Analysis of chaos in high-dimensional wind power system.
Wang, Cong; Zhang, Hongli; Fan, Wenhui; Ma, Ping
2018-01-01
A comprehensive analysis on the chaos of a high-dimensional wind power system is performed in this study. A high-dimensional wind power system is more complex than most power systems. An 11-dimensional wind power system proposed by Huang, which has not been analyzed in previous studies, is investigated. When the systems are affected by external disturbances including single parameter and periodic disturbance, or its parameters changed, chaotic dynamics of the wind power system is analyzed and chaotic parameters ranges are obtained. Chaos existence is confirmed by calculation and analysis of all state variables' Lyapunov exponents and the state variable sequence diagram. Theoretical analysis and numerical simulations show that the wind power system chaos will occur when parameter variations and external disturbances change to a certain degree.
High-Dimensional Adaptive Particle Swarm Optimization on Heterogeneous Systems
International Nuclear Information System (INIS)
Wachowiak, M P; Sarlo, B B; Foster, A E Lambe
2014-01-01
Much work has recently been reported in parallel GPU-based particle swarm optimization (PSO). Motivated by the encouraging results of these investigations, while also recognizing the limitations of GPU-based methods for big problems using a large amount of data, this paper explores the efficacy of employing other types of parallel hardware for PSO. Most commodity systems feature a variety of architectures whose high-performance capabilities can be exploited. In this paper, high-dimensional problems and those that employ a large amount of external data are explored within the context of heterogeneous systems. Large problems are decomposed into constituent components, and analyses are undertaken of which components would benefit from multi-core or GPU parallelism. The current study therefore provides another demonstration that ''supercomputing on a budget'' is possible when subtasks of large problems are run on hardware most suited to these tasks. Experimental results show that large speedups can be achieved on high dimensional, data-intensive problems. Cost functions must first be analysed for parallelization opportunities, and assigned hardware based on the particular task
Quantum correlation of high dimensional system in a dephasing environment
Ji, Yinghua; Ke, Qiang; Hu, Juju
2018-05-01
For a high dimensional spin-S system embedded in a dephasing environment, we theoretically analyze the time evolutions of quantum correlation and entanglement via Frobenius norm and negativity. The quantum correlation dynamics can be considered as a function of the decoherence parameters, including the ratio between the system oscillator frequency ω0 and the reservoir cutoff frequency ωc , and the different environment temperature. It is shown that the quantum correlation can not only measure nonclassical correlation of the considered system, but also perform a better robustness against the dissipation. In addition, the decoherence presents the non-Markovian features and the quantum correlation freeze phenomenon. The former is much weaker than that in the sub-Ohmic or Ohmic thermal reservoir environment.
Problems of high temperature superconductivity in three-dimensional systems
Energy Technology Data Exchange (ETDEWEB)
Geilikman, B T
1973-01-01
A review is given of more recent papers on this subject. These papers have dealt mainly with two-dimensional systems. The present paper extends the treatment to three-dimensional systems, under the following headings: systems with collective electrons of one group and localized electrons of another group (compounds of metals with non-metals-dielectrics, organic substances, undoped semiconductors, molecular crystals); experimental investigations of superconducting compounds of metals with organic compounds, dielectrics, semiconductors, and semi-metals; and systems with two or more groups of collective electrons. Mechanics are considered and models are derived. 86 references.
Statistical mechanics of complex neural systems and high dimensional data
International Nuclear Information System (INIS)
Advani, Madhu; Lahiri, Subhaneil; Ganguli, Surya
2013-01-01
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. (paper)
A qualitative numerical study of high dimensional dynamical systems
Albers, David James
Since Poincare, the father of modern mathematical dynamical systems, much effort has been exerted to achieve a qualitative understanding of the physical world via a qualitative understanding of the functions we use to model the physical world. In this thesis, we construct a numerical framework suitable for a qualitative, statistical study of dynamical systems using the space of artificial neural networks. We analyze the dynamics along intervals in parameter space, separating the set of neural networks into roughly four regions: the fixed point to the first bifurcation; the route to chaos; the chaotic region; and a transition region between chaos and finite-state neural networks. The study is primarily with respect to high-dimensional dynamical systems. We make the following general conclusions as the dimension of the dynamical system is increased: the probability of the first bifurcation being of type Neimark-Sacker is greater than ninety-percent; the most probable route to chaos is via a cascade of bifurcations of high-period periodic orbits, quasi-periodic orbits, and 2-tori; there exists an interval of parameter space such that hyperbolicity is violated on a countable, Lebesgue measure 0, "increasingly dense" subset; chaos is much more likely to persist with respect to parameter perturbation in the chaotic region of parameter space as the dimension is increased; moreover, as the number of positive Lyapunov exponents is increased, the likelihood that any significant portion of these positive exponents can be perturbed away decreases with increasing dimension. The maximum Kaplan-Yorke dimension and the maximum number of positive Lyapunov exponents increases linearly with dimension. The probability of a dynamical system being chaotic increases exponentially with dimension. The results with respect to the first bifurcation and the route to chaos comment on previous results of Newhouse, Ruelle, Takens, Broer, Chenciner, and Iooss. Moreover, results regarding the high-dimensional
Counting and classifying attractors in high dimensional dynamical systems.
Bagley, R J; Glass, L
1996-12-07
Randomly connected Boolean networks have been used as mathematical models of neural, genetic, and immune systems. A key quantity of such networks is the number of basins of attraction in the state space. The number of basins of attraction changes as a function of the size of the network, its connectivity and its transition rules. In discrete networks, a simple count of the number of attractors does not reveal the combinatorial structure of the attractors. These points are illustrated in a reexamination of dynamics in a class of random Boolean networks considered previously by Kauffman. We also consider comparisons between dynamics in discrete networks and continuous analogues. A continuous analogue of a discrete network may have a different number of attractors for many different reasons. Some attractors in discrete networks may be associated with unstable dynamics, and several different attractors in a discrete network may be associated with a single attractor in the continuous case. Special problems in determining attractors in continuous systems arise when there is aperiodic dynamics associated with quasiperiodicity of deterministic chaos.
Linear stability theory as an early warning sign for transitions in high dimensional complex systems
International Nuclear Information System (INIS)
Piovani, Duccio; Grujić, Jelena; Jensen, Henrik Jeldtoft
2016-01-01
We analyse in detail a new approach to the monitoring and forecasting of the onset of transitions in high dimensional complex systems by application to the Tangled Nature model of evolutionary ecology and high dimensional replicator systems with a stochastic element. A high dimensional stability matrix is derived in the mean field approximation to the stochastic dynamics. This allows us to determine the stability spectrum about the observed quasi-stable configurations. From overlap of the instantaneous configuration vector of the full stochastic system with the eigenvectors of the unstable directions of the deterministic mean field approximation, we are able to construct a good early-warning indicator of the transitions occurring intermittently. (paper)
Wang, Zhiping; Chen, Jinyu; Yu, Benli
2017-02-20
We investigate the two-dimensional (2D) and three-dimensional (3D) atom localization behaviors via spontaneously generated coherence in a microwave-driven four-level atomic system. Owing to the space-dependent atom-field interaction, it is found that the detecting probability and precision of 2D and 3D atom localization behaviors can be significantly improved via adjusting the system parameters, the phase, amplitude, and initial population distribution. Interestingly, the atom can be localized in volumes that are substantially smaller than a cubic optical wavelength. Our scheme opens a promising way to achieve high-precision and high-efficiency atom localization, which provides some potential applications in high-dimensional atom nanolithography.
Controlling chaos in low and high dimensional systems with periodic parametric perturbations
International Nuclear Information System (INIS)
Mirus, K.A.; Sprott, J.C.
1998-06-01
The effect of applying a periodic perturbation to an accessible parameter of various chaotic systems is examined. Numerical results indicate that perturbation frequencies near the natural frequencies of the unstable periodic orbits of the chaotic systems can result in limit cycles for relatively small perturbations. Such perturbations can also control or significantly reduce the dimension of high-dimensional systems. Initial application to the control of fluctuations in a prototypical magnetic fusion plasma device will be reviewed
Kinoshita, Hidefumi; Nakagawa, Ken; Usui, Yukio; Iwamura, Masatsugu; Ito, Akihiro; Miyajima, Akira; Hoshi, Akio; Arai, Yoichi; Baba, Shiro; Matsuda, Tadashi
2015-08-01
Three-dimensional (3D) imaging systems have been introduced worldwide for surgical instrumentation. A difficulty of laparoscopic surgery involves converting two-dimensional (2D) images into 3D images and depth perception rearrangement. 3D imaging may remove the need for depth perception rearrangement and therefore have clinical benefits. We conducted a multicenter, open-label, randomized trial to compare the surgical outcome of 3D-high-definition (HD) resolution and 2D-HD imaging in laparoscopic radical prostatectomy (LRP), in order to determine whether an LRP under HD resolution 3D imaging is superior to that under HD resolution 2D imaging in perioperative outcome, feasibility, and fatigue. One-hundred twenty-two patients were randomly assigned to a 2D or 3D group. The primary outcome was time to perform vesicourethral anastomosis (VUA), which is technically demanding and may include a number of technical difficulties considered in laparoscopic surgeries. VUA time was not significantly shorter in the 3D group (26.7 min, mean) compared with the 2D group (30.1 min, mean) (p = 0.11, Student's t test). However, experienced surgeons and 3D-HD imaging were independent predictors for shorter VUA times (p = 0.000, p = 0.014, multivariate logistic regression analysis). Total pneumoperitoneum time was not different. No conversion case from 3D to 2D or LRP to open RP was observed. Fatigue was evaluated by a simulation sickness questionnaire and critical flicker frequency. Results were not different between the two groups. Subjective feasibility and satisfaction scores were significantly higher in the 3D group. Using a 3D imaging system in LRP may have only limited advantages in decreasing operation times over 2D imaging systems. However, the 3D system increased surgical feasibility and decreased surgeons' effort levels without inducing significant fatigue.
Clustering high dimensional data
DEFF Research Database (Denmark)
Assent, Ira
2012-01-01
High-dimensional data, i.e., data described by a large number of attributes, pose specific challenges to clustering. The so-called ‘curse of dimensionality’, coined originally to describe the general increase in complexity of various computational problems as dimensionality increases, is known...... to render traditional clustering algorithms ineffective. The curse of dimensionality, among other effects, means that with increasing number of dimensions, a loss of meaningful differentiation between similar and dissimilar objects is observed. As high-dimensional objects appear almost alike, new approaches...... for clustering are required. Consequently, recent research has focused on developing techniques and clustering algorithms specifically for high-dimensional data. Still, open research issues remain. Clustering is a data mining task devoted to the automatic grouping of data based on mutual similarity. Each cluster...
Ghosts in high dimensional non-linear dynamical systems: The example of the hypercycle
International Nuclear Information System (INIS)
Sardanyes, Josep
2009-01-01
Ghost-induced delayed transitions are analyzed in high dimensional non-linear dynamical systems by means of the hypercycle model. The hypercycle is a network of catalytically-coupled self-replicating RNA-like macromolecules, and has been suggested to be involved in the transition from non-living to living matter in the context of earlier prebiotic evolution. It is demonstrated that, in the vicinity of the saddle-node bifurcation for symmetric hypercycles, the persistence time before extinction, T ε , tends to infinity as n→∞ (being n the number of units of the hypercycle), thus suggesting that the increase in the number of hypercycle units involves a longer resilient time before extinction because of the ghost. Furthermore, by means of numerical analysis the dynamics of three large hypercycle networks is also studied, focusing in their extinction dynamics associated to the ghosts. Such networks allow to explore the properties of the ghosts living in high dimensional phase space with n = 5, n = 10 and n = 15 dimensions. These hypercyclic networks, in agreement with other works, are shown to exhibit self-maintained oscillations governed by stable limit cycles. The bifurcation scenarios for these hypercycles are analyzed, as well as the effect of the phase space dimensionality in the delayed transition phenomena and in the scaling properties of the ghosts near bifurcation threshold
A novel algorithm of artificial immune system for high-dimensional function numerical optimization
Institute of Scientific and Technical Information of China (English)
DU Haifeng; GONG Maoguo; JIAO Licheng; LIU Ruochen
2005-01-01
Based on the clonal selection theory and immune memory theory, a novel artificial immune system algorithm, immune memory clonal programming algorithm (IMCPA), is put forward. Using the theorem of Markov chain, it is proved that IMCPA is convergent. Compared with some other evolutionary programming algorithms (like Breeder genetic algorithm), IMCPA is shown to be an evolutionary strategy capable of solving complex machine learning tasks, like high-dimensional function optimization, which maintains the diversity of the population and avoids prematurity to some extent, and has a higher convergence speed.
International Nuclear Information System (INIS)
Santoyo, B.M.
1989-01-01
The author studies in full detail a possible mechanism of superconductivity in slender electronic systems of finite cross section. This mechanism is based on the pairing interaction mediated by the multiple modes of acoustic plasmons in these structures. First, he shows that multiple non-Landau-damped acoustic plasmon modes exist for electrons in a quasi-one dimensional wire at finite temperatures. These plasmons are of two basic types. The first one is made up by the collective longitudinal oscillations of the electrons essentially of a given transverse energy level oscillating against the electrons in the neighboring transverse energy level. The modes are called Slender Acoustic Plasmons or SAP's. The other mode is the quasi-one dimensional acoustic plasmon mode in which all the electrons oscillate together in phase among themselves but out of phase against the positive ion background. He shows numerically and argues physically that even for a temperature comparable to the mode separation Δω the SAP's and the quasi-one dimensional plasmon persist. Then, based on a clear physical picture, he develops in terms of the dielectric function a theory of superconductivity capable of treating the simultaneous participation of multiple bosonic modes that mediate the pairing interaction. The effect of mode damping is then incorporated in a simple manner that is free of the encumbrance of the strong-coupling, Green's function formalism usually required for the retardation effect. Explicit formulae including such damping are derived for the critical temperature T c and the energy gap Δ 0 . With those modes and armed with such a formalism, he proceeds to investigate a possible superconducting mechanism for high T c in quasi-one dimensional single-wire and multi-wire systems
Geraci, Joseph; Dharsee, Moyez; Nuin, Paulo; Haslehurst, Alexandria; Koti, Madhuri; Feilotter, Harriet E; Evans, Ken
2014-03-01
We introduce a novel method for visualizing high dimensional data via a discrete dynamical system. This method provides a 2D representation of the relationship between subjects according to a set of variables without geometric projections, transformed axes or principal components. The algorithm exploits a memory-type mechanism inherent in a certain class of discrete dynamical systems collectively referred to as the chaos game that are closely related to iterative function systems. The goal of the algorithm was to create a human readable representation of high dimensional patient data that was capable of detecting unrevealed subclusters of patients from within anticipated classifications. This provides a mechanism to further pursue a more personalized exploration of pathology when used with medical data. For clustering and classification protocols, the dynamical system portion of the algorithm is designed to come after some feature selection filter and before some model evaluation (e.g. clustering accuracy) protocol. In the version given here, a univariate features selection step is performed (in practice more complex feature selection methods are used), a discrete dynamical system is driven by this reduced set of variables (which results in a set of 2D cluster models), these models are evaluated for their accuracy (according to a user-defined binary classification) and finally a visual representation of the top classification models are returned. Thus, in addition to the visualization component, this methodology can be used for both supervised and unsupervised machine learning as the top performing models are returned in the protocol we describe here. Butterfly, the algorithm we introduce and provide working code for, uses a discrete dynamical system to classify high dimensional data and provide a 2D representation of the relationship between subjects. We report results on three datasets (two in the article; one in the appendix) including a public lung cancer
Energy Technology Data Exchange (ETDEWEB)
Pelliccione, M. [Department of Applied Physics, Stanford University, 348 Via Pueblo Mall, Stanford, California 94305 (United States); Stanford Institute for Materials and Energy Sciences, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025 (United States); Department of Physics, University of California, Santa Barbara, Santa Barbara, California 93106 (United States); Bartel, J.; Goldhaber-Gordon, D. [Stanford Institute for Materials and Energy Sciences, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025 (United States); Department of Physics, Stanford University, 382 Via Pueblo Mall, Stanford, California 94305 (United States); Sciambi, A. [Department of Applied Physics, Stanford University, 348 Via Pueblo Mall, Stanford, California 94305 (United States); Stanford Institute for Materials and Energy Sciences, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025 (United States); Pfeiffer, L. N.; West, K. W. [Department of Electrical Engineering, Princeton University, Princeton, New Jersey 08544 (United States)
2014-11-03
Correlated electron states in high mobility two-dimensional electron systems (2DESs), including charge density waves and microemulsion phases intermediate between a Fermi liquid and Wigner crystal, are predicted to exhibit complex local charge order. Existing experimental studies, however, have mainly probed these systems at micron to millimeter scales rather than directly mapping spatial organization. Scanning probes should be well-suited to study the spatial structure of these states, but high mobility 2DESs are found at buried semiconductor interfaces, beyond the reach of conventional scanning tunneling microscopy. Scanning techniques based on electrostatic coupling to the 2DES deliver important insights, but generally with resolution limited by the depth of the 2DES. In this letter, we present our progress in developing a technique called “virtual scanning tunneling microscopy” that allows local tunneling into a high mobility 2DES. Using a specially designed bilayer GaAs/AlGaAs heterostructure where the tunnel coupling between two separate 2DESs is tunable via electrostatic gating, combined with a scanning gate, we show that the local tunneling can be controlled with sub-250 nm resolution.
CSIR Research Space (South Africa)
Mc
2012-07-01
Full Text Available stream_source_info McLaren_2012.pdf.txt stream_content_type text/plain stream_size 2190 Content-Encoding ISO-8859-1 stream_name McLaren_2012.pdf.txt Content-Type text/plain; charset=ISO-8859-1 High dimensional... entanglement M. McLAREN1,2, F.S. ROUX1 & A. FORBES1,2,3 1. CSIR National Laser Centre, PO Box 395, Pretoria 0001 2. School of Physics, University of the Stellenbosch, Private Bag X1, 7602, Matieland 3. School of Physics, University of Kwazulu...
Ma, Biao; Zou, Yilin; Xie, Xuan; Zhao, Jinhua; Piao, Xiangfan; Piao, Jingyi; Yao, Zhongping; Quinto, Maurizio; Wang, Gang; Li, Donghao
2017-06-09
A novel high-throughput, solvent saving and versatile integrated two-dimensional microscale carbon fiber/active carbon fiber system (2DμCFs) that allows a simply and rapid separation of compounds in low-polar, medium-polar and high-polar fractions, has been coupled with ambient ionization-mass spectrometry (ESI-Q-TOF-MS and ESI-QqQ-MS) for screening and quantitative analyses of real samples. 2DμCFs led to a substantial interference reduction and minimization of ionization suppression effects, thus increasing the sensitivity and the screening capabilities of the subsequent MS analysis. The method has been applied to the analysis of Schisandra Chinensis extracts, obtaining with a single injection a simultaneous determination of 33 compounds presenting different polarities, such as organic acids, lignans, and flavonoids in less than 7min, at low pressures and using small solvent amounts. The method was also validated using 10 model compounds, giving limit of detections (LODs) ranging from 0.3 to 30ngmL -1 , satisfactory recoveries (from 75.8 to 93.2%) and reproducibilities (relative standard deviations, RSDs, from 1.40 to 8.06%). Copyright © 2017 Elsevier B.V. All rights reserved.
High-precision two-dimensional atom localization via quantum interference in a tripod-type system
International Nuclear Information System (INIS)
Wang, Zhiping; Yu, Benli
2014-01-01
A scheme is proposed for high-precision two-dimensional atom localization in a four-level tripod-type atomic system via measurement of the excited state population. It is found that because of the position-dependent atom–field interaction, the precision of 2D atom localization can be significantly improved by appropriately adjusting the system parameters. Our scheme may be helpful in laser cooling or atom nanolithography via high-precision and high-resolution atom localization. (letter)
Wang, Wei; Yang, Jiong
With the rapid growth of computational biology and e-commerce applications, high-dimensional data becomes very common. Thus, mining high-dimensional data is an urgent problem of great practical importance. However, there are some unique challenges for mining data of high dimensions, including (1) the curse of dimensionality and more crucial (2) the meaningfulness of the similarity measure in the high dimension space. In this chapter, we present several state-of-art techniques for analyzing high-dimensional data, e.g., frequent pattern mining, clustering, and classification. We will discuss how these methods deal with the challenges of high dimensionality.
Chernozhukov, Victor; Hansen, Christian; Spindler, Martin
2016-01-01
In this article the package High-dimensional Metrics (\\texttt{hdm}) is introduced. It is a collection of statistical methods for estimation and quantification of uncertainty in high-dimensional approximately sparse models. It focuses on providing confidence intervals and significance testing for (possibly many) low-dimensional subcomponents of the high-dimensional parameter vector. Efficient estimators and uniformly valid confidence intervals for regression coefficients on target variables (e...
Modeling and simulation of high dimensional stochastic multiscale PDE systems at the exascale
Energy Technology Data Exchange (ETDEWEB)
Zabaras, Nicolas J. [Cornell Univ., Ithaca, NY (United States)
2016-11-08
Predictive Modeling of multiscale and Multiphysics systems requires accurate data driven characterization of the input uncertainties, and understanding of how they propagate across scales and alter the final solution. This project develops a rigorous mathematical framework and scalable uncertainty quantification algorithms to efficiently construct realistic low dimensional input models, and surrogate low complexity systems for the analysis, design, and control of physical systems represented by multiscale stochastic PDEs. The work can be applied to many areas including physical and biological processes, from climate modeling to systems biology.
Highly ordered self-assembly of one-dimensional nanoparticles in amphiphilic molecular systems
International Nuclear Information System (INIS)
Kim, Tae Hwan
2009-02-01
Two kinds of one-dimensional (1D) nanoparticles, stable rod-like nanoparticles with highly controlled surface charge density (cROD) and non-covalently functionalized isolated single wall carbon nanotubes (p-SWNT) that were readily redispersible in water, have been developed. Using these 1D nanoparticles, various highly ordered superstructures of 1D nanoparticles by molecular self-assembling based on electrostatic interaction in amphiphilic molecular systems (two different cationic liposome systems) have been investigated. To our knowledge, this is the first demonstration of highly ordered self-assembly of 1D nanoparticles based on electrostatic interaction between 1D nanoparticles and amphiphilic molecules. The cRODs have been developed by free radical polymerization of a mixture of polymerizable cationic surfactant, cetyltrimethylammonium 4-vinylbenzoate (CTVB), and hydrotropic salt sodium 4-styrenesulfonate (NaSS) in aqueous solution. The surface charge of the cROD was controlled by varying the NaSS concentration during the polymerization process and the charge variation was interpreted in terms of the overcharging effect in colloidal systems. The small angle neutron scattering (SANS) measurements showed that the diameter of cROD is constant at 4 nm and the particle length ranges from 20 nm to 85 nm, depending on the NaSS concentration. The cRODs are longest when the NaSS concentration is 5 mol % which corresponds to the charge inversion or neutral point. The SANS and zeta potential measurements showed that the Coulomb interactions between the particles are strongly dependent on the NaSS concentration and the zeta potential of the cRODs changes from positive to negative (+ 12.8 mV ∼ - 44.2 mV) as the concentration of NaSS increases from 0 mol % to 40 mol %. As the NaSS concentration is further increased, the zeta potential is saturated at approximately - 50 mV. The p-SWNTs have been developed by 1) dispersing single wall carbon nanotubes (SWNTs) in water using
Multi-dimensional diagnostics of high power ion beams by Arrayed Pinhole Camera System
International Nuclear Information System (INIS)
Yasuike, K.; Miyamoto, S.; Shirai, N.; Akiba, T.; Nakai, S.; Imasaki, K.; Yamanaka, C.
1993-01-01
The authors developed multi-dimensional beam diagnostics system (with spatially and time resolution). They used newly developed Arrayed Pinhole Camera (APC) for this diagnosis. The APC can get spatial distribution of divergence and flux density. They use two types of particle detectors in this study. The one is CR-39 can get time integrated images. The other one is gated Micro-Channel-Plate (MCP) with CCD camera. It enables time resolving diagnostics. The diagnostics systems have resolution better than 10mrad divergence, 0.5mm spatial resolution on the objects respectively. The time resolving system has 10ns time resolution. The experiments are performed on Reiden-IV and Reiden-SHVS induction linac. The authors get time integrated divergence distributions on Reiden-IV proton beam. They also get time resolved image on Reiden-SHVS
Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks.
Vlachas, Pantelis R; Byeon, Wonmin; Wan, Zhong Y; Sapsis, Themistoklis P; Koumoutsakos, Petros
2018-05-01
We introduce a data-driven forecasting method for high-dimensional chaotic systems using long short-term memory (LSTM) recurrent neural networks. The proposed LSTM neural networks perform inference of high-dimensional dynamical systems in their reduced order space and are shown to be an effective set of nonlinear approximators of their attractor. We demonstrate the forecasting performance of the LSTM and compare it with Gaussian processes (GPs) in time series obtained from the Lorenz 96 system, the Kuramoto-Sivashinsky equation and a prototype climate model. The LSTM networks outperform the GPs in short-term forecasting accuracy in all applications considered. A hybrid architecture, extending the LSTM with a mean stochastic model (MSM-LSTM), is proposed to ensure convergence to the invariant measure. This novel hybrid method is fully data-driven and extends the forecasting capabilities of LSTM networks.
A New Three-Dimensional High-Accuracy Automatic Alignment System For Single-Mode Fibers
Yun-jiang, Rao; Shang-lian, Huang; Ping, Li; Yu-mei, Wen; Jun, Tang
1990-02-01
In order to achieve the low-loss splices of single-mode fibers, a new three-dimension high-accuracy automatic alignment system for single -mode fibers has been developed, which includes a new-type three-dimension high-resolution microdisplacement servo stage driven by piezoelectric elements, a new high-accuracy measurement system for the misalignment error of the fiber core-axis, and a special single chip microcomputer processing system. The experimental results show that alignment accuracy of ±0.1 pin with a movable stroke of -±20μm has been obtained. This new system has more advantages than that reported.
Three dimensional system integration
Papanikolaou, Antonis; Radojcic, Riko
2010-01-01
Three-dimensional (3D) integrated circuit (IC) stacking is the next big step in electronic system integration. It enables packing more functionality, as well as integration of heterogeneous materials, devices, and signals, in the same space (volume). This results in consumer electronics (e.g., mobile, handheld devices) which can run more powerful applications, such as full-length movies and 3D games, with longer battery life. This technology is so promising that it is expected to be a mainstream technology a few years from now, less than 10-15 years from its original conception. To achieve thi
He, Ling Yan; Wang, Tie-Jun; Wang, Chuan
2016-07-11
High-dimensional quantum system provides a higher capacity of quantum channel, which exhibits potential applications in quantum information processing. However, high-dimensional universal quantum logic gates is difficult to achieve directly with only high-dimensional interaction between two quantum systems and requires a large number of two-dimensional gates to build even a small high-dimensional quantum circuits. In this paper, we propose a scheme to implement a general controlled-flip (CF) gate where the high-dimensional single photon serve as the target qudit and stationary qubits work as the control logic qudit, by employing a three-level Λ-type system coupled with a whispering-gallery-mode microresonator. In our scheme, the required number of interaction times between the photon and solid state system reduce greatly compared with the traditional method which decomposes the high-dimensional Hilbert space into 2-dimensional quantum space, and it is on a shorter temporal scale for the experimental realization. Moreover, we discuss the performance and feasibility of our hybrid CF gate, concluding that it can be easily extended to a 2n-dimensional case and it is feasible with current technology.
Garashchuk, Sophya; Rassolov, Vitaly A
2008-07-14
Semiclassical implementation of the quantum trajectory formalism [J. Chem. Phys. 120, 1181 (2004)] is further developed to give a stable long-time description of zero-point energy in anharmonic systems of high dimensionality. The method is based on a numerically cheap linearized quantum force approach; stabilizing terms compensating for the linearization errors are added into the time-evolution equations for the classical and nonclassical components of the momentum operator. The wave function normalization and energy are rigorously conserved. Numerical tests are performed for model systems of up to 40 degrees of freedom.
Energy Technology Data Exchange (ETDEWEB)
Lee, Nam Ho; Lee, Yong Duk; Choi, Chang Whan; Jung, Kyung Min; Moon, Myung Kook; Kim, Hee Moon
2007-02-15
Technologies for managing the emergency leak accident of radioactive materials have been developed actively in USA, Japan, and Russia, since the Chernobyl nuclear disaster in Russia and nuclear fuel accident in Japan Nuclear fuel Conversion cooperation had occurred. A robot (Pioneer) for managing radioactive materials have been developed in co-operation of USA(CMU), Japan, and Russia. The pioneer is recently examined its performance through exploring test in the Chernobyl nuclear reactor. The exploring function of these system is quite different with a dosimeter for a worker in operation, installation, and radiation measurement. So, it is inevitable to develop a new system. The developed system from now is so expensive and slow in operation. So this problem is pending and must be improved. In this research, instead of an existing expensive system, a CCD(or CMOS) sensor, which has high resolution (640 X 480) and high signal process (30 frame/sec), is used for exploring radioactive materials as economical view and image consideration. The connection with image processing, 3D imaging technology, and radioactive exploring can visualize imaginary radiation source and can improve exploring and managing radioactive materials.
Chen, Hao; Guan, Weipeng; Li, Simin; Wu, Yuxiang
2018-04-01
To improve the precision of indoor positioning and actualize three-dimensional positioning, a reversed indoor positioning system based on visible light communication (VLC) using genetic algorithm (GA) is proposed. In order to solve the problem of interference between signal sources, CDMA modulation is used. Each light-emitting diode (LED) in the system broadcasts a unique identity (ID) code using CDMA modulation. Receiver receives mixed signal from every LED reference point, by the orthogonality of spreading code in CDMA modulation, ID information and intensity attenuation information from every LED can be obtained. According to positioning principle of received signal strength (RSS), the coordinate of the receiver can be determined. Due to system noise and imperfection of device utilized in the system, distance between receiver and transmitters will deviate from the real value resulting in positioning error. By introducing error correction factors to global parallel search of genetic algorithm, coordinates of the receiver in three-dimensional space can be determined precisely. Both simulation results and experimental results show that in practical application scenarios, the proposed positioning system can realize high precision positioning service.
A High Performance Banknote Recognition System Based on a One-Dimensional Visible Light Line Sensor.
Park, Young Ho; Kwon, Seung Yong; Pham, Tuyen Danh; Park, Kang Ryoung; Jeong, Dae Sik; Yoon, Sungsoo
2015-06-15
An algorithm for recognizing banknotes is required in many fields, such as banknote-counting machines and automatic teller machines (ATM). Due to the size and cost limitations of banknote-counting machines and ATMs, the banknote image is usually captured by a one-dimensional (line) sensor instead of a conventional two-dimensional (area) sensor. Because the banknote image is captured by the line sensor while it is moved at fast speed through the rollers inside the banknote-counting machine or ATM, misalignment, geometric distortion, and non-uniform illumination of the captured images frequently occur, which degrades the banknote recognition accuracy. To overcome these problems, we propose a new method for recognizing banknotes. The experimental results using two-fold cross-validation for 61,240 United States dollar (USD) images show that the pre-classification error rate is 0%, and the average error rate for the final recognition of the USD banknotes is 0.114%.
Mao, Xianglong; Li, Hongtao; Han, Yanjun; Luo, Yi
2014-10-20
Designing an illumination system for a surface light source with a strict compactness requirement is quite challenging, especially for the general three-dimensional (3D) case. In accordance with the two key features of an expected illumination distribution, i.e., a well-controlled boundary and a precise illumination pattern, a two-step design method is proposed in this paper for highly compact 3D freeform illumination systems. In the first step, a target shape scaling strategy is combined with an iterative feedback modification algorithm to generate an optimized freeform optical system with a well-controlled boundary of the target distribution. In the second step, a set of selected radii of the system obtained in the first step are optimized to further improve the illuminating quality within the target region. The method is quite flexible and effective to design highly compact optical systems with almost no restriction on the shape of the desired target field. As examples, three highly compact freeform lenses with ratio of center height h of the lens and the maximum dimension D of the source ≤ 2.5:1 are designed for LED surface light sources to form a uniform illumination distribution on a rectangular, a cross-shaped and a complex cross pierced target plane respectively. High light control efficiency of η > 0.7 as well as low relative standard illumination deviation of RSD < 0.07 is obtained simultaneously for all the three design examples.
Luegmair, Georg; Mehta, Daryush D.; Kobler, James B.; Döllinger, Michael
2015-01-01
Vocal fold kinematics and its interaction with aerodynamic characteristics play a primary role in acoustic sound production of the human voice. Investigating the temporal details of these kinematics using high-speed videoendoscopic imaging techniques has proven challenging in part due to the limitations of quantifying complex vocal fold vibratory behavior using only two spatial dimensions. Thus, we propose an optical method of reconstructing the superior vocal fold surface in three spatial dimensions using a high-speed video camera and laser projection system. Using stereo-triangulation principles, we extend the camera-laser projector method and present an efficient image processing workflow to generate the three-dimensional vocal fold surfaces during phonation captured at 4000 frames per second. Initial results are provided for airflow-driven vibration of an ex vivo vocal fold model in which at least 75% of visible laser points contributed to the reconstructed surface. The method captures the vertical motion of the vocal folds at a high accuracy to allow for the computation of three-dimensional mucosal wave features such as vibratory amplitude, velocity, and asymmetry. PMID:26087485
A High Performance Banknote Recognition System Based on a One-Dimensional Visible Light Line Sensor
Directory of Open Access Journals (Sweden)
Young Ho Park
2015-06-01
Full Text Available An algorithm for recognizing banknotes is required in many fields, such as banknote-counting machines and automatic teller machines (ATM. Due to the size and cost limitations of banknote-counting machines and ATMs, the banknote image is usually captured by a one-dimensional (line sensor instead of a conventional two-dimensional (area sensor. Because the banknote image is captured by the line sensor while it is moved at fast speed through the rollers inside the banknote-counting machine or ATM, misalignment, geometric distortion, and non-uniform illumination of the captured images frequently occur, which degrades the banknote recognition accuracy. To overcome these problems, we propose a new method for recognizing banknotes. The experimental results using two-fold cross-validation for 61,240 United States dollar (USD images show that the pre-classification error rate is 0%, and the average error rate for the final recognition of the USD banknotes is 0.114%.
Directory of Open Access Journals (Sweden)
F. C. Cooper
2013-04-01
Full Text Available The fluctuation-dissipation theorem (FDT has been proposed as a method of calculating the response of the earth's atmosphere to a forcing. For this problem the high dimensionality of the relevant data sets makes truncation necessary. Here we propose a method of truncation based upon the assumption that the response to a localised forcing is spatially localised, as an alternative to the standard method of choosing a number of the leading empirical orthogonal functions. For systems where this assumption holds, the response to any sufficiently small non-localised forcing may be estimated using a set of truncations that are chosen algorithmically. We test our algorithm using 36 and 72 variable versions of a stochastic Lorenz 95 system of ordinary differential equations. We find that, for long integrations, the bias in the response estimated by the FDT is reduced from ~75% of the true response to ~30%.
Directory of Open Access Journals (Sweden)
Flor-Henry Michel
2004-11-01
Full Text Available Abstract Background All living organisms emit spontaneous low-level bioluminescence, which can be increased in response to stress. Methods for imaging this ultra-weak luminescence have previously been limited by the sensitivity of the detection systems used. Results We developed a novel configuration of a cooled charge-coupled device (CCD for 2-dimensional imaging of light emission from biological material. In this study, we imaged photon emission from plant leaves. The equipment allowed short integration times for image acquisition, providing high resolution spatial and temporal information on bioluminescence. We were able to carry out time course imaging of both delayed chlorophyll fluorescence from whole leaves, and of low level wound-induced luminescence that we showed to be localised to sites of tissue damage. We found that wound-induced luminescence was chlorophyll-dependent and was enhanced at higher temperatures. Conclusions The data gathered on plant bioluminescence illustrate that the equipment described here represents an improvement in 2-dimensional luminescence imaging technology. Using this system, we identify chlorophyll as the origin of wound-induced luminescence from leaves.
High-dimensional covariance estimation with high-dimensional data
Pourahmadi, Mohsen
2013-01-01
Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences. High-Dimensional Covariance Estimation provides accessible and comprehensive coverage of the classical and modern approaches for estimating covariance matrices as well as their applications to the rapidly developing areas lying at the intersection of statistics and mac
Sample-Based Motion Planning in High-Dimensional and Differentially-Constrained Systems
2010-02-01
path planning and motion primitives to enable crawling gaits on rough terrain e.g. [Rebula et al., 2007, Kolter et al., 2008,Pongas et al., 2007,Ratliff...demonstrating robust planning and locomotion over quite challenging terrain (e.g., [Rebula et al., 2007, Kolter et al., 2008, Pongas et al., 2007, Zucker, 2009...and Systems. [ Kolter et al., 2008] Kolter , J. Z., Rodgers, M. P., and Ng, A. Y. (2008). A control architecture for quadruped locomotion over rough
Physics of low-dimensional systems
International Nuclear Information System (INIS)
Anon.
1989-01-01
The physics of low-dimensional systems has developed in a remarkable way over the last decade and has accelerated over the last few years, in particular because of the discovery of the new high temperature superconductors. The new developments started more than fifteen years ago with the discovery of the unexpected quasi-one-dimensional character of the TTF-TCNQ. Since then the field of conducting quasi-one-dimensional organic system have been rapidly growing. Parallel to the experimental work there has been an important theoretical development of great conceptual importance, such as charge density waves, soliton-like excitations, fractional charges, new symmetry properties etc. A new field of fundamental importance was the discovery of the Quantum Hall Effect in 1980. This field is still expanding with new experimental and theoretical discoveries. In 1986, then, came the totally unexpected discovery of high temperature superconductivity which started an explosive development. The three areas just mentioned formed the main themes of the Symposium. They do not in any way exhaust the progress in low-dimensional physics. We should mention the recent important development with both two-dimensional and one-dimensional and even zero-dimensional structures (quantum dots). The physics of mesoscopic systems is another important area where the low dimensionality is a key feature. Because of the small format of this Symposium we could unfortunately not cover these areas
International Nuclear Information System (INIS)
Bainer, R.W.; Adams, M.L.
1993-02-01
Two three-dimensional (3-D), high-resolution seismic reflection pilot studies were conducted in California at two sites, where the primary contaminants of concern are solvents. Identify pathways of contaminant migration. Determine the subsurface stratigraphy and structure to optimize the location for placement of remedial systems. The geology at the first site, located at the Lawrence Livermore National Laboratory in Livermore, California, is characterized by unconsolidated alluvium. Ground water varies in depth from about 30 to 100 ft. The site typically is subjected to extensive cultural noise. The second site, in Southern California, is located in a broad, synclinal depression in the Transverse Range. Shallow alluvium overlies a marine turbidite sequence that crops out as massive sandstone beds. Field work for both surveys took place in August 1992. A Bison Model 90120-A, 120-channel (DIFP) seismograph was used to record the data. Thirty-hertz, natural-frequency geophones were used to receive the data, and an Elastic Wave Generator (EWG) was used as the seismic source. The use of a signal-stacking, noninvasive source was found to be an effective method of overriding background noise at the sites. Prior to the commencement of the 3-D pilot studies, a two-dimensional (2-D) profile was recorded to test the acquisition parameters, which included the geometry of the survey, digital sample rate, and analog filter settings. The data were monitored in the field with a Bison 486 Explorer outdoor computer. The 2-D data were processed and displayed in the field. Both sites displayed coherent seismic reflections from the depths of interest on the field-stacked sections
International Nuclear Information System (INIS)
Lasker, L.
1976-01-01
OSCIL is a program to predict the effects of seismic input on a HTGR core. The present model is a one-dimensional array of blocks with appropriate spring constants, inter-elemental and ground damping, and clearances. It can be used more generally for systems of moving masses separated by nonlinear springs and dampers
Energy Technology Data Exchange (ETDEWEB)
Lasker, L. (ed.)
1976-01-01
OSCIL is a program to predict the effects of seismic input on a HTGR core. The present model is a one-dimensional array of blocks with appropriate spring constants, inter-elemental and ground damping, and clearances. It can be used more generally for systems of moving masses separated by nonlinear springs and dampers.
Cavaglieri, Daniele; Bewley, Thomas
2015-04-01
Implicit/explicit (IMEX) Runge-Kutta (RK) schemes are effective for time-marching ODE systems with both stiff and nonstiff terms on the RHS; such schemes implement an (often A-stable or better) implicit RK scheme for the stiff part of the ODE, which is often linear, and, simultaneously, a (more convenient) explicit RK scheme for the nonstiff part of the ODE, which is often nonlinear. Low-storage RK schemes are especially effective for time-marching high-dimensional ODE discretizations of PDE systems on modern (cache-based) computational hardware, in which memory management is often the most significant computational bottleneck. In this paper, we develop and characterize eight new low-storage implicit/explicit RK schemes which have higher accuracy and better stability properties than the only low-storage implicit/explicit RK scheme available previously, the venerable second-order Crank-Nicolson/Runge-Kutta-Wray (CN/RKW3) algorithm that has dominated the DNS/LES literature for the last 25 years, while requiring similar storage (two, three, or four registers of length N) and comparable floating-point operations per timestep.
Chernozhukov, Victor; Hansen, Chris; Spindler, Martin
2016-01-01
The package High-dimensional Metrics (\\Rpackage{hdm}) is an evolving collection of statistical methods for estimation and quantification of uncertainty in high-dimensional approximately sparse models. It focuses on providing confidence intervals and significance testing for (possibly many) low-dimensional subcomponents of the high-dimensional parameter vector. Efficient estimators and uniformly valid confidence intervals for regression coefficients on target variables (e.g., treatment or poli...
Directory of Open Access Journals (Sweden)
Nikolay Petrovich Vasilyev
2015-03-01
Full Text Available The paper describes the scope of information security protocols based on PRN G in industrial systems. A method for implementing three-dimensional pseudorandom number generator D O Z E N in hybrid systems is provided. The description and results of studies parallel CUDA-version of the algorithm for use in hybrid data centers and high-performance FPGA-version for use in hardware solutions in controlled facilities of SCADA-systems are given.
Zhou, Hong; Malik, Malika Amattullah; Arab, Aarthi; Hill, Matthew Thomas; Shikanov, Ariella
2015-01-01
Various toxicants, drugs and their metabolites carry potential ovarian toxicity. Ovarian follicles, the functional unit of the ovary, are susceptible to this type of damage at all stages of their development. However, despite of the large scale of potential negative impacts, assays that study ovarian toxicity are limited. Exposure of cultured ovarian follicles to toxicants of interest served as an important tool for evaluation of toxic effects for decades. Mouse follicles cultured on the bottom of a culture dish continue to serve an important approach for mechanistic studies. In this paper, we demonstrated the usefulness of a hydrogel based 3-dimensional (3D) mouse ovarian follicle culture as a tool to study ovarian toxicity in a different setup. The 3D in vitro culture, based on fibrin alginate interpenetrating network (FA-IPN), preserves the architecture of the ovarian follicle and physiological structure-function relationship. We applied the novel 3D high-throughput (HTP) in vitro ovarian follicle culture system to study the ovotoxic effects of an anti-cancer drug, Doxorobucin (DXR). The fibrin component in the system is degraded by plasmin and appears as a clear circle around the encapsulated follicle. The degradation area of the follicle is strongly correlated with follicle survival and growth. To analyze fibrin degradation in a high throughput manner, we created a custom MATLAB® code that converts brightfield micrographs of follicles encapsulated in FA-IPN to binary images, followed by image analysis. We did not observe any significant difference between manually processed images to the automated MATLAB® method, thereby confirming that the automated program is suitable to measure fibrin degradation to evaluate follicle health. The cultured follicles were treated with DXR at concentrations ranging from 0.005 nM to 200 nM, corresponding to the therapeutic plasma levels of DXR in patients. Follicles treated with DXR demonstrated decreased survival rate in
Directory of Open Access Journals (Sweden)
Hong Zhou
Full Text Available Various toxicants, drugs and their metabolites carry potential ovarian toxicity. Ovarian follicles, the functional unit of the ovary, are susceptible to this type of damage at all stages of their development. However, despite of the large scale of potential negative impacts, assays that study ovarian toxicity are limited. Exposure of cultured ovarian follicles to toxicants of interest served as an important tool for evaluation of toxic effects for decades. Mouse follicles cultured on the bottom of a culture dish continue to serve an important approach for mechanistic studies. In this paper, we demonstrated the usefulness of a hydrogel based 3-dimensional (3D mouse ovarian follicle culture as a tool to study ovarian toxicity in a different setup. The 3D in vitro culture, based on fibrin alginate interpenetrating network (FA-IPN, preserves the architecture of the ovarian follicle and physiological structure-function relationship. We applied the novel 3D high-throughput (HTP in vitro ovarian follicle culture system to study the ovotoxic effects of an anti-cancer drug, Doxorobucin (DXR. The fibrin component in the system is degraded by plasmin and appears as a clear circle around the encapsulated follicle. The degradation area of the follicle is strongly correlated with follicle survival and growth. To analyze fibrin degradation in a high throughput manner, we created a custom MATLAB® code that converts brightfield micrographs of follicles encapsulated in FA-IPN to binary images, followed by image analysis. We did not observe any significant difference between manually processed images to the automated MATLAB® method, thereby confirming that the automated program is suitable to measure fibrin degradation to evaluate follicle health. The cultured follicles were treated with DXR at concentrations ranging from 0.005 nM to 200 nM, corresponding to the therapeutic plasma levels of DXR in patients. Follicles treated with DXR demonstrated decreased
4+ Dimensional nuclear systems engineering
International Nuclear Information System (INIS)
Suh, Kune Y.
2009-01-01
Nuclear power plants (NPPs) require massive quantity of data during the design, construction, operation, maintenance and decommissioning stages because of their special features like size, cost, radioactivity, and so forth. The system engineering thus calls for a fully integrated way of managing the information flow spanning their life cycle. This paper proposes digital systems engineering anchored in three dimensional (3D) computer aided design (CAD) models. The signature in the proposal lies with the four plus dimensional (4 + D) Technology TM , a critical know how for digital management. ESSE (Engineering Super Simulation Emulation) features a 4 + D Technology TM for nuclear energy systems engineering. The technology proposed in the 3D space and time plus cost coordinates, i.e. 4 + D, is the backbone of digital engineering in the nuclear systems design and management. Dased on an integrated 3D configuration management system, ESSE consists of solutions JANUS (Junctional Analysis Neodynamic Unit SoftPower), EURUS (Engineering Utilities Research Unit SoftPower), NOTUS (Neosystemic Optimization Technical Unit SoftPower), VENUS (Virtual Engineering Neocybernetic Unit SoftPower) and INUUS (Informative Neographic Utilities Unit SoftPower). NOTUS contributes to reducing the construction cost of the NPPs by optimizing the component manufacturing procedure and the plant construction process. Planning and scheduling construction projects can thus benefit greatly by integrating traditional management techniques with digital process simulation visualization. The 3D visualization of construction processes and the resulting products intrinsically afford most of the advantages realized by incorporating a purely schedule level detail based the 4 + D system. Problems with equipment positioning and manpower congestion in certain areas can be visualized prior to the actual operation, thus preventing accidents and safety problems such as collision between two machines and losses in
Highly conducting one-dimensional solids
Evrard, Roger; Doren, Victor
1979-01-01
Although the problem of a metal in one dimension has long been known to solid-state physicists, it was not until the synthesis of real one-dimensional or quasi-one-dimensional systems that this subject began to attract considerable attention. This has been due in part to the search for high temperature superconductivity and the possibility of reaching this goal with quasi-one-dimensional substances. A period of intense activity began in 1973 with the report of a measurement of an apparently divergent conduc tivity peak in TfF-TCNQ. Since then a great deal has been learned about quasi-one-dimensional conductors. The emphasis now has shifted from trying to find materials of very high conductivity to the many interesting problems of physics and chemistry involved. But many questions remain open and are still under active investigation. This book gives a review of the experimental as well as theoretical progress made in this field over the last years. All the chapters have been written by scientists who have ...
Matsumoto, Karin; Ogura, Daisuke; Kuroki, Kazuhiko
2018-01-01
We study superconductivity in the Hubbard model on various quasi-one-dimensional lattices with coexisting wide and narrow bands originating from multiple sites within a unit cell, where each site corresponds to a single orbital. The systems studied are the two-leg and three-leg ladders, the diamond chain, and the crisscross ladder. These one-dimensional lattices are weakly coupled to form two-dimensional (quasi-one-dimensional) ones, and the fluctuation exchange approximation is adopted to study spin-fluctuation-mediated superconductivity. When one of the bands is perfectly flat and the Fermi level intersecting the wide band is placed in the vicinity of, but not within, the flat band, superconductivity arising from the interband scattering processes is found to be strongly enhanced owing to the combination of the light electron mass of the wide band and the strong pairing interaction due to the large density of states of the flat band. Even when the narrow band has finite bandwidth, the pairing mechanism still works since the edge of the narrow band, due to its large density of states, plays the role of the flat band. The results indicate the wide applicability of the high-Tc pairing mechanism due to coexisting wide and "incipient" narrow bands in quasi-one-dimensional systems.
Gwarda, Radosław Łukasz; Dzido, Tadeusz Henryk
2013-10-18
Among many advantages of planar techniques, two-dimensional (2D) separation seems to be the most important for analysis of complex samples. Here we present quick, simple and efficient two-dimensional high-performance thin-layer chromatography (2D HPTLC) of bovine albumin digest using commercial HPTLC RP-18W plates (silica based stationary phase with chemically bonded octadecyl ligands of coverage density 0.5μmol/m(2) from Merck, Darmstadt). We show, that at low or high concentration of water in the mobile phase comprised methanol and some additives the chromatographic systems with the plates mentioned demonstrate normal- or reversed-phase liquid chromatography properties, respectively, for separation of peptides obtained. These two systems show quite different separation selectivity and their combination into 2D HPTLC process provides excellent separation of peptides of the bovine albumin digest. Copyright © 2013 Elsevier B.V. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Dasgupta, Shivaji
2009-02-15
In this work two-dimensional electron systems (2DESs) based on AlAs/AlGaAs heterostructures doped with Si are investigated. The electrons are confined in AlAs quantum wells (QWs) sandwiched between AlGaAs buffers. Analytical calculations and simulations for AlAs QWs are presented in the first chapter. The results show a cross-over width, above which the wide (001)-oriented QWs show double valley occupancy and wide (110)-oriented QWs show single valley occupancy. We solve the Schroedinger equation analytically for anisotropic masses. The solution shows the orientation dependence of the elliptical cyclotron orbit due to the anisotropic mass. We also present an introduction to the Landau level crossings based on g{sup *}m{sup *} product. In the next chapter, we present experimental results for the double-valley (001)-oriented AlAs QWs. We present the different structures of the deep AlAs QWs along with the low temperature magnetotransport data for these QWs. Thereafter, we present the results on shallow AlAs QWs. We achieved a mobility of 4.2 x 10{sup 5} cm{sup 2}/Vs at 330 mK for the deep backside doped AlAs QW. For the shallow QWs, we achieved a mobility of2.3 x 10{sup 5} cm{sup 2}/Vs at 330 mK, for a density of 2.9 x 10{sup 11} cm{sup -2}. From the magneto-transport data, we see evidence of the double-valley occupation for the (001)-oriented AlAs wide QWs. In the next chapter, we present experimental results for the single-valley (110)-oriented AlAs QWs. We deduced the donor binding energy and the doping efficiency for this facet from a doping series of double-sided doped QWs. Thereafter, we designed different structures for the (110)-oriented AlAs QWs, which we present along with their respective low temperature magneto-transport data. We measured one of the double-sided doped AlAs QWs at very high magnetic fields and low temperatures, down to 60 mK. At the end of the chapter, we present a spike feature observed in the magneto-transport data of these QWs. This
International Nuclear Information System (INIS)
Li Peinan; Zhu Hehua; Li Xiaojun; Wang Ju; Zhong Xia
2010-01-01
The 3D geosciences information system of high-level radioactive waste geological disposal is an important research direction in the current high-level radioactive waste disposal project and a platform of information integration and publishing can be used for the relevant research direction based on the provided data and models interface. Firstly, this paper introduces the basic features about the disposal project of HLW and the function and requirement of the system, which includes the input module, the database management module, the function module, the maintenance module and the output module. Then, the framework system of the high-level waste disposal project information system has been studied, and the overall system architecture has been proposed. Finally, based on the summary and analysis of the database management, the 3D modeling, spatial analysis, digital numerical integration and visualization of underground project, the implementations of key functional modules and the platform have been expounded completely, and the conclusion has been drawn that the component-based software development method should be utilized in system development. (authors)
Modeling High-Dimensional Multichannel Brain Signals
Hu, Lechuan; Fortin, Norbert J.; Ombao, Hernando
2017-01-01
aspects: first, there are major statistical and computational challenges for modeling and analyzing high-dimensional multichannel brain signals; second, there is no set of universally agreed measures for characterizing connectivity. To model multichannel
High dimensional neurocomputing growth, appraisal and applications
Tripathi, Bipin Kumar
2015-01-01
The book presents a coherent understanding of computational intelligence from the perspective of what is known as "intelligent computing" with high-dimensional parameters. It critically discusses the central issue of high-dimensional neurocomputing, such as quantitative representation of signals, extending the dimensionality of neuron, supervised and unsupervised learning and design of higher order neurons. The strong point of the book is its clarity and ability of the underlying theory to unify our understanding of high-dimensional computing where conventional methods fail. The plenty of application oriented problems are presented for evaluating, monitoring and maintaining the stability of adaptive learning machine. Author has taken care to cover the breadth and depth of the subject, both in the qualitative as well as quantitative way. The book is intended to enlighten the scientific community, ranging from advanced undergraduates to engineers, scientists and seasoned researchers in computational intelligenc...
Ikeda, Kazuhiro; Nagata, Shogo; Okitsu, Teru; Takeuchi, Shoji
2017-06-06
Human pluripotent stem cells are a potentially powerful cellular resource for application in regenerative medicine. Because such applications require large numbers of human pluripotent stem cell-derived cells, a scalable culture system of human pluripotent stem cell needs to be developed. Several suspension culture systems for human pluripotent stem cell expansion exist; however, it is difficult to control the thickness of cell aggregations in these systems, leading to increased cell death likely caused by limited diffusion of gases and nutrients into the aggregations. Here, we describe a scalable culture system using the cell fiber technology for the expansion of human induced pluripotent stem (iPS) cells. The cells were encapsulated and cultured within the core region of core-shell hydrogel microfibers, resulting in the formation of rod-shaped or fiber-shaped cell aggregations with sustained thickness and high viability. By encapsulating the cells with type I collagen, we demonstrated a long-term culture of the cells by serial passaging at a high expansion rate (14-fold in four days) while retaining its pluripotency. Therefore, our culture system could be used for large-scale expansion of human pluripotent stem cells for use in regenerative medicine.
International Nuclear Information System (INIS)
Wolf, B.; Bruehl, A.; Magerkurth, J.; Zherlitsyn, S.; Pashchenko, V.; Brendel, B.; Margraf, G.; Lerner, H.-W.; Wagner, M.; Luethi, B.; Lang, M.
2005-01-01
We report measurements of magnetic, magnetothermal and magnetoelastic properties of a new Cu(II)-coordination polymer Cu(II)-2,5-bis(pyrazol-1-yl)-1,4-dihydroxybenzene (CuCCP). According to our results which cover wide ranges of temperatures 0.06K= B =21.5K, it was possible to study the system in its interesting high-field range, i.e., across the saturation field gμ B B s =2|J|, which, at T=0, marks the endpoint of a quantum critical line. Using pulse-field techniques the high-field magnetization and elastic constant have been measured. A comparison with calculated magnetization curves reveals a distinct magnetocaloric effect at high fields for T B , a pronounced acoustic anomaly has been found close to B s and identified as a generic property of the uniform antiferromagnetic Heisenberg chain with a finite spin-lattice interaction
Energy Technology Data Exchange (ETDEWEB)
Griesbeck, Michael
2012-11-22
Since many years there has been great effort to explore the spin dynamics in low-dimensional electron systems embedded in GaAs/AlGaAs based heterostructures for the purpose of quantum computation and spintronics applications. Advances in technology allow for the design of high quality and well-defined two-dimensional electron systems (2DES), which are perfectly suited for the study of the underlying physics that govern the dynamics of the electron spin system. In this work, spin dynamics in high-mobility 2DES is studied by means of the all-optical time-resolved Kerr/Faraday rotation technique. In (001)-grown 2DES, a strong in-plane spin dephasing anisotropy is studied, resulting from the interference of comparable Rashba and Dresselhaus contributions to the spin-orbit field (SOF). The dependence of this anisotropy on parameters like the confinement length of the 2DES, the sample temperature, as well as the electron density is demonstrated. Furthermore, coherent spin dynamics of an ensemble of ballistically moving electrons is studied without and within an applied weak magnetic field perpendicular to the sample plane, which forces the electrons to move on cyclotron orbits. Finally, strongly anisotropic spin dynamics is investigated in symmetric (110)-grown 2DES, using the resonant spin amplification method. Here, extremely long out-of-plane spin dephasing times can be achieved, in consequence of the special symmetry of the Dresselhaus SOF.
Study of the weak localization in high quality two dimensional p-GaAs/AIGaAs systems
International Nuclear Information System (INIS)
Yasin, C.E.; Simmons, M.Y.; Hamilton, A.R.; Pepper, M.; Ritchie, D.A.
