Scattering Solar Thermal Concentrators
Energy Technology Data Exchange (ETDEWEB)
Giebink, Noel C. [Pennsylvania State Univ., State College, PA (United States)
2015-01-31
This program set out to explore a scattering-based approach to concentrate sunlight with the aim of improving collector field reliability and of eliminating wind loading and gross mechanical movement through the use of a stationary collection optic. The approach is based on scattering sunlight from the focal point of a fixed collection optic into the confined modes of a sliding planar waveguide, where it is transported to stationary tubular heat transfer elements located at the edges. Optical design for the first stage of solar concentration, which entails focusing sunlight within a plane over a wide range of incidence angles (>120 degree full field of view) at fixed tilt, led to the development of a new, folded-path collection optic that dramatically out-performs the current state-of-the-art in scattering concentration. Rigorous optical simulation and experimental testing of this collection optic have validated its performance. In the course of this work, we also identified an opportunity for concentrating photovoltaics involving the use of high efficiency microcells made in collaboration with partners at the University of Illinois. This opportunity exploited the same collection optic design as used for the scattering solar thermal concentrator and was therefore pursued in parallel. This system was experimentally demonstrated to achieve >200x optical concentration with >70% optical efficiency over a full day by tracking with <1 cm of lateral movement at fixed latitude tilt. The entire scattering concentrator waveguide optical system has been simulated, tested, and assembled at small scale to verify ray tracing models. These models were subsequently used to predict the full system optical performance at larger, deployment scale ranging up to >1 meter aperture width. Simulations at an aperture widths less than approximately 0.5 m with geometric gains ~100x predict an overall optical efficiency in the range 60-70% for angles up to 50 degrees from normal. However, the
Impact of the Improved Resonance Scattering Kernel on HTR Calculations
International Nuclear Information System (INIS)
Becker, B.; Dagan, R.; Broeders, C.H.M.; Lohnert, G.
2008-01-01
The importance of an advanced neutron scattering model for heavy isotopes with strong energy dependent cross sections such as the pronounced resonances of U 238 has been discussed in various publications where the full double differential scattering kernel was derived. In this study we quantify the effect of the new scattering model for specific innovative types of High Temperature Reactor (HTR) systems which commonly exhibit a higher degree of heterogeneity and higher fuel temperatures, hence increasing the importance of the secondary neutron energy distribution. In particular the impact on the multiplication factor (k ∞ ) and the Doppler reactivity coefficient is presented in view of the packing factors and operating temperatures. A considerable reduction of k ∞ (up to 600 pcm) and an increased Doppler reactivity (up to 10%) is observed. An increase of up to 2.3% of the Pu 239 inventory can be noticed at 90 MWd/tHM burnup due to enhanced neutron absorption of U 238 . Those effects are more pronounced for design cases in which the neutron flux spectrum is hardened towards the resolved resonance range. (authors)
DBRC and WCM scattering kernels for TRIPOLI-4, version 9
Zoia, Andrea; Brun, Emeric; Jouanne, Cédric; Malvagi, Fausto
2014-06-01
Recent works have pointed out some relevant shortcomings of the so called `Sampling of the Velocity of the Target nucleus' (SVT) algorithm, which is currently used in most Monte Carlo codes for the Doppler broadening of the elastic scattering kernel. To overcome these limitations, which affect resonant nuclei such as 238U, and whose consequences in pincell criticality calculations can amount to a drop of a few hundred pcm, the Doppler Broadening Rejection Correction (DBRC) and the Weight Correction Method (WCM) have been proposed. In this work, we illustrate the implementation of DBRC and WCM in the TRIPOLI-4 Monte Carlo code. Several validation tests are discussed, and the impact of using DBRC or WCM to replace SVT is analyzed in detail in static as well as burnup calculations for UOX and MOX pincells, and in a PWR full-core simulation.
Preliminary scattering kernels for ethane and triphenylmethane at cryogenic temperatures
Directory of Open Access Journals (Sweden)
Cantargi F.
2017-01-01
Full Text Available Two potential cold moderator materials were studied: ethane and triphenylmethane. The first one, ethane (C2H6, is an organic compound which is very interesting from the neutronic point of view, in some respects better than liquid methane to produce subthermal neutrons, not only because it remains in liquid phase through a wider temperature range (Tf = 90.4 K, Tb = 184.6 K, but also because of its high protonic density together with its frequency spectrum with a low rotational energy band. Another material, Triphenylmethane is an hydrocarbon with formula C19H16 which has already been proposed as a good candidate for a cold moderator. Following one of the main research topics of the Neutron Physics Department of Centro Atómico Bariloche, we present here two ways to estimate the frequency spectrum which is needed to feed the NJOY nuclear data processing system in order to generate the scattering law of each desired material. For ethane, computer simulations of molecular dynamics were done, while for triphenylmethane existing experimental and calculated data were used to produce a new scattering kernel. With these models, cross section libraries were generated, and applied to neutron spectra calculation.
Preliminary scattering kernels for ethane and triphenylmethane at cryogenic temperatures
Cantargi, F.; Granada, J. R.; Damián, J. I. Márquez
2017-09-01
Two potential cold moderator materials were studied: ethane and triphenylmethane. The first one, ethane (C2H6), is an organic compound which is very interesting from the neutronic point of view, in some respects better than liquid methane to produce subthermal neutrons, not only because it remains in liquid phase through a wider temperature range (Tf = 90.4 K, Tb = 184.6 K), but also because of its high protonic density together with its frequency spectrum with a low rotational energy band. Another material, Triphenylmethane is an hydrocarbon with formula C19H16 which has already been proposed as a good candidate for a cold moderator. Following one of the main research topics of the Neutron Physics Department of Centro Atómico Bariloche, we present here two ways to estimate the frequency spectrum which is needed to feed the NJOY nuclear data processing system in order to generate the scattering law of each desired material. For ethane, computer simulations of molecular dynamics were done, while for triphenylmethane existing experimental and calculated data were used to produce a new scattering kernel. With these models, cross section libraries were generated, and applied to neutron spectra calculation.
SCAP-82, Single Scattering, Albedo Scattering, Point-Kernel Analysis in Complex Geometry
International Nuclear Information System (INIS)
Disney, R.K.; Vogtman, S.E.
1987-01-01
1 - Description of problem or function: SCAP solves for radiation transport in complex geometries using the single or albedo scatter point kernel method. The program is designed to calculate the neutron or gamma ray radiation level at detector points located within or outside a complex radiation scatter source geometry or a user specified discrete scattering volume. Geometry is describable by zones bounded by intersecting quadratic surfaces within an arbitrary maximum number of boundary surfaces per zone. Anisotropic point sources are describable as pointwise energy dependent distributions of polar angles on a meridian; isotropic point sources may also be specified. The attenuation function for gamma rays is an exponential function on the primary source leg and the scatter leg with a build- up factor approximation to account for multiple scatter on the scat- ter leg. The neutron attenuation function is an exponential function using neutron removal cross sections on the primary source leg and scatter leg. Line or volumetric sources can be represented as a distribution of isotropic point sources, with un-collided line-of-sight attenuation and buildup calculated between each source point and the detector point. 2 - Method of solution: A point kernel method using an anisotropic or isotropic point source representation is used, line-of-sight material attenuation and inverse square spatial attenuation between the source point and scatter points and the scatter points and detector point is employed. A direct summation of individual point source results is obtained. 3 - Restrictions on the complexity of the problem: - The SCAP program is written in complete flexible dimensioning so that no restrictions are imposed on the number of energy groups or geometric zones. The geometric zone description is restricted to zones defined by boundary surfaces defined by the general quadratic equation or one of its degenerate forms. The only restriction in the program is that the total
Bibliography for thermal neutron scattering
International Nuclear Information System (INIS)
Sakamoto, M.; Chihara, J.; Nakahara, Y.; Kadotani, H.; Sekiya, T.
1976-12-01
It contains bibliographical references to measurements, calculations, reviews and basic studies on thermal neutron scatterings and dynamical properties of condensed matter. About 2,700 documents up to the end of 1975 are covered. (auth.)
Energy Technology Data Exchange (ETDEWEB)
Tuereci, R. Goekhan [Kirikkale Univ. (Turkey). Kirikkale Vocational School; Tuereci, D. [Ministry of Education, Ankara (Turkey). 75th year Anatolia High School
2017-11-15
One speed, time independent and homogeneous medium neutron transport equation is solved with the anisotropic scattering which includes both the linearly and the quadratically anisotropic scattering kernel. Having written Case's eigenfunctions and the orthogonality relations among of these eigenfunctions, slab albedo problem is investigated as numerically by using Modified F{sub N} method. Selected numerical results are presented in tables.
Bibliography for thermal neutron scattering
International Nuclear Information System (INIS)
Sakamoto, Masanobu; Chihara, Junzo; Gotoh, Yorio; Kadotani, Hiroyuki; Sekiya, Tamotsu.
1979-09-01
Bibliographic references are given for measurements, calculations, reviews and basic studies of thermal neutron scattering and dynamical properties of condensed matter. This is the sixth edition covering 3,326 articles collected up to 1978. The edition being the final issue of the present bibliography series, a forthcoming edition will be published in a new form of bibliography. (author)
A Stochastic Proof of the Resonant Scattering Kernel and its Applications for Gen IV Reactors Type
International Nuclear Information System (INIS)
Becker, B.; Dagan, R.; Broeders, C.H.M.; Lohnert, G.
2008-01-01
Monte Carlo codes such as MCNP are widely accepted as almost-reference for reactor analysis. The Monte Carlo Code should therefore use as few as possible approximations in order to produce 'experimental-level' calculations. In this study we deal with one of the most problematic approximations done in MCNP in which the resonances are ignored for the secondary neutron energy distribution, namely the change of the energy and angular direction of the neutron after interaction with a heavy isotope with pronounced resonances. The endeavour of exploiting the influence of the resonances on the scattering kernel goes back to 1944 where E. Wigner and J. Wilkins developed the first temperature dependent scattering kernel. However only in 1998, the full analytical solution for the double differential resonant dependent scattering kernel was suggested by W. Rothenstein and R. Dagan. An independent stochastic approach is presented for the first time to confirm the above analytical kernel with a complete different methodology. Moreover, by manipulating in a subtle manner the scattering subroutine COLIDN of MCNP, it is proven that this very subroutine is, to some extent, inappropriate as well as the relevant explanation in the MCNP manual. The impact of this improved resonance dependent scattering kernel on diverse types of reactors, in particular for the Generation IV innovative core design HTR, is shown to be significant. (authors)
International Nuclear Information System (INIS)
Markovic, M. I.; Radunovic, J. B.
1976-01-01
Determination of spatial distribution of neutron flux in water, most frequently used moderator in thermal reactors, demands microscopic scattering kernels dependence on cosine of thermal neutrons scattering angle when solving the Boltzmann equation. Since spatial orientation of water molecules influences this dependence it is necessary to perform orientation averaging or rotation-vibrational intermediate scattering function for water molecules. The calculations described in this paper and the obtained results showed that methods of orientation averaging do not influence the anisotropy of thermal neutrons scattering on water molecules, but do influence the inelastic scattering
Scattering of thermal neutron by the water molecule
International Nuclear Information System (INIS)
Rosa, L.P.
The calculation of the differenctial cross section for scattering of thermal neutrons by water, taking into account the translational, rotational and vibrational motions of the water molecule, is presented according to Nelkin' model. Some modifications are presented which have been introduced in the original method to improve the results and an application has been made to reactor physics, by calculating the thermal neutron flux in a homogenous medium containing water and absorver. Thirty thermal energy groups have been used to compute the spectra. Within the limits of error, better agreement has been obtained between theory and experiments by using a modified Nelkin kernel consisting of substituting the asymptotic formulae for the rotational and vibrational motions by more exact expressions, similar to the Buttler model for heavy water
Thermal-neutron multiple scattering: critical double scattering
International Nuclear Information System (INIS)
Holm, W.A.
1976-01-01
A quantum mechanical formulation for multiple scattering of thermal-neutrons from macroscopic targets is presented and applied to single and double scattering. Critical nuclear scattering from liquids and critical magnetic scattering from ferromagnets are treated in detail in the quasielastic approximation for target systems slightly above their critical points. Numerical estimates are made of the double scattering contribution to the critical magnetic cross section using relevant parameters from actual experiments performed on various ferromagnets. The effect is to alter the usual Lorentzian line shape dependence on neutron wave vector transfer. Comparison with corresponding deviations in line shape resulting from the use of Fisher's modified form of the Ornstein-Zernike spin correlations within the framework of single scattering theory leads to values for the critical exponent eta of the modified correlations which reproduce the effect of double scattering. In addition, it is shown that by restricting the range of applicability of the multiple scattering theory from the outset to critical scattering, Glauber's high energy approximation can be used to provide a much simpler and more powerful description of multiple scattering effects. When sufficiently close to the critical point, it provides a closed form expression for the differential cross section which includes all orders of scattering and has the same form as the single scattering cross section with a modified exponent for the wave vector transfer
P- and S-wave Receiver Function Imaging with Scattering Kernels
Hansen, S. M.; Schmandt, B.
