investigated in this paper. A new multirate switching model is constructed to describe the feature of this single input multiple output linear system. According to the difficulty of controller design under multi-constraints in multirate switching model, this model can be converted to a Takagi-Sugeno fuzzy model. By designing a multirate parallel distributed compensation, a sufficient condition is established to ensure this closed-loop fuzzy control system to be globally exponentially stable. The solution of the multirate parallel distributed compensation gains can be obtained by solving an auxiliary convex optimisation problem. Finally, two numerical examples are given to show, compared with solving switching controller, multirate parallel distributed compensation can be obtained easily. Furthermore, it has stronger robust stability than arbitrary switching controller and single-rate parallel distributed compensation under the same conditions.

Relationships among classes of self-oscillating transistor parallel inverters. [for power conditioning applications

NASA Technical Reports Server (NTRS)

Wilson, T. G.; Lee, F. C. Y.; Burns, W. W., III; Owen, H. A., Jr.

1975-01-01

It recently has been shown in the literature that many dc-to-square-wave parallel inverters which are widely used in power-conditioning applications can be grouped into one of two families. Each family is characterized by an equivalent RLC network. Based on this approach, a classification procedure is presented for self-oscillating parallel inverters which makes evident natural relationships which exist between various inverter configurations. By utilizing concepts from the basic theory of negative resistance oscillators and the principle of duality as applied to nonlinear networks, a chain of relationships is established which enables a methodical transfer of knowledge gained about one family of inverters to any of the other families in the classification array.

Parallel architectures for iterative methods on adaptive, block structured grids

NASA Technical Reports Server (NTRS)

Gannon, D.; Vanrosendale, J.

1983-01-01

A parallel computer architecture well suited to the solution of partial differential equations in complicated geometries is proposed. Algorithms for partial differential equations contain a great deal of parallelism. But this parallelism can be difficult to exploit, particularly on complex problems. One approach to extraction of this parallelism is the use of special purpose architectures tuned to a given problem class. The architecture proposed here is tuned to boundary value problems on complex domains. An adaptive elliptic algorithm which maps effectively onto the proposed architecture is considered in detail. Two levels of parallelism are exploited by the proposed architecture. First, by making use of the freedom one has in grid generation, one can construct grids which are locally regular, permitting a one to one mapping of grids to systolic style processor arrays, at least over small regions. All local parallelism can be extracted by this approach. Second, though there may be a regular global structure to the grids constructed, there will be parallelism at this level. One approach to finding and exploiting this parallelism is to use an architecture having a number of processor clusters connected by a switching network. The use of such a network creates a highly flexible architecture which automatically configures to the problem being solved.

Predicting the stability of a compressible periodic parallel jet flow

NASA Technical Reports Server (NTRS)

Miles, Jeffrey H.

1996-01-01

It is known that mixing enhancement in compressible free shear layer flows with high convective Mach numbers is difficult. One design strategy to get around this is to use multiple nozzles. Extrapolating this design concept in a one dimensional manner, one arrives at an array of parallel rectangular nozzles where the smaller dimension is omega and the longer dimension, b, is taken to be infinite. In this paper, the feasibility of predicting the stability of this type of compressible periodic parallel jet flow is discussed. The problem is treated using Floquet-Bloch theory. Numerical solutions to this eigenvalue problem are presented. For the case presented, the interjet spacing, s, was selected so that s/omega =2.23. Typical plots of the eigenvalue and stability curves are presented. Results obtained for a range of convective Mach numbers from 3 to 5 show growth rates omega(sub i)=kc(sub i)/2 range from 0.25 to 0.29. These results indicate that coherent two-dimensional structures can occur without difficulty in multiple parallel periodic jet nozzles and that shear layer mixing should occur with this type of nozzle design.

ColDICE: A parallel Vlasov–Poisson solver using moving adaptive simplicial tessellation

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

Sousbie, Thierry, E-mail: tsousbie@gmail.com; Department of Physics, The University of Tokyo, Tokyo 113-0033; Research Center for the Early Universe, School of Science, The University of Tokyo, Tokyo 113-0033

2016-09-15

Resolving numerically Vlasov–Poisson equations for initially cold systems can be reduced to following the evolution of a three-dimensional sheet evolving in six-dimensional phase-space. We describe a public parallel numerical algorithm consisting in representing the phase-space sheet with a conforming, self-adaptive simplicial tessellation of which the vertices follow the Lagrangian equations of motion. The algorithm is implemented both in six- and four-dimensional phase-space. Refinement of the tessellation mesh is performed using the bisection method and a local representation of the phase-space sheet at second order relying on additional tracers created when needed at runtime. In order to preserve in the bestmore » way the Hamiltonian nature of the system, refinement is anisotropic and constrained by measurements of local Poincaré invariants. Resolution of Poisson equation is performed using the fast Fourier method on a regular rectangular grid, similarly to particle in cells codes. To compute the density projected onto this grid, the intersection of the tessellation and the grid is calculated using the method of Franklin and Kankanhalli [65–67] generalised to linear order. As preliminary tests of the code, we study in four dimensional phase-space the evolution of an initially small patch in a chaotic potential and the cosmological collapse of a fluctuation composed of two sinusoidal waves. We also perform a “warm” dark matter simulation in six-dimensional phase-space that we use to check the parallel scaling of the code.« less

Revisiting the Al/Al₂O₃ interface: coherent interfaces and misfit accommodation.

PubMed

Pilania, Ghanshyam; Thijsse, Barend J; Hoagland, Richard G; Lazić, Ivan; Valone, Steven M; Liu, Xiang-Yang

2014-03-27

We study the coherent and semi-coherent Al/α-Al2O3 interfaces using molecular dynamics simulations with a mixed, metallic-ionic atomistic model. For the coherent interfaces, both Al-terminated and O-terminated nonstoichiometric interfaces have been studied and their relative stability has been established. To understand the misfit accommodation at the semi-coherent interface, a 1-dimensional (1D) misfit dislocation model and a 2-dimensional (2D) dislocation network model have been studied. For the latter case, our analysis reveals an interface dislocation structure with a network of three sets of parallel dislocations, each with pure-edge character, giving rise to a pattern of coherent and stacking-fault-like regions at the interface. Structural relaxation at elevated temperatures leads to a further change of the dislocation pattern, which can be understood in terms of a competition between the stacking fault energy and the dislocation interaction energy at the interface. Our results are expected to serve as an input for the subsequent dislocation dynamics models to understand and predict the macroscopic mechanical behavior of Al/α-Al2O3 composite heterostructures.

Electric-Field-Directed Parallel Alignment Architecting 3D Lithium-Ion Pathways within Solid Composite Electrolyte.

PubMed

Liu, Xueqing; Peng, Sha; Gao, Shuyu; Cao, Yuancheng; You, Qingliang; Zhou, Liyong; Jin, Yongcheng; Liu, Zhihong; Liu, Jiyan

2018-05-09

It is of great significance to seek high-performance solid electrolytes via a facile chemistry and simple process for meeting the requirements of solid batteries. Previous reports revealed that ion conducting pathways within ceramic-polymer composite electrolytes mainly occur at ceramic particles and the ceramic-polymer interface. Herein, one facile strategy toward ceramic particles' alignment and assembly induced by an external alternating-current (AC) electric field is presented. It was manifested by an in situ optical microscope that Li 1.3 Al 0.3 Ti 1.7 (PO 4 ) 3 particles and poly(ethylene glycol) diacrylate in poly(dimethylsiloxane) (LATP@PEGDA@PDMS) assembled into three-dimensional connected networks on applying an external AC electric field. Scanning electron microscopy revealed that the ceramic LATP particles aligned into a necklacelike assembly. Electrochemical impedance spectroscopy confirmed that the ionic conductivity of this necklacelike alignment was significantly enhanced compared to that of the random one. It was demonstrated that this facile strategy of applying an AC electric field can be a very effective approach for architecting three-dimensional lithium-ion conductive networks within solid composite electrolyte.

Low-frequency sine wave hard-limiting technique

NASA Technical Reports Server (NTRS)

Anderson, T. O.

1977-01-01

Circuit includes serial-in/parallel-out shift register and weighting network that are used to eliminate effects of noise and other nonrepetitive circuit transients. Register and weighting network average decisions from section of signal where decisions are more dependable or where differences between two consecutive samples are larger.

Medical applications for high-performance computers in SKIF-GRID network.

PubMed

Zhuchkov, Alexey; Tverdokhlebov, Nikolay

2009-01-01

The paper presents a set of software services for massive mammography image processing by using high-performance parallel computers of SKIF-family which are linked into a service-oriented grid-network. An experience of a prototype system implementation in two medical institutions is also described.

Enabling parallel simulation of large-scale HPC network systems

DOE PAGES

Mubarak, Misbah; Carothers, Christopher D.; Ross, Robert B.; ...

2016-04-07

Here, with the increasing complexity of today’s high-performance computing (HPC) architectures, simulation has become an indispensable tool for exploring the design space of HPC systems—in particular, networks. In order to make effective design decisions, simulations of these systems must possess the following properties: (1) have high accuracy and fidelity, (2) produce results in a timely manner, and (3) be able to analyze a broad range of network workloads. Most state-of-the-art HPC network simulation frameworks, however, are constrained in one or more of these areas. In this work, we present a simulation framework for modeling two important classes of networks usedmore » in today’s IBM and Cray supercomputers: torus and dragonfly networks. We use the Co-Design of Multi-layer Exascale Storage Architecture (CODES) simulation framework to simulate these network topologies at a flit-level detail using the Rensselaer Optimistic Simulation System (ROSS) for parallel discrete-event simulation. Our simulation framework meets all the requirements of a practical network simulation and can assist network designers in design space exploration. First, it uses validated and detailed flit-level network models to provide an accurate and high-fidelity network simulation. Second, instead of relying on serial time-stepped or traditional conservative discrete-event simulations that limit simulation scalability and efficiency, we use the optimistic event-scheduling capability of ROSS to achieve efficient and scalable HPC network simulations on today’s high-performance cluster systems. Third, our models give network designers a choice in simulating a broad range of network workloads, including HPC application workloads using detailed network traces, an ability that is rarely offered in parallel with high-fidelity network simulations« less

Enabling parallel simulation of large-scale HPC network systems

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

Mubarak, Misbah; Carothers, Christopher D.; Ross, Robert B.

Here, with the increasing complexity of today’s high-performance computing (HPC) architectures, simulation has become an indispensable tool for exploring the design space of HPC systems—in particular, networks. In order to make effective design decisions, simulations of these systems must possess the following properties: (1) have high accuracy and fidelity, (2) produce results in a timely manner, and (3) be able to analyze a broad range of network workloads. Most state-of-the-art HPC network simulation frameworks, however, are constrained in one or more of these areas. In this work, we present a simulation framework for modeling two important classes of networks usedmore » in today’s IBM and Cray supercomputers: torus and dragonfly networks. We use the Co-Design of Multi-layer Exascale Storage Architecture (CODES) simulation framework to simulate these network topologies at a flit-level detail using the Rensselaer Optimistic Simulation System (ROSS) for parallel discrete-event simulation. Our simulation framework meets all the requirements of a practical network simulation and can assist network designers in design space exploration. First, it uses validated and detailed flit-level network models to provide an accurate and high-fidelity network simulation. Second, instead of relying on serial time-stepped or traditional conservative discrete-event simulations that limit simulation scalability and efficiency, we use the optimistic event-scheduling capability of ROSS to achieve efficient and scalable HPC network simulations on today’s high-performance cluster systems. Third, our models give network designers a choice in simulating a broad range of network workloads, including HPC application workloads using detailed network traces, an ability that is rarely offered in parallel with high-fidelity network simulations« less

Relativistic effects in the energy loss of a fast charged particle moving parallel to a two-dimensional electron gas

NASA Astrophysics Data System (ADS)

Mišković, Zoran L.; Akbari, Kamran; Segui, Silvina; Gervasoni, Juana L.; Arista, Néstor R.

2018-05-01

We present a fully relativistic formulation for the energy loss rate of a charged particle moving parallel to a sheet containing two-dimensional electron gas, allowing that its in-plane polarization may be described by different longitudinal and transverse conductivities. We apply our formulation to the case of a doped graphene layer in the terahertz range of frequencies, where excitation of the Dirac plasmon polariton (DPP) in graphene plays a major role. By using the Drude model with zero damping we evaluate the energy loss rate due to excitation of the DPP, and show that the retardation effects are important when the incident particle speed and its distance from graphene both increase. Interestingly, the retarded energy loss rate obtained in this manner may be both larger and smaller than its non-retarded counterpart for different combinations of the particle speed and distance.

Tuning zinc coordination architectures by benzenedicarboxylate position isomers and bis(triazole)

NASA Astrophysics Data System (ADS)

Peng, Yan-fen; Li, Ke; Zhao, Shan; Han, Shan-shan; Li, Bao-long; Li, Hai-Yan

2015-08-01

Three position isomers 1,2-, 1,3-, 1,4-benzenedicarboxylate and 1,4-bis(1,2,4-triazol-4-yl)benzene were used to assembly zinc(II) coordination polymers {[Zn2(btx)0.5(1,2-bdc)2(H2O)]·H2O}n (1), {[Zn(btx)(1,3-bdc)]·2H2O·(DMF)}n (2) and {[Zn(btx)(1,4-bdc)]·3H2O}n (3). 1 is a (3,4,4,4)-connected two-dimensional network with point symbol (42·6)(44·62)(43·62·8)(42·6·103). 2 shows a two-dimensional (4,4) network. 3 exhibits a 5-fold interpenetrated three-dimensional diamondoid network. The structural versatility shows that the structures of coordination polymers can be tuned by the position isomers ligands. The luminescence and thermal stability were investigated.

Large-scale three-dimensional phase-field simulations for phase coarsening at ultrahigh volume fraction on high-performance architectures

NASA Astrophysics Data System (ADS)

Yan, Hui; Wang, K. G.; Jones, Jim E.

2016-06-01

A parallel algorithm for large-scale three-dimensional phase-field simulations of phase coarsening is developed and implemented on high-performance architectures. From the large-scale simulations, a new kinetics in phase coarsening in the region of ultrahigh volume fraction is found. The parallel implementation is capable of harnessing the greater computer power available from high-performance architectures. The parallelized code enables increase in three-dimensional simulation system size up to a 5123 grid cube. Through the parallelized code, practical runtime can be achieved for three-dimensional large-scale simulations, and the statistical significance of the results from these high resolution parallel simulations are greatly improved over those obtainable from serial simulations. A detailed performance analysis on speed-up and scalability is presented, showing good scalability which improves with increasing problem size. In addition, a model for prediction of runtime is developed, which shows a good agreement with actual run time from numerical tests.

A FAST ITERATIVE METHOD FOR SOLVING THE EIKONAL EQUATION ON TETRAHEDRAL DOMAINS

PubMed Central

Fu, Zhisong; Kirby, Robert M.; Whitaker, Ross T.

2014-01-01

Generating numerical solutions to the eikonal equation and its many variations has a broad range of applications in both the natural and computational sciences. Efficient solvers on cutting-edge, parallel architectures require new algorithms that may not be theoretically optimal, but that are designed to allow asynchronous solution updates and have limited memory access patterns. This paper presents a parallel algorithm for solving the eikonal equation on fully unstructured tetrahedral meshes. The method is appropriate for the type of fine-grained parallelism found on modern massively-SIMD architectures such as graphics processors and takes into account the particular constraints and capabilities of these computing platforms. This work builds on previous work for solving these equations on triangle meshes; in this paper we adapt and extend previous two-dimensional strategies to accommodate three-dimensional, unstructured, tetrahedralized domains. These new developments include a local update strategy with data compaction for tetrahedral meshes that provides solutions on both serial and parallel architectures, with a generalization to inhomogeneous, anisotropic speed functions. We also propose two new update schemes, specialized to mitigate the natural data increase observed when moving to three dimensions, and the data structures necessary for efficiently mapping data to parallel SIMD processors in a way that maintains computational density. Finally, we present descriptions of the implementations for a single CPU, as well as multicore CPUs with shared memory and SIMD architectures, with comparative results against state-of-the-art eikonal solvers. PMID:25221418

Computation of Coupled Thermal-Fluid Problems in Distributed Memory Environment

NASA Technical Reports Server (NTRS)

Wei, H.; Shang, H. M.; Chen, Y. S.

2001-01-01

The thermal-fluid coupling problems are very important to aerospace and engineering applications. Instead of analyzing heat transfer and fluid flow separately, this study merged two well-accepted engineering solution methods, SINDA for thermal analysis and FDNS for fluid flow simulation, into a unified multi-disciplinary thermal fluid prediction method. A fully conservative patched grid interface algorithm for arbitrary two-dimensional and three-dimensional geometry has been developed. The state-of-the-art parallel computing concept was used to couple SINDA and FDNS for the communication of boundary conditions through PVM (Parallel Virtual Machine) libraries. Therefore, the thermal analysis performed by SINDA and the fluid flow calculated by FDNS are fully coupled to obtain steady state or transient solutions. The natural convection between two thick-walled eccentric tubes was calculated and the predicted results match the experiment data perfectly. A 3-D rocket engine model and a real 3-D SSME geometry were used to test the current model, and the reasonable temperature field was obtained.

A scalable PC-based parallel computer for lattice QCD

NASA Astrophysics Data System (ADS)

Fodor, Z.; Katz, S. D.; Pappa, G.

2003-05-01

A PC-based parallel computer for medium/large scale lattice QCD simulations is suggested. The Eo¨tvo¨s Univ., Inst. Theor. Phys. cluster consists of 137 Intel P4-1.7GHz nodes. Gigabit Ethernet cards are used for nearest neighbor communication in a two-dimensional mesh. The sustained performance for dynamical staggered (wilson) quarks on large lattices is around 70(110) GFlops. The exceptional price/performance ratio is below $1/Mflop.

Element-topology-independent preconditioners for parallel finite element computations

NASA Technical Reports Server (NTRS)

Park, K. C.; Alexander, Scott

1992-01-01

A family of preconditioners for the solution of finite element equations are presented, which are element-topology independent and thus can be applicable to element order-free parallel computations. A key feature of the present preconditioners is the repeated use of element connectivity matrices and their left and right inverses. The properties and performance of the present preconditioners are demonstrated via beam and two-dimensional finite element matrices for implicit time integration computations.

Parallel resonant converter with LLC-type commutation

NASA Astrophysics Data System (ADS)

Lee, C. Q.; Liu, Rui; Batarseh, Issa

1989-11-01

It is shown that by using a proper transformation of state variables, the third-order system of the parallel resonant converter (PRC) with LLC-type commutation can be analyzed by means of a two-dimensional state-plane diagram. A set of characteristic curves which can be used for the converter design is derived from the analysis. It is shown from these curves that the converter possesses more desirable features than the conventional PRC.

Transport of cosmic-ray protons in intermittent heliospheric turbulence: Model and simulations

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

Alouani-Bibi, Fathallah; Le Roux, Jakobus A., E-mail: fb0006@uah.edu

The transport of charged energetic particles in the presence of strong intermittent heliospheric turbulence is computationally analyzed based on known properties of the interplanetary magnetic field and solar wind plasma at 1 astronomical unit. The turbulence is assumed to be static, composite, and quasi-three-dimensional with a varying energy distribution between a one-dimensional Alfvénic (slab) and a structured two-dimensional component. The spatial fluctuations of the turbulent magnetic field are modeled either as homogeneous with a Gaussian probability distribution function (PDF), or as intermittent on large and small scales with a q-Gaussian PDF. Simulations showed that energetic particle diffusion coefficients both parallelmore » and perpendicular to the background magnetic field are significantly affected by intermittency in the turbulence. This effect is especially strong for parallel transport where for large-scale intermittency results show an extended phase of subdiffusive parallel transport during which cross-field transport diffusion dominates. The effects of intermittency are found to depend on particle rigidity and the fraction of slab energy in the turbulence, yielding a perpendicular to parallel mean free path ratio close to 1 for large-scale intermittency. Investigation of higher order transport moments (kurtosis) indicates that non-Gaussian statistical properties of the intermittent turbulent magnetic field are present in the parallel transport, especially for low rigidity particles at all times.« less

Mechanisms of leading edge protrusion in interstitial migration

PubMed Central

Wilson, Kerry; Lewalle, Alexandre; Fritzsche, Marco; Thorogate, Richard; Duke, Tom; Charras, Guillaume

2013-01-01

While the molecular and biophysical mechanisms underlying cell protrusion on two-dimensional substrates are well understood, our knowledge of the actin structures driving protrusion in three-dimensional environments is poor, despite relevance to inflammation, development and cancer. Here we report that, during chemotactic migration through microchannels with 5 μm × 5 μm cross-sections, HL60 neutrophil-like cells assemble an actin-rich slab filling the whole channel cross-section at their front. This leading edge comprises two distinct F-actin networks: an adherent network that polymerizes perpendicular to cell-wall interfaces and a ‘free’ network that grows from the free membrane at the cell front. Each network is polymerized by a distinct nucleator and, due to their geometrical arrangement, the networks interact mechanically. On the basis of our experimental data, we propose that, during interstitial migration, medial growth of the adherent network compresses the free network preventing its retrograde movement and enabling new polymerization to be converted into forward protrusion. PMID:24305616

Dimensionality and entropy of spontaneous and evoked rate activity

NASA Astrophysics Data System (ADS)

Engelken, Rainer; Wolf, Fred

Cortical circuits exhibit complex activity patterns both spontaneously and evoked by external stimuli. Finding low-dimensional structure in population activity is a challenge. What is the diversity of the collective neural activity and how is it affected by an external stimulus? Using concepts from ergodic theory, we calculate the attractor dimensionality and dynamical entropy production of these networks. We obtain these two canonical measures of the collective network dynamics from the full set of Lyapunov exponents. We consider a randomly-wired firing-rate network that exhibits chaotic rate fluctuations for sufficiently strong synaptic weights. We show that dynamical entropy scales logarithmically with synaptic coupling strength, while the attractor dimensionality saturates. Thus, despite the increasing uncertainty, the diversity of collective activity saturates for strong coupling. We find that a time-varying external stimulus drastically reduces both entropy and dimensionality. Finally, we analytically approximate the full Lyapunov spectrum in several limiting cases by random matrix theory. Our study opens a novel avenue to characterize the complex dynamics of rate networks and the geometric structure of the corresponding high-dimensional chaotic attractor. received funding from Evangelisches Studienwerk Villigst, DFG through CRC 889 and Volkswagen Foundation.

Computational neural networks in chemistry: Model free mapping devices for predicting chemical reactivity from molecular structure

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

Elrod, D.W.

1992-01-01

Computational neural networks (CNNs) are a computational paradigm inspired by the brain's massively parallel network of highly interconnected neurons. The power of computational neural networks derives not so much from their ability to model the brain as from their ability to learn by example and to map highly complex, nonlinear functions, without the need to explicitly specify the functional relationship. Two central questions about CNNs were investigated in the context of predicting chemical reactions: (1) the mapping properties of neural networks and (2) the representation of chemical information for use in CNNs. Chemical reactivity is here considered an example ofmore » a complex, nonlinear function of molecular structure. CNN's were trained using modifications of the back propagation learning rule to map a three dimensional response surface similar to those typically observed in quantitative structure-activity and structure-property relationships. The computational neural network's mapping of the response surface was found to be robust to the effects of training sample size, noisy data and intercorrelated input variables. The investigation of chemical structure representation led to the development of a molecular structure-based connection-table representation suitable for neural network training. An extension of this work led to a BE-matrix structure representation that was found to be general for several classes of reactions. The CNN prediction of chemical reactivity and regiochemistry was investigated for electrophilic aromatic substitution reactions, Markovnikov addition to alkenes, Saytzeff elimination from haloalkanes, Diels-Alder cycloaddition, and retro Diels-Alder ring opening reactions using these connectivity-matrix derived representations. The reaction predictions made by the CNNs were more accurate than those of an expert system and were comparable to predictions made by chemists.« less

Mechanics of the Cell

NASA Astrophysics Data System (ADS)

Boal, David

2012-01-01

Preface; List of symbols; 1. Introduction to the cell; 2. Soft materials and fluids; Part I. Rods and Ropes: 3. Polymers; 4. Complex filaments; 5. Two-dimensional networks; 6. Three-dimensional networks; Part II. Membranes: 7. Biomembranes; 8. Membrane undulations; 9. Intermembrane and electrostatic forces; Part III. The Whole Cell: 10. Structure of the simplest cells; 11. Dynamic filaments; 12. Growth and division; 13. Signals and switches; Appendixes; Glossary; References; Index.

Three-dimensional object recognitions from two-dimensional images using wavelet transforms and neural networks

NASA Astrophysics Data System (ADS)

Deschenes, Sylvain; Sheng, Yunlong; Chevrette, Paul C.