2002-01-01
Full text: Despite numerous experimental and theoretical work over the past ∼ 30 years, the nature of the ground state in 2D semiconductor systems remains a subject of controversy. Does the anomalous 'metallic' behavior observed at B = 0 imply the existence of a new 2D 'metallic' ground state or can it be explained within the conventional Fermi liquid theory? To address this question, we have investigated the single particle phase coherent 'weak localization' effect in high quality 2D p-GaAs systems that shows an apparent ' metallic' behavior at B = 0. We have performed detailed temperature dependent magnetoresistance measurements at different carrier densities and fit the experimental data to various models of weak localization in order to extract the phase coherence time, τ φ . We find that as the sample quality increases the mean free path increases, and weak localization must be treated beyond the diffusion approximation, making the data analysis more complex. Our result shows that when these more complex models are applied to the experimental data the systems are well described by Fermi liquid theory despite the strong interactions (r s ∼ 20), indicating that there is no 'metallic' phase in 2D at B = 0
Diaz-Ruelas, Alvaro; Jeldtoft Jensen, Henrik; Piovani, Duccio; Robledo, Alberto
2016-12-01
It is well known that low-dimensional nonlinear deterministic maps close to a tangent bifurcation exhibit intermittency and this circumstance has been exploited, e.g., by Procaccia and Schuster [Phys. Rev. A 28, 1210 (1983)], to develop a general theory of 1/f spectra. This suggests it is interesting to study the extent to which the behavior of a high-dimensional stochastic system can be described by such tangent maps. The Tangled Nature (TaNa) Model of evolutionary ecology is an ideal candidate for such a study, a significant model as it is capable of reproducing a broad range of the phenomenology of macroevolution and ecosystems. The TaNa model exhibits strong intermittency reminiscent of punctuated equilibrium and, like the fossil record of mass extinction, the intermittency in the model is found to be non-stationary, a feature typical of many complex systems. We derive a mean-field version for the evolution of the likelihood function controlling the reproduction of species and find a local map close to tangency. This mean-field map, by our own local approximation, is able to describe qualitatively only one episode of the intermittent dynamics of the full TaNa model. To complement this result, we construct a complete nonlinear dynamical system model consisting of successive tangent bifurcations that generates time evolution patterns resembling those of the full TaNa model in macroscopic scales. The switch from one tangent bifurcation to the next in the sequences produced in this model is stochastic in nature, based on criteria obtained from the local mean-field approximation, and capable of imitating the changing set of types of species and total population in the TaNa model. The model combines full deterministic dynamics with instantaneous parameter random jumps at stochastically drawn times. In spite of the limitations of our approach, which entails a drastic collapse of degrees of freedom, the description of a high-dimensional model system in terms of a low-dimensional
Asymptotically Honest Confidence Regions for High Dimensional
DEFF Research Database (Denmark)
Caner, Mehmet; Kock, Anders Bredahl
While variable selection and oracle inequalities for the estimation and prediction error have received considerable attention in the literature on high-dimensional models, very little work has been done in the area of testing and construction of confidence bands in high-dimensional models. However...... develop an oracle inequality for the conservative Lasso only assuming the existence of a certain number of moments. This is done by means of the Marcinkiewicz-Zygmund inequality which in our context provides sharper bounds than Nemirovski's inequality. As opposed to van de Geer et al. (2014) we allow...
A Shell Multi-dimensional Hierarchical Cubing Approach for High-Dimensional Cube
Zou, Shuzhi; Zhao, Li; Hu, Kongfa
The pre-computation of data cubes is critical for improving the response time of OLAP systems and accelerating data mining tasks in large data warehouses. However, as the sizes of data warehouses grow, the time it takes to perform this pre-computation becomes a significant performance bottleneck. In a high dimensional data warehouse, it might not be practical to build all these cuboids and their indices. In this paper, we propose a shell multi-dimensional hierarchical cubing algorithm, based on an extension of the previous minimal cubing approach. This method partitions the high dimensional data cube into low multi-dimensional hierarchical cube. Experimental results show that the proposed method is significantly more efficient than other existing cubing methods.
Factorizations of one-dimensional classical systems
International Nuclear Information System (INIS)
Kuru, Senguel; Negro, Javier
2008-01-01
A class of one-dimensional classical systems is characterized from an algebraic point of view. The Hamiltonians of these systems are factorized in terms of two functions that together with the Hamiltonian itself close a Poisson algebra. These two functions lead directly to two time-dependent integrals of motion from which the phase motions are derived algebraically. The systems so obtained constitute the classical analogues of the well known factorizable one-dimensional quantum mechanical systems
Clustering high dimensional data using RIA
Energy Technology Data Exchange (ETDEWEB)
Aziz, Nazrina [School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, 06010 Sintok, Kedah (Malaysia)
2015-05-15
Clustering may simply represent a convenient method for organizing a large data set so that it can easily be understood and information can efficiently be retrieved. However, identifying cluster in high dimensionality data sets is a difficult task because of the curse of dimensionality. Another challenge in clustering is some traditional functions cannot capture the pattern dissimilarity among objects. In this article, we used an alternative dissimilarity measurement called Robust Influence Angle (RIA) in the partitioning method. RIA is developed using eigenstructure of the covariance matrix and robust principal component score. We notice that, it can obtain cluster easily and hence avoid the curse of dimensionality. It is also manage to cluster large data sets with mixed numeric and categorical value.
Lyapunov exponents for infinite dimensional dynamical systems
Mhuiris, Nessan Mac Giolla
1987-01-01
Classically it was held that solutions to deterministic partial differential equations (i.e., ones with smooth coefficients and boundary data) could become random only through one mechanism, namely by the activation of more and more of the infinite number of degrees of freedom that are available to such a system. It is only recently that researchers have come to suspect that many infinite dimensional nonlinear systems may in fact possess finite dimensional chaotic attractors. Lyapunov exponents provide a tool for probing the nature of these attractors. This paper examines how these exponents might be measured for infinite dimensional systems.
Study on three dimensional seismic isolation system
International Nuclear Information System (INIS)
Morishita, Masaki; Kitamura, Seiji
2003-01-01
Japan Nuclear Cycle Development Institute (JNC) and Japan Atomic Power Company (JAPC) launched joint research programs on structural design and three-dimensional seismic isolation technologies, as part of the supporting R and D activities for the feasibility studies on commercialized fast breeder reactor cycle systems. A research project by JAPC under the auspices of the Ministry of Economy, Trade, and Industry (METI) with technical support by JNC is included in this joint study. This report contains the results of the research on the three-dimensional seismic isolation technologies, and the results of this year's study are summarized in the following five aspects. (1) Study on Earthquake Condition for Developing 3-dimensional Base Isolation System. The case study S2 is one of the maximum ground motions, of which the records were investigated up to this time. But a few observed near the fault exceed the case study S2 in the long period domain, depending on the fault length and conditions. Generally it is appropriate that the response spectra ratio (vertical/horizontal) is 0.6. (2) Performance Requirement for 3-dimensional Base Isolation System and Devices. Although the integrity map of main equipment/piping dominate the design criteria for the 3-dimensional base isolation system, the combined integrity map is the same as those of FY 2000, which are under fv=1Hz and over hv=20%. (3) Developing Targets and Schedule for 3-dimensional Isolation Technology. The target items for 3-dimensional base isolation system were rearranged into a table, and developing items to be examined concerning the device were also adjusted. A development plan until FY 2009 was made from the viewpoint of realization and establishment of a design guideline on 3-dimensional base isolation system. (4) Study on 3-dimensional Entire Building Base Isolation System. Three ideas among six ideas that had been proposed in FY2001, i.e., '3-dimensional base isolation system incorporating hydraulic
Quantum Phenomena in Low-Dimensional Systems
Geller, Michael R.
2001-01-01
A brief summary of the physics of low-dimensional quantum systems is given. The material should be accessible to advanced physics undergraduate students. References to recent review articles and books are provided when possible.
Phase transitions in two-dimensional systems
International Nuclear Information System (INIS)
Salinas, S.R.A.
1983-01-01
Some experiences are related using synchrotron radiation beams, to characterize solid-liquid (fusion) and commensurate solid-uncommensurate solid transitions in two-dimensional systems. Some ideas involved in the modern theories of two-dimensional fusion are shortly exposed. The systems treated consist of noble gases (Kr,Ar,Xe) adsorbed in the basal plane of graphite and thin films formed by some liquid crystal shells. (L.C.) [pt
High-dimensional quantum cloning and applications to quantum hacking.
Bouchard, Frédéric; Fickler, Robert; Boyd, Robert W; Karimi, Ebrahim
2017-02-01
Attempts at cloning a quantum system result in the introduction of imperfections in the state of the copies. This is a consequence of the no-cloning theorem, which is a fundamental law of quantum physics and the backbone of security for quantum communications. Although perfect copies are prohibited, a quantum state may be copied with maximal accuracy via various optimal cloning schemes. Optimal quantum cloning, which lies at the border of the physical limit imposed by the no-signaling theorem and the Heisenberg uncertainty principle, has been experimentally realized for low-dimensional photonic states. However, an increase in the dimensionality of quantum systems is greatly beneficial to quantum computation and communication protocols. Nonetheless, no experimental demonstration of optimal cloning machines has hitherto been shown for high-dimensional quantum systems. We perform optimal cloning of high-dimensional photonic states by means of the symmetrization method. We show the universality of our technique by conducting cloning of numerous arbitrary input states and fully characterize our cloning machine by performing quantum state tomography on cloned photons. In addition, a cloning attack on a Bennett and Brassard (BB84) quantum key distribution protocol is experimentally demonstrated to reveal the robustness of high-dimensional states in quantum cryptography.
Akimitsu, Moe; Qinghong, Cao; Sawada, Asuka; Hatano, Hironori; Tanabe, Hiroshi; Ono, Yasushi; TS-Group Team
2017-10-01
We have developed a new-types of high-resolution magnetic probe array for our new magnetic reconnection experiments: TS-3U (ST, FRC: R =0.2m, 2017-) and TS-4U (ST, FRC: R =0.5m, 2018-), using the advanced printed-circuit technology. They are equipped with all three-components of magnetic pick-up coils whose size is 1-5mm x 3mm. Each coil is composed of two-sided coil pattern with line width of 0.05mm. We can install two or three printed arrays in a single glass (ceramic) tube for two or three component measurements. Based on this new probe technique, we started high-resolution and high-accuracy measurement of the current sheet thickness and studied its plasma parameter dependence. We found that the thickness of current sheet increases inversely with the guide toroidal field. It is probably determined by the ion gyroradius in agreement with the particle simulation by Horiuchi etc. While the reconnection speed is steady under low guide field condition, it is observed to oscillate in the specific range of guide field, suggesting transition from the quasi-steady reconnection to the intermittent reconnection. Cause and mechanism for intermittent reconnection will be discussed using the current sheet dissipation and dynamic balance between plasma inflow and outflow. This work supported by JSPS KAKENHI Grant Numbers 15H05750, 15K14279 and 17H04863.
International Nuclear Information System (INIS)
Kinoshita, Rumiko; Shimizu, Shinichi; Taguchi, Hiroshi; Katoh, Norio; Fujino, Masaharu; Onimaru, Rikiya; Aoyama, Hidefumi; Katoh, Fumi; Omatsu, Tokuhiko; Ishikawa, Masayori; Shirato, Hiroki
2008-01-01
Purpose: To evaluate the three-dimensional intrafraction motion of the breast during tangential breast irradiation using a real-time tracking radiotherapy (RT) system with a high-sampling frequency. Methods and Materials: A total of 17 patients with breast cancer who had received breast conservation RT were included in this study. A 2.0-mm gold marker was placed on the skin near the nipple of the breast for RT. A fluoroscopic real-time tumor-tracking RT system was used to monitor the marker. The range of motion of each patient was calculated in three directions. Results: The mean ± standard deviation of the range of respiratory motion was 1.0 ± 0.6 mm (median, 0.9; 95% confidence interval [CI] of the marker position, 0.4-2.6), 1.3 ± 0.5 mm (median, 1.1; 95% CI, 0.5-2.5), and 2.6 ± 1.4 (median, 2.3; 95% CI, 1.0-6.9) for the right-left, craniocaudal, and anteroposterior direction, respectively. No correlation was found between the range of motion and the body mass index or respiratory function. The mean ± standard deviation of the absolute value of the baseline shift in the right-left, craniocaudal, and anteroposterior direction was 0.2 ± 0.2 mm (range, 0.0-0.8 mm), 0.3 ± 0.2 mm (range, 0.0-0.7 mm), and 0.8 ± 0.7 mm (range, 0.1-1.8 mm), respectively. Conclusion: Both the range of motion and the baseline shift were within a few millimeters in each direction. As long as the conventional wedge-pair technique and the proper immobilization are used, the intrafraction three-dimensional change in the breast surface did not much influence the dose distribution
Sheng, Yanghao; Zhou, Boting
2017-05-26
Therapeutic drug monitoring (TDM) is one of the most important services of clinical laboratories. Two main techniques are commonly used: the immunoassay and chromatography method. We have developed a cost-effective system of two-dimensional liquid chromatography with ultraviolet detection (2D-LC-UV) for high-throughput determination of vancomycin in human plasma that combines the automation and low start-up costs of the immunoassay with the high selectivity and sensitivity of the liquid chromatography coupled with mass spectrometric detection without incurring their disadvantages, achieving high cost-effectiveness. This 2D-LC system offers a large volume injection to provide sufficient sensitivity and uses simulated gradient peak compression technology to control peak broadening and to improve peak shape. A middle column was added to reduce the analysis cycle time and make it suitable for high-throughput routine clinical assays. The analysis cycle time was 4min and the peak width was 0.8min. Compared with other chromatographic methods that have been developed, the analysis cycle time and peak width for vancomycin was reduced significantly. The lower limit of quantification was 0.20μg/mL for vancomycin, which is the same as certain LC-MS/MS methods that have been recently developed and validated. The method is rapid, automated, and low-cost and has high selectivity and sensitivity for the quantification of vancomycin in human plasma, thus making it well-suited for use in hospital clinical laboratories. Copyright © 2017 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Defeng Wu
2016-08-01
Full Text Available A robot-based three-dimensional (3D measurement system is presented. In the presented system, a structured light vision sensor is mounted on the arm of an industrial robot. Measurement accuracy is one of the most important aspects of any 3D measurement system. To improve the measuring accuracy of the structured light vision sensor, a novel sensor calibration approach is proposed to improve the calibration accuracy. The approach is based on a number of fixed concentric circles manufactured in a calibration target. The concentric circle is employed to determine the real projected centres of the circles. Then, a calibration point generation procedure is used with the help of the calibrated robot. When enough calibration points are ready, the radial alignment constraint (RAC method is adopted to calibrate the camera model. A multilayer perceptron neural network (MLPNN is then employed to identify the calibration residuals after the application of the RAC method. Therefore, the hybrid pinhole model and the MLPNN are used to represent the real camera model. Using a standard ball to validate the effectiveness of the presented technique, the experimental results demonstrate that the proposed novel calibration approach can achieve a highly accurate model of the structured light vision sensor.
Energy Technology Data Exchange (ETDEWEB)
Muthukumaran, M [Apollo Speciality Hospitals, Chennai, Tamil Nadu (India); Manigandan, D [Fortis Cancer Institute, Mohali, Punjab (India); Murali, V; Chitra, S; Ganapathy, K [Apollo Speciality Hospital, Chennai, Tamil Nadu (India); Vikraman, S [Jaypee Hospital – Radiation Onology, Noida, UTTAR PRADESH (India)
2016-06-15
Purpose: The aim of the study is to characterize a two dimensional liquid filled detector array SRS 1000 for routine QA in Cyberknife Robotic Radiosurgery system. Methods: SRS 1000 consists of 977 liquid filled ionization chambers and is designed to be used in small field SRS/SBRT techniques. The detector array has got two different spacial resolutions. Till field size of 5.5×5.5 cm the spacial resolution is 2.5mm (center to center) and after that till field size of 11 × 11 cm the spacial resolution is 5mm. The size of the detector is 2.3 × 2.3 0.5 mm with a volume of .003 cc. The CyberKnife Robotic Radiosurgery System is a frameless stereotactic radiosurgery system in which a LINAC is mounted on a robotic manipulator to deliver beams with a high sub millimeter accuracy. The SRS 1000’s MU linearity, stability, reproducibility in Cyberknife Robotic Radiosurgery system was measured and investigated. The output factors for fixed and IRIS collimators for all available collimators (5mm till 60 mm) was measured and compared with the measurement done with PTW pin-point ionization chamber. Results: The MU linearity was measured from 2 MU till 1000 MU for doserates in the range of 700cGy/min – 780 cGy/min and compared with the measurement done with pin point chamber The MU linearity was with in 3%. The detector arrays stability and reproducibility was excellent and was withinin 0.5% The measured output factors showed an agreement of better than 2% when compared with the measurements with pinpoint chamber for both fixed and IRIS collimators with all available field sizes. Conclusion: We have characterised PTW 1000 SRS as a precise and accurate measurement tool for routine QA of Cyberknife Robotic radiosurgery system.
International Nuclear Information System (INIS)
Muthukumaran, M; Manigandan, D; Murali, V; Chitra, S; Ganapathy, K; Vikraman, S
2016-01-01
Purpose: The aim of the study is to characterize a two dimensional liquid filled detector array SRS 1000 for routine QA in Cyberknife Robotic Radiosurgery system. Methods: SRS 1000 consists of 977 liquid filled ionization chambers and is designed to be used in small field SRS/SBRT techniques. The detector array has got two different spacial resolutions. Till field size of 5.5×5.5 cm the spacial resolution is 2.5mm (center to center) and after that till field size of 11 × 11 cm the spacial resolution is 5mm. The size of the detector is 2.3 × 2.3 0.5 mm with a volume of .003 cc. The CyberKnife Robotic Radiosurgery System is a frameless stereotactic radiosurgery system in which a LINAC is mounted on a robotic manipulator to deliver beams with a high sub millimeter accuracy. The SRS 1000’s MU linearity, stability, reproducibility in Cyberknife Robotic Radiosurgery system was measured and investigated. The output factors for fixed and IRIS collimators for all available collimators (5mm till 60 mm) was measured and compared with the measurement done with PTW pin-point ionization chamber. Results: The MU linearity was measured from 2 MU till 1000 MU for doserates in the range of 700cGy/min – 780 cGy/min and compared with the measurement done with pin point chamber The MU linearity was with in 3%. The detector arrays stability and reproducibility was excellent and was withinin 0.5% The measured output factors showed an agreement of better than 2% when compared with the measurements with pinpoint chamber for both fixed and IRIS collimators with all available field sizes. Conclusion: We have characterised PTW 1000 SRS as a precise and accurate measurement tool for routine QA of Cyberknife Robotic radiosurgery system.
Energy Technology Data Exchange (ETDEWEB)
Ramanayaka, A.N.; Ye, Tianyu; Liu, H.-C. [Department of Physics and Astronomy, Georgia State University, Atlanta, GA 30303 (United States); Wegscheider, W. [Laboratorium fuer Festkoerperphysik, ETH Zurich, 8093 Zurich (Switzerland); Mani, R.G., E-mail: rmani@gsu.edu [Department of Physics and Astronomy, Georgia State University, Atlanta, GA 30303 (United States)
2014-11-15
The influence of microwave excitation on the magnetotransport properties of the high mobility two-dimensional electron system (2DES) in the GaAs/AlGaAs heterostructure system is investigated by exploring (a) the dependence of the amplitude of the microwave-induced magnetoresistance-oscillations on the polarization direction of the linearly polarized microwaves and (b) the microwave reflection from the 2DES. The polarization study indicates that the amplitude of the magnetoresistance oscillations is remarkably responsive to the relative orientation between the linearly polarized microwaves and the current-axis in the specimen. At low microwave power, P, experiments indicate a strong sinusoidal variation in the diagonal resistance R{sub xx} vs. θ at the oscillatory extrema of the microwave-induced magnetoresistance oscillations. The reflection study indicates strong correlations between the microwave induced magnetoresistance oscillations and oscillatory features in the microwave reflection in a concurrent measurement of the magnetoresistance and the microwave magnetoreflection from the 2DES. The correlations are followed as a function of the microwave frequency and the microwave power, and the results are reported.
International Nuclear Information System (INIS)
Ramanayaka, A.N.; Ye, Tianyu; Liu, H.-C.; Wegscheider, W.; Mani, R.G.
2014-01-01
The influence of microwave excitation on the magnetotransport properties of the high mobility two-dimensional electron system (2DES) in the GaAs/AlGaAs heterostructure system is investigated by exploring (a) the dependence of the amplitude of the microwave-induced magnetoresistance-oscillations on the polarization direction of the linearly polarized microwaves and (b) the microwave reflection from the 2DES. The polarization study indicates that the amplitude of the magnetoresistance oscillations is remarkably responsive to the relative orientation between the linearly polarized microwaves and the current-axis in the specimen. At low microwave power, P, experiments indicate a strong sinusoidal variation in the diagonal resistance R xx vs. θ at the oscillatory extrema of the microwave-induced magnetoresistance oscillations. The reflection study indicates strong correlations between the microwave induced magnetoresistance oscillations and oscillatory features in the microwave reflection in a concurrent measurement of the magnetoresistance and the microwave magnetoreflection from the 2DES. The correlations are followed as a function of the microwave frequency and the microwave power, and the results are reported
Introduction to high-dimensional statistics
Giraud, Christophe
2015-01-01
Ever-greater computing technologies have given rise to an exponentially growing volume of data. Today massive data sets (with potentially thousands of variables) play an important role in almost every branch of modern human activity, including networks, finance, and genetics. However, analyzing such data has presented a challenge for statisticians and data analysts and has required the development of new statistical methods capable of separating the signal from the noise.Introduction to High-Dimensional Statistics is a concise guide to state-of-the-art models, techniques, and approaches for ha
Estimating High-Dimensional Time Series Models
DEFF Research Database (Denmark)
Medeiros, Marcelo C.; Mendes, Eduardo F.
We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time-series models. We assume both the number of covariates in the model and candidate variables can increase with the number of observations and the number of candidate variables is, possibly......, larger than the number of observations. We show the adaLASSO consistently chooses the relevant variables as the number of observations increases (model selection consistency), and has the oracle property, even when the errors are non-Gaussian and conditionally heteroskedastic. A simulation study shows...
High dimensional classifiers in the imbalanced case
DEFF Research Database (Denmark)
Bak, Britta Anker; Jensen, Jens Ledet
We consider the binary classification problem in the imbalanced case where the number of samples from the two groups differ. The classification problem is considered in the high dimensional case where the number of variables is much larger than the number of samples, and where the imbalance leads...... to a bias in the classification. A theoretical analysis of the independence classifier reveals the origin of the bias and based on this we suggest two new classifiers that can handle any imbalance ratio. The analytical results are supplemented by a simulation study, where the suggested classifiers in some...
Topology of high-dimensional manifolds
Energy Technology Data Exchange (ETDEWEB)
Farrell, F T [State University of New York, Binghamton (United States); Goettshe, L [Abdus Salam ICTP, Trieste (Italy); Lueck, W [Westfaelische Wilhelms-Universitaet Muenster, Muenster (Germany)
2002-08-15
The School on High-Dimensional Manifold Topology took place at the Abdus Salam ICTP, Trieste from 21 May 2001 to 8 June 2001. The focus of the school was on the classification of manifolds and related aspects of K-theory, geometry, and operator theory. The topics covered included: surgery theory, algebraic K- and L-theory, controlled topology, homology manifolds, exotic aspherical manifolds, homeomorphism and diffeomorphism groups, and scalar curvature. The school consisted of 2 weeks of lecture courses and one week of conference. Thwo-part lecture notes volume contains the notes of most of the lecture courses.
Howes, Amy L; Richardson, Robyn D; Finlay, Darren; Vuori, Kristiina
2014-01-01
3-dimensional (3D) culture models have the potential to bridge the gap between monolayer cell culture and in vivo studies. To benefit anti-cancer drug discovery from 3D models, new techniques are needed that enable their use in high-throughput (HT) screening amenable formats. We have established miniaturized 3D culture methods robust enough for automated HT screens. We have applied these methods to evaluate the sensitivity of normal and tumorigenic breast epithelial cell lines against a panel of oncology drugs when cultured as monolayers (2D) and spheroids (3D). We have identified two classes of compounds that exhibit preferential cytotoxicity against cancer cells over normal cells when cultured as 3D spheroids: microtubule-targeting agents and epidermal growth factor receptor (EGFR) inhibitors. Further improving upon our 3D model, superior differentiation of EC50 values in the proof-of-concept screens was obtained by co-culturing the breast cancer cells with normal human fibroblasts and endothelial cells. Further, the selective sensitivity of the cancer cells towards chemotherapeutics was observed in 3D co-culture conditions, rather than as 2D co-culture monolayers, highlighting the importance of 3D cultures. Finally, we examined the putative mechanisms that drive the differing potency displayed by EGFR inhibitors. In summary, our studies establish robust 3D culture models of human cells for HT assessment of tumor cell-selective agents. This methodology is anticipated to provide a useful tool for the study of biological differences within 2D and 3D culture conditions in HT format, and an important platform for novel anti-cancer drug discovery.
Modeling high dimensional multichannel brain signals
Hu, Lechuan
2017-03-27
In this paper, our goal is to model functional and effective (directional) connectivity in network of multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The primary challenges here are twofold: first, there are major statistical and computational difficulties for modeling and analyzing high dimensional multichannel brain signals; second, there is no set of universally-agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with sufficiently high order so that complex lead-lag temporal dynamics between the channels can be accurately characterized. However, such a model contains a large number of parameters. Thus, we will estimate the high dimensional VAR parameter space by our proposed hybrid LASSLE method (LASSO+LSE) which is imposes regularization on the first step (to control for sparsity) and constrained least squares estimation on the second step (to improve bias and mean-squared error of the estimator). Then to characterize connectivity between channels in a brain network, we will use various measures but put an emphasis on partial directed coherence (PDC) in order to capture directional connectivity between channels. PDC is a directed frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative all possible receivers in the network. Using the proposed modeling approach, we have achieved some insights on learning in a rat engaged in a non-spatial memory task.
Modeling high dimensional multichannel brain signals
Hu, Lechuan; Fortin, Norbert; Ombao, Hernando
2017-01-01
In this paper, our goal is to model functional and effective (directional) connectivity in network of multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The primary challenges here are twofold: first, there are major statistical and computational difficulties for modeling and analyzing high dimensional multichannel brain signals; second, there is no set of universally-agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with sufficiently high order so that complex lead-lag temporal dynamics between the channels can be accurately characterized. However, such a model contains a large number of parameters. Thus, we will estimate the high dimensional VAR parameter space by our proposed hybrid LASSLE method (LASSO+LSE) which is imposes regularization on the first step (to control for sparsity) and constrained least squares estimation on the second step (to improve bias and mean-squared error of the estimator). Then to characterize connectivity between channels in a brain network, we will use various measures but put an emphasis on partial directed coherence (PDC) in order to capture directional connectivity between channels. PDC is a directed frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative all possible receivers in the network. Using the proposed modeling approach, we have achieved some insights on learning in a rat engaged in a non-spatial memory task.
Low-dimensional chaos in a hydrodynamic system
International Nuclear Information System (INIS)
Brandstater, A.; Swift, J.; Swinney, H.L.; Wolf, A.; Farmer, J.D.; Jen, E.; Crutchfield, J.P.
1983-01-01
Evidence is presented for low-dimensional strange attractors in Couette-Taylor flow data. Computations of the largest Lyapunov exponent and metric entropy show that the system displays sensitive dependence on initial conditions. Although the phase space is very high dimensional, analysis of experimental data shows that motion is restricted to an attractor of dimension less than 5 for Reynolds numbers up to 30% above the onset of chaos. The Lyapunov exponent, entropy, and dimension all generally increase with Reynolds number
Longo, Diane M; Louie, Brent; Ptacek, Jason; Friedland, Greg; Evensen, Erik; Putta, Santosh; Atallah, Michelle; Spellmeyer, David; Wang, Ena; Pos, Zoltan; Marincola, Francesco M; Schaeffer, Andrea; Lukac, Suzanne; Railkar, Radha; Beals, Chan R; Cesano, Alessandra; Carayannopoulos, Leonidas N; Hawtin, Rachael E
2014-06-21
Single-cell network profiling (SCNP) is a multiparametric flow cytometry-based approach that simultaneously measures evoked signaling in multiple cell subsets. Previously, using the SCNP approach, age-associated immune signaling responses were identified in a cohort of 60 healthy donors. In the current study, a high-dimensional analysis of intracellular signaling was performed by measuring 24 signaling nodes in 7 distinct immune cell subsets within PBMCs in an independent cohort of 174 healthy donors [144 elderly (>65 yrs); 30 young (25-40 yrs)]. Associations between age and 9 immune signaling responses identified in the previously published 60 donor cohort were confirmed in the current study. Furthermore, within the current study cohort, 48 additional immune signaling responses differed significantly between young and elderly donors. These associations spanned all profiled modulators and immune cell subsets. These results demonstrate that SCNP, a systems-based approach, can capture the complexity of the cellular mechanisms underlying immunological aging. Further, the confirmation of age associations in an independent donor cohort supports the use of SCNP as a tool for identifying reproducible predictive biomarkers in areas such as vaccine response and response to cancer immunotherapies.
Shui, Tao; Yang, Wen-Xing; Chen, Ai-Xi; Liu, Shaopeng; Li, Ling; Zhu, Zhonghu
2018-03-01
We propose a scheme for high-precision two-dimensional (2D) atom localization via the four-wave mixing (FWM) in a four-level double-Λ atomic system. Due to the position-dependent atom-field interaction, the 2D position information of the atoms can be directly determined by the measurement of the normalized light intensity of output FWM-generated field. We further show that, when the position-dependent generated FWM field has become sufficiently intense, efficient back-coupling to the FWM generating state becomes important. This back-coupling pathway leads to competitive multiphoton destructive interference of the FWM generating state by three supplied and one internally generated fields. We find that the precision of 2D atom localization can be improved significantly by the multiphoton destructive interference and depends sensitively on the frequency detunings and the pump field intensity. Interestingly enough, we show that adjusting the frequency detunings and the pump field intensity can modify significantly the FWM efficiency, and consequently lead to a redistribution of the atoms. As a result, the atom can be localized in one of four quadrants with holding the precision of atom localization.
Three dimensional characterization and archiving system
Energy Technology Data Exchange (ETDEWEB)
Sebastian, R.L.; Clark, R.; Gallman, P. [Coleman Research Corp., Springfield, VA (United States)] [and others
1995-10-01
The Three Dimensional Characterization and Archiving System (3D-ICAS) is being developed as a remote system to perform rapid in situ analysis of hazardous organics and radionuclide contamination on structural materials. Coleman Research and its subcontractors, Thermedics Detection, Inc. (TD) and the University of Idaho (UI) are in the second phase of a three phase program to develop 3D-ICAS to support Decontamination and Decommissioning (D&D) operations. Accurate physical characterization of surfaces and the radioactive and organic is a critical D&D task. Surface characterization includes identification of potentially dangerous inorganic materials, such as asbestos and transite. The 3D-ICAS system robotically conveys a multisensor probe near the surface to be inspected. The sensor position and orientation are monitored and controlled by Coherent laser radar (CLR) tracking. The ICAS fills the need for high speed automated organic analysis by means of gas chromatography-mass spectrometry sensors, and also by radionuclide sensors which combines alpha, beta, and gamma counting.
Three dimensional electrochemical system for neurobiological studies
DEFF Research Database (Denmark)
Vazquez, Patricia; Dimaki, Maria; Svendsen, Winnie Edith
2009-01-01
In this work we report a novel three dimensional electrode array for electrochemical measurements in neuronal studies. The main advantage of working with these out-of-plane structures is the enhanced sensitivity of the system in terms of measuring electrochemical changes in the environment...
Three dimensional characterization and archiving system
International Nuclear Information System (INIS)
Sebastian, R.L.; Clark, R.; Gallman, P.
1995-01-01
The Three Dimensional Characterization and Archiving System (3D-ICAS) is being developed as a remote system to perform rapid in situ analysis of hazardous organics and radionuclide contamination on structural materials. Coleman Research and its subcontractors, Thermedics Detection, Inc. (TD) and the University of Idaho (UI) are in the second phase of a three phase program to develop 3D-ICAS to support Decontamination and Decommissioning (D ampersand D) operations. Accurate physical characterization of surfaces and the radioactive and organic is a critical D ampersand D task. Surface characterization includes identification of potentially dangerous inorganic materials, such as asbestos and transite. Real-time remotely operable characterization instrumentation will significantly advance the analysis capabilities beyond those currently employed. Chemical analysis is a primary area where the characterization process will be improved. Chemical analysis plays a vital role throughout the process of decontamination. Before clean-up operations can begin the site must be characterized with respect to the type and concentration of contaminants, and detailed site mapping must clarify areas of both high and low risk. During remediation activities chemical analysis provides a means to measure progress and to adjust clean-up strategy. Once the clean-up process has been completed the results of chemical analysis will verify that the site is in compliance with federal and local regulations
A study of low-dimensional inhomogeneous systems
International Nuclear Information System (INIS)
Arredondo Leon, Yesenia
2009-01-01
While the properties of homogeneous one-dimensional systems, even with disorder, are relatively well-understood, very little is known about the properties of strongly interacting inhomogeneous systems. Their high-energy physics is determined by the underlying chemistry which, in the atomic scale, introduces Coulomb correlations and local potentials. On the other hand, at large length scales, the physics has to be described by the Tomonaga-Luttinger liquid (TLL) model. In order to establish a connection between the low-energy TLL and the quasi-one-dimensional systems synthesized in the laboratory, we investigate the density-density correlation function in inhomogeneous one-dimensional systems in the asymptotic region. To investigate homogeneous as well as inhomogeneous systems, we use the density-matrix renormalization group (DMRG) method. We present results for ground state properties, such as the density-density correlation function and the parameter K c , which characterizes its decay at large distances. (orig.)
A study of low-dimensional inhomogeneous systems
Energy Technology Data Exchange (ETDEWEB)
Arredondo Leon, Yesenia
2009-01-15
While the properties of homogeneous one-dimensional systems, even with disorder, are relatively well-understood, very little is known about the properties of strongly interacting inhomogeneous systems. Their high-energy physics is determined by the underlying chemistry which, in the atomic scale, introduces Coulomb correlations and local potentials. On the other hand, at large length scales, the physics has to be described by the Tomonaga-Luttinger liquid (TLL) model. In order to establish a connection between the low-energy TLL and the quasi-one-dimensional systems synthesized in the laboratory, we investigate the density-density correlation function in inhomogeneous one-dimensional systems in the asymptotic region. To investigate homogeneous as well as inhomogeneous systems, we use the density-matrix renormalization group (DMRG) method. We present results for ground state properties, such as the density-density correlation function and the parameter K{sub c}, which characterizes its decay at large distances. (orig.)
High dimensional model representation method for fuzzy structural dynamics
Adhikari, S.; Chowdhury, R.; Friswell, M. I.
2011-03-01
Uncertainty propagation in multi-parameter complex structures possess significant computational challenges. This paper investigates the possibility of using the High Dimensional Model Representation (HDMR) approach when uncertain system parameters are modeled using fuzzy variables. In particular, the application of HDMR is proposed for fuzzy finite element analysis of linear dynamical systems. The HDMR expansion is an efficient formulation for high-dimensional mapping in complex systems if the higher order variable correlations are weak, thereby permitting the input-output relationship behavior to be captured by the terms of low-order. The computational effort to determine the expansion functions using the α-cut method scales polynomically with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is first illustrated for multi-parameter nonlinear mathematical test functions with fuzzy variables. The method is then integrated with a commercial finite element software (ADINA). Modal analysis of a simplified aircraft wing with fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations. It is shown that using the proposed HDMR approach, the number of finite element function calls can be reduced without significantly compromising the accuracy.
Quantifying high dimensional entanglement with two mutually unbiased bases
Directory of Open Access Journals (Sweden)
Paul Erker
2017-07-01
Full Text Available We derive a framework for quantifying entanglement in multipartite and high dimensional systems using only correlations in two unbiased bases. We furthermore develop such bounds in cases where the second basis is not characterized beyond being unbiased, thus enabling entanglement quantification with minimal assumptions. Furthermore, we show that it is feasible to experimentally implement our method with readily available equipment and even conservative estimates of physical parameters.
Directory of Open Access Journals (Sweden)
Wei Tian
2015-01-01
Full Text Available Background: The treatment of high-grade developmental spondylolisthesis (HGDS is still challenging and controversial. In this study, we investigated the efficacy of the posterior reduction and monosegmental fusion assisted by intraoperative three-dimensional (3D navigation system in managing the HGDS. Methods: Thirteen consecutive HGDS patients were treated with posterior decompression, reduction and monosegmental fusion of L5/S1, assisted by intraoperative 3D navigation system. The clinical and radiographic outcomes were evaluated, with a minimum follow-up of 2 years. The differences between the pre- and post-operative measures were statistically analyzed using a two-tailed, paired t-test. Results: At most recent follow-up, 12 patients were pain-free. Only 1 patient had moderate pain. There were no permanent neurological complications or pseudarthrosis. The magnetic resonance imaging showed that there was no obvious disc degeneration in the adjacent segment. All radiographic parameters were improved. Mean slippage improved from 63.2% before surgery to 12.2% after surgery and 11.0% at latest follow-up. Lumbar lordosis changed from preoperative 34.9 ± 13.3° to postoperative 50.4 ± 9.9°, and 49.3 ± 7.8° at last follow-up. L5 incidence improved from 71.0 ± 11.3° to 54.0 ± 11.9° and did not change significantly at the last follow-up 53.1 ± 15.4°. While pelvic incidence remained unchanged, sacral slip significantly decreased from preoperative 32.7 ± 12.5° to postoperative 42.6 ± 9.8°and remained constant to the last follow-up 44.4 ± 6.9°. Pelvic tilt significantly decreased from 38.4 ± 12.5° to 30.9 ± 8.1° and remained unchanged at the last follow-up 28.1 ± 11.2°. Conclusions: Posterior reduction and monosegmental fusion of L5/S1 assisted by intraoperative 3D navigation are an effective technique for managing high-grade dysplastic spondylolisthesis. A complete reduction of local deformity and excellent correction of overall
Modeling High-Dimensional Multichannel Brain Signals
Hu, Lechuan
2017-12-12
Our goal is to model and measure functional and effective (directional) connectivity in multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The difficulties from analyzing these data mainly come from two aspects: first, there are major statistical and computational challenges for modeling and analyzing high-dimensional multichannel brain signals; second, there is no set of universally agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with potentially high lag order so that complex lead-lag temporal dynamics between the channels can be captured. Estimates of the VAR model will be obtained by our proposed hybrid LASSLE (LASSO + LSE) method which combines regularization (to control for sparsity) and least squares estimation (to improve bias and mean-squared error). Then we employ some measures of connectivity but put an emphasis on partial directed coherence (PDC) which can capture the directional connectivity between channels. PDC is a frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative to all possible receivers in the network. The proposed modeling approach provided key insights into potential functional relationships among simultaneously recorded sites during performance of a complex memory task. Specifically, this novel method was successful in quantifying patterns of effective connectivity across electrode locations, and in capturing how these patterns varied across trial epochs and trial types.
International Nuclear Information System (INIS)
Pernot, P.
1982-01-01
A curved multiwire proportional drift chamber has been built as a general purpose instrument for X-ray scattering and X-ray diffraction experiments with synchrotron radiation. This parallaxe-free one-dimensional linear position sensitive detector has a parallel readout with a double hit logic. The data acquisition system, installed as a part of the D11 camera at LURE-DCI, is designed to perform time slicing and cyclic experiments; it has been used with either the fast multiwire chamber or a standard position sensitive detector with delay line readout [fr
Genuinely high-dimensional nonlocality optimized by complementary measurements
International Nuclear Information System (INIS)
Lim, James; Ryu, Junghee; Yoo, Seokwon; Lee, Changhyoup; Bang, Jeongho; Lee, Jinhyoung
2010-01-01
Qubits exhibit extreme nonlocality when their state is maximally entangled and this is observed by mutually unbiased local measurements. This criterion does not hold for the Bell inequalities of high-dimensional systems (qudits), recently proposed by Collins-Gisin-Linden-Massar-Popescu and Son-Lee-Kim. Taking an alternative approach, called the quantum-to-classical approach, we derive a series of Bell inequalities for qudits that satisfy the criterion as for the qubits. In the derivation each d-dimensional subsystem is assumed to be measured by one of d possible measurements with d being a prime integer. By applying to two qubits (d=2), we find that a derived inequality is reduced to the Clauser-Horne-Shimony-Holt inequality when the degree of nonlocality is optimized over all the possible states and local observables. Further applying to two and three qutrits (d=3), we find Bell inequalities that are violated for the three-dimensionally entangled states but are not violated by any two-dimensionally entangled states. In other words, the inequalities discriminate three-dimensional (3D) entanglement from two-dimensional (2D) entanglement and in this sense they are genuinely 3D. In addition, for the two qutrits we give a quantitative description of the relations among the three degrees of complementarity, entanglement and nonlocality. It is shown that the degree of complementarity jumps abruptly to very close to its maximum as nonlocality starts appearing. These characteristics imply that complementarity plays a more significant role in the present inequality compared with the previously proposed inequality.
Usta, Taner A; Ozkaynak, Aysel; Kovalak, Ebru; Ergul, Erdinc; Naki, M Murat; Kaya, Erdal
2015-08-01
Two-dimensional (2D) view is known to cause practical difficulties for surgeons in conventional laparoscopy. Our goal was to evaluate whether the new-generation, Three-Dimensional Laparoscopic Vision System (3D LVS) provides greater benefit in terms of execution time and error number during the performance of surgical tasks. This study tests the hypothesis that the use of the new generation 3D LVS can significantly improve technical ability on complex laparoscopic tasks in an experimental model. Twenty-four participants (8 experienced, 8 minimally experienced, and 8 inexperienced) were evaluated for 10 different tasks in terms of total execution time and error number. The 4-point lickert scale was used for subjective assessment of the two imaging modalities. All tasks were completed by all participants. Statistically significant difference was determined between 3D and 2D systems in the tasks of bead transfer and drop, suturing, and pick-and-place in the inexperienced group; in the task of passing through two circles with the needle in the minimally experienced group; and in the tasks of bead transfer and drop, suturing and passing through two circles with the needle in the experienced group. Three-dimensional imaging was preferred over 2D in 6 of the 10 subjective criteria questions on 4-point lickert scale. The majority of the tasks were completed in a shorter time using 3D LVS compared to 2D LVS. The subjective Likert-scale ratings from each group also demonstrated a clear preference for 3D LVS. New 3D LVS has the potential to improve the learning curve, and reduce the operating time and error rate during the performances of laparoscopic surgeons. Our results suggest that the new-generation 3D HD LVS will be helpful for surgeons in laparoscopy (Clinical Trial ID: NCT01799577, Protocol ID: BEHGynobs-4).
Two-dimensional topological photonic systems
Sun, Xiao-Chen; He, Cheng; Liu, Xiao-Ping; Lu, Ming-Hui; Zhu, Shi-Ning; Chen, Yan-Feng
2017-09-01
The topological phase of matter, originally proposed and first demonstrated in fermionic electronic systems, has drawn considerable research attention in the past decades due to its robust transport of edge states and its potential with respect to future quantum information, communication, and computation. Recently, searching for such a unique material phase in bosonic systems has become a hot research topic worldwide. So far, many bosonic topological models and methods for realizing them have been discovered in photonic systems, acoustic systems, mechanical systems, etc. These discoveries have certainly yielded vast opportunities in designing material phases and related properties in the topological domain. In this review, we first focus on some of the representative photonic topological models and employ the underlying Dirac model to analyze the edge states and geometric phase. On the basis of these models, three common types of two-dimensional topological photonic systems are discussed: 1) photonic quantum Hall effect with broken time-reversal symmetry; 2) photonic topological insulator and the associated pseudo-time-reversal symmetry-protected mechanism; 3) time/space periodically modulated photonic Floquet topological insulator. Finally, we provide a summary and extension of this emerging field, including a brief introduction to the Weyl point in three-dimensional systems.
High-Dimensional Quantum Information Processing with Linear Optics
Fitzpatrick, Casey A.
Quantum information processing (QIP) is an interdisciplinary field concerned with the development of computers and information processing systems that utilize quantum mechanical properties of nature to carry out their function. QIP systems have become vastly more practical since the turn of the century. Today, QIP applications span imaging, cryptographic security, computation, and simulation (quantum systems that mimic other quantum systems). Many important strategies improve quantum versions of classical information system hardware, such as single photon detectors and quantum repeaters. Another more abstract strategy engineers high-dimensional quantum state spaces, so that each successful event carries more information than traditional two-level systems allow. Photonic states in particular bring the added advantages of weak environmental coupling and data transmission near the speed of light, allowing for simpler control and lower system design complexity. In this dissertation, numerous novel, scalable designs for practical high-dimensional linear-optical QIP systems are presented. First, a correlated photon imaging scheme using orbital angular momentum (OAM) states to detect rotational symmetries in objects using measurements, as well as building images out of those interactions is reported. Then, a statistical detection method using chains of OAM superpositions distributed according to the Fibonacci sequence is established and expanded upon. It is shown that the approach gives rise to schemes for sorting, detecting, and generating the recursively defined high-dimensional states on which some quantum cryptographic protocols depend. Finally, an ongoing study based on a generalization of the standard optical multiport for applications in quantum computation and simulation is reported upon. The architecture allows photons to reverse momentum inside the device. This in turn enables realistic implementation of controllable linear-optical scattering vertices for
71: Three dimensional radiation treatment planning system
International Nuclear Information System (INIS)
Purdy, J.A.; Wong, J.W.; Harms, W.B.; Drzymala, R.E.; Emami, B.
1987-01-01
A prototype 3-dimensional (3-D) radiation treatment planning (RTP) system has been developed and is in use. The system features a real-time display device and an array processor for computer intensive computations. The dose distribution can be displayed as 2-D isodose distributions superimposed on 2-D gray scale images of the patient's anatomy for any arbitrary plane and as a display of isodose surfaces in 3-D. In addition, dose-volume histograms can be generated. 7 refs.; 2 figs
Noise-induced drift in two-dimensional anisotropic systems
Farago, Oded
2017-10-01
We study the isothermal Brownian dynamics of a particle in a system with spatially varying diffusivity. Due to the heterogeneity of the system, the particle's mean displacement does not vanish even if it does not experience any physical force. This phenomenon has been termed "noise-induced drift," and has been extensively studied for one-dimensional systems. Here, we examine the noise-induced drift in a two-dimensional anisotropic system, characterized by a symmetric diffusion tensor with unequal diagonal elements. A general expression for the mean displacement vector is derived and presented as a sum of two vectors, depicting two distinct drifting effects. The first vector describes the tendency of the particle to drift toward the high diffusivity side in each orthogonal principal diffusion direction. This is a generalization of the well-known expression for the noise-induced drift in one-dimensional systems. The second vector represents a novel drifting effect, not found in one-dimensional systems, originating from the spatial rotation in the directions of the principal axes. The validity of the derived expressions is verified by using Langevin dynamics simulations. As a specific example, we consider the relative diffusion of two transmembrane proteins, and demonstrate that the average distance between them increases at a surprisingly fast rate of several tens of micrometers per second.
Blended particle filters for large-dimensional chaotic dynamical systems
Majda, Andrew J.; Qi, Di; Sapsis, Themistoklis P.
2014-01-01
A major challenge in contemporary data science is the development of statistically accurate particle filters to capture non-Gaussian features in large-dimensional chaotic dynamical systems. Blended particle filters that capture non-Gaussian features in an adaptively evolving low-dimensional subspace through particles interacting with evolving Gaussian statistics on the remaining portion of phase space are introduced here. These blended particle filters are constructed in this paper through a mathematical formalism involving conditional Gaussian mixtures combined with statistically nonlinear forecast models compatible with this structure developed recently with high skill for uncertainty quantification. Stringent test cases for filtering involving the 40-dimensional Lorenz 96 model with a 5-dimensional adaptive subspace for nonlinear blended filtering in various turbulent regimes with at least nine positive Lyapunov exponents are used here. These cases demonstrate the high skill of the blended particle filter algorithms in capturing both highly non-Gaussian dynamical features as well as crucial nonlinear statistics for accurate filtering in extreme filtering regimes with sparse infrequent high-quality observations. The formalism developed here is also useful for multiscale filtering of turbulent systems and a simple application is sketched below. PMID:24825886
International Nuclear Information System (INIS)
Tripathy, Rohit; Bilionis, Ilias; Gonzalez, Marcial
2016-01-01
Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the
Tripathy, Rohit; Bilionis, Ilias; Gonzalez, Marcial
2016-09-01
Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the
Energy Technology Data Exchange (ETDEWEB)
Tripathy, Rohit, E-mail: rtripath@purdue.edu; Bilionis, Ilias, E-mail: ibilion@purdue.edu; Gonzalez, Marcial, E-mail: marcial-gonzalez@purdue.edu
2016-09-15
Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the
Network Reconstruction From High-Dimensional Ordinary Differential Equations.
Chen, Shizhe; Shojaie, Ali; Witten, Daniela M
2017-01-01
We consider the task of learning a dynamical system from high-dimensional time-course data. For instance, we might wish to estimate a gene regulatory network from gene expression data measured at discrete time points. We model the dynamical system nonparametrically as a system of additive ordinary differential equations. Most existing methods for parameter estimation in ordinary differential equations estimate the derivatives from noisy observations. This is known to be challenging and inefficient. We propose a novel approach that does not involve derivative estimation. We show that the proposed method can consistently recover the true network structure even in high dimensions, and we demonstrate empirical improvement over competing approaches. Supplementary materials for this article are available online.
One-dimensional autonomous systems and dissipative systems
International Nuclear Information System (INIS)
Lopez, G.
1996-01-01
The Lagrangian and the Generalized Linear Momentum are given in terms of a constant of motion for a one-dimensional autonomous system. The possibility of having an explicit Hamiltonian expression is also analyzed. The approach is applied to some dissipative systems. Copyright copyright 1996 Academic Press, Inc
Methodology for dimensional variation analysis of ITER integrated systems
International Nuclear Information System (INIS)
Fuentes, F. Javier; Trouvé, Vincent; Cordier, Jean-Jacques; Reich, Jens
2016-01-01
Highlights: • Tokamak dimensional management methodology, based on 3D variation analysis, is presented. • Dimensional Variation Model implementation workflow is described. • Methodology phases are described in detail. The application of this methodology to the tolerance analysis of ITER Vacuum Vessel is presented. • Dimensional studies are a valuable tool for the assessment of Tokamak PCR (Project Change Requests), DR (Deviation Requests) and NCR (Non-Conformance Reports). - Abstract: The ITER machine consists of a large number of complex systems highly integrated, with critical functional requirements and reduced design clearances to minimize the impact in cost and performances. Tolerances and assembly accuracies in critical areas could have a serious impact in the final performances, compromising the machine assembly and plasma operation. The management of tolerances allocated to part manufacture and assembly processes, as well as the control of potential deviations and early mitigation of non-compliances with the technical requirements, is a critical activity on the project life cycle. A 3D tolerance simulation analysis of ITER Tokamak machine has been developed based on 3DCS dedicated software. This integrated dimensional variation model is representative of Tokamak manufacturing functional tolerances and assembly processes, predicting accurate values for the amount of variation on critical areas. This paper describes the detailed methodology to implement and update the Tokamak Dimensional Variation Model. The model is managed at system level. The methodology phases are illustrated by its application to the Vacuum Vessel (VV), considering the status of maturity of VV dimensional variation model. The following topics are described in this paper: • Model description and constraints. • Model implementation workflow. • Management of input and output data. • Statistical analysis and risk assessment. The management of the integration studies based on
Methodology for dimensional variation analysis of ITER integrated systems
Energy Technology Data Exchange (ETDEWEB)
Fuentes, F. Javier, E-mail: FranciscoJavier.Fuentes@iter.org [ITER Organization, Route de Vinon-sur-Verdon—CS 90046, 13067 St Paul-lez-Durance (France); Trouvé, Vincent [Assystem Engineering & Operation Services, rue J-M Jacquard CS 60117, 84120 Pertuis (France); Cordier, Jean-Jacques; Reich, Jens [ITER Organization, Route de Vinon-sur-Verdon—CS 90046, 13067 St Paul-lez-Durance (France)
2016-11-01
Highlights: • Tokamak dimensional management methodology, based on 3D variation analysis, is presented. • Dimensional Variation Model implementation workflow is described. • Methodology phases are described in detail. The application of this methodology to the tolerance analysis of ITER Vacuum Vessel is presented. • Dimensional studies are a valuable tool for the assessment of Tokamak PCR (Project Change Requests), DR (Deviation Requests) and NCR (Non-Conformance Reports). - Abstract: The ITER machine consists of a large number of complex systems highly integrated, with critical functional requirements and reduced design clearances to minimize the impact in cost and performances. Tolerances and assembly accuracies in critical areas could have a serious impact in the final performances, compromising the machine assembly and plasma operation. The management of tolerances allocated to part manufacture and assembly processes, as well as the control of potential deviations and early mitigation of non-compliances with the technical requirements, is a critical activity on the project life cycle. A 3D tolerance simulation analysis of ITER Tokamak machine has been developed based on 3DCS dedicated software. This integrated dimensional variation model is representative of Tokamak manufacturing functional tolerances and assembly processes, predicting accurate values for the amount of variation on critical areas. This paper describes the detailed methodology to implement and update the Tokamak Dimensional Variation Model. The model is managed at system level. The methodology phases are illustrated by its application to the Vacuum Vessel (VV), considering the status of maturity of VV dimensional variation model. The following topics are described in this paper: • Model description and constraints. • Model implementation workflow. • Management of input and output data. • Statistical analysis and risk assessment. The management of the integration studies based on
Three-dimensional hologram display system
Mintz, Frederick (Inventor); Chao, Tien-Hsin (Inventor); Bryant, Nevin (Inventor); Tsou, Peter (Inventor)
2009-01-01
The present invention relates to a three-dimensional (3D) hologram display system. The 3D hologram display system includes a projector device for projecting an image upon a display medium to form a 3D hologram. The 3D hologram is formed such that a viewer can view the holographic image from multiple angles up to 360 degrees. Multiple display media are described, namely a spinning diffusive screen, a circular diffuser screen, and an aerogel. The spinning diffusive screen utilizes spatial light modulators to control the image such that the 3D image is displayed on the rotating screen in a time-multiplexing manner. The circular diffuser screen includes multiple, simultaneously-operated projectors to project the image onto the circular diffuser screen from a plurality of locations, thereby forming the 3D image. The aerogel can use the projection device described as applicable to either the spinning diffusive screen or the circular diffuser screen.
Multivariate statistics high-dimensional and large-sample approximations
Fujikoshi, Yasunori; Shimizu, Ryoichi
2010-01-01
A comprehensive examination of high-dimensional analysis of multivariate methods and their real-world applications Multivariate Statistics: High-Dimensional and Large-Sample Approximations is the first book of its kind to explore how classical multivariate methods can be revised and used in place of conventional statistical tools. Written by prominent researchers in the field, the book focuses on high-dimensional and large-scale approximations and details the many basic multivariate methods used to achieve high levels of accuracy. The authors begin with a fundamental presentation of the basic
Some problems of dynamical systems on three dimensional manifolds
International Nuclear Information System (INIS)
Dong Zhenxie.
1985-08-01
It is important to study the dynamical systems on 3-dimensional manifolds, its importance is showing up in its close relation with our life. Because of the complication of topological structure of Dynamical systems on 3-dimensional manifolds, generally speaking, the search for 3-dynamical systems is not easier than 2-dynamical systems. This paper is a summary of the partial result of dynamical systems on 3-dimensional manifolds. (author)
Bifurcation analysis of a three dimensional system
Directory of Open Access Journals (Sweden)
Yongwen WANG
2018-04-01
Full Text Available In order to enrich the stability and bifurcation theory of the three dimensional chaotic systems, taking a quadratic truncate unfolding system with the triple singularity equilibrium as the research subject, the existence of the equilibrium, the stability and the bifurcation of the system near the equilibrium under different parametric conditions are studied. Using the method of mathematical analysis, the existence of the real roots of the corresponding characteristic equation under the different parametric conditions is analyzed, and the local manifolds of the equilibrium are gotten, then the possible bifurcations are guessed. The parametric conditions under which the equilibrium is saddle-focus are analyzed carefully by the Cardan formula. Moreover, the conditions of codimension-one Hopf bifucation and the prerequisites of the supercritical and subcritical Hopf bifurcation are found by computation. The results show that the system has abundant stability and bifurcation, and can also supply theorical support for the proof of the existence of the homoclinic or heteroclinic loop connecting saddle-focus and the Silnikov's chaos. This method can be extended to study the other higher nonlinear systems.
High-dimensional quantum cryptography with twisted light
International Nuclear Information System (INIS)
Mirhosseini, Mohammad; Magaña-Loaiza, Omar S; O’Sullivan, Malcolm N; Rodenburg, Brandon; Malik, Mehul; Boyd, Robert W; Lavery, Martin P J; Padgett, Miles J; Gauthier, Daniel J
2015-01-01
Quantum key distribution (QKD) systems often rely on polarization of light for encoding, thus limiting the amount of information that can be sent per photon and placing tight bounds on the error rates that such a system can tolerate. Here we describe a proof-of-principle experiment that indicates the feasibility of high-dimensional QKD based on the transverse structure of the light field allowing for the transfer of more than 1 bit per photon. Our implementation uses the orbital angular momentum (OAM) of photons and the corresponding mutually unbiased basis of angular position (ANG). Our experiment uses a digital micro-mirror device for the rapid generation of OAM and ANG modes at 4 kHz, and a mode sorter capable of sorting single photons based on their OAM and ANG content with a separation efficiency of 93%. Through the use of a seven-dimensional alphabet encoded in the OAM and ANG bases, we achieve a channel capacity of 2.05 bits per sifted photon. Our experiment demonstrates that, in addition to having an increased information capacity, multilevel QKD systems based on spatial-mode encoding can be more resilient against intercept-resend eavesdropping attacks. (paper)
NMR studies at high magnetic fields of LiVGe_2O_6, a quasi one-dimensional spin S=1 system
Vonlanthen, P.; Tanaka, K. B.; Clark, W. G.; Gavilano, J. L.; Ott, H. R.; Millet, P.; Mila, F.; Kuhns, P.; Reyes, A. P.; Moulton, W. G.