2017-12-01
Full waveform inversion provides a flexible approach to the seismic parameter estimation problem and can account for the full physics of wave propagation using numeric simulations. However, this approach requires significant computational resources due to the demanding nature of solving the forward and adjoint problems. This issue is particularly acute for temporary passive-source seismic experiments (e.g. PASSCAL) that have traditionally relied on teleseismic earthquakes as sources resulting in a global scale forward problem. Various approximation strategies have been proposed to reduce the computational burden such as hybrid methods that embed a heterogeneous regional scale model in a 1D global model. In this study, we focus specifically on the problem of scattered wave imaging (migration) using both P- and S-wave receiver function data. The proposed method relies on body-wave scattering kernels that are derived from the adjoint data sensitivity kernels which are typically used for full waveform inversion. The forward problem is approximated using ray theory yielding a computationally efficient imaging algorithm that can resolve dipping and discontinuous velocity interfaces in 3D. From the imaging perspective, this approach is closely related to elastic reverse time migration. An energy stable finite-difference method is used to simulate elastic wave propagation in a 2D hypothetical subduction zone model. The resulting synthetic P- and S-wave receiver function datasets are used to validate the imaging method. The kernel images are compared with those generated by the Generalized Radon Transform (GRT) and Common Conversion Point stacking (CCP) methods. These results demonstrate the potential of the kernel imaging approach to constrain lithospheric structure in complex geologic environments with sufficiently dense recordings of teleseismic data. This is demonstrated using a receiver function dataset from the Central California Seismic Experiment which shows several
Sterculia striata seed kernel oil: Characterization and thermal stability
Directory of Open Access Journals (Sweden)
Oliveira Cavalheiro, José Marcelino
2008-06-01
Full Text Available The objective of the present work was to characterize sterculia seed kernel oil. The chemical composition of the seeds, physicochemical properties as well as the fatty acid composition of the kernel oil was determined. The chemical composition of kernel flour presented about 25.8% lipid content. The physicochemical parameters such as acid, iodine, peroxide and saponification values were 0.82 (% as oleic acid, 69.2 (g iodine/100 g oil, 4.20 (m eq./kg and 136.1 (mg. KOH/g oil, respectively. With respect to fatty acid composition, the oil contained 36.2, 43.7 and 10.9% saturated, monounsaturated and polyunsaturated fatty acids, respectively. Palmitic acid (31.9%, oleic acid (41.7% and linoleic acid (10.73% were the principal saturated, monounsaturated and polyunsaturated fatty acids. Two cyclopropanoid fatty acids i.e. sterculic and malvalic acid were identified at a concentration of 5.3 and 2.3%, respectively. With regards to the thermal stability of the oil, a thermogravimetric analysis (TGA has shown that the oil was stable until about 284 Â°C, above that the oil started loosing mass, while a differential thermogravimetric analysis (DTGA revealed three stages of degradation with an increase in temperature. These stages corresponded to the degradation of polyunsaturated, monounsaturated and saturated fatty aids. The Differential Scanning Calorimetric (DSC analysis showed the existence of two exothermic events of energy transition, one of which is related to the oxidation reactions and another to the decomposition of the oil. Exothermic transitions in the oil were initiated at a temperature (Ti of 287.79 Â°C, and terminated at 347.81 Â°C, with an enthalpy variation of 11.69 joules.gâ1 and at initial temperature (Ti of 384.87 Â°C, peak temperature (Tp 415.71 Â°C, final temperature (Tf 448.9 Â°C and an enthalpy of 200.83 Joules. Gâ1El objetivo de este trabajo fue la caracterización del aceite de almendra de la semilla de
Tedgren, Åsa Carlsson; Plamondon, Mathieu; Beaulieu, Luc
2015-07-07
The aim of this work was to investigate how dose distributions calculated with the collapsed cone (CC) algorithm depend on the size of the water phantom used in deriving the point kernel for multiple scatter. A research version of the CC algorithm equipped with a set of selectable point kernels for multiple-scatter dose that had initially been derived in water phantoms of various dimensions was used. The new point kernels were generated using EGSnrc in spherical water phantoms of radii 5 cm, 7.5 cm, 10 cm, 15 cm, 20 cm, 30 cm and 50 cm. Dose distributions derived with CC in water phantoms of different dimensions and in a CT-based clinical breast geometry were compared to Monte Carlo (MC) simulations using the Geant4-based brachytherapy specific MC code Algebra. Agreement with MC within 1% was obtained when the dimensions of the phantom used to derive the multiple-scatter kernel were similar to those of the calculation phantom. Doses are overestimated at phantom edges when kernels are derived in larger phantoms and underestimated when derived in smaller phantoms (by around 2% to 7% depending on distance from source and phantom dimensions). CC agrees well with MC in the high dose region of a breast implant and is superior to TG43 in determining skin doses for all multiple-scatter point kernel sizes. Increased agreement between CC and MC is achieved when the point kernel is comparable to breast dimensions. The investigated approximation in multiple scatter dose depends on the choice of point kernel in relation to phantom size and yields a significant fraction of the total dose only at distances of several centimeters from a source/implant which correspond to volumes of low doses. The current implementation of the CC algorithm utilizes a point kernel derived in a comparatively large (radius 20 cm) water phantom. A fixed point kernel leads to predictable behaviour of the algorithm with the worst case being a source/implant located well within a patient
International Nuclear Information System (INIS)
Valente, Mauro; Botta, Francesca; Pedroli, Guido
2012-01-01
Beta-emitters have proved to be appropriate for radioimmunotherapy. The dosimetric characterization of each radionuclide has to be carefully investigated. One usual and practical dosimetric approach is the calculation of dose distribution from a unit point source emitting particles according to any radionuclide of interest, which is known as dose point kernel. Absorbed dose distributions are due to primary and radiation scattering contributions. This work presented a method capable of performing dose distributions for nuclear medicine dosimetry by means of Monte Carlo methods. Dedicated subroutines have been developed in order to separately compute primary and scattering contributions to the total absorbed dose, performing particle transport up to 1 keV or least. Preliminarily, the suitability of the calculation method has been satisfactory, being tested for monoenergetic sources, and it was further applied to the characterization of different beta-minus radionuclides of nuclear medicine interests for radioimmunotherapy. (author)
THERMAL: A routine designed to calculate neutron thermal scattering
International Nuclear Information System (INIS)
Cullen, D.E.
1995-01-01
THERMAL is designed to calculate neutron thermal scattering that is isotropic in the center of mass system. At low energy thermal motion will be included. At high energies the target nuclei are assumed to be stationary. The point of transition between low and high energies has been defined to insure a smooth transition. It is assumed that at low energy the elastic cross section is constant in the center of mass system. At high energy the cross section can be of any form. You can use this routine for all energies where the elastic scattering is isotropic in the center of mass system. In most materials this will be a fairly high energy
Thermally stimulated scattering in plasmas
DEFF Research Database (Denmark)
Dysthe, K. B.; Mjølhus, E.; Pécseli, H. L.
1985-01-01
this experiment local heat conduction is of little importance and the dynamic evolution for the electron temperature is dominated by heating and energy exchange with the ion component. These features are incorporated in the analysis. The resulting set of equations gives a growth rate and characteristic scale size......A theory for stimulated scattering of a laser beam is formulated where the dominant nonlinearity is the ohmic heating of the plasma. The analysis is carried out with particular reference to experimental investigations of CO2 laser heating of linear discharge plasma. In the conditions characterizing...
Attenuation of Scattered Thermal Energy Atomic Oxygen
Banks, Bruce A.; Seroka, Katelyn T.; McPhate, Jason B.; Miller, Sharon K.
2011-01-01
The attenuation of scattered thermal energy atomic oxygen is relevant to the potential damage that can occur within a spacecraft which sweeps through atomic oxygen in low Earth orbit (LEO). Although there can be significant oxidation and resulting degradation of polymers and some metals on the external surfaces of spacecraft, there are often openings on a spacecraft such as telescope apertures, vents, and microwave cavities that can allow atomic oxygen to enter and scatter internally to the spacecraft. Atomic oxygen that enters a spacecraft can thermally accommodate and scatter to ultimately react or recombine on surfaces. The atomic oxygen that does enter a spacecraft can be scavenged by use of high erosion yield polymers to reduce its reaction on critical surfaces and materials. Polyoxymethylene and polyethylene can be used as effective atomic oxygen scavenging polymers.
A Rejection Sampling Based Method for Determining Thermal Scattering Angle and Energy
Energy Technology Data Exchange (ETDEWEB)
Haugen, Carl C.; Forget, Benoit; Smith, Kord S.
2017-09-01
Most high performance computing systems being deployed currently and envisioned for the future are based on making use of heavy parallelism across many computational nodes and many concurrent cores. These types of heavily parallel systems often have relatively little memory per core but large amounts of computing capability. This places a significant constraint on how data storage is handled in many Monte Carlo codes. This is made even more significant in fully coupled multiphysics simulations, which requires simulations of many physical phenomena be carried out concurrently on individual processing nodes, which further reduces the amount of memory available for storage of Monte Carlo data. As such, there has been a move towards on-the-fly nuclear data generation to reduce memory requirements associated with interpolation between pre-generated large nuclear data tables for a selection of system temperatures. Methods have been previously developed and implemented in MIT’s OpenMC Monte Carlo code for both the resolved resonance regime and the unresolved resonance regime, but are currently absent for the thermal energy regime. While there are many components involved in generating a thermal neutron scattering cross section on-the-fly, this work will focus on a proposed method for determining the energy and direction of a neutron after a thermal incoherent inelastic scattering event. This work proposes a rejection sampling based method using the thermal scattering kernel to determine the correct outgoing energy and angle. The goal of this project is to be able to treat the full S (a, ß) kernel for graphite, to assist in high fidelity simulations of the TREAT reactor at Idaho National Laboratory. The method is, however, sufficiently general to be applicable in other thermal scattering materials, and can be initially validated with the continuous analytic free gas model.
Development of temperature related thermal neutron scattering database for MCNP
International Nuclear Information System (INIS)
Mei Longwei; Cai Xiangzhou; Jiang Dazhen; Chen Jingen; Guo Wei
2013-01-01
Based on ENDF/B-Ⅶ neutron library, the thermal neutron scattering library S(α, β) for molten salt reactor moderators was developed. The temperatures of this library were chose as the characteristic temperature of the molten salt reactor. The cross section of the thermal neutron scattering of ACE format was investigated, and this library was also validated by the benchmarks of ICSBEP. The uncertainties shown in the validation were in reasonable range when compared with the thermal neutron scattering library tmccs which included in the MCNP data library. It was proved that the thermal neutron scattering library processed in this study could be used in the molten salt reactor design. (authors)
Applications of thermal neutron scattering in biology, biochemistry and biophysics
International Nuclear Information System (INIS)
Worcester, D.L.
1977-01-01
Biological applications of thermal neutron scattering have increased rapidly in recent years. The following categories of biological research with thermal neutron scattering are presently identified: crystallography of biological molecules; neutron small-angle scattering of biological molecules in solution (these studies have already included numerous measurements of proteins, lippoproteins, viruses, ribosomal subunits and chromatin subunit particles); neutron small-angle diffraction and scattering from biological membranes and membrane components; and neutron quasielastic and inelastic scattering studies of the dynamic properties of biological molecules and materials. (author)
Introduction to the theory of thermal neutron scattering
Squires, G L
2012-01-01
Since the advent of the nuclear reactor, thermal neutron scattering has proved a valuable tool for studying many properties of solids and liquids, and research workers are active in the field at reactor centres and universities throughout the world. This classic text provides the basic quantum theory of thermal neutron scattering and applies the concepts to scattering by crystals, liquids and magnetic systems. Other topics discussed are the relation of the scattering to correlation functions in the scattering system, the dynamical theory of scattering and polarisation analysis. No previous knowledge of the theory of thermal neutron scattering is assumed, but basic knowledge of quantum mechanics and solid state physics is required. The book is intended for experimenters rather than theoreticians, and the discussion is kept as informal as possible. A number of examples, with worked solutions, are included as an aid to the understanding of the text.