1998-03-01

3D object classification from 2D IR images is shown. The wavelet transform is used for edge detection. Edge tracking is used for removing noise effectively int he wavelet transform. The invariant Fourier descriptor is used to describe the contour curves. Invariance under out-of-plane rotation is achieved by the feature space trajectory neural network working as a classifier.

Automated target recognition and tracking using an optical pattern recognition neural network

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

1991-01-01

The on-going development of an automatic target recognition and tracking system at the Jet Propulsion Laboratory is presented. This system is an optical pattern recognition neural network (OPRNN) that is an integration of an innovative optical parallel processor and a feature extraction based neural net training algorithm. The parallel optical processor provides high speed and vast parallelism as well as full shift invariance. The neural network algorithm enables simultaneous discrimination of multiple noisy targets in spite of their scales, rotations, perspectives, and various deformations. This fully developed OPRNN system can be effectively utilized for the automated spacecraft recognition and tracking that will lead to success in the Automated Rendezvous and Capture (AR&C) of the unmanned Cargo Transfer Vehicle (CTV). One of the most powerful optical parallel processors for automatic target recognition is the multichannel correlator. With the inherent advantages of parallel processing capability and shift invariance, multiple objects can be simultaneously recognized and tracked using this multichannel correlator. This target tracking capability can be greatly enhanced by utilizing a powerful feature extraction based neural network training algorithm such as the neocognitron. The OPRNN, currently under investigation at JPL, is constructed with an optical multichannel correlator where holographic filters have been prepared using the neocognitron training algorithm. The computation speed of the neocognitron-type OPRNN is up to 10(exp 14) analog connections/sec that enabling the OPRNN to outperform its state-of-the-art electronics counterpart by at least two orders of magnitude.

A novel method to acquire 3D data from serial 2D images of a dental cast

NASA Astrophysics Data System (ADS)

Yi, Yaxing; Li, Zhongke; Chen, Qi; Shao, Jun; Li, Xinshe; Liu, Zhiqin

2007-05-01

This paper introduced a newly developed method to acquire three-dimensional data from serial two-dimensional images of a dental cast. The system consists of a computer and a set of data acquiring device. The data acquiring device is used to take serial pictures of the a dental cast; an artificial neural network works to translate two-dimensional pictures to three-dimensional data; then three-dimensional image can reconstruct by the computer. The three-dimensional data acquiring of dental casts is the foundation of computer-aided diagnosis and treatment planning in orthodontics.

Execution of a parallel edge-based Navier-Stokes solver on commodity graphics processor units

NASA Astrophysics Data System (ADS)

Corral, Roque; Gisbert, Fernando; Pueblas, Jesus

2017-02-01

The implementation of an edge-based three-dimensional Reynolds Average Navier-Stokes solver for unstructured grids able to run on multiple graphics processing units (GPUs) is presented. Loops over edges, which are the most time-consuming part of the solver, have been written to exploit the massively parallel capabilities of GPUs. Non-blocking communications between parallel processes and between the GPU and the central processor unit (CPU) have been used to enhance code scalability. The code is written using a mixture of C++ and OpenCL, to allow the execution of the source code on GPUs. The Message Passage Interface (MPI) library is used to allow the parallel execution of the solver on multiple GPUs. A comparative study of the solver parallel performance is carried out using a cluster of CPUs and another of GPUs. It is shown that a single GPU is up to 64 times faster than a single CPU core. The parallel scalability of the solver is mainly degraded due to the loss of computing efficiency of the GPU when the size of the case decreases. However, for large enough grid sizes, the scalability is strongly improved. A cluster featuring commodity GPUs and a high bandwidth network is ten times less costly and consumes 33% less energy than a CPU-based cluster with an equivalent computational power.

On a model of three-dimensional bursting and its parallel implementation

NASA Astrophysics Data System (ADS)

Tabik, S.; Romero, L. F.; Garzón, E. M.; Ramos, J. I.

2008-04-01

A mathematical model for the simulation of three-dimensional bursting phenomena and its parallel implementation are presented. The model consists of four nonlinearly coupled partial differential equations that include fast and slow variables, and exhibits bursting in the absence of diffusion. The differential equations have been discretized by means of a second-order accurate in both space and time, linearly-implicit finite difference method in equally-spaced grids. The resulting system of linear algebraic equations at each time level has been solved by means of the Preconditioned Conjugate Gradient (PCG) method. Three different parallel implementations of the proposed mathematical model have been developed; two of these implementations, i.e., the MPI and the PETSc codes, are based on a message passing paradigm, while the third one, i.e., the OpenMP code, is based on a shared space address paradigm. These three implementations are evaluated on two current high performance parallel architectures, i.e., a dual-processor cluster and a Shared Distributed Memory (SDM) system. A novel representation of the results that emphasizes the most relevant factors that affect the performance of the paralled implementations, is proposed. The comparative analysis of the computational results shows that the MPI and the OpenMP implementations are about twice more efficient than the PETSc code on the SDM system. It is also shown that, for the conditions reported here, the nonlinear dynamics of the three-dimensional bursting phenomena exhibits three stages characterized by asynchronous, synchronous and then asynchronous oscillations, before a quiescent state is reached. It is also shown that the fast system reaches steady state in much less time than the slow variables.

A Parallel Adaboost-Backpropagation Neural Network for Massive Image Dataset Classification

NASA Astrophysics Data System (ADS)

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.

PubMed

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

PubMed Central

Cao, Jianfang; Chen, Lichao; Wang, Min; Shi, Hao; Tian, Yun

2016-01-01

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. PMID:27905520

Diffraction mode terahertz tomography

DOEpatents

Ferguson, Bradley; Wang, Shaohong; Zhang, Xi-Cheng

2006-10-31

A method of obtaining a series of images of a three-dimensional object. The method includes the steps of transmitting pulsed terahertz (THz) radiation through the entire object from a plurality of angles, optically detecting changes in the transmitted THz radiation using pulsed laser radiation, and constructing a plurality of imaged slices of the three-dimensional object using the detected changes in the transmitted THz radiation. The THz radiation is transmitted through the object as a two-dimensional array of parallel rays. The optical detection is an array of detectors such as a CCD sensor.

Percolation and epidemics in a two-dimensional small world

NASA Astrophysics Data System (ADS)

Newman, M. E.; Jensen, I.; Ziff, R. M.

2002-02-01

Percolation on two-dimensional small-world networks has been proposed as a model for the spread of plant diseases. In this paper we give an analytic solution of this model using a combination of generating function methods and high-order series expansion. Our solution gives accurate predictions for quantities such as the position of the percolation threshold and the typical size of disease outbreaks as a function of the density of ``shortcuts'' in the small-world network. Our results agree with scaling hypotheses and numerical simulations for the same model.

Impact of network topology on self-organized criticality

NASA Astrophysics Data System (ADS)

Hoffmann, Heiko

2018-02-01

The general mechanisms behind self-organized criticality (SOC) are still unknown. Several microscopic and mean-field theory approaches have been suggested, but they do not explain the dependence of the exponents on the underlying network topology of the SOC system. Here, we first report the phenomena that in the Bak-Tang-Wiesenfeld (BTW) model, sites inside an avalanche area largely return to their original state after the passing of an avalanche, forming, effectively, critically arranged clusters of sites. Then, we hypothesize that SOC relies on the formation process of these clusters, and present a model of such formation. For low-dimensional networks, we show theoretically and in simulation that the exponent of the cluster-size distribution is proportional to the ratio of the fractal dimension of the cluster boundary and the dimensionality of the network. For the BTW model, in our simulations, the exponent of the avalanche-area distribution matched approximately our prediction based on this ratio for two-dimensional networks, but deviated for higher dimensions. We hypothesize a transition from cluster formation to the mean-field theory process with increasing dimensionality. This work sheds light onto the mechanisms behind SOC, particularly, the impact of the network topology.

Parallel 3-D numerical simulation of dielectric barrier discharge plasma actuators

NASA Astrophysics Data System (ADS)

Houba, Tomas

Dielectric barrier discharge plasma actuators have shown promise in a range of applications including flow control, sterilization and ozone generation. Developing numerical models of plasma actuators is of great importance, because a high-fidelity parallel numerical model allows new design configurations to be tested rapidly. Additionally, it provides a better understanding of the plasma actuator physics which is useful for further innovation. The physics of plasma actuators is studied numerically. A loosely coupled approach is utilized for the coupling of the plasma to the neutral fluid. The state of the art in numerical plasma modeling is advanced by the development of a parallel, three-dimensional, first-principles model with detailed air chemistry. The model incorporates 7 charged species and 18 reactions, along with a solution of the electron energy equation. To the author's knowledge, a parallel three-dimensional model of a gas discharge with a detailed air chemistry model and the solution of electron energy is unique. Three representative geometries are studied using the gas discharge model. The discharge of gas between two parallel electrodes is used to validate the air chemistry model developed for the gas discharge code. The gas discharge model is then applied to the discharge produced by placing a dc powered wire and grounded plate electrodes in a channel. Finally, a three-dimensional simulation of gas discharge produced by electrodes placed inside a riblet is carried out. The body force calculated with the gas discharge model is loosely coupled with a fluid model to predict the induced flow inside the riblet.

Neuromorphic computing with nanoscale spintronic oscillators

PubMed Central

Torrejon, Jacob; Riou, Mathieu; Araujo, Flavio Abreu; Tsunegi, Sumito; Khalsa, Guru; Querlioz, Damien; Bortolotti, Paolo; Cros, Vincent; Fukushima, Akio; Kubota, Hitoshi; Yuasa, Shinji; Stiles, M. D.; Grollier, Julie

2017-01-01

Neurons in the brain behave as non-linear oscillators, which develop rhythmic activity and interact to process information1. Taking inspiration from this behavior to realize high density, low power neuromorphic computing will require huge numbers of nanoscale non-linear oscillators. Indeed, a simple estimation indicates that, in order to fit a hundred million oscillators organized in a two-dimensional array inside a chip the size of a thumb, their lateral dimensions must be smaller than one micrometer. However, despite multiple theoretical proposals2–5, and several candidates such as memristive6 or superconducting7 oscillators, there is no proof of concept today of neuromorphic computing with nano-oscillators. Indeed, nanoscale devices tend to be noisy and to lack the stability required to process data in a reliable way. Here, we show experimentally that a nanoscale spintronic oscillator8,9 can achieve spoken digit recognition with accuracies similar to state of the art neural networks. We pinpoint the regime of magnetization dynamics leading to highest performance. These results, combined with the exceptional ability of these spintronic oscillators to interact together, their long lifetime, and low energy consumption, open the path to fast, parallel, on-chip computation based on networks of oscillators. PMID:28748930

Platonic Relationships among Resistors

ERIC Educational Resources Information Center

Allen, Bradley; Liu, Tongtian

2015-01-01

Calculating the effective resistance of an electrical network is a common problem in introductory physics courses. Such calculations are typically restricted to two-dimensional networks, though even such networks can become increasingly complex, leading to several studies on their properties. Furthermore, several authors have used advanced…

A mixed finite difference/Galerkin method for three-dimensional Rayleigh-Benard convection

NASA Technical Reports Server (NTRS)

Buell, Jeffrey C.

1988-01-01

A fast and accurate numerical method, for nonlinear conservation equation systems whose solutions are periodic in two of the three spatial dimensions, is presently implemented for the case of Rayleigh-Benard convection between two rigid parallel plates in the parameter region where steady, three-dimensional convection is known to be stable. High-order streamfunctions secure the reduction of the system of five partial differential equations to a system of only three. Numerical experiments are presented which verify both the expected convergence rates and the absolute accuracy of the method.

Syntheses, crystal structures, and properties of four coordination polymers based on mixed multi-N donor and polycarboxylate ligands

NASA Astrophysics Data System (ADS)

Chen, Shui-Sheng; Guo, Xing-Zhe; Zhao, Yue; Li, Wei-Dong

2018-02-01

Four new coordination polymers [Ni2(HL1)2(L1)3(BTC)2]·6H2O (1), [Ni2(L1)3(HBTC)2]·4H2O (2), [Cd2(L2)(BTC)(H2O)3]·2H2O (3) and [Cd2(HL2)(BTCA)] (4) were synthesized by reactions of nickel(II)/ cadmium(II) salts with rigid ligands of 1,4-di(1H-imidazol-4-yl)benzene (L1), 1,3-di(1-imidazolyl)-5-(4H-tetrazol-5-yl)benzene (HL2) and polycarboxylic acids of 1,3,5-benzenetricarboxylic acid (H3BTC), 1,2,4,5-benzenetetracarboxylic acid (H4BTCA), respectively. The structures of the complexes were determined by single crystal X-ray diffraction analysis. The complex 1 is one-dimensional (1D) chain while 2 is a (4, 4)-connected two-dimensional (2D) layered structure with 2D → 2D parallel interpenetration. Complex 3 is a rare tetranodal (3,4)-connected three-dimensional (3D) CrVTiSc architecture with Point (Schläfli) symbol of (4·82)(4·84·10)(42·82·102)(83), and compound 4 has the 2D network with (4,4) topology based on the [Cd2(COO)4] SBUs. The weak interactions such as hydrogen bonds and π···π stacking contribute to stabilize crystal structure and extend the low-dimensional entities into high-dimensional frameworks. The UV-vis absorption spectra of 1 - 4 are discussed. Moreover, the photo luminescent properties of 3 and 4 and gas sorption property of 2 have been investigated.

Research on parallel load sharing principle of piezoelectric six-dimensional heavy force/torque sensor

NASA Astrophysics Data System (ADS)

Liu, Wei; Li, Ying-jun; Jia, Zhen-yuan; Zhang, Jun; Qian, Min

2011-01-01

In working process of huge heavy-load manipulators, such as the free forging machine, hydraulic die-forging press, forging manipulator, heavy grasping manipulator, large displacement manipulator, measurement of six-dimensional heavy force/torque and real-time force feedback of the operation interface are basis to realize coordinate operation control and force compliance control. It is also an effective way to raise the control accuracy and achieve highly efficient manufacturing. Facing to solve dynamic measurement problem on six-dimensional time-varying heavy load in extremely manufacturing process, the novel principle of parallel load sharing on six-dimensional heavy force/torque is put forward. The measuring principle of six-dimensional force sensor is analyzed, and the spatial model is built and decoupled. The load sharing ratios are analyzed and calculated in vertical and horizontal directions. The mapping relationship between six-dimensional heavy force/torque value to be measured and output force value is built. The finite element model of parallel piezoelectric six-dimensional heavy force/torque sensor is set up, and its static characteristics are analyzed by ANSYS software. The main parameters, which affect load sharing ratio, are analyzed. The experiments for load sharing with different diameters of parallel axis are designed. The results show that the six-dimensional heavy force/torque sensor has good linearity. Non-linearity errors are less than 1%. The parallel axis makes good effect of load sharing. The larger the diameter is, the better the load sharing effect is. The results of experiments are in accordance with the FEM analysis. The sensor has advantages of large measuring range, good linearity, high inherent frequency, and high rigidity. It can be widely used in extreme environments for real-time accurate measurement of six-dimensional time-varying huge loads on manipulators.

Inference of Vohradský's Models of Genetic Networks by Solving Two-Dimensional Function Optimization Problems

PubMed Central

Kimura, Shuhei; Sato, Masanao; Okada-Hatakeyama, Mariko

2013-01-01

The inference of a genetic network is a problem in which mutual interactions among genes are inferred from time-series of gene expression levels. While a number of models have been proposed to describe genetic networks, this study focuses on a mathematical model proposed by Vohradský. Because of its advantageous features, several researchers have proposed the inference methods based on Vohradský's model. When trying to analyze large-scale networks consisting of dozens of genes, however, these methods must solve high-dimensional non-linear function optimization problems. In order to resolve the difficulty of estimating the parameters of the Vohradský's model, this study proposes a new method that defines the problem as several two-dimensional function optimization problems. Through numerical experiments on artificial genetic network inference problems, we showed that, although the computation time of the proposed method is not the shortest, the method has the ability to estimate parameters of Vohradský's models more effectively with sufficiently short computation times. This study then applied the proposed method to an actual inference problem of the bacterial SOS DNA repair system, and succeeded in finding several reasonable regulations. PMID:24386175

Systematic network coding for two-hop lossy transmissions

NASA Astrophysics Data System (ADS)

Li, Ye; Blostein, Steven; Chan, Wai-Yip

2015-12-01

In this paper, we consider network transmissions over a single or multiple parallel two-hop lossy paths. These scenarios occur in applications such as sensor networks or WiFi offloading. Random linear network coding (RLNC), where previously received packets are re-encoded at intermediate nodes and forwarded, is known to be a capacity-achieving approach for these networks. However, a major drawback of RLNC is its high encoding and decoding complexity. In this work, a systematic network coding method is proposed. We show through both analysis and simulation that the proposed method achieves higher end-to-end rate as well as lower computational cost than RLNC for finite field sizes and finite-sized packet transmissions.

Experimental realization of two-dimensional boron sheets

NASA Astrophysics Data System (ADS)

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 sp2 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.

Big Data: A Parallel Particle Swarm Optimization-Back-Propagation Neural Network Algorithm Based on MapReduce.

PubMed

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.

Comparisons Of Two- And Three-Dimensional Convection In Type I X-Ray Bursts

DOE PAGES

Zingale, M.; Malone, C. M.; Nonaka, A.; ...

2015-07-01

We perform the first detailed three-dimensional simulation of low Mach number convection preceding runaway thermonuclear ignition in a mixed H/He X-ray burst. Our simulations include a moderate-sized, approximate network that captures hydrogen and helium burning up through rp-process breakout. We look at the difference between two- and three-dimensional convective fields, including the details of the turbulent convection.

Displacement and deformation measurement for large structures by camera network

NASA Astrophysics Data System (ADS)

Shang, Yang; Yu, Qifeng; Yang, Zhen; Xu, Zhiqiang; Zhang, Xiaohu

2014-03-01

A displacement and deformation measurement method for large structures by a series-parallel connection camera network is presented. By taking the dynamic monitoring of a large-scale crane in lifting operation as an example, a series-parallel connection camera network is designed, and the displacement and deformation measurement method by using this series-parallel connection camera network is studied. The movement range of the crane body is small, and that of the crane arm is large. The displacement of the crane body, the displacement of the crane arm relative to the body and the deformation of the arm are measured. Compared with a pure series or parallel connection camera network, the designed series-parallel connection camera network can be used to measure not only the movement and displacement of a large structure but also the relative movement and deformation of some interesting parts of the large structure by a relatively simple optical measurement system.

Parallel Adaptive Mesh Refinement Library

NASA Technical Reports Server (NTRS)

Mac-Neice, Peter; Olson, Kevin

2005-01-01

Parallel Adaptive Mesh Refinement Library (PARAMESH) is a package of Fortran 90 subroutines designed to provide a computer programmer with an easy route to extension of (1) a previously written serial code that uses a logically Cartesian structured mesh into (2) a parallel code with adaptive mesh refinement (AMR). Alternatively, in its simplest use, and with minimal effort, PARAMESH can operate as a domain-decomposition tool for users who want to parallelize their serial codes but who do not wish to utilize adaptivity. The package builds a hierarchy of sub-grids to cover the computational domain of a given application program, with spatial resolution varying to satisfy the demands of the application. The sub-grid blocks form the nodes of a tree data structure (a quad-tree in two or an oct-tree in three dimensions). Each grid block has a logically Cartesian mesh. The package supports one-, two- and three-dimensional models.

The Software Correlator of the Chinese VLBI Network

NASA Technical Reports Server (NTRS)

Zheng, Weimin; Quan, Ying; Shu, Fengchun; Chen, Zhong; Chen, Shanshan; Wang, Weihua; Wang, Guangli

2010-01-01

The software correlator of the Chinese VLBI Network (CVN) has played an irreplaceable role in the CVN routine data processing, e.g., in the Chinese lunar exploration project. This correlator will be upgraded to process geodetic and astronomical observation data. In the future, with several new stations joining the network, CVN will carry out crustal movement observations, quick UT1 measurements, astrophysical observations, and deep space exploration activities. For the geodetic or astronomical observations, we need a wide-band 10-station correlator. For spacecraft tracking, a realtime and highly reliable correlator is essential. To meet the scientific and navigation requirements of CVN, two parallel software correlators in the multiprocessor environments are under development. A high speed, 10-station prototype correlator using the mixed Pthreads and MPI (Massage Passing Interface) parallel algorithm on a computer cluster platform is being developed. Another real-time software correlator for spacecraft tracking adopts the thread-parallel technology, and it runs on the SMP (Symmetric Multiple Processor) servers. Both correlators have the characteristic of flexible structure and scalability.

Conjugate-Gradient Neural Networks in Classification of Multisource and Very-High-Dimensional Remote Sensing Data

NASA Technical Reports Server (NTRS)

Benediktsson, J. A.; Swain, P. H.; Ersoy, O. K.

1993-01-01

Application of neural networks to classification of remote sensing data is discussed. Conventional two-layer backpropagation is found to give good results in classification of remote sensing data but is not efficient in training. A more efficient variant, based on conjugate-gradient optimization, is used for classification of multisource remote sensing and geographic data and very-high-dimensional data. The conjugate-gradient neural networks give excellent performance in classification of multisource data, but do not compare as well with statistical methods in classification of very-high-dimentional data.

Order parameter for bursting polyrhythms in multifunctional central pattern generators

NASA Astrophysics Data System (ADS)

Wojcik, Jeremy; Clewley, Robert; Shilnikov, Andrey

2011-05-01

We examine multistability of several coexisting bursting patterns in a central pattern generator network composed of three Hodgkin-Huxley type cells coupled reciprocally by inhibitory synapses. We establish that the control of switching between bursting polyrhythms and their bifurcations are determined by the temporal characteristics, such as the duty cycle, of networked interneurons and the coupling strength asymmetry. A computationally effective approach to the reduction of dynamics of the nine-dimensional network to two-dimensional Poincaré return mappings for phase lags between the interneurons is presented.

Optimization by nonhierarchical asynchronous decomposition

NASA Technical Reports Server (NTRS)

Shankar, Jayashree; Ribbens, Calvin J.; Haftka, Raphael T.; Watson, Layne T.

1992-01-01

Large scale optimization problems are tractable only if they are somehow decomposed. Hierarchical decompositions are inappropriate for some types of problems and do not parallelize well. Sobieszczanski-Sobieski has proposed a nonhierarchical decomposition strategy for nonlinear constrained optimization that is naturally parallel. Despite some successes on engineering problems, the algorithm as originally proposed fails on simple two dimensional quadratic programs. The algorithm is carefully analyzed for quadratic programs, and a number of modifications are suggested to improve its robustness.

Accuracy of impressions with different impression materials in angulated implants.

PubMed

Reddy, S; Prasad, K; Vakil, H; Jain, A; Chowdhary, R

2013-01-01

To evaluate the dimensional accuracy of the resultant (duplicative) casts made from two different impression materials (polyvinyl siloxane and polyether) in parallel and angulated implants. Three definitive master casts (control groups) were fabricated in dental stone with three implants, placed at equi-distance. In first group (control), all three implants were placed parallel to each other and perpendicular to the plane of the cast. In the second and third group (control), all three implants were placed at 10° and 15 o angulation respectively to the long axis of the cast, tilting towards the centre. Impressions were made with polyvinyl siloxane and polyether impression materials in a special tray, using a open tray impression technique from the master casts. These impressions were poured to obtain test casts. Three reference distances were evaluated on each test cast by using a profile projector and compared with control groups to determine the effect of combined interaction of implant angulation and impression materials on the accuracy of implant resultant cast. Statistical analysis revealed no significant difference in dimensional accuracy of the resultant casts made from two different impression materials (polyvinyl siloxane and polyether) by closed tray impression technique in parallel and angulated implants. On the basis of the results of this study, the use of both the impression materials i.e., polyether and polyvinyl siloxane impression is recommended for impression making in parallel as well as angulated implants.

Higher-Order Neural Networks Recognize Patterns

NASA Technical Reports Server (NTRS)

Reid, Max B.; Spirkovska, Lilly; Ochoa, Ellen

1996-01-01

Networks of higher order have enhanced capabilities to distinguish between different two-dimensional patterns and to recognize those patterns. Also enhanced capabilities to "learn" patterns to be recognized: "trained" with far fewer examples and, therefore, in less time than necessary to train comparable first-order neural networks.

Throughput Analysis on 3-Dimensional Underwater Acoustic Network with One-Hop Mobile Relay.

PubMed

Zhong, Xuefeng; Chen, Fangjiong; Fan, Jiasheng; Guan, Quansheng; Ji, Fei; Yu, Hua

2018-01-16

Underwater acoustic communication network (UACN) has been considered as an essential infrastructure for ocean exploitation. Performance analysis of UACN is important in underwater acoustic network deployment and management. In this paper, we analyze the network throughput of three-dimensional randomly deployed transmitter-receiver pairs. Due to the long delay of acoustic channels, complicated networking protocols with heavy signaling overhead may not be appropriate. In this paper, we consider only one-hop or two-hop transmission, to save the signaling cost. That is, we assume the transmitter sends the data packet to the receiver by one-hop direct transmission, or by two-hop transmission via mobile relays. We derive the closed-form formulation of packet delivery rate with respect to the transmission delay and the number of transmitter-receiver pairs. The correctness of the derivation results are verified by computer simulations. Our analysis indicates how to obtain a precise tradeoff between the delay constraint and the network capacity.