2001-03-01
We report ^7Li NMR studies of LiVGe_2O_6, a quasi one-dimensional spin S=1 system. Our measurements include NMR spectra, the spin-lattice relaxation rate, T_1-1, and the spin-spin relaxation rate, T_2-1, obtained at magnetic fields (B) of 9 and 23 T and temperatures (T) over the range 1.8 - 300 K. The 9 T NMR spectra show a continuous transfer of spectral weight from a paramagnetic phase to an antiferromagnetic one in a narrow temperature range of about 2 K around the transition temperature TN ≈ 25 K. Both phases coexist in this range. Below 10 K, well into the antiferromagnetic phase, the T_1-1 measurements are consistent with electron spin excitations across an energy gap (Δ) with Δ/k_B≈ 14 K at 9 T and 11 K at about 23 T; i.e., applying a large B slightly reduces Δ. Changing B from 9 to 23 T increases TN by 1 K. Thus, TN is influenced only marginally by B up to 23 Tesla. The UCLA part of the work was supported by NSF Grants DMR-9705369 and DMR-0072524.
Mitigating the Insider Threat Using High-Dimensional Search and Modeling
National Research Council Canada - National Science Library
Van Den Berg, Eric; Uphadyaya, Shambhu; Ngo, Phi H; Muthukrishnan, Muthu; Palan, Rajago
2006-01-01
In this project a system was built aimed at mitigating insider attacks centered around a high-dimensional search engine for correlating the large number of monitoring streams necessary for detecting insider attacks...
Transport in low-dimensional mesoscopic systems
Energy Technology Data Exchange (ETDEWEB)
Syzranov, Sergey
2011-05-05
The work is devoted to the physics of graphene-based optoelectronics and arrays of Josephson junctions. The first part deals with transport in a graphene p-n junction irradiated by an electromagnetic field. The photocurrent in such device is calculated analytically and compared to those observed in the recent experiments on graphene photodetectors. It is shown that in a clean effectively one-dimensional junction the photocurrent oscillates as a function of gate voltages due to the interference between electron paths accompanied by the resonant photon absorption. The second part of the thesis is devoted to the construction of a Drude-like theory for the transport of Cooper pairs in weakly disordered Josephson networks and to finding the conductivity and the characteristic temperature of the commencement of strong localization. Also, it is shown that the low-temperature superconductor-insulator transition is necessarily of the first order in all 3D and in most 2D systems.
Hierarchical low-rank approximation for high dimensional approximation
Nouy, Anthony
2016-01-01
Tensor methods are among the most prominent tools for the numerical solution of high-dimensional problems where functions of multiple variables have to be approximated. Such high-dimensional approximation problems naturally arise in stochastic analysis and uncertainty quantification. In many practical situations, the approximation of high-dimensional functions is made computationally tractable by using rank-structured approximations. In this talk, we present algorithms for the approximation in hierarchical tensor format using statistical methods. Sparse representations in a given tensor format are obtained with adaptive or convex relaxation methods, with a selection of parameters using crossvalidation methods.
Hierarchical low-rank approximation for high dimensional approximation
Nouy, Anthony
2016-01-07
Tensor methods are among the most prominent tools for the numerical solution of high-dimensional problems where functions of multiple variables have to be approximated. Such high-dimensional approximation problems naturally arise in stochastic analysis and uncertainty quantification. In many practical situations, the approximation of high-dimensional functions is made computationally tractable by using rank-structured approximations. In this talk, we present algorithms for the approximation in hierarchical tensor format using statistical methods. Sparse representations in a given tensor format are obtained with adaptive or convex relaxation methods, with a selection of parameters using crossvalidation methods.
Three dimensional characterization and archiving system
International Nuclear Information System (INIS)
Sebastian, R.L.; Clark, R.; Gallman, P.
1996-01-01
The Three Dimensional Characterization and Archiving System (3D-ICAS) is being developed as a remote system to perform rapid in situ analysis of hazardous organics and radionuclide contamination on structural materials. Coleman Research and its subcontractors, Thermedics Detection, Inc. (TD) and the University of Idaho (UI) are in the second phase of a three phase program to develop 3D-ICAS to support Decontamination and Decommissioning (D and D) operations. Accurate physical characterization of surfaces and the radioactive and organic is a critical D and D task. Surface characterization includes identification of potentially dangerous inorganic materials, such as asbestos and transite. Real-time remotely operable characterization instrumentation will significantly advance the analysis capabilities beyond those currently employed. Chemical analysis is a primary area where the characterization process will be improved. The 3D-ICAS system robotically conveys a multisensor probe near the surfaces to be inspected. The sensor position and orientation are monitored and controlled using coherent laser radar (CLR) tracking. The CLR also provides 3D facility maps which establish a 3D world view within which the robotic sensor system can operate
Magnetometry of low-dimensional electron and hole systems
Energy Technology Data Exchange (ETDEWEB)
Usher, A [School of Physics, University of Exeter, Stocker Road, Exeter EX4 4QL (United Kingdom); Elliott, M [School of Physics and Astronomy, Cardiff University, Queens Buildings, Cardiff CF24 3AA (United Kingdom)], E-mail: a.usher@exeter.ac.uk, E-mail: elliottm@cf.ac.uk
2009-03-11
The high-magnetic-field, low-temperature magnetic properties of low-dimensional electron and hole systems reveal a wealth of fundamental information. Quantum oscillations of the thermodynamic equilibrium magnetization yield the total density of states, a central quantity in understanding the quantum Hall effect in 2D systems. The magnetization arising from non-equilibrium circulating currents reveals details, not accessible with traditional measurements, of the vanishingly small longitudinal resistance in the quantum Hall regime. We review how the technique of magnetometry has been applied to these systems, the most important discoveries that have been made, and their theoretical significance. (topical review)
Three-dimensional integrated CAE system applying computer graphic technique
International Nuclear Information System (INIS)
Kato, Toshisada; Tanaka, Kazuo; Akitomo, Norio; Obata, Tokayasu.
1991-01-01
A three-dimensional CAE system for nuclear power plant design is presented. This system utilizes high-speed computer graphic techniques for the plant design review, and an integrated engineering database for handling the large amount of nuclear power plant engineering data in a unified data format. Applying this system makes it possible to construct a nuclear power plant using only computer data from the basic design phase to the manufacturing phase, and it increases the productivity and reliability of the nuclear power plants. (author)
Liya Thomas; R. Edward. Thomas
2011-01-01
We have developed an automated defect detection system and a state-of-the-art Graphic User Interface (GUI) for hardwood logs. The algorithm identifies defects at least 0.5 inch high and at least 3 inches in diameter on barked hardwood log and stem surfaces. To summarize defect features and to build a knowledge base, hundreds of defects were measured, photographed, and...
PREFACE: Dynamics of low-dimensional systems Dynamics of low-dimensional systems
Bernasconi, M.; Miret-Artés, S.; Toennies, J. P.
2012-03-01
With the development of techniques for high-resolution inelastic helium atom scattering (HAS), electron scattering (EELS) and neutron spin echo spectroscopy, it has become possible, within approximately the last thirty years, to measure the dispersion curves of surface phonons in insulators, semiconductors and metals. In recent years, the advent of new experimental techniques such as 3He spin-echo spectroscopy, scanning inelastic electron tunnel spectroscopy, inelastic x-ray scattering spectroscopy and inelastic photoemission have extended surface phonon spectroscopy to a variety of systems. These include ultra-thin metal films, adsorbates at surface and elementary processes where surface phonons play an important role. Other important directions have been actively pursued in the past decade: the dynamics of stepped surfaces and clusters grown on metal surfaces, due to their relevance in many dynamical and chemical processes at surfaces, including heterogeneous catalysis; clusters; diffusion etc. The role of surface effects in these processes has been conjectured since the early days of surface dynamics, although only now is the availability of ab initio approaches providing those conjectures with a microscopic basis. Last but not least, the investigation of non-adiabatic effects, originating for instance from the hybridization (avoided crossing) of the surface phonons branches with the quasi 1D electron-hole excitation branch, is also a challenging new direction. Furthermore, other elementary oscillations such as surface plasmons are being actively investigated. The aforementioned experimental breakthroughs have been accompanied by advances in the theoretical study of atom-surface interaction. In particular, in the past decade first principles calculations based on density functional perturbation theory have boosted the theoretical study of the dynamics of low-dimensional systems. Phonon dispersion relations of clean surfaces, the dynamics of adsorbates, and the
High-dimensional single-cell cancer biology.
Irish, Jonathan M; Doxie, Deon B
2014-01-01
Cancer cells are distinguished from each other and from healthy cells by features that drive clonal evolution and therapy resistance. New advances in high-dimensional flow cytometry make it possible to systematically measure mechanisms of tumor initiation, progression, and therapy resistance on millions of cells from human tumors. Here we describe flow cytometry techniques that enable a "single-cell " view of cancer. High-dimensional techniques like mass cytometry enable multiplexed single-cell analysis of cell identity, clinical biomarkers, signaling network phospho-proteins, transcription factors, and functional readouts of proliferation, cell cycle status, and apoptosis. This capability pairs well with a signaling profiles approach that dissects mechanism by systematically perturbing and measuring many nodes in a signaling network. Single-cell approaches enable study of cellular heterogeneity of primary tissues and turn cell subsets into experimental controls or opportunities for new discovery. Rare populations of stem cells or therapy-resistant cancer cells can be identified and compared to other types of cells within the same sample. In the long term, these techniques will enable tracking of minimal residual disease (MRD) and disease progression. By better understanding biological systems that control development and cell-cell interactions in healthy and diseased contexts, we can learn to program cells to become therapeutic agents or target malignant signaling events to specifically kill cancer cells. Single-cell approaches that provide deep insight into cell signaling and fate decisions will be critical to optimizing the next generation of cancer treatments combining targeted approaches and immunotherapy.
Relativistic collective diffusion in one-dimensional systems
Lin, Gui-Wu; Lam, Yu-Yiu; Zheng, Dong-Qin; Zhong, Wei-Rong
2018-05-01
The relativistic collective diffusion in one-dimensional molecular system is investigated through nonequilibrium molecular dynamics with Monte Carlo methods. We have proposed the relationship among the speed, the temperature, the density distribution and the collective diffusion coefficient of particles in a relativistic moving system. It is found that the relativistic speed of the system has no effect on the temperature, but the collective diffusion coefficient decreases to zero as the velocity of the system approaches to the speed of light. The collective diffusion coefficient is modified as D‧ = D(1 ‑w2 c2 )3 2 for satisfying the relativistic circumstances. The present results may contribute to the understanding of the behavior of the particles transport diffusion in a high speed system, as well as enlighten the study of biological metabolism at relativistic high speed situation.
Pattern formation in two-dimensional square-shoulder systems
International Nuclear Information System (INIS)
Fornleitner, Julia; Kahl, Gerhard
2010-01-01
Using a highly efficient and reliable optimization tool that is based on ideas of genetic algorithms, we have systematically studied the pattern formation of the two-dimensional square-shoulder system. An overwhelming wealth of complex ordered equilibrium structures emerge from this investigation as we vary the shoulder width. With increasing pressure three structural archetypes could be identified: cluster lattices, where clusters of particles occupy the sites of distorted hexagonal lattices, lane formation, and compact particle arrangements with high coordination numbers. The internal complexity of these structures increases with increasing shoulder width.
Pattern formation in two-dimensional square-shoulder systems
Energy Technology Data Exchange (ETDEWEB)
Fornleitner, Julia [Institut fuer Festkoerperforschung, Forschungsszentrum Juelich, D-52425 Juelich (Germany); Kahl, Gerhard, E-mail: fornleitner@cmt.tuwien.ac.a [Institut fuer Theoretische Physik and Centre for Computational Materials Science (CMS), Technische Universitaet Wien, Wiedner Hauptstrasse 8-10, A-1040 Wien (Austria)
2010-03-17
Using a highly efficient and reliable optimization tool that is based on ideas of genetic algorithms, we have systematically studied the pattern formation of the two-dimensional square-shoulder system. An overwhelming wealth of complex ordered equilibrium structures emerge from this investigation as we vary the shoulder width. With increasing pressure three structural archetypes could be identified: cluster lattices, where clusters of particles occupy the sites of distorted hexagonal lattices, lane formation, and compact particle arrangements with high coordination numbers. The internal complexity of these structures increases with increasing shoulder width.
Applications of Asymptotic Sampling on High Dimensional Structural Dynamic Problems
DEFF Research Database (Denmark)
Sichani, Mahdi Teimouri; Nielsen, Søren R.K.; Bucher, Christian
2011-01-01
The paper represents application of the asymptotic sampling on various structural models subjected to random excitations. A detailed study on the effect of different distributions of the so-called support points is performed. This study shows that the distribution of the support points has consid...... dimensional reliability problems in structural dynamics.......The paper represents application of the asymptotic sampling on various structural models subjected to random excitations. A detailed study on the effect of different distributions of the so-called support points is performed. This study shows that the distribution of the support points has...... is minimized. Next, the method is applied on different cases of linear and nonlinear systems with a large number of random variables representing the dynamic excitation. The results show that asymptotic sampling is capable of providing good approximations of low failure probability events for very high...
Distribution of high-dimensional entanglement via an intra-city free-space link.
Steinlechner, Fabian; Ecker, Sebastian; Fink, Matthias; Liu, Bo; Bavaresco, Jessica; Huber, Marcus; Scheidl, Thomas; Ursin, Rupert
2017-07-24
Quantum entanglement is a fundamental resource in quantum information processing and its distribution between distant parties is a key challenge in quantum communications. Increasing the dimensionality of entanglement has been shown to improve robustness and channel capacities in secure quantum communications. Here we report on the distribution of genuine high-dimensional entanglement via a 1.2-km-long free-space link across Vienna. We exploit hyperentanglement, that is, simultaneous entanglement in polarization and energy-time bases, to encode quantum information, and observe high-visibility interference for successive correlation measurements in each degree of freedom. These visibilities impose lower bounds on entanglement in each subspace individually and certify four-dimensional entanglement for the hyperentangled system. The high-fidelity transmission of high-dimensional entanglement under real-world atmospheric link conditions represents an important step towards long-distance quantum communications with more complex quantum systems and the implementation of advanced quantum experiments with satellite links.
Structures of two-dimensional three-body systems
International Nuclear Information System (INIS)
Ruan, W.Y.; Liu, Y.Y.; Bao, C.G.
1996-01-01
Features of the structure of L = 0 states of a two-dimensional three-body model system have been investigated. Three types of permutation symmetry of the spatial part, namely symmetric, antisymmetric, and mixed, have been considered. A comparison has been made between the two-dimensional system and the corresponding three-dimensional one. The effect of symmetry on microscopic structures is emphasized. (author)
Statistical mechanical analysis of (1 + ∞) dimensional disordered systems
International Nuclear Information System (INIS)
Skantzos, Nikolaos Stavrou
2001-01-01
Valuable insight into the theory of disordered systems and spin-glasses has been offered by two classes of exactly solvable models: one-dimensional models and mean-field (infinite-range) ones, which, each carry their own specific techniques and restrictions. Both classes of models are now considered as 'exactly solvable' in the sense that in the thermodynamic limit the partition sum can been carried out analytically and the average over the disorder can be performed using methods which are well understood. In this thesis I study equilibrium properties of spin systems with a combination of one-dimensional short- and infinite-range interactions. I find that such systems, under either synchronous or asynchronous spin dynamics, and even in the absence of disorder, lead to phase diagrams with first-order transitions and regions with a multiple number of locally stable states. I then proceed to the study of recurrent neural network models with (1+∞)-dimensional interactions, and find that the competing short- and long-range forces lead to highly complex phase diagrams and that unlike infinite-range (Hopfield-type) models these phase diagrams depend crucially on the number of patterns stored, even away from saturation. To solve the statics of such models for the case of synchronous dynamics I first make a detour to solve the synchronous counterpart of the one-dimensional random-field Ising model, where I prove rigorously that the physics of the two random-field models (synchronous vs. sequential) becomes asymptotically the same, leading to an extensive ground state entropy and an infinite hierarchy of discontinuous transitions close to zero temperature. Finally, I propose and solve the statics of a spin model for the prediction of secondary structure in random hetero-polymers (which are considered as the natural first step to the study of real proteins). The model lies in the class of (1+∞)-dimensional disordered systems as a consequence of having steric- and hydrogen
High-dimensional data in economics and their (robust) analysis
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2017-01-01
Roč. 12, č. 1 (2017), s. 171-183 ISSN 1452-4864 R&D Projects: GA ČR GA17-07384S Institutional support: RVO:67985556 Keywords : econometrics * high-dimensional data * dimensionality reduction * linear regression * classification analysis * robustness Subject RIV: BA - General Mathematics OBOR OECD: Business and management http://library.utia.cas.cz/separaty/2017/SI/kalina-0474076.pdf
High-dimensional Data in Economics and their (Robust) Analysis
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2017-01-01
Roč. 12, č. 1 (2017), s. 171-183 ISSN 1452-4864 R&D Projects: GA ČR GA17-07384S Grant - others:GA ČR(CZ) GA13-01930S Institutional support: RVO:67985807 Keywords : econometrics * high-dimensional data * dimensionality reduction * linear regression * classification analysis * robustness Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability
A sparse grid based method for generative dimensionality reduction of high-dimensional data
Bohn, Bastian; Garcke, Jochen; Griebel, Michael
2016-03-01
Generative dimensionality reduction methods play an important role in machine learning applications because they construct an explicit mapping from a low-dimensional space to the high-dimensional data space. We discuss a general framework to describe generative dimensionality reduction methods, where the main focus lies on a regularized principal manifold learning variant. Since most generative dimensionality reduction algorithms exploit the representer theorem for reproducing kernel Hilbert spaces, their computational costs grow at least quadratically in the number n of data. Instead, we introduce a grid-based discretization approach which automatically scales just linearly in n. To circumvent the curse of dimensionality of full tensor product grids, we use the concept of sparse grids. Furthermore, in real-world applications, some embedding directions are usually more important than others and it is reasonable to refine the underlying discretization space only in these directions. To this end, we employ a dimension-adaptive algorithm which is based on the ANOVA (analysis of variance) decomposition of a function. In particular, the reconstruction error is used to measure the quality of an embedding. As an application, the study of large simulation data from an engineering application in the automotive industry (car crash simulation) is performed.
Harnessing high-dimensional hyperentanglement through a biphoton frequency comb
Xie, Zhenda; Zhong, Tian; Shrestha, Sajan; Xu, Xinan; Liang, Junlin; Gong, Yan-Xiao; Bienfang, Joshua C.; Restelli, Alessandro; Shapiro, Jeffrey H.; Wong, Franco N. C.; Wei Wong, Chee
2015-08-01
Quantum entanglement is a fundamental resource for secure information processing and communications, and hyperentanglement or high-dimensional entanglement has been separately proposed for its high data capacity and error resilience. The continuous-variable nature of the energy-time entanglement makes it an ideal candidate for efficient high-dimensional coding with minimal limitations. Here, we demonstrate the first simultaneous high-dimensional hyperentanglement using a biphoton frequency comb to harness the full potential in both the energy and time domain. Long-postulated Hong-Ou-Mandel quantum revival is exhibited, with up to 19 time-bins and 96.5% visibilities. We further witness the high-dimensional energy-time entanglement through Franson revivals, observed periodically at integer time-bins, with 97.8% visibility. This qudit state is observed to simultaneously violate the generalized Bell inequality by up to 10.95 standard deviations while observing recurrent Clauser-Horne-Shimony-Holt S-parameters up to 2.76. Our biphoton frequency comb provides a platform for photon-efficient quantum communications towards the ultimate channel capacity through energy-time-polarization high-dimensional encoding.
Smooth controllability of infinite-dimensional quantum-mechanical systems
International Nuclear Information System (INIS)
Wu, Re-Bing; Tarn, Tzyh-Jong; Li, Chun-Wen
2006-01-01
Manipulation of infinite-dimensional quantum systems is important to controlling complex quantum dynamics with many practical physical and chemical backgrounds. In this paper, a general investigation is casted to the controllability problem of quantum systems evolving on infinite-dimensional manifolds. Recognizing that such problems are related with infinite-dimensional controllability algebras, we introduce an algebraic mathematical framework to describe quantum control systems possessing such controllability algebras. Then we present the concept of smooth controllability on infinite-dimensional manifolds, and draw the main result on approximate strong smooth controllability. This is a nontrivial extension of the existing controllability results based on the analysis over finite-dimensional vector spaces to analysis over infinite-dimensional manifolds. It also opens up many interesting problems for future studies
Unmanned Aerial System Four-Dimensional Gunnery Training Device Development
2017-10-01
Aerial System (UAS) Four-Dimensional Gunnery Training Device: Training Effectiveness Assessment (James & Miller, in press). 31 Technical ...Research Product 2018-05 Unmanned Aerial System Four-Dimensional Gunnery Training Device Development David R. James...for the Department of the Army by Northrop Grumman Corporation. Technical review by Thomas Rhett Graves, Ph.D., U.S. Army Research Institute
International Nuclear Information System (INIS)
Mertens, J.C.E.; Williams, J.J.; Chawla, Nikhilesh
2014-01-01
The design and construction of a modular high resolution X-ray computed tomography (XCT) system is highlighted in this paper. The design approach is detailed for meeting a specified set of instrument performance goals tailored towards experimental versatility and high resolution imaging. The XCT tool is unique in the detector and X-ray source design configuration, enabling control in the balance between detection efficiency and spatial resolution. The system package is also unique: The sample manipulation approach implemented enables a wide gamut of in situ experimentation to analyze structure evolution under applied stimulus, by optimizing scan conditions through a high degree of controllability. The component selection and design process is detailed: Incorporated components are specified, custom designs are shared, and the approach for their integration into a fully functional XCT scanner is provided. Custom designs discussed include the dual-target X-ray source cradle which maintains position and trajectory of the beam between the two X-ray target configurations with respect to a scintillator mounting and positioning assembly and the imaging sensor, as well as a novel large-format X-ray detector with enhanced adaptability. The instrument is discussed from an operational point of view, including the details of data acquisition and processing implemented for 3D imaging via micro-CT. The performance of the instrument is demonstrated on a silica-glass particle/hydroxyl-terminated-polybutadiene (HTPB) matrix binder PBX simulant. Post-scan data processing, specifically segmentation of the sample's relevant microstructure from the 3D reconstruction, is provided to demonstrate the utility of the instrument. - Highlights: • Custom built X-ray tomography system for microstructural characterization • Detector design for maximizing polychromatic X-ray detection efficiency • X-ray design offered for maximizing X-ray flux with respect to imaging resolution
Explorations on High Dimensional Landscapes: Spin Glasses and Deep Learning
Sagun, Levent
This thesis deals with understanding the structure of high-dimensional and non-convex energy landscapes. In particular, its focus is on the optimization of two classes of functions: homogeneous polynomials and loss functions that arise in machine learning. In the first part, the notion of complexity of a smooth, real-valued function is studied through its critical points. Existing theoretical results predict that certain random functions that are defined on high dimensional domains have a narrow band of values whose pre-image contains the bulk of its critical points. This section provides empirical evidence for convergence of gradient descent to local minima whose energies are near the predicted threshold justifying the existing asymptotic theory. Moreover, it is empirically shown that a similar phenomenon may hold for deep learning loss functions. Furthermore, there is a comparative analysis of gradient descent and its stochastic version showing that in high dimensional regimes the latter is a mere speedup. The next study focuses on the halting time of an algorithm at a given stopping condition. Given an algorithm, the normalized fluctuations of the halting time follow a distribution that remains unchanged even when the input data is sampled from a new distribution. Two qualitative classes are observed: a Gumbel-like distribution that appears in Google searches, human decision times, and spin glasses and a Gaussian-like distribution that appears in conjugate gradient method, deep learning with MNIST and random input data. Following the universality phenomenon, the Hessian of the loss functions of deep learning is studied. The spectrum is seen to be composed of two parts, the bulk which is concentrated around zero, and the edges which are scattered away from zero. Empirical evidence is presented for the bulk indicating how over-parametrized the system is, and for the edges that depend on the input data. Furthermore, an algorithm is proposed such that it would
High Performance, Three-Dimensional Bilateral Filtering
International Nuclear Information System (INIS)
Bethel, E. Wes
2008-01-01
Image smoothing is a fundamental operation in computer vision and image processing. This work has two main thrusts: (1) implementation of a bilateral filter suitable for use in smoothing, or denoising, 3D volumetric data; (2) implementation of the 3D bilateral filter in three different parallelization models, along with parallel performance studies on two modern HPC architectures. Our bilateral filter formulation is based upon the work of Tomasi [11], but extended to 3D for use on volumetric data. Our three parallel implementations use POSIX threads, the Message Passing Interface (MPI), and Unified Parallel C (UPC), a Partitioned Global Address Space (PGAS) language. Our parallel performance studies, which were conducted on a Cray XT4 supercomputer and aquad-socket, quad-core Opteron workstation, show our algorithm to have near-perfect scalability up to 120 processors. Parallel algorithms, such as the one we present here, will have an increasingly important role for use in production visual analysis systems as the underlying computational platforms transition from single- to multi-core architectures in the future.
High Performance, Three-Dimensional Bilateral Filtering
Energy Technology Data Exchange (ETDEWEB)
Bethel, E. Wes
2008-06-05
Image smoothing is a fundamental operation in computer vision and image processing. This work has two main thrusts: (1) implementation of a bilateral filter suitable for use in smoothing, or denoising, 3D volumetric data; (2) implementation of the 3D bilateral filter in three different parallelization models, along with parallel performance studies on two modern HPC architectures. Our bilateral filter formulation is based upon the work of Tomasi [11], but extended to 3D for use on volumetric data. Our three parallel implementations use POSIX threads, the Message Passing Interface (MPI), and Unified Parallel C (UPC), a Partitioned Global Address Space (PGAS) language. Our parallel performance studies, which were conducted on a Cray XT4 supercomputer and aquad-socket, quad-core Opteron workstation, show our algorithm to have near-perfect scalability up to 120 processors. Parallel algorithms, such as the one we present here, will have an increasingly important role for use in production visual analysis systems as the underlying computational platforms transition from single- to multi-core architectures in the future.
Safaei, S.; Haghnegahdar, A.; Razavi, S.
2016-12-01
Complex environmental models are now the primary tool to inform decision makers for the current or future management of environmental resources under the climate and environmental changes. These complex models often contain a large number of parameters that need to be determined by a computationally intensive calibration procedure. Sensitivity analysis (SA) is a very useful tool that not only allows for understanding the model behavior, but also helps in reducing the number of calibration parameters by identifying unimportant ones. The issue is that most global sensitivity techniques are highly computationally demanding themselves for generating robust and stable sensitivity metrics over the entire model response surface. Recently, a novel global sensitivity analysis method, Variogram Analysis of Response Surfaces (VARS), is introduced that can efficiently provide a comprehensive assessment of global sensitivity using the Variogram concept. In this work, we aim to evaluate the effectiveness of this highly efficient GSA method in saving computational burden, when applied to systems with extra-large number of input factors ( 100). We use a test function and a hydrological modelling case study to demonstrate the capability of VARS method in reducing problem dimensionality by identifying important vs unimportant input factors.
Generation and confirmation of a (100 x 100)-dimensional entangled quantum system.
Krenn, Mario; Huber, Marcus; Fickler, Robert; Lapkiewicz, Radek; Ramelow, Sven; Zeilinger, Anton
2014-04-29
Entangled quantum systems have properties that have fundamentally overthrown the classical worldview. Increasing the complexity of entangled states by expanding their dimensionality allows the implementation of novel fundamental tests of nature, and moreover also enables genuinely new protocols for quantum information processing. Here we present the creation of a (100 × 100)-dimensional entangled quantum system, using spatial modes of photons. For its verification we develop a novel nonlinear criterion which infers entanglement dimensionality of a global state by using only information about its subspace correlations. This allows very practical experimental implementation as well as highly efficient extraction of entanglement dimensionality information. Applications in quantum cryptography and other protocols are very promising.
Supporting Dynamic Quantization for High-Dimensional Data Analytics.
Guzun, Gheorghi; Canahuate, Guadalupe
2017-05-01
Similarity searches are at the heart of exploratory data analysis tasks. Distance metrics are typically used to characterize the similarity between data objects represented as feature vectors. However, when the dimensionality of the data increases and the number of features is large, traditional distance metrics fail to distinguish between the closest and furthest data points. Localized distance functions have been proposed as an alternative to traditional distance metrics. These functions only consider dimensions close to query to compute the distance/similarity. Furthermore, in order to enable interactive explorations of high-dimensional data, indexing support for ad-hoc queries is needed. In this work we set up to investigate whether bit-sliced indices can be used for exploratory analytics such as similarity searches and data clustering for high-dimensional big-data. We also propose a novel dynamic quantization called Query dependent Equi-Depth (QED) quantization and show its effectiveness on characterizing high-dimensional similarity. When applying QED we observe improvements in kNN classification accuracy over traditional distance functions. Gheorghi Guzun and Guadalupe Canahuate. 2017. Supporting Dynamic Quantization for High-Dimensional Data Analytics. In Proceedings of Ex-ploreDB'17, Chicago, IL, USA, May 14-19, 2017, 6 pages. https://doi.org/http://dx.doi.org/10.1145/3077331.3077336.
Analysing spatially extended high-dimensional dynamics by recurrence plots
Energy Technology Data Exchange (ETDEWEB)
Marwan, Norbert, E-mail: marwan@pik-potsdam.de [Potsdam Institute for Climate Impact Research, 14412 Potsdam (Germany); Kurths, Jürgen [Potsdam Institute for Climate Impact Research, 14412 Potsdam (Germany); Humboldt Universität zu Berlin, Institut für Physik (Germany); Nizhny Novgorod State University, Department of Control Theory, Nizhny Novgorod (Russian Federation); Foerster, Saskia [GFZ German Research Centre for Geosciences, Section 1.4 Remote Sensing, Telegrafenberg, 14473 Potsdam (Germany)
2015-05-08
Recurrence plot based measures of complexity are capable tools for characterizing complex dynamics. In this letter we show the potential of selected recurrence plot measures for the investigation of even high-dimensional dynamics. We apply this method on spatially extended chaos, such as derived from the Lorenz96 model and show that the recurrence plot based measures can qualitatively characterize typical dynamical properties such as chaotic or periodic dynamics. Moreover, we demonstrate its power by analysing satellite image time series of vegetation cover with contrasting dynamics as a spatially extended and potentially high-dimensional example from the real world. - Highlights: • We use recurrence plots for analysing partially extended dynamics. • We investigate the high-dimensional chaos of the Lorenz96 model. • The approach distinguishes different spatio-temporal dynamics. • We use the method for studying vegetation cover time series.
Accurate correlation energies in one-dimensional systems from small system-adapted basis functions
Baker, Thomas E.; Burke, Kieron; White, Steven R.
2018-02-01
We propose a general method for constructing system-dependent basis functions for correlated quantum calculations. Our construction combines features from several traditional approaches: plane waves, localized basis functions, and wavelets. In a one-dimensional mimic of Coulomb systems, it requires only 2-3 basis functions per electron to achieve high accuracy, and reproduces the natural orbitals. We illustrate its effectiveness for molecular energy curves and chains of many one-dimensional atoms. We discuss the promise and challenges for realistic quantum chemical calculations.
On spectral distribution of high dimensional covariation matrices
DEFF Research Database (Denmark)
Heinrich, Claudio; Podolskij, Mark
In this paper we present the asymptotic theory for spectral distributions of high dimensional covariation matrices of Brownian diffusions. More specifically, we consider N-dimensional Itô integrals with time varying matrix-valued integrands. We observe n equidistant high frequency data points...... of the underlying Brownian diffusion and we assume that N/n -> c in (0,oo). We show that under a certain mixed spectral moment condition the spectral distribution of the empirical covariation matrix converges in distribution almost surely. Our proof relies on method of moments and applications of graph theory....
High-dimensional model estimation and model selection
CERN. Geneva
2015-01-01
I will review concepts and algorithms from high-dimensional statistics for linear model estimation and model selection. I will particularly focus on the so-called p>>n setting where the number of variables p is much larger than the number of samples n. I will focus mostly on regularized statistical estimators that produce sparse models. Important examples include the LASSO and its matrix extension, the Graphical LASSO, and more recent non-convex methods such as the TREX. I will show the applicability of these estimators in a diverse range of scientific applications, such as sparse interaction graph recovery and high-dimensional classification and regression problems in genomics.
HSM: Heterogeneous Subspace Mining in High Dimensional Data
DEFF Research Database (Denmark)
Müller, Emmanuel; Assent, Ira; Seidl, Thomas
2009-01-01
Heterogeneous data, i.e. data with both categorical and continuous values, is common in many databases. However, most data mining algorithms assume either continuous or categorical attributes, but not both. In high dimensional data, phenomena due to the "curse of dimensionality" pose additional...... challenges. Usually, due to locally varying relevance of attributes, patterns do not show across the full set of attributes. In this paper we propose HSM, which defines a new pattern model for heterogeneous high dimensional data. It allows data mining in arbitrary subsets of the attributes that are relevant...... for the respective patterns. Based on this model we propose an efficient algorithm, which is aware of the heterogeneity of the attributes. We extend an indexing structure for continuous attributes such that HSM indexing adapts to different attribute types. In our experiments we show that HSM efficiently mines...
Quantum confinement effects in low-dimensional systems
Indian Academy of Sciences (India)
2015-06-03
Jun 3, 2015 ... Quantum confinement effects in low-dimensional systems. Figure 5. (a) Various cuts of the three-dimensional data showing energy vs. momen- tum dispersion relations for Ag film of 17 ML thickness on Ge(111). (b) Photo- emission intensity maps along ¯M– ¯ – ¯K direction. (c) Substrate bands replotted ...
Study of one dimensional magnetic system via field theory
International Nuclear Information System (INIS)
Talim, S.L.
1988-04-01
We present a study of one-dimensional magnetic system using field theory methods. We studied the discreteness effects in a classical anisotropic one dimensional antiferromagnet in an external magnetic field. It is shown that for TMMC, at the temperatures and magnetic fields where most experiments have been done, the corrections are small and can be neglected. (author)
Properties of interacting low-dimensional systems
Gumbs, Godfrey
2013-01-01
Filling the gap for comprehensive coverage of the realistic fundamentals and approaches needed to perform cutting-edge research on mesoscopic systems, this textbook allows advanced students to acquire and use the skills at a highly technical, research-qualifying level. Starting with a brief refresher to get all readers on an equal footing, the text moves on to a broad selection of advanced topics, backed by problems with solutions for use in classrooms as well as for self-study. Written by authors with research and teaching backgrounds from eminent institutions and based on a tried-and
Integrable finite-dimensional systems related to Lie algebras
International Nuclear Information System (INIS)
Olshanetsky, M.A.; Perelomov, A.M.
1979-01-01
Some solvable finite-dimensional classical and quantum systems related to the Lie algebras are considered. The dynamics of these systems is closely related to free motion on symmetric spaces. In specific cases the systems considered describe the one-dimensional n-body problem recently considered by many authors. The review represents from general and universal point of view the results obtained during the last few years. Besides, it contains some results both of physical and mathematical type
A hybridized K-means clustering approach for high dimensional ...
African Journals Online (AJOL)
International Journal of Engineering, Science and Technology ... Due to incredible growth of high dimensional dataset, conventional data base querying methods are inadequate to extract useful information, so researchers nowadays ... Recently cluster analysis is a popularly used data analysis method in number of areas.
High Dimensional Classification Using Features Annealed Independence Rules.
Fan, Jianqing; Fan, Yingying
2008-01-01
Classification using high-dimensional features arises frequently in many contemporary statistical studies such as tumor classification using microarray or other high-throughput data. The impact of dimensionality on classifications is largely poorly understood. In a seminal paper, Bickel and Levina (2004) show that the Fisher discriminant performs poorly due to diverging spectra and they propose to use the independence rule to overcome the problem. We first demonstrate that even for the independence classification rule, classification using all the features can be as bad as the random guessing due to noise accumulation in estimating population centroids in high-dimensional feature space. In fact, we demonstrate further that almost all linear discriminants can perform as bad as the random guessing. Thus, it is paramountly important to select a subset of important features for high-dimensional classification, resulting in Features Annealed Independence Rules (FAIR). The conditions under which all the important features can be selected by the two-sample t-statistic are established. The choice of the optimal number of features, or equivalently, the threshold value of the test statistics are proposed based on an upper bound of the classification error. Simulation studies and real data analysis support our theoretical results and demonstrate convincingly the advantage of our new classification procedure.
On Robust Information Extraction from High-Dimensional Data
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2014-01-01
Roč. 9, č. 1 (2014), s. 131-144 ISSN 1452-4864 Grant - others:GA ČR(CZ) GA13-01930S Institutional support: RVO:67985807 Keywords : data mining * high-dimensional data * robust econometrics * outliers * machine learning Subject RIV: IN - Informatics, Computer Science
Inference in High-dimensional Dynamic Panel Data Models
DEFF Research Database (Denmark)
Kock, Anders Bredahl; Tang, Haihan
We establish oracle inequalities for a version of the Lasso in high-dimensional fixed effects dynamic panel data models. The inequalities are valid for the coefficients of the dynamic and exogenous regressors. Separate oracle inequalities are derived for the fixed effects. Next, we show how one can...
Pricing High-Dimensional American Options Using Local Consistency Conditions
Berridge, S.J.; Schumacher, J.M.
2004-01-01
We investigate a new method for pricing high-dimensional American options. The method is of finite difference type but is also related to Monte Carlo techniques in that it involves a representative sampling of the underlying variables.An approximating Markov chain is built using this sampling and
Irregular grid methods for pricing high-dimensional American options
Berridge, S.J.
2004-01-01
This thesis proposes and studies numerical methods for pricing high-dimensional American options; important examples being basket options, Bermudan swaptions and real options. Four new methods are presented and analysed, both in terms of their application to various test problems, and in terms of
Asymptotics of empirical eigenstructure for high dimensional spiked covariance.
Wang, Weichen; Fan, Jianqing
2017-06-01
We derive the asymptotic distributions of the spiked eigenvalues and eigenvectors under a generalized and unified asymptotic regime, which takes into account the magnitude of spiked eigenvalues, sample size, and dimensionality. This regime allows high dimensionality and diverging eigenvalues and provides new insights into the roles that the leading eigenvalues, sample size, and dimensionality play in principal component analysis. Our results are a natural extension of those in Paul (2007) to a more general setting and solve the rates of convergence problems in Shen et al. (2013). They also reveal the biases of estimating leading eigenvalues and eigenvectors by using principal component analysis, and lead to a new covariance estimator for the approximate factor model, called shrinkage principal orthogonal complement thresholding (S-POET), that corrects the biases. Our results are successfully applied to outstanding problems in estimation of risks of large portfolios and false discovery proportions for dependent test statistics and are illustrated by simulation studies.
Global communication schemes for the numerical solution of high-dimensional PDEs
DEFF Research Database (Denmark)
Hupp, Philipp; Heene, Mario; Jacob, Riko
2016-01-01
The numerical treatment of high-dimensional partial differential equations is among the most compute-hungry problems and in urgent need for current and future high-performance computing (HPC) systems. It is thus also facing the grand challenges of exascale computing such as the requirement...
Three dimensional characterization and archiving system
International Nuclear Information System (INIS)
Clark, R.; Gallman, P.; Gaudreault, J.; Mosehauer, R.; Slotwinski, A.; Jarvis, G.; Griffiths, P.
1996-01-01
This system (3D-ICAS) is being developed as a remote system to perform rapid in situ analysis of hazardous organics and radionuclide contamination on structural materials. It is in the final phase of a 3-phase program to support Decontamination and Decommissioning (D ampersand D) operations. Accurate physical characterization of surfaces and radioactive and organic contamination is a critical D ampersand D task. Surface characterization includes identification of dangerous inorganic materials such as asbestos and transite. 3D-ICAS robotically conveys a multisensor probe near the surfaces to be inspected, using coherent laser radar tracking, which also provides 3D facility maps. High-speed automated organic analysis is provided by means of gas chromatograph-mass spectrometer sensor which can process a sample without contact in one minute. Volatile organics are extracted directly from contaminated surfaces without sample removal; multiple stage focusing is used for high time resolution. Additional discrimination is obtained through a final stage time-of-flight mass spectrometer. The radionuclide sensors combines α, β, and γ counting with energy discrimination of the α channel; this quantifies isotopes of U, Pu, Th, Tc, Np, and Am in one minute. The Molecular Vibrational Spectrometry sensor is used to characterize substrate material such as concrete, transite, wood, or asbestos; this can be used to provide estimates of the depth of contamination. The 3D-ICAS will be available for real-time monitoring immediately after each 1 to 2 minute sample period. After surface mapping, 3-D displays will be provided showing contours of detected contaminant concentrations. Permanent measurement and contaminant level archiving will be provided, assuring data integrity and allowing regulatory review before and after D ampersand D operations
Three-dimensional reconstruction and visualization system for medical images
International Nuclear Information System (INIS)
Preston, D.F.; Batnitzky, S.; Kyo Rak Lee; Cook, P.N.; Cook, L.T.; Dwyer, S.J.
1982-01-01
A three-dimensional reconstruction and visualization system could be of significant advantage in medical application such as neurosurgery and radiation treatment planning. The reconstructed anatomic structures from CT head scans could be used in a head stereotactic system to help plan the surgical procedure and the radiation treatment for a brain lesion. Also, the use of three-dimensional reconstruction algorithm provides for quantitative measures such as volume and surface area estimation of the anatomic features. This aspect of the three-dimensional reconstruction system may be used to monitor the progress or staging of a disease and the effects of patient treatment. Two cases are presented to illustrate the three-dimensional surface reconstruction and visualization system
Multisoliton formula for completely integrable two-dimensional systems
International Nuclear Information System (INIS)
Chudnovsky, D.V.; Chudnovsky, G.V.
1979-01-01
For general two-dimensional completely integrable systems, the exact formulae for multisoliton type solutions are given. The formulae are obtained algebrically from solutions of two linear partial differential equations
Strong chaos in one-dimensional quantum system
International Nuclear Information System (INIS)
Yang, C.-D.; Wei, C.-H.
2008-01-01
According to the Poincare-Bendixson theorem, a minimum of three autonomous equations is required to exhibit deterministic chaos. Because a one-dimensional quantum system is described by only two autonomous equations using de Broglie-Bohm's trajectory interpretation, chaos in one-dimensional quantum systems has long been considered impossible. We will prove in this paper that chaos phenomenon does exist in one-dimensional quantum systems, if the domain of quantum motions is extended to complex space by noting that the quantum world is actually characterized by a four-dimensional complex spacetime according to the E (∞) theory. Furthermore, we point out that the interaction between the real and imaginary parts of complex trajectories produces a new chaos phenomenon unique to quantum systems, called strong chaos, which describes the situation that quantum trajectories may emerge and diverge spontaneously without any perturbation in the initial position
Nonlinear transport behavior of low dimensional electron systems
Zhang, Jingqiao
The nonlinear behavior of low-dimensional electron systems attracts a great deal of attention for its fundamental interest as well as for potentially important applications in nanoelectronics. In response to microwave radiation and dc bias, strongly nonlinear electron transport that gives rise to unusual electron states has been reported in two-dimensional systems of electrons in high magnetic fields. There has also been great interest in the nonlinear response of quantum ballistic constrictions, where the effects of quantum interference, spatial dispersion and electron-electron interactions play crucial roles. In this thesis, experimental results of the research of low dimensional electron gas systems are presented. The first nonlinear phenomena were observed in samples of highly mobile two dimensional electrons in GaAs heavily doped quantum wells at different magnitudes of DC and AC (10 KHz to 20 GHz) excitations. We found that in the DC excitation regime the differential resistance oscillates with the DC current and external magnetic field, similar behavior was observed earlier in AlGaAs/GaAs heterostructures [C.L. Yang et al. ]. At external AC excitations the resistance is found to be also oscillating as a function of the magnetic field. However the form of the oscillations is considerably different from the DC case. We show that at frequencies below 100 KHz the difference is a result of a specific average of the DC differential resistance during the period of the external AC excitations. Secondly, in similar samples, strong suppression of the resistance by the electric field is observed in magnetic fields at which the Landau quantization of electron motion occurs. The phenomenon survives at high temperatures at which the Shubnikov de Haas oscillations are absent. The scale of the electric fields essential for the effect, is found to be proportional to temperature in the low temperature limit. We suggest that the strong reduction of the longitudinal resistance
Microfluidic engineered high cell density three-dimensional neural cultures
Cullen, D. Kacy; Vukasinovic, Jelena; Glezer, Ari; La Placa, Michelle C.
2007-06-01
Three-dimensional (3D) neural cultures with cells distributed throughout a thick, bioactive protein scaffold may better represent neurobiological phenomena than planar correlates lacking matrix support. Neural cells in vivo interact within a complex, multicellular environment with tightly coupled 3D cell-cell/cell-matrix interactions; however, thick 3D neural cultures at cell densities approaching that of brain rapidly decay, presumably due to diffusion limited interstitial mass transport. To address this issue, we have developed a novel perfusion platform that utilizes forced intercellular convection to enhance mass transport. First, we demonstrated that in thick (>500 µm) 3D neural cultures supported by passive diffusion, cell densities =104 cells mm-3), continuous medium perfusion at 2.0-11.0 µL min-1 improved viability compared to non-perfused cultures (p death and matrix degradation. In perfused cultures, survival was dependent on proximity to the perfusion source at 2.00-6.25 µL min-1 (p 90% viability in both neuronal cultures and neuronal-astrocytic co-cultures. This work demonstrates the utility of forced interstitial convection in improving the survival of high cell density 3D engineered neural constructs and may aid in the development of novel tissue-engineered systems reconstituting 3D cell-cell/cell-matrix interactions.
Growing B Lymphocytes in a Three-Dimensional Culture System
Wu, J. H. David; Bottaro, Andrea
2010-01-01
A three-dimensional (3D) culture system for growing long-lived B lymphocytes has been invented. The capabilities afforded by the system can be expected to expand the range of options for immunological research and related activities, including testing of immunogenicity of vaccine candidates in vitro, generation of human monoclonal antibodies, and immunotherapy. Mature lymphocytes, which are the effectors of adaptive immune responses in vertebrates, are extremely susceptible to apoptotic death, and depend on continuous reception of survival-inducing stimulation (in the forms of cytokines, cell-to-cell contacts, and antigen receptor signaling) from the microenvironment. For this reason, efforts to develop systems for long-term culture of functional, non-transformed and non-activated mature lymphocytes have been unsuccessful until now. The bone-marrow microenvironment supports the growth and differentiation of many hematopoietic lineages, in addition to B-lymphocytes. Primary bone-marrow cell cultures designed to promote the development of specific cell types in vitro are highly desirable experimental systems, amenable to manipulation under controlled conditions. However, the dynamic and complex network of stromal cells and insoluble matrix proteins is disrupted in prior plate- and flask-based culture systems, wherein the microenvironments have a predominantly two-dimensional (2D) character. In 2D bone-marrow cultures, normal B-lymphoid cells become progressively skewed toward precursor B-cell populations that do not retain a normal immunophenotype, and such mature B-lymphocytes as those harvested from the spleen or lymph nodes do not survive beyond several days ex vivo in the absence of mitogenic stimulation. The present 3D culture system is a bioreactor that contains highly porous artificial scaffolding that supports the long-term culture of bone marrow, spleen, and lymph-node samples. In this system, unlike in 2D culture systems, B-cell subpopulations developing
High speed laser tomography system
Samsonov, D.; Elsaesser, A.; Edwards, A.; Thomas, H. M.; Morfill, G. E.
2008-03-01
A high speed laser tomography system was developed capable of acquiring three-dimensional (3D) images of optically thin clouds of moving micron-sized particles. It operates by parallel-shifting an illuminating laser sheet with a pair of galvanometer-driven mirrors and synchronously recording two-dimensional (2D) images of thin slices of the imaged volume. The maximum scanning speed achieved was 120000slices/s, sequences of 24 volume scans (up to 256 slices each) have been obtained. The 2D slices were stacked to form 3D images of the volume, then the positions of the particles were identified and followed in the consecutive scans. The system was used to image a complex plasma with particles moving at speeds up to cm/s.
Implementation of three dimensional treatment planning system for external radiotherapy
International Nuclear Information System (INIS)
Major, Tibor; Kurup, P.G.G.; Stumpf, Janos
1997-01-01
A three dimensional (3D) treatment planning system was installed at Apollo Cancer Hospital, Chennai, India in 1995. This paper gives a short description of the system including hardware components, calculation algorithm, measured data requirements and specific three dimensional features. The concept and the structure of the system are shortly described. The first impressions along with critical opinions and the experiences are gained during the data acquisition are mentioned. Some improvements in the user interface are suggested. It is emphasized that although a 3D system offers more detailed and accurate dose distributions compared to a 2D system, it also introduces a greatly increased workload for the planning staff. (author)
The theory of critical phenomena in two-dimensional systems
International Nuclear Information System (INIS)
Olvera de la C, M.
1981-01-01
An exposition of the theory of critical phenomena in two-dimensional physical systems is presented. The first six chapters deal with the mean field theory of critical phenomena, scale invariance of the thermodynamic functions, Kadanoff's spin block construction, Wilson's renormalization group treatment of critical phenomena in configuration space, and the two-dimensional Ising model on a triangular lattice. The second part of this work is made of four chapters devoted to the application of the ideas expounded in the first part to the discussion of critical phenomena in superfluid films, two-dimensional crystals and the two-dimensional XY model of magnetic systems. Chapters seven to ten are devoted to the following subjects: analysis of long range order in one, two, and three-dimensional physical systems. Topological defects in the XY model, in superfluid films and in two-dimensional crystals. The Thouless-Kosterlitz iterated mean field theory of the dipole gas. The renormalization group treatment of the XY model, superfluid films and two-dimensional crystal. (author)
Tikhonov, Mikhail; Monasson, Remi
2018-01-01
Much of our understanding of ecological and evolutionary mechanisms derives from analysis of low-dimensional models: with few interacting species, or few axes defining "fitness". It is not always clear to what extent the intuition derived from low-dimensional models applies to the complex, high-dimensional reality. For instance, most naturally occurring microbial communities are strikingly diverse, harboring a large number of coexisting species, each of which contributes to shaping the environment of others. Understanding the eco-evolutionary interplay in these systems is an important challenge, and an exciting new domain for statistical physics. Recent work identified a promising new platform for investigating highly diverse ecosystems, based on the classic resource competition model of MacArthur. Here, we describe how the same analytical framework can be used to study evolutionary questions. Our analysis illustrates how, at high dimension, the intuition promoted by a one-dimensional (scalar) notion of fitness can become misleading. Specifically, while the low-dimensional picture emphasizes organism cost or efficiency, we exhibit a regime where cost becomes irrelevant for survival, and link this observation to generic properties of high-dimensional geometry.
One dimensional systems with singular perturbations
International Nuclear Information System (INIS)
Alvarez, J J; Gadella, M; Nieto, L M; Glasser, L M; Lara, L P
2011-01-01
This paper discusses some one dimensional quantum models with singular perturbations. Eventually, a mass discontinuity is added at the points that support the singular perturbations. The simplest model includes an attractive singular potential with a mass jump both located at the origin. We study the form of the only bound state. Another model exhibits a hard core at the origin plus one or more repulsive deltas with mass jumps at the points supporting these deltas. We study the location and the multiplicity of these resonances for the case of one or two deltas and settle the basis for a generalization. Finally, we consider the harmonic oscillator and the infinite square well plus a singular potential at the origin. We see how the energy of bound states is affected by the singular perturbation.
Engineering two-photon high-dimensional states through quantum interference
Zhang, Yingwen; Roux, Filippus S.; Konrad, Thomas; Agnew, Megan; Leach, Jonathan; Forbes, Andrew
2016-01-01
Many protocols in quantum science, for example, linear optical quantum computing, require access to large-scale entangled quantum states. Such systems can be realized through many-particle qubits, but this approach often suffers from scalability problems. An alternative strategy is to consider a lesser number of particles that exist in high-dimensional states. The spatial modes of light are one such candidate that provides access to high-dimensional quantum states, and thus they increase the storage and processing potential of quantum information systems. We demonstrate the controlled engineering of two-photon high-dimensional states entangled in their orbital angular momentum through Hong-Ou-Mandel interference. We prepare a large range of high-dimensional entangled states and implement precise quantum state filtering. We characterize the full quantum state before and after the filter, and are thus able to determine that only the antisymmetric component of the initial state remains. This work paves the way for high-dimensional processing and communication of multiphoton quantum states, for example, in teleportation beyond qubits. PMID:26933685
[Three dimensional CT reconstruction system on a personal computer].
Watanabe, E; Ide, T; Teramoto, A; Mayanagi, Y
1991-03-01
A new computer system to produce three dimensional surface image from CT scan has been invented. Although many similar systems have been already developed and reported, they are too expensive to be set up in routine clinical services because most of these systems are based on high power mini-computer systems. According to the opinion that a practical 3D-CT system should be used in daily clinical activities using only a personal computer, we have transplanted the 3D program into a personal computer working in MS-DOS (16-bit, 12 MHz). We added to the program a routine which simulates surgical dissection on the surface image. The time required to produce the surface image ranges from 40 to 90 seconds. To facilitate the simulation, we connected a 3D system with the neuronavigator. The navigator gives the position of the surgical simulation when the surgeon places the navigator tip on the patient's head thus simulating the surgical excision before the real dissection.
Applying recursive numerical integration techniques for solving high dimensional integrals
International Nuclear Information System (INIS)
Ammon, Andreas; Genz, Alan; Hartung, Tobias; Jansen, Karl; Volmer, Julia; Leoevey, Hernan
2016-11-01
The error scaling for Markov-Chain Monte Carlo techniques (MCMC) with N samples behaves like 1/√(N). This scaling makes it often very time intensive to reduce the error of computed observables, in particular for applications in lattice QCD. It is therefore highly desirable to have alternative methods at hand which show an improved error scaling. One candidate for such an alternative integration technique is the method of recursive numerical integration (RNI). The basic idea of this method is to use an efficient low-dimensional quadrature rule (usually of Gaussian type) and apply it iteratively to integrate over high-dimensional observables and Boltzmann weights. We present the application of such an algorithm to the topological rotor and the anharmonic oscillator and compare the error scaling to MCMC results. In particular, we demonstrate that the RNI technique shows an error scaling in the number of integration points m that is at least exponential.
High Dimensional Modulation and MIMO Techniques for Access Networks
DEFF Research Database (Denmark)
Binti Othman, Maisara
Exploration of advanced modulation formats and multiplexing techniques for next generation optical access networks are of interest as promising solutions for delivering multiple services to end-users. This thesis addresses this from two different angles: high dimensionality carrierless...... the capacity per wavelength of the femto-cell network. Bit rate up to 1.59 Gbps with fiber-wireless transmission over 1 m air distance is demonstrated. The results presented in this thesis demonstrate the feasibility of high dimensionality CAP in increasing the number of dimensions and their potentially......) optical access network. 2 X 2 MIMO RoF employing orthogonal frequency division multiplexing (OFDM) with 5.6 GHz RoF signaling over all-vertical cavity surface emitting lasers (VCSEL) WDM passive optical networks (PONs). We have employed polarization division multiplexing (PDM) to further increase...
Applying recursive numerical integration techniques for solving high dimensional integrals
Energy Technology Data Exchange (ETDEWEB)
Ammon, Andreas [IVU Traffic Technologies AG, Berlin (Germany); Genz, Alan [Washington State Univ., Pullman, WA (United States). Dept. of Mathematics; Hartung, Tobias [King' s College, London (United Kingdom). Dept. of Mathematics; Jansen, Karl; Volmer, Julia [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Leoevey, Hernan [Humboldt Univ. Berlin (Germany). Inst. fuer Mathematik
2016-11-15
The error scaling for Markov-Chain Monte Carlo techniques (MCMC) with N samples behaves like 1/√(N). This scaling makes it often very time intensive to reduce the error of computed observables, in particular for applications in lattice QCD. It is therefore highly desirable to have alternative methods at hand which show an improved error scaling. One candidate for such an alternative integration technique is the method of recursive numerical integration (RNI). The basic idea of this method is to use an efficient low-dimensional quadrature rule (usually of Gaussian type) and apply it iteratively to integrate over high-dimensional observables and Boltzmann weights. We present the application of such an algorithm to the topological rotor and the anharmonic oscillator and compare the error scaling to MCMC results. In particular, we demonstrate that the RNI technique shows an error scaling in the number of integration points m that is at least exponential.
HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.
Fan, Jianqing; Liao, Yuan; Mincheva, Martina
2011-01-01
The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied.
Impurity states in two - and three-dimensional disordered systems
International Nuclear Information System (INIS)
Silva, A.F. da; Fabbri, M.