New evaluation of thermal neutron scattering libraries for light and heavy water
Directory of Open Access Journals (Sweden)
Marquez Damian Jose Ignacio
2017-01-01
Full Text Available In order to improve the design and safety of thermal nuclear reactors and for verification of criticality safety conditions on systems with significant amount of fissile materials and water, it is necessary to perform high-precision neutron transport calculations and estimate uncertainties of the results. These calculations are based on neutron interaction data distributed in evaluated nuclear data libraries. To improve the evaluations of thermal scattering sub-libraries, we developed a set of thermal neutron scattering cross sections (scattering kernels for hydrogen bound in light water, and deuterium and oxygen bound in heavy water, in the ENDF-6 format from room temperature up to the critical temperatures of molecular liquids. The new evaluations were generated and processable with NJOY99 and also with NJOY-2012 with minor modifications (updates, and with the new version of NJOY-2016. The new TSL libraries are based on molecular dynamics simulations with GROMACS and recent experimental data, and result in an improvement of the calculation of single neutron scattering quantities. In this work, we discuss the importance of taking into account self-diffusion in liquids to accurately describe the neutron scattering at low neutron energies (quasi-elastic peak problem. To improve modeling of heavy water, it is important to take into account temperature-dependent static structure factors and apply Sköld approximation to the coherent inelastic components of the scattering matrix. The usage of the new set of scattering matrices and cross-sections improves the calculation of thermal critical systems moderated and/or reflected with light/heavy water obtained from the International Criticality Safety Benchmark Evaluation Project (ICSBEP handbook. For example, the use of the new thermal scattering library for heavy water, combined with the ROSFOND-2010 evaluation of the cross sections for deuterium, results in an improvement of the C/E ratio in 48 out of
New evaluation of thermal neutron scattering libraries for light and heavy water
Marquez Damian, Jose Ignacio; Granada, Jose Rolando; Cantargi, Florencia; Roubtsov, Danila
2017-09-01
In order to improve the design and safety of thermal nuclear reactors and for verification of criticality safety conditions on systems with significant amount of fissile materials and water, it is necessary to perform high-precision neutron transport calculations and estimate uncertainties of the results. These calculations are based on neutron interaction data distributed in evaluated nuclear data libraries. To improve the evaluations of thermal scattering sub-libraries, we developed a set of thermal neutron scattering cross sections (scattering kernels) for hydrogen bound in light water, and deuterium and oxygen bound in heavy water, in the ENDF-6 format from room temperature up to the critical temperatures of molecular liquids. The new evaluations were generated and processable with NJOY99 and also with NJOY-2012 with minor modifications (updates), and with the new version of NJOY-2016. The new TSL libraries are based on molecular dynamics simulations with GROMACS and recent experimental data, and result in an improvement of the calculation of single neutron scattering quantities. In this work, we discuss the importance of taking into account self-diffusion in liquids to accurately describe the neutron scattering at low neutron energies (quasi-elastic peak problem). To improve modeling of heavy water, it is important to take into account temperature-dependent static structure factors and apply Sköld approximation to the coherent inelastic components of the scattering matrix. The usage of the new set of scattering matrices and cross-sections improves the calculation of thermal critical systems moderated and/or reflected with light/heavy water obtained from the International Criticality Safety Benchmark Evaluation Project (ICSBEP) handbook. For example, the use of the new thermal scattering library for heavy water, combined with the ROSFOND-2010 evaluation of the cross sections for deuterium, results in an improvement of the C/E ratio in 48 out of 65
Thermal invisibility based on scattering cancellation and mantle cloaking
Farhat, Mohamed
2015-04-30
We theoretically and numerically analyze thermal invisibility based on the concept of scattering cancellation and mantle cloaking. We show that a small object can be made completely invisible to heat diffusion waves, by tailoring the heat conductivity of the spherical shell enclosing the object. This means that the thermal scattering from the object is suppressed, and the heat flow outside the object and the cloak made of these spherical shells behaves as if the object is not present. Thermal invisibility may open new vistas in hiding hot spots in infrared thermography, military furtivity, and electronics heating reduction.
Directory of Open Access Journals (Sweden)
Holmes Jesse
2017-01-01
Full Text Available The neutron scattering properties of water ice are of interest to the nuclear criticality safety community for the transport and storage of nuclear materials in cold environments. The common hexagonal phase ice Ih has locally ordered, but globally disordered, H2O molecular orientations. A 96-molecule supercell is modeled using the VASP ab initio density functional theory code and PHONON lattice dynamics code to calculate the phonon vibrational spectra of H and O in ice Ih. These spectra are supplied to the LEAPR module of the NJOY2012 nuclear data processing code to generate thermal neutron scattering laws for H and O in ice Ih in the incoherent approximation. The predicted vibrational spectra are optimized to be representative of the globally averaged ice Ih structure by comparing theoretically calculated and experimentally measured total cross sections and inelastic neutron scattering spectra. The resulting scattering kernel is then supplied to the MC21 Monte Carlo transport code to calculate time eigenvalues for the fundamental mode decay in ice cylinders at various temperatures. Results are compared to experimental flux decay measurements for a pulsed-neutron die-away diffusion benchmark.
Directory of Open Access Journals (Sweden)
JONG WOON KIM
2014-04-01
In this paper, we introduce a modified scattering kernel approach to avoid the unnecessarily repeated calculations involved with the scattering source calculation, and used it with parallel computing to effectively reduce the computation time. Its computational efficiency was tested for three-dimensional full-coupled photon-electron transport problems using our computer program which solves the multi-group discrete ordinates transport equation by using the discontinuous finite element method with unstructured tetrahedral meshes for complicated geometrical problems. The numerical tests show that we can improve speed up to 17∼42 times for the elapsed time per iteration using the modified scattering kernel, not only in the single CPU calculation but also in the parallel computing with several CPUs.
Thermal, crystallinity and morphological studies of the filled RBD palm kernel oil polyurethane foam
International Nuclear Information System (INIS)
Khairiah Badri; Sahrim Ahmad; Sarani Zakaria
2000-01-01
The synthesis of RBD palm kernel oil (PKO) polyurethane polyol and the polyurethane foam has well been documented. However, less study has been put in discovering the thermal properties and crystallinity of the foam. It is also an initiative to investigate the effect of oil palm empty fruit bunch (EFB) and sorbitol as fillers in the polyurethane (PU) foam to these properties. Thermogravimetric (TGA) investigation of the PKO PU foam was performed to study their decompositions. The semi-crystalline nature of EFB-filled PU was confirmed by x-ray diffratogram and DSC thermogram of glass transition temperature, T g . The x-ray diffraction (XRD) study of the unfilled PU showed a broad amorphous halo, indicative of absence of crystallinity in the polymer, which has been explained as due to strong hydrogen bonding in the hard phase. Overall crystallinity decreases with an increase in the polyester content in agreement with the XRD results. The crystallinity however, increases with the inclusion of EFB in the polyurethane system. This study was followed by the observation of the surface morphologies of the PKO PU foam with and without fillers. The scanning electron micrographs verified the finding on the improved k-factor values. (Author)
Specimen environments in thermal neutron scattering experiments
International Nuclear Information System (INIS)
Cebula, D.J.
1980-11-01
This report is an attempt to collect into one place outline information concerning the techniques used and basic design of sample environment apparatus employed in neutron scattering experiments. Preliminary recommendations for the specimen environment programme of the SNS are presented. The general conclusion reached is that effort should be devoted towards improving reliability and efficiency of operation of specimen environment apparatus and developing systems which are robust and easy to use, rather than achieving performance at the limits of technology. (author)
Comparing Thermal Process Validation Methods for Salmonella Inactivation on Almond Kernels.
Jeong, Sanghyup; Marks, Bradley P; James, Michael K
2017-01-01
Ongoing regulatory changes are increasing the need for reliable process validation methods for pathogen reduction processes involving low-moisture products; however, the reliability of various validation methods has not been evaluated. Therefore, the objective was to quantify accuracy and repeatability of four validation methods (two biologically based and two based on time-temperature models) for thermal pasteurization of almonds. Almond kernels were inoculated with Salmonella Enteritidis phage type 30 or Enterococcus faecium (NRRL B-2354) at ~10 8 CFU/g, equilibrated to 0.24, 0.45, 0.58, or 0.78 water activity (a w ), and then heated in a pilot-scale, moist-air impingement oven (dry bulb 121, 149, or 177°C; dew point Salmonella inactivation using a traditional (D, z) model and a modified model accounting for process humidity. Among the process validation methods, both methods based on time-temperature models had better repeatability, with replication errors approximately half those of the surrogate ( E. faecium ). Additionally, the modified model yielded the lowest root mean squared error in predicting Salmonella inactivation (1.1 to 1.5 log CFU/g); in contrast, E. faecium yielded a root mean squared error of 1.2 to 1.6 log CFU/g, and the traditional model yielded an unacceptably high error (3.4 to 4.4 log CFU/g). Importantly, the surrogate and modified model both yielded lethality predictions that were statistically equivalent (α = 0.05) to actual Salmonella lethality. The results demonstrate the importance of methodology, a w , and process humidity when validating thermal pasteurization processes for low-moisture foods, which should help processors select and interpret validation methods to ensure product safety.
A thermal neutron scattering law for yttrium hydride
Zerkle, Michael; Holmes, Jesse
2017-09-01
Yttrium hydride (YH2) is of interest as a high temperature moderator material because of its superior ability to retain hydrogen at elevated temperatures. Thermal neutron scattering laws for hydrogen bound in yttrium hydride (H-YH2) and yttrium bound in yttrium hydride (Y-YH2) prepared using the ab initio approach are presented. Density functional theory, incorporating the generalized gradient approximation (GGA) for the exchange-correlation energy, is used to simulate the face-centered cubic structure of YH2 and calculate the interatomic Hellmann-Feynman forces for a 2 × 2 × 2 supercell containing 96 atoms. Lattice dynamics calculations using PHONON are then used to determine the phonon dispersion relations and density of states. The calculated phonon density of states for H and Y in YH2 are used to prepare H-YH2 and Y-YH2 thermal scattering laws using the LEAPR module of NJOY2012. Analysis of the resulting integral and differential scattering cross sections demonstrates adequate resolution of the S(α,β) function. Comparison of experimental lattice constant, heat capacity, inelastic neutron scattering spectra and total scattering cross section measurements to calculated values are used to validate the thermal scattering laws.
A thermal neutron scattering law for yttrium hydride
Directory of Open Access Journals (Sweden)
Zerkle Michael
2017-01-01
Full Text Available Yttrium hydride (YH2 is of interest as a high temperature moderator material because of its superior ability to retain hydrogen at elevated temperatures. Thermal neutron scattering laws for hydrogen bound in yttrium hydride (H-YH2 and yttrium bound in yttrium hydride (Y-YH2 prepared using the ab initio approach are presented. Density functional theory, incorporating the generalized gradient approximation (GGA for the exchange-correlation energy, is used to simulate the face-centered cubic structure of YH2 and calculate the interatomic Hellmann-Feynman forces for a 2 × 2 × 2 supercell containing 96 atoms. Lattice dynamics calculations using PHONON are then used to determine the phonon dispersion relations and density of states. The calculated phonon density of states for H and Y in YH2 are used to prepare H-YH2 and Y-YH2 thermal scattering laws using the LEAPR module of NJOY2012. Analysis of the resulting integral and differential scattering cross sections demonstrates adequate resolution of the S(α,β function. Comparison of experimental lattice constant, heat capacity, inelastic neutron scattering spectra and total scattering cross section measurements to calculated values are used to validate the thermal scattering laws.
Thermal neutron scattering cross sections of beryllium and magnesium oxides
International Nuclear Information System (INIS)
Al-Qasir, Iyad; Jisrawi, Najeh; Gillette, Victor; Qteish, Abdallah
2016-01-01
Highlights: • Neutron thermalization in BeO and MgO was studied using Ab initio lattice dynamics. • The BeO phonon density of states used to generate the current ENDF library has issues. • The BeO cross sections can provide a more accurate ENDF library than the current one. • For MgO an ENDF library is lacking: a new accurate one can be built from our results. • BeO is a better filter than MgO, especially when cooled down to 77 K. - Abstract: Alkaline-earth beryllium and magnesium oxides are fundamental materials in nuclear industry and thermal neutron scattering applications. The calculation of the thermal neutron scattering cross sections requires a detailed knowledge of the lattice dynamics of the scattering medium. The vibrational properties of BeO and MgO are studied using first-principles calculations within the frame work of the density functional perturbation theory. Excellent agreement between the calculated phonon dispersion relations and the experimental data have been obtained. The phonon densities of states are utilized to calculate the scattering laws using the incoherent approximation. For BeO, there are concerns about the accuracy of the phonon density of states used to generate the current ENDF/B-VII.1 libraries. These concerns are identified, and their influences on the scattering law and inelastic scattering cross section are analyzed. For MgO, no up to date thermal neutron scattering cross section ENDF library is available, and our results represent a potential one for use in different applications. Moreover, the BeO and MgO efficiencies as neutron filters at different temperatures are investigated. BeO is found to be a better filter than MgO, especially when cooled down, and cooling MgO below 77 K does not significantly improve the filter’s efficiency.
Mancinelli, N. J.; Fischer, K. M.
2018-03-01
We characterize the spatial sensitivity of Sp converted waves to improve constraints on lateral variations in uppermost-mantle velocity gradients, such as the lithosphere-asthenosphere boundary (LAB) and the mid-lithospheric discontinuities. We use SPECFEM2D to generate 2-D scattering kernels that relate perturbations from an elastic half-space to Sp waveforms. We then show that these kernels can be well approximated using ray theory, and develop an approach to calculating kernels for layered background models. As proof of concept, we show that lateral variations in uppermost-mantle discontinuity structure are retrieved by implementing these scattering kernels in the first iteration of a conjugate-directions inversion algorithm. We evaluate the performance of this technique on synthetic seismograms computed for 2-D models with undulations on the LAB of varying amplitude, wavelength and depth. The technique reliably images the position of discontinuities with dips 100-200 km. In cases of mild topography on a shallow LAB, the relative brightness of the LAB and Moho converters approximately agrees with the ratio of velocity contrasts across the discontinuities. Amplitude retrieval degrades at deeper depths. For dominant periods of 4 s, the minimum station spacing required to produce unaliased results is 5 km, but the application of a Gaussian filter can improve discontinuity imaging where station spacing is greater.
Measurement of the stimulated thermal Rayleigh scattering instability
International Nuclear Information System (INIS)
Karr, T.J.; Rushford, M.C.; Murray, J.R.; Morris, J.R.