Throughput Analysis on 3-Dimensional Underwater Acoustic Network with One-Hop Mobile Relay

PubMed Central

Zhong, Xuefeng; Fan, Jiasheng; Guan, Quansheng; Ji, Fei; Yu, Hua

2018-01-01

Underwater acoustic communication network (UACN) has been considered as an essential infrastructure for ocean exploitation. Performance analysis of UACN is important in underwater acoustic network deployment and management. In this paper, we analyze the network throughput of three-dimensional randomly deployed transmitter–receiver pairs. Due to the long delay of acoustic channels, complicated networking protocols with heavy signaling overhead may not be appropriate. In this paper, we consider only one-hop or two-hop transmission, to save the signaling cost. That is, we assume the transmitter sends the data packet to the receiver by one-hop direct transmission, or by two-hop transmission via mobile relays. We derive the closed-form formulation of packet delivery rate with respect to the transmission delay and the number of transmitter–receiver pairs. The correctness of the derivation results are verified by computer simulations. Our analysis indicates how to obtain a precise tradeoff between the delay constraint and the network capacity. PMID:29337911

Long-distance quantum communication over noisy networks without long-time quantum memory

NASA Astrophysics Data System (ADS)

Mazurek, Paweł; Grudka, Andrzej; Horodecki, Michał; Horodecki, Paweł; Łodyga, Justyna; Pankowski, Łukasz; PrzysieŻna, Anna

2014-12-01

The problem of sharing entanglement over large distances is crucial for implementations of quantum cryptography. A possible scheme for long-distance entanglement sharing and quantum communication exploits networks whose nodes share Einstein-Podolsky-Rosen (EPR) pairs. In Perseguers et al. [Phys. Rev. A 78, 062324 (2008), 10.1103/PhysRevA.78.062324] the authors put forward an important isomorphism between storing quantum information in a dimension D and transmission of quantum information in a D +1 -dimensional network. We show that it is possible to obtain long-distance entanglement in a noisy two-dimensional (2D) network, even when taking into account that encoding and decoding of a state is exposed to an error. For 3D networks we propose a simple encoding and decoding scheme based solely on syndrome measurements on 2D Kitaev topological quantum memory. Our procedure constitutes an alternative scheme of state injection that can be used for universal quantum computation on 2D Kitaev code. It is shown that the encoding scheme is equivalent to teleporting the state, from a specific node into a whole two-dimensional network, through some virtual EPR pair existing within the rest of network qubits. We present an analytic lower bound on fidelity of the encoding and decoding procedure, using as our main tool a modified metric on space-time lattice, deviating from a taxicab metric at the first and the last time slices.

An adaptive front tracking technique for three-dimensional transient flows

NASA Astrophysics Data System (ADS)

Galaktionov, O. S.; Anderson, P. D.; Peters, G. W. M.; van de Vosse, F. N.

2000-01-01

An adaptive technique, based on both surface stretching and surface curvature analysis for tracking strongly deforming fluid volumes in three-dimensional flows is presented. The efficiency and accuracy of the technique are demonstrated for two- and three-dimensional flow simulations. For the two-dimensional test example, the results are compared with results obtained using a different tracking approach based on the advection of a passive scalar. Although for both techniques roughly the same structures are found, the resolution for the front tracking technique is much higher. In the three-dimensional test example, a spherical blob is tracked in a chaotic mixing flow. For this problem, the accuracy of the adaptive tracking is demonstrated by the volume conservation for the advected blob. Adaptive front tracking is suitable for simulation of the initial stages of fluid mixing, where the interfacial area can grow exponentially with time. The efficiency of the algorithm significantly benefits from parallelization of the code. Copyright

On an Additive Semigraphoid Model for Statistical Networks With Application to Pathway Analysis.

PubMed

Li, Bing; Chun, Hyonho; Zhao, Hongyu

2014-09-01

We introduce a nonparametric method for estimating non-gaussian graphical models based on a new statistical relation called additive conditional independence, which is a three-way relation among random vectors that resembles the logical structure of conditional independence. Additive conditional independence allows us to use one-dimensional kernel regardless of the dimension of the graph, which not only avoids the curse of dimensionality but also simplifies computation. It also gives rise to a parallel structure to the gaussian graphical model that replaces the precision matrix by an additive precision operator. The estimators derived from additive conditional independence cover the recently introduced nonparanormal graphical model as a special case, but outperform it when the gaussian copula assumption is violated. We compare the new method with existing ones by simulations and in genetic pathway analysis.

Network selection, Information filtering and Scalable computation

NASA Astrophysics Data System (ADS)

Ye, Changqing

This dissertation explores two application scenarios of sparsity pursuit method on large scale data sets. The first scenario is classification and regression in analyzing high dimensional structured data, where predictors corresponds to nodes of a given directed graph. This arises in, for instance, identification of disease genes for the Parkinson's diseases from a network of candidate genes. In such a situation, directed graph describes dependencies among the genes, where direction of edges represent certain causal effects. Key to high-dimensional structured classification and regression is how to utilize dependencies among predictors as specified by directions of the graph. In this dissertation, we develop a novel method that fully takes into account such dependencies formulated through certain nonlinear constraints. We apply the proposed method to two applications, feature selection in large margin binary classification and in linear regression. We implement the proposed method through difference convex programming for the cost function and constraints. Finally, theoretical and numerical analyses suggest that the proposed method achieves the desired objectives. An application to disease gene identification is presented. The second application scenario is personalized information filtering which extracts the information specifically relevant to a user, predicting his/her preference over a large number of items, based on the opinions of users who think alike or its content. This problem is cast into the framework of regression and classification, where we introduce novel partial latent models to integrate additional user-specific and content-specific predictors, for higher predictive accuracy. In particular, we factorize a user-over-item preference matrix into a product of two matrices, each representing a user's preference and an item preference by users. Then we propose a likelihood method to seek a sparsest latent factorization, from a class of over-complete factorizations, possibly with a high percentage of missing values. This promotes additional sparsity beyond rank reduction. Computationally, we design methods based on a ``decomposition and combination'' strategy, to break large-scale optimization into many small subproblems to solve in a recursive and parallel manner. On this basis, we implement the proposed methods through multi-platform shared-memory parallel programming, and through Mahout, a library for scalable machine learning and data mining, for mapReduce computation. For example, our methods are scalable to a dataset consisting of three billions of observations on a single machine with sufficient memory, having good timings. Both theoretical and numerical investigations show that the proposed methods exhibit significant improvement in accuracy over state-of-the-art scalable methods.

Merging parallel tempering with sequential geostatistical resampling for improved posterior exploration of high-dimensional subsurface categorical fields

NASA Astrophysics Data System (ADS)

Laloy, Eric; Linde, Niklas; Jacques, Diederik; Mariethoz, Grégoire

2016-04-01

The sequential geostatistical resampling (SGR) algorithm is a Markov chain Monte Carlo (MCMC) scheme for sampling from possibly non-Gaussian, complex spatially-distributed prior models such as geologic facies or categorical fields. In this work, we highlight the limits of standard SGR for posterior inference of high-dimensional categorical fields with realistically complex likelihood landscapes and benchmark a parallel tempering implementation (PT-SGR). Our proposed PT-SGR approach is demonstrated using synthetic (error corrupted) data from steady-state flow and transport experiments in categorical 7575- and 10,000-dimensional 2D conductivity fields. In both case studies, every SGR trial gets trapped in a local optima while PT-SGR maintains an higher diversity in the sampled model states. The advantage of PT-SGR is most apparent in an inverse transport problem where the posterior distribution is made bimodal by construction. PT-SGR then converges towards the appropriate data misfit much faster than SGR and partly recovers the two modes. In contrast, for the same computational resources SGR does not fit the data to the appropriate error level and hardly produces a locally optimal solution that looks visually similar to one of the two reference modes. Although PT-SGR clearly surpasses SGR in performance, our results also indicate that using a small number (16-24) of temperatures (and thus parallel cores) may not permit complete sampling of the posterior distribution by PT-SGR within a reasonable computational time (less than 1-2 weeks).

Self-organizing neural networks--an alternative way of cluster analysis in clinical chemistry.

PubMed

Reibnegger, G; Wachter, H

1996-04-15

Supervised learning schemes have been employed by several workers for training neural networks designed to solve clinical problems. We demonstrate that unsupervised techniques can also produce interesting and meaningful results. Using a data set on the chemical composition of milk from 22 different mammals, we demonstrate that self-organizing feature maps (Kohonen networks) as well as a modified version of error backpropagation technique yield results mimicking conventional cluster analysis. Both techniques are able to project a potentially multi-dimensional input vector onto a two-dimensional space whereby neighborhood relationships remain conserved. Thus, these techniques can be used for reducing dimensionality of complicated data sets and for enhancing comprehensibility of features hidden in the data matrix.

Four dimensional X-ray imaging of deformation modes in organic-rich Green River Shale retorted under uniaxial compression

NASA Astrophysics Data System (ADS)

Kobchenko, M.; Pluymakers, A.; Cordonnier, B.; Tairova, A.; Renard, F.

2017-12-01

Time-lapse imaging of fracture network development in organic-rich shales at elevated temperatures while kerogen is retorted allows characterizing the development of microfractures and the onset of primary migration. When the solid organic matter is transformed to hydrocarbons with lower molecular weight, the local pore-pressure increases and drives the propagation of hydro-fractures sub-parallel to the shale lamination. On the scale of samples of several mm size, these fractures can be described as mode I opening, where fracture walls dilate in the direction of minimal compression. However, so far experiments coupled to microtomography in situ imaging have been performed on samples where no load was imposed. Here, an external load was applied perpendicular to the sample laminations and we show that this stress state slows down, but does not stop, the propagation of fracture along bedding. Conversely, microfractures also propagate sub-perpendicular to the shale lamination, creating a percolating network in three dimensions. To monitor this process we have used a uniaxial compaction rig combined with in-situ heating from 50 to 500 deg C, while capturing three-dimensional X-ray microtomography scans at a voxel resolution of 2.2 μm; Data were acquired at beamline ID19 at the European Synchrotron Radiation Facility. In total ten time-resolved experiments were performed at different vertical loading conditions, with and without lateral passive confinement and different heating rates. At high external load the sample fails by symmetric bulging, while at lower external load the reaction-induced fracture network develops with the presence of microfractures both sub-parallel and sub-perpendicular to the bedding direction. In addition, the variation of experimental conditions allows the decoupling of the effects of the hydrocarbon decomposition reaction on the deformation process from the influence of thermal stress heating on the weakening and failure mode of immature shale.

Scalable loading of a two-dimensional trapped-ion array

PubMed Central

Bruzewicz, Colin D.; McConnell, Robert; Chiaverini, John; Sage, Jeremy M.

2016-01-01

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. PMID:27677357

Duct flow nonuniformities: Effect of struts in SSME HGM II(+)

NASA Technical Reports Server (NTRS)

Burke, Roger

1988-01-01

A numerical study, using the INS3D flow solver, of laminar and turbulent flow around a two dimensional strut, and three dimensional flow around a strut in an annulus is presented. A multi-block procedure was used to calculate two dimensional laminar flow around two struts in parallel, with each strut represented by one computational block. Single block calculations were performed for turbulent flow around a two dimensional strut, using a Baldwin-Lomax turbulence model to parameterize the turbulent shear stresses. A modified Baldwin-Lomax model was applied to the case of a three dimensional strut in an annulus. The results displayed the essential features of wing-body flows, including the presence of a horseshoe vortex system at the junction of the strut and the lower annulus surface. A similar system was observed at the upper annulus surface. The test geometries discussed were useful in developing the capability to perform multiblock calculations, and to simulate turbulent flow around obstructions located between curved walls. Both of these skills will be necessary to model the three dimensional flow in the strut assembly of the SSME. Work is now in progress on performing a three dimensional two block turbulent calculation of the flow in the turnaround duct (TAD) and strut/fuel bowl juncture region.

Investigations of photosynthetic light harvesting by two-dimensional electronic spectroscopy

NASA Astrophysics Data System (ADS)

Read, Elizabeth Louise

Photosynthesis begins with the harvesting of sunlight by antenna pigments, organized in a network of pigment-protein complexes that rapidly funnel energy to photochemical reaction centers. The intricate design of these systems---the widely varying structural motifs of pigment organization within proteins and protein organization within a larger, cooperative network---underlies the remarkable speed and efficiency of light harvesting. Advances in femtosecond laser spectroscopy have enabled researchers to follow light energy on its course through the energetic levels of photosynthetic systems. Now, newly-developed femtosecond two-dimensional electronic spectroscopy reveals deeper insight into the fundamental molecular interactions and dynamics that emerge in these structures. The following chapters present investigations of a number of natural light-harvesting complexes using two-dimensional electronic spectroscopy. These studies demonstrate the various types of information contained in experimental two-dimensional spectra, and they show that the technique makes it possible to probe pigment-protein complexes on the length- and time-scales relevant to their functioning. New methods are described that further extend the capabilities of two-dimensional electronic spectroscopy, for example, by independently controlling the excitation laser pulse polarizations. The experiments, coupled with theoretical simulation, elucidate spatial pathways of energy flow, unravel molecular and electronic structures, and point to potential new quantum mechanical mechanisms of light harvesting.

Chaos and Robustness in a Single Family of Genetic Oscillatory Networks

PubMed Central

Fu, Daniel; Tan, Patrick; Kuznetsov, Alexey; Molkov, Yaroslav I.

2014-01-01

Genetic oscillatory networks can be mathematically modeled with delay differential equations (DDEs). Interpreting genetic networks with DDEs gives a more intuitive understanding from a biological standpoint. However, it presents a problem mathematically, for DDEs are by construction infinitely-dimensional and thus cannot be analyzed using methods common for systems of ordinary differential equations (ODEs). In our study, we address this problem by developing a method for reducing infinitely-dimensional DDEs to two- and three-dimensional systems of ODEs. We find that the three-dimensional reductions provide qualitative improvements over the two-dimensional reductions. We find that the reducibility of a DDE corresponds to its robustness. For non-robust DDEs that exhibit high-dimensional dynamics, we calculate analytic dimension lines to predict the dependence of the DDEs’ correlation dimension on parameters. From these lines, we deduce that the correlation dimension of non-robust DDEs grows linearly with the delay. On the other hand, for robust DDEs, we find that the period of oscillation grows linearly with delay. We find that DDEs with exclusively negative feedback are robust, whereas DDEs with feedback that changes its sign are not robust. We find that non-saturable degradation damps oscillations and narrows the range of parameter values for which oscillations exist. Finally, we deduce that natural genetic oscillators with highly-regular periods likely have solely negative feedback. PMID:24667178

2-Amino-4,6-dimethyl­pyrimidin-1-ium chloride

PubMed Central

Hu, Hui-Ling; Yeh, Chun-Wei

2012-01-01

In the title compound, C6H10N3 +·Cl−, the cation is essentially planar with an r.m.s. deviations of the fitted atoms of 0.008 Å. In the crystal, adjacent ions are linked by weak N—H⋯Cl hydrogen bonds involving the pyrimidine and amine N atoms, forming a three-dimensional network. C—H⋯π inter­actions between the methyl and pyrimidine groups and π–π stacking [centroid–centroid distance = 3.474 (1) Å] between parallel pyrimidine ring systems are also observed. PMID:23476204

Aligned 1-D nanorods of a π-gelator exhibit molecular orientation and excitation energy transport different from entangled fiber networks.

PubMed

Sakakibara, Keita; Chithra, Parayalil; Das, Bidisa; Mori, Taizo; Akada, Misaho; Labuta, Jan; Tsuruoka, Tohru; Maji, Subrata; Furumi, Seiichi; Shrestha, Lok Kumar; Hill, Jonathan P; Acharya, Somobrata; Ariga, Katsuhiko; Ajayaghosh, Ayyappanpillai

2014-06-18

Linear π-gelators self-assemble into entangled fibers in which the molecules are arranged perpendicular to the fiber long axis. However, orientation of gelator molecules in a direction parallel to the long axes of the one-dimensional (1-D) structures remains challenging. Herein we demonstrate that, at the air-water interface, an oligo(p-phenylenevinylene)-derived π-gelator forms aligned nanorods of 340 ± 120 nm length and 34 ± 5 nm width, in which the gelator molecules are reoriented parallel to the long axis of the rods. The orientation change of the molecules results in distinct excited-state properties upon local photoexcitation, as evidenced by near-field scanning optical microscopy. A detailed understanding of the mechanism by which excitation energy migrates through these 1-D molecular assemblies might help in the design of supramolecular structures with improved charge-transport properties.

Frequency domain model for analysis of paralleled, series-output-connected Mapham inverters

NASA Technical Reports Server (NTRS)

Brush, Andrew S.; Sundberg, Richard C.; Button, Robert M.

1989-01-01

The Mapham resonant inverter is characterized as a two-port network driven by a selected periodic voltage. The two-port model is then used to model a pair of Mapham inverters connected in series and employing phasor voltage regulation. It is shown that the model is useful for predicting power output in paralleled inverter units, and for predicting harmonic current output of inverter pairs, using standard power flow techniques. Some sample results are compared to data obtained from testing hardware inverters.

Frequency domain model for analysis of paralleled, series-output-connected Mapham inverters

NASA Technical Reports Server (NTRS)

Brush, Andrew S.; Sundberg, Richard C.; Button, Robert M.

1989-01-01

The Mapham resonant inverter is characterized as a two-port network driven by a selected periodic voltage. The two-port model is then used to model a pair of Mapham inverters connected in series and employing phasor voltage regulation. It is shown that the model is useful for predicting power output in paralleled inverter units, and for predicting harmonic current output of inverter pairs, using standard power flow techniques. Some examples are compared to data obtained from testing hardware inverters.

Logarithmic Superdiffusion in Two Dimensional Driven Lattice Gases

NASA Astrophysics Data System (ADS)

Krug, J.; Neiss, R. A.; Schadschneider, A.; Schmidt, J.

2018-03-01

The spreading of density fluctuations in two-dimensional driven diffusive systems is marginally anomalous. Mode coupling theory predicts that the diffusivity in the direction of the drive diverges with time as (ln t)^{2/3} with a prefactor depending on the macroscopic current-density relation and the diffusion tensor of the fluctuating hydrodynamic field equation. Here we present the first numerical verification of this behavior for a particular version of the two-dimensional asymmetric exclusion process. Particles jump strictly asymmetrically along one of the lattice directions and symmetrically along the other, and an anisotropy parameter p governs the ratio between the two rates. Using a novel massively parallel coupling algorithm that strongly reduces the fluctuations in the numerical estimate of the two-point correlation function, we are able to accurately determine the exponent of the logarithmic correction. In addition, the variation of the prefactor with p provides a stringent test of mode coupling theory.

Distributed parallel messaging for multiprocessor systems

DOEpatents

Chen, Dong; Heidelberger, Philip; Salapura, Valentina; Senger, Robert M; Steinmacher-Burrow, Burhard; Sugawara, Yutaka

2013-06-04

A method and apparatus for distributed parallel messaging in a parallel computing system. The apparatus includes, at each node of a multiprocessor network, multiple injection messaging engine units and reception messaging engine units, each implementing a DMA engine and each supporting both multiple packet injection into and multiple reception from a network, in parallel. The reception side of the messaging unit (MU) includes a switch interface enabling writing of data of a packet received from the network to the memory system. The transmission side of the messaging unit, includes switch interface for reading from the memory system when injecting packets into the network.

Generation of Rising-tone Chorus in a Two-dimensional Mirror Field by Using the General Curvilinear PIC Code

NASA Astrophysics Data System (ADS)

Ke, Y.; Gao, X.; Lu, Q.; Wang, X.; Wang, S.

2017-12-01

Recently, the generation of rising-tone chorus has been implemented with one-dimensional (1-D) particle-in-cell (PIC) simulations in an inhomogeneous background magnetic field, where both the propagation of waves and motion of electrons are simply forced to be parallel to the background magnetic field. We have developed a two-dimensional(2-D) general curvilinear PIC simulation code, and successfully reproduced rising-tone chorus waves excited from an anisotropic electron distribution in a 2-D mirror field. Our simulation results show that whistler waves are mainly generated around the magnetic equator, and continuously gain growth during their propagation toward higher-latitude regions. The rising-tone chorus waves are formed off the magnetic equator, which propagate quasi-parallel to the background magnetic field with the finite wave normal angle. Due to the propagating effect, the wave normal angle of chorus waves is increasing during their propagation toward higher-latitude regions along an enough curved field line. The chirping rate of chorus waves are found to be larger along a field line more close to the middle field line in the mirror field.

Generation of rising-tone chorus in a two-dimensional mirror field by using the general curvilinear PIC code

NASA Astrophysics Data System (ADS)

Ke, Yangguang; Gao, Xinliang; Lu, Quanming; Wang, Xueyi; Wang, Shui

2017-08-01

Recently, the generation of rising-tone chorus has been implemented with one-dimensional (1-D) particle-in-cell (PIC) simulations in an inhomogeneous background magnetic field, where both the propagation of waves and motion of electrons are simply forced to be parallel to the background magnetic field. In this paper, we have developed a two-dimensional (2-D) general curvilinear PIC simulation code and successfully reproduced rising-tone chorus waves excited from an anisotropic electron distribution in a 2-D mirror field. Our simulation results show that whistler waves are mainly generated around the magnetic equator and continuously gain growth during their propagation toward higher-latitude regions. The rising-tone chorus waves are observed off the magnetic equator, which propagate quasi-parallel to the background magnetic field with the wave normal angle smaller than 25°. Due to the propagating effect, the wave normal angle of chorus waves is increasing during their propagation toward higher-latitude regions along an enough curved field line. The chirping rate of chorus waves is found to be larger along a field line with a smaller curvature.

Determination of statistics for any rotation of axes of a bivariate normal elliptical distribution. [of wind vector components

NASA Technical Reports Server (NTRS)

Falls, L. W.; Crutcher, H. L.

1976-01-01

Transformation of statistics from a dimensional set to another dimensional set involves linear functions of the original set of statistics. Similarly, linear functions will transform statistics within a dimensional set such that the new statistics are relevant to a new set of coordinate axes. A restricted case of the latter is the rotation of axes in a coordinate system involving any two correlated random variables. A special case is the transformation for horizontal wind distributions. Wind statistics are usually provided in terms of wind speed and direction (measured clockwise from north) or in east-west and north-south components. A direct application of this technique allows the determination of appropriate wind statistics parallel and normal to any preselected flight path of a space vehicle. Among the constraints for launching space vehicles are critical values selected from the distribution of the expected winds parallel to and normal to the flight path. These procedures are applied to space vehicle launches at Cape Kennedy, Florida.

Parallel phase-sensitive three-dimensional imaging camera

DOEpatents

Smithpeter, Colin L.; Hoover, Eddie R.; Pain, Bedabrata; Hancock, Bruce R.; Nellums, Robert O.

2007-09-25

An apparatus is disclosed for generating a three-dimensional (3-D) image of a scene illuminated by a pulsed light source (e.g. a laser or light-emitting diode). The apparatus, referred to as a phase-sensitive 3-D imaging camera utilizes a two-dimensional (2-D) array of photodetectors to receive light that is reflected or scattered from the scene and processes an electrical output signal from each photodetector in the 2-D array in parallel using multiple modulators, each having inputs of the photodetector output signal and a reference signal, with the reference signal provided to each modulator having a different phase delay. The output from each modulator is provided to a computational unit which can be used to generate intensity and range information for use in generating a 3-D image of the scene. The 3-D camera is capable of generating a 3-D image using a single pulse of light, or alternately can be used to generate subsequent 3-D images with each additional pulse of light.

Bifurcations of large networks of two-dimensional integrate and fire neurons.

PubMed

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.

Parallel computing using a Lagrangian formulation

NASA Technical Reports Server (NTRS)

Liou, May-Fun; Loh, Ching-Yuen

1992-01-01

This paper adopts a new Lagrangian formulation of the Euler equation for the calculation of two dimensional supersonic steady flow. The Lagrangian formulation represents the inherent parallelism of the flow field better than the common Eulerian formulation and offers a competitive alternative on parallel computers. The implementation of the Lagrangian formulation on the Thinking Machines Corporation CM-2 Computer is described. The program uses a finite volume, first-order Godunov scheme and exhibits high accuracy in dealing with multidimensional discontinuities (slip-line and shock). By using this formulation, we have achieved better than six times speed-up on a 8192-processor CM-2 over a single processor of a CRAY-2.