1984-01-01
We investigate the microscopic structure of the impurity states in two-and three-dimensional (2D and 3d) disordered systems. A cluster model is outlined for the donor impurity density of states (DIDS) of doped semiconductors. It is shown that the impurity states are very sensitive to a change in the dimensionality of the system, i.e from 3D to 2D system. It is found that all eigenstates become localized in 2D disordered system for a large range of concentration. (Author) [pt
International Nuclear Information System (INIS)
Wu, T.; Cowan, C.L.; Lauer, A.; Schwiegk, H.J.
1982-03-01
The ASTERIX modular code package was developed at KFA Laboratory-Juelich for the steady state and xenon transient analysis of a pebble bed high temperature reactor. The code package was implemented on the Stanford Linear Accelerator Center Computer in August, 1980, and a user's manual for the current version of the code, identified as ASTERIX-2, was prepared as a cooperative effort by KFA Laboratory and GE-ARSD. The material in the manual includes the requirements for accessing the program, a description of the major subroutines, a listing of the input options, and a listing of the input data for a sample problem. The material is provided in sufficient detail for the user to carry out a wide range of analysis from steady state operations to the xenon induced power transients in which the local xenon, temperature, buckling and control feedback effects have been incorporated in the problem solution. (orig.)
High-dimensional change-point estimation: Combining filtering with convex optimization
Soh, Yong Sheng; Chandrasekaran, Venkat
2017-01-01
We consider change-point estimation in a sequence of high-dimensional signals given noisy observations. Classical approaches to this problem such as the filtered derivative method are useful for sequences of scalar-valued signals, but they have undesirable scaling behavior in the high-dimensional setting. However, many high-dimensional signals encountered in practice frequently possess latent low-dimensional structure. Motivated by this observation, we propose a technique for high-dimensional...
Model space dimensionalities for multiparticle fermion systems
International Nuclear Information System (INIS)
Draayer, J.P.; Valdes, H.T.
1985-01-01
A menu driven program for determining the dimensionalities of fixed-(J) [or (J,T)] model spaces built by distributing identical fermions (electrons, neutrons, protons) or two distinguihable fermion types (neutron-proton and isospin formalisms) among any mixture of positive and negative parity spherical orbitals is presented. The algorithm, built around the elementary difference formula d(J)=d(M=J)-d(M=J+1), takes full advantage of M->-M and particle-hole symmetries. A 96 K version of the program suffices for as compilated a case as d[(+1/2, +3/2, + 5/2, + 7/2-11/2)sup(n-26)J=2 + ,T=7]=210,442,716,722 found in the 0hω valence space of 56 126 Ba 70 . The program calculates the total fixed-(Jsup(π)) or fixed-(Jsup(π),T) dimensionality of a model space generated by distributing a specified number of fermions among a set of input positive and negative parity (π) spherical (j) orbitals. The user is queried at each step to select among various options: 1. formalism - identical particle, neutron-proton, isospin; 2. orbits -bumber, +/-2*J of all orbits; 3. limits -minimum/maximum number of particles of each parity; 4. specifics - number of particles, +/-2*J (total), 2*T; 5. continue - same orbit structure, new case quit. Though designed for nuclear applications (jj-coupling), the program can be used in the atomic case (LS-coupling) so long as half integer spin values (j=l+-1/2) are input for the valnce orbitals. Mutiple occurrences of a given j value are properly taken into account. A minor extension provides labelling information for a generalized seniority classification scheme. The program logic is an adaption of methods used in statistical spectroscopy to evaluate configuration averages. Indeed, the need for fixed symmetry leve densities in spectral distribution theory motivated this work. The methods extend to other group structures where there are M-like additive quantum labels. (orig.)
Manifold learning to interpret JET high-dimensional operational space
International Nuclear Information System (INIS)
Cannas, B; Fanni, A; Pau, A; Sias, G; Murari, A
2013-01-01
In this paper, the problem of visualization and exploration of JET high-dimensional operational space is considered. The data come from plasma discharges selected from JET campaigns from C15 (year 2005) up to C27 (year 2009). The aim is to learn the possible manifold structure embedded in the data and to create some representations of the plasma parameters on low-dimensional maps, which are understandable and which preserve the essential properties owned by the original data. A crucial issue for the design of such mappings is the quality of the dataset. This paper reports the details of the criteria used to properly select suitable signals downloaded from JET databases in order to obtain a dataset of reliable observations. Moreover, a statistical analysis is performed to recognize the presence of outliers. Finally data reduction, based on clustering methods, is performed to select a limited and representative number of samples for the operational space mapping. The high-dimensional operational space of JET is mapped using a widely used manifold learning method, the self-organizing maps. The results are compared with other data visualization methods. The obtained maps can be used to identify characteristic regions of the plasma scenario, allowing to discriminate between regions with high risk of disruption and those with low risk of disruption. (paper)
Four-dimensional maps of the human somatosensory system.
Avanzini, Pietro; Abdollahi, Rouhollah O; Sartori, Ivana; Caruana, Fausto; Pelliccia, Veronica; Casaceli, Giuseppe; Mai, Roberto; Lo Russo, Giorgio; Rizzolatti, Giacomo; Orban, Guy A
2016-03-29
A fine-grained description of the spatiotemporal dynamics of human brain activity is a major goal of neuroscientific research. Limitations in spatial and temporal resolution of available noninvasive recording and imaging techniques have hindered so far the acquisition of precise, comprehensive four-dimensional maps of human neural activity. The present study combines anatomical and functional data from intracerebral recordings of nearly 100 patients, to generate highly resolved four-dimensional maps of human cortical processing of nonpainful somatosensory stimuli. These maps indicate that the human somatosensory system devoted to the hand encompasses a widespread network covering more than 10% of the cortical surface of both hemispheres. This network includes phasic components, centered on primary somatosensory cortex and neighboring motor, premotor, and inferior parietal regions, and tonic components, centered on opercular and insular areas, and involving human parietal rostroventral area and ventral medial-superior-temporal area. The technique described opens new avenues for investigating the neural basis of all levels of cortical processing in humans.
Anonymous voting for multi-dimensional CV quantum system
International Nuclear Information System (INIS)
Shi Rong-Hua; Xiao Yi; Shi Jin-Jing; Guo Ying; Lee, Moon-Ho
2016-01-01
We investigate the design of anonymous voting protocols, CV-based binary-valued ballot and CV-based multi-valued ballot with continuous variables (CV) in a multi-dimensional quantum cryptosystem to ensure the security of voting procedure and data privacy. The quantum entangled states are employed in the continuous variable quantum system to carry the voting information and assist information transmission, which takes the advantage of the GHZ-like states in terms of improving the utilization of quantum states by decreasing the number of required quantum states. It provides a potential approach to achieve the efficient quantum anonymous voting with high transmission security, especially in large-scale votes. (paper)
One dimensional Bosons: From Condensed Matter Systems to Ultracold Gases
Cazalilla, M. A.; Citro, R.; Giamarchi, T.; Orignac, E.; Rigol, M.
2011-01-01
The physics of one-dimensional interacting bosonic systems is reviewed. Beginning with results from exactly solvable models and computational approaches, the concept of bosonic Tomonaga-Luttinger liquids relevant for one-dimensional Bose fluids is introduced, and compared with Bose-Einstein condensates existing in dimensions higher than one. The effects of various perturbations on the Tomonaga-Luttinger liquid state are discussed as well as extensions to multicomponent and out of equilibrium ...
Three-dimensional measurement system for crime scene documentation
Adamczyk, Marcin; Hołowko, Elwira; Lech, Krzysztof; Michoński, Jakub; MÄ czkowski, Grzegorz; Bolewicki, Paweł; Januszkiewicz, Kamil; Sitnik, Robert
2017-10-01
Three dimensional measurements (such as photogrammetry, Time of Flight, Structure from Motion or Structured Light techniques) are becoming a standard in the crime scene documentation process. The usage of 3D measurement techniques provide an opportunity to prepare more insightful investigation and helps to show every trace in the context of the entire crime scene. In this paper we would like to present a hierarchical, three-dimensional measurement system that is designed for crime scenes documentation process. Our system reflects the actual standards in crime scene documentation process - it is designed to perform measurement in two stages. First stage of documentation, the most general, is prepared with a scanner with relatively low spatial resolution but also big measuring volume - it is used for the whole scene documentation. Second stage is much more detailed: high resolution but smaller size of measuring volume for areas that required more detailed approach. The documentation process is supervised by a specialised application CrimeView3D, that is a software platform for measurements management (connecting with scanners and carrying out measurements, automatic or semi-automatic data registration in the real time) and data visualisation (3D visualisation of documented scenes). It also provides a series of useful tools for forensic technicians: virtual measuring tape, searching for sources of blood spatter, virtual walk on the crime scene and many others. In this paper we present our measuring system and the developed software. We also provide an outcome from research on metrological validation of scanners that was performed according to VDI/VDE standard. We present a CrimeView3D - a software-platform that was developed to manage the crime scene documentation process. We also present an outcome from measurement sessions that were conducted on real crime scenes with cooperation with Technicians from Central Forensic Laboratory of Police.
OBSERVING LYAPUNOV EXPONENTS OF INFINITE-DIMENSIONAL DYNAMICAL SYSTEMS.
Ott, William; Rivas, Mauricio A; West, James
2015-12-01
Can Lyapunov exponents of infinite-dimensional dynamical systems be observed by projecting the dynamics into ℝ N using a 'typical' nonlinear projection map? We answer this question affirmatively by developing embedding theorems for compact invariant sets associated with C 1 maps on Hilbert spaces. Examples of such discrete-time dynamical systems include time- T maps and Poincaré return maps generated by the solution semigroups of evolution partial differential equations. We make every effort to place hypotheses on the projected dynamics rather than on the underlying infinite-dimensional dynamical system. In so doing, we adopt an empirical approach and formulate checkable conditions under which a Lyapunov exponent computed from experimental data will be a Lyapunov exponent of the infinite-dimensional dynamical system under study (provided the nonlinear projection map producing the data is typical in the sense of prevalence).
Dynamical class of a two-dimensional plasmonic Dirac system.
Silva, Érica de Mello
2015-10-01
A current goal in plasmonic science and technology is to figure out how to manage the relaxational dynamics of surface plasmons in graphene since its damping constitutes a hinder for the realization of graphene-based plasmonic devices. In this sense we believe it might be of interest to enlarge the knowledge on the dynamical class of two-dimensional plasmonic Dirac systems. According to the recurrence relations method, different systems are said to be dynamically equivalent if they have identical relaxation functions at all times, and such commonality may lead to deep connections between seemingly unrelated physical systems. We employ the recurrence relations approach to obtain relaxation and memory functions of density fluctuations and show that a two-dimensional plasmonic Dirac system at long wavelength and zero temperature belongs to the same dynamical class of standard two-dimensional electron gas and classical harmonic oscillator chain with an impurity mass.
Elucidating high-dimensional cancer hallmark annotation via enriched ontology.
Yan, Shankai; Wong, Ka-Chun
2017-09-01
Cancer hallmark annotation is a promising technique that could discover novel knowledge about cancer from the biomedical literature. The automated annotation of cancer hallmarks could reveal relevant cancer transformation processes in the literature or extract the articles that correspond to the cancer hallmark of interest. It acts as a complementary approach that can retrieve knowledge from massive text information, advancing numerous focused studies in cancer research. Nonetheless, the high-dimensional nature of cancer hallmark annotation imposes a unique challenge. To address the curse of dimensionality, we compared multiple cancer hallmark annotation methods on 1580 PubMed abstracts. Based on the insights, a novel approach, UDT-RF, which makes use of ontological features is proposed. It expands the feature space via the Medical Subject Headings (MeSH) ontology graph and utilizes novel feature selections for elucidating the high-dimensional cancer hallmark annotation space. To demonstrate its effectiveness, state-of-the-art methods are compared and evaluated by a multitude of performance metrics, revealing the full performance spectrum on the full set of cancer hallmarks. Several case studies are conducted, demonstrating how the proposed approach could reveal novel insights into cancers. https://github.com/cskyan/chmannot. Copyright © 2017 Elsevier Inc. All rights reserved.
Reduced order surrogate modelling (ROSM) of high dimensional deterministic simulations
Mitry, Mina
Often, computationally expensive engineering simulations can prohibit the engineering design process. As a result, designers may turn to a less computationally demanding approximate, or surrogate, model to facilitate their design process. However, owing to the the curse of dimensionality, classical surrogate models become too computationally expensive for high dimensional data. To address this limitation of classical methods, we develop linear and non-linear Reduced Order Surrogate Modelling (ROSM) techniques. Two algorithms are presented, which are based on a combination of linear/kernel principal component analysis and radial basis functions. These algorithms are applied to subsonic and transonic aerodynamic data, as well as a model for a chemical spill in a channel. The results of this thesis show that ROSM can provide a significant computational benefit over classical surrogate modelling, sometimes at the expense of a minor loss in accuracy.
Electronic states in systems of reduced dimensionality
International Nuclear Information System (INIS)
Ulloa, S.E.
1992-01-01
This report briefly discusses the following research: magnetically modulated systems, inelastic magnetotunneling, ballistic transport review, screening in reduced dimensions, raman and electron energy loss spectroscopy; and ballistic quantum interference effects. (LSP)
Two dimensional electron systems for solid state quantum computation
Mondal, Sumit
Two dimensional electron systems based on GaAs/AlGaAs heterostructures are extremely useful in various scientific investigations of recent times including the search for quantum computational schemes. Although significant strides have been made over the past few years to realize solid state qubits on GaAs/AlGaAs 2DEGs, there are numerous factors limiting the progress. We attempt to identify factors that have material and design-specific origin and develop ways to overcome them. The thesis is divided in two broad segments. In the first segment we describe the realization of a new field-effect induced two dimensional electron system on GaAs/AlGaAs heterostructure where the novel device-design is expected to suppress the level of charge noise present in the device. Modulation-doped GaAs/AlGaAs heterostructures are utilized extensively in the study of quantum transport in nanostructures, but charge fluctuations associated with remote ionized dopants often produce deleterious effects. Electric field-induced carrier systems offer an attractive alternative if certain challenges can be overcome. We demonstrate a field-effect transistor in which the active channel is locally devoid of modulation-doping, but silicon dopant atoms are retained in the ohmic contact region to facilitate low-resistance contacts. A high quality two-dimensional electron gas is induced by a field-effect that is tunable over a density range of 6.5x10 10cm-2 to 2.6x1011cm-2 . Device design, fabrication, and low temperature (T=0.3K) characterization results are discussed. The demonstrated device-design overcomes several existing limitations in the fabrication of field-induced 2DEGs and might find utility in hosting nanostructures required for making spin qubits. The second broad segment describes our effort to correlate transport parameters measured at T=0.3K to the strength of the fractional quantum Hall state observed at nu=5/2 in the second Landau level of high-mobility GaAs/AlGaAs two dimensional
Port Hamiltonian Formulation of Infinite Dimensional Systems I. Modeling
Macchelli, Alessandro; Schaft, Arjan J. van der; Melchiorri, Claudio
2004-01-01
In this paper, some new results concerning the modeling of distributed parameter systems in port Hamiltonian form are presented. The classical finite dimensional port Hamiltonian formulation of a dynamical system is generalized in order to cope with the distributed parameter and multi-variable case.
Lyapunov equation for infinite-dimensional discrete bilinear systems
International Nuclear Information System (INIS)
Costa, O.L.V.; Kubrusly, C.S.
1991-03-01
Mean-square stability for discrete systems requires that uniform convergence is preserved between input and state correlation sequences. Such a convergence preserving property holds for an infinite-dimensional bilinear system if and only if the associate Lyapunov equation has a unique strictly positive solution. (author)
Machine Learning Control For Highly Reconfigurable High-Order Systems
2015-01-02
calibration and applications,” Mechatronics and Embedded Systems and Applications (MESA), 2010 IEEE/ASME International Conference on, IEEE, 2010, pp. 38–43...AFRL-OSR-VA-TR-2015-0012 MACHINE LEARNING CONTROL FOR HIGHLY RECONFIGURABLE HIGH-ORDER SYSTEMS John Valasek TEXAS ENGINEERING EXPERIMENT STATION...DIMENSIONAL RECONFIGURABLE SYSTEMS FA9550-11-1-0302 Period of Performance 1 July 2011 – 29 September 2014 John Valasek Aerospace Engineering
Phonons in low-dimensional systems
International Nuclear Information System (INIS)
Mayer, A P; Bonart, D; Strauch, D
2004-01-01
An introduction is given to the dynamical properties of crystalline systems having lattice-translational symmetry in less than three dimensions. These include surfaces of and interfaces between crystals, layered structures (2D lattice periodicity), bars and wires (1D lattice periodicity), as well as crystallites and clusters that have no lattice translational symmetry at all. In addition, superlattices are covered as artificial materials, giving rise to interesting dynamical effects. Crystal surfaces and crystalline bars are considered in some detail. For these systems, changes of the atomic equilibrium positions in comparison to the corresponding bulk crystals are also discussed since they frequently affect the dynamical properties
Accuracy Assessment for the Three-Dimensional Coordinates by High-Speed Videogrammetric Measurement
Directory of Open Access Journals (Sweden)
Xianglei Liu
2018-01-01
Full Text Available High-speed CMOS camera is a new kind of transducer to make the videogrammetric measurement for monitoring the displacement of high-speed shaking table structure. The purpose of this paper is to validate the three-dimensional coordinate accuracy of the shaking table structure acquired from the presented high-speed videogrammetric measuring system. In the paper, all of the key intermediate links are discussed, including the high-speed CMOS videogrammetric measurement system, the layout of the control network, the elliptical target detection, and the accuracy validation of final 3D spatial results. Through the accuracy analysis, the submillimeter accuracy can be made for the final the three-dimensional spatial coordinates which certify that the proposed high-speed videogrammetric technique is a better alternative technique which can replace the traditional transducer technique for monitoring the dynamic response for the shaking table structure.
INTRODUCTION: Physics of Low-dimensional Systems: Nobel Symposium 73
Lundqvist, Stig
1989-01-01
The physics of low-dimensional systems has developed in a remarkable way over the last decade and has accelerated over the last few years, in particular because of the discovery of the new high temperature superconductors. The new developments started more than fifteen years ago with the discovery of the unexpected quasi-one-dimensional character of the TTF-TCNQ. Since then the field of conducting quasi-one-dimensional organic systems have been rapidly growing. Parallel to the experimental work there has been an important theoretical development of great conceptual importance, such as charge density waves, soliton-like excitations, fractional charges, new symmetry properties etc. A new field of fundamental importance was the discovery of the Quantum Hall Effect in 1980. This field is still expanding with new experimental and theoretical discoveries. In 1986, then, came the totally unexpected discovery of high temperature superconductivity which started an explosive development. The three areas just mentioned formed the main themes of the Symposium. They do not in any way exhaust the progress in low-dimensional physics. We should mention the recent important development with both two-dimensional and one-dimensional and even zero-dimensional structures (quantum dots). The physics of mesoscopic systems is another important area where the low dimensionality is a key feature. Because of the small format of this Symposium we could unfortunately not cover these areas. A Nobel Symposium provides an excellent opportunity to bring together a group of prominent scientists for a stimulating exchange of new ideas and results. The Nobel Symposia are very small meetings by invitation only and the number of key international participants is typically in the range 25-40. These Symposia are arranged through a special Nobel Symposium Committee after proposal from individuals. This Symposium was sponsored by the Nobel Foundation through its Nobel Symposium Fund with grants from The
Internet-based dimensional verification system for reverse engineering processes
International Nuclear Information System (INIS)
Song, In Ho; Kim, Kyung Don; Chung, Sung Chong
2008-01-01
This paper proposes a design methodology for a Web-based collaborative system applicable to reverse engineering processes in a distributed environment. By using the developed system, design reviewers of new products are able to confirm geometric shapes, inspect dimensional information of products through measured point data, and exchange views with other design reviewers on the Web. In addition, it is applicable to verifying accuracy of production processes by manufacturing engineers. Functional requirements for designing this Web-based dimensional verification system are described in this paper. ActiveX-server architecture and OpenGL plug-in methods using ActiveX controls realize the proposed system. In the developed system, visualization and dimensional inspection of the measured point data are done directly on the Web: conversion of the point data into a CAD file or a VRML form is unnecessary. Dimensional verification results and design modification ideas are uploaded to markups and/or XML files during collaboration processes. Collaborators review the markup results created by others to produce a good design result on the Web. The use of XML files allows information sharing on the Web to be independent of the platform of the developed system. It is possible to diversify the information sharing capability among design collaborators. Validity and effectiveness of the developed system has been confirmed by case studies
Internet-based dimensional verification system for reverse engineering processes
Energy Technology Data Exchange (ETDEWEB)
Song, In Ho [Ajou University, Suwon (Korea, Republic of); Kim, Kyung Don [Small Business Corporation, Suwon (Korea, Republic of); Chung, Sung Chong [Hanyang University, Seoul (Korea, Republic of)
2008-07-15
This paper proposes a design methodology for a Web-based collaborative system applicable to reverse engineering processes in a distributed environment. By using the developed system, design reviewers of new products are able to confirm geometric shapes, inspect dimensional information of products through measured point data, and exchange views with other design reviewers on the Web. In addition, it is applicable to verifying accuracy of production processes by manufacturing engineers. Functional requirements for designing this Web-based dimensional verification system are described in this paper. ActiveX-server architecture and OpenGL plug-in methods using ActiveX controls realize the proposed system. In the developed system, visualization and dimensional inspection of the measured point data are done directly on the Web: conversion of the point data into a CAD file or a VRML form is unnecessary. Dimensional verification results and design modification ideas are uploaded to markups and/or XML files during collaboration processes. Collaborators review the markup results created by others to produce a good design result on the Web. The use of XML files allows information sharing on the Web to be independent of the platform of the developed system. It is possible to diversify the information sharing capability among design collaborators. Validity and effectiveness of the developed system has been confirmed by case studies
Xu, Cenke
Several examples of quantum spin systems and pseudo spin systems have been studied, and unconventional states of matters and phase transitions have been realized in all these systems under consideration. In the p +/- ip superconductor Josephson lattice and the p--band cold atomic system trapped in optical lattices, novel phases which behave similarly to 1+1 dimensional systems are realized, despite the fact that the real physical systems are in two or three dimensional spaces. For instance, by employing a spin-wave analysis together with a new duality transformation, we establish the existence and stability of a novel gapless "critical phase", which we refer to as a "bond algebraic liquid". This novel critical phase is analogous to the 1+1 dimensional algebraic boson liquid phase. The reason for the novel physics is that there is a quasilocal gauge symmetry in the effective low energy Hamiltonian. In a spin-1 system on the kagome lattice, and a hard-core boson system on the honeycomb lattice, the low energy physics is controlled by two components of compact U(1) gauge symmetries that emerge at low energy. Making use of the confinement nature of the 2+1 dimensional compact gauge theories and the powerful duality between gauge theories and height field theories, the crystalline phase diagrams are studied for both systems, and the transitions to other phases are also considered. These phase diagrams might be accessible in strongly correlated materials, or atomic systems in optical lattices. A novel quantum ground state of matter is realized in a bosonic model on three dimensional fcc lattice with emergent low energy excitations. The novel phase obtained is a stable gapless boson liquid phase, with algebraic boson density correlations. The stability of this phase is protected against the instanton effect and superfluidity by self-duality and large gauge symmetries on both sides of the duality. The gapless collective excitations of this phase closely resemble the
Three-Dimensional Electromagnetic High Frequency Axisymmetric Cavity Scars.
Energy Technology Data Exchange (ETDEWEB)
Warne, Larry Kevin; Jorgenson, Roy Eberhardt
2014-10-01
This report examines the localization of high frequency electromagnetic fi elds in three-dimensional axisymmetric cavities along periodic paths between opposing sides of the cavity. The cases where these orbits lead to unstable localized modes are known as scars. This report treats both the case where the opposing sides, or mirrors, are convex, where there are no interior foci, and the case where they are concave, leading to interior foci. The scalar problem is treated fi rst but the approximations required to treat the vector fi eld components are also examined. Particular att ention is focused on the normalization through the electromagnetic energy theorem. Both projections of the fi eld along the scarred orbit as well as point statistics are examined. Statistical comparisons are m ade with a numerical calculation of the scars run with an axisymmetric simulation. This axisymmetric cas eformstheoppositeextreme(wherethetwomirror radii at each end of the ray orbit are equal) from the two -dimensional solution examined previously (where one mirror radius is vastly di ff erent from the other). The enhancement of the fi eldontheorbitaxiscanbe larger here than in the two-dimensional case. Intentionally Left Blank
High-dimensional cluster analysis with the Masked EM Algorithm
Kadir, Shabnam N.; Goodman, Dan F. M.; Harris, Kenneth D.
2014-01-01
Cluster analysis faces two problems in high dimensions: first, the “curse of dimensionality” that can lead to overfitting and poor generalization performance; and second, the sheer time taken for conventional algorithms to process large amounts of high-dimensional data. We describe a solution to these problems, designed for the application of “spike sorting” for next-generation high channel-count neural probes. In this problem, only a small subset of features provide information about the cluster member-ship of any one data vector, but this informative feature subset is not the same for all data points, rendering classical feature selection ineffective. We introduce a “Masked EM” algorithm that allows accurate and time-efficient clustering of up to millions of points in thousands of dimensions. We demonstrate its applicability to synthetic data, and to real-world high-channel-count spike sorting data. PMID:25149694
Reinforcement learning on slow features of high-dimensional input streams.
Directory of Open Access Journals (Sweden)
Robert Legenstein
Full Text Available Humans and animals are able to learn complex behaviors based on a massive stream of sensory information from different modalities. Early animal studies have identified learning mechanisms that are based on reward and punishment such that animals tend to avoid actions that lead to punishment whereas rewarded actions are reinforced. However, most algorithms for reward-based learning are only applicable if the dimensionality of the state-space is sufficiently small or its structure is sufficiently simple. Therefore, the question arises how the problem of learning on high-dimensional data is solved in the brain. In this article, we propose a biologically plausible generic two-stage learning system that can directly be applied to raw high-dimensional input streams. The system is composed of a hierarchical slow feature analysis (SFA network for preprocessing and a simple neural network on top that is trained based on rewards. We demonstrate by computer simulations that this generic architecture is able to learn quite demanding reinforcement learning tasks on high-dimensional visual input streams in a time that is comparable to the time needed when an explicit highly informative low-dimensional state-space representation is given instead of the high-dimensional visual input. The learning speed of the proposed architecture in a task similar to the Morris water maze task is comparable to that found in experimental studies with rats. This study thus supports the hypothesis that slowness learning is one important unsupervised learning principle utilized in the brain to form efficient state representations for behavioral learning.
Electron localization in one-dimensional systems
International Nuclear Information System (INIS)
Chao, K.A.
1984-01-01
The pure regional localization and the global localization have been investigated via the inverse participation ratio and te moment analysis. If the envelop function of a localized state is more complicated than the simple exponential function e sup(-r/xi), the inverse participation ratio is inadequate to describe the localization properties of an electron. This is the case discovered recently in a stereo-irregular chain fo atoms including the electron-electron interaction and the structure disorder. The localization properties in this system are analysed in terms of the moments. (Author) [pt
Hawking radiation of a high-dimensional rotating black hole
Energy Technology Data Exchange (ETDEWEB)
Zhao, Ren; Zhang, Lichun; Li, Huaifan; Wu, Yueqin [Shanxi Datong University, Institute of Theoretical Physics, Department of Physics, Datong (China)
2010-01-15
We extend the classical Damour-Ruffini method and discuss Hawking radiation spectrum of high-dimensional rotating black hole using Tortoise coordinate transformation defined by taking the reaction of the radiation to the spacetime into consideration. Under the condition that the energy and angular momentum are conservative, taking self-gravitation action into account, we derive Hawking radiation spectrums which satisfy unitary principle in quantum mechanics. It is shown that the process that the black hole radiates particles with energy {omega} is a continuous tunneling process. We provide a theoretical basis for further studying the physical mechanism of black-hole radiation. (orig.)
The additive hazards model with high-dimensional regressors
DEFF Research Database (Denmark)
Martinussen, Torben; Scheike, Thomas
2009-01-01
This paper considers estimation and prediction in the Aalen additive hazards model in the case where the covariate vector is high-dimensional such as gene expression measurements. Some form of dimension reduction of the covariate space is needed to obtain useful statistical analyses. We study...... model. A standard PLS algorithm can also be constructed, but it turns out that the resulting predictor can only be related to the original covariates via time-dependent coefficients. The methods are applied to a breast cancer data set with gene expression recordings and to the well known primary biliary...
High-dimensional quantum channel estimation using classical light
CSIR Research Space (South Africa)
Mabena, Chemist M
2017-11-01
Full Text Available stream_source_info Mabena_20007_2017.pdf.txt stream_content_type text/plain stream_size 960 Content-Encoding UTF-8 stream_name Mabena_20007_2017.pdf.txt Content-Type text/plain; charset=UTF-8 PHYSICAL REVIEW A 96, 053860... (2017) High-dimensional quantum channel estimation using classical light Chemist M. Mabena CSIR National Laser Centre, P.O. Box 395, Pretoria 0001, South Africa and School of Physics, University of the Witwatersrand, Johannesburg 2000, South...
Data analysis in high-dimensional sparse spaces
DEFF Research Database (Denmark)
Clemmensen, Line Katrine Harder
classification techniques for high-dimensional problems are presented: Sparse discriminant analysis, sparse mixture discriminant analysis and orthogonality constrained support vector machines. The first two introduces sparseness to the well known linear and mixture discriminant analysis and thereby provide low...... are applied to classifications of fish species, ear canal impressions used in the hearing aid industry, microbiological fungi species, and various cancerous tissues and healthy tissues. In addition, novel applications of sparse regressions (also called the elastic net) to the medical, concrete, and food...
Jacob, V Y P; Stallmach, A; Felber, J
2016-06-01
Changes in gastric and small bowel motility are a common clinical problem. Currently diagnostic options are limited because each method harbors certain disadvantages. It has been shown that the high-resolution three-dimensional magnetic detector system 3D-MAGMA is capable of reliably measuring gastric and small intestine motor activity. This system allows precise localization of a small magnetic marker and determination of its three-dimensional orientation inside a human body. The aim of the current study was to determine if 3D-MAGMA is reliably able to detect changes in gastric and small bowel motility under controlled conditions. MCP was used as a well known prokinetic agent to shorten the gastric and small bowel passage. 8 healthy volunteers (fasting) underwent motility testing of the stomach and small bowel by 3D-MAGMA with and without administration of MCP (10 mg orally). Among other data the time the capsule needed to pass through the stomach and the duodenum and the time the capsule needed to pass through the first 50 cm of the jejunum were recorded. The retention time of the capsule in the stomach under physiological conditions was 49.1 minutes (median; min. 18 min; max. 88.8 min). The median time the capsule needed to pass through the duodenum was 13.8 minutes (median; min. 1.7 min; max. 24.8 min). The time the capsule needed to pass through the first 50 cm of the jejunum under physiological conditions was 33.0 minutes (median; min. 20.2 min; max. 67.2 min). The retention time of the capsule in the stomach decreased significantly after administration of MCP to 20.9 minutes (median; min. 1.7 min; max. 62.8 min; p = 0.008). The time the capsule needed to pass through the duodenum was also reduced to 7.1 minutes (median; min. 3.1 min; max. 18.3 min; p = 0.055). The time the capsule needed to pass through the first 50 cm of the jejunum was also reduced to 21.7 minutes (median; min. 10.7 min; max. 31.2 min; p = 0.069). 3D-MAGMA is able
International Nuclear Information System (INIS)
Yamamoto, Ritsu; Yonesaka, Akio; Nishioka, Seiko; Watari, Hidemichi; Hashimoto, Takayuki; Uchida, Daichi; Taguchi, Hiroshi; Nishioka, Takeshi; Miyasaka, Kazuo; Sakuragi, Noriaki; Shirato, Hiroki
2004-01-01
The feasibility and accuracy of high dose three-dimensional conformal boost (3DCB) using three internal fiducial markers and a two-orthogonal X-ray set-up of the real-time tumor-tracking system on patients with gynecological malignancy were investigated in 10 patients. The standard deviation of the distribution of systematic deviations (Σ) was reduced from 3.8, 4.6, and 4.9 mm in the manual set-up to 2.3, 2.3 and 2.7 mm in the set-up using the internal markers. The average standard deviation of the distribution of random deviations (σ) was reduced from 3.7, 5.0, and 4.5 mm in the manual set-up to 3.3, 3.0, and 4.2 mm in the marker set-up. The appropriate PTV margin was estimated to be 10.2, 12.8, and 12.9 mm in the manual set-up and 6.9, 6.7, and 8.3 mm in the gold marker set-up, respectively, using the formula 2Σ+0.7σ. Set-up of the patients with three markers and two fluoroscopy is useful to reduce PTV margin and perform 3DCB
Generic Bell inequalities for multipartite mulit-dimensional systems
International Nuclear Information System (INIS)
Son, W.; Lee, J.; Kim, M.S.
2005-01-01
Full text: We present generic Bell inequalities for multipartite multi-dimensional systems. They utilize the set of measurements, which are coincident with the generalized version of Greenberger, Horne and Zeilinger (GHZ) paradox. The inequalities that must be satisfied by any local realistic theories are violated by quantum mechanics for even-dimensional multipartite systems. It is also shown that the maximal violation of the inequality is obtained by the generalized GHZ state, which is true multi-body nonseparable state. As a special case for the multipartite two-dimensional systems, it can be shown that the inequality agrees with Bell-Mermin version of inequality. Large sets of variants are shown to naturally emerge from the generic Bell inequalities. We will discuss the particular variants of Bell inequalities that are violated for all the systems including odd-dimensional multipartite systems. Interestingly the variants can be reduced into the Clauser-Horne-Shimony-Holt (CHSH) inequality as well as Ardehali inequality. (author)
Simulations of dimensionally reduced effective theories of high temperature QCD
Hietanen, Ari
Quantum chromodynamics (QCD) is the theory describing interaction between quarks and gluons. At low temperatures, quarks are confined forming hadrons, e.g. protons and neutrons. However, at extremely high temperatures the hadrons break apart and the matter transforms into plasma of individual quarks and gluons. In this theses the quark gluon plasma (QGP) phase of QCD is studied using lattice techniques in the framework of dimensionally reduced effective theories EQCD and MQCD. Two quantities are in particular interest: the pressure (or grand potential) and the quark number susceptibility. At high temperatures the pressure admits a generalised coupling constant expansion, where some coefficients are non-perturbative. We determine the first such contribution of order g^6 by performing lattice simulations in MQCD. This requires high precision lattice calculations, which we perform with different number of colors N_c to obtain N_c-dependence on the coefficient. The quark number susceptibility is studied by perf...
Two-dimensional approach to relativistic positioning systems
International Nuclear Information System (INIS)
Coll, Bartolome; Ferrando, Joan Josep; Morales, Juan Antonio
2006-01-01
A relativistic positioning system is a physical realization of a coordinate system consisting in four clocks in arbitrary motion broadcasting their proper times. The basic elements of the relativistic positioning systems are presented in the two-dimensional case. This simplified approach allows to explain and to analyze the properties and interest of these new systems. The positioning system defined by geodesic emitters in flat metric is developed in detail. The information that the data generated by a relativistic positioning system give on the space-time metric interval is analyzed, and the interest of these results in gravimetry is pointed out
Scalable Nearest Neighbor Algorithms for High Dimensional Data.
Muja, Marius; Lowe, David G
2014-11-01
For many computer vision and machine learning problems, large training sets are key for good performance. However, the most computationally expensive part of many computer vision and machine learning algorithms consists of finding nearest neighbor matches to high dimensional vectors that represent the training data. We propose new algorithms for approximate nearest neighbor matching and evaluate and compare them with previous algorithms. For matching high dimensional features, we find two algorithms to be the most efficient: the randomized k-d forest and a new algorithm proposed in this paper, the priority search k-means tree. We also propose a new algorithm for matching binary features by searching multiple hierarchical clustering trees and show it outperforms methods typically used in the literature. We show that the optimal nearest neighbor algorithm and its parameters depend on the data set characteristics and describe an automated configuration procedure for finding the best algorithm to search a particular data set. In order to scale to very large data sets that would otherwise not fit in the memory of a single machine, we propose a distributed nearest neighbor matching framework that can be used with any of the algorithms described in the paper. All this research has been released as an open source library called fast library for approximate nearest neighbors (FLANN), which has been incorporated into OpenCV and is now one of the most popular libraries for nearest neighbor matching.
Multi-dimensional virtual system introduced to enhance canonical sampling
Higo, Junichi; Kasahara, Kota; Nakamura, Haruki
2017-10-01
When an important process of a molecular system occurs via a combination of two or more rare events, which occur almost independently to one another, computational sampling for the important process is difficult. Here, to sample such a process effectively, we developed a new method, named the "multi-dimensional Virtual-system coupled Monte Carlo (multi-dimensional-VcMC)" method, where the system interacts with a virtual system expressed by two or more virtual coordinates. Each virtual coordinate controls sampling along a reaction coordinate. By setting multiple reaction coordinates to be related to the corresponding rare events, sampling of the important process can be enhanced. An advantage of multi-dimensional-VcMC is its simplicity: Namely, the conformation moves widely in the multi-dimensional reaction coordinate space without knowledge of canonical distribution functions of the system. To examine the effectiveness of the algorithm, we introduced a toy model where two molecules (receptor and its ligand) bind and unbind to each other. The receptor has a deep binding pocket, to which the ligand enters for binding. Furthermore, a gate is set at the entrance of the pocket, and the gate is usually closed. Thus, the molecular binding takes place via the two events: ligand approach to the pocket and gate opening. In two-dimensional (2D)-VcMC, the two molecules exhibited repeated binding and unbinding, and an equilibrated distribution was obtained as expected. A conventional canonical simulation, which was 200 times longer than 2D-VcMC, failed in sampling the binding/unbinding effectively. The current method is applicable to various biological systems.
Three-Dimensional Extension of a Digital Library Service System
Xiao, Long
2010-01-01
Purpose: The paper aims to provide an overall methodology and case study for the innovation and extension of a digital library, especially the service system. Design/methodology/approach: Based on the three-dimensional structure theory of the information service industry, this paper combines a comprehensive analysis with the practical experiences…
Second invariant for two-dimensional classical super systems
Indian Academy of Sciences (India)
Construction of superpotentials for two-dimensional classical super systems (for N. 2) is carried ... extensively used for the case of non-linear partial differential equation by various authors. [3,4–7,12 ..... found to be integrable just by accident.
Kondo effect in three-dimensional Dirac and Weyl systems
Mitchell, Andrew K.; Fritz, Lars
2015-01-01
Magnetic impurities in three-dimensional Dirac and Weyl systems are shown to exhibit a fascinatingly diverse range of Kondo physics, with distinctive experimental spectroscopic signatures. When the Fermi level is precisely at the Dirac point, Dirac semimetals are in fact unlikely candidates for a
Statistics of resonances in one-dimensional continuous systems
Indian Academy of Sciences (India)
Vol. 73, No. 3. — journal of. September 2009 physics pp. 565–572. Statistics of resonances in one-dimensional continuous systems. JOSHUA FEINBERG. Physics Department, University of Haifa at Oranim, Tivon 36006, Israel ..... relativistic quantum mechanics (Israel Program for Scientific Translations, Jerusalem,. 1969).
Three-dimensional computer models of electrospinning systems
Directory of Open Access Journals (Sweden)
Smółka Krzysztof
2017-12-01
Full Text Available Electrospinning is a very interesting method that allows the fabrication of continuous fibers with diameters down to a few nanometers. This paper presents an overview of electrospinning systems as well as their comparison using proposed three-dimensional parameterized numerical models. The presented solutions allow an analysis of the electric field distribution.
Patched Green's function techniques for two-dimensional systems
DEFF Research Database (Denmark)
Settnes, Mikkel; Power, Stephen; Lin, Jun
2015-01-01
We present a numerically efficient technique to evaluate the Green's function for extended two-dimensional systems without relying on periodic boundary conditions. Different regions of interest, or “patches,” are connected using self-energy terms which encode the information of the extended parts...
Light propagation in one-dimensional porous silicon complex systems
Oton, C.J.; Dal Negro, L.; Gaburro, Z.; Pavesi, L.; Johnson, P.J.; Lagendijk, Aart; Wiersma, D.S.
2003-01-01
We discuss the optical properties of one-dimensional complex dielectric systems, in particular the time-resolved transmission through thick porous silicon quasiperiodic multi-layers. Both in numerical calculations and experiments we find dramatic distortion effects, i.e. pulse stretching and
Equilibrium spherically curved two-dimensional Lennard-Jones systems
Voogd, J.M.; Sloot, P.M.A.; van Dantzig, R.
2005-01-01
To learn about basic aspects of nano-scale spherical molecular shells during their formation, spherically curved two-dimensional N-particle Lennard-Jones systems are simulated, studying curvature evolution paths at zero-temperature. For many N-values (N < 800) equilibrium configu- rations are traced
Generation and confirmation of a (100 × 100)-dimensional entangled quantum system
Krenn, Mario; Huber, Marcus; Fickler, Robert; Lapkiewicz, Radek; Ramelow, Sven; Zeilinger, Anton
2014-01-01
Entangled quantum systems have properties that have fundamentally overthrown the classical worldview. Increasing the complexity of entangled states by expanding their dimensionality allows the implementation of novel fundamental tests of nature, and moreover also enables genuinely new protocols for quantum information processing. Here we present the creation of a (100 × 100)-dimensional entangled quantum system, using spatial modes of photons. For its verification we develop a novel nonlinear criterion which infers entanglement dimensionality of a global state by using only information about its subspace correlations. This allows very practical experimental implementation as well as highly efficient extraction of entanglement dimensionality information. Applications in quantum cryptography and other protocols are very promising. PMID:24706902
Hasei, Tomohiro; Nakanishi, Haruka; Toda, Yumiko; Watanabe, Tetsushi
2012-08-31
3-Nitrobenzanthrone (3-NBA) is an extremely strong mutagen and carcinogen in rats inducing squamous cell carcinoma and adenocarcinoma. We developed a new sensitive analytical method, a two-dimensional HPLC system coupled with on-line reduction, to quantify non-fluorescent 3-NBA as fluorescent 3-aminobenzanthrone (3-ABA). The two-dimensional HPLC system consisted of reversed-phase HPLC and normal-phase HPLC, which were connected with a switch valve. 3-NBA was purified by reversed-phase HPLC and reduced to 3-ABA with a catalyst column, packed with alumina coated with platinum, in ethanol. An alcoholic solvent is necessary for reduction of 3-NBA, but 3-ABA is not fluorescent in the alcoholic solvent. Therefore, 3-ABA was separated from alcohol and impurities by normal-phase HPLC and detected with a fluorescence detector. Extracts from surface soil, airborne particles, classified airborne particles, and incinerator dust were applied to the two-dimensional HPLC system after clean-up with a silica gel column. 3-NBA, detected as 3-ABA, in the extracts was found as a single peak on the chromatograms without any interfering peaks. 3-NBA was detected in 4 incinerator dust samples (n=5). When classified airborne particles, that is, those 7.0 μm in size, were applied to the two-dimensional HPLC system after purified using a silica gel column, 3-NBA was detected in those particles with particle sizes NBA in airborne particles and the detection of 3-NBA in incinerator dust. Copyright © 2012 Elsevier B.V. All rights reserved.
Application of 3-dimensional CAD modeling system in nuclear plants
International Nuclear Information System (INIS)
Suwa, Minoru; Saito, Shunji; Nobuhiro, Minoru
1990-01-01
Until now, the preliminary work for mutual components in nuclear plant were readied by using plastic models. Recently with the development of computer graphic techniques, we can display the components on the graphics terminal, better than with use of plastic model and actual plants. The computer model can be handled, both telescopically and microscopically. A computer technique called 3-dimensional CAD modeling system was used as the preliminary work and design system. Through application of this system, database for nuclear plants was completed in arrangement step. The data can be used for piping design, stress analysis, shop production, testing and site construction, in all steps. In addition, the data can be used for various planning works, even after starting operation of plant. This paper describes the outline of the 3-dimensional CAD modeling system. (author)
A practical three-dimensional dosimetry system for radiation therapy
International Nuclear Information System (INIS)
Guo Pengyi; Adamovics, John; Oldham, Mark
2006-01-01
There is a pressing need for a practical three-dimensional (3D) dosimetry system, convenient for clinical use, and with the accuracy and resolution to enable comprehensive verification of the complex dose distributions typical of modern radiation therapy. Here we introduce a dosimetry system that can achieve this challenge, consisting of a radiochromic dosimeter (PRESAGE trade mark sign ) and a commercial optical computed tomography (CT) scanning system (OCTOPUS trade mark sign ). PRESAGE trade mark sign is a transparent material with compelling properties for dosimetry, including insensitivity of the dose response to atmospheric exposure, a solid texture negating the need for an external container (reducing edge effects), and amenability to accurate optical CT scanning due to radiochromic optical contrast as opposed to light-scattering contrast. An evaluation of the performance and viability of the PRESAGE trade mark sign /OCTOPUS, combination for routine clinical 3D dosimetry is presented. The performance of the two components (scanner and dosimeter) was investigated separately prior to full system test. The optical CT scanner has a spatial resolution of ≤1 mm, geometric accuracy within 1 mm, and high reconstruction linearity (with a R 2 value of 0.9979 and a standard error of estimation of ∼1%) relative to independent measurement. The overall performance of the PRESAGE trade mark sign /OCTOPUS system was evaluated with respect to a simple known 3D dose distribution, by comparison with GAFCHROMIC[reg] EBT film and the calculated dose from a commissioned planning system. The 'measured' dose distribution in a cylindrical PRESAGE trade mark sign dosimeter (16 cm diameter and 11 cm height) was determined by optical-CT, using a filtered backprojection reconstruction algorithm. A three-way Gamma map comparison (4% dose difference and 4 mm distance to agreement), between the PRESAGE trade mark sign , EBT and calculated dose distributions, showed full agreement in
Class prediction for high-dimensional class-imbalanced data
Directory of Open Access Journals (Sweden)
Lusa Lara
2010-10-01
Full Text Available Abstract Background The goal of class prediction studies is to develop rules to accurately predict the class membership of new samples. The rules are derived using the values of the variables available for each subject: the main characteristic of high-dimensional data is that the number of variables greatly exceeds the number of samples. Frequently the classifiers are developed using class-imbalanced data, i.e., data sets where the number of samples in each class is not equal. Standard classification methods used on class-imbalanced data often produce classifiers that do not accurately predict the minority class; the prediction is biased towards the majority class. In this paper we investigate if the high-dimensionality poses additional challenges when dealing with class-imbalanced prediction. We evaluate the performance of six types of classifiers on class-imbalanced data, using simulated data and a publicly available data set from a breast cancer gene-expression microarray study. We also investigate the effectiveness of some strategies that are available to overcome the effect of class imbalance. Results Our results show that the evaluated classifiers are highly sensitive to class imbalance and that variable selection introduces an additional bias towards classification into the majority class. Most new samples are assigned to the majority class from the training set, unless the difference between the classes is very large. As a consequence, the class-specific predictive accuracies differ considerably. When the class imbalance is not too severe, down-sizing and asymmetric bagging embedding variable selection work well, while over-sampling does not. Variable normalization can further worsen the performance of the classifiers. Conclusions Our results show that matching the prevalence of the classes in training and test set does not guarantee good performance of classifiers and that the problems related to classification with class
Energy Technology Data Exchange (ETDEWEB)
Vigil, M.B. [comp.
1995-03-01
This document provides a written compilation of the presentations and viewgraphs from the 1994 Conference on High Speed Computing given at the High Speed Computing Conference, {open_quotes}High Performance Systems,{close_quotes} held at Gleneden Beach, Oregon, on April 18 through 21, 1994.
Linear Port-Hamiltonian Systems on Infinite-dimensional Spaces
Jacob, Birgit
2012-01-01
This book provides a self-contained introduction to the theory of infinite-dimensional systems theory and its applications to port-Hamiltonian systems. The textbook starts with elementary known results, then progresses smoothly to advanced topics in current research. Many physical systems can be formulated using a Hamiltonian framework, leading to models described by ordinary or partial differential equations. For the purpose of control and for the interconnection of two or more Hamiltonian systems it is essential to take into account this interaction with the environment. This book is the fir
Two-dimensional computer simulation of high intensity proton beams
Lapostolle, Pierre M
1972-01-01
A computer program has been developed which simulates the two- dimensional transverse behaviour of a proton beam in a focusing channel. The model is represented by an assembly of a few thousand 'superparticles' acted upon by their own self-consistent electric field and an external focusing force. The evolution of the system is computed stepwise in time by successively solving Poisson's equation and Newton's law of motion. Fast Fourier transform techniques are used for speed in the solution of Poisson's equation, while extensive area weighting is utilized for the accurate evaluation of electric field components. A computer experiment has been performed on the CERN CDC 6600 computer to study the nonlinear behaviour of an intense beam in phase space, showing under certain circumstances a filamentation due to space charge and an apparent emittance growth. (14 refs).
Solitons in one-dimensional charge density wave systems
International Nuclear Information System (INIS)
Su, W.P.
1981-01-01
Theoretical research on one dimensional charge density wave systems is outlined. A simple coupled electron-photon Hamiltonian is studied including a Green's function approach, molecular dynamics, and Monte Carlo path integral method. As in superconductivity, the nonperturbative nature of the system makes the physical ground states and low energy excitations drastically different from the bare electrons and phonons. Solitons carry quantum numbers which are entirely different from those of the bare electrons and holes. The fractional charge character of the solitons is an example of this fact. Solitons are conveniently generated by doping material with donors or acceptors or by photon absorption. Most predictions of the theory are in qualitative agreement with experiments. The one dimensional charge density wave system has potential technological importance and a possible role in uncovering phenomena which might have implications in relativistic field theory and elementary particle physics
Sequentially generated states for the study of two dimensional systems
Energy Technology Data Exchange (ETDEWEB)
Banuls, Mari-Carmen; Cirac, J. Ignacio [Max-Planck-Institut fuer Quantenoptik, Garching (Germany); Perez-Garcia, David [Depto. Analisis Matematico, Universidad Complutense de Madrid (Spain); Wolf, Michael M. [Niels Bohr Institut, Copenhagen (Denmark); Verstraete, Frank [Fakultaet fuer Physik, Universitaet Wien (Austria)
2009-07-01
The family of Matrix Product States represents a powerful tool for the study of physical one-dimensional quantum many-body systems, such as spin chains. Besides, Matrix Product States can be defined as the family of quantum states that can be sequentially generated in a one-dimensional system. We have introduced a new family of states which extends this sequential definition to two dimensions. Like in Matrix Product States, expectation values of few body observables can be efficiently evaluated and, for the case of translationally invariant systems, the correlation functions decay exponentially with the distance. We show that such states are a subclass of Projected Entangled Pair States and investigate their suitability for approximating the ground states of local Hamiltonians.
Variance inflation in high dimensional Support Vector Machines
DEFF Research Database (Denmark)
Abrahamsen, Trine Julie; Hansen, Lars Kai
2013-01-01
Many important machine learning models, supervised and unsupervised, are based on simple Euclidean distance or orthogonal projection in a high dimensional feature space. When estimating such models from small training sets we face the problem that the span of the training data set input vectors...... the case of Support Vector Machines (SVMS) and we propose a non-parametric scheme to restore proper generalizability. We illustrate the algorithm and its ability to restore performance on a wide range of benchmark data sets....... follow a different probability law with less variance. While the problem and basic means to reconstruct and deflate are well understood in unsupervised learning, the case of supervised learning is less well understood. We here investigate the effect of variance inflation in supervised learning including...
Evaluating Clustering in Subspace Projections of High Dimensional Data
DEFF Research Database (Denmark)
Müller, Emmanuel; Günnemann, Stephan; Assent, Ira
2009-01-01
Clustering high dimensional data is an emerging research field. Subspace clustering or projected clustering group similar objects in subspaces, i.e. projections, of the full space. In the past decade, several clustering paradigms have been developed in parallel, without thorough evaluation...... and comparison between these paradigms on a common basis. Conclusive evaluation and comparison is challenged by three major issues. First, there is no ground truth that describes the "true" clusters in real world data. Second, a large variety of evaluation measures have been used that reflect different aspects...... of the clustering result. Finally, in typical publications authors have limited their analysis to their favored paradigm only, while paying other paradigms little or no attention. In this paper, we take a systematic approach to evaluate the major paradigms in a common framework. We study representative clustering...
Volumetric three-dimensional display system with rasterization hardware
Favalora, Gregg E.; Dorval, Rick K.; Hall, Deirdre M.; Giovinco, Michael; Napoli, Joshua
2001-06-01
An 8-color multiplanar volumetric display is being developed by Actuality Systems, Inc. It will be capable of utilizing an image volume greater than 90 million voxels, which we believe is the greatest utilizable voxel set of any volumetric display constructed to date. The display is designed to be used for molecular visualization, mechanical CAD, e-commerce, entertainment, and medical imaging. As such, it contains a new graphics processing architecture, novel high-performance line- drawing algorithms, and an API similar to a current standard. Three-dimensional imagery is created by projecting a series of 2-D bitmaps ('image slices') onto a diffuse screen that rotates at 600 rpm. Persistence of vision fuses the slices into a volume-filling 3-D image. A modified three-panel Texas Instruments projector provides slices at approximately 4 kHz, resulting in 8-color 3-D imagery comprised of roughly 200 radially-disposed slices which are updated at 20 Hz. Each slice has a resolution of 768 by 768 pixels, subtending 10 inches. An unusual off-axis projection scheme incorporating tilted rotating optics is used to maintain good focus across the projection screen. The display electronics includes a custom rasterization architecture which converts the user's 3- D geometry data into image slices, as well as 6 Gbits of DDR SDRAM graphics memory.
High-Dimensional Single-Photon Quantum Gates: Concepts and Experiments.
Babazadeh, Amin; Erhard, Manuel; Wang, Feiran; Malik, Mehul; Nouroozi, Rahman; Krenn, Mario; Zeilinger, Anton
2017-11-03
Transformations on quantum states form a basic building block of every quantum information system. From photonic polarization to two-level atoms, complete sets of quantum gates for a variety of qubit systems are well known. For multilevel quantum systems beyond qubits, the situation is more challenging. The orbital angular momentum modes of photons comprise one such high-dimensional system for which generation and measurement techniques are well studied. However, arbitrary transformations for such quantum states are not known. Here we experimentally demonstrate a four-dimensional generalization of the Pauli X gate and all of its integer powers on single photons carrying orbital angular momentum. Together with the well-known Z gate, this forms the first complete set of high-dimensional quantum gates implemented experimentally. The concept of the X gate is based on independent access to quantum states with different parities and can thus be generalized to other photonic degrees of freedom and potentially also to other quantum systems.
Three-dimensional computer aided design system for plant layout
International Nuclear Information System (INIS)
Yoshinaga, Toshiaki; Kiguchi, Takashi; Tokumasu, Shinji; Kumamoto, Kenjiro.
1986-01-01
The CAD system for three-dimensional plant layout planning, with which the layout of pipings, cable trays, air conditioning ducts and so on in nuclear power plants can be planned and designed effectively in a short period is reported. This system comprises the automatic routing system by storing the rich experience and know-how of designers in a computer as the knowledge, and deciding the layout automatically following the predetermined sequence by using these, the interactive layout system for reviewing the routing results from higher level and modifying to the optimum layout, the layout evaluation system for synthetically evaluating the layout from the viewpoint of the operability such as checkup and maintenance, and the data base system which enables these effective planning and design. In this report, the total constitution of this system and the technical features and effects of the individual subsystems are outlined. In this CAD system for three-dimensional plant layout planning, knowledge engineering, CAD/CAM, computer graphics and other latest technology were introduced, accordingly by applying this system to plant design, the design can be performed quickly, various case studies can be carried out at planning stage, and systematic and optimum layout planning becomes possible. (Kako, I.)
Reduced, three-dimensional, nonlinear equations for high-β plasmas including toroidal effects
International Nuclear Information System (INIS)
Schmalz, R.
1980-11-01
The resistive MHD equations for toroidal plasma configurations are reduced by expanding to the second order in epsilon, the inverse aspect ratio, allowing for high β = μsub(o)p/B 2 of order epsilon. The result is a closed system of nonlinear, three-dimensional equations where the fast magnetohydrodynamic time scale is eliminated. In particular, the equation for the toroidal velocity remains decoupled. (orig.)
Thermal conductivity in one-dimensional nonlinear systems
Politi, Antonio; Giardinà, Cristian; Livi, Roberto; Vassalli, Massimo
2000-03-01
Thermal conducitivity of one-dimensional nonlinear systems typically diverges in the thermodynamic limit, whenever the momentum is conserved (i.e. in the absence of interactions with an external substrate). Evidence comes from detailed studies of Fermi-Pasta-Ulam and diatomic Toda chains. Here, we discuss the first example of a one-dimensional system obeying Fourier law : a chain of coupled rotators. Numerical estimates of the thermal conductivity obtained by simulating a chain in contact with two thermal baths at different temperatures are found to be consistent with those ones based on linear response theory. The dynamics of the Fourier modes provides direct evidence of energy diffusion. The finiteness of the conductivity is traced back to the occurrence of phase-jumps. Our conclusions are confirmed by the analysis of two variants of the rotator model.