1989-04-01
Growth of perturbations due to stimulated thermal Rayleigh scattering was observed on a laser beam propagating in a 1 meter cell of CC14. Initial sinusoidal irradiance perturbations were seeded onto the laser leam, and their amplification in the cell was recorded by a near field camera. The perturbation growth rate is in agreement with analytical predictions of linearized propagation theory
International Nuclear Information System (INIS)
Zhao, Shuyuan; Zhang, Wenjiao; He, Xiaodong; Li, Jianjun; Yao, Yongtao; Lin, Xiu
2015-01-01
To probe thermal degradation behavior of fibrous insulation for long-term service, an inverse analysis model was developed to simultaneously reconstruct thermal degradation properties of fibers after thermal exposures from the experimental thermal response data, by using the measured infrared spectral transmittance and X-ray phase analysis data as direct inputs. To take into account the possible influence of fibers degradation after thermal exposure on the conduction heat transfer, we introduced a new parameter in the thermal conductivity model. The effect of microstructures on the thermal degradation parameters was evaluated. It was found that after high temperature thermal exposure the decay rate of the radiation intensity passing through the material was weakened, and the probability of being scattered decreased during the photons traveling in the medium. The fibrous medium scattered more radiation into the forward directions. The shortened heat transfer path due to possible mechanical degradation, along with the enhancement of mean free path of phonon scattering as devitrification after severe heat treatment, made the coupled solid/gas thermal conductivities increase with the rise of heat treatment temperature. - Highlights: • A new model is developed to probe conductive and radiative properties degradation of fibers. • To characterize mechanical degradation, a new parameter is introduced in the model. • Thermal degradation properties are reconstructed from experiments by L–M algorithm. • The effect of microstructures on the thermal degradation parameters is evaluated. • The analysis provides a powerful tool to quantify thermal degradation of fiber medium
Directory of Open Access Journals (Sweden)
S. M.A. Elbadawi
2017-03-01
Full Text Available In the present study, the effects of roasting and boiling on the proximate composition of the kernels as well as the physicochemical properties and oxidative stabilities of the extracted oils of Balanites aegyptiaca were investigated. Roasting was performed at 180 ˚C for 15 minutes, whereas boiling of the kernels was carried out in tap water for one hour. The oils from raw and thermally processed samples were extracted using n-hexane in a Soxhlet extraction apparatus and characterized. The roasting significantly (p < 0.05 influenced the peroxide value and the oxidative stability of the extracted oil in a positive way; whereas boiling had the opposite effect. The oils were composed of linoleic, oleic, stearic, and palmitic acids as the major fatty acids (96% and contained predominantly α- and γ-tocopherols (ca. 400mg/kg. The study suggests that the oil from roasted kernels could be used as a natural antioxidant for enhancing the characteristics of other edible oils via blending.
International Nuclear Information System (INIS)
Elbadawi, S.M.A.; Ahmad, E.E.M.; Mariod, A.A.; Mathäus, B.
2017-01-01
In the present study, the effects of roasting and boiling on the proximate composition of the kernels as well as the physicochemical properties and oxidative stabilities of the extracted oils of Balanites aegyptiaca were investigated. Roasting was performed at 180 °C for 15 minutes, whereas boiling of the kernels was carried out in tap water for one hour. The oils from raw and thermally processed samples were extracted using n-hexane in a Soxhlet extraction apparatus and characterized. The roasting significantly (p < 0.05) influenced the peroxide value and the oxidative stability of the extracted oil in a positive way; whereas boiling had the opposite effect. The oils were composed of linoleic, oleic, stearic, and palmitic acids as the major fatty acids (96%) and contained predominantly α- and γ-tocopherols (ca. 400mg/kg). The study suggests that the oil from roasted kernels could be used as a natural antioxidant for enhancing the characteristics of other edible oils via blending. [es
Phonon Surface Scattering and Thermal Energy Distribution in Superlattices.
Kothari, Kartik; Maldovan, Martin
2017-07-17
Thermal transport at small length scales has attracted significant attention in recent years and various experimental and theoretical methods have been developed to establish the reduced thermal conductivity. The fundamental understanding of how phonons move and the physical mechanisms behind nanoscale thermal transport, however, remains poorly understood. Here we move beyond thermal conductivity calculations and provide a rigorous and comprehensive physical description of thermal phonon transport in superlattices by solving the Boltzmann transport equation and using the Beckman-Kirchhoff surface scattering theory with shadowing to precisely describe phonon-surface interactions. We show that thermal transport in superlattices can be divided in two different heat transport modes having different physical properties at small length scales: layer-restricted and extended heat modes. We study how interface conditions, periodicity, and composition can be used to manipulate the distribution of thermal energy flow among such layer-restricted and extended heat modes. From predicted frequency and mean free path spectra of superlattices, we also investigate the existence of wave effects. The results and insights in this paper advance the fundamental understanding of heat transport in superlattices and the prospects of rationally designing thermal systems with tailored phonon transport properties.
Thermal neutron scattering studies of condensed matter under high pressures
International Nuclear Information System (INIS)
Carlile, C.J.; Salter, D.C.
1978-01-01
Although temperature has been used as a thermodynamic variable for samples in thermal neutron scattering experiments since the inception of the neutron technique, it is only in the last decade that high pressures have been utilised for this purpose. In the paper the problems particular to this field of work are outlined and a review is made of the types of high-pressure cells used and the scientific results obtained from the experiments. 103 references. (author)
Benchmark calculations of thermal reaction rates. I - Quantal scattering theory
Chatfield, David C.; Truhlar, Donald G.; Schwenke, David W.
1991-01-01
The thermal rate coefficient for the prototype reaction H + H2 yields H2 + H with zero total angular momentum is calculated by summing, averaging, and numerically integrating state-to-state reaction probabilities calculated by time-independent quantum-mechanical scattering theory. The results are very carefully converged with respect to all numerical parameters in order to provide high-precision benchmark results for confirming the accuracy of new methods and testing their efficiency.
International Nuclear Information System (INIS)
Akaho, E.H.K.; Dagadu, C.P.K.; Maaku, B.T.; Anim-Sampong, S.; Kyere, A.W.K.; Jonah, S.A.
2001-01-01
A fast and non-destructive technique based on thermal neutron moderation has been used for determining the total hydrogen content in two types of red palm oil (dzomi and amidze) and palm kernel oil produced by traditional methods in Ghana. An equipment consisting of an 241 Am-Be neutron source and 3 He neutron detector was used in the investigation. The equipment was originally designed for detection of liquid levels in petrochemical and other process industries. Standards in the form of liquid hydrocarbons were used to obtain calibration lines for thermal neutron reflection parameter as a function of hydrogen content. Measured reflection parameters with respective hydrogen content with or without heat treatment of the three edible palm oils available on the market were compared with a brand cooking oil (frytol). The average total hydrogen content in the local oil samples prior to heating was measured to be 11.62 w% which compared well with acceptable value of 12 w% for palm oils in the sub-region. After heat treatment, the frytol oil (produced through bleaching process) had the least loss of hydrogen content of 0.26% in comparison with palm kernel oil of 0.44% followed by dzomi of 1.96% and by amidze of 3.22%. (author)
Compton scattering at finite temperature: thermal field dynamics approach
International Nuclear Information System (INIS)
Juraev, F.I.
2006-01-01
Full text: Compton scattering is a classical problem of quantum electrodynamics and has been studied in its early beginnings. Perturbation theory and Feynman diagram technique enables comprehensive analysis of this problem on the basis of which famous Klein-Nishina formula is obtained [1, 2]. In this work this problem is extended to the case of finite temperature. Finite-temperature effects in Compton scattering is of practical importance for various processes in relativistic thermal plasmas in astrophysics. Recently Compton effect have been explored using closed-time path formalism with temperature corrections estimated [3]. It was found that the thermal cross section can be larger than that for zero-temperature by several orders of magnitude for the high temperature realistic in astrophysics [3]. In our work we use a main tool to account finite-temperature effects, a real-time finite-temperature quantum field theory, so-called thermofield dynamics [4, 5]. Thermofield dynamics is a canonical formalism to explore field-theoretical processes at finite temperature. It consists of two steps, doubling of Fock space and Bogolyubov transformations. Doubling leads to appearing additional degrees of freedom, called tilded operators which together with usual field operators create so-called thermal doublet. Bogolyubov transformations make field operators temperature-dependent. Using this formalism we treat Compton scattering at finite temperature via replacing in transition amplitude zero-temperature propagators by finite-temperature ones. As a result finite-temperature extension of the Klein-Nishina formula is obtained in which differential cross section is represented as a sum of zero-temperature cross section and finite-temperature correction. The obtained result could be useful in quantum electrodynamics of lasers and for relativistic thermal plasma processes in astrophysics where correct account of finite-temperature effects is important. (author)
Equilibrium limit of thermal conduction and boundary scattering in nanostructures.
Haskins, Justin B; Kınacı, Alper; Sevik, Cem; Çağın, Tahir
2014-06-28
Determining the lattice thermal conductivity (κ) of nanostructures is especially challenging in that, aside from the phonon-phonon scattering present in large systems, the scattering of phonons from the system boundary greatly influences heat transport, particularly when system length (L) is less than the average phonon mean free path (MFP). One possible route to modeling κ in these systems is through molecular dynamics (MD) simulations, inherently including both phonon-phonon and phonon-boundary scattering effects in the classical limit. Here, we compare current MD methods for computing κ in nanostructures with both L ⩽ MFP and L ≫ MFP, referred to as mean free path constrained (cMFP) and unconstrained (uMFP), respectively. Using a (10,0) CNT (carbon nanotube) as a benchmark case, we find that while the uMFP limit of κ is well-defined through the use of equilibrium MD and the time-correlation formalism, the standard equilibrium procedure for κ is not appropriate for the treatment of the cMFP limit because of the large influence of boundary scattering. To address this issue, we define an appropriate equilibrium procedure for cMFP systems that, through comparison to high-fidelity non-equilibrium methods, is shown to be the low thermal gradient limit to non-equilibrium results. Further, as a means of predicting κ in systems having L ≫ MFP from cMFP results, we employ an extrapolation procedure based on the phenomenological, boundary scattering inclusive expression of Callaway [Phys. Rev. 113, 1046 (1959)]. Using κ from systems with L ⩽ 3 μm in the extrapolation, we find that the equilibrium uMFP κ of a (10,0) CNT can be predicted within 5%. The equilibrium procedure is then applied to a variety of carbon-based nanostructures, such as graphene flakes (GF), graphene nanoribbons (GNRs), CNTs, and icosahedral fullerenes, to determine the influence of size and environment (suspended versus supported) on κ. Concerning the GF and GNR systems, we find that
International Nuclear Information System (INIS)
Farag, M.D
2007-01-01
The raw seed kernels of local mango (MSK) varieties (Magnifera indica L.) were analyzed for composition, levels of trypsin inhibitors, tannins, cyanogenetic glucosides, in vitro protein digestibility and apparent metabolizable energy (AMEn) as being effected by boiling, autoclaving as well as irradiation processing at doses 5, 10, 15, and 20 kGy. The air-dry mango kernels contained 70, 128, and 67 g kg -1 of crude protein, crude fat, and tannins, respectively. Compared with raw samples, the contents of trypsin inhibitory activity (30 TIU g -1 ) and cyanogenetic glucosides, as hydrocyanic acid, (71 mg kg -1 ) were lowered by boiling, autoclaving and radiation treatments. Only boiling and autoclaving lowered tannin content (67.2 g kg -1 in raw kernel), but irradiation does not introduce any effect. The in vitro protein digestibility and AMEn values of raw MSK were low and the processing methods enhanced the in vitro protein digestibility and AMEn of MSK. The improvements paralleled reductions in trypsin inhibitory activity, cyanogenetic glucosides and tannin contents. Greater improvements were noticed with boiling and autoclaving than with irradiation alone. While autoclaving for 30min plus irradiation treatment up to 20 kGy maximized the in vitro protein digestibility and AMEn value by 139% and 72%, respectively. These results indicate that tannins, trypsin inhibitors and cyanogenetic glucosides, are responsible for poor nutritive value of MSK. The results suggested that the combination of autoclaving for 30 min plus irradiation treatment up to 20 kGy upgraded the nutritive value and that this method is more effective in processing MSK to be used as animal feed.
Energy Technology Data Exchange (ETDEWEB)
Jeong, Kyung Chai; Eom, Sung Ho; Kim, Yeon Ku; Yeo, Seoung Hwan; Kim, Young Min; Cho, Moon Sung [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2016-10-15
VHTR (Very High Temperature Gas Reactor) fuel technology is being actively developed in the US, China, Japan, and Korea for a Next Generation Nuclear Plant (NGNP). The concept of fuel of a VHTR is based on a sphere kernel of UO{sub 2} or UCO, with multiple coating layers to create a gas-tight particle. The fuel particle of a VHTR in the US is based on microspheres containing a UCO, mixture compound of UO{sub 2} and UC{sub 2} , coated particles with multi carbon layers and a SiC layer. This was first prepared through an internal gelation method at ORNL in the late 1970s. This study presents; (1) C-ADU gel particles were prepared using a modified sol-gel process. The particles fabricated with a KAERI-established gelation and AWD processes showed good sphericity and no cracks were found on the surfaces. (2) High temperature rotating furnace was designed and fabricated in our laboratory, and the maximum operation temperature was about 2000℃. The furnace was equipped with Mo crucible and graphite heating system, and now it is being operated. (3) Well-prepared C-ADU gel particles were converted into UCO compounds using high temperature rotating furnace, and the physical properties of the UCO kernels will be analyzed.