Implementation of Parallel Dynamic Simulation on Shared-Memory vs. Distributed-Memory Environments

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

Jin, Shuangshuang; Chen, Yousu; Wu, Di

2015-12-09

Power system dynamic simulation computes the system response to a sequence of large disturbance, such as sudden changes in generation or load, or a network short circuit followed by protective branch switching operation. It consists of a large set of differential and algebraic equations, which is computational intensive and challenging to solve using single-processor based dynamic simulation solution. High-performance computing (HPC) based parallel computing is a very promising technology to speed up the computation and facilitate the simulation process. This paper presents two different parallel implementations of power grid dynamic simulation using Open Multi-processing (OpenMP) on shared-memory platform, and Messagemore » Passing Interface (MPI) on distributed-memory clusters, respectively. The difference of the parallel simulation algorithms and architectures of the two HPC technologies are illustrated, and their performances for running parallel dynamic simulation are compared and demonstrated.« less

Two interpenetrating Cu{sup II}/Ni{sup II}-coordinated polymers based on an unsymmetrical bifunctional N/O-tectonic: Syntheses, structures and magnetic properties

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

Liu, Yong-Liang; Department of Chemistry and Chemical Engineering, Shaanxi Key Laboratory of Comprehensive Utilization of Tailings Resources, Shang Luo University, Shang Luo 726000; Wu, Ya-Pan

2015-03-15

Two new interpenetrating Cu{sup II}/Ni{sup II} coordination polymers, based on a unsymmetrical bifunctional N/O-tectonic 3-(pyrid-4′-yl)-5-(4″-carbonylphenyl)-1,2,4-triazolyl (H{sub 2}pycz), ([Cu-(Hpycz){sub 2}]·2H{sub 2}O){sub n} (1) and ([Ni(Hpycz){sub 2}]·H{sub 2}O){sub n} (2), have been solvothermally synthesized and structure characterization. Single crystal X-ray analysis indicates that compound 1 shows 2-fold parallel interpenetrated 4{sup 4}-sql layers with the same handedness. The overall structure of 1 is achiral—in each layer of doubly interpenetrating nets, the two individual nets have the opposite handedness to the corresponding nets in the adjoining layers—while 2 features a rare 8-fold interpenetrating 6{sup 6}-dia network that belongs to class IIIa interpenetration. In addition,more » compounds 1 and 2 both show similar paramagnetic characteristic properties. - Graphical abstract: Two new Cu(II)/Ni(II) coordination polymers present 2D parallel 2-fold interpenetrated 4{sup 4}-sql layers and a rare 3D 8-fold interpenetrating 6{sup 6}-dia network. In addition, magnetic susceptibility measurements show similar paramagnetic characteristic for two complexes. - Highlights: • A new unsymmetrical bifunctional N/O-tectonic as 4-connected spacer. • A 2-fold parallel interpenetrated sql layer with the same handedness. • A rare 8-fold interpenetrating dia network (class IIIa)« less

A High-Order Method Using Unstructured Grids for the Aeroacoustic Analysis of Realistic Aircraft Configurations

NASA Technical Reports Server (NTRS)

Atkins, Harold L.; Lockard, David P.

1999-01-01

A method for the prediction of acoustic scatter from complex geometries is presented. The discontinuous Galerkin method provides a framework for the development of a high-order method using unstructured grids. The method's compact form contributes to its accuracy and efficiency, and makes the method well suited for distributed memory parallel computing platforms. Mesh refinement studies are presented to validate the expected convergence properties of the method, and to establish the absolute levels of a error one can expect at a given level of resolution. For a two-dimensional shear layer instability wave and for three-dimensional wave propagation, the method is demonstrated to be insensitive to mesh smoothness. Simulations of scatter from a two-dimensional slat configuration and a three-dimensional blended-wing-body demonstrate the capability of the method to efficiently treat realistic geometries.

A neural network approach for image reconstruction in electron magnetic resonance tomography.

PubMed

Durairaj, D Christopher; Krishna, Murali C; Murugesan, Ramachandran

2007-10-01

An object-oriented, artificial neural network (ANN) based, application system for reconstruction of two-dimensional spatial images in electron magnetic resonance (EMR) tomography is presented. The standard back propagation algorithm is utilized to train a three-layer sigmoidal feed-forward, supervised, ANN to perform the image reconstruction. The network learns the relationship between the 'ideal' images that are reconstructed using filtered back projection (FBP) technique and the corresponding projection data (sinograms). The input layer of the network is provided with a training set that contains projection data from various phantoms as well as in vivo objects, acquired from an EMR imager. Twenty five different network configurations are investigated to test the ability of the generalization of the network. The trained ANN then reconstructs two-dimensional temporal spatial images that present the distribution of free radicals in biological systems. Image reconstruction by the trained neural network shows better time complexity than the conventional iterative reconstruction algorithms such as multiplicative algebraic reconstruction technique (MART). The network is further explored for image reconstruction from 'noisy' EMR data and the results show better performance than the FBP method. The network is also tested for its ability to reconstruct from limited-angle EMR data set.

Two Dimensional Array Based Overlay Network for Balancing Load of Peer-to-Peer Live Video Streaming

NASA Astrophysics Data System (ADS)

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.

Acoustic receptivity and transition modeling of Tollmien-Schlichting disturbances induced by distributed surface roughness

NASA Astrophysics Data System (ADS)

Raposo, Henrique; Mughal, Shahid; Ashworth, Richard

2018-04-01

Acoustic receptivity to Tollmien-Schlichting waves in the presence of surface roughness is investigated for a flat plate boundary layer using the time-harmonic incompressible linearized Navier-Stokes equations. It is shown to be an accurate and efficient means of predicting receptivity amplitudes and, therefore, to be more suitable for parametric investigations than other approaches with direct-numerical-simulation-like accuracy. Comparison with the literature provides strong evidence of the correctness of the approach, including the ability to quantify non-parallel flow effects. These effects are found to be small for the efficiency function over a wide range of frequencies and local Reynolds numbers. In the presence of a two-dimensional wavy-wall, non-parallel flow effects are quite significant, producing both wavenumber detuning and an increase in maximum amplitude. However, a smaller influence is observed when considering an oblique Tollmien-Schlichting wave. This is explained by considering the non-parallel effects on receptivity and on linear growth which may, under certain conditions, cancel each other out. Ultimately, we undertake a Monte Carlo type uncertainty quantification analysis with two-dimensional distributed random roughness. Its power spectral density (PSD) is assumed to follow a power law with an associated uncertainty following a probabilistic Gaussian distribution. The effects of the acoustic frequency over the mean amplitude of the generated two-dimensional Tollmien-Schlichting waves are studied. A strong dependence on the mean PSD shape is observed and discussed according to the basic resonance mechanisms leading to receptivity. The growth of Tollmien-Schlichting waves is predicted with non-linear parabolized stability equations computations to assess the effects of stochasticity in transition location.

Storm Observations of Persistent Three-Dimensional Shoreline Morphology and Bathymetry Along a Geologically Influenced Shoreface Using X-Band Radar (BASIR)

NASA Astrophysics Data System (ADS)

Brodie, K. L.; McNinch, J. E.

2008-12-01

Accurate predictions of shoreline response to storms are contingent upon coastal-morphodynamic models effectively synthesizing the complex evolving relationships between beach topography, sandbar morphology, nearshore bathymetry, underlying geology, and the nearshore wave-field during storm events. Analysis of "pre" and "post" storm data sets have led to a common theory for event response of the nearshore system: pre-storm three-dimensional bar and shoreline configurations shift to two-dimensional, linear forms post- storm. A lack of data during storms has unfortunately left a gap in our knowledge of how the system explicitly changes during the storm event. This work presents daily observations of the beach and nearshore during high-energy storm events over a spatially extensive field site (order of magnitude: 10 km) using Bar and Swash Imaging Radar (BASIR), a mobile x-band radar system. The field site contains a complexity of features including shore-oblique bars and troughs, heterogeneous sediment, and an erosional hotspot. BASIR data provide observations of the evolution of shoreline and bar morphology, as well as nearshore bathymetry, throughout the storm events. Nearshore bathymetry is calculated using a bathymetry inversion from radar- derived wave celerity measurements. Preliminary results show a relatively stable but non-linear shore-parallel bar and a non-linear shoreline with megacusp and embayment features (order of magnitude: 1 km) that are enhanced during the wave events. Both the shoreline and shore-parallel bar undulate at a similar spatial frequency to the nearshore shore- oblique bar-field. Large-scale shore-oblique bars and troughs remain relatively static in position and morphology throughout the storm events. The persistence of a three-dimensional shoreline, shore-parallel bar, and large-scale shore-oblique bars and troughs, contradicts the idea of event-driven shifts to two- dimensional morphology and suggests that beach and nearshore response to storms may be location specific. We hypothesize that the influence of underlying geology, defined by (1) the introduction of heterogeneous sediment and (2) the possible creation of shore-oblique bars and troughs in the nearshore, may be responsible for the persistence of three-dimensional forms and the associated shoreline hotspots during storm events.

Providing nearest neighbor point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer

DOEpatents

Archer, Charles J.; Faraj, Ahmad A.; Inglett, Todd A.; Ratterman, Joseph D.

2012-10-23

Methods, apparatus, and products are disclosed for providing nearest neighbor point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer, each compute node connected to each adjacent compute node in the global combining network through a link, that include: identifying each link in the global combining network for each compute node of the operational group; designating one of a plurality of point-to-point class routing identifiers for each link such that no compute node in the operational group is connected to two adjacent compute nodes in the operational group with links designated for the same class routing identifiers; and configuring each compute node of the operational group for point-to-point communications with each adjacent compute node in the global combining network through the link between that compute node and that adjacent compute node using that link's designated class routing identifier.

Two-dimensional radiant energy array computers and computing devices

NASA Technical Reports Server (NTRS)

Schaefer, D. H.; Strong, J. P., III (Inventor)

1976-01-01

Two dimensional digital computers and computer devices operate in parallel on rectangular arrays of digital radiant energy optical signal elements which are arranged in ordered rows and columns. Logic gate devices receive two input arrays and provide an output array having digital states dependent only on the digital states of the signal elements of the two input arrays at corresponding row and column positions. The logic devices include an array of photoconductors responsive to at least one of the input arrays for either selectively accelerating electrons to a phosphor output surface, applying potentials to an electroluminescent output layer, exciting an array of discrete radiant energy sources, or exciting a liquid crystal to influence crystal transparency or reflectivity.

A neural-network approach to robotic control

NASA Technical Reports Server (NTRS)

Graham, D. P. W.; Deleuterio, G. M. T.

1993-01-01

An artificial neural-network paradigm for the control of robotic systems is presented. The approach is based on the Cerebellar Model Articulation Controller created by James Albus and incorporates several extensions. First, recognizing the essential structure of multibody equations of motion, two parallel modules are used that directly reflect the dynamical characteristics of multibody systems. Second, the architecture of the proposed network is imbued with a self-organizational capability which improves efficiency and accuracy. Also, the networks can be arranged in hierarchical fashion with each subsequent network providing finer and finer resolution.

Order-disorder transition in a two-dimensional boron-carbon-nitride alloy

NASA Astrophysics Data System (ADS)

Lu, Jiong; Zhang, Kai; Feng Liu, Xin; Zhang, Han; Chien Sum, Tze; Castro Neto, Antonio H.; Loh, Kian Ping

2013-10-01

Two-dimensional boron-carbon-nitride materials exhibit a spectrum of electronic properties ranging from insulating to semimetallic, depending on their composition and geometry. Detailed experimental insights into the phase separation and ordering in such alloy are currently lacking. Here we report the mixing and demixing of boron-nitrogen and carbon phases on ruthenium (0001) and found that energetics for such processes are modified by the metal substrate. The brick-and-mortar patchwork observed of stoichiometrically percolated hexagonal boron-carbon-nitride domains surrounded by a network of segregated graphene nanoribbons can be described within the Blume-Emery-Griffiths model applied to a honeycomb lattice. The isostructural boron nitride and graphene assumes remarkable fluidity and can be exchanged entirely into one another by a catalytically assistant substitution. Visualizing the dynamics of phase separation at the atomic level provides the premise for enabling structural control in a two-dimensional network for broad nanotechnology applications.

Nebula: reconstruction and visualization of scattering data in reciprocal space.

PubMed

Reiten, Andreas; Chernyshov, Dmitry; Mathiesen, Ragnvald H

2015-04-01

Two-dimensional solid-state X-ray detectors can now operate at considerable data throughput rates that allow full three-dimensional sampling of scattering data from extended volumes of reciprocal space within second to minute time-scales. For such experiments, simultaneous analysis and visualization allows for remeasurements and a more dynamic measurement strategy. A new software, Nebula , is presented. It efficiently reconstructs X-ray scattering data, generates three-dimensional reciprocal space data sets that can be visualized interactively, and aims to enable real-time processing in high-throughput measurements by employing parallel computing on commodity hardware.

Nebula: reconstruction and visualization of scattering data in reciprocal space

PubMed Central

Reiten, Andreas; Chernyshov, Dmitry; Mathiesen, Ragnvald H.

2015-01-01

Two-dimensional solid-state X-ray detectors can now operate at considerable data throughput rates that allow full three-dimensional sampling of scattering data from extended volumes of reciprocal space within second to minute time­scales. For such experiments, simultaneous analysis and visualization allows for remeasurements and a more dynamic measurement strategy. A new software, Nebula, is presented. It efficiently reconstructs X-ray scattering data, generates three-dimensional reciprocal space data sets that can be visualized interactively, and aims to enable real-time processing in high-throughput measurements by employing parallel computing on commodity hardware. PMID:25844083

Network control processor for a TDMA system

NASA Astrophysics Data System (ADS)

Suryadevara, Omkarmurthy; Debettencourt, Thomas J.; Shulman, R. B.

Two unique aspects of designing a network control processor (NCP) to monitor and control a demand-assigned, time-division multiple-access (TDMA) network are described. The first involves the implementation of redundancy by synchronizing the databases of two geographically remote NCPs. The two sets of databases are kept in synchronization by collecting data on both systems, transferring databases, sending incremental updates, and the parallel updating of databases. A periodic audit compares the checksums of the databases to ensure synchronization. The second aspect involves the use of a tracking algorithm to dynamically reallocate TDMA frame space. This algorithm detects and tracks current and long-term load changes in the network. When some portions of the network are overloaded while others have excess capacity, the algorithm automatically calculates and implements a new burst time plan.

A parallel input composite transimpedance amplifier.

PubMed

Kim, D J; Kim, C

2018-01-01

A new approach to high performance current to voltage preamplifier design is presented. The design using multiple operational amplifiers (op-amps) has a parasitic capacitance compensation network and a composite amplifier topology for fast, precision, and low noise performance. The input stage consisting of a parallel linked JFET op-amps and a high-speed bipolar junction transistor (BJT) gain stage driving the output in the composite amplifier topology, cooperating with the capacitance compensation feedback network, ensures wide bandwidth stability in the presence of input capacitance above 40 nF. The design is ideal for any two-probe measurement, including high impedance transport and scanning tunneling microscopy measurements.

A parallel input composite transimpedance amplifier

NASA Astrophysics Data System (ADS)

Kim, D. J.; Kim, C.

2018-01-01

A new approach to high performance current to voltage preamplifier design is presented. The design using multiple operational amplifiers (op-amps) has a parasitic capacitance compensation network and a composite amplifier topology for fast, precision, and low noise performance. The input stage consisting of a parallel linked JFET op-amps and a high-speed bipolar junction transistor (BJT) gain stage driving the output in the composite amplifier topology, cooperating with the capacitance compensation feedback network, ensures wide bandwidth stability in the presence of input capacitance above 40 nF. The design is ideal for any two-probe measurement, including high impedance transport and scanning tunneling microscopy measurements.

Quasirandom geometric networks from low-discrepancy sequences

NASA Astrophysics Data System (ADS)

Estrada, Ernesto

2017-08-01

We define quasirandom geometric networks using low-discrepancy sequences, such as Halton, Sobol, and Niederreiter. The networks are built in d dimensions by considering the d -tuples of digits generated by these sequences as the coordinates of the vertices of the networks in a d -dimensional Id unit hypercube. Then, two vertices are connected by an edge if they are at a distance smaller than a connection radius. We investigate computationally 11 network-theoretic properties of two-dimensional quasirandom networks and compare them with analogous random geometric networks. We also study their degree distribution and their spectral density distributions. We conclude from this intensive computational study that in terms of the uniformity of the distribution of the vertices in the unit square, the quasirandom networks look more random than the random geometric networks. We include an analysis of potential strategies for generating higher-dimensional quasirandom networks, where it is know that some of the low-discrepancy sequences are highly correlated. In this respect, we conclude that up to dimension 20, the use of scrambling, skipping and leaping strategies generate quasirandom networks with the desired properties of uniformity. Finally, we consider a diffusive process taking place on the nodes and edges of the quasirandom and random geometric graphs. We show that the diffusion time is shorter in the quasirandom graphs as a consequence of their larger structural homogeneity. In the random geometric graphs the diffusion produces clusters of concentration that make the process more slow. Such clusters are a direct consequence of the heterogeneous and irregular distribution of the nodes in the unit square in which the generation of random geometric graphs is based on.

Neural networks for vertical microcode compaction

NASA Astrophysics Data System (ADS)

Chu, Pong P.

1992-09-01

Neural networks provide an alternative way to solve complex optimization problems. Instead of performing a program of instructions sequentially as in a traditional computer, neural network model explores many competing hypotheses simultaneously using its massively parallel net. The paper shows how to use the neural network approach to perform vertical micro-code compaction for a micro-programmed control unit. The compaction procedure includes two basic steps. The first step determines the compatibility classes and the second step selects a minimal subset to cover the control signals. Since the selection process is an NP- complete problem, to find an optimal solution is impractical. In this study, we employ a customized neural network to obtain the minimal subset. We first formalize this problem, and then define an `energy function' and map it to a two-layer fully connected neural network. The modified network has two types of neurons and can always obtain a valid solution.

7-Meth­oxy­indan-1-one

PubMed Central

Chang, Yuan Jay; Chen, Kew-Yu

2012-01-01

In the title compound, C10H10O2, the 1-indanone unit is essentially planar (r.m.s. deviation = 0.028 Å). In the crystal, molecules are linked via C—H⋯O hydrogen bonds, forming layers lying parallel to the ab plane. This two-dimensional structure is stabilized by a weak C—H⋯π inter­action. A second weak C—H⋯π inter­action links the layers, forming a three-dimensional structure. PMID:23284398

Development of a Three-Dimensional PSE Code for Compressible Flows: Stability of Three-Dimensional Compressible Boundary Layers

NASA Technical Reports Server (NTRS)

Balakumar, P.; Jeyasingham, Samarasingham

1999-01-01

A program is developed to investigate the linear stability of three-dimensional compressible boundary layer flows over bodies of revolutions. The problem is formulated as a two dimensional (2D) eigenvalue problem incorporating the meanflow variations in the normal and azimuthal directions. Normal mode solutions are sought in the whole plane rather than in a line normal to the wall as is done in the classical one dimensional (1D) stability theory. The stability characteristics of a supersonic boundary layer over a sharp cone with 50 half-angle at 2 degrees angle of attack is investigated. The 1D eigenvalue computations showed that the most amplified disturbances occur around x(sub 2) = 90 degrees and the azimuthal mode number for the most amplified disturbances range between m = -30 to -40. The frequencies of the most amplified waves are smaller in the middle region where the crossflow dominates the instability than the most amplified frequencies near the windward and leeward planes. The 2D eigenvalue computations showed that due to the variations in the azimuthal direction, the eigenmodes are clustered into isolated confined regions. For some eigenvalues, the eigenfunctions are clustered in two regions. Due to the nonparallel effect in the azimuthal direction, the eigenmodes are clustered into isolated confined regions. For some eigenvalues, the eigenfunctions are clustered in two regions. Due to the nonparallel effect in the azimuthal direction, the most amplified disturbances are shifted to 120 degrees compared to 90 degrees for the parallel theory. It is also observed that the nonparallel amplification rates are smaller than that is obtained from the parallel theory.

Generalized three-dimensional lattice Boltzmann color-gradient method for immiscible two-phase pore-scale imbibition and drainage in porous media

NASA Astrophysics Data System (ADS)

Leclaire, Sébastien; Parmigiani, Andrea; Malaspinas, Orestis; Chopard, Bastien; Latt, Jonas

2017-03-01

This article presents a three-dimensional numerical framework for the simulation of fluid-fluid immiscible compounds in complex geometries, based on the multiple-relaxation-time lattice Boltzmann method to model the fluid dynamics and the color-gradient approach to model multicomponent flow interaction. New lattice weights for the lattices D3Q15, D3Q19, and D3Q27 that improve the Galilean invariance of the color-gradient model as well as for modeling the interfacial tension are derived and provided in the Appendix. The presented method proposes in particular an approach to model the interaction between the fluid compound and the solid, and to maintain a precise contact angle between the two-component interface and the wall. Contrarily to previous approaches proposed in the literature, this method yields accurate solutions even in complex geometries and does not suffer from numerical artifacts like nonphysical mass transfer along the solid wall, which is crucial for modeling imbibition-type problems. The article also proposes an approach to model inflow and outflow boundaries with the color-gradient method by generalizing the regularized boundary conditions. The numerical framework is first validated for three-dimensional (3D) stationary state (Jurin's law) and time-dependent (Washburn's law and capillary waves) problems. Then, the usefulness of the method for practical problems of pore-scale flow imbibition and drainage in porous media is demonstrated. Through the simulation of nonwetting displacement in two-dimensional random porous media networks, we show that the model properly reproduces three main invasion regimes (stable displacement, capillary fingering, and viscous fingering) as well as the saturating zone transition between these regimes. Finally, the ability to simulate immiscible two-component flow imbibition and drainage is validated, with excellent results, by numerical simulations in a Berea sandstone, a frequently used benchmark case used in this field, using a complex geometry that originates from a 3D scan of a porous sandstone. The methods presented in this article were implemented in the open-source PALABOS library, a general C++ matrix-based library well adapted for massive fluid flow parallel computation.

An obstacle to building a time machine

NASA Astrophysics Data System (ADS)

Carroll, Sean M.; Farhi, Edward; Guth, Alan H.

1992-01-01

Gott (1991) has shown that a spacetime with two infinite parallel cosmic strings passing each other with sufficient velocity contains closed timelike curves. An attempt to build such a time machine is discussed. Using the energy-momentum conservation laws in the equivalent (2 + 1)-dimensional theory, the spacetime representing the decay of one gravitating particle into two is explicitly constructed; there is never enough mass in an open universe to build the time machine from the products of decays of stationary particles. More generally, the Gott time machine cannot exist in any open (2 + 1)-dimensional universe for which the total momentum is timelike.

DESIGN OF A PATTERN RECOGNITION DIGITAL COMPUTER WITH APPLICATION TO THE AUTOMATIC SCANNING OF BUBBLE CHAMBER NEGATIVES

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

McCormick, B.H.; Narasimhan, R.

1963-01-01

The overall computer system contains three main parts: an input device, a pattern recognition unit (PRU), and a control computer. The bubble chamber picture is divided into a grid of st run. Concent 1-mm squares on the film. It is then processed in parallel in a two-dimensional array of 1024 identical processing modules (stalactites) of the PRU. The array can function as a two- dimensional shift register in which results of successive shifting operations can be accumulated. The pattern recognition process is generally controlled by a conventional arithmetic computer. (A.G.W.)

Two-dimensional infrared spectroscopy of supercooled water.

PubMed

Perakis, Fivos; Hamm, Peter

2011-05-12

We present two-dimensional infrared (2D IR) spectra of the OD stretch vibration of isotope diluted water (HOD/H(2)O) from ambient conditions (293 K) down to the metastable supercooled regime (260 K). We observe that spectral diffusion slows down from 700 fs to 2.6 ps as we lower the temperature. A comparison between measurements performed at the magic angle with those at parallel polarization shows that the 2D IR line shape is affected by the frequency-dependent anisotropy decay in the case of parallel polarization, altering the extracted correlation decay. A fit within the framework of an Arrhenius law reveals an activation energy of E(a) = 6.2 ± 0.2 kcal/mol and a pre-exponential factor of 1/A = 0.02 ± 0.01 fs. Alternatively, a power law fit results in an exponent γ = 2.2 and a singularity temperature T(s) = 221 K. We tentatively conclude that the power law provides the better physical picture to describe the dynamics of liquid water around the freezing point.