High-dimensional statistical inference: From vector to matrix
Zhang, Anru
Statistical inference for sparse signals or low-rank matrices in high-dimensional settings is of significant interest in a range of contemporary applications. It has attracted significant recent attention in many fields including statistics, applied mathematics and electrical engineering. In this thesis, we consider several problems in including sparse signal recovery (compressed sensing under restricted isometry) and low-rank matrix recovery (matrix recovery via rank-one projections and structured matrix completion). The first part of the thesis discusses compressed sensing and affine rank minimization in both noiseless and noisy cases and establishes sharp restricted isometry conditions for sparse signal and low-rank matrix recovery. The analysis relies on a key technical tool which represents points in a polytope by convex combinations of sparse vectors. The technique is elementary while leads to sharp results. It is shown that, in compressed sensing, delta kA 0, delta kA < 1/3 + epsilon, deltak A + thetak,kA < 1 + epsilon, or deltatkA< √(t - 1) / t + epsilon are not sufficient to guarantee the exact recovery of all k-sparse signals for large k. Similar result also holds for matrix recovery. In addition, the conditions delta kA<1/3, deltak A+ thetak,kA<1, delta tkA < √(t - 1)/t and deltarM<1/3, delta rM+ thetar,rM<1, delta trM< √(t - 1)/ t are also shown to be sufficient respectively for stable recovery of approximately sparse signals and low-rank matrices in the noisy case. For the second part of the thesis, we introduce a rank-one projection model for low-rank matrix recovery and propose a constrained nuclear norm minimization method for stable recovery of low-rank matrices in the noisy case. The procedure is adaptive to the rank and robust against small perturbations. Both upper and lower bounds for the estimation accuracy under the Frobenius norm loss are obtained. The proposed estimator is shown to be rate-optimal under certain conditions. The
Aspects of jamming in two-dimensional athermal frictionless systems.
Reichhardt, C; Reichhardt, C J Olson
2014-05-07
In this work we provide an overview of jamming transitions in two dimensional systems focusing on the limit of frictionless particle interactions in the absence of thermal fluctuations. We first discuss jamming in systems with short range repulsive interactions, where the onset of jamming occurs at a critical packing density and where certain quantities show a divergence indicative of critical behavior. We describe how aspects of the dynamics change as the jamming density is approached and how these dynamics can be explored using externally driven probes. Different particle shapes can produce jamming densities much lower than those observed for disk-shaped particles, and we show how jamming exhibits fragility for some shapes while for other shapes this is absent. Next we describe the effects of long range interactions and jamming behavior in systems such as charged colloids, vortices in type-II superconductors, and dislocations. We consider the effect of adding obstacles to frictionless jamming systems and discuss connections between this type of jamming and systems that exhibit depinning transitions. Finally, we discuss open questions such as whether the jamming transition in all these different systems can be described by the same or a small subset of universal behaviors, as well as future directions for studies of jamming transitions in two dimensional systems, such as jamming in self-driven or active matter systems.
The role of three-dimensional high-definition laparoscopic surgery for gynaecology.
Usta, Taner A; Gundogdu, Elif C
2015-08-01
This article reviews the potential benefits and disadvantages of new three-dimensional (3D) high-definition laparoscopic surgery for gynaecology. With the new-generation 3D high-definition laparoscopic vision systems (LVSs), operation time and learning period are reduced and procedural error margin is decreased. New-generation 3D high-definition LVSs enable to reduce operation time both for novice and experienced surgeons. Headache, eye fatigue or nausea reported with first-generation systems are not different than two-dimensional (2D) LVSs. The system's being more expensive, having the obligation to wear glasses, big and heavy camera probe in some of the devices are accounted for negative aspects of the system that need to be improved. Depth loss in tissues in 2D LVSs and associated adverse events can be eliminated with 3D high-definition LVSs. By virtue of faster learning curve, shorter operation time, reduced error margin and lack of side-effects reported by surgeons with first-generation systems, 3D LVSs seem to be a strong competition to classical laparoscopic imaging systems. Thanks to technological advancements, using lighter and smaller cameras and monitors without glasses is in the near future.
Nonlinear acoustic wave propagating in one-dimensional layered system
International Nuclear Information System (INIS)
Yun, Y.; Miao, G.Q.; Zhang, P.; Huang, K.; Wei, R.J.
2005-01-01
The propagation of finite-amplitude plane sound in one-dimensional layered media is studied by the extended method of transfer matrix formalism. For the periodic layered system consisting of two alternate types of liquid, the energy distribution and the phase vectors of the interface vibration are computed and analyzed. It is found that in the pass-band, the second harmonic of sound wave can propagate with the characteristic modulation
Approximation of High-Dimensional Rank One Tensors
Bachmayr, Markus
2013-11-12
Many real world problems are high-dimensional in that their solution is a function which depends on many variables or parameters. This presents a computational challenge since traditional numerical techniques are built on model classes for functions based solely on smoothness. It is known that the approximation of smoothness classes of functions suffers from the so-called \\'curse of dimensionality\\'. Avoiding this curse requires new model classes for real world functions that match applications. This has led to the introduction of notions such as sparsity, variable reduction, and reduced modeling. One theme that is particularly common is to assume a tensor structure for the target function. This paper investigates how well a rank one function f(x 1,...,x d)=f 1(x 1)⋯f d(x d), defined on Ω=[0,1]d can be captured through point queries. It is shown that such a rank one function with component functions f j in W∞ r([0,1]) can be captured (in L ∞) to accuracy O(C(d,r)N -r) from N well-chosen point evaluations. The constant C(d,r) scales like d dr. The queries in our algorithms have two ingredients, a set of points built on the results from discrepancy theory and a second adaptive set of queries dependent on the information drawn from the first set. Under the assumption that a point z∈Ω with nonvanishing f(z) is known, the accuracy improves to O(dN -r). © 2013 Springer Science+Business Media New York.
Design guidelines for high dimensional stability of CFRP optical bench
Desnoyers, Nichola; Boucher, Marc-André; Goyette, Philippe
2013-09-01
In carbon fiber reinforced plastic (CFRP) optomechanical structures, particularly when embodying reflective optics, angular stability is critical. Angular stability or warping stability is greatly affected by moisture absorption and thermal gradients. Unfortunately, it is impossible to achieve the perfect laminate and there will always be manufacturing errors in trying to reach a quasi-iso laminate. Some errors, such as those related to the angular position of each ply and the facesheet parallelism (for a bench) can be easily monitored in order to control the stability more adequately. This paper presents warping experiments and finite-element analyses (FEA) obtained from typical optomechanical sandwich structures. Experiments were done using a thermal vacuum chamber to cycle the structures from -40°C to 50°C. Moisture desorption tests were also performed for a number of specific configurations. The selected composite material for the study is the unidirectional prepreg from Tencate M55J/TC410. M55J is a high modulus fiber and TC410 is a new-generation cyanate ester designed for dimensionally stable optical benches. In the studied cases, the main contributors were found to be: the ply angular errors, laminate in-plane parallelism (between 0° ply direction of both facesheets), fiber volume fraction tolerance and joints. Final results show that some tested configurations demonstrated good warping stability. FEA and measurements are in good agreement despite the fact that some defects or fabrication errors remain unpredictable. Design guidelines to maximize the warping stability by taking into account the main dimensional stability contributors, the bench geometry and the optical mount interface are then proposed.
Approximation of High-Dimensional Rank One Tensors
Bachmayr, Markus; Dahmen, Wolfgang; DeVore, Ronald; Grasedyck, Lars
2013-01-01
Many real world problems are high-dimensional in that their solution is a function which depends on many variables or parameters. This presents a computational challenge since traditional numerical techniques are built on model classes for functions based solely on smoothness. It is known that the approximation of smoothness classes of functions suffers from the so-called 'curse of dimensionality'. Avoiding this curse requires new model classes for real world functions that match applications. This has led to the introduction of notions such as sparsity, variable reduction, and reduced modeling. One theme that is particularly common is to assume a tensor structure for the target function. This paper investigates how well a rank one function f(x 1,...,x d)=f 1(x 1)⋯f d(x d), defined on Ω=[0,1]d can be captured through point queries. It is shown that such a rank one function with component functions f j in W∞ r([0,1]) can be captured (in L ∞) to accuracy O(C(d,r)N -r) from N well-chosen point evaluations. The constant C(d,r) scales like d dr. The queries in our algorithms have two ingredients, a set of points built on the results from discrepancy theory and a second adaptive set of queries dependent on the information drawn from the first set. Under the assumption that a point z∈Ω with nonvanishing f(z) is known, the accuracy improves to O(dN -r). © 2013 Springer Science+Business Media New York.
Progress in high-dimensional percolation and random graphs
Heydenreich, Markus
2017-01-01
This text presents an engaging exposition of the active field of high-dimensional percolation that will likely provide an impetus for future work. With over 90 exercises designed to enhance the reader’s understanding of the material, as well as many open problems, the book is aimed at graduate students and researchers who wish to enter the world of this rich topic. The text may also be useful in advanced courses and seminars, as well as for reference and individual study. Part I, consisting of 3 chapters, presents a general introduction to percolation, stating the main results, defining the central objects, and proving its main properties. No prior knowledge of percolation is assumed. Part II, consisting of Chapters 4–9, discusses mean-field critical behavior by describing the two main techniques used, namely, differential inequalities and the lace expansion. In Parts I and II, all results are proved, making this the first self-contained text discussing high-dimensiona l percolation. Part III, consist...
Efficient Smoothed Concomitant Lasso Estimation for High Dimensional Regression
Ndiaye, Eugene; Fercoq, Olivier; Gramfort, Alexandre; Leclère, Vincent; Salmon, Joseph
2017-10-01
In high dimensional settings, sparse structures are crucial for efficiency, both in term of memory, computation and performance. It is customary to consider ℓ 1 penalty to enforce sparsity in such scenarios. Sparsity enforcing methods, the Lasso being a canonical example, are popular candidates to address high dimension. For efficiency, they rely on tuning a parameter trading data fitting versus sparsity. For the Lasso theory to hold this tuning parameter should be proportional to the noise level, yet the latter is often unknown in practice. A possible remedy is to jointly optimize over the regression parameter as well as over the noise level. This has been considered under several names in the literature: Scaled-Lasso, Square-root Lasso, Concomitant Lasso estimation for instance, and could be of interest for uncertainty quantification. In this work, after illustrating numerical difficulties for the Concomitant Lasso formulation, we propose a modification we coined Smoothed Concomitant Lasso, aimed at increasing numerical stability. We propose an efficient and accurate solver leading to a computational cost no more expensive than the one for the Lasso. We leverage on standard ingredients behind the success of fast Lasso solvers: a coordinate descent algorithm, combined with safe screening rules to achieve speed efficiency, by eliminating early irrelevant features.
International Nuclear Information System (INIS)
Martin, M.
1991-01-01
Industrial processes usually require electrical power. This power is used to drive motors, to heat materials, or in electrochemical processes. Often the power requirements of a plant require the electric power to be delivered at high voltage. In this paper high voltage is considered any voltage over 600 V. This voltage could be as high as 138,000 V for some very large facilities. The characteristics of this voltage and the enormous amounts of power being transmitted necessitate special safety considerations. Safety must be considered during the four activities associated with a high voltage electrical system. These activities are: Design; Installation; Operation; and Maintenance
A low dimensional dynamical system for the wall layer
Aubry, N.; Keefe, L. R.
1987-01-01
Low dimensional dynamical systems which model a fully developed turbulent wall layer were derived.The model is based on the optimally fast convergent proper orthogonal decomposition, or Karhunen-Loeve expansion. This decomposition provides a set of eigenfunctions which are derived from the autocorrelation tensor at zero time lag. Via Galerkin projection, low dimensional sets of ordinary differential equations in time, for the coefficients of the expansion, were derived from the Navier-Stokes equations. The energy loss to the unresolved modes was modeled by an eddy viscosity representation, analogous to Heisenberg's spectral model. A set of eigenfunctions and eigenvalues were obtained from direct numerical simulation of a plane channel at a Reynolds number of 6600, based on the mean centerline velocity and the channel width flow and compared with previous work done by Herzog. Using the new eigenvalues and eigenfunctions, a new ten dimensional set of ordinary differential equations were derived using five non-zero cross-stream Fourier modes with a periodic length of 377 wall units. The dynamical system was integrated for a range of the eddy viscosity prameter alpha. This work is encouraging.
Exactly integrable analogue of a one-dimensional gravitating system
International Nuclear Information System (INIS)
Miller, Bruce N.; Yawn, Kenneth R.; Maier, Bill
2005-01-01
Exchange symmetry in acceleration partitions the configuration space of an N particle one-dimensional gravitational system (OGS) into N! equivalent cells. We take advantage of the resulting small angular separation between the forces in neighboring cells to construct a related integrable version of the system that takes the form of a central force problem in N-1 dimensions. The properties of the latter, including the construction of trajectories and possible continuum limits, are developed. Dynamical simulation is employed to compare the two models. For some initial conditions, excellent agreement is observed
On the Zeeman Effect in highly excited atoms: 2. Three-dimensional case
International Nuclear Information System (INIS)
Baseia, B.; Medeiros e Silva Filho, J.
1984-01-01
A previous result, found in two-dimensional hydrogen-atoms, is extended to the three-dimensional case. A mapping of a four-dimensional space R 4 onto R 3 , that establishes an equivalence between Coulomb and harmonic potentials, is used to show that the exact solution of the Zeeman effect in highly excited atoms, cannot be reached. (Author) [pt
Bound states of Dipolar Bosons in One-dimensional Systems
DEFF Research Database (Denmark)
G. Volosniev, A.; R. Armstrong, J.; V. Fedorov, D.
2013-01-01
that in the weakly-coupled limit the inter-tube interaction is similar to a zero-range term with a suitable rescaled strength. This allows us to address the corresponding many-body physics of the system by constructing a model where bound chains with one molecule in each tube are the effective degrees of freedom......We consider one-dimensional tubes containing bosonic polar molecules. The long-range dipole-dipole interactions act both within a single tube and between different tubes. We consider arbitrary values of the externally aligned dipole moments with respect to the symmetry axis of the tubes. The few....... This model can be mapped onto one-dimensional Hamiltonians for which exact solutions are known....
Topologically protected states in one-dimensional systems
Fefferman, C L; Weinstein, M I
2017-01-01
The authors study a class of periodic Schrödinger operators, which in distinguished cases can be proved to have linear band-crossings or "Dirac points". They then show that the introduction of an "edge", via adiabatic modulation of these periodic potentials by a domain wall, results in the bifurcation of spatially localized "edge states". These bound states are associated with the topologically protected zero-energy mode of an asymptotic one-dimensional Dirac operator. The authors' model captures many aspects of the phenomenon of topologically protected edge states for two-dimensional bulk structures such as the honeycomb structure of graphene. The states the authors construct can be realized as highly robust TM-electromagnetic modes for a class of photonic waveguides with a phase-defect.
Three-dimensional micro electromechanical system piezoelectric ultrasound transducer
Hajati, Arman; Latev, Dimitre; Gardner, Deane; Hajati, Azadeh; Imai, Darren; Torrey, Marc; Schoeppler, Martin
2012-12-01
Here we present the design and experimental acoustic test data for an ultrasound transducer technology based on a combination of micromachined dome-shaped piezoelectric resonators arranged in a flexible architecture. Our high performance niobium-doped lead zirconate titanate film is implemented in three-dimensional dome-shaped structures, which form the basic resonating cells. Adjustable frequency response is realized by mixing these basic cells and modifying their dimensions by lithography. Improved characteristics such as high sensitivity, adjustable wide-bandwidth frequency response, low transmit voltage compatible with ordinary integrated circuitry, low electrical impedance well matched to coaxial cabling, and intrinsic acoustic impedance match to water are demonstrated.
Characterization of highly anisotropic three-dimensionally nanostructured surfaces
International Nuclear Information System (INIS)
Schmidt, Daniel
2014-01-01
Generalized ellipsometry, a non-destructive optical characterization technique, is employed to determine geometrical structure parameters and anisotropic dielectric properties of highly spatially coherent three-dimensionally nanostructured thin films grown by glancing angle deposition. The (piecewise) homogeneous biaxial layer model approach is discussed, which can be universally applied to model the optical response of sculptured thin films with different geometries and from diverse materials, and structural parameters as well as effective optical properties of the nanostructured thin films are obtained. Alternative model approaches for slanted columnar thin films, anisotropic effective medium approximations based on the Bruggeman formalism, are presented, which deliver results comparable to the homogeneous biaxial layer approach and in addition provide film constituent volume fraction parameters as well as depolarization or shape factors. Advantages of these ellipsometry models are discussed on the example of metal slanted columnar thin films, which have been conformally coated with a thin passivating oxide layer by atomic layer deposition. Furthermore, the application of an effective medium approximation approach to in-situ growth monitoring of this anisotropic thin film functionalization process is presented. It was found that structural parameters determined with the presented optical model equivalents for slanted columnar thin films agree very well with scanning electron microscope image estimates. - Highlights: • Summary of optical model strategies for sculptured thin films with arbitrary geometries • Application of the rigorous anisotropic Bruggeman effective medium applications • In-situ growth monitoring of atomic layer deposition on biaxial metal slanted columnar thin film
Effects of dependence in high-dimensional multiple testing problems
Directory of Open Access Journals (Sweden)
van de Wiel Mark A
2008-02-01
Full Text Available Abstract Background We consider effects of dependence among variables of high-dimensional data in multiple hypothesis testing problems, in particular the False Discovery Rate (FDR control procedures. Recent simulation studies consider only simple correlation structures among variables, which is hardly inspired by real data features. Our aim is to systematically study effects of several network features like sparsity and correlation strength by imposing dependence structures among variables using random correlation matrices. Results We study the robustness against dependence of several FDR procedures that are popular in microarray studies, such as Benjamin-Hochberg FDR, Storey's q-value, SAM and resampling based FDR procedures. False Non-discovery Rates and estimates of the number of null hypotheses are computed from those methods and compared. Our simulation study shows that methods such as SAM and the q-value do not adequately control the FDR to the level claimed under dependence conditions. On the other hand, the adaptive Benjamini-Hochberg procedure seems to be most robust while remaining conservative. Finally, the estimates of the number of true null hypotheses under various dependence conditions are variable. Conclusion We discuss a new method for efficient guided simulation of dependent data, which satisfy imposed network constraints as conditional independence structures. Our simulation set-up allows for a structural study of the effect of dependencies on multiple testing criterions and is useful for testing a potentially new method on π0 or FDR estimation in a dependency context.
Inference for High-dimensional Differential Correlation Matrices.
Cai, T Tony; Zhang, Anru
2016-01-01
Motivated by differential co-expression analysis in genomics, we consider in this paper estimation and testing of high-dimensional differential correlation matrices. An adaptive thresholding procedure is introduced and theoretical guarantees are given. Minimax rate of convergence is established and the proposed estimator is shown to be adaptively rate-optimal over collections of paired correlation matrices with approximately sparse differences. Simulation results show that the procedure significantly outperforms two other natural methods that are based on separate estimation of the individual correlation matrices. The procedure is also illustrated through an analysis of a breast cancer dataset, which provides evidence at the gene co-expression level that several genes, of which a subset has been previously verified, are associated with the breast cancer. Hypothesis testing on the differential correlation matrices is also considered. A test, which is particularly well suited for testing against sparse alternatives, is introduced. In addition, other related problems, including estimation of a single sparse correlation matrix, estimation of the differential covariance matrices, and estimation of the differential cross-correlation matrices, are also discussed.
Bayesian Subset Modeling for High-Dimensional Generalized Linear Models
Liang, Faming
2013-06-01
This article presents a new prior setting for high-dimensional generalized linear models, which leads to a Bayesian subset regression (BSR) with the maximum a posteriori model approximately equivalent to the minimum extended Bayesian information criterion model. The consistency of the resulting posterior is established under mild conditions. Further, a variable screening procedure is proposed based on the marginal inclusion probability, which shares the same properties of sure screening and consistency with the existing sure independence screening (SIS) and iterative sure independence screening (ISIS) procedures. However, since the proposed procedure makes use of joint information from all predictors, it generally outperforms SIS and ISIS in real applications. This article also makes extensive comparisons of BSR with the popular penalized likelihood methods, including Lasso, elastic net, SIS, and ISIS. The numerical results indicate that BSR can generally outperform the penalized likelihood methods. The models selected by BSR tend to be sparser and, more importantly, of higher prediction ability. In addition, the performance of the penalized likelihood methods tends to deteriorate as the number of predictors increases, while this is not significant for BSR. Supplementary materials for this article are available online. © 2013 American Statistical Association.
The literary uses of high-dimensional space
Directory of Open Access Journals (Sweden)
Ted Underwood
2015-12-01
Full Text Available Debates over “Big Data” shed more heat than light in the humanities, because the term ascribes new importance to statistical methods without explaining how those methods have changed. What we badly need instead is a conversation about the substantive innovations that have made statistical modeling useful for disciplines where, in the past, it truly wasn’t. These innovations are partly technical, but more fundamentally expressed in what Leo Breiman calls a new “culture” of statistical modeling. Where 20th-century methods often required humanists to squeeze our unstructured texts, sounds, or images into some special-purpose data model, new methods can handle unstructured evidence more directly by modeling it in a high-dimensional space. This opens a range of research opportunities that humanists have barely begun to discuss. To date, topic modeling has received most attention, but in the long run, supervised predictive models may be even more important. I sketch their potential by describing how Jordan Sellers and I have begun to model poetic distinction in the long 19th century—revealing an arc of gradual change much longer than received literary histories would lead us to expect.
Three-dimensional wedge filling in ordered and disordered systems
International Nuclear Information System (INIS)
Greenall, M J; Parry, A O; Romero-Enrique, J M
2004-01-01
We investigate interfacial structural and fluctuation effects occurring at continuous filling transitions in 3D wedge geometries. We show that fluctuation-induced wedge covariance relations that have been reported recently for 2D filling and wetting have mean-field or classical analogues that apply to higher-dimensional systems. Classical wedge covariance emerges from analysis of filling in shallow wedges based on a simple interfacial Hamiltonian model and is supported by detailed numerical investigations of filling within a more microscopic Landau-like density functional theory. Evidence is presented that classical wedge covariance is also obeyed for filling in more acute wedges in the asymptotic critical regime. For sufficiently short-ranged forces mean-field predictions for the filling critical exponents and covariance are destroyed by pseudo-one-dimensional interfacial fluctuations. We argue that in this filling fluctuation regime the critical exponents describing the divergence of length scales are related to values of the interfacial wandering exponent ζ(d) defined for planar interfaces in (bulk) two-dimensional (d = 2) and three-dimensional (d = 3) systems. For the interfacial height l w ∼ θ-α) -β w , with θ the contact angle and α the wedge tilt angle, we find β w = ζ(2)/2(1-ζ(3)). For pure systems (thermal disorder) we recover the known result β w = 1/4 predicted by interfacial Hamiltonian studies whilst for random-bond disorder we predict the universal critical exponent β ∼ even in the presence of dispersion forces. We revisit the transfer matrix theory of three-dimensional filling based on an effective interfacial Hamiltonian model and discuss the interplay between breather, tilt and torsional interfacial fluctuations. We show that the coupling of the modes allows the problem to be mapped onto a quantum mechanical problem as conjectured by previous authors. The form of the interfacial height probability distribution function predicted by
Three-dimensional true FISP for high-resolution imaging of the whole brain
International Nuclear Information System (INIS)
Schmitz, B.; Hagen, T.; Reith, W.
2003-01-01
While high-resolution T1-weighted sequences, such as three-dimensional magnetization-prepared rapid gradient-echo imaging, are widely available, there is a lack of an equivalent fast high-resolution sequence providing T2 contrast. Using fast high-performance gradient systems we show the feasibility of three-dimensional true fast imaging with steady-state precession (FISP) to fill this gap. We applied a three-dimensional true-FISP protocol with voxel sizes down to 0.5 x 0.5 x 0.5 mm and acquisition times of approximately 8 min on a 1.5-T Sonata (Siemens, Erlangen, Germany) magnetic resonance scanner. The sequence was included into routine brain imaging protocols for patients with cerebrospinal-fluid-related intracranial pathology. Images from 20 patients and 20 healthy volunteers were evaluated by two neuroradiologists with respect to diagnostic image quality and artifacts. All true-FISP scans showed excellent imaging quality free of artifacts in patients and volunteers. They were valuable for the assessment of anatomical and pathologic aspects of the included patients. High-resolution true-FISP imaging is a valuable adjunct for the exploration and neuronavigation of intracranial pathologies especially if cerebrospinal fluid is involved. (orig.)
Critical phenomena in quasi-two-dimensional vibrated granular systems.
Guzmán, Marcelo; Soto, Rodrigo
2018-01-01
The critical phenomena associated to the liquid-to-solid transition of quasi-two-dimensional vibrated granular systems is studied using molecular dynamics simulations of the inelastic hard sphere model. The critical properties are associated to the fourfold bond-orientational order parameter χ_{4}, which measures the level of square crystallization of the system. Previous experimental results have shown that the transition of χ_{4}, when varying the vibration amplitude, can be either discontinuous or continuous, for two different values of the height of the box. Exploring the amplitude-height phase space, a transition line is found, which can be either discontinuous or continuous, merging at a tricritical point and the continuous branch ends in an upper critical point. In the continuous transition branch, the critical properties are studied. The exponent associated to the amplitude of the order parameter is β=1/2, for various system sizes, in complete agreement with the experimental results. However, the fluctuations of χ_{4} do not show any critical behavior, probably due to crossover effects by the close presence of the tricritical point. Finally, in quasi-one-dimensional systems, the transition is only discontinuous, limited by one critical point, indicating that two is the lower dimension for having a tricritical point.
Incoherent control and entanglement for two-dimensional coupled systems
International Nuclear Information System (INIS)
Romano, Raffaele; D'Alessandro, Domenico
2006-01-01
We investigate accessibility and controllability of a quantum system S coupled to a quantum probe P, both described by two-dimensional Hilbert spaces, under the hypothesis that the external control affects only P. In this context accessibility and controllability properties describe to what extent it is possible to drive the state of the system S by acting on P and using the interaction between the two systems. We give necessary and sufficient conditions for these properties and we discuss the relation with the entangling capability of the interaction between S and P. In particular, we show that controllability can be expressed in terms of the SWAP and √(SWAP) operators acting on the composite system
Two-dimensional nuclear magnetic resonance of quadrupolar systems
Energy Technology Data Exchange (ETDEWEB)
Wang, Shuanhu [Univ. of California, Berkeley, CA (United States)
1997-09-01
This dissertation describes two-dimensional nuclear magnetic resonance theory and experiments which have been developed to study quadruples in the solid state. The technique of multiple-quantum magic-angle spinning (MQMAS) is extensively reviewed and expanded upon in this thesis. Specifically, MQMAS is first compared with another technique, dynamic-angle spinning (DAS). The similarity between the two techniques allows us to extend much of the DAS work to the MQMAS case. Application of MQMAS to a series of aluminum containing materials is then presented. The superior resolution enhancement through MQMAS is exploited to detect the five- and six-coordinated aluminum in many aluminosilicate glasses. Combining the MQMAS method with other experiments, such as HETCOR, greatly expands the possibility of the use of MQMAS to study a large range of problems and is demonstrated in Chapter 5. Finally, the technique switching-angle spinning (SAS) is applied to quadrupolar nuclei to fully characterize a quadrupolar spin system in which all of the 8 NMR parameters are accurately determined. This dissertation is meant to demonstrate that with the combination of two-dimensional NMR concepts and new advanced spinning technologies, a series of multiple-dimensional NMR techniques can be designed to allow a detailed study of quadrupolar nuclei in the solid state.
High-speed fan-beam reconstruction using direct two-dimensional Fourier transform method
International Nuclear Information System (INIS)
Niki, Noboru; Mizutani, Toshio; Takahashi, Yoshizo; Inouye, Tamon.
1984-01-01
Since the first development of X-ray computer tomography (CT), various efforts have been made to obtain high quality of high-speed image. However, the development of high resolution CT and the ultra-high speed CT to be applied to hearts is still desired. The X-ray beam scanning method was already changed from the parallel beam system to the fan-beam system in order to greatly shorten the scanning time. Also, the filtered back projection (DFBP) method has been employed to directly processing fan-beam projection data as reconstruction method. Although the two-dimensional Fourier transform (TFT) method significantly faster than FBP method was proposed, it has not been sufficiently examined for fan-beam projection data. Thus, the ITFT method was investigated, which first executes rebinning algorithm to convert the fan-beam projection data to the parallel beam projection data, thereafter, uses two-dimensional Fourier transform. By this method, although high speed is expected, the reconstructed images might be degraded due to the adoption of rebinning algorithm. Therefore, the effect of the interpolation error of rebinning algorithm on the reconstructed images has been analyzed theoretically, and finally, the result of the employment of spline interpolation which allows the acquisition of high quality images with less errors has been shown by the numerical and visual evaluation based on simulation and actual data. Computation time was reduced to 1/15 for the image matrix of 512 and to 1/30 for doubled matrix. (Wakatsuki, Y.)
Violating Bell inequalities maximally for two d-dimensional systems
International Nuclear Information System (INIS)
Chen Jingling; Wu Chunfeng; Oh, C. H.; Kwek, L. C.; Ge Molin
2006-01-01
We show the maximal violation of Bell inequalities for two d-dimensional systems by using the method of the Bell operator. The maximal violation corresponds to the maximal eigenvalue of the Bell operator matrix. The eigenvectors corresponding to these eigenvalues are described by asymmetric entangled states. We estimate the maximum value of the eigenvalue for large dimension. A family of elegant entangled states |Ψ> app that violate Bell inequality more strongly than the maximally entangled state but are somewhat close to these eigenvectors is presented. These approximate states can potentially be useful for quantum cryptography as well as many other important fields of quantum information
Wave dispersion relations in two-dimensional Yukawa systems
International Nuclear Information System (INIS)
Liu Yanhong; Liu Bin; Chen Yanping; Yang Size; Wang Long; Wang Xiaogang
2003-01-01
Collective modes in a two-dimensional Yukawa system are investigated by molecular dynamics simulation in a wide range of coupling parameter Γ and screening strength κ. The dispersion relations and sound speeds of the transverse and longitudinal waves obtained for hexagonal lattice are in agreement with the theoretical results. The negative dispersion of the longitudinal wave is demonstrated. Frequency gaps are found on the dispersion curves of the transverse wave due to scattering of the waves on lattice defects for proper values of Γ. The common frequency of transverse and longitudinal waves drops dramatically with the increasing screening strength κ
Quality and efficiency in high dimensional Nearest neighbor search
Tao, Yufei; Yi, Ke; Sheng, Cheng; Kalnis, Panos
2009-01-01
Nearest neighbor (NN) search in high dimensional space is an important problem in many applications. Ideally, a practical solution (i) should be implementable in a relational database, and (ii) its query cost should grow sub-linearly with the dataset size, regardless of the data and query distributions. Despite the bulk of NN literature, no solution fulfills both requirements, except locality sensitive hashing (LSH). The existing LSH implementations are either rigorous or adhoc. Rigorous-LSH ensures good quality of query results, but requires expensive space and query cost. Although adhoc-LSH is more efficient, it abandons quality control, i.e., the neighbor it outputs can be arbitrarily bad. As a result, currently no method is able to ensure both quality and efficiency simultaneously in practice. Motivated by this, we propose a new access method called the locality sensitive B-tree (LSB-tree) that enables fast highdimensional NN search with excellent quality. The combination of several LSB-trees leads to a structure called the LSB-forest that ensures the same result quality as rigorous-LSH, but reduces its space and query cost dramatically. The LSB-forest also outperforms adhoc-LSH, even though the latter has no quality guarantee. Besides its appealing theoretical properties, the LSB-tree itself also serves as an effective index that consumes linear space, and supports efficient updates. Our extensive experiments confirm that the LSB-tree is faster than (i) the state of the art of exact NN search by two orders of magnitude, and (ii) the best (linear-space) method of approximate retrieval by an order of magnitude, and at the same time, returns neighbors with much better quality. © 2009 ACM.
Shape synchronization control for three-dimensional chaotic systems
International Nuclear Information System (INIS)
Huang, Yuanyuan; Wang, Yinhe; Chen, Haoguang; Zhang, Siying
2016-01-01
This paper aims to the three-dimensional continuous chaotic system and shape of the chaotic attractor by utilizing the basic theory of plane curves in classical differential geometry, the continuous controller is synthesized for the master–slave synchronization in shape. This means that the slave system can possess the same shape of state trajectory with the master system via the continuous controller. The continuous controller is composed of three sub-controllers, which respectively correspond to the master–slave synchronization in shape for the three projective curves of the chaotic attractor onto the three coordinate planes. Moreover, the proposed shape synchronization technique as well as application of control scheme to secure communication is also demonstrated in this paper, where numerical simulation results show the proposed control method works well.
A three-dimensional computerized isometric strength measurement system.
Black, Nancy L; Das, Biman
2007-05-01
The three-dimensional Computerized Isometric Strength Measurement System (CISMS) reliably and accurately measures isometric pull and push strengths in work spaces of paraplegic populations while anticipating comparative studies with other populations. The main elements of the system were: an extendable arm, a vertical supporting track, a rotating platform, a force transducer, stability sensors and a computerized data collection interface. The CISMS with minor modification was successfully used to measure isometric push-up and pull-down strengths of paraplegics and isometric push, pull, push-up and pull-down strength in work spaces for seated and standing able-bodied populations. The instrument has satisfied criteria of versatility, safety and comfort, ease of operation, and durability. Results are accurate within 2N for aligned forces. Costing approximately $1,500 (US) including computer, the system is affordable and accurate for aligned isometric strength measurements.
DEFF Research Database (Denmark)
Fergo, Charlotte; Burcharth, Jakob; Pommergaard, Hans-Christian
2017-01-01
BACKGROUND: This systematic review investigates newer generation 3-dimensional (3D) laparoscopy vs 2-dimensional (2D) laparoscopy in terms of error rating, performance time, and subjective assessment as early comparisons have shown contradictory results due to technological shortcomings. DATA...... Central Register of Controlled Trials database. CONCLUSIONS: Of 643 articles, 13 RCTs were included, of which 2 were clinical trials. Nine of 13 trials (69%) and 10 of 13 trials (77%) found a significant reduction in performance time and error, respectively, with the use of 3D-laparoscopy. Overall, 3D......-laparoscopy was found to be superior or equal to 2D-laparoscopy. All trials featuring subjective evaluation found a superiority of 3D-laparoscopy. More clinical RCTs are still awaited for the convincing results to be reproduced....
Using High-Dimensional Image Models to Perform Highly Undetectable Steganography
Pevný, Tomáš; Filler, Tomáš; Bas, Patrick
This paper presents a complete methodology for designing practical and highly-undetectable stegosystems for real digital media. The main design principle is to minimize a suitably-defined distortion by means of efficient coding algorithm. The distortion is defined as a weighted difference of extended state-of-the-art feature vectors already used in steganalysis. This allows us to "preserve" the model used by steganalyst and thus be undetectable even for large payloads. This framework can be efficiently implemented even when the dimensionality of the feature set used by the embedder is larger than 107. The high dimensional model is necessary to avoid known security weaknesses. Although high-dimensional models might be problem in steganalysis, we explain, why they are acceptable in steganography. As an example, we introduce HUGO, a new embedding algorithm for spatial-domain digital images and we contrast its performance with LSB matching. On the BOWS2 image database and in contrast with LSB matching, HUGO allows the embedder to hide 7× longer message with the same level of security level.
Directory of Open Access Journals (Sweden)
D. A. Fetisov
2015-01-01
Full Text Available The controllability conditions are well known if we speak about linear stationary systems: a linear stationary system is controllable if and only if the dimension of the state vector is equal to the rank of the controllability matrix. The concept of the controllability matrix is extended to affine systems, but relations between affine systems controllability and properties of this matrix are more complicated. Various controllability conditions are set for affine systems, but they deal as usual either with systems of some special form or with controllability in some small neighborhood of the concerned point. An affine system is known to be controllable if the system is equivalent to a system of a canonical form, which is defined and regular in the whole space of states. In this case, the system is said to be feedback linearizable in the space of states. However there are examples, which illustrate that a system can be controllable even if it is not feedback linearizable in any open subset in the space of states. In this article we deal with such systems.Affine systems with two-dimensional control are considered. The system in question is assumed to be equivalent to a system of a quasicanonical form with two-dimensional zero dynamics which is defined and regular in the whole space of states. Therefore the controllability of the original system is equivalent to the controllability of the received system of a quasicanonical form. In this article the sufficient condition for an available solution of the terminal problem is proven for systems of a quasicanonical form with two-dimensional control and two-dimensional zero dynamics. The condition is valid in the case of an arbitrary time interval and arbitrary initial and finite states of the system. Therefore the controllability condition is set for systems of a quasicanonical form with two-dimensional control and two-dimensional zero dynamics. An example is given which illustrates how the proved
An Unbiased Distance-based Outlier Detection Approach for High-dimensional Data
DEFF Research Database (Denmark)
Nguyen, Hoang Vu; Gopalkrishnan, Vivekanand; Assent, Ira
2011-01-01
than a global property. Different from existing approaches, it is not grid-based and dimensionality unbiased. Thus, its performance is impervious to grid resolution as well as the curse of dimensionality. In addition, our approach ranks the outliers, allowing users to select the number of desired...... outliers, thus mitigating the issue of high false alarm rate. Extensive empirical studies on real datasets show that our approach efficiently and effectively detects outliers, even in high-dimensional spaces....
Dimensionality analysis of multiparticle production at high energies
International Nuclear Information System (INIS)
Chilingaryan, A.A.
1989-01-01
An algorithm of analysis of multiparticle final states is offered. By the Renyi dimensionalities, which were calculated according to experimental data, though it were hadron distribution over the rapidity intervals or particle distribution in an N-dimensional momentum space, we can judge about the degree of correlation of particles, separate the momentum space projections and areas where the probability measure singularities are observed. The method is tested in a series of calculations with samples of fractal object points and with samples obtained by means of different generators of pseudo- and quasi-random numbers. 27 refs.; 11 figs
Development of a three-dimensional radiation dosimetry system
International Nuclear Information System (INIS)
Bero, M.A.
2001-12-01
The direct non-destructive measurement of the radiation absorbed dose in three dimensions is considered to be technically difficult. Accurate determination of the spatial distribution of absorbed dose plays an important role in many applications particularly in medicine. In radiotherapy computer calculations are frequently used to estimate three-dimensional dose distributions in complex geometry, hence a practical dosimetry system able to provide three-dimensional (3-D) integrated measurements is highly desirable for verifying such dose predictions. Magnetic Resonance Imaging (MRI) has been used to visualise 3-D dose distributions, inside two different detector materials, namely the ferrous sulphate gel (Fricke gel) and the polymer gel system. Each of these procedures has its own drawbacks and limitations, and this research project sought to find improvements and alternatives to overcome these problems. Work on the Fricke gel led to an improved preparation procedure employing gelatin gel whose lower melting point reduces the possibility of dissolved oxygen loss. The role of each component was clarified which led to the omission of all unnecessary chemicals such as the sodium chloride and benzoic acid. Initially MRI was the only 3-D readout technique available, however simple relaxometry was used to characterise the detector quantitatively with each modification before employing an MRI scanner to obtain images. Optimisation of the active constituents saves time and effort, and minimises the cost of equipment as well as materials. A serious drawback of the Fricke gel is ion diffusion, which causes blurring of the recorded spatial distribution and much effort was given to attempts to reduce this. However it was concluded that it is possible to slow down ion diffusion but at the cost of detector sensitivity. Therefore the best way of dealing with this problem is by introducing a fast readout technique so that the dose distribution can be recorded before serious
Energy Current Cumulants in One-Dimensional Systems in Equilibrium
Dhar, Abhishek; Saito, Keiji; Roy, Anjan
2018-06-01
A recent theory based on fluctuating hydrodynamics predicts that one-dimensional interacting systems with particle, momentum, and energy conservation exhibit anomalous transport that falls into two main universality classes. The classification is based on behavior of equilibrium dynamical correlations of the conserved quantities. One class is characterized by sound modes with Kardar-Parisi-Zhang scaling, while the second class has diffusive sound modes. The heat mode follows Lévy statistics, with different exponents for the two classes. Here we consider heat current fluctuations in two specific systems, which are expected to be in the above two universality classes, namely, a hard particle gas with Hamiltonian dynamics and a harmonic chain with momentum conserving stochastic dynamics. Numerical simulations show completely different system-size dependence of current cumulants in these two systems. We explain this numerical observation using a phenomenological model of Lévy walkers with inputs from fluctuating hydrodynamics. This consistently explains the system-size dependence of heat current fluctuations. For the latter system, we derive the cumulant-generating function from a more microscopic theory, which also gives the same system-size dependence of cumulants.
Muon studies of low-dimensional solid state systems
International Nuclear Information System (INIS)
Jestaedt, T.
1999-04-01
This thesis concerns the use of the technique of μSR, an abbreviation which stands for three separate types of experiments: muon spin rotation, muon spin relaxation and muon spin resonance. The experiments presented here were performed on beamlines at the ISIS facility at the Rutherford Appleton Laboratory (UK) and at the Paul Scherrer Institut (Villigen, Switzerland). The systems studied are linked by the common theme of reduced dimensionality. Results of μSR measurements on La 2-x Sr x NiO 4+δ (nickelates) are presented. In these systems the lattice constants are much smaller in two of the dimensions as compared to the third, leading to two dimensional magnetism. Earlier experiments using techniques other than μSR concentrated mainly on materials with x = 0 and δ ≠ 0. The work that I describe on La 2-x Sr x NiO 4+δ shows that, there are interesting magnetic features as a function of strontium doping, and the details of this dependence are examined. In each of the samples oscillations of the muon spin polarization were observed below a sample dependent temperature, showing that low temperature magnetic order occurs. μSR is also used to study Sr 2 LnMn 2 O 7 (the Ruddlesden- Popper phases), where Ln are various ions of the lanthanide series. These manganates have a layered structure, leading to a reduced dimensionality as compared to the related perovskite compounds of the MnO 3 series. Like the doped MnO 3 compounds, some of the Ruddlesden-Popper phases exhibit colossal magnetoresistance (CMR), all effect which initially stirred interest in the MnO 3 systems. In contrast to the MnO 3 systems, the relevant Mn 2 O 7 materials show this CMR effect over an extended temperature range. The μSR work is consistent with the existence of magnetic clusters in some of the Mn 2 O 7 materials and these clusters appear to be associated with the observation of CMR. The compound CaV 4 O 9 is the first known two-dimensional compound to exhibit a spin-gap and the effects
Spin precession in inversion-asymmetric two-dimensional systems
International Nuclear Information System (INIS)
Liu, M.-H.; Chang, C.-R.
2006-01-01
We present a theoretical method to calculate the expectation value of spin in an inversion-asymmetric two-dimensional (2D) system with respect to an arbitrarily spin-polarized electron state, injected via an ideal point contact. The 2D system is confined in a [0 0 1]-grown quantum well, where both the Rashba and the Dresselhaus spin-orbit couplings are taken into account. The obtained analytical results allow more concrete description of the spatial behaviors of the spin precession caused individually by the Rashba and the Dresselhaus terms. Applying the calculation on the Datta-Das spin-FET, whose original design considers only the Rashba effect inside the channel, we investigate the possible influence due to the Dresselhaus spin-orbit coupling. Concluded solution is the choice of ±[1±10], in particular [1 1 0], as the channel direction
A Three-Dimensional Cooperative Guidance Law of Multimissile System
Directory of Open Access Journals (Sweden)
Xing Wei
2015-01-01
Full Text Available In order to conduct saturation attacks on a static target, the cooperative guidance problem of multimissile system is researched. A three-dimensional guidance model is built using vector calculation and the classic proportional navigation guidance (PNG law is extended to three dimensions. Based on this guidance law, a distributed cooperative guidance strategy is proposed and a consensus protocol is designed to coordinate the time-to-go commands of all missiles. Then an expert system, which contains two extreme learning machines (ELM, is developed to regulate the local proportional coefficient of each missile according to the command. All missiles can arrive at the target simultaneously under the assumption that the multimissile network is connected. A simulation scenario is given to demonstrate the validity of the proposed method.
Quantum key distribution for composite dimensional finite systems
Shalaby, Mohamed; Kamal, Yasser
2017-06-01
The application of quantum mechanics contributes to the field of cryptography with very important advantage as it offers a mechanism for detecting the eavesdropper. The pioneering work of quantum key distribution uses mutually unbiased bases (MUBs) to prepare and measure qubits (or qudits). Weak mutually unbiased bases (WMUBs) have weaker properties than MUBs properties, however, unlike MUBs, a complete set of WMUBs can be constructed for systems with composite dimensions. In this paper, we study the use of weak mutually unbiased bases (WMUBs) in quantum key distribution for composite dimensional finite systems. We prove that the security analysis of using a complete set of WMUBs to prepare and measure the quantum states in the generalized BB84 protocol, gives better results than using the maximum number of MUBs that can be constructed, when they are analyzed against the intercept and resend attack.
Magnon damping in two-dimensional Heisenberg ferromagnetic system
International Nuclear Information System (INIS)
Cheng, T.-M.; Li Lin; Ze Xianyu
2006-01-01
A magnon-phonon interaction model is set up for a two-dimensional insulating ferromagnetic system. By using Matsubara function theory we have studied the magnon damping -I m Σ* (1) (k->) and calculated the magnon damping -I m Σ* (1) (k->) curve on the main symmetric point and line in the Brillouin zone for various parameters in the system. It is concluded that at the boundary of Brillouin zone there is a strong magnon damping. However, the magnon damping is very weak on the zone of small wave vector and the magnon damping reaches maximal value at very low temperature. The contributions of longitudinal phonon and transverse phonon on the magnon damping are compared and the influences of various parameters are also discussed
High-efficiency one-dimensional atom localization via two parallel standing-wave fields
International Nuclear Information System (INIS)
Wang, Zhiping; Wu, Xuqiang; Lu, Liang; Yu, Benli
2014-01-01
We present a new scheme of high-efficiency one-dimensional (1D) atom localization via measurement of upper state population or the probe absorption in a four-level N-type atomic system. By applying two classical standing-wave fields, the localization peak position and number, as well as the conditional position probability, can be easily controlled by the system parameters, and the sub-half-wavelength atom localization is also observed. More importantly, there is 100% detecting probability of the atom in the subwavelength domain when the corresponding conditions are satisfied. The proposed scheme may open up a promising way to achieve high-precision and high-efficiency 1D atom localization. (paper)
On the partition function of d+1 dimensional kink-bearing systems
International Nuclear Information System (INIS)
Radosz, A.; Salejda, W.
1987-01-01
It is suggested that the problem of finding a partition function of d+1 dimensional kink-bearing system in the classical approximation may be formulated as an eigenvalue problem of an appropriate d dimensional quantum
Matrix correlations for high-dimensional data: The modified RV-coefficient
Smilde, A.K.; Kiers, H.A.L.; Bijlsma, S.; Rubingh, C.M.; Erk, M.J. van
2009-01-01
Motivation: Modern functional genomics generates high-dimensional datasets. It is often convenient to have a single simple number characterizing the relationship between pairs of such high-dimensional datasets in a comprehensive way. Matrix correlations are such numbers and are appealing since they
On-chip generation of high-dimensional entangled quantum states and their coherent control.
Kues, Michael; Reimer, Christian; Roztocki, Piotr; Cortés, Luis Romero; Sciara, Stefania; Wetzel, Benjamin; Zhang, Yanbing; Cino, Alfonso; Chu, Sai T; Little, Brent E; Moss, David J; Caspani, Lucia; Azaña, José; Morandotti, Roberto
2017-06-28
Optical quantum states based on entangled photons are essential for solving questions in fundamental physics and are at the heart of quantum information science. Specifically, the realization of high-dimensional states (D-level quantum systems, that is, qudits, with D > 2) and their control are necessary for fundamental investigations of quantum mechanics, for increasing the sensitivity of quantum imaging schemes, for improving the robustness and key rate of quantum communication protocols, for enabling a richer variety of quantum simulations, and for achieving more efficient and error-tolerant quantum computation. Integrated photonics has recently become a leading platform for the compact, cost-efficient, and stable generation and processing of non-classical optical states. However, so far, integrated entangled quantum sources have been limited to qubits (D = 2). Here we demonstrate on-chip generation of entangled qudit states, where the photons are created in a coherent superposition of multiple high-purity frequency modes. In particular, we confirm the realization of a quantum system with at least one hundred dimensions, formed by two entangled qudits with D = 10. Furthermore, using state-of-the-art, yet off-the-shelf telecommunications components, we introduce a coherent manipulation platform with which to control frequency-entangled states, capable of performing deterministic high-dimensional gate operations. We validate this platform by measuring Bell inequality violations and performing quantum state tomography. Our work enables the generation and processing of high-dimensional quantum states in a single spatial mode.
International Nuclear Information System (INIS)
Nowak, S.; Orefice, A.
1994-01-01
In today's high frequency systems employed for plasma diagnostics, power heating, and current drive the behavior of the wave beams is appreciably affected by the self-diffraction phenomena due to their narrow collimation. In the present article the three-dimensional propagation of Gaussian beams in inhomogeneous and anisotropic media is analyzed, starting from a properly formulated dispersion relation. Particular attention is paid, in the case of electromagnetic electron cyclotron (EC) waves, to the toroidal geometry characterizing tokamak plasmas, to the power density evolution on the advancing wave fronts, and to the absorption features occurring when a beam crosses an EC resonant layer
Three-dimensional modeler for animated images display system
International Nuclear Information System (INIS)
Boubekeur, Rania
1987-01-01
The mv3d software allows the modeling and display of three dimensional objects in interpretative mode with animation possibility in real time. This system is intended for a graphical extension of a FORTH interpreter (implemented by CEA/IRDI/D.LETI/DEIN) in order to control a specific hardware (3.D card designed and implemented by DEIN) allowing the generation of three dimensional objects. The object description is carried out with a specific graphical language integrated in the FORTH interpreter. Objects are modeled using elementary solids called basic forms (cube, cone, cylinder...) assembled with classical geometric transformations (rotation, translation and scaling). These basic forms are approximated by plane polygonal facets further divided in triangles. Coordinates of the summits of triangles constitute the geometrical data. These are sent to the 3.D. card for processing and display. Performed processing are: geometrical transformations on display, hidden surface elimination, shading and clipping. The mv3d software is not an entire modeler but a simple, modular and extensible tool, to which other specific functions may be easily added such as: robots motion, collisions... (author) [fr
Growth and electronic properties of two-dimensional systems on (110) oriented GaAs
Energy Technology Data Exchange (ETDEWEB)
Fischer, F.
2005-07-01
As the only non-polar plane the (110) surface has a unique role in GaAs. Together with Silicon as a dopant it is an important substrate orientation for the growth of n-type or p-type heterostructures. As a consequence, this thesis will concentrate on growth and research on that surface. In the course of this work we were able to realize two-dimensional electron systems with the highest mobilities reported so far on this orientation. Therefore, we review the necessary growth conditions and the accompanying molecular process. The two-dimensional electron systems allowed the study of a new, intriguing transport anisotropy not explained by current theory. Moreover, we were the first growing a two-dimensional hole gas on (110) GaAs with Si as dopant. For this purpose we invented a new growth modulation technique necessary to retrieve high mobility systems. In addition, we discovered and studied the metal-insulator transition in thin bulk p-type layers on (110) GaAs. Besides we investigated the activation process related to the conduction in the valence band and a parallelly conducting hopping band. The new two-dimensional hole gases revealed interesting physics. We studied the zero B-field spin splitting in these systems and compared it with the known theory. Furthermore, we investigated the anisotropy of the mobility. As opposed to the expectations we observed a strong persistent photoconductivity in our samples. Landau levels for two dimensional hole systems are non-linear and can show anticrossings. For the first time we were able to resolve anticrossings in a transport experiment and study the corresponding activation process. Finally, we compared these striking results with theoretical calculations. (orig.)
Three-dimensional alginate spheroid culture system of murine osteosarcoma.
Akeda, Koji; Nishimura, Akinobu; Satonaka, Haruhiko; Shintani, Ken; Kusuzaki, Katsuyuki; Matsumine, Akihiko; Kasai, Yuichi; Masuda, Koichi; Uchida, Atsumasa
2009-11-01
Osteosarcoma (OS) is the most common primary malignant tumor of the bone and often forms pulmonary metastases, which are the most important prognostic factor. For further elucidation of the mechanism underlying the progression and metastasis of human OS, a culture system mimicking the microenvironment of the tumor in vivo is needed. We report a novel three-dimensional (3D) alginate spheroid culture system of murine osteosarcoma. Two different metastatic clones, the parental Dunn and its derivative line LM8, which has a higher metastatic potential to the lungs, were encapsulated in alginate beads to develop the 3D culture system. The beads containing murine OS cells were also transplanted into mice to determine their metastatic potential in vivo. In this culture system, murine OS cells encapsulated in alginate beads were able to grow in a 3D structure with cells detaching from the alginate environment. The number of detaching cells was higher in the LM8 cell line than the Dunn cell line. In the in vivo alginate bead transplantation model, the rate of pulmonary metastasis was higher with LM8 cells compared with that of Dunn cells. The cell characteristics and kinetics in this culture system closely reflect the original malignant potential of the cells in vivo.
High-resolution coherent three-dimensional spectroscopy of Br2.
Chen, Peter C; Wells, Thresa A; Strangfeld, Benjamin R
2013-07-25
In the past, high-resolution spectroscopy has been limited to small, simple molecules that yield relatively uncongested spectra. Larger and more complex molecules have a higher density of peaks and are susceptible to complications (e.g., effects from conical intersections) that can obscure the patterns needed to resolve and assign peaks. Recently, high-resolution coherent two-dimensional (2D) spectroscopy has been used to resolve and sort peaks into easily identifiable patterns for molecules where pattern-recognition has been difficult. For very highly congested spectra, however, the ability to resolve peaks using coherent 2D spectroscopy is limited by the bandwidth of instrumentation. In this article, we introduce and investigate high-resolution coherent three-dimensional spectroscopy (HRC3D) as a method for dealing with heavily congested systems. The resulting patterns are unlike those in high-resolution coherent 2D spectra. Analysis of HRC3D spectra could provide a means for exploring the spectroscopy of large and complex molecules that have previously been considered too difficult to study.
Dimensional consistency achieved in high-performance synchronizing hubs
International Nuclear Information System (INIS)
Garcia, P.; Campos, M.; Torralba, M.
2013-01-01
The tolerances of parts produced for the automotive industry are so tight that any small process variation may mean that the product does not fulfill them. As dimensional tolerances decrease, the material properties of parts are expected to be improved. Depending on the dimensional and material requirements of a part, different production routes are available to find robust processes, minimizing cost and maximizing process capability. Dimensional tolerances have been reduced in recent years, and as a result, the double pressing-double sintering production via ( 2 P2S ) has again become an accurate way to meet these increasingly narrow tolerances. In this paper, it is shown that the process parameters of the first sintering have great influence on the following production steps and the dimensions of the final parts. The roles of factors other than density and the second sintering process in defining the final dimensions of product are probed. All trials were done in a production line that produces synchronizer hubs for manual transmissions, allowing the maintenance of stable conditions and control of those parameters that are relevant for the product and process. (Author) 21 refs.
One- and zero-dimensional electron systems over liquid helium (Review article)
Kovdrya, Y Z
2003-01-01
Experimental and theoretical investigations of one-dimensional and zero-dimensional electron systems near the liquid helium surface are surveyed. The properties of electron states over the plane surface of liquid helium including thin layers of helium are considered. The methods of realization of one- and zero-dimensional electron systems are discussed, and the results of experimental and theoretical investigations of their properties are given. The experiments with localization processes in a quasi-one-dimensional electron systems on liquid helium are described. The collective effects in one-dimensional and quasi-one-dimensional electron systems are considered, and the point of possible application of low-dimensional electron systems on liquid helium in electron devices and quantum computers is discussed.
Two-dimensional impurity transport calculations for a high recycling divertor
International Nuclear Information System (INIS)
Brooks, J.N.
1986-04-01
Two dimensional analysis of impurity transport in a high recycling divertor shows asymmetric particle fluxes to the divertor plate, low helium pumping efficiency, and high scrapeoff zone shielding for sputtered impurities
Predicting the bounds of large chaotic systems using low-dimensional manifolds.
Directory of Open Access Journals (Sweden)
Asger M Haugaard
Full Text Available Predicting extrema of chaotic systems in high-dimensional phase space remains a challenge. Methods, which give extrema that are valid in the long term, have thus far been restricted to models of only a few variables. Here, a method is presented which treats extrema of chaotic systems as belonging to discretised manifolds of low dimension (low-D embedded in high-dimensional (high-D phase space. As a central feature, the method exploits that strange attractor dimension is generally much smaller than parent system phase space dimension. This is important, since the computational cost associated with discretised manifolds depends exponentially on their dimension. Thus, systems that would otherwise be associated with tremendous computational challenges, can be tackled on a laptop. As a test, bounding manifolds are calculated for high-D modifications of the canonical Duffing system. Parameters can be set such that the bounding manifold displays harmonic behaviour even if the underlying system is chaotic. Thus, solving for one post-transient forcing cycle of the bounding manifold predicts the extrema of the underlying chaotic problem indefinitely.
Simulating three-dimensional nonthermal high-energy photon emission in colliding-wind binaries
Energy Technology Data Exchange (ETDEWEB)
Reitberger, K.; Kissmann, R.; Reimer, A.; Reimer, O., E-mail: klaus.reitberger@uibk.ac.at [Institut für Astro- und Teilchenphysik and Institut für Theoretische Physik, Leopold-Franzens-Universität Innsbruck, A-6020 Innsbruck (Austria)
2014-07-01
Massive stars in binary systems have long been regarded as potential sources of high-energy γ rays. The emission is principally thought to arise in the region where the stellar winds collide and accelerate relativistic particles which subsequently emit γ rays. On the basis of a three-dimensional distribution function of high-energy particles in the wind collision region—as obtained by a numerical hydrodynamics and particle transport model—we present the computation of the three-dimensional nonthermal photon emission for a given line of sight. Anisotropic inverse Compton emission is modeled using the target radiation field of both stars. Photons from relativistic bremsstrahlung and neutral pion decay are computed on the basis of local wind plasma densities. We also consider photon-photon opacity effects due to the dense radiation fields of the stars. Results are shown for different stellar separations of a given binary system comprising of a B star and a Wolf-Rayet star. The influence of orbital orientation with respect to the line of sight is also studied by using different orbital viewing angles. For the chosen electron-proton injection ratio of 10{sup –2}, we present the ensuing photon emission in terms of two-dimensional projections maps, spectral energy distributions, and integrated photon flux values in various energy bands. Here, we find a transition from hadron-dominated to lepton-dominated high-energy emission with increasing stellar separations. In addition, we confirm findings from previous analytic modeling that the spectral energy distribution varies significantly with orbital orientation.