The fluctuating ribosome: thermal molecular dynamics characterized by neutron scattering
Zaccai, Giuseppe; Natali, Francesca; Peters, Judith; Řihová, Martina; Zimmerman, Ella; Ollivier, J.; Combet, J.; Maurel, Marie-Christine; Bashan, Anat; Yonath, Ada
2016-11-01
Conformational changes associated with ribosome function have been identified by X-ray crystallography and cryo-electron microscopy. These methods, however, inform poorly on timescales. Neutron scattering is well adapted for direct measurements of thermal molecular dynamics, the ‘lubricant’ for the conformational fluctuations required for biological activity. The method was applied to compare water dynamics and conformational fluctuations in the 30 S and 50 S ribosomal subunits from Haloarcula marismortui, under high salt, stable conditions. Similar free and hydration water diffusion parameters are found for both subunits. With respect to the 50 S subunit, the 30 S is characterized by a softer force constant and larger mean square displacements (MSD), which would facilitate conformational adjustments required for messenger and transfer RNA binding. It has been shown previously that systems from mesophiles and extremophiles are adapted to have similar MSD under their respective physiological conditions. This suggests that the results presented are not specific to halophiles in high salt but a general property of ribosome dynamics under corresponding, active conditions. The current study opens new perspectives for neutron scattering characterization of component functional molecular dynamics within the ribosome.
Directory of Open Access Journals (Sweden)
D. Chamli
2017-09-01
Full Text Available A comparative study was conducted to determine the fatty acids, triacylglycerol compositions and thermal properties of Tunisian kernel oils from the Prunus persica varieties, peach and nectarine, grown in two areas of Tunisia, Gabes and Morneg. Qualitatively, the fatty acids composition and triacylglycerol species were identical for all samples. Oleic acid (67.7-75.0% was the main fatty acid, followed by linoleic (15.7-22.1% and palmitic (5.6-6.3% acids. The major triacylglycerol species were triolein, OOO (38.4-50.5%, followed by OOL (18.2-23.2%, POO (8.3-9.7% and OLL (6.3-10.1%. The thermal profiles were highly influenced by the high content of triolein due to the importance of oleic acid in these oils. Moreover, the fatty acids distribution in TAG external positions was determined as corresponding to an α asymmetry coefficient that was between 0.10 and 0.12, indicating a high asymmetry in the distribution of saturated fatty acids in the position sn-1 and sn-3 in the TAG species of all samples.
International Nuclear Information System (INIS)
Abdallah, A. M.; Elsherbiny, E. M.; Sobhy, M.
1995-01-01
The P n -spatial expansion method has been used for calculating the one speed transport utilization factor in heterogenous slab cells in which neutrons may scatter anisotropically; by considering the P 1- approximation with a two-term scattering kernel in both the fuel and moderator regions, an analytical expression for the disadvantage factor has been derived. The numerical results obtained have been shown to be much better than those calculated by the usual P 1- and P 3- approximations and comparable with those obtained by some exact methods. 3 tabs
International Nuclear Information System (INIS)
Sur, B.; Anghel, V.N.P.; Rogge, R.B.; Katsaras, J.
2005-01-01
The diffraction of spherical waves (S waves) interacting with a periodic scattering length distribution produces characteristic intensity patterns known as Kossel and Kikuchi lines (collectively called K lines). The K-line signal can be inverted to give the three-dimensional structure of the coherent scattering length distribution surrounding the source of S waves - a process known as 'Gabor holography' or, simply, 'holography'. This paper outlines a kinematical formulation for the diffraction pattern of monochromatic plane waves scattering from a mixed incoherent and coherent S-wave scattering length distribution. The formulation demonstrates that the diffraction pattern of plane waves incident on a sample with a uniformly random distribution of incoherent scatterers is the same as that from a sample with a single incoherent scatterer per unit cell. In practice, one can therefore reconstruct the holographic data from samples with numerous incoherent S-wave scatterers per unit cell. Thus atomic resolution thermal neutron holography is possible for materials naturally rich in incoherent thermal neutron scatterers, such as hydrogen (e.g., biological and polymeric materials). Additionally, holographic inversions from single-wavelength data have suffered from the so-called conjugate or twin-image problem. The formulation presented for holographic inversion - different from those used previously [e.g., T. Gog et al., Phys. Rev. Lett. 76, 3132 (1996)] - eliminates the twin-image problem for single-wavelength data
Four-phonon scattering significantly reduces intrinsic thermal conductivity of solids
Feng, Tianli; Lindsay, Lucas; Ruan, Xiulin
2017-10-01
For decades, the three-phonon scattering process has been considered to govern thermal transport in solids, while the role of higher-order four-phonon scattering has been persistently unclear and so ignored. However, recent quantitative calculations of three-phonon scattering have often shown a significant overestimation of thermal conductivity as compared to experimental values. In this Rapid Communication we show that four-phonon scattering is generally important in solids and can remedy such discrepancies. For silicon and diamond, the predicted thermal conductivity is reduced by 30% at 1000 K after including four-phonon scattering, bringing predictions in excellent agreement with measurements. For the projected ultrahigh-thermal conductivity material, zinc-blende BAs, a competitor of diamond as a heat sink material, four-phonon scattering is found to be strikingly strong as three-phonon processes have an extremely limited phase space for scattering. The four-phonon scattering reduces the predicted thermal conductivity from 2200 to 1400 W/m K at room temperature. The reduction at 1000 K is 60%. We also find that optical phonon scattering rates are largely affected, being important in applications such as phonon bottlenecks in equilibrating electronic excitations. Recognizing that four-phonon scattering is expensive to calculate, in the end we provide some guidelines on how to quickly assess the significance of four-phonon scattering, based on energy surface anharmonicity and the scattering phase space. Our work clears the decades-long fundamental question of the significance of higher-order scattering, and points out ways to improve thermoelectrics, thermal barrier coatings, nuclear materials, and radiative heat transfer.
Fauzi, Siti Hazirah Mohamad; Rashid, Norizzah Abd; Omar, Zaliha
2013-04-15
Blends of palm stearin (PS), palm kernel oil (PKO) and soybean oil (SBO) at certain proportions were formulated using a mixture design based on simplex-lattice (Design Expert 8.0.4 Stat-Ease Inc., Minneapolis, 2010). All the 10 oil blends were subjected to chemical interesterification (CIE) using sodium methoxide as the catalyst. The solid fat content (SFC), triacylglycerol (TAG) composition, thermal properties (DSC), polymorphism and microstructural properties were studied. Palm-based trans-free table margarine containing ternary mixture of PS/PKO/SBO [49/20/31 (w/w)], was optimally formulated through analysis of multiple isosolid diagrams and was found to have quite similar SMP and SFC profile as compared to the commercial table margarine. This study has shown chemical interesterification are effective in modifying the physicochemical properties of palm stearin, palm kernel oil, soybean oil and their mixtures. Copyright © 2012 Elsevier Ltd. All rights reserved.
Scattering of thermal photons by a 46 GeV positron beam at LEP
International Nuclear Information System (INIS)
Bini, C.; De Zorzi, G.; Diambrini-Palazzi, G.; Di Cosimo, G.; Di Domenico, A.; Gauzzi, P.; Zanello, D.
1991-01-01
The scattering of thermal photons present in the vacuum pipe of LEP against the high energy positron beam has been detected. The spectrum of the back-scattered photons is presented for a positron beam energy of 46.1 GeV. Measurements have been performed in the interaction region 1 with the LEP-5 experiment calorimeter. (orig.)
Set of thermal neutron-scattering experiments for the Weapons Neutron Research Facility
International Nuclear Information System (INIS)
Brugger, R.M.
1975-12-01
Six classes of experiments form the base of a program of thermal neutron scattering at the Weapons Neutron Research (WNR) Facility. Three classes are to determine the average microscopic positions of atoms in materials and three are to determine the microscopic vibrations of these atoms. The first three classes concern (a) powder sample neutron diffraction, (b) small angle scattering, and (c) single crystal Laue diffraction. The second three concern (d) small kappa inelastic scattering, (e) scattering surface phonon measurements, and (f) line widths. An instrument to couple with the WNR pulsed source is briefly outlined for each experiment
Electron-phonon scattering effect on the lattice thermal conductivity of silicon nanostructures.
Fu, Bo; Tang, Guihua; Li, Yifei
2017-11-01
Nanostructuring technology has been widely employed to reduce the thermal conductivity of thermoelectric materials because of the strong phonon-boundary scattering. Optimizing the carrier concentration can not only improve the electrical properties, but also affect the lattice thermal conductivity significantly due to the electron-phonon scattering. The lattice thermal conductivity of silicon nanostructures considering electron-phonon scattering is investigated for comparing the lattice thermal conductivity reductions resulting from nanostructuring technology and the carrier concentration optimization. We performed frequency-dependent simulations of thermal transport systematically in nanowires, solid thin films and nanoporous thin films by solving the phonon Boltzmann transport equation using the discrete ordinate method. All the phonon properties are based on the first-principles calculations. The results show that the lattice thermal conductivity reduction due to the electron-phonon scattering decreases as the feature size of nanostructures goes down and could be ignored at low feature sizes (50 nm for n-type nanowires and 20 nm for p-type nanowires and n-type solid thin films) or a high porosity (0.6 for n-type 500 nm-thick nanoporous thin films) even when the carrier concentration is as high as 10 21 cm -3 . Similarly, the size effect due to the phonon-boundary scattering also becomes less significant with the increase of carrier concentration. The findings provide a fundamental understanding of electron and phonon transports in nanostructures, which is important for the optimization of nanostructured thermoelectric materials.
Ab initio phonon point defect scattering and thermal transport in graphene
Polanco, Carlos A.; Lindsay, Lucas
2018-01-01
We study the scattering of phonons from point defects and their effect on lattice thermal conductivity κ using a parameter-free ab initio Green's function methodology. Specifically, we focus on the scattering of phonons by boron (B), nitrogen (N), and phosphorus substitutions as well as single- and double-carbon vacancies in graphene. We show that changes of the atomic structure and harmonic interatomic force constants locally near defects govern the strength and frequency trends of the scattering of out-of-plane acoustic (ZA) phonons, the dominant heat carriers in graphene. ZA scattering rates due to N substitutions are nearly an order of magnitude smaller than those for B defects despite having similar mass perturbations. Furthermore, ZA phonon scattering rates from N defects decrease with increasing frequency in the lower-frequency spectrum in stark contrast to expected trends from simple models. ZA phonon-vacancy scattering rates are found to have a significantly softer frequency dependence (˜ω0 ) in graphene than typically employed in phenomenological models. The rigorous Green's function calculations demonstrate that typical mass-defect models do not adequately describe ZA phonon-defect scattering rates. Our ab initio calculations capture well the trend of κ vs vacancy density from experiments, though not the magnitudes. This work elucidates important insights into phonon-defect scattering and thermal transport in graphene, and demonstrates the applicability of first-principles methods toward describing these properties in imperfect materials.
Haskins, Justin; Kinaci, Alper; Sevik, Cem; Cagin, Tahir
2012-01-01
It is widely known that graphene and many of its derivative nanostructures have exceedingly high reported thermal conductivities (up to 4000 W/mK at 300 K). Such attractive thermal properties beg the use of these structures in practical devices; however, to implement these materials while preserving transport quality, the influence of structure on thermal conductivity should be thoroughly understood. For graphene nanostructures, having average phonon mean free paths on the order of one micron, a primary concern is how size influences the potential for heat conduction. To investigate this, we employ a novel technique to evaluate the lattice thermal conductivity from the Green-Kubo relations and equilibrium molecular dynamics in systems where phonon-boundary scattering dominates heat flow. Specifically, the thermal conductivities of graphene nanoribbons and carbon nanotubes are calculated in sizes up to 3 microns, and the relative influence of boundary scattering on thermal transport is determined to be dominant at sizes less than 1 micron, after which the thermal transport largely depends on the quality of the nanostructure interface. The method is also extended to carbon nanostructures (fullerenes) where phonon confinement, as opposed to boundary scattering, dominates, and general trends related to the influence of curvature on thermal transport in these materials are discussed.
Nonlinear inverse scattering methods for thermal- wave slice tomography: a wavelet domain approach
Energy Technology Data Exchange (ETDEWEB)
Miller, E.L. [Department of Electrical and Computer Engineering, Northeastern University, 235 Forsyth Building, Boston, Massachusetts02115 (United States); Nicolaides, L.; Mandelis, A. [Photothermal and Optoelectronic Diagnostics Laboratory, Department of Mechanical Engineering, University of Toronto, 5 Kings College Road, Toronto M5S3G8, Ontario (Canada)
1998-06-01
A wavelet domain, nonlinear inverse scattering approach is presented for imaging subsurface defects in a material sample, given observations of scattered thermal waves. Unlike methods using the Born linearization, our inversion scheme is based on the full wave-field model describing the propagation of thermal waves. Multiresolution techniques are employed to regularize and to lower the computational burden of this ill-posed imaging problem. We use newly developed wavelet-based regularization methods to resolve better the edge structures of defects relative to reconstructions obtained with smoothness-type regularizers. A nonlinear approximation to the exact forward-scattering model is introduced to simplify the inversion with little loss in accuracy. We demonstrate this approach on cross-section imaging problems by using synthetically generated scattering data from transmission and backprojection geometries. {copyright} 1998 Optical Society of America
Characterization of thermal plasmas by laser light scattering
International Nuclear Information System (INIS)
Snyder, S.C.; Lassahn, G.D.; Reynolds, L.D.; Fincke, J.R.
1993-01-01
Characterization of an atmospheric pressure free-burning arc discharge and a plasma jet by lineshape analysis of scattered laser light is described. Unlike emission spectroscopy, this technique provides direct measurement of plasma gas temperature, electron temperature and electron density without the assumption of local thermodynamic equilibrium (LTE). Plasma gas velocity can also be determined from the Doppler shift of the scattered laser light. Radial gas temperature, electron temperature and electron density profiles are presented for an atmospheric pressure argon free-burning arc discharge. These results show a significant departure from LTE in the arc column, contradicting results obtained from emission spectroscopy. Radial gas temperature and gas velocity profiles in the exit plane of a subsonic atmospheric pressure argon plasma jet are also presented. In this case, the results show the plasma jet is close to LTE in the center, but not in the fringes. The velocity profile is parabolic
International Nuclear Information System (INIS)
Dixon, Robert L.; Boone, John M.