Pattern recognition and classification of vibrational spectra by artificial neural networks

NASA Astrophysics Data System (ADS)

Yang, Husheng

1999-10-01

A drawback of current open-path Fourier transform infrared (OP/FT-IR) systems is that they need a human expert to determine those compounds that may be quantified from a given spectrum. In this study, three types of artificial neural networks were used to alleviate this problem. Firstly, multi-layer feed-forward neural networks were used to automatically recognize compounds in an OP/FT-IR spectrum. Each neural network was trained to recognize one compound in the presence of up to ten interferents in an OP/FT-IR spectrum. The networks were successfully used to recognize five alcohols and two chlorinated compounds in field-measured controlled-release OP/FT-IR spectra of mixtures of these compounds. It has also been demonstrated that a neural network could correctly identify a spectrum in the presence of an interferent that was not included in the training set and could also reject interferents it has not seen before. Secondly, the possibility of using one- and two- dimensional Kohonen self-organizing maps (SOMs) to recognize similarities in low-resolution vapor-phase infrared spectra without any additional information has been investigated. Both full-range reference spectra and open-path window reference spectra were used to train the networks and the trained networks were then used to classify the reference spectra into several groups. The results showed that the SOMs obtained from the two different training sets were quite different, and it is more appropriate to use the second SOM in OP/FT-IR spectrometry. Thirdly, vapor-phase FT-IR reference spectra of five alcohols along with four baseline spectra were encoded as prototype vectors for a Hopfield network. Inclusion of the baseline spectra allowed the network to classify spectra as unknowns, when the reference spectra of these compounds were not stored as prototype vectors in the network. The network could identify each of the 5 alcohols correctly even in the presence of noise and interfering compounds. Finally, one- and two-dimensional Kohonen SOMs were also successfully used for the unsupervised differentiation of the Fourier transform Raman spectra of hardwoods from softwoods. A semi-quantitative method that is based on the Euclidean distances of the weight matrix has been developed to assist the automatic clustering of the neurons in a two-dimensional SOM.

Coupling Network Computing Applications in Air-cooled Turbine Blades Optimization

NASA Astrophysics Data System (ADS)

Shi, Liang; Yan, Peigang; Xie, Ming; Han, Wanjin

2018-05-01

Through establishing control parameters from blade outside to inside, the parametric design of air-cooled turbine blade based on airfoil has been implemented. On the basis of fast updating structure features and generating solid model, a complex cooling system has been created. Different flow units are modeled into a complex network topology with parallel and serial connection. Applying one-dimensional flow theory, programs have been composed to get pipeline network physical quantities along flow path, including flow rate, pressure, temperature and other parameters. These inner units parameters set as inner boundary conditions for external flow field calculation program HIT-3D by interpolation, thus to achieve full field thermal coupling simulation. Referring the studies in literatures to verify the effectiveness of pipeline network program and coupling algorithm. After that, on the basis of a modified design, and with the help of iSIGHT-FD, an optimization platform had been established. Through MIGA mechanism, the target of enhancing cooling efficiency has been reached, and the thermal stress has been effectively reduced. Research work in this paper has significance for rapid deploying the cooling structure design.

In situ Gelable Interpenetrating Double Network Hydrogel Formulated from Binary Components: Thiolated Chitosan and Oxidized Dextran

PubMed Central

Zhang, Hanwei; Qadeer, Aisha; Chen, Weiliam

2011-01-01

In situ gelable interpenetrating double network hydrogels composed of thiolated chitosan (Chitosan-NAC) and oxidized dextran (Odex), completely devoid of potentially cytotoxic small molecule crosslinkers and do not require complex maneuvers or catalysis, have been formulated. The interpenetrating network structure is created by Schiff base formations and disulfide bond inter-crosslinkings through exploiting the disparity of their reaction times. Compare to the auto-gelable thiolated chitosan hydrogels that typically require a relatively long time span for gelation to occur, the Odex/Chitosan-NAC composition solidifies rapidly and forms a well-developed three-dimensional network in a short time span. Compare to typical hydrogels derived from natural materials, the Odex/Chitosan-NAC hydrogels are mechanically strong and resist degradation. The cytotoxicity potential of the hydrogels was determined by an in vitro viability assay using fibroblast as a model cell and the results reveal that the hydrogels are non-cytotoxic. In parallel, in vivo results from subdermal implantation in mice models demonstrate that this hydrogel is not only highly resistant to degradation but also induces very mild tissue response. PMID:21410248

Frequency mode excitations in two-dimensional Hindmarsh-Rose neural networks

NASA Astrophysics Data System (ADS)

Tabi, Conrad Bertrand; Etémé, Armand Sylvin; Mohamadou, Alidou

2017-05-01

In this work, we explicitly show the existence of two frequency regimes in a two-dimensional Hindmarsh-Rose neural network. Each of the regimes, through the semi-discrete approximation, is shown to be described by a two-dimensional complex Ginzburg-Landau equation. The modulational instability phenomenon for the two regimes is studied, with consideration given to the coupling intensities among neighboring neurons. Analytical solutions are also investigated, along with their propagation in the two frequency regimes. These waves, depending on the coupling strength, are identified as breathers, impulses and trains of soliton-like structures. Although the waves in two regimes appear in some common regions of parameters, some phase differences are noticed and the global dynamics of the system is highly influenced by the values of the coupling terms. For some values of such parameters, the high-frequency regime displays modulated trains of waves, while the low-frequency dynamics keeps the original asymmetric character of action potentials. We argue that in a wide range of pathological situations, strong interactions among neurons can be responsible for some pathological states, including schizophrenia and epilepsy.

Effects of the underlying topology on perturbation spreading in the Axelrod model for cultural dissemination

NASA Astrophysics Data System (ADS)

Kim, Yup; Cho, Minsoo; Yook, Soon-Hyung

2011-10-01

We study the effects of the underlying topologies on a single feature perturbation imposed to the Axelrod model of consensus formation. From the numerical simulations we show that there are successive updates which are similar to avalanches in many self-organized criticality systems when a perturbation is imposed. We find that the distribution of avalanche size satisfies the finite-size scaling (FSS) ansatz on two-dimensional lattices and random networks. However, on scale-free networks with the degree exponent γ≤3 we show that the avalanche size distribution does not satisfy the FSS ansatz. The results indicate that the disordered configurations on two-dimensional lattices or on random networks are still stable against the perturbation in the limit N (network size) →∞. However, on scale-free networks with γ≤3 the perturbation always drives the disordered phase into an ordered phase. The possible relationship between the properties of phase transition of the Axelrod model and the avalanche distribution is also discussed.

Uncluttered Single-Image Visualization of Vascular Structures using GPU and Integer Programming

PubMed Central

Won, Joong-Ho; Jeon, Yongkweon; Rosenberg, Jarrett; Yoon, Sungroh; Rubin, Geoffrey D.; Napel, Sandy

2013-01-01

Direct projection of three-dimensional branching structures, such as networks of cables, blood vessels, or neurons onto a 2D image creates the illusion of intersecting structural parts and creates challenges for understanding and communication. We present a method for visualizing such structures, and demonstrate its utility in visualizing the abdominal aorta and its branches, whose tomographic images might be obtained by computed tomography or magnetic resonance angiography, in a single two-dimensional stylistic image, without overlaps among branches. The visualization method, termed uncluttered single-image visualization (USIV), involves optimization of geometry. This paper proposes a novel optimization technique that utilizes an interesting connection of the optimization problem regarding USIV to the protein structure prediction problem. Adopting the integer linear programming-based formulation for the protein structure prediction problem, we tested the proposed technique using 30 visualizations produced from five patient scans with representative anatomical variants in the abdominal aortic vessel tree. The novel technique can exploit commodity-level parallelism, enabling use of general-purpose graphics processing unit (GPGPU) technology that yields a significant speedup. Comparison of the results with the other optimization technique previously reported elsewhere suggests that, in most aspects, the quality of the visualization is comparable to that of the previous one, with a significant gain in the computation time of the algorithm. PMID:22291148

High-throughput flow injection analysis mass spectroscopy with networked delivery of color-rendered results. 2. Three-dimensional spectral mapping of 96-well combinatorial chemistry racks.

PubMed

Görlach, E; Richmond, R; Lewis, I

1998-08-01

For the last two years, the mass spectroscopy section of the Novartis Pharma Research Core Technology group has analyzed tens of thousands of multiple parallel synthesis samples from the Novartis Pharma Combinatorial Chemistry program, using an in-house developed automated high-throughput flow injection analysis electrospray ionization mass spectroscopy system. The electrospray spectra of these samples reflect the many structures present after the cleavage step from the solid support. The overall success of the sequential synthesis is mirrored in the purity of the expected end product, but the partial success of individual synthesis steps is evident in the impurities in the mass spectrum. However this latter reaction information, which is of considerable utility to the combinatorial chemist, is effectively hidden from view by the very large number of analyzed samples. This information is now revealed at the workbench of the combinatorial chemist by a novel three-dimensional display of each rack's complete mass spectral ion current using the in-house RackViewer Visual Basic application. Colorization of "forbidden loss" and "forbidden gas-adduct" zones, normalization to expected monoisotopic molecular weight, colorization of ionization intensity, and sorting by row or column were used in combination to highlight systematic patterns in the mass spectroscopy data.

Lax pair, conservation laws and solitons for a (2 + 1)-dimensional fourth-order nonlinear Schrödinger equation governing an α-helical protein

NASA Astrophysics Data System (ADS)

Chai, Jun; Tian, Bo; Zhen, Hui-Ling; Sun, Wen-Rong

2015-11-01

Energy transfer through a (2+1)-dimensional α-helical protein can be described by a (2+1)-dimensional fourth-order nonlinear Schrödinger equation. For such an equation, a Lax pair and the infinitely-many conservation laws are derived. Using an auxiliary function and a bilinear formulation, we get the one-, two-, three- and N-soliton solutions via the Hirota method. The soliton velocity is linearly related to the lattice parameter γ, while the soliton' direction and amplitude do not depend on γ. Interactions between the two solitons are elastic, while those among the three solitons are pairwise elastic. Oblique, head-on and overtaking interactions between the two solitons are displayed. Oblique interaction among the three solitons and interactions among the two parallel solitons and a single one are presented as well.

Revisiting the Al/Al 2O 3 Interface: Coherent Interfaces and Misfit Accommodation

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

Pilania, Ghanshyam; Thijsse, Barend J.; Hoagland, Richard G.

We report the coherent and semi-coherent Al/α-Al 2O 3 interfaces using molecular dynamics simulations with a mixed, metallic-ionic atomistic model. For the coherent interfaces, both Al-terminated and O-terminated nonstoichiometric interfaces have been studied and their relative stability has been established. To understand the misfit accommodation at the semi-coherent interface, a 1-dimensional (1D) misfit dislocation model and a 2-dimensional (2D) dislocation network model have been studied. For the latter case, our analysis reveals an interface dislocation structure with a network of three sets of parallel dislocations, each with pure-edge character, giving rise to a pattern of coherent and stacking-fault-like regions atmore » the interface. Structural relaxation at elevated temperatures leads to a further change of the dislocation pattern, which can be understood in terms of a competition between the stacking fault energy and the dislocation interaction energy at the interface. In conclusion, our results are expected to serve as an input for the subsequent dislocation dynamics models to understand and predict the macroscopic mechanical behavior of Al/α-Al 2O 3 composite heterostructures.« less

Revisiting the Al/Al 2O 3 Interface: Coherent Interfaces and Misfit Accommodation

DOE PAGES

Pilania, Ghanshyam; Thijsse, Barend J.; Hoagland, Richard G.; ...

2014-03-27

We report the coherent and semi-coherent Al/α-Al 2O 3 interfaces using molecular dynamics simulations with a mixed, metallic-ionic atomistic model. For the coherent interfaces, both Al-terminated and O-terminated nonstoichiometric interfaces have been studied and their relative stability has been established. To understand the misfit accommodation at the semi-coherent interface, a 1-dimensional (1D) misfit dislocation model and a 2-dimensional (2D) dislocation network model have been studied. For the latter case, our analysis reveals an interface dislocation structure with a network of three sets of parallel dislocations, each with pure-edge character, giving rise to a pattern of coherent and stacking-fault-like regions atmore » the interface. Structural relaxation at elevated temperatures leads to a further change of the dislocation pattern, which can be understood in terms of a competition between the stacking fault energy and the dislocation interaction energy at the interface. In conclusion, our results are expected to serve as an input for the subsequent dislocation dynamics models to understand and predict the macroscopic mechanical behavior of Al/α-Al 2O 3 composite heterostructures.« less

Trace-Driven Debugging of Message Passing Programs

NASA Technical Reports Server (NTRS)

Frumkin, Michael; Hood, Robert; Lopez, Louis; Bailey, David (Technical Monitor)

1998-01-01

In this paper we report on features added to a parallel debugger to simplify the debugging of parallel message passing programs. These features include replay, setting consistent breakpoints based on interprocess event causality, a parallel undo operation, and communication supervision. These features all use trace information collected during the execution of the program being debugged. We used a number of different instrumentation techniques to collect traces. We also implemented trace displays using two different trace visualization systems. The implementation was tested on an SGI Power Challenge cluster and a network of SGI workstations.

Recognition of the optical packet header for two channels utilizing the parallel reservoir computing based on a semiconductor ring laser

NASA Astrophysics Data System (ADS)

Bao, Xiurong; Zhao, Qingchun; Yin, Hongxi; Qin, Jie

2018-05-01

In this paper, an all-optical parallel reservoir computing (RC) system with two channels for the optical packet header recognition is proposed and simulated, which is based on a semiconductor ring laser (SRL) with the characteristic of bidirectional light paths. The parallel optical loops are built through the cross-feedback of the bidirectional light paths where every optical loop can independently recognize each injected optical packet header. Two input signals are mapped and recognized simultaneously by training all-optical parallel reservoir, which is attributed to the nonlinear states in the laser. The recognition of optical packet headers for two channels from 4 bits to 32 bits is implemented through the simulation optimizing system parameters and therefore, the optimal recognition error ratio is 0. Since this structure can combine with the wavelength division multiplexing (WDM) optical packet switching network, the wavelength of each channel of optical packet headers for recognition can be different, and a better recognition result can be obtained.

Method and structure for skewed block-cyclic distribution of lower-dimensional data arrays in higher-dimensional processor grids

DOEpatents

Chatterjee, Siddhartha [Yorktown Heights, NY; Gunnels, John A [Brewster, NY

2011-11-08

A method and structure of distributing elements of an array of data in a computer memory to a specific processor of a multi-dimensional mesh of parallel processors includes designating a distribution of elements of at least a portion of the array to be executed by specific processors in the multi-dimensional mesh of parallel processors. The pattern of the designating includes a cyclical repetitive pattern of the parallel processor mesh, as modified to have a skew in at least one dimension so that both a row of data in the array and a column of data in the array map to respective contiguous groupings of the processors such that a dimension of the contiguous groupings is greater than one.

Big Data: A Parallel Particle Swarm Optimization-Back-Propagation Neural Network Algorithm Based on MapReduce

PubMed Central

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

Two-Dimensional Sequential and Concurrent Finite Element Analysis of Unstiffened and Stiffened Aluminum and Composite Panels with Hole

NASA Technical Reports Server (NTRS)

Razzaq, Zia; Prasad, Venkatesh

1988-01-01

The results of a detailed investigation of the distribution of stresses in aluminum and composite panels subjected to uniform end shortening are presented. The focus problem is a rectangular panel with two longitudinal stiffeners, and an inner stiffener discontinuous at a central hole in the panel. The influence of the stiffeners on the stresses is evaluated through a two-dimensional global finite element analysis in the absence or presence of the hole. Contrary to the physical feel, it is found that the maximum stresses from the glocal analysis for both stiffened aluminum and composite panels are greater than the corresponding stresses for the unstiffened panels. The inner discontinuous stiffener causes a greater increase in stresses than the reduction provided by the two outer stiffeners. A detailed layer-by-layer study of stresses around the hole is also presented for both unstiffened and stiffened composite panels. A parallel equation solver is used for the global system of equations since the computational time is far less than that using a sequential scheme. A parallel Choleski method with up to 16 processors is used on Flex/32 Multicomputer at NASA Langley Research Center. The parallel computing results are summarized and include the computational times, speedups, bandwidths, and their inter-relationships for the panel problems. It is found that the computational time for the Choleski method decreases with a decrease in bandwidth, and better speedups result as the bandwidth increases.

Adaptive particle-based pore-level modeling of incompressible fluid flow in porous media: a direct and parallel approach

NASA Astrophysics Data System (ADS)

Ovaysi, S.; Piri, M.

2009-12-01

We present a three-dimensional fully dynamic parallel particle-based model for direct pore-level simulation of incompressible viscous fluid flow in disordered porous media. The model was developed from scratch and is capable of simulating flow directly in three-dimensional high-resolution microtomography images of naturally occurring or man-made porous systems. It reads the images as input where the position of the solid walls are given. The entire medium, i.e., solid and fluid, is then discretized using particles. The model is based on Moving Particle Semi-implicit (MPS) technique. We modify this technique in order to improve its stability. The model handles highly irregular fluid-solid boundaries effectively. It takes into account viscous pressure drop in addition to the gravity forces. It conserves mass and can automatically detect any false connectivity with fluid particles in the neighboring pores and throats. It includes a sophisticated algorithm to automatically split and merge particles to maintain hydraulic connectivity of extremely narrow conduits. Furthermore, it uses novel methods to handle particle inconsistencies and open boundaries. To handle the computational load, we present a fully parallel version of the model that runs on distributed memory computer clusters and exhibits excellent scalability. The model is used to simulate unsteady-state flow problems under different conditions starting from straight noncircular capillary tubes with different cross-sectional shapes, i.e., circular/elliptical, square/rectangular and triangular cross-sections. We compare the predicted dimensionless hydraulic conductances with the data available in the literature and observe an excellent agreement. We then test the scalability of our parallel model with two samples of an artificial sandstone, samples A and B, with different volumes and different distributions (non-uniform and uniform) of solid particles among the processors. An excellent linear scalability is obtained for sample B that has more uniform distribution of solid particles leading to a superior load balancing. The model is then used to simulate fluid flow directly in REV size three-dimensional x-ray images of a naturally occurring sandstone. We analyze the quality and consistency of the predicted flow behavior and calculate absolute permeability, which compares well with the available network modeling and Lattice-Boltzmann permeabilities available in the literature for the same sandstone. We show that the model conserves mass very well and is stable computationally even at very narrow fluid conduits. The transient- and the steady-state fluid flow patterns are presented as well as the steady-state flow rates to compute absolute permeability. Furthermore, we discuss the vital role of our adaptive particle resolution scheme in preserving the original pore connectivity of the samples and their narrow channels through splitting and merging of fluid particles.

Two-dimensional quantum repeaters

NASA Astrophysics Data System (ADS)

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.

Superresolution parallel magnetic resonance imaging: Application to functional and spectroscopic imaging

PubMed Central

Otazo, Ricardo; Lin, Fa-Hsuan; Wiggins, Graham; Jordan, Ramiro; Sodickson, Daniel; Posse, Stefan

2009-01-01

Standard parallel magnetic resonance imaging (MRI) techniques suffer from residual aliasing artifacts when the coil sensitivities vary within the image voxel. In this work, a parallel MRI approach known as Superresolution SENSE (SURE-SENSE) is presented in which acceleration is performed by acquiring only the central region of k-space instead of increasing the sampling distance over the complete k-space matrix and reconstruction is explicitly based on intra-voxel coil sensitivity variation. In SURE-SENSE, parallel MRI reconstruction is formulated as a superresolution imaging problem where a collection of low resolution images acquired with multiple receiver coils are combined into a single image with higher spatial resolution using coil sensitivities acquired with high spatial resolution. The effective acceleration of conventional gradient encoding is given by the gain in spatial resolution, which is dictated by the degree of variation of the different coil sensitivity profiles within the low resolution image voxel. Since SURE-SENSE is an ill-posed inverse problem, Tikhonov regularization is employed to control noise amplification. Unlike standard SENSE, for which acceleration is constrained to the phase-encoding dimension/s, SURE-SENSE allows acceleration along all encoding directions — for example, two-dimensional acceleration of a 2D echo-planar acquisition. SURE-SENSE is particularly suitable for low spatial resolution imaging modalities such as spectroscopic imaging and functional imaging with high temporal resolution. Application to echo-planar functional and spectroscopic imaging in human brain is presented using two-dimensional acceleration with a 32-channel receiver coil. PMID:19341804

Three-dimensional aromatic networks.

PubMed

Toyota, Shinji; Iwanaga, Tetsuo

2014-01-01

Three-dimensional (3D) networks consisting of aromatic units and linkers are reviewed from various aspects. To understand principles for the construction of such compounds, we generalize the roles of building units, the synthetic approaches, and the classification of networks. As fundamental compounds, cyclophanes with large aromatic units and aromatic macrocycles with linear acetylene linkers are highlighted in terms of transannular interactions between aromatic units, conformational preference, and resolution of chiral derivatives. Polycyclic cage compounds are constructed from building units by linkages via covalent bonds, metal-coordination bonds, or hydrogen bonds. Large cage networks often include a wide range of guest species in their cavity to afford novel inclusion compounds. Topological isomers consisting of two or more macrocycles are formed by cyclization of preorganized species. Some complicated topological networks are constructed by self-assembly of simple building units.

A Comparison of Numerical and Analytical Radiative-Transfer Solutions for Plane Albedo of Natural Waters

EPA Science Inventory

Three numerical algorithms were compared to provide a solution of a radiative transfer equation (RTE) for plane albedo (hemispherical reflectance) in semi-infinite one-dimensional plane-parallel layer. Algorithms were based on the invariant imbedding method and two different var...

Optimizing transformations of stencil operations for parallel cache-based architectures

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

Bassetti, F.; Davis, K.

This paper describes a new technique for optimizing serial and parallel stencil- and stencil-like operations for cache-based architectures. This technique takes advantage of the semantic knowledge implicity in stencil-like computations. The technique is implemented as a source-to-source program transformation; because of its specificity it could not be expected of a conventional compiler. Empirical results demonstrate a uniform factor of two speedup. The experiments clearly show the benefits of this technique to be a consequence, as intended, of the reduction in cache misses. The test codes are based on a 5-point stencil obtained by the discretization of the Poisson equation andmore » applied to a two-dimensional uniform grid using the Jacobi method as an iterative solver. Results are presented for a 1-D tiling for a single processor, and in parallel using 1-D data partition. For the parallel case both blocking and non-blocking communication are tested. The same scheme of experiments has bee n performed for the 2-D tiling case. However, for the parallel case the 2-D partitioning is not discussed here, so the parallel case handled for 2-D is 2-D tiling with 1-D data partitioning.« less

New 2D diffraction model and its applications to terahertz parallel-plate waveguide power splitters

PubMed Central

Zhang, Fan; Song, Kaijun; Fan, Yong

2017-01-01

A two-dimensional (2D) diffraction model for the calculation of the diffraction field in 2D space and its applications to terahertz parallel-plate waveguide power splitters are proposed in this paper. Compared with the Huygens-Fresnel principle in three-dimensional (3D) space, the proposed model provides an approximate analytical expression to calculate the diffraction field in 2D space. The diffraction filed is regarded as the superposition integral in 2D space. The calculated results obtained from the proposed diffraction model agree well with the ones by software HFSS based on the element method (FEM). Based on the proposed 2D diffraction model, two parallel-plate waveguide power splitters are presented. The splitters consist of a transmitting horn antenna, reflectors, and a receiving antenna array. The reflector is cylindrical parabolic with superimposed surface relief to efficiently couple the transmitted wave into the receiving antenna array. The reflector is applied as computer-generated holograms to match the transformed field to the receiving antenna aperture field. The power splitters were optimized by a modified real-coded genetic algorithm. The computed results of the splitters agreed well with the ones obtained by software HFSS verify the novel design method for power splitter, which shows good applied prospects of the proposed 2D diffraction model. PMID:28181514

Reconnection in Three Dimensions

NASA Technical Reports Server (NTRS)

Hesse, Michael

1999-01-01

Analyzing the qualitative three-dimensional magnetic structure of a plasmoid, we were led to reconsider the concept of magnetic reconnection from a general point of view. The properties of relatively simple magnetic field models provide a strong preference for one of two definitions of magnetic reconnection that exist in the literature. Any concept of magnetic reconnection defined in terms of magnetic topology seems naturally restricted to cases where the magnetic field vanishes somewhere in the nonideal (diffusion) region. The main part of this paper is concerned with magnetic reconnection in nonvanishing magnetic fields (finite-B reconnection), which has attracted less attention in the past. We show that the electric field component parallel to the magnetic field plays a crucial physical role in finite-B reconnection, and we present two theorems involving the former. The first states a necessary and sufficient condition on the parallel electric field for global reconnection to occur. Here the term "global" means the generic case where the breakdown of magnetic connection occurs for plasma elements that stay outside the nonideal region. The second theorem relates the change of magnetic helicity to the parallel electric field for cases where the electric field vanishes at large distances. That these results provide new insight into three-dimensional reconnection processes is illustrated in terms of the plasmoid configuration, which was our starting point.