Resonant scattering induced thermopower in one-dimensional disordered systems
Müller, Daniel; Smit, Wilbert J.; Sigrist, Manfred
2015-05-01
This study analyzes thermoelectric properties of a one-dimensional random conductor which shows localization effects and simultaneously includes resonant scatterers yielding sharp conductance resonances. These sharp features give rise to a distinct behavior of the Seebeck coefficient in finite systems and incorporate the degree of localization as a means to enhance thermoelectric performance, in principle. The model for noninteracting electrons is discussed within the Landauer-Büttiker formalism such that analytical treatment is possible for a wide range of properties, if a special averaging scheme is applied. The approximations in the averaging procedure are tested with numerical evaluations showing good qualitative agreement, with some limited quantitative disagreement. The validity of low-temperature Mott's formula is determined and a good approximation is developed for the intermediate temperature range. In both regimes the intricate interplay between Anderson localization due to disorder and conductance resonances of the disorder potential is analyzed.
Four-dimensional gravity as an almost-Poisson system
Ita, Eyo Eyo
2015-04-01
In this paper, we examine the phase space structure of a noncanonical formulation of four-dimensional gravity referred to as the Instanton representation of Plebanski gravity (IRPG). The typical Hamiltonian (symplectic) approach leads to an obstruction to the definition of a symplectic structure on the full phase space of the IRPG. We circumvent this obstruction, using the Lagrange equations of motion, to find the appropriate generalization of the Poisson bracket. It is shown that the IRPG does not support a Poisson bracket except on the vector constraint surface. Yet there exists a fundamental bilinear operation on its phase space which produces the correct equations of motion and induces the correct transformation properties of the basic fields. This bilinear operation is known as the almost-Poisson bracket, which fails to satisfy the Jacobi identity and in this case also the condition of antisymmetry. We place these results into the overall context of nonsymplectic systems.
Thermoelectric transport in two-dimensional giant Rashba systems
Xiao, Cong; Li, Dingping; Ma, Zhongshui; Niu, Qian
Thermoelectric transport in strongly spin-orbit coupled two-dimensional Rashba systems is studied using the analytical solution of the linearized Boltzmann equation. To highlight the effects of inter-band scattering, we assume point-like potential impurities, and obtain the band-and energy-dependent transport relaxation times. Unconventional transport behaviors arise when the Fermi level lies near or below the band crossing point (BCP), such as the non-Drude electrical conducivity below the BCP, the failure of the standard Mott relation linking the Peltier coefficient to the electrical conductivity near the BCP, the enhancement of diffusion thermopower and figure of merit below the BCP, the zero-field Hall coefficient which is not inversely proportional to and not a monotonic function of the carrier density, the enhanced Nernst coefficient below the BCP, and the enhanced current-induced spin-polarization efficiency.
Gauge theory for finite-dimensional dynamical systems
International Nuclear Information System (INIS)
Gurfil, Pini
2007-01-01
Gauge theory is a well-established concept in quantum physics, electrodynamics, and cosmology. This concept has recently proliferated into new areas, such as mechanics and astrodynamics. In this paper, we discuss a few applications of gauge theory in finite-dimensional dynamical systems. We focus on the concept of rescriptive gauge symmetry, which is, in essence, rescaling of an independent variable. We show that a simple gauge transformation of multiple harmonic oscillators driven by chaotic processes can render an apparently ''disordered'' flow into a regular dynamical process, and that there exists a strong connection between gauge transformations and reduction theory of ordinary differential equations. Throughout the discussion, we demonstrate the main ideas by considering examples from diverse fields, including quantum mechanics, chemistry, rigid-body dynamics, and information theory
Dimensional consistency achieved in high-performance synchronizing hubs
Directory of Open Access Journals (Sweden)
García, P.
2013-02-01
Full Text Available The tolerances of parts produced for the automotive industry are so tight that any small process variation may mean that the product does not fulfill them. As dimensional tolerances decrease, the material properties of parts are expected to be improved. Depending on the dimensional and material requirements of a part, different production routes are available to find robust processes, minimizing cost and maximizing process capability. Dimensional tolerances have been reduced in recent years, and as a result, the double pressing-double sintering production via (“2P2S” has again become an accurate way to meet these increasingly narrow tolerances. In this paper, it is shown that the process parameters of the first sintering have great influence on the following production steps and the dimensions of the final parts. The roles of factors other than density and the second sintering process in defining the final dimensions of product are probed. All trials were done in a production line that produces synchronizer hubs for manual transmissions, allowing the maintenance of stable conditions and control of those parameters that are relevant for the product and process.
Las tolerancias en componentes fabricados para la industria del automóvil son tan estrechas que cualquier modificación en las variables del proceso puede provocar que no se cumplan. Una disminución de las tolerancias dimensionales, puede significar una mejora en las propiedades de las piezas. Dependiendo de los requerimientos dimensionales y del material, distintas rutas de procesado pueden seguirse para encontrar un método de procesado robusto, que minimice costes y maximice la capacidad del proceso. En los últimos años, la tolerancia dimensional se ha ajustado gracias a métodos de procesado como el doble prensado/doble sinterizado (“2P2S”, método de gran precisión para conseguir estrechas tolerancias. En este trabajo, se muestra que los parámetros de procesado
Construction of high-dimensional neural network potentials using environment-dependent atom pairs.
Jose, K V Jovan; Artrith, Nongnuch; Behler, Jörg
2012-05-21
An accurate determination of the potential energy is the crucial step in computer simulations of chemical processes, but using electronic structure methods on-the-fly in molecular dynamics (MD) is computationally too demanding for many systems. Constructing more efficient interatomic potentials becomes intricate with increasing dimensionality of the potential-energy surface (PES), and for numerous systems the accuracy that can be achieved is still not satisfying and far from the reliability of first-principles calculations. Feed-forward neural networks (NNs) have a very flexible functional form, and in recent years they have been shown to be an accurate tool to construct efficient PESs. High-dimensional NN potentials based on environment-dependent atomic energy contributions have been presented for a number of materials. Still, these potentials may be improved by a more detailed structural description, e.g., in form of atom pairs, which directly reflect the atomic interactions and take the chemical environment into account. We present an implementation of an NN method based on atom pairs, and its accuracy and performance are compared to the atom-based NN approach using two very different systems, the methanol molecule and metallic copper. We find that both types of NN potentials provide an excellent description of both PESs, with the pair-based method yielding a slightly higher accuracy making it a competitive alternative for addressing complex systems in MD simulations.
High precision detector robot arm system
Shu, Deming; Chu, Yong
2017-01-31
A method and high precision robot arm system are provided, for example, for X-ray nanodiffraction with an X-ray nanoprobe. The robot arm system includes duo-vertical-stages and a kinematic linkage system. A two-dimensional (2D) vertical plane ultra-precision robot arm supporting an X-ray detector provides positioning and manipulating of the X-ray detector. A vertical support for the 2D vertical plane robot arm includes spaced apart rails respectively engaging a first bearing structure and a second bearing structure carried by the 2D vertical plane robot arm.
Five-dimensional ultrasound system for soft tissue visualization.
Deshmukh, Nishikant P; Caban, Jesus J; Taylor, Russell H; Hager, Gregory D; Boctor, Emad M
2015-12-01
A five-dimensional ultrasound (US) system is proposed as a real-time pipeline involving fusion of 3D B-mode data with the 3D ultrasound elastography (USE) data as well as visualization of these fused data and a real-time update capability over time for each consecutive scan. 3D B-mode data assist in visualizing the anatomy of the target organ, and 3D elastography data adds strain information. We investigate the feasibility of such a system and show that an end-to-end real-time system, from acquisition to visualization, can be developed. We present a system that consists of (a) a real-time 3D elastography algorithm based on a normalized cross-correlation (NCC) computation on a GPU; (b) real-time 3D B-mode acquisition and network transfer; (c) scan conversion of 3D elastography and B-mode volumes (if acquired by 4D wobbler probe); and (d) visualization software that fuses, visualizes, and updates 3D B-mode and 3D elastography data in real time. We achieved a speed improvement of 4.45-fold for the threaded version of the NCC-based 3D USE versus the non-threaded version. The maximum speed was 79 volumes/s for 3D scan conversion. In a phantom, we validated the dimensions of a 2.2-cm-diameter sphere scan-converted to B-mode volume. Also, we validated the 5D US system visualization transfer function and detected 1- and 2-cm spherical objects (phantom lesion). Finally, we applied the system to a phantom consisting of three lesions to delineate the lesions from the surrounding background regions of the phantom. A 5D US system is achievable with real-time performance. We can distinguish between hard and soft areas in a phantom using the transfer functions.
Calibration of the ORNL two-dimensional Thomson scattering system
International Nuclear Information System (INIS)
Thomas, C.E. Jr.; Lazarus, E.A.; Kindsfather, R.R.; Murakami, M.; Stewart, K.A.
1985-10-01
A unified presentation of the calibrations needed for accurate calculation of electron temperature and density from Thomson scattering data for the Oak Ridge National Laboratory two-dimensional Thomson scattering system (SCATPAK II) is made. Techniques are described for measuring the range of wavelengths to which each channel is responsive. A statistical method for calibrating the gain of each channel in the system is given, and methods of checking for internal consistency and accuracy are presented. The relationship between the constants describing the relative light collection efficiency of each channel and plasma light-scattering theory is developed, methods for measuring the channel efficiencies and evaluating their accuracy are described, and the effect on these constants of bending fiber optics is discussed. The use of Rayleigh or Raman scattering for absolute efficiency (density) calibration, stray light measurement, and system efficiency evaluation is discussed; the relative merits of Rayleigh vs Raman scattering are presented; and the relationship among the Rayleigh/Raman calibrations, relative channel efficiency constants, and absolute efficiencies is developed
Unraveling surface enabled magnetic phenomena in low dimensional systems
Baljozovic, Milos; Girovsky, Jan; Nowakowski, Jan; Ali, Md Ehesan; Rossmann, Harald; Nijs, Thomas; Aeby, Elise; Nowakowska, Sylwia; Siewert, Dorota; Srivastava, Gitika; WäCkerlin, Christian; Dreiser, Jan; Decurtins, Silvio; Liu, Shi-Xia; Oppeneer, Peter M.; Jung, Thomas A.; Ballav, Nirmalya
Molecular spin systems with controllable interactions are of both fundamental and applied importance. These systems help us to better understand the fundamental origins of the interactions involved in low dimensional magnetic systems and to put them in the framework of existing models towards their further development. Following our first observation of exchange induced magnetic ordering in paramagnetic porphyrins adsorbed on ferromagnetic Co surface we showed that magnetic properties of such molecules can be controllably altered upon exposure to chemical and physical stimuli. In our most recent work it was shown that a synthetically programmed co-assembly of Fe and Mn phthalocyanines can also be realized on diamagnetic Au(111) surfaces where it induces long-range 2D ferrimagnetic order, at first glance in conflict with the Mermin-Wagner theory. Here we provide evidence for the first direct observation of such ordering from STM/STS and XMCD data and from DFT +U calculations demonstrating key role of the Au(111) surface states in mediating AFM RKKY coupling of the Kondo underscreened magnetic moments.
Performance Estimation for Two-Dimensional Brownian Rotary Ratchet Systems
Tutu, Hiroki; Horita, Takehiko; Ouchi, Katsuya
2015-04-01
Within the context of the Brownian ratchet model, a molecular rotary system that can perform unidirectional rotations induced by linearly polarized ac fields and produce positive work under loads was studied. The model is based on the Langevin equation for a particle in a two-dimensional (2D) three-tooth ratchet potential of threefold symmetry. The performance of the system is characterized by the coercive torque, i.e., the strength of the load competing with the torque induced by the ac driving field, and the energy efficiency in force conversion from the driving field to the torque. We propose a master equation for coarse-grained states, which takes into account the boundary motion between states, and develop a kinetic description to estimate the mean angular momentum (MAM) and powers relevant to the energy balance equation. The framework of analysis incorporates several 2D characteristics and is applicable to a wide class of models of smooth 2D ratchet potential. We confirm that the obtained expressions for MAM, power, and efficiency of the model can enable us to predict qualitative behaviors. We also discuss the usefulness of the torque/power relationship for experimental analyses, and propose a characteristic for 2D ratchet systems.
Three-Dimensional Reconstruction Optical System Using Shadows Triangulation
Barba, J. Leiner; Vargas, Q. Lorena; Torres, M. Cesar; Mattos, V. Lorenzo
2008-04-01
In this work is developed a three-dimensional reconstruction system using the Shades3D tool of the Matlab® Programming Language and materials of low cost, such as webcam camera, a stick, a weak structured lighting system composed by a desk lamp, and observation plane in which the object is located. The reconstruction is obtained through a triangulation process that is executed after acquiring a sequence of images of the scene with a shadow projected on the object; additionally an image filtering process is done for obtaining only the part of the scene that will be reconstructed. Previously, it is necessary to develop a calibration process for determining the internal camera geometric and optical characteristics (intrinsic parameters), and the 3D position and orientation of the camera frame relative to a certain world coordinate system (extrinsic parameters). The lamp and the stick are used to produce a shadow which scans the object; in this technique, it is not necessary to know the position of the light source, instead the triangulation is obtained using shadow plane produced by intersection between the stick and the illumination pattern. The webcam camera captures all images with the shadow scanning the object, and Shades3D tool processes all information taking into account captured images and calibration parameters. Likewise, this technique is evaluated in the reconstruction of parts of the human body and its application in the detection of external abnormalities and elaboration of prosthesis or implant.
A Three-Dimensional Wireless Indoor Localization System
Directory of Open Access Journals (Sweden)
Ping Yi
2014-01-01
Full Text Available Indoor localization, an emerging technology in location based service (LBS, is now playing a more and more important role both in commercial and in civilian industry. Global position system (GPS is the most popular solution in outdoor localization field, and the accuracy is around 10 meter error in positioning. However, with complex obstacles in buildings, problems rise in the “last mile” of localization field, which encourage a momentum of indoor localization. The traditional indoor localization system is either range-based or fingerprinting-based, which requires a lot of time and efforts to do the predeployment. In this paper, we present a 3-dimensional on-demand indoor localization system (3D-ODIL, which can be fingerprint-free and deployed rapidly in a multistorey building. The 3D-ODIL consists of two phases, vertical localization and horizontal localization. On vertical direction, we propose multistorey differential (MSD algorithm and implement it to fulfill the vertical localization, which can greatly reduce the number of anchors deployed. We use enhanced field division (EFD algorithm to conduct the horizontal localization. EFD algorithm is a range-free algorithm, the main idea of which is to dynamically divide the field within different signature area and position the target. The accuracy and performance have been validated through our extensive analysis and systematic experiments.
Energy Efficient MAC Scheme for Wireless Sensor Networks with High-Dimensional Data Aggregate
Directory of Open Access Journals (Sweden)
Seokhoon Kim
2015-01-01
Full Text Available This paper presents a novel and sustainable medium access control (MAC scheme for wireless sensor network (WSN systems that process high-dimensional aggregated data. Based on a preamble signal and buffer threshold analysis, it maximizes the energy efficiency of the wireless sensor devices which have limited energy resources. The proposed group management MAC (GM-MAC approach not only sets the buffer threshold value of a sensor device to be reciprocal to the preamble signal but also sets a transmittable group value to each sensor device by using the preamble signal of the sink node. The primary difference between the previous and the proposed approach is that existing state-of-the-art schemes use duty cycle and sleep mode to save energy consumption of individual sensor devices, whereas the proposed scheme employs the group management MAC scheme for sensor devices to maximize the overall energy efficiency of the whole WSN systems by minimizing the energy consumption of sensor devices located near the sink node. Performance evaluations show that the proposed scheme outperforms the previous schemes in terms of active time of sensor devices, transmission delay, control overhead, and energy consumption. Therefore, the proposed scheme is suitable for sensor devices in a variety of wireless sensor networking environments with high-dimensional data aggregate.
Fickler, Robert; Lapkiewicz, Radek; Huber, Marcus; Lavery, Martin P J; Padgett, Miles J; Zeilinger, Anton
2014-07-30
Photonics has become a mature field of quantum information science, where integrated optical circuits offer a way to scale the complexity of the set-up as well as the dimensionality of the quantum state. On photonic chips, paths are the natural way to encode information. To distribute those high-dimensional quantum states over large distances, transverse spatial modes, like orbital angular momentum possessing Laguerre Gauss modes, are favourable as flying information carriers. Here we demonstrate a quantum interface between these two vibrant photonic fields. We create three-dimensional path entanglement between two photons in a nonlinear crystal and use a mode sorter as the quantum interface to transfer the entanglement to the orbital angular momentum degree of freedom. Thus our results show a flexible way to create high-dimensional spatial mode entanglement. Moreover, they pave the way to implement broad complex quantum networks where high-dimensionally entangled states could be distributed over distant photonic chips.
Multigrid for high dimensional elliptic partial differential equations on non-equidistant grids
bin Zubair, H.; Oosterlee, C.E.; Wienands, R.
2006-01-01
This work presents techniques, theory and numbers for multigrid in a general d-dimensional setting. The main focus is the multigrid convergence for high-dimensional partial differential equations (PDEs). As a model problem we have chosen the anisotropic diffusion equation, on a unit hypercube. We
Tomograms for open quantum systems: In(finite) dimensional optical and spin systems
International Nuclear Information System (INIS)
Thapliyal, Kishore; Banerjee, Subhashish; Pathak, Anirban
2016-01-01
Tomograms are obtained as probability distributions and are used to reconstruct a quantum state from experimentally measured values. We study the evolution of tomograms for different quantum systems, both finite and infinite dimensional. In realistic experimental conditions, quantum states are exposed to the ambient environment and hence subject to effects like decoherence and dissipation, which are dealt with here, consistently, using the formalism of open quantum systems. This is extremely relevant from the perspective of experimental implementation and issues related to state reconstruction in quantum computation and communication. These considerations are also expected to affect the quasiprobability distribution obtained from experimentally generated tomograms and nonclassicality observed from them. -- Highlights: •Tomograms are constructed for open quantum systems. •Finite and infinite dimensional quantum systems are studied. •Finite dimensional systems (phase states, single & two qubit spin states) are studied. •A dissipative harmonic oscillator is considered as an infinite dimensional system. •Both pure dephasing as well as dissipation effects are studied.
Tomograms for open quantum systems: In(finite) dimensional optical and spin systems
Energy Technology Data Exchange (ETDEWEB)
Thapliyal, Kishore, E-mail: tkishore36@yahoo.com [Jaypee Institute of Information Technology, A-10, Sector-62, Noida, UP-201307 (India); Banerjee, Subhashish, E-mail: subhashish@iitj.ac.in [Indian Institute of Technology Jodhpur, Jodhpur 342011 (India); Pathak, Anirban, E-mail: anirban.pathak@gmail.com [Jaypee Institute of Information Technology, A-10, Sector-62, Noida, UP-201307 (India)
2016-03-15
Tomograms are obtained as probability distributions and are used to reconstruct a quantum state from experimentally measured values. We study the evolution of tomograms for different quantum systems, both finite and infinite dimensional. In realistic experimental conditions, quantum states are exposed to the ambient environment and hence subject to effects like decoherence and dissipation, which are dealt with here, consistently, using the formalism of open quantum systems. This is extremely relevant from the perspective of experimental implementation and issues related to state reconstruction in quantum computation and communication. These considerations are also expected to affect the quasiprobability distribution obtained from experimentally generated tomograms and nonclassicality observed from them. -- Highlights: •Tomograms are constructed for open quantum systems. •Finite and infinite dimensional quantum systems are studied. •Finite dimensional systems (phase states, single & two qubit spin states) are studied. •A dissipative harmonic oscillator is considered as an infinite dimensional system. •Both pure dephasing as well as dissipation effects are studied.
Institute of Scientific and Technical Information of China (English)
YANGYong－Hong; WANGYong－Gang; 等
2002-01-01
Two kinds of spin-dependent scattering effects (magnetic-impurity and spin-orbit scatterings) are investigated theoretically in a quasi-tow-dimensional (quasi-2D) disordered electron system.By making use of the diagrammatic techniques in perturbation theory,we have calculated the dc conductivity and magnetoresistance due to weak-localization effects,the analytical expressions of them are obtained as functions of the interlayer hopping energy and the characteristic times:elastic,inelastic,magnetic and spin-orbit scattering times.The relevant dimensional crossover behavior from 3D to 2D with decreasing the interlayer coupling is discussed,and the condition for the crossover is shown to be dependent on the aforementioned scattering times.At low temperature there exists a spin-dependent-scattering-induced dimensional crossover in this system.
Reducing the Complexity of Genetic Fuzzy Classifiers in Highly-Dimensional Classification Problems
Directory of Open Access Journals (Sweden)
DimitrisG. Stavrakoudis
2012-04-01
Full Text Available This paper introduces the Fast Iterative Rule-based Linguistic Classifier (FaIRLiC, a Genetic Fuzzy Rule-Based Classification System (GFRBCS which targets at reducing the structural complexity of the resulting rule base, as well as its learning algorithm's computational requirements, especially when dealing with high-dimensional feature spaces. The proposed methodology follows the principles of the iterative rule learning (IRL approach, whereby a rule extraction algorithm (REA is invoked in an iterative fashion, producing one fuzzy rule at a time. The REA is performed in two successive steps: the first one selects the relevant features of the currently extracted rule, whereas the second one decides the antecedent part of the fuzzy rule, using the previously selected subset of features. The performance of the classifier is finally optimized through a genetic tuning post-processing stage. Comparative results in a hyperspectral remote sensing classification as well as in 12 real-world classification datasets indicate the effectiveness of the proposed methodology in generating high-performing and compact fuzzy rule-based classifiers, even for very high-dimensional feature spaces.
K-intercalated carbon systems: Effects of dimensionality and substrate
Kaloni, Thaneshwor P.; Kahaly, M. Upadhyay; Cheng, Yingchun; Schwingenschlö gl, Udo
2012-01-01
the charge carrier density. Reasonably high values are found for all systems, the highest carrier density for the bilayer. The band structure and electron-phonon coupling of free-standing K-intercalated bilayer graphene points to a high probability
Taşkin Kaya, Gülşen
2013-10-01
-output relationships in high-dimensional systems for many problems in science and engineering. The HDMR method is developed to improve the efficiency of the deducing high dimensional behaviors. The method is formed by a particular organization of low dimensional component functions, in which each function is the contribution of one or more input variables to the output variables.
An improved three-dimensional non-scanning laser imaging system based on digital micromirror device
Xia, Wenze; Han, Shaokun; Lei, Jieyu; Zhai, Yu; Timofeev, Alexander N.
2018-01-01
Nowadays, there are two main methods to realize three-dimensional non-scanning laser imaging detection, which are detection method based on APD and detection method based on Streak Tube. However, the detection method based on APD possesses some disadvantages, such as small number of pixels, big pixel interval and complex supporting circuit. The detection method based on Streak Tube possesses some disadvantages, such as big volume, bad reliability and high cost. In order to resolve the above questions, this paper proposes an improved three-dimensional non-scanning laser imaging system based on Digital Micromirror Device. In this imaging system, accurate control of laser beams and compact design of imaging structure are realized by several quarter-wave plates and a polarizing beam splitter. The remapping fiber optics is used to sample the image plane of receiving optical lens, and transform the image into line light resource, which can realize the non-scanning imaging principle. The Digital Micromirror Device is used to convert laser pulses from temporal domain to spatial domain. The CCD with strong sensitivity is used to detect the final reflected laser pulses. In this paper, we also use an algorithm which is used to simulate this improved laser imaging system. In the last, the simulated imaging experiment demonstrates that this improved laser imaging system can realize three-dimensional non-scanning laser imaging detection.
Possibilities of identifying cyber attack in noisy space of n-dimensional abstract system
Energy Technology Data Exchange (ETDEWEB)
Jašek, Roman; Dvořák, Jiří; Janková, Martina; Sedláček, Michal [Tomas Bata University in Zlin Nad Stranemi 4511, 760 05 Zlin, Czech republic jasek@fai.utb.cz, dvorakj@aconte.cz, martina.jankova@email.cz, michal.sedlacek@email.cz (Czech Republic)
2016-06-08
This article briefly mentions some selected options of current concept for identifying cyber attacks from the perspective of the new cyberspace of real system. In the cyberspace, there is defined n-dimensional abstract system containing elements of the spatial arrangement of partial system elements such as micro-environment of cyber systems surrounded by other suitably arranged corresponding noise space. This space is also gradually supplemented by a new image of dynamic processes in a discreet environment, and corresponding again to n-dimensional expression of time space defining existence and also the prediction for expected cyber attacksin the noise space. Noises are seen here as useful and necessary for modern information and communication technologies (e.g. in processes of applied cryptography in ICT) and then the so-called useless noises designed for initial (necessary) filtering of this highly aggressive environment and in future expectedly offensive background in cyber war (e.g. the destruction of unmanned means of an electromagnetic pulse, or for destruction of new safety barriers created on principles of electrostatic field or on other principles of modern physics, etc.). The key to these new options is the expression of abstract systems based on the models of microelements of cyber systems and their hierarchical concept in structure of n-dimensional system in given cyberspace. The aim of this article is to highlight the possible systemic expression of cyberspace of abstract system and possible identification in time-spatial expression of real environment (on microelements of cyber systems and their surroundings with noise characteristics and time dimension in dynamic of microelements’ own time and externaltime defined by real environment). The article was based on a partial task of faculty specific research.
Possibilities of identifying cyber attack in noisy space of n-dimensional abstract system
International Nuclear Information System (INIS)
Jašek, Roman; Dvořák, Jiří; Janková, Martina; Sedláček, Michal
2016-01-01
This article briefly mentions some selected options of current concept for identifying cyber attacks from the perspective of the new cyberspace of real system. In the cyberspace, there is defined n-dimensional abstract system containing elements of the spatial arrangement of partial system elements such as micro-environment of cyber systems surrounded by other suitably arranged corresponding noise space. This space is also gradually supplemented by a new image of dynamic processes in a discreet environment, and corresponding again to n-dimensional expression of time space defining existence and also the prediction for expected cyber attacksin the noise space. Noises are seen here as useful and necessary for modern information and communication technologies (e.g. in processes of applied cryptography in ICT) and then the so-called useless noises designed for initial (necessary) filtering of this highly aggressive environment and in future expectedly offensive background in cyber war (e.g. the destruction of unmanned means of an electromagnetic pulse, or for destruction of new safety barriers created on principles of electrostatic field or on other principles of modern physics, etc.). The key to these new options is the expression of abstract systems based on the models of microelements of cyber systems and their hierarchical concept in structure of n-dimensional system in given cyberspace. The aim of this article is to highlight the possible systemic expression of cyberspace of abstract system and possible identification in time-spatial expression of real environment (on microelements of cyber systems and their surroundings with noise characteristics and time dimension in dynamic of microelements’ own time and externaltime defined by real environment). The article was based on a partial task of faculty specific research.
Possibilities of identifying cyber attack in noisy space of n-dimensional abstract system
Jašek, Roman; Dvořák, Jiří; Janková, Martina; Sedláček, Michal
2016-06-01
This article briefly mentions some selected options of current concept for identifying cyber attacks from the perspective of the new cyberspace of real system. In the cyberspace, there is defined n-dimensional abstract system containing elements of the spatial arrangement of partial system elements such as micro-environment of cyber systems surrounded by other suitably arranged corresponding noise space. This space is also gradually supplemented by a new image of dynamic processes in a discreet environment, and corresponding again to n-dimensional expression of time space defining existence and also the prediction for expected cyber attacksin the noise space. Noises are seen here as useful and necessary for modern information and communication technologies (e.g. in processes of applied cryptography in ICT) and then the so-called useless noises designed for initial (necessary) filtering of this highly aggressive environment and in future expectedly offensive background in cyber war (e.g. the destruction of unmanned means of an electromagnetic pulse, or for destruction of new safety barriers created on principles of electrostatic field or on other principles of modern physics, etc.). The key to these new options is the expression of abstract systems based on the models of microelements of cyber systems and their hierarchical concept in structure of n-dimensional system in given cyberspace. The aim of this article is to highlight the possible systemic expression of cyberspace of abstract system and possible identification in time-spatial expression of real environment (on microelements of cyber systems and their surroundings with noise characteristics and time dimension in dynamic of microelements' own time and externaltime defined by real environment). The article was based on a partial task of faculty specific research.
Ewald, Megan
As a result of recent mandates of the Next Generation Science Standards, assessments are a "system of meaning" amidst a paradigm shift toward three-dimensional assessments. This study is motivated by two research questions: 1) how do high school science teachers describe their processes of decision-making in the development and use of three-dimensional assessments and 2) how do high school science teachers negotiate their identities as assessors in designing three-dimensional assessments. An important factor in teachers' assessment decision making is how they identify themselves as assessors. Therefore, this study investigated the teachers' roles as assessors through the Sociocultural Identity Theory. The most important contribution from this study is the emergent teacher assessment sub-identities: the modifier-recycler , the feeler-finder, and the creator. Using a qualitative phenomenological research design, focus groups, three-series interviews, think-alouds, and document analysis were utilized in this study. These qualitative methods were chosen to elicit rich conversations among teachers, make meaning of the teachers' experiences through in-depth interviews, amplify the thought processes of individual teachers while making assessment decisions, and analyze assessment documents in relation to teachers' perspectives. The findings from this study suggest that--of the 19 participants--only two teachers could consistently be identified as creators and aligned their assessment practices with NGSS. However, assessment sub-identities are not static and teachers may negotiate their identities from one moment to the next within socially constructed realms of interpretation known as figured worlds. Because teachers are positioned in less powerful figured worlds within the dominant discourse of standardization, this study raises awareness as to how the external pressures from more powerful figured worlds socially construct teachers' identities as assessors. For teachers
High-Dimensional Function Approximation With Neural Networks for Large Volumes of Data.
Andras, Peter
2018-02-01
Approximation of high-dimensional functions is a challenge for neural networks due to the curse of dimensionality. Often the data for which the approximated function is defined resides on a low-dimensional manifold and in principle the approximation of the function over this manifold should improve the approximation performance. It has been show that projecting the data manifold into a lower dimensional space, followed by the neural network approximation of the function over this space, provides a more precise approximation of the function than the approximation of the function with neural networks in the original data space. However, if the data volume is very large, the projection into the low-dimensional space has to be based on a limited sample of the data. Here, we investigate the nature of the approximation error of neural networks trained over the projection space. We show that such neural networks should have better approximation performance than neural networks trained on high-dimensional data even if the projection is based on a relatively sparse sample of the data manifold. We also find that it is preferable to use a uniformly distributed sparse sample of the data for the purpose of the generation of the low-dimensional projection. We illustrate these results considering the practical neural network approximation of a set of functions defined on high-dimensional data including real world data as well.
Classical and quantum phases of low-dimensional dipolar systems
Energy Technology Data Exchange (ETDEWEB)
Cartarius, Florian
2016-09-22
In this thesis we present a detailed study of the phase diagram of ultracold bosonic atoms confined along a tight atomic wave guide, along which they experience an optical lattice potential. In this quasi-one dimensional model we analyse the interplay between interactions and quantum fluctuations in (i) determining the non-equilibrium steady state after a quench and (ii) giving rise to novel equilibrium phases, when the interactions combine the s-wave contact interaction and the anisotropic long range dipole-dipole interactions. In detail, in the first part of the thesis we study the depinning of a gas of impenetrable bosons following the sudden switch of of the optical lattice. By means of a Bose-Fermi mapping we infer the exact quantum dynamical evolution and show that in the thermodynamic limit the system is in a non-equilibrium steady state without quasi-long range order. In the second part of the thesis, we study the effect of quantum fluctuations on the linear-zigzag instability in the ground state of ultracold dipolar bosons, as a function of the strength of the transverse confinement. We first analyse the linear-zigzag instability in the classical regime, and then use our results to develop a multi-mode Bose-Hubbard model for the system. We then develop several numerical methods, to determine the ground state.
Bayesian Inference of High-Dimensional Dynamical Ocean Models
Lin, J.; Lermusiaux, P. F. J.; Lolla, S. V. T.; Gupta, A.; Haley, P. J., Jr.
2015-12-01
This presentation addresses a holistic set of challenges in high-dimension ocean Bayesian nonlinear estimation: i) predict the probability distribution functions (pdfs) of large nonlinear dynamical systems using stochastic partial differential equations (PDEs); ii) assimilate data using Bayes' law with these pdfs; iii) predict the future data that optimally reduce uncertainties; and (iv) rank the known and learn the new model formulations themselves. Overall, we allow the joint inference of the state, equations, geometry, boundary conditions and initial conditions of dynamical models. Examples are provided for time-dependent fluid and ocean flows, including cavity, double-gyre and Strait flows with jets and eddies. The Bayesian model inference, based on limited observations, is illustrated first by the estimation of obstacle shapes and positions in fluid flows. Next, the Bayesian inference of biogeochemical reaction equations and of their states and parameters is presented, illustrating how PDE-based machine learning can rigorously guide the selection and discovery of complex ecosystem models. Finally, the inference of multiscale bottom gravity current dynamics is illustrated, motivated in part by classic overflows and dense water formation sites and their relevance to climate monitoring and dynamics. This is joint work with our MSEAS group at MIT.
Optimization Techniques for Dimensionally Truncated Sparse Grids on Heterogeneous Systems
Deftu, A.
2013-02-01
Given the existing heterogeneous processor landscape dominated by CPUs and GPUs, topics such as programming productivity and performance portability have become increasingly important. In this context, an important question refers to how can we develop optimization strategies that cover both CPUs and GPUs. We answer this for fastsg, a library that provides functionality for handling efficiently high-dimensional functions. As it can be employed for compressing and decompressing large-scale simulation data, it finds itself at the core of a computational steering application which serves us as test case. We describe our experience with implementing fastsg\\'s time critical routines for Intel CPUs and Nvidia Fermi GPUs. We show the differences and especially the similarities between our optimization strategies for the two architectures. With regard to our test case for which achieving high speedups is a "must" for real-time visualization, we report a speedup of up to 6.2x times compared to the state-of-the-art implementation of the sparse grid technique for GPUs. © 2013 IEEE.
Hybrid three-dimensional variation and particle filtering for nonlinear systems
International Nuclear Information System (INIS)
Leng Hong-Ze; Song Jun-Qiang
2013-01-01
This work addresses the problem of estimating the states of nonlinear dynamic systems with sparse observations. We present a hybrid three-dimensional variation (3DVar) and particle piltering (PF) method, which combines the advantages of 3DVar and particle-based filters. By minimizing the cost function, this approach will produce a better proposal distribution of the state. Afterwards the stochastic resampling step in standard PF can be avoided through a deterministic scheme. The simulation results show that the performance of the new method is superior to the traditional ensemble Kalman filtering (EnKF) and the standard PF, especially in highly nonlinear systems
Method and system for manipulating a digital representation of a three-dimensional object
DEFF Research Database (Denmark)
2010-01-01
A method of manipulating a three-dimensional virtual building block model by means of two-dimensional cursor movements, the virtual building block model including a plurality of virtual building blocks each including a number of connection elements for connecting the virtual building block...... with another virtual building block according to a set of connection rules, the method comprising positioning by means of cursor movements in a computer display area representing a two-dimensional projection of said model, a two-dimensional projection of a first virtual building block to be connected...... to the structure, resulting in a two-dimensional position; determining, from the two-dimensional position, a number of three-dimensional candidate positions of the first virtual building block in the three-dimensional coordinate system; selecting one of said candidate positions based on the connection rules...
Cowley, Benjamin R.; Kaufman, Matthew T.; Churchland, Mark M.; Ryu, Stephen I.; Shenoy, Krishna V.; Yu, Byron M.
2012-01-01
The activity of tens to hundreds of neurons can be succinctly summarized by a smaller number of latent variables extracted using dimensionality reduction methods. These latent variables define a reduced-dimensional space in which we can study how population activity varies over time, across trials, and across experimental conditions. Ideally, we would like to visualize the population activity directly in the reduced-dimensional space, whose optimal dimensionality (as determined from the data)...
Approximating high-dimensional dynamics by barycentric coordinates with linear programming
Energy Technology Data Exchange (ETDEWEB)
Hirata, Yoshito, E-mail: yoshito@sat.t.u-tokyo.ac.jp; Aihara, Kazuyuki; Suzuki, Hideyuki [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan); Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); CREST, JST, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012 (Japan); Shiro, Masanori [Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); Mathematical Neuroinformatics Group, Advanced Industrial Science and Technology, Tsukuba, Ibaraki 305-8568 (Japan); Takahashi, Nozomu; Mas, Paloma [Center for Research in Agricultural Genomics (CRAG), Consorci CSIC-IRTA-UAB-UB, Barcelona 08193 (Spain)
2015-01-15
The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.
Approximating high-dimensional dynamics by barycentric coordinates with linear programming
International Nuclear Information System (INIS)
Hirata, Yoshito; Aihara, Kazuyuki; Suzuki, Hideyuki; Shiro, Masanori; Takahashi, Nozomu; Mas, Paloma
2015-01-01
The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data
Approximating high-dimensional dynamics by barycentric coordinates with linear programming.
Hirata, Yoshito; Shiro, Masanori; Takahashi, Nozomu; Aihara, Kazuyuki; Suzuki, Hideyuki; Mas, Paloma
2015-01-01
The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.
Efficient and accurate nearest neighbor and closest pair search in high-dimensional space
Tao, Yufei; Yi, Ke; Sheng, Cheng; Kalnis, Panos
2010-01-01
Nearest Neighbor (NN) search in high-dimensional space is an important problem in many applications. From the database perspective, a good solution needs to have two properties: (i) it can be easily incorporated in a relational database, and (ii
Reduced basis ANOVA methods for partial differential equations with high-dimensional random inputs
Energy Technology Data Exchange (ETDEWEB)
Liao, Qifeng, E-mail: liaoqf@shanghaitech.edu.cn [School of Information Science and Technology, ShanghaiTech University, Shanghai 200031 (China); Lin, Guang, E-mail: guanglin@purdue.edu [Department of Mathematics & School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907 (United States)
2016-07-15
In this paper we present a reduced basis ANOVA approach for partial deferential equations (PDEs) with random inputs. The ANOVA method combined with stochastic collocation methods provides model reduction in high-dimensional parameter space through decomposing high-dimensional inputs into unions of low-dimensional inputs. In this work, to further reduce the computational cost, we investigate spatial low-rank structures in the ANOVA-collocation method, and develop efficient spatial model reduction techniques using hierarchically generated reduced bases. We present a general mathematical framework of the methodology, validate its accuracy and demonstrate its efficiency with numerical experiments.
K-intercalated carbon systems: Effects of dimensionality and substrate
Kaloni, Thaneshwor P.
2012-06-01
Density functional theory is employed to investigate the electronic properties of K-intercalated carbon systems. Young\\'s modulus indicates that the intercalation increases the intrinsic stiffness. For K-intercalated bilayer graphene on SiC(0001) the Dirac cone is maintained, whereas a trilayer configuration exhibits a small splitting at the Dirac point. Interestingly, in contrast to many other intercalated carbon systems, the presence of the SiC(0001) substrate does not suppress but rather enhances the charge carrier density. Reasonably high values are found for all systems, the highest carrier density for the bilayer. The band structure and electron-phonon coupling of free-standing K-intercalated bilayer graphene points to a high probability for superconductivity in this system. © 2012 Europhysics Letters Association.
Development of a three-dimensionally movable phantom system for dosimetric verifications
International Nuclear Information System (INIS)
Nakayama, Hiroshi; Mizowaki, Takashi; Narita, Yuichiro; Kawada, Noriyuki; Takahashi, Kunio; Mihara, Kazumasa; Hiraoka, Masahiro
2008-01-01
The authors developed a three-dimensionally movable phantom system (3D movable phantom system) which can reproduce three-dimensional movements to experimentally verify the impact of radiotherapy treatment-related movements on dose distribution. The phantom system consists of three integrated components: a three-dimensional driving mechanism (3D driving mechanism), computer control system, and phantoms for film dosimetry. The 3D driving mechanism is a quintessential part of this system. It is composed of three linear-motion tables (single-axis robots) which are joined orthogonally to each other. This mechanism has a motion range of 100 mm, with a maximum velocity of 200 mm/s in each dimension, and 3D motion ability of arbitrary patterns. These attributes are sufficient to reproduce almost all organ movements. The positional accuracy of this 3D movable phantom system in a state of geostationary is less than 0.1 mm. The maximum error in terms of the absolute position on movement was 0.56 mm. The positional reappearance error on movement was up to 0.23 mm. The observed fluctuation of time was 0.012 s in the cycle of 4.5 s of oscillation. These results suggested that the 3D movable phantom system exhibited a sufficient level of accuracy in terms of geometry and timing to reproduce interfractional organ movement or setup errors in order to assess the influence of these errors on high-precision radiotherapy such as stereotactic irradiation and intensity-modulated radiotherapy. In addition, the authors 3D movable phantom system will also be useful in evaluating the adequacy and efficacy of new treatment techniques such as gating or tracking radiotherapy
Unexpected magnetism in low dimensional systems: the role of symmetry
International Nuclear Information System (INIS)
Munoz, MC; Chico, L; Lopez-Sancho, MP; Beltran, JI; Gallego, S; Cerda, J
2006-01-01
The symmetry underlying the geometric structure of materials determines most of their physical properties. In low dimensional systems the role of symmetry is enhanced and can give rise to new phenomena. Here, we report on unexpected magnetism in carbon nanotubes and O-rich surfaces of ionic oxides, to show how its existence is closely related to the symmetry conditions. First, based on tight-binding models, we demonstrate that chiral carbon nanotubes present spin splitting at the Fermi level in the absence of a magneticfield, whereas achiral tubes preserve spin degeneracy. These remarkably different behaviors of chiral and non-chiral nanotubes are due to the intrinsic symmetry dependence of the spin-orbit interaction. Second, the occurrence of spin-polarization at ZrO 2 , Al 2 O 3 and MgO surfaces is proved by means of abinitio calculations within the density functional theory. Large spin moments develop at O-ended polar terminations, transforming the non-magnetic insulator into a half-metal. The magnetic moments mainly reside in the surface oxygen atoms, and their origin is related to the existence of 2p holes of well-defined spin polarization at the valence band of the ionic oxide. The direct relation between magnetization and local loss of donor charge shows that at the origin of these phenomena is the reduced surface symmetry
Conformal algebras of two-dimensional disordered systems
International Nuclear Information System (INIS)
Gurarie, Victor; Ludwig, Andreas W.W.
2002-01-01
We discuss the structure of two-dimensional conformal field theories at a central charge c=0 describing critical disordered systems, polymers and percolation. We construct a novel extension of the c=0 Virasoro algebra, characterized by a number b measuring the effective number of massless degrees of freedom, and by a logarithmic partner of the stress tensor. It is argued to be present at a generic random critical point, lacking super Kac-Moody, or other higher symmetries, and is a tool to describe and classify such theories. Interestingly, this algebra is not only consistent with, but indeed naturally accommodates in general an underlying global supersymmetry. Polymers and percolation realize this algebra. Unexpectedly, we find that the c=0 Kac table of the degenerate fields contains two distinct theories with b=5/6 and b=-5/8 which we conjecture to correspond to percolation and polymers, respectively. A given Kac-table field can be degenerate only in one of them. Remarkably, we also find this algebra, and thereby an ensuing hidden supersymmetry, realized at general replica-averaged critical points, for which we derive an explicit formula for b. (author). Letter-to-the-editor
Two dimensional simulation of high power laser-surface interaction
International Nuclear Information System (INIS)
Goldman, S.R.; Wilke, M.D.; Green, R.E.L.; Johnson, R.P.; Busch, G.E.
1998-01-01
For laser intensities in the range of 10 8 --10 9 W/cm 2 , and pulse lengths of order 10 microsec or longer, the authors have modified the inertial confinement fusion code Lasnex to simulate gaseous and some dense material aspects of the laser-matter interaction. The unique aspect of their treatment consists of an ablation model which defines a dense material-vapor interface and then calculates the mass flow across this interface. The model treats the dense material as a rigid two-dimensional mass and heat reservoir suppressing all hydrodynamic motion in the dense material. The computer simulations and additional post-processors provide predictions for measurements including impulse given to the target, pressures at the target interface, electron temperatures and densities in the vapor-plasma plume region, and emission of radiation from the target. The authors will present an analysis of some relatively well diagnosed experiments which have been useful in developing their modeling. The simulations match experimentally obtained target impulses, pressures at the target surface inside the laser spot, and radiation emission from the target to within about 20%. Hence their simulational technique appears to form a useful basis for further investigation of laser-surface interaction in this intensity, pulse-width range. This work is useful in many technical areas such as materials processing
Multivariate statistical analysis a high-dimensional approach
Serdobolskii, V
2000-01-01
In the last few decades the accumulation of large amounts of in formation in numerous applications. has stimtllated an increased in terest in multivariate analysis. Computer technologies allow one to use multi-dimensional and multi-parametric models successfully. At the same time, an interest arose in statistical analysis with a de ficiency of sample data. Nevertheless, it is difficult to describe the recent state of affairs in applied multivariate methods as satisfactory. Unimprovable (dominating) statistical procedures are still unknown except for a few specific cases. The simplest problem of estimat ing the mean vector with minimum quadratic risk is unsolved, even for normal distributions. Commonly used standard linear multivari ate procedures based on the inversion of sample covariance matrices can lead to unstable results or provide no solution in dependence of data. Programs included in standard statistical packages cannot process 'multi-collinear data' and there are no theoretical recommen ...
Two-dimensional readout system for radiation detector
International Nuclear Information System (INIS)
Lee, L.Y.
1975-01-01
A two dimensional readout system has been provided for reading out locations of scintillations produced in a scintillation type radiation detector array wherein strips of scintillator material are arranged in a parallel planar array. Two sets of light guides are placed perpendicular to the scintillator strips, one on the top and one on the bottom to extend in alignment across the strips. Both the top and bottom guides are composed of a number of 90 0 triangular prisms with the lateral side forming the hypotenuse equal to twice the width of a scintillator strip. The prism system reflects light from a scintillation along one of the strips back and forth through adjacent strips to light pipes coupled to the outermost strips of the detector array which transmit light pulses to appropriate detectors to determine the scintillation along one axis. Other light pipes are connected to the end portions of the strips to transmit light from the individual strips to appropriate light detectors to indicate the particular strip activated, thereby determining the position of a scintillation along the other axis. The number of light guide pairs may be equal the number of the scintillation strips when equal spatial resolution for each of the two coordinates is desired. When the scintillator array detects an event which produces a scintillation along one of the strips, the emitted light travels along four different paths, two of which are along the strip, and two of which are through the light guide pair perpendicular to the strips until all four beams reach the outer edges of the array where they may be transmitted to light detectors by means of light pipes connected therebetween according to a binary code for direct digital readout. (U.S.)
International Nuclear Information System (INIS)
Zhang, Wuhong; Su, Ming; Wu, Ziwen; Lu, Meng; Huang, Bingwei; Chen, Lixiang
2013-01-01
Twisted photons enable the definition of a Hilbert space beyond two dimensions by orbital angular momentum (OAM) eigenstates. Here we propose a feasible entanglement concentration experiment, to enhance the quality of high-dimensional entanglement shared by twisted photon pairs. Our approach is started from the full characterization of entangled spiral bandwidth, and is then based on the careful selection of the Laguerre–Gaussian (LG) modes with specific radial and azimuthal indices p and ℓ. In particular, we demonstrate the possibility of high-dimensional entanglement concentration residing in the OAM subspace of up to 21 dimensions. By means of LabVIEW simulations with spatial light modulators, we show that the Shannon dimensionality could be employed to quantify the quality of the present concentration. Our scheme holds promise in quantum information applications defined in high-dimensional Hilbert space. (letter)
Detection of Subtle Context-Dependent Model Inaccuracies in High-Dimensional Robot Domains.
Mendoza, Juan Pablo; Simmons, Reid; Veloso, Manuela
2016-12-01
Autonomous robots often rely on models of their sensing and actions for intelligent decision making. However, when operating in unconstrained environments, the complexity of the world makes it infeasible to create models that are accurate in every situation. This article addresses the problem of using potentially large and high-dimensional sets of robot execution data to detect situations in which a robot model is inaccurate-that is, detecting context-dependent model inaccuracies in a high-dimensional context space. To find inaccuracies tractably, the robot conducts an informed search through low-dimensional projections of execution data to find parametric Regions of Inaccurate Modeling (RIMs). Empirical evidence from two robot domains shows that this approach significantly enhances the detection power of existing RIM-detection algorithms in high-dimensional spaces.
Study of three-dimensional image display by systemic CT
International Nuclear Information System (INIS)
Fujioka, Tadao; Ebihara, Yoshiyuki; Unei, Hiroshi; Hayashi, Masao; Shinohe, Tooru; Wada, Yuji; Sakai, Takatsugu; Kashima, Kenji; Fujita, Yoshihiro
1989-01-01
A head phantom for CT was scanned at 2 mm intervals from the cervix to the vertex in an attempt to obtain a three-dimensional image display of bones and facial epidermis from an ordinary axial image. Clinically, three-dimensional images were formed at eye sockets and hip joints. With the three-dimensional image using the head phantom, the entire head could be displayed at any angle. Clinically, images were obtained that could not be attained by ordinary CT scanning, such as broken bones in eye sockets and stereoscopic structure at the bottom of a cranium. The three-dimensional image display is considered to be useful in clinical diagnosis. (author)
Self-dissimilarity as a High Dimensional Complexity Measure
Wolpert, David H.; Macready, William
2005-01-01
For many systems characterized as "complex" the patterns exhibited on different scales differ markedly from one another. For example the biomass distribution in a human body "looks very different" depending on the scale at which one examines it. Conversely, the patterns at different scales in "simple" systems (e.g., gases, mountains, crystals) vary little from one scale to another. Accordingly, the degrees of self-dissimilarity between the patterns of a system at various scales constitute a complexity "signature" of that system. Here we present a novel quantification of self-dissimilarity. This signature can, if desired, incorporate a novel information-theoretic measure of the distance between probability distributions that we derive here. Whatever distance measure is chosen, our quantification of self-dissimilarity can be measured for many kinds of real-world data. This allows comparisons of the complexity signatures of wholly different kinds of systems (e.g., systems involving information density in a digital computer vs. species densities in a rain-forest vs. capital density in an economy, etc.). Moreover, in contrast to many other suggested complexity measures, evaluating the self-dissimilarity of a system does not require one to already have a model of the system. These facts may allow self-dissimilarity signatures to be used a s the underlying observational variables of an eventual overarching theory relating all complex systems. To illustrate self-dissimilarity we present several numerical experiments. In particular, we show that underlying structure of the logistic map is picked out by the self-dissimilarity signature of time series produced by that map
A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data
Directory of Open Access Journals (Sweden)
Hongchao Song
2017-01-01
Full Text Available Anomaly detection, which aims to identify observations that deviate from a nominal sample, is a challenging task for high-dimensional data. Traditional distance-based anomaly detection methods compute the neighborhood distance between each observation and suffer from the curse of dimensionality in high-dimensional space; for example, the distances between any pair of samples are similar and each sample may perform like an outlier. In this paper, we propose a hybrid semi-supervised anomaly detection model for high-dimensional data that consists of two parts: a deep autoencoder (DAE and an ensemble k-nearest neighbor graphs- (K-NNG- based anomaly detector. Benefiting from the ability of nonlinear mapping, the DAE is first trained to learn the intrinsic features of a high-dimensional dataset to represent the high-dimensional data in a more compact subspace. Several nonparametric KNN-based anomaly detectors are then built from different subsets that are randomly sampled from the whole dataset. The final prediction is made by all the anomaly detectors. The performance of the proposed method is evaluated on several real-life datasets, and the results confirm that the proposed hybrid model improves the detection accuracy and reduces the computational complexity.
Rampinelli, Vittorio; Doglietto, Francesco; Mattavelli, Davide; Qiu, Jimmy; Raffetti, Elena; Schreiber, Alberto; Villaret, Andrea Bolzoni; Kucharczyk, Walter; Donato, Francesco; Fontanella, Marco Maria; Nicolai, Piero
2017-09-01
Three-dimensional (3D) endoscopy has been recently introduced in endonasal skull base surgery. Only a relatively limited number of studies have compared it to 2-dimensional, high definition technology. The objective was to compare, in a preclinical setting for endonasal endoscopic surgery, the surgical maneuverability of 2-dimensional, high definition and 3D endoscopy. A group of 68 volunteers, novice and experienced surgeons, were asked to perform 2 tasks, namely simulating grasping and dissection surgical maneuvers, in a model of the nasal cavities. Time to complete the tasks was recorded. A questionnaire to investigate subjective feelings during tasks was filled by each participant. In 25 subjects, the surgeons' movements were continuously tracked by a magnetic-based neuronavigator coupled with dedicated software (ApproachViewer, part of GTx-UHN) and the recorded trajectories were analyzed by comparing jitter, sum of square differences, and funnel index. Total execution time was significantly lower with 3D technology (P < 0.05) in beginners and experts. Questionnaires showed that beginners preferred 3D endoscopy more frequently than experts. A minority (14%) of beginners experienced discomfort with 3D endoscopy. Analysis of jitter showed a trend toward increased effectiveness of surgical maneuvers with 3D endoscopy. Sum of square differences and funnel index analyses documented better values with 3D endoscopy in experts. In a preclinical setting for endonasal skull base surgery, 3D technology appears to confer an advantage in terms of time of execution and precision of surgical maneuvers. Copyright © 2017 Elsevier Inc. All rights reserved.
Space Based Infrared System High (SBIRS High)
2015-12-01
elements (five SMGTs) for the S2E2 Mobile Ground System. SBIRS Block Buy (GEO 5-6) The GEO 5-6 Tech Refresh (TR) Engineering Change Proposal was...Selected Acquisition Report (SAR) RCS: DD-A&T(Q&A)823-210 Space Based Infrared System High ( SBIRS High) As of FY 2017 President’s Budget Defense...Acquisition Management Information Retrieval (DAMIR) March 23, 2016 11:24:26 UNCLASSIFIED SBIRS High December 2015 SAR March 23, 2016 11:24:26
Variable kernel density estimation in high-dimensional feature spaces
CSIR Research Space (South Africa)
Van der Walt, Christiaan M
2017-02-01
Full Text Available Estimating the joint probability density function of a dataset is a central task in many machine learning applications. In this work we address the fundamental problem of kernel bandwidth estimation for variable kernel density estimation in high...
High-Performance Operating Systems
DEFF Research Database (Denmark)
Sharp, Robin
1999-01-01
Notes prepared for the DTU course 49421 "High Performance Operating Systems". The notes deal with quantitative and qualitative techniques for use in the design and evaluation of operating systems in computer systems for which performance is an important parameter, such as real-time applications......, communication systems and multimedia systems....
Vorobiev, Dmitry; Ninkov, Zoran
2017-11-01
Recent advances in photolithography allowed the fabrication of high-quality wire grid polarizers for the visible and near-infrared regimes. In turn, micropolarizer arrays (MPAs) based on wire grid polarizers have been developed and used to construct compact, versatile imaging polarimeters. However, the contrast and throughput of these polarimeters are significantly worse than one might expect based on the performance of large area wire grid polarizers or MPAs, alone. We investigate the parameters that affect the performance of wire grid polarizers and MPAs, using high-resolution two-dimensional and three-dimensional (3-D) finite-difference time-domain simulations. We pay special attention to numerical errors and other challenges that arise in models of these and other subwavelength optical devices. Our tests show that simulations of these structures in the visible and near-IR begin to converge numerically when the mesh size is smaller than ˜4 nm. The performance of wire grid polarizers is very sensitive to the shape, spacing, and conductivity of the metal wires. Using 3-D simulations of micropolarizer "superpixels," we directly study the cross talk due to diffraction at the edges of each micropolarizer, which decreases the contrast of MPAs to ˜200∶1.
Energy Technology Data Exchange (ETDEWEB)
Tahira, Rabia; Ikram, Manzoor; Zubairy, M Suhail [Centre for Quantum Physics, COMSATS Institute of Information Technology, Islamabad (Pakistan); Bougouffa, Smail [Department of Physics, Faculty of Science, Taibah University, PO Box 30002, Madinah (Saudi Arabia)
2010-02-14
We investigate the phenomenon of sudden death of entanglement in a high-dimensional bipartite system subjected to dissipative environments with an arbitrary initial pure entangled state between two fields in the cavities. We find that in a vacuum reservoir, the presence of the state where one or more than one (two) photons in each cavity are present is a necessary condition for the sudden death of entanglement. Otherwise entanglement remains for infinite time and decays asymptotically with the decay of individual qubits. For pure two-qubit entangled states in a thermal environment, we observe that sudden death of entanglement always occurs. The sudden death time of the entangled states is related to the number of photons in the cavities, the temperature of the reservoir and the initial preparation of the entangled states.