2011-01-01
Purpose: Knowledge of the complete axial dose profile f(z), including its long scatter tails, provides the most complete (and flexible) description of the accumulated dose in CT scanning. The CTDI paradigm (including CTDI vol ) requires shift-invariance along z (identical dose profiles spaced at equal intervals), and is therefore inapplicable to many of the new and complex shift-variant scan protocols, e.g., high dose perfusion studies using variable (or zero) pitch. In this work, a convolution-based beam model developed by Dixon et al.[Med. Phys. 32, 3712-3728, (2005)] updated with a scatter LSF kernel (or DSF) derived from a Monte Carlo simulation by Boone [Med. Phys. 36, 4547-4554 (2009)] is used to create an analytical equation for the axial dose profile f(z) in a cylindrical phantom. Using f(z), equations are derived which provide the analytical description of conventional (axial and helical) dose, demonstrating its physical underpinnings; and likewise for the peak axial dose f(0) appropriate to stationary phantom cone beam CT, (SCBCT). The methodology can also be applied to dose calculations in shift-variant scan protocols. This paper is an extension of our recent work Dixon and Boone [Med. Phys. 37, 2703-2718 (2010)], which dealt only with the properties of the peak dose f(0), its relationship to CTDI, and its appropriateness to SCBCT. Methods: The experimental beam profile data f(z) of Mori et al.[Med. Phys. 32, 1061-1069 (2005)] from a 256 channel prototype cone beam scanner for beam widths (apertures) ranging from a = 28 to 138 mm are used to corroborate the theoretical axial profiles in a 32 cm PMMA body phantom. Results: The theoretical functions f(z) closely-matched the central axis experimental profile data 11 for all apertures (a = 28 -138 mm). Integration of f(z) likewise yields analytical equations for all the (CTDI-based) dosimetric quantities of conventional CT (including CTDI L itself) in addition to the peak dose f(0) relevant to SCBCT
Feng, Tianli; Ruan, Xiulin
2018-01-01
We have developed a formalism of the exact solution to linearized phonon Boltzmann transport equation (BTE) for thermal conductivity calculation including three- and four-phonon scattering. We find strikingly high four-phonon scattering rates in single-layer graphene (SLG) based on the optimized Tersoff potential. The reflection symmetry in graphene, which forbids the three-ZA (out-of-plane acoustic) scattering, allows the four-ZA processes ZA +ZA ⇌ZA +ZA and ZA ⇌ZA +ZA + ZA. As a result, the large phonon population of the low-energy ZA branch originated from the quadratic phonon dispersion leads to high four-phonon scattering rates, even much higher than the three-phonon scattering rates at room temperature. These four-phonon processes are dominated by the normal processes, which lead to a failure of the single mode relaxation time approximation. Therefore, we have solved the exact phonon BTE using an iterative scheme and then calculated the length- and temperature-dependent thermal conductivities. We find that the predicted thermal conductivity of SLG is lower than the previously predicted value from the three-phonon scattering only. The relative contribution of the ZA branch is reduced from 70% to 30% when four-phonon scattering is included. Furthermore, we have demonstrated that the four-phonon scattering in multilayer graphene and graphite is not strong due to the ZA splitting by interlayer van der Waals interaction. We also demonstrate that the five-phonon process in SLG is not strong due to the restriction of reflection symmetry.
Energy Technology Data Exchange (ETDEWEB)
Conti, Andrea
2011-10-15
This work is a contribution to the HPLWR2 (High Performance Light Water Reactor Phase 2), a research project having the goal to investigate the technical feasibility of the High Performance Light Water Reactor. The basic idea of the HPLWR is that of an LWR working at supercritical pressure, which would allow heating up the coolant to a temperature of about 500 C without having phase transition and sending the coolant directly to the turbine. One issue aroused by this design, deserving to be addressed by research, is the behaviour of thermal neutrons in supercritical water. At thermal energies, the De Broglie wavelength associated with the neutron is comparable to the interatomic distances in crystals and molecules and the scattering is fully governed by the laws of quantum mechanics, according to which the geometry of the aggregates the nuclei are bound to and their intra- and intermolecular dynamics are of crucial importance. It can be shown that there is a certain mathematical relation between the Fourier-transform of the hydrogen atoms' velocity autocorrelation function and their double-differential scattering cross section. This Fourier-transform, called ''generalized frequency distribution'', can be derived from experimental measurements and, effectively, Bernnat et al. of the Institut fuer Kernenergetik und Energiesysteme of the University of Stuttgart derived the generalized frequency distribution for liquid water on the basis of experimental results of Page and Haywood. Unfortunately there exists no experimental facility nowadays to support a thorough work of this type on supercritical water and therefore the scattering kernel for thermal neutrons in supercritical water is unknown. In criticality calculations involving supercritical water one can turn to one of the thermal scattering kernels available nowadays for hydrogen bound to the H{sub 2}O molecule: for liquid water, for vapour or considering the nuclei of hydrogen as unbound
Czech Academy of Sciences Publication Activity Database
Man, O.; Pantělejev, L.; Kunz, Ludvík
2010-01-01
Roč. 51, č. 2 (2010), s. 209-213 ISSN 1345-9678 R&D Projects: GA AV ČR 1QS200410502 Institutional research plan: CEZ:AV0Z20410507 Keywords : ultra-fine grained copper * thermal stability of microstructure * electron back scattering diffraction * grain size * texture Subject RIV: JG - Metallurgy Impact factor: 0.779, year: 2010
Mean scatterer spacing estimation in normal and thermally coagulated ex vivo bovine liver.
Rubert, Nicholas; Varghese, Tomy
2014-04-01
The liver has been hypothesized to have a unique arrangement of microvasculature that presents as an arrangement of quasiperiodic scatterers to an interrogating ultrasound pulse. The mean scatterer spacing (MSS) of these quasiperiodic scatterers has been proposed as a useful quantitative ultrasound biomarker for characterizing liver tissue. Thermal ablation is an increasingly popular method for treating hepatic tumors, and ultrasonic imaging approaches for delineating the extent of thermal ablation are in high demand. In this work, we examine the distribution of estimated MSS in thermally coagulated bovine liver and normal untreated bovine liver ex vivo. We estimate MSS by detecting local maxima in the spectral coherence function of radio frequency echoes from a clinical transducer, the Siemens VFX 9L4 transducer operating on an S2000 scanner. We find that normal untreated bovine liver was characterized by an MSS of approximately 1.3 mm. We examined regions of interest 12 mm wide laterally, and ranging from 12 mm to 18 mm axially, in 2 mm increments. Over these parameters, the mode of the MSS estimates was between 1.25 and 1.37 mm. On the other hand, estimation of MSS in thermally coagulated liver tissue yields a distribution of MSS estimates whose mode varied between 0.45 and 1.0 mm when examining regions of interest over the same sizes. We demonstrate that the estimated MSS in thermally coagulated liver favors small spacings because the randomly positioned scatterers in this tissue are better modeled as aperiodic scatterers. The submillimeter spacings result from the fact that this was the most probable spacing to be estimated if the discretely sampled spectral coherence function was a uniformly random two-dimensional function.
Kuleev, I G
2001-01-01
The effect of normal processes of the phonon-phonon scattering on the thermal conductivity of the germanium crystals with various isotopic disorder degrees is considered. The phonon pulse redistribution in the normal scattering processes both inside each oscillatory branch (the Simons mechanism) and between various phonon oscillatory branches (the Herring mechanism) is accounted for. The contributions of the longitudinal and cross-sectional phonons drift motion into the thermal conductivity are analyzed. It is shown that the pulse redistribution in the Herring relaxation mechanism leads to essential suppression of the longitudinal phonons drift motion in the isotopically pure germanium crystals. The calculations results of thermal conductivity for the Herring relaxation mechanism agree well with experimental data on the germanium crystals with various isotopic disorder degrees
Mitigation of artifacts in rtm with migration kernel decomposition
Zhan, Ge
2012-01-01
The migration kernel for reverse-time migration (RTM) can be decomposed into four component kernels using Born scattering and migration theory. Each component kernel has a unique physical interpretation and can be interpreted differently. In this paper, we present a generalized diffraction-stack migration approach for reducing RTM artifacts via decomposition of migration kernel. The decomposition leads to an improved understanding of migration artifacts and, therefore, presents us with opportunities for improving the quality of RTM images.
Gyrotron scattering from non-thermal fluctuations in the Tara Tandem Mirror
International Nuclear Information System (INIS)
Machuzak, J.S.; Myer, R.C.; Woskoboinikow, P.P.
1987-09-01
A 137 GHz, ∼0.4 kW, 75 ms pulsed gyrotron has been used for collective Thomson scattering in the Tara Tandem Mirror plug cell at MIT. Scattering from ion cyclotron waves during ion cyclotron resonance frequency (ICRF) heating, ion Bernstein wave harmonics, and plasma fluctuations possibly due to microinstabilities have been observed. The observed harmonic nature of the ion Bernstein waves may be due to an enhanced ion thermal frequency spectrum in an ICRF heated plasma. 6 refs., 1 fig
International Nuclear Information System (INIS)
Verkerk, P.; Pruisken, A.M.M.
1979-01-01
A description is presented of the construction and performance of a container for thermal neutron scattering on a fluid sample with about 1.5 cm -1 macroscopic cross section (neglecting absorption). The maximum pressure is about 900 bar. The container is made of 5052 aluminium capillary with inner diameter 0.75 mm and wall thickness 0.25 mm; it covers a neutron beam with a cross section of 9 X 2.5 cm 2 . The container has been successfully used in neutron diffraction and time-of-flight experiments on argon-36 at 120 K and several pressures up to 850 bar. It is shown that during these measurements the temperature gradient over the sample as well as the error in the absolute temperature were both less than 0.05 K. Subtraction of the Bragg peaks due to container scattering in diffraction experiments may be dfficult, but seems feasible because of the small amount of aluminium in the neutron beam. Correction for container scattering and multiple scattering in time-of-flight experiments may be difficult only in the case of coherently scattering samples and small scattering angles. (Auth.)
International Nuclear Information System (INIS)
Shahriari, M.; Soharbpour, M.
1997-01-01
Monte Carlo calculation using MCNP code has been carried out to determine the time dependent responses of pulsed neutron gamma spectrometry tools. Inelastic scattering and thermal capture gamma count rates after each 14 MeV neutron pulse has been calculated and is shown that the pulse height response of the inelastic gamma rays can be easily separated from the thermal capture gamma response in the time domain. There by it is possible to improve the precision of the carbon oxygen ratios in the borehole formations
Noninvasive monitoring of the thermal stress in RPE using light scattering spectroscopy
Schule, Georg; Huie, Philip; Vankov, Alexander B.; Vitkin, Edward; Fang, Hui; Hanlon, Eugene B.; Perelman, Lev T.; Palanker, Daniel V.
2004-07-01
Introduction: Light Scattering Spectroscopy has been a recently developed as a non-invasive technique capable of sizing the cellular organelles. With this technique, we monitor the heat-induced sub-cellular structural transformations in a human RPE cell culture. Material and Methods: A single layer of human RPE cells (ATCC) was grown on a glass slide. Cells are illuminated with light from a fiber-coupled broadband tungsten lamp. The backscattered (180 degree) light spectra are measured with an optical multichannel analyzer (OMA). Spectra are measured during heating of the sample. Results: We reconstructed the size distribution of sub-micron organelles in the RPE cells and observed temperature-related changes in the scattering density of the organelles in the 200-300nm range (which might be peroxisomes, microsomes or lysosomes). The sizes of the organelles did not vary with temperature, so the change in scattering is most probably due to the change in the refractive indexes. As opposed to strong spectral variation with temperature, the total intensity of the backscattered light did not significantly change in the temperature range of 32-49 °C. Conclusion: We demonstrate that Light Scattering Spectroscopy is a powerful tool for monitoring the temperature-induced sub-cellular transformations. This technique providing an insight into the temperature-induced cellular processes and can play an important role in quantitative assessment of the laser-induced thermal effects during retinal laser treatments, such as Transpupillary Thermal Therapy (TTT), photocoagulation, and Photodynamic Therapy (PDT).
Kovalchuk, M V; Nosik, V L
2001-01-01
A theory of thermal diffuse scattering (TDS) in a crystal disturbed by high frequency ultrasonic vibrations is considered. In this case additional X-ray reflexes (satellites) are formed which can be used for obtaining information about vibrational excitations in a crystal. By varying the incident angle one can excite all the satellites one after another and detect the variation in the TDS yield. The possibilities of the experimental observation of these phenomena will also be discussed.