Apparatus for reading two-dimensional electrophoretograms containing. beta. -ray-emitting labeled compounds

DOEpatents

Anderson, H.L.; Kinnison, W.W.; Lillberg, J.W.

1985-04-30

An apparatus and method for electronically reading planar two-dimensional ..beta..-ray emitter-labeled gel electrophoretograms. A single, flat rectangular multiwire proportional chamber is placed in close proximity to the gel and the assembly placed in an intense uniform magnetic field disposed in a perpendicular manner to the rectangular face of the proportional chamber. Beta rays emitted in the direction of the proportional chamber are caused to execute helical motions which substantially preserve knowledge the coordinates of their origin in the gel. Perpendicularly oriented, parallel wire, parallel plane cathodes electronically sense the location of the ..beta..-rays from ionization generated thereby in a detection gas coupled with an electron avalanche effect resulting from the action of a parallel wire anode located therebetween. A scintillator permits the present apparatus to be rendered insensitive when signals are generated from cosmic rays incident on the proportional chamber. Resolution for concentrations of radioactive compounds in the gel exceeds 700-..mu..m. The apparatus and method of the present invention represent a significant improvement over conventional autoradiographic techniques in dynamic range, linearity and sensitivity of data collection. A concentration and position map for gel electrophoretograms having significant concentrations of labeled compounds and/or highly radioactive labeling nuclides can generally be obtained in less than one hour.

Apparatus and method for reading two-dimensional electrophoretograms containing .beta.-ray-emitting labeled compounds

DOEpatents

Anderson, Herbert L.; Kinnison, W. Wayne; Lillberg, John W.

1987-01-01

Apparatus and method for electronically reading planar two dimensional .beta.-ray emitter-labeled gel electrophoretograms. A single, flat rectangular multiwire proportional chamber is placed in close proximity to the gel and the assembly placed in an intense uniform magnetic field disposed in a perpendicular manner to the rectangular face of the proportional chamber. Beta rays emitted in the direction of the proportional chamber are caused to execute helical motions which substantially preserve knowledge of the coordinates of their origin in the gel. Perpendicularly oriented, parallel wire, parallel plane cathodes electronically sense the location of the .beta.-rays from ionization generated thereby in a detection gas coupled with an electron avalanche effect resulting from the action of a parallel wire anode located therebetween. A scintillator permits the present apparatus to be rendered insensitive when signals are generated from cosmic rays incident on the proportional chamber. Resolution for concentrations of radioactive compounds in the gel exceeds 700 .mu.m. The apparatus and method of the present invention represent a significant improvement over conventional autoradiographic techniques in dynamic range, linearity and sensitivity of data collection. A concentration and position map for gel electrophoretograms having significant concentrations of labeled compounds and/or highly radioactive labeling nuclides can generally be obtained in less than one hour.

Image gathering, coding, and processing: End-to-end optimization for efficient and robust acquisition of visual information

NASA Technical Reports Server (NTRS)

Huck, Friedrich O.; Fales, Carl L.

1990-01-01

Researchers are concerned with the end-to-end performance of image gathering, coding, and processing. The applications range from high-resolution television to vision-based robotics, wherever the resolution, efficiency and robustness of visual information acquisition and processing are critical. For the presentation at this workshop, it is convenient to divide research activities into the following two overlapping areas: The first is the development of focal-plane processing techniques and technology to effectively combine image gathering with coding, with an emphasis on low-level vision processing akin to the retinal processing in human vision. The approach includes the familiar Laplacian pyramid, the new intensity-dependent spatial summation, and parallel sensing/processing networks. Three-dimensional image gathering is attained by combining laser ranging with sensor-array imaging. The second is the rigorous extension of information theory and optimal filtering to visual information acquisition and processing. The goal is to provide a comprehensive methodology for quantitatively assessing the end-to-end performance of image gathering, coding, and processing.

Crystal structure of bis[bis(4-azaniumylphenyl) sulfone] tetranitrate monohydrate

PubMed Central

Benahsene, Amani Hind; Bendjeddou, Lamia; Merazig, Hocine

2017-01-01

In the title compound, the hydrated tetra­(nitrate) salt of dapsone (4,4′-di­amino­diphenyl­sulfone), 2C12H14N2O2S2+·4NO3 −·H2O {alternative name: bis[bis­(4,4′-di­aza­niumylphen­yl) sulfone] tetra­nitrate monohydrate}, the cations are conformationally similar, with comparable dihedral angles between the two benzene rings in each of 70.03 (18) and 69.69 (19)°. In the crystal, mixed cation–anion–water mol­ecule layers lying parallel to the (001) plane are formed through N—H⋯O, O—H⋯O and C—H⋯O hydrogen-bonding inter­actions and these layers are further extended into an overall three-dimensional supra­molecular network structure. Inter-ring π–π inter­actions are also present [minimum ring centroid separation = 3.693 (3) Å]. PMID:29152359

Three new enantiomerically pure ferrocenylphosphole compounds.

PubMed

López Cortés, José Guadalupe; Vincendeau, Sandrine; Daran, Jean Claude; Manoury, Eric; Gouygou, Maryse

2006-05-01

The absolute configurations of three new enantiomerically pure ferrocenylphosphole compounds, namely (2S,4S,S(Fc))-4-methoxymethyl-2-[2-(9-thioxo-9lambda5-phosphafluoren-9-yl)ferrocenyl]-1,3-dioxane, [Fe(C5H5)(C23H22O3PS)], (III), (S(Fc))-[2-(9-thioxo-9lambda5-phosphafluoren-9-yl)ferrocenyl]methanol, [Fe(C5H5)(C18H14OPS)], (V), and (S(Fc))-diphenyl[2-(9-thioxo-9lambda5-phosphafluoren-9-yl]ferrocenylmethyl]phosphine, [Fe(C5H5)(C30H23P2)], (VIII), have been unambiguously established. All three ligands contain a planar chiral ferrocene group, bearing a dibenzophosphole and either a dioxane, a methanol or a diphenylphosphinomethane group on the same cyclopentadienyl. In compound (V), the occurrence of O-H...S and C-H...S hydrogen bonds results in the formation of a two-dimensional network parallel to (001). The geometry of the ferrocene frameworks agrees with related reported structures.

Performance Evaluation in Network-Based Parallel Computing

NASA Technical Reports Server (NTRS)

Dezhgosha, Kamyar

1996-01-01

Network-based parallel computing is emerging as a cost-effective alternative for solving many problems which require use of supercomputers or massively parallel computers. The primary objective of this project has been to conduct experimental research on performance evaluation for clustered parallel computing. First, a testbed was established by augmenting our existing SUNSPARCs' network with PVM (Parallel Virtual Machine) which is a software system for linking clusters of machines. Second, a set of three basic applications were selected. The applications consist of a parallel search, a parallel sort, a parallel matrix multiplication. These application programs were implemented in C programming language under PVM. Third, we conducted performance evaluation under various configurations and problem sizes. Alternative parallel computing models and workload allocations for application programs were explored. The performance metric was limited to elapsed time or response time which in the context of parallel computing can be expressed in terms of speedup. The results reveal that the overhead of communication latency between processes in many cases is the restricting factor to performance. That is, coarse-grain parallelism which requires less frequent communication between processes will result in higher performance in network-based computing. Finally, we are in the final stages of installing an Asynchronous Transfer Mode (ATM) switch and four ATM interfaces (each 155 Mbps) which will allow us to extend our study to newer applications, performance metrics, and configurations.

Design of a MIMD neural network processor

NASA Astrophysics Data System (ADS)

Saeks, Richard E.; Priddy, Kevin L.; Pap, Robert M.; Stowell, S.

1994-03-01

The Accurate Automation Corporation (AAC) neural network processor (NNP) module is a fully programmable multiple instruction multiple data (MIMD) parallel processor optimized for the implementation of neural networks. The AAC NNP design fully exploits the intrinsic sparseness of neural network topologies. Moreover, by using a MIMD parallel processing architecture one can update multiple neurons in parallel with efficiency approaching 100 percent as the size of the network increases. Each AAC NNP module has 8 K neurons and 32 K interconnections and is capable of 140,000,000 connections per second with an eight processor array capable of over one billion connections per second.

Unstructured mesh algorithms for aerodynamic calculations

NASA Technical Reports Server (NTRS)

Mavriplis, D. J.

1992-01-01

The use of unstructured mesh techniques for solving complex aerodynamic flows is discussed. The principle advantages of unstructured mesh strategies, as they relate to complex geometries, adaptive meshing capabilities, and parallel processing are emphasized. The various aspects required for the efficient and accurate solution of aerodynamic flows are addressed. These include mesh generation, mesh adaptivity, solution algorithms, convergence acceleration, and turbulence modeling. Computations of viscous turbulent two-dimensional flows and inviscid three-dimensional flows about complex configurations are demonstrated. Remaining obstacles and directions for future research are also outlined.

Computational strategies for three-dimensional flow simulations on distributed computer systems. Ph.D. Thesis Semiannual Status Report, 15 Aug. 1993 - 15 Feb. 1994

NASA Technical Reports Server (NTRS)

Weed, Richard Allen; Sankar, L. N.

1994-01-01

An increasing amount of research activity in computational fluid dynamics has been devoted to the development of efficient algorithms for parallel computing systems. The increasing performance to price ratio of engineering workstations has led to research to development procedures for implementing a parallel computing system composed of distributed workstations. This thesis proposal outlines an ongoing research program to develop efficient strategies for performing three-dimensional flow analysis on distributed computing systems. The PVM parallel programming interface was used to modify an existing three-dimensional flow solver, the TEAM code developed by Lockheed for the Air Force, to function as a parallel flow solver on clusters of workstations. Steady flow solutions were generated for three different wing and body geometries to validate the code and evaluate code performance. The proposed research will extend the parallel code development to determine the most efficient strategies for unsteady flow simulations.

Performance of a parallel code for the Euler equations on hypercube computers

NASA Technical Reports Server (NTRS)

Barszcz, Eric; Chan, Tony F.; Jesperson, Dennis C.; Tuminaro, Raymond S.

1990-01-01

The performance of hypercubes were evaluated on a computational fluid dynamics problem and the parallel environment issues were considered that must be addressed, such as algorithm changes, implementation choices, programming effort, and programming environment. The evaluation focuses on a widely used fluid dynamics code, FLO52, which solves the two dimensional steady Euler equations describing flow around the airfoil. The code development experience is described, including interacting with the operating system, utilizing the message-passing communication system, and code modifications necessary to increase parallel efficiency. Results from two hypercube parallel computers (a 16-node iPSC/2, and a 512-node NCUBE/ten) are discussed and compared. In addition, a mathematical model of the execution time was developed as a function of several machine and algorithm parameters. This model accurately predicts the actual run times obtained and is used to explore the performance of the code in interesting but yet physically realizable regions of the parameter space. Based on this model, predictions about future hypercubes are made.

HeNCE: A Heterogeneous Network Computing Environment

DOE PAGES

Beguelin, Adam; Dongarra, Jack J.; Geist, George Al; ...

1994-01-01

Network computing seeks to utilize the aggregate resources of many networked computers to solve a single problem. In so doing it is often possible to obtain supercomputer performance from an inexpensive local area network. The drawback is that network computing is complicated and error prone when done by hand, especially if the computers have different operating systems and data formats and are thus heterogeneous. The heterogeneous network computing environment (HeNCE) is an integrated graphical environment for creating and running parallel programs over a heterogeneous collection of computers. It is built on a lower level package called parallel virtual machine (PVM).more » The HeNCE philosophy of parallel programming is to have the programmer graphically specify the parallelism of a computation and to automate, as much as possible, the tasks of writing, compiling, executing, debugging, and tracing the network computation. Key to HeNCE is a graphical language based on directed graphs that describe the parallelism and data dependencies of an application. Nodes in the graphs represent conventional Fortran or C subroutines and the arcs represent data and control flow. This article describes the present state of HeNCE, its capabilities, limitations, and areas of future research.« less

Large-Scale Modeling of Epileptic Seizures: Scaling Properties of Two Parallel Neuronal Network Simulation Algorithms

DOE PAGES

Pesce, Lorenzo L.; Lee, Hyong C.; Hereld, Mark; ...

2013-01-01

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 determinedmore » 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.« less

The control of a parallel hybrid-electric propulsion system for a small unmanned aerial vehicle using a CMAC neural network.

PubMed

Harmon, Frederick G; Frank, Andrew A; Joshi, Sanjay S

2005-01-01

A Simulink model, a propulsion energy optimization algorithm, and a CMAC controller were developed for a small parallel hybrid-electric unmanned aerial vehicle (UAV). The hybrid-electric UAV is intended for military, homeland security, and disaster-monitoring missions involving intelligence, surveillance, and reconnaissance (ISR). The Simulink model is a forward-facing simulation program used to test different control strategies. The flexible energy optimization algorithm for the propulsion system allows relative importance to be assigned between the use of gasoline, electricity, and recharging. A cerebellar model arithmetic computer (CMAC) neural network approximates the energy optimization results and is used to control the parallel hybrid-electric propulsion system. The hybrid-electric UAV with the CMAC controller uses 67.3% less energy than a two-stroke gasoline-powered UAV during a 1-h ISR mission and 37.8% less energy during a longer 3-h ISR mission.

Engineering rules for evaluating the efficiency of multiplexing traffic streams

NASA Astrophysics Data System (ADS)

Klincewicz, John G.

2004-09-01

It is common, either for a telecommunications service provider or for a corporate enterprise, to have multiple data networks. For example, both an IP network and an ATM or Frame Relay network could be in operation to serve different applications. This can result in parallel transport links between the same two locations, each carrying data traffic under a different protocol. In this paper, we consider some practical engineering rules, for particular situations, to evaluate whether or not it is advantageous to combine these parallel traffic streams onto a single transport link. Combining the streams requires additional overhead (a so-called "cell tax" ) but, in at least some situations, can result in more efficient use of modular transport capacity. Simple graphs can be used to summarize the analysis. Some interesting, and perhaps unexpected, observations can be made.

MPI-AMRVAC 2.0 for Solar and Astrophysical Applications

NASA Astrophysics Data System (ADS)

Xia, C.; Teunissen, J.; El Mellah, I.; Chané, E.; Keppens, R.

2018-02-01

We report on the development of MPI-AMRVAC version 2.0, which is an open-source framework for parallel, grid-adaptive simulations of hydrodynamic and magnetohydrodynamic (MHD) astrophysical applications. The framework now supports radial grid stretching in combination with adaptive mesh refinement (AMR). The advantages of this combined approach are demonstrated with one-dimensional, two-dimensional, and three-dimensional examples of spherically symmetric Bondi accretion, steady planar Bondi–Hoyle–Lyttleton flows, and wind accretion in supergiant X-ray binaries. Another improvement is support for the generic splitting of any background magnetic field. We present several tests relevant for solar physics applications to demonstrate the advantages of field splitting on accuracy and robustness in extremely low-plasma β environments: a static magnetic flux rope, a magnetic null-point, and magnetic reconnection in a current sheet with either uniform or anomalous resistivity. Our implementation for treating anisotropic thermal conduction in multi-dimensional MHD applications is also described, which generalizes the original slope-limited symmetric scheme from two to three dimensions. We perform ring diffusion tests that demonstrate its accuracy and robustness, and show that it prevents the unphysical thermal flux present in traditional schemes. The improved parallel scaling of the code is demonstrated with three-dimensional AMR simulations of solar coronal rain, which show satisfactory strong scaling up to 2000 cores. Other framework improvements are also reported: the modernization and reorganization into a library, the handling of automatic regression tests, the use of inline/online Doxygen documentation, and a new future-proof data format for input/output.

Two-Dimensional Optoelectronic Graphene Nanoprobes for Neural Nerwork

NASA Astrophysics Data System (ADS)

Hong, Tu; Kitko, Kristina; Wang, Rui; Zhang, Qi; Xu, Yaqiong

2014-03-01

Brain is the most complex network created by nature, with billions of neurons connected by trillions of synapses through sophisticated wiring patterns and countless modulatory mechanisms. Current methods to study the neuronal process, either by electrophysiology or optical imaging, have significant limitations on throughput and sensitivity. Here, we use graphene, a monolayer of carbon atoms, as a two-dimensional nanoprobe for neural network. Scanning photocurrent measurement is applied to detect the local integration of electrical and chemical signals in mammalian neurons. Such interface between nanoscale electronic device and biological system provides not only ultra-high sensitivity, but also sub-millisecond temporal resolution, owing to the high carrier mobility of graphene.

Real-time, interactive animation of deformable two- and three-dimensional objects

DOEpatents

Desbrun, Mathieu; Schroeder, Peter; Meyer, Mark; Barr, Alan H.

2003-06-03

A method of updating in real-time the locations and velocities of mass points of a two- or three-dimensional object represented by a mass-spring system. A modified implicit Euler integration scheme is employed to determine the updated locations and velocities. In an optional post-integration step, the updated locations are corrected to preserve angular momentum. A processor readable medium and a network server each tangibly embodying the method are also provided. A system comprising a processor in combination with the medium, and a system comprising the server in combination with a client for accessing the server over a computer network, are also provided.

Dimensional synthesis of a 3-DOF parallel manipulator with full circle rotation

NASA Astrophysics Data System (ADS)

Ni, Yanbing; Wu, Nan; Zhong, Xueyong; Zhang, Biao

2015-07-01

Parallel robots are widely used in the academic and industrial fields. In spite of the numerous achievements in the design and dimensional synthesis of the low-mobility parallel robots, few research efforts are directed towards the asymmetric 3-DOF parallel robots whose end-effector can realize 2 translational and 1 rotational(2T1R) motion. In order to develop a manipulator with the capability of full circle rotation to enlarge the workspace, a new 2T1R parallel mechanism is proposed. The modeling approach and kinematic analysis of this proposed mechanism are investigated. Using the method of vector analysis, the inverse kinematic equations are established. This is followed by a vigorous proof that this mechanism attains an annular workspace through its circular rotation and 2 dimensional translations. Taking the first order perturbation of the kinematic equations, the error Jacobian matrix which represents the mapping relationship between the error sources of geometric parameters and the end-effector position errors is derived. With consideration of the constraint conditions of pressure angles and feasible workspace, the dimensional synthesis is conducted with a goal to minimize the global comprehensive performance index. The dimension parameters making the mechanism to have optimal error mapping and kinematic performance are obtained through the optimization algorithm. All these research achievements lay the foundation for the prototype building of such kind of parallel robots.

Grid cell mechanisms and function: Contributions of entorhinal persistent spiking and phase resetting

PubMed Central

Hasselmo, Michael E.

2008-01-01

This article presents a model of grid cell firing based on the intrinsic persistent firing shown experimentally in neurons of entorhinal cortex. In this model, the mechanism of persistent firing allows individual neurons to hold a stable baseline firing frequency. Depolarizing input from speed modulated head direction cells transiently shifts the frequency of firing from baseline, resulting in a shift in spiking phase in proportion to the integral of velocity. The convergence of input from different persistent firing neurons causes spiking in a grid cell only when the persistent firing neurons are within similar phase ranges. This model effectively simulates the two-dimensional firing of grid cells in open field environments, as well as the properties of theta phase precession. This model provides an alternate implementation of oscillatory interference models. The persistent firing could also interact on a circuit level with rhythmic inhibition and neurons showing membrane potential oscillations to code position with spiking phase. These mechanisms could operate in parallel with computation of position from visual angle and distance of stimuli. In addition to simulating two-dimensional grid patterns, models of phase interference can account for context-dependent firing in other tasks. In network simulations of entorhinal cortex, hippocampus and postsubiculum, the reset of phase effectively replicates context-dependent firing by entorhinal and hippocampal neurons during performance of a continuous spatial alternation task, a delayed spatial alternation task with running in a wheel during the delay period, and a hairpin maze task. PMID:19021258

A Green's function method for two-dimensional reactive solute transport in a parallel fracture-matrix system

NASA Astrophysics Data System (ADS)

Chen, Kewei; Zhan, Hongbin

2018-06-01

The reactive solute transport in a single fracture bounded by upper and lower matrixes is a classical problem that captures the dominant factors affecting transport behavior beyond pore scale. A parallel fracture-matrix system which considers the interaction among multiple paralleled fractures is an extension to a single fracture-matrix system. The existing analytical or semi-analytical solution for solute transport in a parallel fracture-matrix simplifies the problem to various degrees, such as neglecting the transverse dispersion in the fracture and/or the longitudinal diffusion in the matrix. The difficulty of solving the full two-dimensional (2-D) problem lies in the calculation of the mass exchange between the fracture and matrix. In this study, we propose an innovative Green's function approach to address the 2-D reactive solute transport in a parallel fracture-matrix system. The flux at the interface is calculated numerically. It is found that the transverse dispersion in the fracture can be safely neglected due to the small scale of fracture aperture. However, neglecting the longitudinal matrix diffusion would overestimate the concentration profile near the solute entrance face and underestimate the concentration profile at the far side. The error caused by neglecting the longitudinal matrix diffusion decreases with increasing Peclet number. The longitudinal matrix diffusion does not have obvious influence on the concentration profile in long-term. The developed model is applied to a non-aqueous-phase-liquid (DNAPL) contamination field case in New Haven Arkose of Connecticut in USA to estimate the Trichloroethylene (TCE) behavior over 40 years. The ratio of TCE mass stored in the matrix and the injected TCE mass increases above 90% in less than 10 years.

Structural and magnetic properties of two- and three-dimensional molecule-based magnets (cat) +[M IIM III(C 2O 4) 3] -

NASA Astrophysics Data System (ADS)

Ovanesyan, Nikolai S.; Shilov, Gena V.; Pyalling, Alex A.; Train, Cyrille; Gredin, Patrick; Gruselle, Michel; Kiss, László F.; Bottyán, László

2004-05-01

We discuss the different structural arrangements of NBu 4[Fe IICr III(C 2O 4) 3] layered compounds in their racemic and enantiomeric forms and related magnetic properties. For [Mn IIFe III(C 2O 4) 3] networks of dimensionalities 2 and 3 Mössbauer spectroscopy was applied to study the Fe III sublattice magnetization. Unusual magnetic relaxation phenomena below TN were observed for both 2D and 3D networks.

Parallel Monte Carlo transport modeling in the context of a time-dependent, three-dimensional multi-physics code

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

Procassini, R.J.

1997-12-31

The fine-scale, multi-space resolution that is envisioned for accurate simulations of complex weapons systems in three spatial dimensions implies flop-rate and memory-storage requirements that will only be obtained in the near future through the use of parallel computational techniques. Since the Monte Carlo transport models in these simulations usually stress both of these computational resources, they are prime candidates for parallelization. The MONACO Monte Carlo transport package, which is currently under development at LLNL, will utilize two types of parallelism within the context of a multi-physics design code: decomposition of the spatial domain across processors (spatial parallelism) and distribution ofmore » particles in a given spatial subdomain across additional processors (particle parallelism). This implementation of the package will utilize explicit data communication between domains (message passing). Such a parallel implementation of a Monte Carlo transport model will result in non-deterministic communication patterns. The communication of particles between subdomains during a Monte Carlo time step may require a significant level of effort to achieve a high parallel efficiency.« less

An efficient high-frequency analysis of modal reflection and transmission coefficients for a class of waveguide discontinuities

NASA Technical Reports Server (NTRS)

Pathak, P. H.; Altintas, A.

1988-01-01

A high-frequency analysis of electromagnetic modal reflection and transmission coefficients is presented for waveguide discontinuities formed by joining different waveguide sections. The analysis uses an extended version of the concept of geometrical theory of diffraction based equivalent edge currents in conjunction with the reciprocity theorem to describe interior scattering effects. If the waveguide modes and their associated modal rays can be found explicitly, general two- and three-dimensional waveguide geometries can be analyzed. Expressions are developed for two-dimensional reflection and transmission coefficients. Numerical results are given for a flanged, semi-infinite parallel plate waveguide and for the junction between two linearly tapered waveguides.

Unsteady boundary-layer injection

NASA Technical Reports Server (NTRS)

Telionis, D. P.; Jones, G. S.

1981-01-01

The boundary-layer equations for two-dimensional incompressible flow are integrated numerically for the flow over a flat plate and a Howarth body. Injection is introduced either impulsively or periodically along a narrow strip. Results indicate that injection perpendicular to the wall is transmitted instantly across the boundary layer and has little effect on the velocity profile parallel to the wall. The effect is a little more noticeable for flows with adverse pressure gradients. Injection parallel to the wall results in fuller velocity profiles. Parallel and oscillatory injection appears to influence the mean. The amplitude of oscillation decreases with distance from the injection strip but further downstream it increases again in a manner reminiscent of an unstable process.

A parallel reaction-transport model applied to cement hydration and microstructure development

NASA Astrophysics Data System (ADS)

Bullard, Jeffrey W.; Enjolras, Edith; George, William L.; Satterfield, Steven G.; Terrill, Judith E.