International Nuclear Information System (INIS)
Tahira, Rabia; Ikram, Manzoor; Zubairy, M Suhail; Bougouffa, Smail
2010-01-01
We investigate the phenomenon of sudden death of entanglement in a high-dimensional bipartite system subjected to dissipative environments with an arbitrary initial pure entangled state between two fields in the cavities. We find that in a vacuum reservoir, the presence of the state where one or more than one (two) photons in each cavity are present is a necessary condition for the sudden death of entanglement. Otherwise entanglement remains for infinite time and decays asymptotically with the decay of individual qubits. For pure two-qubit entangled states in a thermal environment, we observe that sudden death of entanglement always occurs. The sudden death time of the entangled states is related to the number of photons in the cavities, the temperature of the reservoir and the initial preparation of the entangled states.
Efficient High-Dimensional Entanglement Imaging with a Compressive-Sensing Double-Pixel Camera
Directory of Open Access Journals (Sweden)
Gregory A. Howland
2013-02-01
Full Text Available We implement a double-pixel compressive-sensing camera to efficiently characterize, at high resolution, the spatially entangled fields that are produced by spontaneous parametric down-conversion. This technique leverages sparsity in spatial correlations between entangled photons to improve acquisition times over raster scanning by a scaling factor up to n^{2}/log(n for n-dimensional images. We image at resolutions up to 1024 dimensions per detector and demonstrate a channel capacity of 8.4 bits per photon. By comparing the entangled photons’ classical mutual information in conjugate bases, we violate an entropic Einstein-Podolsky-Rosen separability criterion for all measured resolutions. More broadly, our result indicates that compressive sensing can be especially effective for higher-order measurements on correlated systems.
Talib, Imran; Belgacem, Fethi Bin Muhammad; Asif, Naseer Ahmad; Khalil, Hammad
2017-01-01
In this research article, we derive and analyze an efficient spectral method based on the operational matrices of three dimensional orthogonal Jacobi polynomials to solve numerically the mixed partial derivatives type multi-terms high dimensions generalized class of fractional order partial differential equations. We transform the considered fractional order problem to an easily solvable algebraic equations with the aid of the operational matrices. Being easily solvable, the associated algebraic system leads to finding the solution of the problem. Some test problems are considered to confirm the accuracy and validity of the proposed numerical method. The convergence of the method is ensured by comparing our Matlab software simulations based obtained results with the exact solutions in the literature, yielding negligible errors. Moreover, comparative results discussed in the literature are extended and improved in this study.
Chatwin, Chris; Young, Rupert; Birch, Philip
2015-01-01
Some laser history;\\ud Airborne Laser Testbed & Chemical Oxygen Iodine Laser (COIL);\\ud Laser modes and beam propagation;\\ud Fibre lasers and applications;\\ud US Navy Laser system – NRL 33kW fibre laser;\\ud Lockheed Martin 30kW fibre laser;\\ud Conclusions
On High Dimensional Searching Spaces and Learning Methods
DEFF Research Database (Denmark)
Yazdani, Hossein; Ortiz-Arroyo, Daniel; Choros, Kazimierz
2017-01-01
, and similarity functions and discuss the pros and cons of using each of them. Conventional similarity functions evaluate objects in the vector space. Contrarily, Weighted Feature Distance (WFD) functions compare data objects in both feature and vector spaces, preventing the system from being affected by some...
HASE: Framework for efficient high-dimensional association analyses
G.V. Roshchupkin (Gennady); H.H.H. Adams (Hieab); M.W. Vernooij (Meike); A. Hofman (Albert); C.M. van Duijn (Cornelia); M.K. Ikram (Kamran); W.J. Niessen (Wiro)
2016-01-01
textabstractHigh-throughput technology can now provide rich information on a person's biological makeup and environmental surroundings. Important discoveries have been made by relating these data to various health outcomes in fields such as genomics, proteomics, and medical imaging. However,
HASE : Framework for efficient high-dimensional association analyses
Roshchupkin, G. V.; Adams, H; Vernooij, Meike W.; Hofman, A; Van Duijn, C. M.; Ikram, M. Arfan; Niessen, W.J.
2016-01-01
High-throughput technology can now provide rich information on a person's biological makeup and environmental surroundings. Important discoveries have been made by relating these data to various health outcomes in fields such as genomics, proteomics, and medical imaging. However,
A Comparison of Machine Learning Methods in a High-Dimensional Classification Problem
Zekić-Sušac, Marijana; Pfeifer, Sanja; Šarlija, Nataša
2014-01-01
Background: Large-dimensional data modelling often relies on variable reduction methods in the pre-processing and in the post-processing stage. However, such a reduction usually provides less information and yields a lower accuracy of the model. Objectives: The aim of this paper is to assess the high-dimensional classification problem of recognizing entrepreneurial intentions of students by machine learning methods. Methods/Approach: Four methods were tested: artificial neural networks, CART ...
Secure data storage by three-dimensional absorbers in highly scattering volume medium
International Nuclear Information System (INIS)
Matoba, Osamu; Matsuki, Shinichiro; Nitta, Kouichi
2008-01-01
A novel data storage in a volume medium with highly scattering coefficient is proposed for data security application. Three-dimensional absorbers are used as data. These absorbers can not be measured by interferometer when the scattering in a volume medium is strong enough. We present a method to reconstruct three-dimensional absorbers and present numerical results to show the effectiveness of the proposed data storage.
A one-dimensional ion beam figuring system for x-ray mirror fabrication
International Nuclear Information System (INIS)
Idir, Mourad; Huang, Lei; Bouet, Nathalie; Kaznatcheev, Konstantine; Vescovi, Matthew; Lauer, Ken; Conley, Ray; Rennie, Kent; Kahn, Jim; Nethery, Richard; Zhou, Lin
2015-01-01
We report on the development of a one-dimensional Ion Beam Figuring (IBF) system for x-ray mirror polishing. Ion beam figuring provides a highly deterministic method for the final precision figuring of optical components with advantages over conventional methods. The system is based on a state of the art sputtering deposition system outfitted with a gridded radio frequency inductive coupled plasma ion beam source equipped with ion optics and dedicated slit developed specifically for this application. The production of an IBF system able to produce an elongated removal function rather than circular is presented in this paper, where we describe in detail the technical aspect and present the first obtained results
A one-dimensional ion beam figuring system for x-ray mirror fabrication
Energy Technology Data Exchange (ETDEWEB)
Idir, Mourad, E-mail: midir@bnl.gov; Huang, Lei; Bouet, Nathalie; Kaznatcheev, Konstantine; Vescovi, Matthew; Lauer, Ken [NSLS-II, Brookhaven National Laboratory, P.O. Box 5000, Upton, New York 11973 (United States); Conley, Ray [Advanced Photon Source, Argonne National Laboratory, Argonne, Illinois 60439 (United States); Rennie, Kent; Kahn, Jim; Nethery, Richard [Kaufman & Robinson, Inc., 1330 Blue Spruce Drive, Fort Collins, Colorado 80524 (United States); Zhou, Lin [College of Mechatronics and Automation, National University of Defense Technology, 109 Deya Road, Changsha, Hunan 410073 (China); Hu’nan Key Laboratory of Ultra-precision Machining Technology, Changsha, Hunan 410073 (China)
2015-10-15
We report on the development of a one-dimensional Ion Beam Figuring (IBF) system for x-ray mirror polishing. Ion beam figuring provides a highly deterministic method for the final precision figuring of optical components with advantages over conventional methods. The system is based on a state of the art sputtering deposition system outfitted with a gridded radio frequency inductive coupled plasma ion beam source equipped with ion optics and dedicated slit developed specifically for this application. The production of an IBF system able to produce an elongated removal function rather than circular is presented in this paper, where we describe in detail the technical aspect and present the first obtained results.
Institute of Scientific and Technical Information of China (English)
YANG YongHong; WANG YongGang; LIU Mei; WANG Jin
2002-01-01
Two kinds of spin-depcndcnt scattering effects (magnetic-iinpurity and spin-orbit scatterings) axe investi-gated theoretically in a quasi-two-dimensional (quasi-2D) disordered electron system. By making use of the diagrammatictechniques in perturbation theory, we have calculated the dc conductivity and magnetoresistance due to weak-localizationeffects, the analytical expressions of them are obtained as functions of the interlayer hopping energy and the charac-teristic times: elastic, inelastic, magnetic and spin-orbit scattering times. The relevant dimensional crossover behaviorfrom 3D to 2D with decreasing the interlayer coupling is discussed, and the condition for the crossover is shown to bedependent on the aforementioned scattering times. At low temperature there exists a spin-dcpendent-scattering-induccddimensional crossover in this system.
Approximate Dynamic Programming Based on High Dimensional Model Representation
Czech Academy of Sciences Publication Activity Database
Pištěk, Miroslav
2013-01-01
Roč. 49, č. 5 (2013), s. 720-737 ISSN 0023-5954 R&D Projects: GA ČR(CZ) GAP102/11/0437 Institutional support: RVO:67985556 Keywords : approximate dynamic programming * Bellman equation * approximate HDMR minimization * trust region problem Subject RIV: BC - Control Systems Theory Impact factor: 0.563, year: 2013 http://library.utia.cas.cz/separaty/2013/AS/pistek-0399560.pdf
High dimensional biological data retrieval optimization with NoSQL technology
2014-01-01
Background High-throughput transcriptomic data generated by microarray experiments is the most abundant and frequently stored kind of data currently used in translational medicine studies. Although microarray data is supported in data warehouses such as tranSMART, when querying relational databases for hundreds of different patient gene expression records queries are slow due to poor performance. Non-relational data models, such as the key-value model implemented in NoSQL databases, hold promise to be more performant solutions. Our motivation is to improve the performance of the tranSMART data warehouse with a view to supporting Next Generation Sequencing data. Results In this paper we introduce a new data model better suited for high-dimensional data storage and querying, optimized for database scalability and performance. We have designed a key-value pair data model to support faster queries over large-scale microarray data and implemented the model using HBase, an implementation of Google's BigTable storage system. An experimental performance comparison was carried out against the traditional relational data model implemented in both MySQL Cluster and MongoDB, using a large publicly available transcriptomic data set taken from NCBI GEO concerning Multiple Myeloma. Our new key-value data model implemented on HBase exhibits an average 5.24-fold increase in high-dimensional biological data query performance compared to the relational model implemented on MySQL Cluster, and an average 6.47-fold increase on query performance on MongoDB. Conclusions The performance evaluation found that the new key-value data model, in particular its implementation in HBase, outperforms the relational model currently implemented in tranSMART. We propose that NoSQL technology holds great promise for large-scale data management, in particular for high-dimensional biological data such as that demonstrated in the performance evaluation described in this paper. We aim to use this new data
High dimensional biological data retrieval optimization with NoSQL technology.
Wang, Shicai; Pandis, Ioannis; Wu, Chao; He, Sijin; Johnson, David; Emam, Ibrahim; Guitton, Florian; Guo, Yike
2014-01-01
High-throughput transcriptomic data generated by microarray experiments is the most abundant and frequently stored kind of data currently used in translational medicine studies. Although microarray data is supported in data warehouses such as tranSMART, when querying relational databases for hundreds of different patient gene expression records queries are slow due to poor performance. Non-relational data models, such as the key-value model implemented in NoSQL databases, hold promise to be more performant solutions. Our motivation is to improve the performance of the tranSMART data warehouse with a view to supporting Next Generation Sequencing data. In this paper we introduce a new data model better suited for high-dimensional data storage and querying, optimized for database scalability and performance. We have designed a key-value pair data model to support faster queries over large-scale microarray data and implemented the model using HBase, an implementation of Google's BigTable storage system. An experimental performance comparison was carried out against the traditional relational data model implemented in both MySQL Cluster and MongoDB, using a large publicly available transcriptomic data set taken from NCBI GEO concerning Multiple Myeloma. Our new key-value data model implemented on HBase exhibits an average 5.24-fold increase in high-dimensional biological data query performance compared to the relational model implemented on MySQL Cluster, and an average 6.47-fold increase on query performance on MongoDB. The performance evaluation found that the new key-value data model, in particular its implementation in HBase, outperforms the relational model currently implemented in tranSMART. We propose that NoSQL technology holds great promise for large-scale data management, in particular for high-dimensional biological data such as that demonstrated in the performance evaluation described in this paper. We aim to use this new data model as a basis for migrating
BioSig3D: High Content Screening of Three-Dimensional Cell Culture Models.
Directory of Open Access Journals (Sweden)
Cemal Cagatay Bilgin
Full Text Available BioSig3D is a computational platform for high-content screening of three-dimensional (3D cell culture models that are imaged in full 3D volume. It provides an end-to-end solution for designing high content screening assays, based on colony organization that is derived from segmentation of nuclei in each colony. BioSig3D also enables visualization of raw and processed 3D volumetric data for quality control, and integrates advanced bioinformatics analysis. The system consists of multiple computational and annotation modules that are coupled together with a strong use of controlled vocabularies to reduce ambiguities between different users. It is a web-based system that allows users to: design an experiment by defining experimental variables, upload a large set of volumetric images into the system, analyze and visualize the dataset, and either display computed indices as a heatmap, or phenotypic subtypes for heterogeneity analysis, or download computed indices for statistical analysis or integrative biology. BioSig3D has been used to profile baseline colony formations with two experiments: (i morphogenesis of a panel of human mammary epithelial cell lines (HMEC, and (ii heterogeneity in colony formation using an immortalized non-transformed cell line. These experiments reveal intrinsic growth properties of well-characterized cell lines that are routinely used for biological studies. BioSig3D is being released with seed datasets and video-based documentation.
High Speed Water Sterilization Using One-Dimensional Nanostructures
Schoen, David T.; Schoen, Alia P.; Hu, Liangbing; Kim, Han Sun; Heilshorn, Sarah C.; Cui, Yi
2010-01-01
The removal of bacteria and other organisms from water is an extremely important process, not only for drinking and sanitation but also industrially as biofouling is a commonplace and serious problem. We here present a textile based multiscale device for the high speed electrical sterilization of water using silver nanowires, carbon nanotubes, and cotton. This approach, which combines several materials spanning three very different length scales with simple dying based fabrication, makes a gravity fed device operating at 100000 L/(h m2) which can inactivate >98% of bacteria with only several seconds of total incubation time. This excellent performance is enabled by the use of an electrical mechanism rather than size exclusion, while the very high surface area of the device coupled with large electric field concentrations near the silver nanowire tips allows for effective bacterial inactivation. © 2010 American Chemical Society.
High Speed Water Sterilization Using One-Dimensional Nanostructures
Schoen, David T.
2010-09-08
The removal of bacteria and other organisms from water is an extremely important process, not only for drinking and sanitation but also industrially as biofouling is a commonplace and serious problem. We here present a textile based multiscale device for the high speed electrical sterilization of water using silver nanowires, carbon nanotubes, and cotton. This approach, which combines several materials spanning three very different length scales with simple dying based fabrication, makes a gravity fed device operating at 100000 L/(h m2) which can inactivate >98% of bacteria with only several seconds of total incubation time. This excellent performance is enabled by the use of an electrical mechanism rather than size exclusion, while the very high surface area of the device coupled with large electric field concentrations near the silver nanowire tips allows for effective bacterial inactivation. © 2010 American Chemical Society.
One-dimensional model for QCD at high energy
International Nuclear Information System (INIS)
Iancu, E.; Santana Amaral, J.T. de; Soyez, G.; Triantafyllopoulos, D.N.
2007-01-01
We propose a stochastic particle model in (1+1) dimensions, with one dimension corresponding to rapidity and the other one to the transverse size of a dipole in QCD, which mimics high-energy evolution and scattering in QCD in the presence of both saturation and particle-number fluctuations, and hence of pomeron loops. The model evolves via non-linear particle splitting, with a non-local splitting rate which is constrained by boost-invariance and multiple scattering. The splitting rate saturates at high density, so like the gluon emission rate in the JIMWLK evolution. In the mean field approximation obtained by ignoring fluctuations, the model exhibits the hallmarks of the BK equation, namely a BFKL-like evolution at low density, the formation of a traveling wave, and geometric scaling. In the full evolution including fluctuations, the geometric scaling is washed out at high energy and replaced by diffusive scaling. It is likely that the model belongs to the universality class of the reaction-diffusion process. The analysis of the model sheds new light on the pomeron loops equations in QCD and their possible improvements
Energy Technology Data Exchange (ETDEWEB)
NONE
2000-05-01
Research and development is conducted of (1) a three dimensional data reconstruction system and (2) a three-dimensional image processing system. Under item (1), an experimental 3-dimensional image reconstruction unit is built. Its arithmetic performance is evaluated, and it is found that it will complete a 512{sup 3}-voxel reconstruction process in 5 minutes. An experimenting system which is a one-piece unit is built for evaluating apparatuses. Under item (2), a viewer is fabricated as an element basic to 3-dimensional image processing, which is to display 3-dimensional data in a 2-dimensional image. In addition, basic 3-dimensional image processing is enabled by adding to the viewer an image filter and a function of describing the cross section at an arbitrarily chosen angle. In the development of a total system, (1) a basic design is prepared for a data collecting device IC, (2) a sampling grate is designed, (3) basic designs are prepared for the gantry and the bed, and (4) an image quality assessment system is constructed. Under item (1), specifications are determined for the data collecting device IC, and a test piece is built. Under item (2), it is confirmed that the experimental data transmitter is capable of 622Mbps. Under item (3), preparation of a detailed design is stared. Under item (4), a simulation is conducted for the formation of a human body equivalent-phantom. (NEDO)
Three-dimensional oscillator and Coulomb systems reduced from Kaehler spaces
International Nuclear Information System (INIS)
Nersessian, Armen; Yeranyan, Armen
2004-01-01
We define the oscillator and Coulomb systems on four-dimensional spaces with U(2)-invariant Kaehler metric and perform their Hamiltonian reduction to the three-dimensional oscillator and Coulomb systems specified by the presence of Dirac monopoles. We find the Kaehler spaces with conic singularity, where the oscillator and Coulomb systems on three-dimensional sphere and two-sheet hyperboloid originate. Then we construct the superintegrable oscillator system on three-dimensional sphere and hyperboloid, coupled to a monopole, and find their four-dimensional origins. In the latter case the metric of configuration space is a non-Kaehler one. Finally, we extend these results to the family of Kaehler spaces with conic singularities
Interactive Visualization of Large High-Dimensional Datasets
Ding, Wei; Chen, Ping
Nowadays many companies and public organizations use powerful database systems for collecting and managing information. Huge amount of data records are often accumulated within a short period of time. Valuable information is embedded in these data, which could help discover interesting knowledge and significantly assist in decision-making process. However, human beings are not capable of understanding so many data records which often have lots of attributes. The need for automated knowledge extraction is widely recognized, and leads to a rapidly developing market of data analysis and knowledge discovery tools.
Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction
Li, Zhijin; Chao, Yi; Li, P. Peggy
2012-01-01
A multi-scale three-dimensional variational data assimilation system (MS-3DVAR) has been formulated and the associated software system has been developed for improving high-resolution coastal ocean prediction. This system helps improve coastal ocean prediction skill, and has been used in support of operational coastal ocean forecasting systems and field experiments. The system has been developed to improve the capability of data assimilation for assimilating, simultaneously and effectively, sparse vertical profiles and high-resolution remote sensing surface measurements into coastal ocean models, as well as constraining model biases. In this system, the cost function is decomposed into two separate units for the large- and small-scale components, respectively. As such, data assimilation is implemented sequentially from large to small scales, the background error covariance is constructed to be scale-dependent, and a scale-dependent dynamic balance is incorporated. This scheme then allows effective constraining large scales and model bias through assimilating sparse vertical profiles, and small scales through assimilating high-resolution surface measurements. This MS-3DVAR enhances the capability of the traditional 3DVAR for assimilating highly heterogeneously distributed observations, such as along-track satellite altimetry data, and particularly maximizing the extraction of information from limited numbers of vertical profile observations.
High counting rate, two-dimensional position sensitive timing RPC
Petrovici, M.; Simion, V; Bartos, D; Caragheorgheopol, G; Deppner, I; Adamczewski-Musch, J; Linev, S; Williams, MCS; Loizeau, P; Herrmann, N; Doroud, K; Radulescu, L; Constantin, F
2012-01-01
Resistive Plate Chambers (RPCs) are widely employed as muon trigger systems at the Large Hadron Collider (LHC) experiments. Their large detector volume and the use of a relatively expensive gas mixture make a closed-loop gas circulation unavoidable. The return gas of RPCs operated in conditions similar to the experimental background foreseen at LHC contains large amount of impurities potentially dangerous for long-term operation. Several gas-cleaning agents, characterized during the past years, are currently in use. New test allowed understanding of the properties and performance of a large number of purifiers. On that basis, an optimal combination of different filters consisting of Molecular Sieve (MS) 5Å and 4Å, and a Cu catalyst R11 has been chosen and validated irradiating a set of RPCs at the CERN Gamma Irradiation Facility (GIF) for several years. A very important feature of this new configuration is the increase of the cycle duration for each purifier, which results in better system stabilit...
Feature selection for high-dimensional integrated data
Zheng, Charles; Schwartz, Scott; Chapkin, Robert S.; Carroll, Raymond J.; Ivanov, Ivan
2012-01-01
Motivated by the problem of identifying correlations between genes or features of two related biological systems, we propose a model of feature selection in which only a subset of the predictors Xt are dependent on the multidimensional variate Y, and the remainder of the predictors constitute a “noise set” Xu independent of Y. Using Monte Carlo simulations, we investigated the relative performance of two methods: thresholding and singular-value decomposition, in combination with stochastic optimization to determine “empirical bounds” on the small-sample accuracy of an asymptotic approximation. We demonstrate utility of the thresholding and SVD feature selection methods to with respect to a recent infant intestinal gene expression and metagenomics dataset.
Feature selection for high-dimensional integrated data
Zheng, Charles
2012-04-26
Motivated by the problem of identifying correlations between genes or features of two related biological systems, we propose a model of feature selection in which only a subset of the predictors Xt are dependent on the multidimensional variate Y, and the remainder of the predictors constitute a “noise set” Xu independent of Y. Using Monte Carlo simulations, we investigated the relative performance of two methods: thresholding and singular-value decomposition, in combination with stochastic optimization to determine “empirical bounds” on the small-sample accuracy of an asymptotic approximation. We demonstrate utility of the thresholding and SVD feature selection methods to with respect to a recent infant intestinal gene expression and metagenomics dataset.
A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix
Hu, Zongliang
2017-09-27
The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.
A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix.
Hu, Zongliang; Dong, Kai; Dai, Wenlin; Tong, Tiejun
2017-09-21
The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.
A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix
Hu, Zongliang; Dong, Kai; Dai, Wenlin; Tong, Tiejun
2017-01-01
The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.
Accelerated Sensitivity Analysis in High-Dimensional Stochastic Reaction Networks.
Arampatzis, Georgios; Katsoulakis, Markos A; Pantazis, Yannis
2015-01-01
Existing sensitivity analysis approaches are not able to handle efficiently stochastic reaction networks with a large number of parameters and species, which are typical in the modeling and simulation of complex biochemical phenomena. In this paper, a two-step strategy for parametric sensitivity analysis for such systems is proposed, exploiting advantages and synergies between two recently proposed sensitivity analysis methodologies for stochastic dynamics. The first method performs sensitivity analysis of the stochastic dynamics by means of the Fisher Information Matrix on the underlying distribution of the trajectories; the second method is a reduced-variance, finite-difference, gradient-type sensitivity approach relying on stochastic coupling techniques for variance reduction. Here we demonstrate that these two methods can be combined and deployed together by means of a new sensitivity bound which incorporates the variance of the quantity of interest as well as the Fisher Information Matrix estimated from the first method. The first step of the proposed strategy labels sensitivities using the bound and screens out the insensitive parameters in a controlled manner. In the second step of the proposed strategy, a finite-difference method is applied only for the sensitivity estimation of the (potentially) sensitive parameters that have not been screened out in the first step. Results on an epidermal growth factor network with fifty parameters and on a protein homeostasis with eighty parameters demonstrate that the proposed strategy is able to quickly discover and discard the insensitive parameters and in the remaining potentially sensitive parameters it accurately estimates the sensitivities. The new sensitivity strategy can be several times faster than current state-of-the-art approaches that test all parameters, especially in "sloppy" systems. In particular, the computational acceleration is quantified by the ratio between the total number of parameters over the
Accelerated Sensitivity Analysis in High-Dimensional Stochastic Reaction Networks.
Directory of Open Access Journals (Sweden)
Georgios Arampatzis
Full Text Available Existing sensitivity analysis approaches are not able to handle efficiently stochastic reaction networks with a large number of parameters and species, which are typical in the modeling and simulation of complex biochemical phenomena. In this paper, a two-step strategy for parametric sensitivity analysis for such systems is proposed, exploiting advantages and synergies between two recently proposed sensitivity analysis methodologies for stochastic dynamics. The first method performs sensitivity analysis of the stochastic dynamics by means of the Fisher Information Matrix on the underlying distribution of the trajectories; the second method is a reduced-variance, finite-difference, gradient-type sensitivity approach relying on stochastic coupling techniques for variance reduction. Here we demonstrate that these two methods can be combined and deployed together by means of a new sensitivity bound which incorporates the variance of the quantity of interest as well as the Fisher Information Matrix estimated from the first method. The first step of the proposed strategy labels sensitivities using the bound and screens out the insensitive parameters in a controlled manner. In the second step of the proposed strategy, a finite-difference method is applied only for the sensitivity estimation of the (potentially sensitive parameters that have not been screened out in the first step. Results on an epidermal growth factor network with fifty parameters and on a protein homeostasis with eighty parameters demonstrate that the proposed strategy is able to quickly discover and discard the insensitive parameters and in the remaining potentially sensitive parameters it accurately estimates the sensitivities. The new sensitivity strategy can be several times faster than current state-of-the-art approaches that test all parameters, especially in "sloppy" systems. In particular, the computational acceleration is quantified by the ratio between the total number of
Relativistic band gaps in one-dimensional disordered systems
International Nuclear Information System (INIS)
Clerk, G.J.; McKellar, B.H.J.
1992-01-01
Conditions for the existence of band gaps in a one-dimensional disordered array of δ-function potentials possessing short range order are developed in a relativistic framework. Both Lorentz vector and scalar type potentials are treated. The relationship between the energy gaps and the transmission properties of the array are also discussed. 20 refs., 2 figs
Neutron scattering studies of low dimensional magnetic systems
DEFF Research Database (Denmark)
Hansen, Ursula Bengård
investigated at low temperaturesand in a longitudinal magnetic eld using neutron spectroscopy. Here we observe thehybridisation of the magnon bound states, inherent to the low dimensional nature ofCoCl2 · 2D2O.At higher temperature, signatures which can be attributed to Magnetic Bloch Oscillationsis observed...
Xu, Jiandong; Gao, Qiuming; Zhang, Yunlu; Tan, Yanli; Tian, Weiqian; Zhu, Lihua; Jiang, Lei
2014-07-01
Two-dimensional (2D) porous carbon AC-SPN-3 possessing of amazing high micropore volume ratio of 83% and large surface area of about 1069 m2 g-1 is high-yield obtained by pyrolysis of natural waste Pistachio nutshells with KOH activation. The AC-SPN-3 has a curved 2D lamellar morphology with the thickness of each slice about 200 nm. The porous carbon is consists of highly interconnected uniform pores with the median pore diameter of about 0.76 nm, which could potentially improve the performance by maximizing the electrode surface area accessible to the typical electrolyte ions (such as TEA+, diameter = ~0.68 nm). Electrochemical analyses show that AC-SPN-3 has significantly large areal capacitance of 29.3/20.1 μF cm-2 and high energy density of 10/39 Wh kg-1 at power of 52/286 kW kg-1 in 6 M KOH aqueous electrolyte and 1 M TEABF4 in EC-DEC (1:1) organic electrolyte system, respectively.
Three-dimensional atom localization via probe absorption in a cascade four-level atomic system
Directory of Open Access Journals (Sweden)
Zeng Wei
2018-03-01
Full Text Available For an atomic system with cascade four-level type, a useful scheme about three-dimensional (3D atom localization is proposed. In our scheme the atomic system is coherently controlled by using a radio-frequency field to couple with two-folded levels under the condition of the existence of probe absorption. Our results show that detecting precision of 3D atom localization may be obviously improved by properly adjusting the frequency detuning and strength of the radio-frequency driving field. So our scheme could be helpful to realize 3D atom localization with high-efficiency and high-precision . In the field of laser cooling or the atom nano-lithography, our studies provide potential applications.
Wang, Zhiping; Cao, Dewei; Yu, Benli
2016-05-01
We present a new scheme for three-dimensional (3D) atom localization in a three-level atomic system via measuring the absorption of a weak probe field. Owing to the space-dependent atom-field interaction, the position probability distribution of the atom can be directly determined by measuring the probe absorption. It is found that, by properly varying the parameters of the system, the probability of finding the atom in 3D space can be almost 100%. Our scheme opens a promising way to achieve high-precision and high-efficiency 3D atom localization, which provides some potential applications in laser cooling or atom nano-lithography via atom localization.
Three-dimensional atom localization via probe absorption in a cascade four-level atomic system
Zeng, Wei; Deng, Li; Chen, Aixi
2018-03-01
For an atomic system with cascade four-level type, a useful scheme about three-dimensional (3D) atom localization is proposed. In our scheme the atomic system is coherently controlled by using a radio-frequency field to couple with two-folded levels under the condition of the existence of probe absorption. Our results show that detecting precision of 3D atom localization may be obviously improved by properly adjusting the frequency detuning and strength of the radio-frequency driving field. So our scheme could be helpful to realize 3D atom localization with high-efficiency and high-precision . In the field of laser cooling or the atom nano-lithography, our studies provide potential applications.
Zhu, Shuze; Geng, Xiumei; Han, Yang; Benamara, Mourad; Chen, Liao; Li, Jingxiao; Bilgin, Ismail; Zhu, Hongli
2017-10-01
Element sulfur in nature is an insulating solid. While it has been tested that one-dimensional sulfur chain is metallic and conducting, the investigation on two-dimensional sulfur remains elusive. We report that molybdenum disulfide layers are able to serve as the nanotemplate to facilitate the formation of two-dimensional sulfur. Density functional theory calculations suggest that confined in-between layers of molybdenum disulfide, sulfur atoms are able to form two-dimensional triangular arrays that are highly metallic. As a result, these arrays contribute to the high conductivity and metallic phase of the hybrid structures of molybdenum disulfide layers and two-dimensional sulfur arrays. The experimentally measured conductivity of such hybrid structures reaches up to 223 S/m. Multiple experimental results, including X-ray photoelectron spectroscopy (XPS), transition electron microscope (TEM), selected area electron diffraction (SAED), agree with the computational insights. Due to the excellent conductivity, the current density is linearly proportional to the scan rate until 30,000 mV s-1 without the attendance of conductive additives. Using such hybrid structures as electrode, the two-electrode supercapacitor cells yield a power density of 106 Wh kg-1 and energy density 47.5 Wh kg-1 in ionic liquid electrolytes. Our findings offer new insights into using two-dimensional materials and their Van der Waals heterostructures as nanotemplates to pattern foreign atoms for unprecedented material properties.
Similarity measurement method of high-dimensional data based on normalized net lattice subspace
Institute of Scientific and Technical Information of China (English)
Li Wenfa; Wang Gongming; Li Ke; Huang Su
2017-01-01
The performance of conventional similarity measurement methods is affected seriously by the curse of dimensionality of high-dimensional data.The reason is that data difference between sparse and noisy dimensionalities occupies a large proportion of the similarity, leading to the dissimilarities between any results.A similarity measurement method of high-dimensional data based on normalized net lattice subspace is proposed.The data range of each dimension is divided into several intervals, and the components in different dimensions are mapped onto the corresponding interval.Only the component in the same or adjacent interval is used to calculate the similarity.To validate this meth-od, three data types are used, and seven common similarity measurement methods are compared. The experimental result indicates that the relative difference of the method is increasing with the di-mensionality and is approximately two or three orders of magnitude higher than the conventional method.In addition, the similarity range of this method in different dimensions is [0, 1], which is fit for similarity analysis after dimensionality reduction.
Cowley, Benjamin R.; Kaufman, Matthew T.; Butler, Zachary S.; Churchland, Mark M.; Ryu, Stephen I.; Shenoy, Krishna V.; Yu, Byron M.
2013-12-01
Objective. Analyzing and interpreting the activity of a heterogeneous population of neurons can be challenging, especially as the number of neurons, experimental trials, and experimental conditions increases. One approach is to extract a set of latent variables that succinctly captures the prominent co-fluctuation patterns across the neural population. A key problem is that the number of latent variables needed to adequately describe the population activity is often greater than 3, thereby preventing direct visualization of the latent space. By visualizing a small number of 2-d projections of the latent space or each latent variable individually, it is easy to miss salient features of the population activity. Approach. To address this limitation, we developed a Matlab graphical user interface (called DataHigh) that allows the user to quickly and smoothly navigate through a continuum of different 2-d projections of the latent space. We also implemented a suite of additional visualization tools (including playing out population activity timecourses as a movie and displaying summary statistics, such as covariance ellipses and average timecourses) and an optional tool for performing dimensionality reduction. Main results. To demonstrate the utility and versatility of DataHigh, we used it to analyze single-trial spike count and single-trial timecourse population activity recorded using a multi-electrode array, as well as trial-averaged population activity recorded using single electrodes. Significance. DataHigh was developed to fulfil a need for visualization in exploratory neural data analysis, which can provide intuition that is critical for building scientific hypotheses and models of population activity.
Cowley, Benjamin R; Kaufman, Matthew T; Butler, Zachary S; Churchland, Mark M; Ryu, Stephen I; Shenoy, Krishna V; Yu, Byron M
2013-12-01
Analyzing and interpreting the activity of a heterogeneous population of neurons can be challenging, especially as the number of neurons, experimental trials, and experimental conditions increases. One approach is to extract a set of latent variables that succinctly captures the prominent co-fluctuation patterns across the neural population. A key problem is that the number of latent variables needed to adequately describe the population activity is often greater than 3, thereby preventing direct visualization of the latent space. By visualizing a small number of 2-d projections of the latent space or each latent variable individually, it is easy to miss salient features of the population activity. To address this limitation, we developed a Matlab graphical user interface (called DataHigh) that allows the user to quickly and smoothly navigate through a continuum of different 2-d projections of the latent space. We also implemented a suite of additional visualization tools (including playing out population activity timecourses as a movie and displaying summary statistics, such as covariance ellipses and average timecourses) and an optional tool for performing dimensionality reduction. To demonstrate the utility and versatility of DataHigh, we used it to analyze single-trial spike count and single-trial timecourse population activity recorded using a multi-electrode array, as well as trial-averaged population activity recorded using single electrodes. DataHigh was developed to fulfil a need for visualization in exploratory neural data analysis, which can provide intuition that is critical for building scientific hypotheses and models of population activity.
Cowley, Benjamin R.; Kaufman, Matthew T.; Butler, Zachary S.; Churchland, Mark M.; Ryu, Stephen I.; Shenoy, Krishna V.; Yu, Byron M.
2014-01-01
Objective Analyzing and interpreting the activity of a heterogeneous population of neurons can be challenging, especially as the number of neurons, experimental trials, and experimental conditions increases. One approach is to extract a set of latent variables that succinctly captures the prominent co-fluctuation patterns across the neural population. A key problem is that the number of latent variables needed to adequately describe the population activity is often greater than three, thereby preventing direct visualization of the latent space. By visualizing a small number of 2-d projections of the latent space or each latent variable individually, it is easy to miss salient features of the population activity. Approach To address this limitation, we developed a Matlab graphical user interface (called DataHigh) that allows the user to quickly and smoothly navigate through a continuum of different 2-d projections of the latent space. We also implemented a suite of additional visualization tools (including playing out population activity timecourses as a movie and displaying summary statistics, such as covariance ellipses and average timecourses) and an optional tool for performing dimensionality reduction. Main results To demonstrate the utility and versatility of DataHigh, we used it to analyze single-trial spike count and single-trial timecourse population activity recorded using a multi-electrode array, as well as trial-averaged population activity recorded using single electrodes. Significance DataHigh was developed to fulfill a need for visualization in exploratory neural data analysis, which can provide intuition that is critical for building scientific hypotheses and models of population activity. PMID:24216250
Effects of applying three-dimensional seismic isolation system on the seismic design of FBR
International Nuclear Information System (INIS)
Hirata, Kazuta; Yabana, Shuichi; Kanazawa, Kenji; Matsuda, Akihiro
1997-01-01
In this study conceptional three-dimensional seismic isolation system for fast breeder reactor (FBR) is proposed. Effects of applying three-dimensional seismic isolation system on the seismic design for the FBR equipment are evaluated quantitatively. From the evaluation, it is concluded following effects are expected by applying the three-dimensional seismic isolation system to the FBR and the effects are evaluated quantitatively. (1) Reduction of membrane thickness of the reactor vessel (2) Suppression of uplift of fuels by reducing vertical seismic response of the core (3) Reduction of the supports for the piping system (4) Three-dimensional base isolation system for the whole reactor building is advantageous to the combined isolation system of horizontal base isolation for the reactor building and vertical isolation for the equipment. (author)
International Nuclear Information System (INIS)
Liu, W; Sawant, A; Ruan, D
2016-01-01
Purpose: The development of high dimensional imaging systems (e.g. volumetric MRI, CBCT, photogrammetry systems) in image-guided radiotherapy provides important pathways to the ultimate goal of real-time volumetric/surface motion monitoring. This study aims to develop a prediction method for the high dimensional state subject to respiratory motion. Compared to conventional linear dimension reduction based approaches, our method utilizes manifold learning to construct a descriptive feature submanifold, where more efficient and accurate prediction can be performed. Methods: We developed a prediction framework for high-dimensional state subject to respiratory motion. The proposed method performs dimension reduction in a nonlinear setting to permit more descriptive features compared to its linear counterparts (e.g., classic PCA). Specifically, a kernel PCA is used to construct a proper low-dimensional feature manifold, where low-dimensional prediction is performed. A fixed-point iterative pre-image estimation method is applied subsequently to recover the predicted value in the original state space. We evaluated and compared the proposed method with PCA-based method on 200 level-set surfaces reconstructed from surface point clouds captured by the VisionRT system. The prediction accuracy was evaluated with respect to root-mean-squared-error (RMSE) for both 200ms and 600ms lookahead lengths. Results: The proposed method outperformed PCA-based approach with statistically higher prediction accuracy. In one-dimensional feature subspace, our method achieved mean prediction accuracy of 0.86mm and 0.89mm for 200ms and 600ms lookahead lengths respectively, compared to 0.95mm and 1.04mm from PCA-based method. The paired t-tests further demonstrated the statistical significance of the superiority of our method, with p-values of 6.33e-3 and 5.78e-5, respectively. Conclusion: The proposed approach benefits from the descriptiveness of a nonlinear manifold and the prediction
High-Dimensional Intrinsic Interpolation Using Gaussian Process Regression and Diffusion Maps
International Nuclear Information System (INIS)
Thimmisetty, Charanraj A.; Ghanem, Roger G.; White, Joshua A.; Chen, Xiao
2017-01-01
This article considers the challenging task of estimating geologic properties of interest using a suite of proxy measurements. The current work recast this task as a manifold learning problem. In this process, this article introduces a novel regression procedure for intrinsic variables constrained onto a manifold embedded in an ambient space. The procedure is meant to sharpen high-dimensional interpolation by inferring non-linear correlations from the data being interpolated. The proposed approach augments manifold learning procedures with a Gaussian process regression. It first identifies, using diffusion maps, a low-dimensional manifold embedded in an ambient high-dimensional space associated with the data. It relies on the diffusion distance associated with this construction to define a distance function with which the data model is equipped. This distance metric function is then used to compute the correlation structure of a Gaussian process that describes the statistical dependence of quantities of interest in the high-dimensional ambient space. The proposed method is applicable to arbitrarily high-dimensional data sets. Here, it is applied to subsurface characterization using a suite of well log measurements. The predictions obtained in original, principal component, and diffusion space are compared using both qualitative and quantitative metrics. Considerable improvement in the prediction of the geological structural properties is observed with the proposed method.
Development of three-dimensional computed tomography system using TNRF2 of JRR-3M
Energy Technology Data Exchange (ETDEWEB)
Murata, Yutaka; Mochiki, Koh-ichi [Musashi Inst. of Tech., Tokyo (Japan); Matsubayashi, Masahito
1998-01-01
A three-dimensional filtering engine, a convolution engine, and a back projection engine were developed for real-time signal processing of three-dimensional computed tomography. The performance of the system was measured and through-put of 0.5 second per one cross sectional data processing was attained. (author)
International Nuclear Information System (INIS)
Chen Jingyun; Cong Peng; Song Qi
2006-01-01
The authors present a new DR image segmentation method based on two-dimensional histogram and watershed algorithm. The authors use watershed algorithm to locate threshold on the vertical projection plane of two-dimensional histogram. This method is applied to the segmentation of DR images produced by luggage inspection system with DR-CT. The advantage of this method is also analyzed. (authors)
Directory of Open Access Journals (Sweden)
Enkelejda Miho
2018-02-01
Full Text Available The adaptive immune system recognizes antigens via an immense array of antigen-binding antibodies and T-cell receptors, the immune repertoire. The interrogation of immune repertoires is of high relevance for understanding the adaptive immune response in disease and infection (e.g., autoimmunity, cancer, HIV. Adaptive immune receptor repertoire sequencing (AIRR-seq has driven the quantitative and molecular-level profiling of immune repertoires, thereby revealing the high-dimensional complexity of the immune receptor sequence landscape. Several methods for the computational and statistical analysis of large-scale AIRR-seq data have been developed to resolve immune repertoire complexity and to understand the dynamics of adaptive immunity. Here, we review the current research on (i diversity, (ii clustering and network, (iii phylogenetic, and (iv machine learning methods applied to dissect, quantify, and compare the architecture, evolution, and specificity of immune repertoires. We summarize outstanding questions in computational immunology and propose future directions for systems immunology toward coupling AIRR-seq with the computational discovery of immunotherapeutics, vaccines, and immunodiagnostics.
Sideband instability analysis based on a one-dimensional high-gain free electron laser model
Tsai, Cheng-Ying; Wu, Juhao; Yang, Chuan; Yoon, Moohyun; Zhou, Guanqun
2017-12-01
When an untapered high-gain free electron laser (FEL) reaches saturation, the exponential growth ceases and the radiation power starts to oscillate about an equilibrium. The FEL radiation power or efficiency can be increased by undulator tapering. For a high-gain tapered FEL, although the power is enhanced after the first saturation, it is known that there is a so-called second saturation where the FEL power growth stops even with a tapered undulator system. The sideband instability is one of the primary reasons leading to this second saturation. In this paper, we provide a quantitative analysis on how the gradient of undulator tapering can mitigate the sideband growth. The study is carried out semianalytically and compared with one-dimensional numerical simulations. The physical parameters are taken from Linac Coherent Light Source-like electron bunch and undulator systems. The sideband field gain and the evolution of the radiation spectra for different gradients of undulator tapering are examined. It is found that a strong undulator tapering (˜10 %) provides effective suppression of the sideband instability in the postsaturation regime.
Model-based Clustering of High-Dimensional Data in Astrophysics
Bouveyron, C.
2016-05-01
The nature of data in Astrophysics has changed, as in other scientific fields, in the past decades due to the increase of the measurement capabilities. As a consequence, data are nowadays frequently of high dimensionality and available in mass or stream. Model-based techniques for clustering are popular tools which are renowned for their probabilistic foundations and their flexibility. However, classical model-based techniques show a disappointing behavior in high-dimensional spaces which is mainly due to their dramatical over-parametrization. The recent developments in model-based classification overcome these drawbacks and allow to efficiently classify high-dimensional data, even in the "small n / large p" situation. This work presents a comprehensive review of these recent approaches, including regularization-based techniques, parsimonious modeling, subspace classification methods and classification methods based on variable selection. The use of these model-based methods is also illustrated on real-world classification problems in Astrophysics using R packages.
Robust and sparse correlation matrix estimation for the analysis of high-dimensional genomics data.
Serra, Angela; Coretto, Pietro; Fratello, Michele; Tagliaferri, Roberto; Stegle, Oliver
2018-02-15
Microarray technology can be used to study the expression of thousands of genes across a number of different experimental conditions, usually hundreds. The underlying principle is that genes sharing similar expression patterns, across different samples, can be part of the same co-expression system, or they may share the same biological functions. Groups of genes are usually identified based on cluster analysis. Clustering methods rely on the similarity matrix between genes. A common choice to measure similarity is to compute the sample correlation matrix. Dimensionality reduction is another popular data analysis task which is also based on covariance/correlation matrix estimates. Unfortunately, covariance/correlation matrix estimation suffers from the intrinsic noise present in high-dimensional data. Sources of noise are: sampling variations, presents of outlying sample units, and the fact that in most cases the number of units is much larger than the number of genes. In this paper, we propose a robust correlation matrix estimator that is regularized based on adaptive thresholding. The resulting method jointly tames the effects of the high-dimensionality, and data contamination. Computations are easy to implement and do not require hand tunings. Both simulated and real data are analyzed. A Monte Carlo experiment shows that the proposed method is capable of remarkable performances. Our correlation metric is more robust to outliers compared with the existing alternatives in two gene expression datasets. It is also shown how the regularization allows to automatically detect and filter spurious correlations. The same regularization is also extended to other less robust correlation measures. Finally, we apply the ARACNE algorithm on the SyNTreN gene expression data. Sensitivity and specificity of the reconstructed network is compared with the gold standard. We show that ARACNE performs better when it takes the proposed correlation matrix estimator as input. The R
Control and synchronisation of a novel seven-dimensional hyperchaotic system with active control
Varan, Metin; Akgul, Akif
2018-04-01
In this work, active control method is proposed for controlling and synchronising seven-dimensional (7D) hyperchaotic systems. The seven-dimensional hyperchaotic system is considered for the implementation. Seven-dimensional hyperchaotic system is also investigated via time series, phase portraits and bifurcation diagrams. For understanding the impact of active controllers on global asymptotic stability of synchronisation and control errors, the Lyapunov function is used. Numerical analysis is done to reveal the effectiveness of applied active control method and the results are discussed.
Instability of higher dimensional Yang-Mills systems
International Nuclear Information System (INIS)
Randjbar-Daemi, S.; Strathdee, J.
1983-01-01
We investigate the stability of Poincare xO(3) invariant solutions for a pure semi-simple Yang-Mills, as well as Yang-Mills coupled to gravity in 6-dimensional space-time compactified over M 4 xS 2 . In contrast to the Maxwell U(1) theory (IC-82/208) in six dimensions coupled with gravity and investigated previously, the present theory exhibits tachyonic excitations and is unstable. (author)
Evaluation of applicability of lead damper to 3-dimensional isolation system based on loading tests
International Nuclear Information System (INIS)
Matsuda, Akihiro
2003-01-01
To develop a damper for 3-dimensional base isolation system, horizontal and vertical mechanical properties, effect of loading frequency on vertical mechanical properties, coupled properties between horizontal and vertical directions, stability performance due to cyclic deformation are evaluated experimentally using scale models of lead damper originally developed for horizontal base isolation system. Loading test results are summarized as follows; 1) The lead damper has good vertical damping performance, in that the vertical yield load of the lead damper is three times as large as that for the horizontal direction, and the lead damper shows plastic behavior in the small deformation region. 2) The lead damper shows enough stability for static vertical displacement of ±40 mm. 3) the lead damper shows high stability performance for dynamic cyclic loading test using motions of isolation layer calculated by earthquake response analysis of FBR building subjected to S2-earthquake motion. Thus, applicability of the lead damper to 3-dimensional isolation system is shown from these results. (author)
Enhancing Three-dimensional Movement Control System for Assemblies of Machine-Building Facilities
Kuzyakov, O. N.; Andreeva, M. A.
2018-01-01
Aspects of enhancing three-dimensional movement control system are given in the paper. Such system is to be used while controlling assemblies of machine-building facilities, which is a relevant issue. The base of the system known is three-dimensional movement control device with optical principle of action. The device consists of multi point light emitter and light receiver matrix. The processing of signals is enhanced to increase accuracy of measurements by switching from discrete to analog signals. Light receiver matrix is divided into four areas, and the output value of each light emitter in each matrix area is proportional to its luminance level. Thus, determing output electric signal value of each light emitter in corresponding area leads to determing position of multipoint light emitter and position of object tracked. This is done by using Case-based reasoning method, the precedent in which is described as integral signal value of each matrix area, coordinates of light receivers, which luminance level is high, and decision to be made in this situation.
DEFF Research Database (Denmark)
Ding, Yunhong; Bacco, Davide; Dalgaard, Kjeld
2017-01-01
is intrinsically limited to 1 bit/photon. Here we propose and experimentally demonstrate, for the first time, a high-dimensional quantum key distribution protocol based on space division multiplexing in multicore fiber using silicon photonic integrated lightwave circuits. We successfully realized three mutually......-dimensional quantum states, and enables breaking the information efficiency limit of traditional quantum key distribution protocols. In addition, the silicon photonic circuits used in our work integrate variable optical attenuators, highly efficient multicore fiber couplers, and Mach-Zehnder interferometers, enabling...
Scanning three-dimensional x-ray diffraction microscopy using a high-energy microbeam
International Nuclear Information System (INIS)
Hayashi, Y.; Hirose, Y.; Seno, Y.
2016-01-01
A scanning three-dimensional X-ray diffraction (3DXRD) microscope apparatus with a high-energy microbeam was installed at the BL33XU Toyota beamline at SPring-8. The size of the 50 keV beam focused using Kirkpatrick-Baez mirrors was 1.3 μm wide and 1.6 μm high in full width at half maximum. The scanning 3DXRD method was tested for a cold-rolled carbon steel sheet sample. A three-dimensional orientation map with 37 "3 voxels was obtained.
Scanning three-dimensional x-ray diffraction microscopy using a high-energy microbeam
Energy Technology Data Exchange (ETDEWEB)
Hayashi, Y., E-mail: y-hayashi@mosk.tytlabs.co.jp; Hirose, Y.; Seno, Y. [Toyota Central R& D Toyota Central R& D Labs., Inc., 41-1 Nagakute Aichi 480-1192 Japan (Japan)
2016-07-27
A scanning three-dimensional X-ray diffraction (3DXRD) microscope apparatus with a high-energy microbeam was installed at the BL33XU Toyota beamline at SPring-8. The size of the 50 keV beam focused using Kirkpatrick-Baez mirrors was 1.3 μm wide and 1.6 μm high in full width at half maximum. The scanning 3DXRD method was tested for a cold-rolled carbon steel sheet sample. A three-dimensional orientation map with 37 {sup 3} voxels was obtained.
Directory of Open Access Journals (Sweden)
Thenmozhi Srinivasan
2015-01-01
Full Text Available Clusters of high-dimensional data techniques are emerging, according to data noisy and poor quality challenges. This paper has been developed to cluster data using high-dimensional similarity based PCM (SPCM, with ant colony optimization intelligence which is effective in clustering nonspatial data without getting knowledge about cluster number from the user. The PCM becomes similarity based by using mountain method with it. Though this is efficient clustering, it is checked for optimization using ant colony algorithm with swarm intelligence. Thus the scalable clustering technique is obtained and the evaluation results are checked with synthetic datasets.
The validation and assessment of machine learning: a game of prediction from high-dimensional data
DEFF Research Database (Denmark)
Pers, Tune Hannes; Albrechtsen, A; Holst, C
2009-01-01
In applied statistics, tools from machine learning are popular for analyzing complex and high-dimensional data. However, few theoretical results are available that could guide to the appropriate machine learning tool in a new application. Initial development of an overall strategy thus often...... the ideas, the game is applied to data from the Nugenob Study where the aim is to predict the fat oxidation capacity based on conventional factors and high-dimensional metabolomics data. Three players have chosen to use support vector machines, LASSO, and random forests, respectively....
Highly ordered three-dimensional macroporous carbon spheres for determination of heavy metal ions
Energy Technology Data Exchange (ETDEWEB)
Zhang, Yuxiao; Zhang, Jianming [Institute of Functional Nano and Soft Materials (FUNSOM) and Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123 (China); Liu, Yang, E-mail: yangl@suda.edu.cn [Institute of Functional Nano and Soft Materials (FUNSOM) and Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123 (China); Huang, Hui [Institute of Functional Nano and Soft Materials (FUNSOM) and Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123 (China); Kang, Zhenhui, E-mail: zhkang@suda.edu.cn [Institute of Functional Nano and Soft Materials (FUNSOM) and Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123 (China)
2012-04-15
Highlights: Black-Right-Pointing-Pointer Highly ordered three dimensional macroporous carbon spheres (MPCSs) were prepared. Black-Right-Pointing-Pointer MPCS was covalently modified by cysteine (MPCS-CO-Cys). Black-Right-Pointing-Pointer MPCS-CO-Cys was first time used in electrochemical detection of heavy metal ions. Black-Right-Pointing-Pointer Heavy metal ions such as Pb{sup 2+} and Cd{sup 2+} can be simultaneously determined. -- Abstract: An effective voltammetric method for detection of trace heavy metal ions using chemically modified highly ordered three dimensional macroporous carbon spheres electrode surfaces is described. The highly ordered three dimensional macroporous carbon spheres were prepared by carbonization of glucose in silica crystal bead template, followed by removal of the template. The highly ordered three dimensional macroporous carbon spheres were covalently modified by cysteine, an amino acid with high affinities towards some heavy metals. The materials were characterized by physical adsorption of nitrogen, scanning electron microscopy, and transmission electron microscopy techniques. While the Fourier-transform infrared spectroscopy was used to characterize the functional groups on the surface of carbon spheres. High sensitivity was exhibited when this material was used in electrochemical detection (square wave anodic stripping voltammetry) of heavy metal ions due to the porous structure. And the potential application for simultaneous detection of heavy metal ions was also investigated.
Highly ordered three-dimensional macroporous carbon spheres for determination of heavy metal ions
International Nuclear Information System (INIS)
Zhang, Yuxiao; Zhang, Jianming; Liu, Yang; Huang, Hui; Kang, Zhenhui
2012-01-01
Highlights: ► Highly ordered three dimensional macroporous carbon spheres (MPCSs) were prepared. ► MPCS was covalently modified by cysteine (MPCS–CO–Cys). ► MPCS–CO–Cys was first time used in electrochemical detection of heavy metal ions. ► Heavy metal ions such as Pb 2+ and Cd 2+ can be simultaneously determined. -- Abstract: An effective voltammetric method for detection of trace heavy metal ions using chemically modified highly ordered three dimensional macroporous carbon spheres electrode surfaces is described. The highly ordered three dimensional macroporous carbon spheres were prepared by carbonization of glucose in silica crystal bead template, followed by removal of the template. The highly ordered three dimensional macroporous carbon spheres were covalently modified by cysteine, an amino acid with high affinities towards some heavy metals. The materials were characterized by physical adsorption of nitrogen, scanning electron microscopy, and transmission electron microscopy techniques. While the Fourier-transform infrared spectroscopy was used to characterize the functional groups on the surface of carbon spheres. High sensitivity was exhibited when this material was used in electrochemical detection (square wave anodic stripping voltammetry) of heavy metal ions due to the porous structure. And the potential application for simultaneous detection of heavy metal ions was also investigated.
Shaffer, Patrick; Valsson, Omar; Parrinello, Michele
2016-02-02
The capabilities of molecular simulations have been greatly extended by a number of widely used enhanced sampling methods that facilitate escaping from metastable states and crossing large barriers. Despite these developments there are still many problems which remain out of reach for these methods which has led to a vigorous effort in this area. One of the most important problems that remains unsolved is sampling high-dimensional free-energy landscapes and systems that are not easily described by a small number of collective variables. In this work we demonstrate a new way to compute free-energy landscapes of high dimensionality based on the previously introduced variationally enhanced sampling, and we apply it to the miniprotein chignolin.
Shaffer, Patrick; Valsson, Omar; Parrinello, Michele
2016-01-01
The capabilities of molecular simulations have been greatly extended by a number of widely used enhanced sampling methods that facilitate escaping from metastable states and crossing large barriers. Despite these developments there are still many problems which remain out of reach for these methods which has led to a vigorous effort in this area. One of the most important problems that remains unsolved is sampling high-dimensional free-energy landscapes and systems that are not easily described by a small number of collective variables. In this work we demonstrate a new way to compute free-energy landscapes of high dimensionality based on the previously introduced variationally enhanced sampling, and we apply it to the miniprotein chignolin. PMID:26787868
Characterization of discontinuities in high-dimensional stochastic problems on adaptive sparse grids
International Nuclear Information System (INIS)
Jakeman, John D.; Archibald, Richard; Xiu Dongbin
2011-01-01
In this paper we present a set of efficient algorithms for detection and identification of discontinuities in high dimensional space. The method is based on extension of polynomial annihilation for discontinuity detection in low dimensions. Compared to the earlier work, the present method poses significant improvements for high dimensional problems. The core of the algorithms relies on adaptive refinement of sparse grids. It is demonstrated that in the commonly encountered cases where a discontinuity resides on a small subset of the dimensions, the present method becomes 'optimal', in the sense that the total number of points required for function evaluations depends linearly on the dimensionality of the space. The details of the algorithms will be presented and various numerical examples are utilized to demonstrate the efficacy of the method.
Non-intrusive low-rank separated approximation of high-dimensional stochastic models
Doostan, Alireza; Validi, AbdoulAhad; Iaccarino, Gianluca
2013-01-01
This work proposes a sampling-based (non-intrusive) approach within the context of low-. rank separated representations to tackle the issue of curse-of-dimensionality associated with the solution of models, e.g., PDEs/ODEs, with high-dimensional random inputs. Under some conditions discussed in details, the number of random realizations of the solution, required for a successful approximation, grows linearly with respect to the number of random inputs. The construction of the separated representation is achieved via a regularized alternating least-squares regression, together with an error indicator to estimate model parameters. The computational complexity of such a construction is quadratic in the number of random inputs. The performance of the method is investigated through its application to three numerical examples including two ODE problems with high-dimensional random inputs. © 2013 Elsevier B.V.