Comparison of thermal scattering processing options for S(α,β) cards in MCNP
International Nuclear Information System (INIS)
Čerba, Štefan; Damian, Jose Ignacio Marquez; Lüley, Jakub; Vrban, Branislav; Farkas, Gabriel; Nečas, Vladimír; Haščík, Jan
2013-01-01
Highlights: ► Determination of MCNP calculation bias for WWER-440. ► Specific scattering law S(α,β). ► Benchmark cases investigated. ► Three methods to process material cards for hydrogen bound in light water. - Abstract: The MCNP distributions include sets of pre-calculated thermal scattering libraries but these libraries are available for several temperature steps only. In order to achieve reliable results it is suitable to process the cross section libraries for the desired temperature. In general, there are three methods to process these thermal scattering libraries for the desired temperatures. This paper deals with the comparison of these three methods on the basis of several benchmarks and on the basis of a thermal transient experiment of a WWER-440 reactor. The choice is up to the MCNP user but unfortunately very few studies concerning the comparison have been published so far. Therefore conclusions and results presented in this paper may help the user to choose the most appropriate method for his calculation
Phononic thermal conductivity in silicene: the role of vacancy defects and boundary scattering
Barati, M.; Vazifehshenas, T.; Salavati-fard, T.; Farmanbar, M.
2018-04-01
We calculate the thermal conductivity of free-standing silicene using the phonon Boltzmann transport equation within the relaxation time approximation. In this calculation, we investigate the effects of sample size and different scattering mechanisms such as phonon–phonon, phonon-boundary, phonon-isotope and phonon-vacancy defect. We obtain some similar results to earlier works using a different model and provide a more detailed analysis of the phonon conduction behavior and various mode contributions. We show that the dominant contribution to the thermal conductivity of silicene, which originates from the in-plane acoustic branches, is about 70% at room temperature and this contribution becomes larger by considering vacancy defects. Our results indicate that while the thermal conductivity of silicene is significantly suppressed by the vacancy defects, the effect of isotopes on the phononic transport is small. Our calculations demonstrate that by removing only one of every 400 silicon atoms, a substantial reduction of about 58% in thermal conductivity is achieved. Furthermore, we find that the phonon-boundary scattering is important in defectless and small-size silicene samples, especially at low temperatures.
International Nuclear Information System (INIS)
Broome, J.
1965-11-01
The programme SCATTER is a KDF9 programme in the Egtran dialect of Fortran to generate normalized angular distributions for elastically scattered neutrons from data input as the coefficients of a Legendre polynomial series, or from differential cross-section data. Also, differential cross-section data may be analysed to produce Legendre polynomial coefficients. Output on cards punched in the format of the U.K. A. E. A. Nuclear Data Library is optional. (author)
Optimizing Neutron Thermal Scattering Effects in very High Temperature Reactors. Final Report
International Nuclear Information System (INIS)
Hawari, Ayman
2014-01-01
This project aims to develop a holistic understanding of the phenomenon of neutron thermalization in the VHTR. Neutron thermalization is dependent on the type and structure of the moderating material. The fact that the moderator (and reflector) in the VHTR is a solid material will introduce new and interesting considerations that do not apply in other (e.g. light water) reactors. The moderator structure is expected to undergo radiation induced changes as the irradiation (or burnup) history progresses. In this case, the induced changes in structure will have a direct impact on many properties including the neutronic behavior. This can be easily anticipated if one recognizes the dependence of neutron thermalization on the scattering law of the moderator. For the pebble bed reactor, it is anticipated that the moderating behavior can be tailored, e.g. using moderators that consist of composite materials, which could allow improved optimization of the moderator-to-fuel ratio.
A neutron scattering study on the stability of trehalose mycolates under thermal stress
International Nuclear Information System (INIS)
Migliardo, F.; Salmeron, C.; Bayan, N.
2013-01-01
Highlights: ► Neutron scattering measurements have been performed on mycolate water mixtures. ► A comparison with lecithin lipid water mixtures has been carried out. ► Mycolates show a lower mobility and flexibility compared to lecithin. ► The observed peculiarities of mycolic acids could be ascribed to trehalose. ► The results could justify the high resistance to thermal stress of mycobacteria. - Abstract: The present paper is focused on the study of the dynamics of mycolic acids, which are fundamental components of the outer membrane (mycomembrane) of Mycobacterium tuberculosis. An elastic neutron scattering study of mycolic acid/H 2 O and lecithin/H 2 O mixtures as a function of temperature and exchanged wavevector Q has been carried out. This study provides an effective way for characterizing the dynamical properties, furnishing a set of parameters characterizing the different flexibility and rigidity of the investigated lipids. The behavior of the elastically scattered intensity profiles and the derived mean square displacements as a function of temperature shows a more marked temperature dependence for lecithin lipids in comparison with mycolic acids, so revealing a higher thermal stability of these latter. These findings could be useful for understanding the dynamics-function relation in the mycomembrane and then to relate it to the low permeability and high resistance of mycobacteria to many antibiotics
A neutron scattering study on the stability of trehalose mycolates under thermal stress
Energy Technology Data Exchange (ETDEWEB)
Migliardo, F., E-mail: fmigliardo@unime.it [Department of Physics, University of Messina, Viale D’Alcontres 31, 98166 Messina (Italy); Salmeron, C.; Bayan, N. [Laboratoire de Microbiologie Moléculaire et Cellulaire, IBBMC, Bat 430, Université de Paris Sud XI, 15 rue Georges Clémenceau, 91405 Orsay Cedex (France)
2013-10-16
Highlights: ► Neutron scattering measurements have been performed on mycolate water mixtures. ► A comparison with lecithin lipid water mixtures has been carried out. ► Mycolates show a lower mobility and flexibility compared to lecithin. ► The observed peculiarities of mycolic acids could be ascribed to trehalose. ► The results could justify the high resistance to thermal stress of mycobacteria. - Abstract: The present paper is focused on the study of the dynamics of mycolic acids, which are fundamental components of the outer membrane (mycomembrane) of Mycobacterium tuberculosis. An elastic neutron scattering study of mycolic acid/H{sub 2}O and lecithin/H{sub 2}O mixtures as a function of temperature and exchanged wavevector Q has been carried out. This study provides an effective way for characterizing the dynamical properties, furnishing a set of parameters characterizing the different flexibility and rigidity of the investigated lipids. The behavior of the elastically scattered intensity profiles and the derived mean square displacements as a function of temperature shows a more marked temperature dependence for lecithin lipids in comparison with mycolic acids, so revealing a higher thermal stability of these latter. These findings could be useful for understanding the dynamics-function relation in the mycomembrane and then to relate it to the low permeability and high resistance of mycobacteria to many antibiotics.
A neutron scattering study on the stability of trehalose mycolates under thermal stress
Migliardo, F.; Salmeron, C.; Bayan, N.
2013-10-01
The present paper is focused on the study of the dynamics of mycolic acids, which are fundamental components of the outer membrane (mycomembrane) of Mycobacterium tuberculosis. An elastic neutron scattering study of mycolic acid/H2O and lecithin/H2O mixtures as a function of temperature and exchanged wavevector Q has been carried out. This study provides an effective way for characterizing the dynamical properties, furnishing a set of parameters characterizing the different flexibility and rigidity of the investigated lipids. The behavior of the elastically scattered intensity profiles and the derived mean square displacements as a function of temperature shows a more marked temperature dependence for lecithin lipids in comparison with mycolic acids, so revealing a higher thermal stability of these latter. These findings could be useful for understanding the dynamics-function relation in the mycomembrane and then to relate it to the low permeability and high resistance of mycobacteria to many antibiotics.
Verstraeten, B.; Sermeus, J.; Salenbien, R.; Fivez, J.; Shkerdin, G.; Glorieux, C.
2015-01-01
The underlying working principle of detecting impulsive stimulated scattering signals in a differential configuration of heterodyne diffraction detection is unraveled by involving optical scattering theory. The feasibility of the method for the thermoelastic characterization of coating-substrate systems is demonstrated on the basis of simulated data containing typical levels of noise. Besides the classical analysis of the photoacoustic part of the signals, which involves fitting surface acoustic wave dispersion curves, the photothermal part of the signals is analyzed by introducing thermal wave dispersion curves to represent and interpret their grating wavelength dependence. The intrinsic possibilities and limitations of both inverse problems are quantified by making use of least and most squares analysis. PMID:26236643
Experimental determination of anomalous scattering lengths of samarium for thermal neutrons
International Nuclear Information System (INIS)
Engel, D.W.; Koetzle, T.F.
1981-01-01
Anomalous scattering lengths of natural Sm for thermal neutrons with wavelengths between 0.827 and 1.300 A have been determined using a single crysrtal of a Sm-complex of known structure. 140 selected reflections were measured at each wavelength and b 0 + b' and b'' refined in each case. The values obtained are in good agreement with theoretical values obtained from a Breit-Wigner calculation using tabulated resonance parameters for 149 Sm. A value of b 0 = 4.3 +- 0.2 fm is deduced from the diffraction experiment
Elo, Teemu; Lähteenmäki, Pasi; Golubev, Dmitri; Savin, Alexander; Arutyunov, Konstantin; Hakonen, Pertti
2017-11-01
We have employed noise thermometry for investigations of thermal relaxation between the electrons and the substrate in nanowires patterned from 40-nm-thick titanium film on top of silicon wafers covered by a native oxide. By controlling the electronic temperature T_e by Joule heating at the base temperature of a dilution refrigerator, we probe the electron-phonon coupling and the thermal boundary resistance at temperatures T_e= 0.5-3 K. Using a regular T^5-dependent electron-phonon coupling of clean metals and a T^4-dependent interfacial heat flow, we deduce a small contribution for the direct energy transfer from the titanium electrons to the substrate phonons due to inelastic electron-boundary scattering.
An evaluation of the ENDF/GASKET model for thermal neutron scattering in heavy water
International Nuclear Information System (INIS)
Abbate, M.J.; Antunez, H.M.
1977-06-01
The ENDF/GASKET model for computing thermal neutron scattering was selected for studies undertaken with the purpose of getting thoroughly acquainted with the behavior of the heavy water as a moderator. As a first step in its evaluation, the scattering law S(α,β) was computed with ENDF/GASKET. A comparison of the values so obtained with others previously measured or computed showed that the model is not completely satisfactory in this respect. This is attributed to coherent scattering not included in the model and to the need of improving its frequency spectrum. Any way, the experimental values show serious descrepancies and it is difficult to reach definitive conclusions. The Legendre moments of the double differential cross section and its microscopic values were also computed. As it was found by other authors, the incoherent approximation of ENDF/GASKET results in a drastic departure from the measured total cross section below 0,006 eV. In addition, the discrepancies between measured and calculated average μ, might also imply that the coherence effects are appreciable at higher energies. Also decay constance and diffusion parameters were computed for D 2 O (100%), and these agree well with values of other sources. The measurement and computation of neutron spectra in heavy water is presently intented for the sake of completing evaluation. So far two alternatives are foreseen for further work: the improvement of ENDF/GASKET, or the evaluation of the more recent Jarvis model. (author) [es
Neutron spectral modulation as a new thermal neutron scattering technique. Pt. 1
International Nuclear Information System (INIS)
Ito, Y.; Nishi, M.; Motoya, K.
1982-01-01
A thermal neutron scattering technique is presented based on a new idea of labelling each neutron in its spectral position as well as in time through the scattering process. The method makes possible the simultaneous determination of both the accurate dispersion relation and its broadening by utilizing the resolution cancellation property of zero-crossing points in the cross-correlated time spectrum together with the Fourier transform scheme of the neutron spin echo without resorting to the echoing. The channel Fourier transform applied to the present method also makes possible the determination of the accurate direct energy scan profile of the scattering function with a rather broad incident neutron wavelength distribution. Therefore the intensity sacrifice for attaining high accurarcy is minimized. The technique is used with either a polarized or unpolarized beam at the sample position with no precautions against beam depolarization at the sample for the latter case. Relative time accurarcy of the order of 10 -3 to 10 -4 may be obtained for the general dispersion relation and for the quasi-elastic energy transfers using correspondingly the relative incident neutron wavelength spread of 10 to 1% around an incident neutron energy of a few meV. (orig.)
A relationship between Gel'fand-Levitan and Marchenko kernels
International Nuclear Information System (INIS)
Kirst, T.; Von Geramb, H.V.; Amos, K.A.
1989-01-01
An integral equation which relates the output kernels of the Gel'fand-Levitan and Marchenko inverse scattering equations is specified. Structural details of this integral equation are studied when the S-matrix is a rational function, and the output kernels are separable in terms of Bessel, Hankel and Jost solutions. 4 refs
On sensitivity kernels for 'wave-equation' transmission tomography
Hoop, Maarten V. de; Hilst, R.D. van der
2004-01-01
We combine seismological scattering theory with the theory of distributions to study some properties of sensitivity kernels for finite frequency seismic delay times. The theory to be used for calculating the kernels depends on the way the measurements are made. For example, the sensitivity to the
International Nuclear Information System (INIS)
Ozgener, B.; Ozgener, H.A.
2005-01-01
A multiregion, multigroup collision probability method with white boundary condition is developed for thermalization calculations of light water moderated reactors. Hydrogen scatterings are treated by Nelkin's kernel while scatterings from other nuclei are assumed to obey the free-gas scattering kernel. The isotropic return (white) boundary condition is applied directly by using the appropriate collision probabilities. Comparisons with alternate numerical methods show the validity of the present formulation. Comparisons with some experimental results indicate that the present formulation is capable of calculating disadvantage factors which are closer to the experimental results than alternative methods
Defect induced phonon scattering for tuning the lattice thermal conductivity of SiO2 thin films
Directory of Open Access Journals (Sweden)
Sen Cao
2017-01-01
Full Text Available In this work, the thermal properties of nanoscale SiO2 thin films have been systematically investigated with respect to the thickness, crystal orientations and the void defects using non-equilibrium molecular-dynamics (NEMD simulation. Size effect for the lattice thermal conductivity of nanoscale SiO2 thin films was observed. Additionally, SiO2 thin films with [001] oriented exhibited greater thermal conductivity compared with other crystal orientations which was discussed in terms of phonon density of states (PDOS. Furthermore, the porosity of void defects was introduced to quantify the influence of defects for thermal conductivity. Results exhibited that the thermal conductivity degraded with the increase of porosity. Two thermal conductivity suppression mechanisms, namely, void defects induced material loss interdicting heat conduction and phonon scattering enhanced by the boundary of defects, were proposed. Then, a further simulation was deployed to find that the effect of boundary scattering of defects was dominant in thermal conductivity degradation compared with material loss mechanism. The conclusion suggests that the thermal conductivity could be configured via regulating the distribution of PDOS directly associated with void defects.