2010-03-01

A recently described stochastic reaction-transport model on three-dimensional lattices is parallelized and is used to simulate the time-dependent structural and chemical evolution in multicomponent reactive systems. The model, called HydratiCA, uses probabilistic rules to simulate the kinetics of diffusion, homogeneous reactions and heterogeneous phenomena such as solid nucleation, growth and dissolution in complex three-dimensional systems. The algorithms require information only from each lattice site and its immediate neighbors, and this localization enables the parallelized model to exhibit near-linear scaling up to several hundred processors. Although applicable to a wide range of material systems, including sedimentary rock beds, reacting colloids and biochemical systems, validation is performed here on two minerals that are commonly found in Portland cement paste, calcium hydroxide and ettringite, by comparing their simulated dissolution or precipitation rates far from equilibrium to standard rate equations, and also by comparing simulated equilibrium states to thermodynamic calculations, as a function of temperature and pH. Finally, we demonstrate how HydratiCA can be used to investigate microstructure characteristics, such as spatial correlations between different condensed phases, in more complex microstructures.

Development of a two-dimensional zonally averaged statistical-dynamical model. III - The parameterization of the eddy fluxes of heat and moisture

NASA Technical Reports Server (NTRS)

Stone, Peter H.; Yao, Mao-Sung

1990-01-01

A number of perpetual January simulations are carried out with a two-dimensional zonally averaged model employing various parameterizations of the eddy fluxes of heat (potential temperature) and moisture. The parameterizations are evaluated by comparing these results with the eddy fluxes calculated in a parallel simulation using a three-dimensional general circulation model with zonally symmetric forcing. The three-dimensional model's performance in turn is evaluated by comparing its results using realistic (nonsymmetric) boundary conditions with observations. Branscome's parameterization of the meridional eddy flux of heat and Leovy's parameterization of the meridional eddy flux of moisture simulate the seasonal and latitudinal variations of these fluxes reasonably well, while somewhat underestimating their magnitudes. New parameterizations of the vertical eddy fluxes are developed that take into account the enhancement of the eddy mixing slope in a growing baroclinic wave due to condensation, and also the effect of eddy fluctuations in relative humidity. The new parameterizations, when tested in the two-dimensional model, simulate the seasonal, latitudinal, and vertical variations of the vertical eddy fluxes quite well, when compared with the three-dimensional model, and only underestimate the magnitude of the fluxes by 10 to 20 percent.

Changes in collagen fibril network organization and proteoglycan distribution in equine articular cartilage during maturation and growth

PubMed Central

Hyttinen, Mika M; Holopainen, Jaakko; René van Weeren, P; Firth, Elwyn C; Helminen, Heikki J; Brama, Pieter A J

2009-01-01

The aim of this study was to record growth-related changes in collagen network organization and proteoglycan distribution in intermittently peak-loaded and continuously lower-level-loaded articular cartilage. Cartilage from the proximal phalangeal bone of the equine metacarpophalangeal joint at birth, at 5, 11 and 18 months, and at 6–10 years of age was collected from two sites. Site 1, at the joint margin, is unloaded at slow gaits but is subjected to high-intensity loading during athletic activity; site 2 is a continuously but less intensively loaded site in the centre of the joint. The degree of collagen parallelism was determined with quantitative polarized light microscopy and the parallelism index for collagen fibrils was computed from the cartilage surface to the osteochondral junction. Concurrent changes in the proteoglycan distribution were quantified with digital densitometry. We found that the parallelism index increased significantly with age (up to 90%). At birth, site 2 exhibited a more organized collagen network than site 1. In adult horses this situation was reversed. The superficial and intermediate zones exhibited the greatest reorganization of collagen. Site 1 had a higher proteoglycan content than site 2 at birth but here too the situation was reversed in adult horses. We conclude that large changes in joint loading during growth and maturation in the period from birth to adulthood profoundly affect the architecture of the collagen network in equine cartilage. In addition, the distribution and content of proteoglycans are modified significantly by altered joint use. Intermittent peak-loading with shear seems to induce higher collagen parallelism and a lower proteoglycan content in cartilage than more constant weight-bearing. Therefore, we hypothesize that the formation of mature articular cartilage with a highly parallel collagen network and relatively low proteoglycan content in the peak-loaded area of a joint is needed to withstand intermittent stress and shear, whereas a constantly weight-bearing joint area benefits from lower collagen parallelism and a higher proteoglycan content. PMID:19732210

[Effect of the number and inclination of implant on stress distribution for mandibular full-arch fixed prosthesis].

PubMed

Zheng, Xiaoying; Li, Xiaomei; Tang, Zhen; Gong, Lulu; Wang, Dalin

2014-06-01

To study the effect of implant number and inclination on stress distribution in implant and its surrounding bone with three-dimensional finite element analysis. A special denture was made for an edentulous mandible cast to collect three-dimensional finite element data. Three three-dimensional finite element models were established as follows. Model 1: 6 paralleled implants; model 2: 4 paralleled implants; model 3: 4 implants, the two anterior implants were parallel, the two distal implants were tilted 30° distally. Among the three models, the maximum stress values found in anterior implants, posterior implants, and peri-implant bone were modle 3

Weak antilocalization in Cd3As2 thin films

PubMed Central

Zhao, Bo; Cheng, Peihong; Pan, Haiyang; Zhang, Shuai; Wang, Baigeng; Wang, Guanghou; Xiu, Faxian; Song, Fengqi

2016-01-01

Recently, it has been theoretically predicted that Cd3As2 is a three dimensional Dirac material, a new topological phase discovered after topological insulators, which exhibits a linear energy dispersion in the bulk with massless Dirac fermions. Here, we report on the low-temperature magnetoresistance measurements on a ~50 nm-thick Cd3As2 film. The weak antilocalization under perpendicular magnetic field is discussed based on the two-dimensional Hikami-Larkin-Nagaoka (HLN) theory. The electron-electron interaction is addressed as the source of the dephasing based on the temperature-dependent scaling behavior. The weak antilocalization can be also observed while the magnetic field is parallel to the electric field due to the strong interaction between the different conductance channels in this quasi-two-dimensional film. PMID:26935029

Weak antilocalization in Cd3As2 thin films.

PubMed

Zhao, Bo; Cheng, Peihong; Pan, Haiyang; Zhang, Shuai; Wang, Baigeng; Wang, Guanghou; Xiu, Faxian; Song, Fengqi

2016-03-03

Recently, it has been theoretically predicted that Cd3As2 is a three dimensional Dirac material, a new topological phase discovered after topological insulators, which exhibits a linear energy dispersion in the bulk with massless Dirac fermions. Here, we report on the low-temperature magnetoresistance measurements on a ~50 nm-thick Cd3As2 film. The weak antilocalization under perpendicular magnetic field is discussed based on the two-dimensional Hikami-Larkin-Nagaoka (HLN) theory. The electron-electron interaction is addressed as the source of the dephasing based on the temperature-dependent scaling behavior. The weak antilocalization can be also observed while the magnetic field is parallel to the electric field due to the strong interaction between the different conductance channels in this quasi-two-dimensional film.

Dynamical features and electric field strengths of double layers driven by currents. [in auroras

NASA Technical Reports Server (NTRS)

Singh, N.; Thiemann, H.; Schunk, R. W.

1985-01-01

In recent years, a number of papers have been concerned with 'ion-acoustic' double layers. In the present investigation, results from numerical simulations are presented to show that the shapes and forms of current-driven double layers evolve dynamically with the fluctuations in the current through the plasma. It is shown that double layers with a potential dip can form even without the excitation of ion-acoustic modes. Double layers in two-and one-half-dimensional simulations are discussed, taking into account the simulation technique, the spatial and temporal features of plasma, and the dynamical behavior of the parallel potential distribution. Attention is also given to double layers in one-dimensional simulations, and electrical field strengths predicted by two-and one-half-dimensional simulations.

Carbon nanotube dispersed conductive network for microbial fuel cells

NASA Astrophysics Data System (ADS)

Matsumoto, S.; Yamanaka, K.; Ogikubo, H.; Akasaka, H.; Ohtake, N.

2014-08-01

Microbial fuel cells (MFCs) are promising devices for capturing biomass energy. Although they have recently attracted considerable attention, their power densities are too low for practical use. Increasing their electrode surface area is a key factor for improving the performance of MFC. Carbon nanotubes (CNTs), which have excellent electrical conductivity and extremely high specific surface area, are promising materials for electrodes. However, CNTs are insoluble in aqueous solution because of their strong intertube van der Waals interactions, which make practical use of CNTs difficult. In this study, we revealed that CNTs have a strong interaction with Saccharomyces cerevisiae cells. CNTs attach to the cells and are dispersed in a mixture of water and S. cerevisiae, forming a three-dimensional CNT conductive network. Compared with a conventional two-dimensional electrode, such as carbon paper, the three-dimensional conductive network has a much larger surface area. By applying this conductive network to MFCs as an anode electrode, power density is increased to 176 μW/cm2, which is approximately 25-fold higher than that in the case without CNTs addition. Maximum current density is also increased to approximately 8-fold higher. These results suggest that three-dimensional CNT conductive network contributes to improve the performance of MFC by increasing surface area.

Digital and optical shape representation and pattern recognition; Proceedings of the Meeting, Orlando, FL, Apr. 4-6, 1988

NASA Technical Reports Server (NTRS)

Juday, Richard D. (Editor)

1988-01-01

The present conference discusses topics in pattern-recognition correlator architectures, digital stereo systems, geometric image transformations and their applications, topics in pattern recognition, filter algorithms, object detection and classification, shape representation techniques, and model-based object recognition methods. Attention is given to edge-enhancement preprocessing using liquid crystal TVs, massively-parallel optical data base management, three-dimensional sensing with polar exponential sensor arrays, the optical processing of imaging spectrometer data, hybrid associative memories and metric data models, the representation of shape primitives in neural networks, and the Monte Carlo estimation of moment invariants for pattern recognition.

Neuromorphic computing with nanoscale spintronic oscillators.

PubMed

Torrejon, Jacob; Riou, Mathieu; Araujo, Flavio Abreu; Tsunegi, Sumito; Khalsa, Guru; Querlioz, Damien; Bortolotti, Paolo; Cros, Vincent; Yakushiji, Kay; Fukushima, Akio; Kubota, Hitoshi; Yuasa, Shinji; Stiles, Mark D; Grollier, Julie

2017-07-26

Neurons in the brain behave as nonlinear oscillators, which develop rhythmic activity and interact to process information. Taking inspiration from this behaviour to realize high-density, low-power neuromorphic computing will require very large numbers of nanoscale nonlinear oscillators. A simple estimation indicates that to fit 10 8 oscillators organized in a two-dimensional array inside a chip the size of a thumb, the lateral dimension of each oscillator must be smaller than one micrometre. However, nanoscale devices tend to be noisy and to lack the stability that is required to process data in a reliable way. For this reason, despite multiple theoretical proposals and several candidates, including memristive and superconducting oscillators, a proof of concept of neuromorphic computing using nanoscale oscillators has yet to be demonstrated. Here we show experimentally that a nanoscale spintronic oscillator (a magnetic tunnel junction) can be used to achieve spoken-digit recognition with an accuracy similar to that of state-of-the-art neural networks. We also determine the regime of magnetization dynamics that leads to the greatest performance. These results, combined with the ability of the spintronic oscillators to interact with each other, and their long lifetime and low energy consumption, open up a path to fast, parallel, on-chip computation based on networks of oscillators.

Bounds on the number of hidden neurons in three-layer binary neural networks.

PubMed

Zhang, Zhaozhi; Ma, Xiaomin; Yang, Yixian

2003-09-01

This paper investigates an important problem concerning the complexity of three-layer binary neural networks (BNNs) with one hidden layer. The neuron in the studied BNNs employs a hard limiter activation function with only integer weights and an integer threshold. The studies are focused on implementations of arbitrary Boolean functions which map from [0, 1]n into [0, 1]. A deterministic algorithm called set covering algorithm (SCA) is proposed for the construction of a three-layer BNN to implement an arbitrary Boolean function. The SCA is based on a unit sphere covering (USC) of the Hamming space (HS) which is chosen in advance. It is proved that for the implementation of an arbitrary Boolean function of n-variables (n > or = 3) by using SCA, [3L/2] hidden neurons are necessary and sufficient, where L is the number of unit spheres contained in the chosen USC of the n-dimensional HS. It is shown that by using SCA, the number of hidden neurons required is much less than that by using a two-parallel hyperplane method. In order to indicate the potential ability of three-layer BNNs, a lower bound on the required number of hidden neurons which is derived by using the method of estimating the Vapnik-Chervonenkis (VC) dimension is also given.

Linear stability of three-dimensional boundary layers - Effects of curvature and non-parallelism

NASA Technical Reports Server (NTRS)

Malik, M. R.; Balakumar, P.

1993-01-01

In this paper we study the effect of in-plane (wavefront) curvature on the stability of three-dimensional boundary layers. It is found that this effect is stabilizing or destabilizing depending upon the sign of the crossflow velocity profile. We also investigate the effects of surface curvature and nonparallelism on crossflow instability. Computations performed for an infinite-swept cylinder show that while convex curvature stabilizes the three-dimensional boundary layer, nonparallelism is, in general, destabilizing and the net effect of the two depends upon meanflow and disturbance parameters. It is also found that concave surface curvature further destabilizes the crossflow instability.

Constructing Neuronal Network Models in Massively Parallel Environments.

PubMed

Ippen, Tammo; Eppler, Jochen M; Plesser, Hans E; Diesmann, Markus

2017-01-01

Recent advances in the development of data structures to represent spiking neuron network models enable us to exploit the complete memory of petascale computers for a single brain-scale network simulation. In this work, we investigate how well we can exploit the computing power of such supercomputers for the creation of neuronal networks. Using an established benchmark, we divide the runtime of simulation code into the phase of network construction and the phase during which the dynamical state is advanced in time. We find that on multi-core compute nodes network creation scales well with process-parallel code but exhibits a prohibitively large memory consumption. Thread-parallel network creation, in contrast, exhibits speedup only up to a small number of threads but has little overhead in terms of memory. We further observe that the algorithms creating instances of model neurons and their connections scale well for networks of ten thousand neurons, but do not show the same speedup for networks of millions of neurons. Our work uncovers that the lack of scaling of thread-parallel network creation is due to inadequate memory allocation strategies and demonstrates that thread-optimized memory allocators recover excellent scaling. An analysis of the loop order used for network construction reveals that more complex tests on the locality of operations significantly improve scaling and reduce runtime by allowing construction algorithms to step through large networks more efficiently than in existing code. The combination of these techniques increases performance by an order of magnitude and harnesses the increasingly parallel compute power of the compute nodes in high-performance clusters and supercomputers.

Constructing Neuronal Network Models in Massively Parallel Environments

PubMed Central

Ippen, Tammo; Eppler, Jochen M.; Plesser, Hans E.; Diesmann, Markus

2017-01-01

Recent advances in the development of data structures to represent spiking neuron network models enable us to exploit the complete memory of petascale computers for a single brain-scale network simulation. In this work, we investigate how well we can exploit the computing power of such supercomputers for the creation of neuronal networks. Using an established benchmark, we divide the runtime of simulation code into the phase of network construction and the phase during which the dynamical state is advanced in time. We find that on multi-core compute nodes network creation scales well with process-parallel code but exhibits a prohibitively large memory consumption. Thread-parallel network creation, in contrast, exhibits speedup only up to a small number of threads but has little overhead in terms of memory. We further observe that the algorithms creating instances of model neurons and their connections scale well for networks of ten thousand neurons, but do not show the same speedup for networks of millions of neurons. Our work uncovers that the lack of scaling of thread-parallel network creation is due to inadequate memory allocation strategies and demonstrates that thread-optimized memory allocators recover excellent scaling. An analysis of the loop order used for network construction reveals that more complex tests on the locality of operations significantly improve scaling and reduce runtime by allowing construction algorithms to step through large networks more efficiently than in existing code. The combination of these techniques increases performance by an order of magnitude and harnesses the increasingly parallel compute power of the compute nodes in high-performance clusters and supercomputers. PMID:28559808

Anatomically constrained neural network models for the categorization of facial expression

NASA Astrophysics Data System (ADS)

McMenamin, Brenton W.; Assadi, Amir H.

2004-12-01

The ability to recognize facial expression in humans is performed with the amygdala which uses parallel processing streams to identify the expressions quickly and accurately. Additionally, it is possible that a feedback mechanism may play a role in this process as well. Implementing a model with similar parallel structure and feedback mechanisms could be used to improve current facial recognition algorithms for which varied expressions are a source for error. An anatomically constrained artificial neural-network model was created that uses this parallel processing architecture and feedback to categorize facial expressions. The presence of a feedback mechanism was not found to significantly improve performance for models with parallel architecture. However the use of parallel processing streams significantly improved accuracy over a similar network that did not have parallel architecture. Further investigation is necessary to determine the benefits of using parallel streams and feedback mechanisms in more advanced object recognition tasks.

Anatomically constrained neural network models for the categorization of facial expression

NASA Astrophysics Data System (ADS)

McMenamin, Brenton W.; Assadi, Amir H.

2005-01-01

The ability to recognize facial expression in humans is performed with the amygdala which uses parallel processing streams to identify the expressions quickly and accurately. Additionally, it is possible that a feedback mechanism may play a role in this process as well. Implementing a model with similar parallel structure and feedback mechanisms could be used to improve current facial recognition algorithms for which varied expressions are a source for error. An anatomically constrained artificial neural-network model was created that uses this parallel processing architecture and feedback to categorize facial expressions. The presence of a feedback mechanism was not found to significantly improve performance for models with parallel architecture. However the use of parallel processing streams significantly improved accuracy over a similar network that did not have parallel architecture. Further investigation is necessary to determine the benefits of using parallel streams and feedback mechanisms in more advanced object recognition tasks.

Flux quantization in periodic networks containing tiles with irrational ratio of areas

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

Santhanam, P.; Chi, C.C.; Molzen, W.W.

1988-02-01

We report measurements of the superconducting-normal transition boundary T/sub c/(H) of two-dimensional periodic networks with two different space-group symmetries in a magnetic field. Each network is a mixture of squares and equilateral triangles. In both cases, we observe maxima in T/sub c/(H) with one major period, which does not correspond to the area of either the square or the triangle. We interpret the results in terms of flux configurations whose energies are sensitive to the geometry of a given network.

Statistical investigation of avalanches of three-dimensional small-world networks and their boundary and bulk cross-sections

NASA Astrophysics Data System (ADS)

Najafi, M. N.; Dashti-Naserabadi, H.

2018-03-01

In many situations we are interested in the propagation of energy in some portions of a three-dimensional system with dilute long-range links. In this paper, a sandpile model is defined on the three-dimensional small-world network with real dissipative boundaries and the energy propagation is studied in three dimensions as well as the two-dimensional cross-sections. Two types of cross-sections are defined in the system, one in the bulk and another in the system boundary. The motivation of this is to make clear how the statistics of the avalanches in the bulk cross-section tend to the statistics of the dissipative avalanches, defined in the boundaries as the concentration of long-range links (α ) increases. This trend is numerically shown to be a power law in a manner described in the paper. Two regimes of α are considered in this work. For sufficiently small α s the dominant behavior of the system is just like that of the regular BTW, whereas for the intermediate values the behavior is nontrivial with some exponents that are reported in the paper. It is shown that the spatial extent up to which the statistics is similar to the regular BTW model scales with α just like the dissipative BTW model with the dissipation factor (mass in the corresponding ghost model) m2˜α for the three-dimensional system as well as its two-dimensional cross-sections.

Multiphase three-dimensional direct numerical simulation of a rotating impeller with code Blue

NASA Astrophysics Data System (ADS)

Kahouadji, Lyes; Shin, Seungwon; Chergui, Jalel; Juric, Damir; Craster, Richard V.; Matar, Omar K.

2017-11-01

The flow driven by a rotating impeller inside an open fixed cylindrical cavity is simulated using code Blue, a solver for massively-parallel simulations of fully three-dimensional multiphase flows. The impeller is composed of four blades at a 45° inclination all attached to a central hub and tube stem. In Blue, solid forms are constructed through the definition of immersed objects via a distance function that accounts for the object's interaction with the flow for both single and two-phase flows. We use a moving frame technique for imposing translation and/or rotation. The variation of the Reynolds number, the clearance, and the tank aspect ratio are considered, and we highlight the importance of the confinement ratio (blade radius versus the tank radius) in the mixing process. Blue uses a domain decomposition strategy for parallelization with MPI. The fluid interface solver is based on a parallel implementation of a hybrid front-tracking/level-set method designed complex interfacial topological changes. Parallel GMRES and multigrid iterative solvers are applied to the linear systems arising from the implicit solution for the fluid velocities and pressure in the presence of strong density and viscosity discontinuities across fluid phases. EPSRC, UK, MEMPHIS program Grant (EP/K003976/1), RAEng Research Chair (OKM).

A Bootstrap Generalization of Modified Parallel Analysis for IRT Dimensionality Assessment

ERIC Educational Resources Information Center

Finch, Holmes; Monahan, Patrick

2008-01-01

This article introduces a bootstrap generalization to the Modified Parallel Analysis (MPA) method of test dimensionality assessment using factor analysis. This methodology, based on the use of Marginal Maximum Likelihood nonlinear factor analysis, provides for the calculation of a test statistic based on a parametric bootstrap using the MPA…

Liouville action as path-integral complexity: from continuous tensor networks to AdS/CFT

NASA Astrophysics Data System (ADS)

Caputa, Pawel; Kundu, Nilay; Miyaji, Masamichi; Takayanagi, Tadashi; Watanabe, Kento

2017-11-01

We propose an optimization procedure for Euclidean path-integrals that evaluate CFT wave functionals in arbitrary dimensions. The optimization is performed by minimizing certain functional, which can be interpreted as a measure of computational complexity, with respect to background metrics for the path-integrals. In two dimensional CFTs, this functional is given by the Liouville action. We also formulate the optimization for higher dimensional CFTs and, in various examples, find that the optimized hyperbolic metrics coincide with the time slices of expected gravity duals. Moreover, if we optimize a reduced density matrix, the geometry becomes two copies of the entanglement wedge and reproduces the holographic entanglement entropy. Our approach resembles a continuous tensor network renormalization and provides a concrete realization of the proposed interpretation of AdS/CFT as tensor networks. The present paper is an extended version of our earlier report arXiv:1703.00456 and includes many new results such as evaluations of complexity functionals, energy stress tensor, higher dimensional extensions and time evolutions of thermofield double states.

Combustion monitoring of a water tube boiler using a discriminant radial basis network.

PubMed

Sujatha, K; Pappa, N

2011-01-01

This research work includes a combination of Fisher's linear discriminant (FLD) analysis and a radial basis network (RBN) for monitoring the combustion conditions for a coal fired boiler so as to allow control of the air/fuel ratio. For this, two-dimensional flame images are required, which were captured with a CCD camera; the features of the images-average intensity, area, brightness and orientation etc of the flame-are extracted after preprocessing the images. The FLD is applied to reduce the n-dimensional feature size to a two-dimensional feature size for faster learning of the RBN. Also, three classes of images corresponding to different burning conditions of the flames have been extracted from continuous video processing. In this, the corresponding temperatures, and the carbon monoxide (CO) emissions and those of other flue gases have been obtained through measurement. Further, the training and testing of Fisher's linear discriminant radial basis network (FLDRBN), with the data collected, have been carried out and the performance of the algorithms is presented. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Comparative analysis of two discretizations of Ricci curvature for complex networks.

PubMed

Samal, Areejit; Sreejith, R P; Gu, Jiao; Liu, Shiping; Saucan, Emil; Jost, Jürgen

2018-06-05

We have performed an empirical comparison of two distinct notions of discrete Ricci curvature for graphs or networks, namely, the Forman-Ricci curvature and Ollivier-Ricci curvature. Importantly, these two discretizations of the Ricci curvature were developed based on different properties of the classical smooth notion, and thus, the two notions shed light on different aspects of network structure and behavior. Nevertheless, our extensive computational analysis in a wide range of both model and real-world networks shows that the two discretizations of Ricci curvature are highly correlated in many networks. Moreover, we show that if one considers the augmented Forman-Ricci curvature which also accounts for the two-dimensional simplicial complexes arising in graphs, the observed correlation between the two discretizations is even higher, especially, in real networks. Besides the potential theoretical implications of these observations, the close relationship between the two discretizations has practical implications whereby Forman-Ricci curvature can be employed in place of Ollivier-Ricci curvature for faster computation in larger real-world networks whenever coarse analysis suffices.