Non-intrusive low-rank separated approximation of high-dimensional stochastic models
Doostan, Alireza
2013-08-01
This work proposes a sampling-based (non-intrusive) approach within the context of low-. rank separated representations to tackle the issue of curse-of-dimensionality associated with the solution of models, e.g., PDEs/ODEs, with high-dimensional random inputs. Under some conditions discussed in details, the number of random realizations of the solution, required for a successful approximation, grows linearly with respect to the number of random inputs. The construction of the separated representation is achieved via a regularized alternating least-squares regression, together with an error indicator to estimate model parameters. The computational complexity of such a construction is quadratic in the number of random inputs. The performance of the method is investigated through its application to three numerical examples including two ODE problems with high-dimensional random inputs. © 2013 Elsevier B.V.
Statistical Analysis for High-Dimensional Data : The Abel Symposium 2014
Bühlmann, Peter; Glad, Ingrid; Langaas, Mette; Richardson, Sylvia; Vannucci, Marina
2016-01-01
This book features research contributions from The Abel Symposium on Statistical Analysis for High Dimensional Data, held in Nyvågar, Lofoten, Norway, in May 2014. The focus of the symposium was on statistical and machine learning methodologies specifically developed for inference in “big data” situations, with particular reference to genomic applications. The contributors, who are among the most prominent researchers on the theory of statistics for high dimensional inference, present new theories and methods, as well as challenging applications and computational solutions. Specific themes include, among others, variable selection and screening, penalised regression, sparsity, thresholding, low dimensional structures, computational challenges, non-convex situations, learning graphical models, sparse covariance and precision matrices, semi- and non-parametric formulations, multiple testing, classification, factor models, clustering, and preselection. Highlighting cutting-edge research and casting light on...
Energy Technology Data Exchange (ETDEWEB)
NONE
2000-03-01
The system manipulates such bio-materials as cells, DNA (deoxyribonucleic acid), etc., 3-dimensionally in the micro/nano scale domain. In the field of screening and transportation technology, a device is improved which selectively and speedily extracts a required one out of a great quantity of microbes dispersed in a solution. The target microbe is trapped in a laser beam and moved, and then collected. In the case of yeast, a cell is extracted in 10 seconds. The system separates a target microbe with a probability of 60%. For improvement on operability in dissecting cells and the like using a 3-dimensional micromanipulation system, a device is improved which positions objects in a liquid. The effect of dielectrophoresic force and rotating torque on yeast cells is confirmed. An improved micro triaxial force sensor is incorporated into the device. Based on this device, a master-slave system is constructed, remotely controllable and capable of triaxial force measurement, and force sense presenting algorithm is incorporated into the system for the realization of cell operation through position and force control. The development of microscopic processing technologies such as X-ray lithography is also explained. (NEDO)
International Nuclear Information System (INIS)
Oku, H.; Ogawa, N.; Ishikawa, M.; Hashimoto, K.
2005-01-01
In this article, a micro-organism tracking system using a high-speed vision system is reported. This system two dimensionally tracks a freely swimming micro-organism within the field of an optical microscope by moving a chamber of target micro-organisms based on high-speed visual feedback. The system we developed could track a paramecium using various imaging techniques, including bright-field illumination, dark-field illumination, and differential interference contrast, at magnifications of 5 times and 20 times. A maximum tracking duration of 300 s was demonstrated. Also, the system could track an object with a velocity of up to 35 000 μm/s (175 diameters/s), which is significantly faster than swimming micro-organisms
Monolithic three-dimensional electrochemical energy storage system on aerogel or nanotube scaffold
Farmer, Joseph C; Stadermann, Michael
2013-11-12
A monolithic three-dimensional electrochemical energy storage system is provided on an aerogel or nanotube scaffold. An anode, separator, cathode, and cathodic current collector are deposited on the aerogel or nanotube scaffold.
On the absence of order in 2-dimensional systems with compact symmetry
International Nuclear Information System (INIS)
Bruschi, M.L.; Garcia, A.A.; Masperi, L.; Garcia Canal, C.A.
1984-01-01
An alternative proof for the generalization to any compact Lie group of the absence of an ordered phase in one and two dimensional classical systems is provided using the original Bogoliubov inequality. (Author) [pt
International Nuclear Information System (INIS)
Ma Songhua; Fang Jianping; Zheng Chunlong
2009-01-01
By means of an extended mapping method and a variable separation method, a series of solitary wave solutions, periodic wave solutions and variable separation solutions to the (2 + 1)-dimensional breaking soliton system is derived.
System and method for three-dimensional image reconstruction using an absolute orientation sensor
Giancola, Silvio; Ghanem, Bernard; Schneider, Jens; Wonka, Peter
2018-01-01
A three-dimensional image reconstruction system includes an image capture device, an inertial measurement unit (IMU), and an image processor. The image capture device captures image data. The inertial measurement unit (IMU) is affixed to the image
Investigation of advanced materials based on low-dimensional systems
Energy Technology Data Exchange (ETDEWEB)
Babenkov, Sergey
2016-11-15
In the framework of this thesis, a new end-station dedicated for dynamic-XPS measurements is created. The end-station is based on a new hemispherical electron spectrometer Argus which is equipped with a high speed detection system. In combination with the high brilliance XUV beamline P04 at PETRA III it provides users a unique tool for fast (down to 0.1 s/spectrum) and detailed investigations compared to existing XPS devices at other synchrotrons. This end-station is integrated into beamline P04 and available for users. During this research work it was widely used for fabrication of samples (Ar{sup +} sputtering, sample heating, film growth etc) and investigation of their properties by means of dynamic-XPS. Using several methods, the atomic and electronic structure of graphene grown on technically relevant substrates of cubic-SiC(001)/Si(001) (''on-axis'' and ''vicinal'') was investigated. We have shown a way to control the number of graphene layers by real-time photoemission measurements during preparation procedure. Using this approach, we have synthesized several samples with different numbers of graphene layers. Consequent atomically resolved STM studies prove the synthesis of a uniform, millimeter-scale graphene overlayer. At the same time, the graphene overlayer possesses rippled morphology and consists of large amount of domain boundaries. Directions of domain boundaries coincide with the directions of carbon atomic chains which were fabricated prior to graphene synthesis on the SiC(001)-c(2 x 2) surface reconstruction. Further, using vicinal-SiC, we synthesized Bernal-stacked trilayer graphene with self-aligned periodic nanodomain boundaries. We proposed a simple method to achieve a current On-Off ratio of 104 by opening a transport gap in Bernal-stacked trilayer graphene. Our low-temperature transport measurements clearly demonstrate that the self-aligned periodic NBs can induce a charge transport gap greater than 1
Investigation of advanced materials based on low-dimensional systems
International Nuclear Information System (INIS)
Babenkov, Sergey
2016-11-01
In the framework of this thesis, a new end-station dedicated for dynamic-XPS measurements is created. The end-station is based on a new hemispherical electron spectrometer Argus which is equipped with a high speed detection system. In combination with the high brilliance XUV beamline P04 at PETRA III it provides users a unique tool for fast (down to 0.1 s/spectrum) and detailed investigations compared to existing XPS devices at other synchrotrons. This end-station is integrated into beamline P04 and available for users. During this research work it was widely used for fabrication of samples (Ar"+ sputtering, sample heating, film growth etc) and investigation of their properties by means of dynamic-XPS. Using several methods, the atomic and electronic structure of graphene grown on technically relevant substrates of cubic-SiC(001)/Si(001) (''on-axis'' and ''vicinal'') was investigated. We have shown a way to control the number of graphene layers by real-time photoemission measurements during preparation procedure. Using this approach, we have synthesized several samples with different numbers of graphene layers. Consequent atomically resolved STM studies prove the synthesis of a uniform, millimeter-scale graphene overlayer. At the same time, the graphene overlayer possesses rippled morphology and consists of large amount of domain boundaries. Directions of domain boundaries coincide with the directions of carbon atomic chains which were fabricated prior to graphene synthesis on the SiC(001)-c(2 x 2) surface reconstruction. Further, using vicinal-SiC, we synthesized Bernal-stacked trilayer graphene with self-aligned periodic nanodomain boundaries. We proposed a simple method to achieve a current On-Off ratio of 104 by opening a transport gap in Bernal-stacked trilayer graphene. Our low-temperature transport measurements clearly demonstrate that the self-aligned periodic NBs can induce a charge transport gap greater than 1.3 eV. More remarkably, the transport gap of
Directory of Open Access Journals (Sweden)
Zhao Yan
2016-01-01
Full Text Available An improved backstepping control method for three-dimensional trajectory tracking of a midwater trawl system is investigated. A new mathematical model of the trawl system while considering the horizontal expansion effect of two otter boards is presented based on the Newton Euler method. Subsequently, an active path tracking strategy of the trawl system based on the backstepping method is proposed. The nonstrict feedback characteristic of the proposed model employs a control allocation method and several parallel nonlinear PID (Proportion Integration Differentiation controllers to eliminate the high-order state variables. Then, the stability analysis by the Lyapunov Stability Theory shows that the proposed controller can maintain the stability of the trawl system even with the presence of external disturbances. To validate the proposed controller, a simulation comparison with a linear PID controller was conducted. The simulation results illustrate that the improved backstepping controller is effective for three-dimensional trajectory tracking of the midwater trawl system.
Density of states of two-dimensional systems with long-range logarithmic interactions
Energy Technology Data Exchange (ETDEWEB)
Somoza, Andrés M.; Ortuño, Miguel; Baturina, Tatyana I.; Vinokur, Valerii M.
2015-08-03
We investigate a single-particle density of states (DOS) in strongly disordered two- dimensional high dielectric permittivity systems with logarithmic Coulomb interaction between particles. We derive self-consistent DOS at zero temperature and show that it is appreciably suppressed as compared to the DOS expected from the Efros-Shklovskii approach.We carry out zero- and finite-temperature Monte Carlo numerical studies of the DOS and find the perfect agreement between the numerical and analytical results at zero temperature, observing, in particular, a hardening of the Coulomb gap with the increasing electrostatic screening length. At finite temperatures, we reveal a striking scaling of the DOS as a function of energy normalized to the temperature of the system.
Three-Dimensional Design of a Non-Axisymmetric Periodic Permanent Magnet Focusing System
Chen Chi Ping; Radovinsky, Alexey; Zhou, Jing
2005-01-01
A three-dimensional (3D) design is presented of a non-axisymmetric periodic permanent magnet focusing system which will be used to focus a large-aspect-ratio, ellipse-shaped, space-charge-dominated electron beam. In this design, an analytic theory is used to specify the magnetic profile for beam transport. The OPERA3D code is used to compute and optimize a realizable magnet system. Results of the magnetic design are verified by two-dimensional particle-in-cell and three-dimensional trajectory simulations of beam propagation using PFB2D and OMNITRAK, respectively. Results of fabrication tolerance studies are discussed.
On the generating function of Poincare plots defining one dimensional perturbed Hamiltonian systems
International Nuclear Information System (INIS)
Montvai, A.
1989-01-01
A simple numerical method has been devised, for deriving the generating function of an arbitrary, one dimensional Hamiltonian system represented by its Poincare plot. In this case, the plot to be numerically processed is an area preserving transformation of a two-dimensional surface onto itself. Although the method in its present form is capable of treating only this case, there are no principal restrictions excluding the analysis of systems with higher dimensionality as well. As an example, the generating function of the motion of alpha particles in a nonsymmetric, toroidal magnetic field is derived and studied numerically. (orig.)
International Nuclear Information System (INIS)
Zheng Chunlong; Qiang Jiye; Wang Shaohua
2010-01-01
In the paper, the variable separation approach, homoclinic test technique and bilinear method are successfully extended to a (1 + 1)-dimensional Caudry-Dodd-Gibbon-Sawada-Kortera (CDGSK) system, respectively. Based on the derived exact solutions, some significant types of localized excitations such as standing waves, periodic waves, solitary waves are simultaneously derived from the (1 + 1)-dimensional Caudry-Dodd-Gibbon-Sawada-Kortera system by entrancing appropriate parameters. (general)
Magnetoresistance of amorphous CuZr: weak localization in a three dimensional system
International Nuclear Information System (INIS)
Bieri, J.B.; Fert, A.; Creuzet, G.
1984-01-01
Observations of anomalous magnetoresistance in amorphous CuZr at low temperature are reported. The magnetoresistance can be precisely accounted for in theoretical models of localization for 3-dimensional metallic systems in the presence of strong spin-orbit interactions (with a significant additional contribution from the quenching of superconducting fluctuations at the lowest temperatures). Magnetoresistance measurements on various other systems show that such 3-dimensional localization effects are very generally observed in amorphous alloys. (author)
Large angle and high linearity two-dimensional laser scanner based on voice coil actuators
Wu, Xin; Chen, Sihai; Chen, Wei; Yang, Minghui; Fu, Wen
2011-10-01
A large angle and high linearity two-dimensional laser scanner with an in-house ingenious deflection angle detecting system is developed based on voice coil actuators direct driving mechanism. The specially designed voice coil actuators make the steering mirror moving at a sufficiently large angle. Frequency sweep method based on virtual instruments is employed to achieve the natural frequency of the laser scanner. The response shows that the performance of the laser scanner is limited by the mechanical resonances. The closed-loop controller based on mathematical model is used to reduce the oscillation of the laser scanner at resonance frequency. To design a qualified controller, the model of the laser scanner is set up. The transfer function of the model is identified with MATLAB according to the tested data. After introducing of the controller, the nonlinearity decreases from 13.75% to 2.67% at 50 Hz. The laser scanner also has other advantages such as large deflection mirror, small mechanical structure, and high scanning speed.
A novel three-dimensional and high-definition flexible scope.
Nishiyama, Kenichi; Natori, Yoshihiro; Oka, Kazunari
2014-06-01
Recent high-tech innovations in digital surgical technology have led to advances in three-dimensional (3D) and high-definition (HD) operating scopes. We introduce a novel 3D-HD flexible surgical scope called "3D-Eye-Flex" and evaluate its utility as an alternative to the operating microscope. The 3D-Eye-Flex has a 15 mm long 3D-HD scope-head with a 15 mm outer diameter, a focus distance of 18-100 mm and 80° angle of view. Attached to a 615-mm-long flexible bellows, 3D-Eye-Flex can be easily fixed to the operating table. Microsurgical dissection of wet brain tissue and drilling a skull base model were performed under the scope while using the 3D-HD video monitor. This scope system provided excellent illumination and image quality during the procedures. A large depth of field with stereoscopic vision had a greater advantage over using an operating microscope. 3D-Eye-Flex was easy to manipulate and provided an abundance of space above the operative field. Surgeons felt comfortable while working and could easily shift the position of the scope. This novel 3D-HD flexible scope is an effective alternative to the operating microscope as a new surgeon's eye and will be suitable for digital image-based surgery with further refinement.
A variational Bayesian multiple particle filtering scheme for large-dimensional systems
Ait-El-Fquih, Boujemaa
2016-06-14
This paper considers the Bayesian filtering problem in high-dimensional nonlinear state-space systems. In such systems, classical particle filters (PFs) are impractical due to the prohibitive number of required particles to obtain reasonable performances. One approach that has been introduced to overcome this problem is the concept of multiple PFs (MPFs), where the state-space is split into low-dimensional subspaces and then a separate PF is applied to each subspace. Remarkable performances of MPF-like filters motivated our investigation here into a new strategy that combines the variational Bayesian approach to split the state-space with random sampling techniques, to derive a new computationally efficient MPF. The propagation of each particle in the prediction step of the resulting filter requires generating only a single particle in contrast with standard MPFs, for which a set of (children) particles is required. We present simulation results to evaluate the behavior of the proposed filter and compare its performances against standard PF and a MPF.
A variational Bayesian multiple particle filtering scheme for large-dimensional systems
Ait-El-Fquih, Boujemaa; Hoteit, Ibrahim
2016-01-01
This paper considers the Bayesian filtering problem in high-dimensional nonlinear state-space systems. In such systems, classical particle filters (PFs) are impractical due to the prohibitive number of required particles to obtain reasonable performances. One approach that has been introduced to overcome this problem is the concept of multiple PFs (MPFs), where the state-space is split into low-dimensional subspaces and then a separate PF is applied to each subspace. Remarkable performances of MPF-like filters motivated our investigation here into a new strategy that combines the variational Bayesian approach to split the state-space with random sampling techniques, to derive a new computationally efficient MPF. The propagation of each particle in the prediction step of the resulting filter requires generating only a single particle in contrast with standard MPFs, for which a set of (children) particles is required. We present simulation results to evaluate the behavior of the proposed filter and compare its performances against standard PF and a MPF.
An irregular grid approach for pricing high-dimensional American options
Berridge, S.J.; Schumacher, J.M.
2008-01-01
We propose and test a new method for pricing American options in a high-dimensional setting. The method is centered around the approximation of the associated complementarity problem on an irregular grid. We approximate the partial differential operator on this grid by appealing to the SDE
Can We Train Machine Learning Methods to Outperform the High-dimensional Propensity Score Algorithm?
Karim, Mohammad Ehsanul; Pang, Menglan; Platt, Robert W
2018-03-01
The use of retrospective health care claims datasets is frequently criticized for the lack of complete information on potential confounders. Utilizing patient's health status-related information from claims datasets as surrogates or proxies for mismeasured and unobserved confounders, the high-dimensional propensity score algorithm enables us to reduce bias. Using a previously published cohort study of postmyocardial infarction statin use (1998-2012), we compare the performance of the algorithm with a number of popular machine learning approaches for confounder selection in high-dimensional covariate spaces: random forest, least absolute shrinkage and selection operator, and elastic net. Our results suggest that, when the data analysis is done with epidemiologic principles in mind, machine learning methods perform as well as the high-dimensional propensity score algorithm. Using a plasmode framework that mimicked the empirical data, we also showed that a hybrid of machine learning and high-dimensional propensity score algorithms generally perform slightly better than both in terms of mean squared error, when a bias-based analysis is used.
CSIR Research Space (South Africa)
Giovannini, D
2013-06-01
Full Text Available : QELS_Fundamental Science, San Jose, California United States, 9-14 June 2013 Reconstruction of High-Dimensional States Entangled in Orbital Angular Momentum Using Mutually Unbiased Measurements D. Giovannini1, ⇤, J. Romero1, 2, J. Leach3, A...
Three-dimensionality of field-induced magnetism in a high-temperature superconductor
DEFF Research Database (Denmark)
Lake, B.; Lefmann, K.; Christensen, N.B.
2005-01-01
Many physical properties of high-temperature superconductors are two-dimensional phenomena derived from their square-planar CuO(2) building blocks. This is especially true of the magnetism from the copper ions. As mobile charge carriers enter the CuO(2) layers, the antiferromagnetism of the parent...
Ferdosi, Bilkis J.; Buddelmeijer, Hugo; Trager, Scott; Wilkinson, Michael H.F.; Roerdink, Jos B.T.M.
2010-01-01
Data sets in astronomy are growing to enormous sizes. Modern astronomical surveys provide not only image data but also catalogues of millions of objects (stars, galaxies), each object with hundreds of associated parameters. Exploration of this very high-dimensional data space poses a huge challenge.
High-Dimensional Exploratory Item Factor Analysis by a Metropolis-Hastings Robbins-Monro Algorithm
Cai, Li
2010-01-01
A Metropolis-Hastings Robbins-Monro (MH-RM) algorithm for high-dimensional maximum marginal likelihood exploratory item factor analysis is proposed. The sequence of estimates from the MH-RM algorithm converges with probability one to the maximum likelihood solution. Details on the computer implementation of this algorithm are provided. The…
Estimating the effect of a variable in a high-dimensional regression model
DEFF Research Database (Denmark)
Jensen, Peter Sandholt; Wurtz, Allan
assume that the effect is identified in a high-dimensional linear model specified by unconditional moment restrictions. We consider properties of the following methods, which rely on lowdimensional models to infer the effect: Extreme bounds analysis, the minimum t-statistic over models, Sala...
Multi-Scale Factor Analysis of High-Dimensional Brain Signals
Ting, Chee-Ming; Ombao, Hernando; Salleh, Sh-Hussain
2017-01-01
In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive
Spectrally-Corrected Estimation for High-Dimensional Markowitz Mean-Variance Optimization
Z. Bai (Zhidong); H. Li (Hua); M.J. McAleer (Michael); W.-K. Wong (Wing-Keung)
2016-01-01
textabstractThis paper considers the portfolio problem for high dimensional data when the dimension and size are both large. We analyze the traditional Markowitz mean-variance (MV) portfolio by large dimension matrix theory, and find the spectral distribution of the sample covariance is the main
Berridge, S.J.; Schumacher, J.M.
2004-01-01
We propose a method for pricing high-dimensional American options on an irregular grid; the method involves using quadratic functions to approximate the local effect of the Black-Scholes operator.Once such an approximation is known, one can solve the pricing problem by time stepping in an explicit
An Irregular Grid Approach for Pricing High-Dimensional American Options
Berridge, S.J.; Schumacher, J.M.
2004-01-01
We propose and test a new method for pricing American options in a high-dimensional setting.The method is centred around the approximation of the associated complementarity problem on an irregular grid.We approximate the partial differential operator on this grid by appealing to the SDE
Pricing and hedging high-dimensional American options : an irregular grid approach
Berridge, S.; Schumacher, H.
2002-01-01
We propose and test a new method for pricing American options in a high dimensional setting. The method is centred around the approximation of the associated variational inequality on an irregular grid. We approximate the partial differential operator on this grid by appealing to the SDE
Electrical detection of spin transport in Si two-dimensional electron gas systems
Chang, Li-Te; Fischer, Inga Anita; Tang, Jianshi; Wang, Chiu-Yen; Yu, Guoqiang; Fan, Yabin; Murata, Koichi; Nie, Tianxiao; Oehme, Michael; Schulze, Jörg; Wang, Kang L.
2016-09-01
Spin transport in a semiconductor-based two-dimensional electron gas (2DEG) system has been attractive in spintronics for more than ten years. The inherent advantages of high-mobility channel and enhanced spin-orbital interaction promise a long spin diffusion length and efficient spin manipulation, which are essential for the application of spintronics devices. However, the difficulty of making high-quality ferromagnetic (FM) contacts to the buried 2DEG channel in the heterostructure systems limits the potential developments in functional devices. In this paper, we experimentally demonstrate electrical detection of spin transport in a high-mobility 2DEG system using FM Mn-germanosilicide (Mn(Si0.7Ge0.3)x) end contacts, which is the first report of spin injection and detection in a 2DEG confined in a Si/SiGe modulation doped quantum well structure (MODQW). The extracted spin diffusion length and lifetime are l sf = 4.5 μm and {τ }{{s}}=16 {{ns}} at 1.9 K respectively. Our results provide a promising approach for spin injection into 2DEG system in the Si-based MODQW, which may lead to innovative spintronic applications such as spin-based transistor, logic, and memory devices.
International Nuclear Information System (INIS)
Schlottmann, P.
1998-01-01
Properties of highly correlated electrons, such as heavy fermion compounds, metal-insulator transitions, one-dimensional conductors and systems of restricted dimensionality are studied theoretically. The main focus is on Kondo insulators and impurity bands due to Kondo holes, the low-temperature magnetoresistivity of heavy fermion alloys, the n-channel Kondo problem, mesoscopic systems and one-dimensional conductors
Ouyang, X.; Leonards, P.E.G.; Legler, J.; van der Oost, R.; de Boer, J.; Lamoree, M.H.
2015-01-01
For the first time a comprehensive two-dimensional liquid chromatography (LC. ×. LC) system coupled with a high resolution time-of-flight mass spectrometer (HR-ToF MS) was developed and applied for analysis of emerging toxicants in wastewater effluent. The system was optimized and validated using
Unlabored system motion by specially conditioned electromagnetic fields in higher dimensional realms
David Froning, H.; Meholic, Gregory V.
2010-01-01
This third of three papers explores the possibility of swift, stress-less system transitions between slower-than-light and faster-than-light speeds with negligible net expenditure of system energetics. The previous papers derived a realm of higher dimensionality than 4-D spacetime that enabled such unlabored motion; and showed that fields that could propel and guide systems on unlabored paths in the higher dimensional realm must be fields that have been conditioned to SU(2) (or higher) Lie group symmetry. This paper shows that the system's surrounding vacuum dielectric ɛμ, within the higher dimensional realm's is a vector (not scalar) quantity with fixed magnitude ɛ0μ0 and changing direction within the realm with changing system speed. Thus, ɛμ generated by the system's EM field must remain tuned to vacuum ɛ0μ0 in both magnitude and direction during swift, unlabored system transitions between slower and faster than light speeds. As a result, the system's changing path and speed is such that the magnitude of the higher dimensional realm's ɛ0μ0 is not disturbed. And it is shown that a system's flight trajectories associated with its swift, unlabored transitions between zero and infinite speed can be represented by curved paths traced-out within the higher dimensional realm.
Computer controlled high voltage system
Energy Technology Data Exchange (ETDEWEB)
Kunov, B; Georgiev, G; Dimitrov, L [and others
1996-12-31
A multichannel computer controlled high-voltage power supply system is developed. The basic technical parameters of the system are: output voltage -100-3000 V, output current - 0-3 mA, maximum number of channels in one crate - 78. 3 refs.
Zero- and two-dimensional hybrid carbon phosphors for high colorimetric purity white light-emission.
Ding, Yamei; Chang, Qing; Xiu, Fei; Chen, Yingying; Liu, Zhengdong; Ban, Chaoyi; Cheng, Shuai; Liu, Juqing; Huang, Wei
2018-03-01
Carbon nanomaterials are promising phosphors for white light emission. A facile single-step synthesis method has been developed to prepare zero- and two-dimensional hybrid carbon phosphors for the first time. Zero-dimensional carbon dots (C-dots) emit bright blue luminescence under 365 nm UV light and two-dimensional nanoplates improve the dispersity and film forming ability of C-dots. As a proof-of-concept application, the as-prepared hybrid carbon phosphors emit bright white luminescence in the solid state, and the phosphor-coated blue LEDs exhibit high colorimetric purity white light-emission with a color coordinate of (0.3308, 0.3312), potentially enabling the successful application of white emitting phosphors in the LED field.
On Interconnections of Infinite-dimensional Port-Hamiltonian Systems
Pasumarthy, Ramkrishna; Schaft, Arjan J. van der
2004-01-01
Network modeling of complex physical systems leads to a class of nonlinear systems called port-Hamiltonian systems, which are defined with respect to a Dirac structure (a geometric structure which formalizes the power-conserving interconnection structure of the system). A power conserving
On interconnections of infinite-dimensional port-Hamiltonian systems
Ramkrishna Pasumarthy, R.P.; van der Schaft, Arjan
2004-01-01
Network modeling of complex physical systems leads to a class of nonlinear systems called port-Hamiltonian systems, which are defined with respect to a Dirac structure (a geometric structure which formalizes the power-conserving interconnection structure of the system). A power conserving
High magnetic field MRI system
International Nuclear Information System (INIS)
Maeda, Hideaki; Urata, Masami; Satoh, Kozo
1990-01-01
A high field superconducting magnet, 4-5 T in central magnetic field, is required for magnetic resonance spectroscopic imaging (MRSI) on 31 P, essential nuclei for energy metabolism of human body. This paper reviews superconducting magnets for high field MRSI systems. Examples of the cross-sectional image and the spectrum of living animals are shown in the paper. (author)
Hypergraph-based anomaly detection of high-dimensional co-occurrences.
Silva, Jorge; Willett, Rebecca
2009-03-01
This paper addresses the problem of detecting anomalous multivariate co-occurrences using a limited number of unlabeled training observations. A novel method based on using a hypergraph representation of the data is proposed to deal with this very high-dimensional problem. Hypergraphs constitute an important extension of graphs which allow edges to connect more than two vertices simultaneously. A variational Expectation-Maximization algorithm for detecting anomalies directly on the hypergraph domain without any feature selection or dimensionality reduction is presented. The resulting estimate can be used to calculate a measure of anomalousness based on the False Discovery Rate. The algorithm has O(np) computational complexity, where n is the number of training observations and p is the number of potential participants in each co-occurrence event. This efficiency makes the method ideally suited for very high-dimensional settings, and requires no tuning, bandwidth or regularization parameters. The proposed approach is validated on both high-dimensional synthetic data and the Enron email database, where p > 75,000, and it is shown that it can outperform other state-of-the-art methods.
Pattern formation in three-dimensional reaction-diffusion systems
Callahan, T. K.; Knobloch, E.
1999-08-01
Existing group theoretic analysis of pattern formation in three dimensions [T.K. Callahan, E. Knobloch, Symmetry-breaking bifurcations on cubic lattices, Nonlinearity 10 (1997) 1179-1216] is used to make specific predictions about the formation of three-dimensional patterns in two models of the Turing instability, the Brusselator model and the Lengyel-Epstein model. Spatially periodic patterns having the periodicity of the simple cubic (SC), face-centered cubic (FCC) or body-centered cubic (BCC) lattices are considered. An efficient center manifold reduction is described and used to identify parameter regimes permitting stable lamellæ, SC, FCC, double-diamond, hexagonal prism, BCC and BCCI states. Both models possess a special wavenumber k* at which the normal form coefficients take on fixed model-independent ratios and both are described by identical bifurcation diagrams. This property is generic for two-species chemical reaction-diffusion models with a single activator and inhibitor.
Charge and spin separation in one-dimensional systems
International Nuclear Information System (INIS)
Balseiro, C.A.; Jagla, E.A.; Hallberg, K.
1995-01-01
In this article we discuss charge and spin separation and quantum interference in one-dimensional models. After a short introduction we briefly present the Hubbard and Luttinger models and discuss some of the known exact results. We study numerically the charge and spin separation in the Hubbard model. The time evolution of a wave packet is obtained and the charge and spin densities are evaluated for different times. The charge and spin wave packets propagate with different velocities. The results are interpreted in terms of the Bethe-ansatz solution. In section IV we study the effect of charge and spin separation on the quantum interference in a Aharonov-Bohm experiment. By calculating the one-particle propagators of the Luttinger model for a mesoscopic ring with a magnetic field we calculate the Aharonov-Bohm conductance. The conductance oscillates with the magnetic field with a characteristic frequency that depends on the charge and spin velocities. (author)
Three New (2+1)-dimensional Integrable Systems and Some Related Darboux Transformations
International Nuclear Information System (INIS)
Guo Xiu-Rong
2016-01-01
We introduce two operator commutators by using different-degree loop algebras of the Lie algebra A 1 , then under the framework of zero curvature equations we generate two (2+1)-dimensional integrable hierarchies, including the (2+1)-dimensional shallow water wave (SWW) hierarchy and the (2+1)-dimensional Kaup-Newell (KN) hierarchy. Through reduction of the (2+1)-dimensional hierarchies, we get a (2+1)-dimensional SWW equation and a (2+1)-dimensional KN equation. Furthermore, we obtain two Darboux transformations of the (2+1)-dimensional SWW equation. Similarly, the Darboux transformations of the (2+1)-dimensional KN equation could be deduced. Finally, with the help of the spatial spectral matrix of SWW hierarchy, we generate a (2+1) heat equation and a (2+1) nonlinear generalized SWW system containing inverse operators with respect to the variables x and y by using a reduction spectral problem from the self-dual Yang-Mills equations. (paper)
Three New (2+1)-dimensional Integrable Systems and Some Related Darboux Transformations
Guo, Xiu-Rong
2016-06-01
We introduce two operator commutators by using different-degree loop algebras of the Lie algebra A1, then under the framework of zero curvature equations we generate two (2+1)-dimensional integrable hierarchies, including the (2+1)-dimensional shallow water wave (SWW) hierarchy and the (2+1)-dimensional Kaup-Newell (KN) hierarchy. Through reduction of the (2+1)-dimensional hierarchies, we get a (2+1)-dimensional SWW equation and a (2+1)-dimensional KN equation. Furthermore, we obtain two Darboux transformations of the (2+1)-dimensional SWW equation. Similarly, the Darboux transformations of the (2+1)-dimensional KN equation could be deduced. Finally, with the help of the spatial spectral matrix of SWW hierarchy, we generate a (2+1) heat equation and a (2+1) nonlinear generalized SWW system containing inverse operators with respect to the variables x and y by using a reduction spectral problem from the self-dual Yang-Mills equations. Supported by the National Natural Science Foundation of China under Grant No. 11371361, the Shandong Provincial Natural Science Foundation of China under Grant Nos. ZR2012AQ011, ZR2013AL016, ZR2015EM042, National Social Science Foundation of China under Grant No. 13BJY026, the Development of Science and Technology Project under Grant No. 2015NS1048 and A Project of Shandong Province Higher Educational Science and Technology Program under Grant No. J14LI58
Thermal Investigation of Three-Dimensional GaN-on-SiC High Electron Mobility Transistors
2017-07-01
University of L’Aquila, (2011). 23 Rao, H. & Bosman, G. Hot-electron induced defect generation in AlGaN/GaN high electron mobility transistors. Solid...AFRL-RY-WP-TR-2017-0143 THERMAL INVESTIGATION OF THREE- DIMENSIONAL GaN-on-SiC HIGH ELECTRON MOBILITY TRANSISTORS Qing Hao The University of Arizona...clarification memorandum dated 16 Jan 09. This report is available to the general public, including foreign nationals. Copies may be obtained from the
Viazzi, S.; Bahr, C.; Hertem, van T.; Schlageter-Tello, A.; Romanini, C.E.B.; Halachmi, I.; Lokhorst, C.; Berckmans, D.
2014-01-01
In this study, two different computer vision techniques to automatically measure the back posture in dairy cows were tested and evaluated. A two-dimensional and a three-dimensional camera system were used to extract the back posture from walking cows, which is one measurement used by experts to
Generation of 2N + 1-scroll existence in new three-dimensional chaos systems
Energy Technology Data Exchange (ETDEWEB)
Liu, Yue; Guan, Jian; Ma, Chunyang; Guo, Shuxu, E-mail: guosx@jlu.edu.cn [College of Electronic Science and Engineering, Jilin University, Changchun 130012 (China)
2016-08-15
We propose a systematic methodology for creating 2N + 1-scroll chaotic attractors from a simple three-dimensional system, which is named as the translation chaotic system. It satisfies the condition a{sub 12}a{sub 21} = 0, while the Chua system satisfies a{sub 12}a{sub 21} > 0. In this paper, we also propose a successful (an effective) design and an analytical approach for constructing 2N + 1-scrolls, the translation transformation principle. Also, the dynamics properties of the system are studied in detail. MATLAB simulation results show very sophisticated dynamical behaviors and unique chaotic behaviors of the system. It provides a new approach for 2N + 1-scroll attractors. Finally, to explore the potential use in technological applications, a novel block circuit diagram is also designed for the hardware implementation of 1-, 3-, 5-, and 7-scroll attractors via switching the switches. Translation chaotic system has the merit of convenience and high sensitivity to initial values, emerging potentials in future engineering chaos design.
Nam, Julia EunJu; Mueller, Klaus
2013-02-01
Gaining a true appreciation of high-dimensional space remains difficult since all of the existing high-dimensional space exploration techniques serialize the space travel in some way. This is not so foreign to us since we, when traveling, also experience the world in a serial fashion. But we typically have access to a map to help with positioning, orientation, navigation, and trip planning. Here, we propose a multivariate data exploration tool that compares high-dimensional space navigation with a sightseeing trip. It decomposes this activity into five major tasks: 1) Identify the sights: use a map to identify the sights of interest and their location; 2) Plan the trip: connect the sights of interest along a specifyable path; 3) Go on the trip: travel along the route; 4) Hop off the bus: experience the location, look around, zoom into detail; and 5) Orient and localize: regain bearings in the map. We describe intuitive and interactive tools for all of these tasks, both global navigation within the map and local exploration of the data distributions. For the latter, we describe a polygonal touchpad interface which enables users to smoothly tilt the projection plane in high-dimensional space to produce multivariate scatterplots that best convey the data relationships under investigation. Motion parallax and illustrative motion trails aid in the perception of these transient patterns. We describe the use of our system within two applications: 1) the exploratory discovery of data configurations that best fit a personal preference in the presence of tradeoffs and 2) interactive cluster analysis via cluster sculpting in N-D.
Xu, Chao; Fang, Jian; Shen, Hui; Wang, Yu-Ping; Deng, Hong-Wen
2018-01-25
Extreme phenotype sampling (EPS) is a broadly-used design to identify candidate genetic factors contributing to the variation of quantitative traits. By enriching the signals in extreme phenotypic samples, EPS can boost the association power compared to random sampling. Most existing statistical methods for EPS examine the genetic factors individually, despite many quantitative traits have multiple genetic factors underlying their variation. It is desirable to model the joint effects of genetic factors, which may increase the power and identify novel quantitative trait loci under EPS. The joint analysis of genetic data in high-dimensional situations requires specialized techniques, e.g., the least absolute shrinkage and selection operator (LASSO). Although there are extensive research and application related to LASSO, the statistical inference and testing for the sparse model under EPS remain unknown. We propose a novel sparse model (EPS-LASSO) with hypothesis test for high-dimensional regression under EPS based on a decorrelated score function. The comprehensive simulation shows EPS-LASSO outperforms existing methods with stable type I error and FDR control. EPS-LASSO can provide a consistent power for both low- and high-dimensional situations compared with the other methods dealing with high-dimensional situations. The power of EPS-LASSO is close to other low-dimensional methods when the causal effect sizes are small and is superior when the effects are large. Applying EPS-LASSO to a transcriptome-wide gene expression study for obesity reveals 10 significant body mass index associated genes. Our results indicate that EPS-LASSO is an effective method for EPS data analysis, which can account for correlated predictors. The source code is available at https://github.com/xu1912/EPSLASSO. hdeng2@tulane.edu. Supplementary data are available at Bioinformatics online. © The Author (2018). Published by Oxford University Press. All rights reserved. For Permissions, please
Banks, H. T.; Ito, K.
1991-01-01
A hybrid method for computing the feedback gains in linear quadratic regulator problem is proposed. The method, which combines use of a Chandrasekhar type system with an iteration of the Newton-Kleinman form with variable acceleration parameter Smith schemes, is formulated to efficiently compute directly the feedback gains rather than solutions of an associated Riccati equation. The hybrid method is particularly appropriate when used with large dimensional systems such as those arising in approximating infinite-dimensional (distributed parameter) control systems (e.g., those governed by delay-differential and partial differential equations). Computational advantages of the proposed algorithm over the standard eigenvector (Potter, Laub-Schur) based techniques are discussed, and numerical evidence of the efficacy of these ideas is presented.
Rational solutions to two- and one-dimensional multicomponent Yajima–Oikawa systems
International Nuclear Information System (INIS)
Chen, Junchao; Chen, Yong; Feng, Bao-Feng; Maruno, Ken-ichi
2015-01-01
Exact explicit rational solutions of two- and one-dimensional multicomponent Yajima–Oikawa (YO) systems, which contain multi-short-wave components and single long-wave one, are presented by using the bilinear method. For two-dimensional system, the fundamental rational solution first describes the localized lumps, which have three different patterns: bright, intermediate and dark states. Then, rogue waves can be obtained under certain parameter conditions and their behaviors are also classified to above three patterns with different definition. It is shown that the simplest (fundamental) rogue waves are line localized waves which arise from the constant background with a line profile and then disappear into the constant background again. In particular, two-dimensional intermediate and dark counterparts of rogue wave are found with the different parameter requirements. We demonstrate that multirogue waves describe the interaction of several fundamental rogue waves, in which interesting curvy wave patterns appear in the intermediate times. Different curvy wave patterns form in the interaction of different types fundamental rogue waves. Higher-order rogue waves exhibit the dynamic behaviors that the wave structures start from lump and then retreat back to it, and this transient wave possesses the patterns such as parabolas. Furthermore, different states of higher-order rogue wave result in completely distinguishing lumps and parabolas. Moreover, one-dimensional rogue wave solutions with three states are constructed through the further reduction. Specifically, higher-order rogue wave in one-dimensional case is derived under the parameter constraints. - Highlights: • Exact explicit rational solutions of two-and one-dimensional multicomponent Yajima–Oikawa systems. • Two-dimensional rogue wave contains three different patterns: bright, intermediate and dark states. • Multi- and higher-order rogue waves exhibit distinct dynamic behaviors in two-dimensional case
Numerical Three-Dimensional Model of Airport Terminal Drainage System
Strzelecki Michał
2014-01-01
During the construction of an airport terminal it was found that as a result of the hydrostatic pressure of underground water the foundation plate of the building had dangerously shifted in the direction opposite to that of the gravitational forces. The only effective measure was to introduce a drainage system on the site. The complex geology of the area indicated that two independent drainage systems, i.e., a horizontal system in the Quaternary beds and a vertical system in the Tertiary wate...
Estimation Methods for Infinite-Dimensional Systems Applied to the Hemodynamic Response in the Brain
Belkhatir, Zehor
2018-05-01
Infinite-Dimensional Systems (IDSs) which have been made possible by recent advances in mathematical and computational tools can be used to model complex real phenomena. However, due to physical, economic, or stringent non-invasive constraints on real systems, the underlying characteristics for mathematical models in general (and IDSs in particular) are often missing or subject to uncertainty. Therefore, developing efficient estimation techniques to extract missing pieces of information from available measurements is essential. The human brain is an example of IDSs with severe constraints on information collection from controlled experiments and invasive sensors. Investigating the intriguing modeling potential of the brain is, in fact, the main motivation for this work. Here, we will characterize the hemodynamic behavior of the brain using functional magnetic resonance imaging data. In this regard, we propose efficient estimation methods for two classes of IDSs, namely Partial Differential Equations (PDEs) and Fractional Differential Equations (FDEs). This work is divided into two parts. The first part addresses the joint estimation problem of the state, parameters, and input for a coupled second-order hyperbolic PDE and an infinite-dimensional ordinary differential equation using sampled-in-space measurements. Two estimation techniques are proposed: a Kalman-based algorithm that relies on a reduced finite-dimensional model of the IDS, and an infinite-dimensional adaptive estimator whose convergence proof is based on the Lyapunov approach. We study and discuss the identifiability of the unknown variables for both cases. The second part contributes to the development of estimation methods for FDEs where major challenges arise in estimating fractional differentiation orders and non-smooth pointwise inputs. First, we propose a fractional high-order sliding mode observer to jointly estimate the pseudo-state and input of commensurate FDEs. Second, we propose a
Nambu-Poisson reformulation of the finite dimensional dynamical systems
International Nuclear Information System (INIS)
Baleanu, D.; Makhaldiani, N.
1998-01-01
A system of nonlinear ordinary differential equations which in a particular case reduces to Volterra's system is introduced. We found in two simplest cases the complete sets of the integrals of motion using Nambu-Poisson reformulation of the Hamiltonian dynamics. In these cases we have solved the systems by quadratures
Dhaliwal, Anandika; Brenner, Matthew; Wolujewicz, Paul; Zhang, Zheng; Mao, Yong; Batish, Mona; Kohn, Joachim; Moghe, Prabhas V
2016-11-01
A predictive framework for the evolution of stem cell biology in 3-D is currently lacking. In this study we propose deep image informatics of the nuclear biology of stem cells to elucidate how 3-D biomaterials steer stem cell lineage phenotypes. The approach is based on high content imaging informatics to capture minute variations in the 3-D spatial organization of splicing factor SC-35 in the nucleoplasm as a marker to classify emergent cell phenotypes of human mesenchymal stem cells (hMSCs). The cells were cultured in varied 3-D culture systems including hydrogels, electrospun mats and salt leached scaffolds. The approach encompasses high resolution 3-D imaging of SC-35 domains and high content image analysis (HCIA) to compute quantitative 3-D nuclear metrics for SC-35 organization in single cells in concert with machine learning approaches to construct a predictive cell-state classification model. Our findings indicate that hMSCs cultured in collagen hydrogels and induced to differentiate into osteogenic or adipogenic lineages could be classified into the three lineages (stem, adipogenic, osteogenic) with ⩾80% precision and sensitivity, within 72h. Using this framework, the augmentation of osteogenesis by scaffold design exerted by porogen leached scaffolds was also profiled within 72h with ∼80% high sensitivity. Furthermore, by employing 3-D SC-35 organizational metrics, differential osteogenesis induced by novel electrospun fibrous polymer mats incorporating decellularized matrix could also be elucidated and predictably modeled at just 3days with high precision. We demonstrate that 3-D SC-35 organizational metrics can be applied to model the stem cell state in 3-D scaffolds. We propose that this methodology can robustly discern minute changes in stem cell states within complex 3-D architectures and map single cell biological readouts that are critical to assessing population level cell heterogeneity. The sustained development and validation of bioactive
Computation of focal values and stability analysis of 4-dimensional systems
Directory of Open Access Journals (Sweden)
Bo Sang
2015-08-01
Full Text Available This article presents a recursive formula for computing the n-th singular point values of a class of 4-dimensional autonomous systems, and establishes the algebraic equivalence between focal values and singular point values. The formula is linear and then avoids complicated integrating operations, therefore the calculation can be carried out by computer algebra system such as Maple. As an application of the formula, bifurcation analysis is made for a quadratic system with a Hopf equilibrium, which can have three small limit cycles around an equilibrium point. The theory and methodology developed in this paper can be used for higher-dimensional systems.
Impurity states in two-and three-dimensional disordered systems
International Nuclear Information System (INIS)
Silva, A.F. da; Fabbri, M.
1984-04-01
The microscopic structure of the impurity states in two-and three-dimensional (2D and 3D) disordered systems is investigated. A cluster model is outlined for the donor impurity density of states (DIDS) of doped semiconductors. It is shown that the impurity states are very sensitive to a change in the dimensionality of the system, i.e., from 3D to 2D system. It is found that all eigenstates become localized in 2D disordered system for a large range of concentration. (Author) [pt
Energy Technology Data Exchange (ETDEWEB)
Dan Maljovec; Bei Wang; Valerio Pascucci; Peer-Timo Bremer; Michael Pernice; Robert Nourgaliev
2013-05-01
The next generation of methodologies for nuclear reactor Probabilistic Risk Assessment (PRA) explicitly accounts for the time element in modeling the probabilistic system evolution and uses numerical simulation tools to account for possible dependencies between failure events. The Monte-Carlo (MC) and the Dynamic Event Tree (DET) approaches belong to this new class of dynamic PRA methodologies. A challenge of dynamic PRA algorithms is the large amount of data they produce which may be difficult to visualize and analyze in order to extract useful information. We present a software tool that is designed to address these goals. We model a large-scale nuclear simulation dataset as a high-dimensional scalar function defined over a discrete sample of the domain. First, we provide structural analysis of such a function at multiple scales and provide insight into the relationship between the input parameters and the output. Second, we enable exploratory analysis for users, where we help the users to differentiate features from noise through multi-scale analysis on an interactive platform, based on domain knowledge and data characterization. Our analysis is performed by exploiting the topological and geometric properties of the domain, building statistical models based on its topological segmentations and providing interactive visual interfaces to facilitate such explorations. We provide a user’s guide to our software tool by highlighting its analysis and visualization capabilities, along with a use case involving dataset from a nuclear reactor safety simulation.
Mounet, Nicolas; Gibertini, Marco; Schwaller, Philippe; Campi, Davide; Merkys, Andrius; Marrazzo, Antimo; Sohier, Thibault; Castelli, Ivano Eligio; Cepellotti, Andrea; Pizzi, Giovanni; Marzari, Nicola
2018-02-01
Two-dimensional (2D) materials have emerged as promising candidates for next-generation electronic and optoelectronic applications. Yet, only a few dozen 2D materials have been successfully synthesized or exfoliated. Here, we search for 2D materials that can be easily exfoliated from their parent compounds. Starting from 108,423 unique, experimentally known 3D compounds, we identify a subset of 5,619 compounds that appear layered according to robust geometric and bonding criteria. High-throughput calculations using van der Waals density functional theory, validated against experimental structural data and calculated random phase approximation binding energies, further allowed the identification of 1,825 compounds that are either easily or potentially exfoliable. In particular, the subset of 1,036 easily exfoliable cases provides novel structural prototypes and simple ternary compounds as well as a large portfolio of materials to search from for optimal properties. For a subset of 258 compounds, we explore vibrational, electronic, magnetic and topological properties, identifying 56 ferromagnetic and antiferromagnetic systems, including half-metals and half-semiconductors.
Tao, Chenyang; Nichols, Thomas E; Hua, Xue; Ching, Christopher R K; Rolls, Edmund T; Thompson, Paul M; Feng, Jianfeng
2017-01-01
We propose a generalized reduced rank latent factor regression model (GRRLF) for the analysis of tensor field responses and high dimensional covariates. The model is motivated by the need from imaging-genetic studies to identify genetic variants that are associated with brain imaging phenotypes, often in the form of high dimensional tensor fields. GRRLF identifies from the structure in the data the effective dimensionality of the data, and then jointly performs dimension reduction of the covariates, dynamic identification of latent factors, and nonparametric estimation of both covariate and latent response fields. After accounting for the latent and covariate effects, GRLLF performs a nonparametric test on the remaining factor of interest. GRRLF provides a better factorization of the signals compared with common solutions, and is less susceptible to overfitting because it exploits the effective dimensionality. The generality and the flexibility of GRRLF also allow various statistical models to be handled in a unified framework and solutions can be efficiently computed. Within the field of neuroimaging, it improves the sensitivity for weak signals and is a promising alternative to existing approaches. The operation of the framework is demonstrated with both synthetic datasets and a real-world neuroimaging example in which the effects of a set of genes on the structure of the brain at the voxel level were measured, and the results compared favorably with those from existing approaches. Copyright © 2016. Published by Elsevier Inc.
International Nuclear Information System (INIS)
Li Zhu; Dong Huanhe
2008-01-01
Under the frame of the (2 + 1)-dimensional zero curvature equation and Tu model, (2 + 1)-dimensional Dirac hierarchy is obtained. Again by use of the expanding loop algebra the integrable coupling system of the above hierarchy is given
Directory of Open Access Journals (Sweden)
V. A. Trudonoshin
2015-01-01
Full Text Available The article proposes a technique to develop mathematical models (MM of elements of the three-dimensional (3D mechanical systems for universal simulation software systems that allow us automatically generate the MM of a system based on MM elements and their connections. The technique is based on the MM of 3 D body. Linear and angular velocities are used as the main phase variables (unknown in the MM of the system, linear and angular movements are used as the additional ones, the latter being defined by the normalized quaternions that have computational advantages over turning angles.The paper has considered equations of dynamics, formulas of transition from the global coordinate system to the local one and vice versa. A spherical movable joint is presented as an example of the interaction element between the bodies. The paper shows the MM equivalent circuits of a body and a spherical joint. Such a representation, as the equivalent circuit, automatically enables us to obtain topological equations of the system. Various options to build equations of the joint and advices for their practical use are given.
Light scattering studies of lower dimensional colloidal particle and critical fluid systems
International Nuclear Information System (INIS)
O'Sullivan, W.J.; Mockler, R.C.
1984-09-01
The authors have studied the response to compression of colloidal particle crystals in monolayers on the surface of water. The crystals deform elastically as the crystals are compressed in a Langmuir trough from a lattice spacing of ten microns to spacings less than two microns. A phase transition to a close packed triangular lattice phase occurs at very high densities, when the attractive van der Waals/steric interations between particles dominate. The authors have found that the aggregates formed, when a colloidal particle monolayer coagulates following switching off of the repulsive electric dipole-dipole interactions, show scale invariance with a fractal dimension consistent with the prediction of a theory of diffusion limited aggregation in two dimensions. The authors have made progress toward the development of a computer processed array detector-spectrometer to be used in studies of melting and crystallization of two dimensional colloidal particle films. Stable black bilipid membranes have been produced, both spherical and planar, with and without embedded microparticles. We have modified our heterodyne autocorrelation spectrometer, used for studies of the dynamic response of critical fluid films, to enable us to measure the intensity autocorrelation of light scattered at forward angles. Rayleigh linewidth data has been gathered from a 1.9 micron film of a 2,6-lutidine+water critical mixture, taken at a scattering angle of ten degrees. The preliminary results indicate that the film dynamical response remains that of an equivalent three dimensional system, in apparent disgreement with recent theoretical predictions of Calvo and Ferrell
Three-dimensional MR imaging of the cerebrospinal system with the RARE technique
International Nuclear Information System (INIS)
Hennig, J.; Ott, D.; Ylayasski, J.
1987-01-01
Three-dimensional RARE myelography is a fast technique for high-resolution imaging of the cerebrospinal fluid. A data set with 1 x 1 x 1-mm resolution can be generated with a 12-minute acquisition time. Sophisticated three-dimensional display algorithms allow reconstruction of planes at arbitrary angles and full three-dimensional displays, which yield extremely useful information for neurosurgical planning. Additionally, the injection of contrast agent can be simulated on the computer and communication pathways between structures of interest can be found noninvasively
The quantum spectral analysis of the two-dimensional annular billiard system
International Nuclear Information System (INIS)
Yan-Hui, Zhang; Ji-Quan, Zhang; Xue-You, Xu; Sheng-Lu, Lin
2009-01-01
Based on the extended closed-orbit theory together with spectral analysis, this paper studies the correspondence between quantum mechanics and the classical counterpart in a two-dimensional annular billiard. The results demonstrate that the Fourier-transformed quantum spectra are in very good accordance with the lengths of the classical ballistic trajectories, whereas spectral strength is intimately associated with the shapes of possible open orbits connecting arbitrary two points in the annular cavity. This approach facilitates an intuitive understanding of basic quantum features such as quantum interference, locations of the wavefunctions, and allows quantitative calculations in the range of high energies, where full quantum calculations may become impractical in general. This treatment provides a thread to explore the properties of microjunction transport and even quantum chaos under the much more general system. (general)
Energy Technology Data Exchange (ETDEWEB)
Choi, Jong Ho; Ohn, M. Y.; Cho, C. H. [KOPEC, Taejon (Korea)
2002-03-01
The trip coverage analysis model requires the geometry network for primary and secondary circuit as well as the plant control system to simulate all the possible plant operating conditions throughout the plant life. The model was validated for the power maneuvering and the Wolsong 4 commissioning test. The trip coverage map was produced for the large break loss of coolant accident and the complete loss of class IV power event. The reliable multi-dimensional hydrogen analysis requires the high capability for thermal hydraulic modelling. To acquire such a basic capability and verify the applicability of GOTHIC code, the assessment of heat transfer model, hydrogen mixing and combustion model was performed. Also, the assessment methodology for flame acceleration and deflagration-to-detonation transition is established. 22 refs., 120 figs., 31 tabs. (Author)
Quantum one dimensional spin systems. Disorder and impurities
International Nuclear Information System (INIS)
Brunel, V.
1999-01-01
This thesis presents three studies that are respectively the spin-1 disordered chain, the non magnetic impurities in the spin-1/2 chain and the reaction-diffusion process. The spin-1 chain of weak disorder is performed by the Abelian bosonization and the renormalization group. This allows to take into account the competition between the disorder and the interactions and predicts the effects of various spin-1 anisotropy chain phases under many different disorders. A second work uses the non magnetic impurities as local probes of the correlations in the spin-1/2 chain. When the impurities are connected to the chain boundary, the author predicts a temperature dependence of the relaxation rate (1/T) of the nuclear spin impurities, different from the case of these impurities connected to the whole chain. The last work deals with one dimensional reaction-diffusion problem. The Jordan-Wigner transformation allows to consider a fermionic field theory that critical exponents follow from the renormalization group. (A.L.B.)
Numerical Three-Dimensional Model of Airport Terminal Drainage System
Directory of Open Access Journals (Sweden)
Strzelecki Michał
2014-03-01
Full Text Available During the construction of an airport terminal it was found that as a result of the hydrostatic pressure of underground water the foundation plate of the building had dangerously shifted in the direction opposite to that of the gravitational forces. The only effective measure was to introduce a drainage system on the site. The complex geology of the area indicated that two independent drainage systems, i.e., a horizontal system in the Quaternary beds and a vertical system in the Tertiary water-bearing levels, were necessary. This paper presents numerical FEM calculations of the two drainage systems being part of the airport terminal drainaged esign. The computer simulation which was carried out took into consideration the actual effect of the drainage systems and their impact on the depression cone being formed in the two aquifers.
Rahman, Ahmad Taufek Abdul; Farah Rosli, Nurul; Zain, Shafirah Mohd; Zin, Hafiz M.
2018-01-01
Radiotherapy delivery techniques for cancer treatment are becoming more complex and highly focused, to enable accurate radiation dose delivery to the cancerous tissue and minimum dose to the healthy tissue adjacent to tumour. Instrument to verify the complex dose delivery in radiotherapy such as optical computed tomography (OCT) measures the dose from a three-dimensional (3D) radiochromic dosimeter to ensure the accuracy of the radiotherapy beam delivery to the patient. OCT measures the optical density in radiochromic material that changes predictably upon exposure to radiotherapy beams. OCT systems have been developed using a photodiode and charged coupled device (CCD) as the detector. The existing OCT imaging systems have limitation in terms of the accuracy and the speed of the measurement. Advances in on-pixel intelligence CMOS image sensor (CIS) will be exploited in this work to replace current detector in OCT imaging systems. CIS is capable of on-pixel signal processing at a very fast imaging speed (over several hundred images per second) that will allow improvement in the 3D measurement of the optical density. The paper will review 3D radiochromic dosimeters and OCT systems developed and discuss how CMOS based OCT imaging will provide accurate and fast optical density measurements in 3D. The paper will also discuss the configuration of the CMOS based OCT developed in this work and how it may improve the existing OCT system.