Evaluation of a two-dimensional numerical model for air quality simulation in a street canyon

NASA Astrophysics Data System (ADS)

Okamoto, Shin `Ichi; Lin, Fu Chi; Yamada, Hiroaki; Shiozawa, Kiyoshige

For many urban areas, the most severe air pollution caused by automobile emissions appears along a road surrounded by tall buildings: the so=called street canyon. A practical two-dimensional numerical model has been developed to be applied to this kind of road structure. This model contains two submodels: a wind-field model and a diffusion model based on a Monte Carlo particle scheme. In order to evaluate the predictive performance of this model, an air quality simulation was carried out at three trunk roads in the Tokyo metropolitan area: Nishi-Shimbashi, Aoyama and Kanda-Nishikicho (using SF 6 as a tracer and NO x measurement). Since this model has two-dimensional properties and cannot be used for the parallel wind condition, the perpendicular wind condition was selected for the simulation. The correlation coefficients for the SF 6 and NO x data in Aoyama were 0.67 and 0.62, respectively. When predictive performance of this model is compared with other models, this model is comparable to the SRI model, and superior to the APPS three-dimensional numerical model.

Web-Based Learning in the Computer-Aided Design Curriculum.

ERIC Educational Resources Information Center

Sung, Wen-Tsai; Ou, S. C.

2002-01-01

Applies principles of constructivism and virtual reality (VR) to computer-aided design (CAD) curriculum, particularly engineering, by integrating network, VR and CAD technologies into a Web-based learning environment that expands traditional two-dimensional computer graphics into a three-dimensional real-time simulation that enhances user…

Low-dimensional recurrent neural network-based Kalman filter for speech enhancement.

PubMed

Xia, Youshen; Wang, Jun

2015-07-01

This paper proposes a new recurrent neural network-based Kalman filter for speech enhancement, based on a noise-constrained least squares estimate. The parameters of speech signal modeled as autoregressive process are first estimated by using the proposed recurrent neural network and the speech signal is then recovered from Kalman filtering. The proposed recurrent neural network is globally asymptomatically stable to the noise-constrained estimate. Because the noise-constrained estimate has a robust performance against non-Gaussian noise, the proposed recurrent neural network-based speech enhancement algorithm can minimize the estimation error of Kalman filter parameters in non-Gaussian noise. Furthermore, having a low-dimensional model feature, the proposed neural network-based speech enhancement algorithm has a much faster speed than two existing recurrent neural networks-based speech enhancement algorithms. Simulation results show that the proposed recurrent neural network-based speech enhancement algorithm can produce a good performance with fast computation and noise reduction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Parametric Study of Afterbody/nozzle Drag on Twin Two-dimensional Convergent-divergent Nozzles at Mach Numbers from 0.60 to 1.20

NASA Technical Reports Server (NTRS)

Pendergraft, Odis C., Jr.; Burley, James R., II; Bare, E. Ann

1986-01-01

An investigation has been conducted in the Langley 16-Foot Transonic Tunnel to determine the effects of upper and lower external nozzle flap geometry on the external afterbody/nozzle drag of nonaxisymmetric two-dimensional convergent-divergent exhaust nozzles having parallel external sidewalls installed on a generic twin-engine, fighter-aircraft model. Tests were conducted over a Mach number range from 0.60 to 1.20 and over an angle-of-attack range from -5 to 9 deg. Nozzle pressure ratio was varied from jet off (1.0) to approximately 10.0, depending on Mach number.

Charge order-superfluidity transition in a two-dimensional system of hard-core bosons and emerging domain structures

NASA Astrophysics Data System (ADS)

Moskvin, A. S.; Panov, Yu. D.; Rybakov, F. N.; Borisov, A. B.

2017-11-01

We have used high-performance parallel computations by NVIDIA graphics cards applying the method of nonlinear conjugate gradients and Monte Carlo method to observe directly the developing ground state configuration of a two-dimensional hard-core boson system with decrease in temperature, and its evolution with deviation from a half-filling. This has allowed us to explore unconventional features of a charge order—superfluidity phase transition, specifically, formation of an irregular domain structure, emergence of a filamentary superfluid structure that condenses within of the charge-ordered phase domain antiphase boundaries, and formation and evolution of various topological structures.

Anisotropic mean-square displacements in two-dimensional colloidal crystals of tilted dipoles

NASA Astrophysics Data System (ADS)

Froltsov, V. A.; Likos, C. N.; Löwen, H.; Eisenmann, C.; Gasser, U.; Keim, P.; Maret, G.

2005-03-01

Superparamagnetic colloidal particles confined to a flat horizontal air-water interface in an external magnetic field, which is tilted relative to the interface, form anisotropic two-dimensional crystals resulting from their mutual dipole-dipole interactions. Using real-space experiments and harmonic lattice theory we explore the mean-square displacements of the particles in the directions parallel and perpendicular to the in-plane component of the external magnetic field as a function of the tilt angle. We find that the anisotropy of the mean-square displacement behaves nonmonotonically as a function of the tilt angle and does not correlate with the structural anisotropy of the crystal.

Upscaling permeability for three-dimensional fractured porous rocks with the multiple boundary method

NASA Astrophysics Data System (ADS)

Chen, Tao; Clauser, Christoph; Marquart, Gabriele; Willbrand, Karen; Hiller, Thomas

2018-02-01

Upscaling permeability of grid blocks is crucial for groundwater models. A novel upscaling method for three-dimensional fractured porous rocks is presented. The objective of the study was to compare this method with the commonly used Oda upscaling method and the volume averaging method. First, the multiple boundary method and its computational framework were defined for three-dimensional stochastic fracture networks. Then, the different upscaling methods were compared for a set of rotated fractures, for tortuous fractures, and for two discrete fracture networks. The results computed by the multiple boundary method are comparable with those of the other two methods and fit best the analytical solution for a set of rotated fractures. The errors in flow rate of the equivalent fracture model decrease when using the multiple boundary method. Furthermore, the errors of the equivalent fracture models increase from well-connected fracture networks to poorly connected ones. Finally, the diagonal components of the equivalent permeability tensors tend to follow a normal or log-normal distribution for the well-connected fracture network model with infinite fracture size. By contrast, they exhibit a power-law distribution for the poorly connected fracture network with multiple scale fractures. The study demonstrates the accuracy and the flexibility of the multiple boundary upscaling concept. This makes it attractive for being incorporated into any existing flow-based upscaling procedures, which helps in reducing the uncertainty of groundwater models.

Smart-Pixel Array Processors Based on Optimal Cellular Neural Networks for Space Sensor Applications

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi; Sheu, Bing J.; Venus, Holger; Sandau, Rainer

1997-01-01

A smart-pixel cellular neural network (CNN) with hardware annealing capability, digitally programmable synaptic weights, and multisensor parallel interface has been under development for advanced space sensor applications. The smart-pixel CNN architecture is a programmable multi-dimensional array of optoelectronic neurons which are locally connected with their local neurons and associated active-pixel sensors. Integration of the neuroprocessor in each processor node of a scalable multiprocessor system offers orders-of-magnitude computing performance enhancements for on-board real-time intelligent multisensor processing and control tasks of advanced small satellites. The smart-pixel CNN operation theory, architecture, design and implementation, and system applications are investigated in detail. The VLSI (Very Large Scale Integration) implementation feasibility was illustrated by a prototype smart-pixel 5x5 neuroprocessor array chip of active dimensions 1380 micron x 746 micron in a 2-micron CMOS technology.

Crystal structure of N,N,N′,N′,N′′,N′′-hexa­methyl­guanidinium cyanate 1.5-hydrate

PubMed Central

Tiritiris, Ioannis; Kantlehner, Willi

2015-01-01

The title hydrated salt, C7H18N3 +·OCN−.1.5H2O, was synthesized starting from N,N,N′,N′,N′′,N′′-hexa­methyl­guanidinium chloride by a twofold anion-exchange reaction. The asymmetric unit contains two cations, two cyanate anions and three water mol­ecules. One cation shows orientational disorder and two sets of N-atom positions were found related by a 60° rotation, with an occupancy ratio of 0.852 (6):0.148 (6). The C—N bond lengths in both guanidin­ium ions range from 1.329 (2) to 1.358 (10) Å, indicating double-bond character, pointing towards charge delocalization within the NCN planes. Strong O—H⋯N hydrogen bonds between the crystal water mol­ecules and the cyanate ions and strong O—H⋯O hydrogen bonds between the water mol­ecules are present, resulting in a two-dimensional hydrogen bonded network running parallel to the (001) plane. The hexa­methyl­guanidinium ions are packed in between the layers built up by water mol­ecules and cyanate ions. PMID:26870506

The 2.5-dimensional equivalent sources method for directly exposed and shielded urban canyons.

PubMed

Hornikx, Maarten; Forssén, Jens

2007-11-01

When a domain in outdoor acoustics is invariant in one direction, an inverse Fourier transform can be used to transform solutions of the two-dimensional Helmholtz equation to a solution of the three-dimensional Helmholtz equation for arbitrary source and observer positions, thereby reducing the computational costs. This previously published approach [D. Duhamel, J. Sound Vib. 197, 547-571 (1996)] is called a 2.5-dimensional method and has here been extended to the urban geometry of parallel canyons, thereby using the equivalent sources method to generate the two-dimensional solutions. No atmospheric effects are considered. To keep the error arising from the transform small, two-dimensional solutions with a very fine frequency resolution are necessary due to the multiple reflections in the canyons. Using the transform, the solution for an incoherent line source can be obtained much more efficiently than by using the three-dimensional solution. It is shown that the use of a coherent line source for shielded urban canyon observer positions leads mostly to an overprediction of levels and can yield erroneous results for noise abatement schemes. Moreover, the importance of multiple facade reflections in shielded urban areas is emphasized by vehicle pass-by calculations, where cases with absorptive and diffusive surfaces have been modeled.

3D printed soft parallel actuator

NASA Astrophysics Data System (ADS)

Zolfagharian, Ali; Kouzani, Abbas Z.; Khoo, Sui Yang; Noshadi, Amin; Kaynak, Akif

2018-04-01

This paper presents a 3-dimensional (3D) printed soft parallel contactless actuator for the first time. The actuator involves an electro-responsive parallel mechanism made of two segments namely active chain and passive chain both 3D printed. The active chain is attached to the ground from one end and constitutes two actuator links made of responsive hydrogel. The passive chain, on the other hand, is attached to the active chain from one end and consists of two rigid links made of polymer. The actuator links are printed using an extrusion-based 3D-Bioplotter with polyelectrolyte hydrogel as printer ink. The rigid links are also printed by a 3D fused deposition modelling (FDM) printer with acrylonitrile butadiene styrene (ABS) as print material. The kinematics model of the soft parallel actuator is derived via transformation matrices notations to simulate and determine the workspace of the actuator. The printed soft parallel actuator is then immersed into NaOH solution with specific voltage applied to it via two contactless electrodes. The experimental data is then collected and used to develop a parametric model to estimate the end-effector position and regulate kinematics model in response to specific input voltage over time. It is observed that the electroactive actuator demonstrates expected behaviour according to the simulation of its kinematics model. The use of 3D printing for the fabrication of parallel soft actuators opens a new chapter in manufacturing sophisticated soft actuators with high dexterity and mechanical robustness for biomedical applications such as cell manipulation and drug release.

Dense wavelength division multiplexing devices for metropolitan-area datacom and telecom networks

NASA Astrophysics Data System (ADS)

DeCusatis, Casimer M.; Priest, David G.

2000-12-01

Large data processing environments in use today can require multi-gigabyte or terabyte capacity in the data communication infrastructure; these requirements are being driven by storage area networks with access to petabyte data bases, new architecture for parallel processing which require high bandwidth optical links, and rapidly growing network applications such as electronic commerce over the Internet or virtual private networks. These datacom applications require high availability, fault tolerance, security, and the capacity to recover from any single point of failure without relying on traditional SONET-based networking. These requirements, coupled with fiber exhaust in metropolitan areas, are driving the introduction of dense optical wavelength division multiplexing (DWDM) in data communication systems, particularly for large enterprise servers or mainframes. In this paper, we examine the technical requirements for emerging nextgeneration DWDM systems. Protocols for storage area networks and computer architectures such as Parallel Sysplex are presented, including their fiber bandwidth requirements. We then describe two commercially available DWDM solutions, a first generation 10 channel system and a recently announced next generation 32 channel system. Technical requirements, network management and security, fault tolerant network designs, new network topologies enabled by DWDM, and the role of time division multiplexing in the network are all discussed. Finally, we present a description of testing conducted on these networks and future directions for this technology.

Polymorphic organization of the endoplasmic reticulum of the Malpighian tubule. Evidence for a transcellular route.

PubMed

Berthelet, F; Beaudry-Lonergan, M; Linares, H; Whittembury, G; Bergeron, M

1987-01-01

Isosmotic fluid absorption carried out by many mammalian epithelia appears to be similar to the isosmotic secretion of insect epithelia such as the Malpighian tubules, which are responsible for urine formation and osmoregulation. We have studied by electron microscopy (80 kV) the three-dimensional characteristics of organelles in the Malpighian tubules of Rhodnius prolixus using thick sections (0.3-0.5 microns) and uranyl and lead impregnation. The ER presents a different organization in the upper (distal) and lower (proximal) segments of the Malpighian tubule. In distal secretory segment, the ER forms a network made of chains of vesicles having irregular shapes (ca. 0.06 micron in diameter) connected to each other by canaliculi while in the lower absorptive segment, the ER is made of parallel saccules arranged in stacks or whorls in the central region of the cytoplasm. In both segments, the ER network extends throughout the cytoplasm from the basolateral infoldings to the apex between the many mitochondria present in these two areas. A unique feature of these cells, revealed by thick sections, is the presence in each microvillus of either a mitochondrion or an ER canaliculus in continuity with the ER network. The ER does not seem to have any specific association with mitochondria or other organelles. As in the mammalian nephron, this ER organization is most likely related to specific segmental functions and adds support to its potential role as a transcellular epithelial route.

Investigation of the components of the NAL high Reynolds number two-dimensional wind tunnel. Part 4: Design, construction and performance of the exhaust silencer

NASA Technical Reports Server (NTRS)

Sakakibara, S.; Miwa, H.; Kayaba, S.; Sato, M.

1986-01-01

Presented is a description of the design construction and performance of the exhaust silencer for the NAL high Reynolds number two-dimensional transonic blow down wind tunnel, which was completed in October 1979. The silencer is a two-storied construction made of reinforced concrete, 40 m. long, 10 m. wide and 19 m. high and entirely enclosed by thick concrete walls. The upstream part of the first story, particularly, is covered with double walls, the thickness of the two walls being 0.3 m. (inner wall) and 0.2 m. (outer wall), respectively. A noise reduction system using three kinds of parallel baffles and two kinds of lined bends is adopted for the wind tunnel exhaust noise.

Wet Chemistry Synthesis of Multidimensional Nanocarbon-Sulfur Hybrid Materials with Ultrahigh Sulfur Loading for Lithium-Sulfur Batteries.

PubMed

Du, Wen-Cheng; Yin, Ya-Xia; Zeng, Xian-Xiang; Shi, Ji-Lei; Zhang, Shuai-Feng; Wan, Li-Jun; Guo, Yu-Guo

2016-02-17

An optimized nanocarbon-sulfur cathode material with ultrahigh sulfur loading of up to 90 wt % is realized in the form of sulfur nanolayer-coated three-dimensional (3D) conducting network. This 3D nanocarbon-sulfur network combines three different nanocarbons, as follows: zero-dimensional carbon nanoparticle, one-dimensional carbon nanotube, and two-dimensional graphene. This 3D nanocarbon-sulfur network is synthesized by using a method based on soluble chemistry of elemental sulfur and three types of nanocarbons in well-chosen solvents. The resultant sulfur-carbon material shows a high specific capacity of 1115 mA h g(-1) at 0.02C and good rate performance of 551 mA h g(-1) at 1C based on the mass of sulfur-carbon composite. Good battery performance can be attributed to the homogeneous compositing of sulfur with the 3D hierarchical hybrid nanocarbon networks at nanometer scale, which provides efficient multidimensional transport pathways for electrons and ions. Wet chemical method developed here provides an easy and cost-effective way to prepare sulfur-carbon cathode materials with high sulfur loading for application in high-energy Li-S batteries.

On the impact of communication complexity in the design of parallel numerical algorithms

NASA Technical Reports Server (NTRS)

Gannon, D.; Vanrosendale, J.

1984-01-01

This paper describes two models of the cost of data movement in parallel numerical algorithms. One model is a generalization of an approach due to Hockney, and is suitable for shared memory multiprocessors where each processor has vector capabilities. The other model is applicable to highly parallel nonshared memory MIMD systems. In the second model, algorithm performance is characterized in terms of the communication network design. Techniques used in VLSI complexity theory are also brought in, and algorithm independent upper bounds on system performance are derived for several problems that are important to scientific computation.

On the impact of communication complexity on the design of parallel numerical algorithms

NASA Technical Reports Server (NTRS)

Gannon, D. B.; Van Rosendale, J.

1984-01-01

This paper describes two models of the cost of data movement in parallel numerical alorithms. One model is a generalization of an approach due to Hockney, and is suitable for shared memory multiprocessors where each processor has vector capabilities. The other model is applicable to highly parallel nonshared memory MIMD systems. In this second model, algorithm performance is characterized in terms of the communication network design. Techniques used in VLSI complexity theory are also brought in, and algorithm-independent upper bounds on system performance are derived for several problems that are important to scientific computation.

One-dimensional and two-dimensional hydrodynamic modelling derived flow properties: Impacts on aquatic habitat quality predictions

Treesearch

Rohan Benjankar; Daniele Tonina; James McKean

2014-01-01

Studies of the effects of hydrodynamic model dimensionality on simulated flow properties and derived quantities such as aquatic habitat quality are limited. It is important to close this knowledge gap especially now that entire river networks can be mapped at the microhabitat scale due to the advent of point-cloud techniques. This study compares flow properties, such...

Parallel representation of stimulus identity and intensity in a dual pathway model inspired by the olfactory system of the honeybee.

PubMed

Schmuker, Michael; Yamagata, Nobuhiro; Nawrot, Martin Paul; Menzel, Randolf

2011-01-01

The honeybee Apis mellifera has a remarkable ability to detect and locate food sources during foraging, and to associate odor cues with food rewards. In the honeybee's olfactory system, sensory input is first processed in the antennal lobe (AL) network. Uniglomerular projection neurons (PNs) convey the sensory code from the AL to higher brain regions via two parallel but anatomically distinct pathways, the lateral and the medial antenno-cerebral tract (l- and m-ACT). Neurons innervating either tract show characteristic differences in odor selectivity, concentration dependence, and representation of mixtures. It is still unknown how this differential stimulus representation is achieved within the AL network. In this contribution, we use a computational network model to demonstrate that the experimentally observed features of odor coding in PNs can be reproduced by varying lateral inhibition and gain control in an otherwise unchanged AL network. We show that odor coding in the l-ACT supports detection and accurate identification of weak odor traces at the expense of concentration sensitivity, while odor coding in the m-ACT provides the basis for the computation and following of concentration gradients but provides weaker discrimination power. Both coding strategies are mutually exclusive, which creates a tradeoff between detection accuracy and sensitivity. The development of two parallel systems may thus reflect an evolutionary solution to this problem that enables honeybees to achieve both tasks during bee foraging in their natural environment, and which could inspire the development of artificial chemosensory devices for odor-guided navigation in robots.

Separating figure from ground with a parallel network.

PubMed

Kienker, P K; Sejnowski, T J; Hinton, G E; Schumacher, L E

1986-01-01

The differentiation of figure from ground plays an important role in the perceptual organization of visual stimuli. The rapidity with which we can discriminate the inside from the outside of a figure suggests that at least this step in the process may be performed in visual cortex by a large number of neurons in several different areas working together in parallel. We have attempted to simulate this collective computation by designing a network of simple processing units that receives two types of information: bottom-up input from the image containing the outlines of a figure, which may be incomplete, and a top-down attentional input that biases one part of the image to be the inside of the figure. No presegmentation of the image was assumed. Two methods for performing the computation were explored: gradient descent, which seeks locally optimal states, and simulated annealing, which attempts to find globally optimal states by introducing noise into the computation. For complete outlines, gradient descent was faster, but the range of input parameters leading to successful performance was very narrow. In contrast, simulated annealing was more robust: it worked over a wider range of attention parameters and a wider range of outlines, including incomplete ones. Our network model is too simplified to serve as a model of human performance, but it does demonstrate that one global property of outlines can be computed through local interactions in a parallel network. Some features of the model, such as the role of noise in escaping from nonglobal optima, may generalize to more realistic models.

Distributed Processing System for Restoration of Electric Power Distribution Network Using Two-Layered Contract Net Protocol

NASA Astrophysics Data System (ADS)

Kodama, Yu; Hamagami, Tomoki

Distributed processing system for restoration of electric power distribution network using two-layered CNP is proposed. The goal of this study is to develop the restoration system which adjusts to the future power network with distributed generators. The state of the art of this study is that the two-layered CNP is applied for the distributed computing environment in practical use. The two-layered CNP has two classes of agents, named field agent and operating agent in the network. In order to avoid conflicts of tasks, operating agent controls privilege for managers to send the task announcement messages in CNP. This technique realizes the coordination between agents which work asynchronously in parallel with others. Moreover, this study implements the distributed processing system using a de-fact standard multi-agent framework, JADE(Java Agent DEvelopment framework). This study conducts the simulation experiments of power distribution network restoration and compares the proposed system with the previous system. We confirmed the results show effectiveness of the proposed system.

Fencing data transfers in a parallel active messaging interface of a parallel computer

DOEpatents

Blocksome, Michael A.; Mamidala, Amith R.

2015-08-11

Fencing data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint comprising a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes coupled for data communications through the PAMI and through data communications resources including a deterministic data communications network, including initiating execution through the PAMI of an ordered sequence of active SEND instructions for SEND data transfers between two endpoints, effecting deterministic SEND data transfers; and executing through the PAMI, with no FENCE accounting for SEND data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all SEND instructions initiated prior to execution of the FENCE instruction for SEND data transfers between the two endpoints.

Fencing data transfers in a parallel active messaging interface of a parallel computer

DOEpatents

Blocksome, Michael A.; Mamidala, Amith R.

2015-06-30

Fencing data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint comprising a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes coupled for data communications through the PAMI and through data communications resources including a deterministic data communications network, including initiating execution through the PAMI of an ordered sequence of active SEND instructions for SEND data transfers between two endpoints, effecting deterministic SEND data transfers; and executing through the PAMI, with no FENCE accounting for SEND data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all SEND instructions initiated prior to execution of the FENCE instruction for SEND data transfers between the two endpoints.

Efficient parallel implementation of active appearance model fitting algorithm on GPU.

PubMed

Wang, Jinwei; Ma, Xirong; Zhu, Yuanping; Sun, Jizhou

2014-01-01

The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures.

Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU

PubMed Central

Wang, Jinwei; Ma, Xirong; Zhu, Yuanping; Sun, Jizhou

2014-01-01

The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures. PMID:24723812

Trigonometrical sums connected with the chiral Potts model, Verlinde dimension formula, two-dimensional resistor network, and number theory

NASA Astrophysics Data System (ADS)

Chair, Noureddine

2014-02-01

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.

Node-Based Learning of Multiple Gaussian Graphical Models

PubMed Central

Mohan, Karthik; London, Palma; Fazel, Maryam; Witten, Daniela; Lee, Su-In

2014-01-01

We consider the problem of estimating high-dimensional Gaussian graphical models corresponding to a single set of variables under several distinct conditions. This problem is motivated by the task of recovering transcriptional regulatory networks on the basis of gene expression data containing heterogeneous samples, such as different disease states, multiple species, or different developmental stages. We assume that most aspects of the conditional dependence networks are shared, but that there are some structured differences between them. Rather than assuming that similarities and differences between networks are driven by individual edges, we take a node-based approach, which in many cases provides a more intuitive interpretation of the network differences. We consider estimation under two distinct assumptions: (1) differences between the K networks are due to individual nodes that are perturbed across conditions, or (2) similarities among the K networks are due to the presence of common hub nodes that are shared across all K networks. Using a row-column overlap norm penalty function, we formulate two convex optimization problems that correspond to these two assumptions. We solve these problems using an alternating direction method of multipliers algorithm, and we derive a set of necessary and sufficient conditions that allows us to decompose the problem into independent subproblems so that our algorithm can be scaled to high-dimensional settings. Our proposal is illustrated on synthetic data, a webpage data set, and a brain cancer gene expression data set. PMID:25309137

Alternative parallel ring protocols

NASA Technical Reports Server (NTRS)

Mukkamala, R.; Foudriat, E. C.; Maly, Kurt J.; Kale, V.

1990-01-01

Communication protocols are know to influence the utilization and performance of communication network. The effect of two token ring protocols on a gigabit network with multiple ring structure is investigated. In the first protocol, a mode sends at most one message on receiving a token. In the second protocol, a mode sends all the waiting messages when a token is received. The behavior of these protocols is shown to be highly dependent on the number of rings as well as the load in the network.