Biagioni, Angelo; Bettucci, Andrea; Passeri, Daniele; Alippi, Adriano
2015-06-01
Ultrasound contrast agents are used in echographic imaging techniques to enhance image contrast. In addition, they may represent an interesting solution to the problem of non-invasive temperature monitoring inside the human body, based on some thermal variations of their physical properties. Contrast agents, indeed, are inserted into blood circulation and they reach the most important organs inside the human body; consequently, any thermometric property that they may possess, could be exploited for realizing a non-invasive thermometer. They essentially are a suspension of microbubbles containing a gas enclosed in a phospholipid membrane; temperature variations induce structural modifications of the microbubble phospholipid shell, thus causing thermal dependence of contrast agent's elastic characteristics. In this paper, the acoustic scattering efficiency of a bulk suspension of of SonoVue® (Bracco SpA Milan, Italy) has been studied using a pulse-echo technique in the frequency range 1-17 MHz, as it depends upon temperatures between 25 and 65°C. Experimental data confirm that the ultrasonic attenuation coefficient of SonoVue® depends on temperature between 25 and 60°C. Chemical composition of the bubble shell seem to support the hypothesis that a phase transition in the microstructure of lipid-coated microbubbles could play a key role in explaining such effect.
Update of Continuous-Energy Data for Hydrogen and SiO_{2} Thermal Scattering
Energy Technology Data Exchange (ETDEWEB)
Conlin, Jeremy Lloyd [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Parsons, Donald Kent [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-02-23
The Nuclear Data Team has released updated continuous-energy neutron data files for: 1) hydrogen, and 2) S (α; β) (thermal scattering) on SiO_{2}. A list of new ZAIDs and the data that is updated (Old ZAID) is given in Table 1. The old data are still accessible, but are not the default.
Collision kernels in the eikonal approximation for Lennard-Jones interaction potential
International Nuclear Information System (INIS)
Zielinska, S.
1985-03-01
The velocity changing collisions are conveniently described by collisional kernels. These kernels depend on an interaction potential and there is a necessity for evaluating them for realistic interatomic potentials. Using the collision kernels, we are able to investigate the redistribution of atomic population's caused by the laser light and velocity changing collisions. In this paper we present the method of evaluating the collision kernels in the eikonal approximation. We discuss the influence of the potential parameters Rsub(o)sup(i), epsilonsub(o)sup(i) on kernel width for a given atomic state. It turns out that unlike the collision kernel for the hard sphere model of scattering the Lennard-Jones kernel is not so sensitive to changes of Rsub(o)sup(i) as the previous one. Contrary to the general tendency of approximating collisional kernels by the Gaussian curve, kernels for the Lennard-Jones potential do not exhibit such a behaviour. (author)
Neutron cross sections of cryogenic materials: a synthetic kernel for molecular solids
International Nuclear Information System (INIS)
Granada, J.R.; Gillette, V.H.; Petriw, S.; Cantargi, F.; Pepe, M.E.; Sbaffoni, M.M.
2004-01-01
A new synthetic scattering function aimed at the description of the interaction of thermal neutrons with molecular solids has been developed. At low incident neutron energies, both lattice modes and molecular rotations are specifically accounted for, through an expansion of the scattering law in few phonon terms. Simple representations of the molecular dynamical modes are used, in order to produce a fairly accurate description of neutron scattering kernels and cross sections with a minimum set of input data. As the neutron energies become much larger than that corresponding to the characteristic Debye temperature and to the rotational energies of the molecular solid, the 'phonon formulation' transforms into the traditional description for molecular gases. (orig.)
Mishchenko, Michael I.
2017-10-01
The majority of previous studies of the interaction of individual particles and multi-particle groups with electromagnetic field have focused on either elastic scattering in the presence of an external field or self-emission of electromagnetic radiation. In this paper we apply semi-classical fluctuational electrodynamics to address the ubiquitous scenario wherein a fixed particle or a fixed multi-particle group is exposed to an external quasi-polychromatic electromagnetic field as well as thermally emits its own electromagnetic radiation. We summarize the main relevant axioms of fluctuational electrodynamics, formulate in maximally rigorous mathematical terms the general scattering-emission problem for a fixed object, and derive such fundamental corollaries as the scattering-emission volume integral equation, the Lippmann-Schwinger equation for the dyadic transition operator, the multi-particle scattering-emission equations, and the far-field limit. We show that in the framework of fluctuational electrodynamics, the computation of the self-emitted component of the total field is completely separated from that of the elastically scattered field. The same is true of the computation of the emitted and elastically scattered components of quadratic/bilinear forms in the total electromagnetic field. These results pave the way to the practical computation of relevant optical observables.
Energy Technology Data Exchange (ETDEWEB)
Duff, I.
1994-12-31
This workshop focuses on kernels for iterative software packages. Specifically, the three speakers discuss various aspects of sparse BLAS kernels. Their topics are: `Current status of user lever sparse BLAS`; Current status of the sparse BLAS toolkit`; and `Adding matrix-matrix and matrix-matrix-matrix multiply to the sparse BLAS toolkit`.
International Nuclear Information System (INIS)
Gangopadhyay, A. K.; Blodgett, M. E.; Johnson, M. L.; Vogt, A. J.; Mauro, N. A.; Kelton, K. F.
2014-01-01
Measurements of sharp diffraction peaks as a function of temperature are routinely used to obtain precise linear expansion coefficients of crystalline solids. In this case, the relation between temperature dependent changes in peak position in momentum transfer (q 1 ) and volume expansion is straightforward (Ehrenfest's relation: q 1 = K(2π/d), where K is a constant and d is the interatomic spacing) and the data obtained are usually in close agreement with more direct measurements. With high intensity synchrotron x-ray and spallation neutron sources, it is also possible to accurately measure the positions of the much broader peaks for liquids and glasses. This has led to a debate on whether linear expansion coefficients derived from these data are an accurate representation of the volume expansion coefficients. We present here volume thermal expansion and x-ray diffraction data for a large number of glass-forming alloy liquids acquired in a containerless environment using the beamline electrostatic levitation technique. The data show a large difference in the values obtained from the two different techniques. Moreover, the position of the first peak (q 1 ) in the scattered intensity in the structure factor (S(q)) and the atomic volume v for all liquids follow a simple relationship, v∝(q 1 ) −ε . The exponent, ε = 2.28 (±0.11), is much different from the expected value of 3 from Ehrenfest's relation and shows no temperature dependence over the temperature range of the data collected
Gärtner, Thomas
2009-01-01
This book provides a unique treatment of an important area of machine learning and answers the question of how kernel methods can be applied to structured data. Kernel methods are a class of state-of-the-art learning algorithms that exhibit excellent learning results in several application domains. Originally, kernel methods were developed with data in mind that can easily be embedded in a Euclidean vector space. Much real-world data does not have this property but is inherently structured. An example of such data, often consulted in the book, is the (2D) graph structure of molecules formed by
International Nuclear Information System (INIS)
Fortier, Dominique.
1976-07-01
Besides the three phonon scattering mechanisms generally considered in insulators, i.e. boundary effect, isotopic scattering and phonon-phonon interaction, the electron-phonon scattering mechanism was studied with special reference to the scattering of thermal phonons by donor impurities in silicon. In order to demonstrate clearly the effect of the electronic structure of the impurity on this scattering, three donor centres were investigated: Li, Li-O and P. On the basis of the calculated relaxation times it was possible from theoretical analysis to account for the main results and to explain why the Li centre scatters thermal phonons more efficiently than Li-O and P centres in the isolated impurity range [fr
Kroah-Hartman, Greg
2009-01-01
Linux Kernel in a Nutshell covers the entire range of kernel tasks, starting with downloading the source and making sure that the kernel is in sync with the versions of the tools you need. In addition to configuration and installation steps, the book offers reference material and discussions of related topics such as control of kernel options at runtime.
Motai, Yuichi
2015-01-01
Describes and discusses the variants of kernel analysis methods for data types that have been intensely studied in recent years This book covers kernel analysis topics ranging from the fundamental theory of kernel functions to its applications. The book surveys the current status, popular trends, and developments in kernel analysis studies. The author discusses multiple kernel learning algorithms and how to choose the appropriate kernels during the learning phase. Data-Variant Kernel Analysis is a new pattern analysis framework for different types of data configurations. The chapters include
Small-angle thermal neutron scattering of hen egg-white lysozyme in aqueous solution
International Nuclear Information System (INIS)
Sangawa, U.; Niimura, N.
1992-01-01
A small-angle neutron scattering measurement was done for a lysozyme sample in aqueous solutions with different D 2 O/H 2 O ratios. Structure parameters such as R gc , α and β and the scattering functions such as I c (Q), I s (Q) and I cs (Q) were obtained. (orig.)
The effect of thermal vibrations of lattice atoms on the scattering of low energetic ions (2-10keV)
International Nuclear Information System (INIS)
Poelsema, B.; Boers, A.L.
1977-01-01
An introduction to the study of solid state surfaces by analyzing the scattering behavior of low energetic noble gas ions is given. Attention is paid to thermal vibrations of the surface atoms. The scattering of Ar and Kr ions on a Cu monocrystal is discussed as an example
Choi, Y N; Lee, C H; Oh, H S; Park, S D; Somenkov, V A
2002-01-01
In neutron-scattering experiments, the incoherent scattering contributes to the background signal, which is an unwelcome property of matter. Among natural nuclei, the hydrogen nucleus (proton) has a remarkably large value of incoherent neutron scattering cross section. Therefore, a very small amount of hydrogen in a material could be analyzed by measuring the neutron incoherent scattering of the material. The hydrogen content of a metal or semiconductor is a matter of concern because it can affect significantly the physical, mechanical or chemical properties of materials although the amount of hydrogen is very small. In this study, the neutron incoherent scattering was measured using a 1-D position-sensitive detector at 1.835 A. Estimated detection limits are about 5 and 2 mu g/g for 10-min and 1-h measurements, respectively. Using the calibration data obtained by measurement of artificial samples (zircaloy+polypropylene films), the relative amounts of hydrogen in three commercial zircaloy samples were estima...
Outline of Neutron Scattering Formalism
Berk, N. F.
1993-01-01
Neutron scattering formalism is briefly surveyed. Topics touched upon include coherent and incoherent scattering, bound and free cross-sections, the Van Hove formalism, magnetic scattering, elastic scattering, the static approximation, sum rules, small angle scattering, inelastic scattering, thermal diffuse scattering, quasielastic scattering, and neutron optics.
Lee, S. H.; Yang, B. X.; Collins, J. T.; Ramanathan, M.
2017-02-01
Accurate and stable x-ray beam position monitors (XBPMs) are key elements in obtaining the desired user beam stability in the Advanced Photon Source Upgrade. In the next-generation XBPMs for the canted-undulator front ends, where two undulator beams are separated by 1.0 mrad, the lower beam power (changes through the interface via thermal simulations, the thermal contact resistance (TCR) of TIMs at an interface between two solid materials under even contact pressure must be known. This paper addresses the TCR measurements of several TIMs, including gold, silver, pyrolytic graphite sheet, and 3D graphene foam. In addition, a prototype of a Compton-scattering XBPM with diamond blades was installed at APS Beamline 24-ID-A in May 2015 and has been tested. This paper presents the design of the Compton-scattering XBPM, and compares thermal simulation results obtained for the diamond blade of this XBPM by the finite element method with in situ empirical measurements obtained by using reliable infrared technology.
Energy Technology Data Exchange (ETDEWEB)
Kozier, K. S.; Roubtsov, D. [AECL, Chalk River Laboratories, Chalk River, ON (Canada); Plompen, A. J. M.; Kopecky, S. [EC-JRC, Inst. for Reference Materials and Measurements, Retieseweg 111, 2440 Geel (Belgium)
2012-07-01
The thermal neutron-elastic-scattering cross-section data for {sup 16}O used in various modern evaluated-nuclear-data libraries were reviewed and found to be generally too high compared with the best available experimental measurements. Some of the proposed revisions to the ENDF/B-VII.0 {sup 16}O data library and recent results from the TENDL system increase this discrepancy further. The reactivity impact of revising the {sup 16}O data downward to be consistent with the best measurements was tested using the JENDL-3.3 {sup 16}O cross-section values and was found to be very small in MCNP5 simulations of the UO{sub 2} and reactor-recycle MOX-fuel cases of the ANS Doppler-defect numerical benchmark. However, large reactivity differences of up to about 14 mk (1400 pcm) were observed using {sup 16}O data files from several evaluated-nuclear-data libraries in MCNP5 simulations of the Los Alamos National Laboratory HEU heavy-water solution thermal critical experiments, which were performed in the 1950's. The latter result suggests that new measurements using HEU in a heavy-water-moderated critical facility, such as the ZED-2 zero-power reactor at the Chalk River Laboratories, might help to resolve the discrepancy between the {sup 16}O thermal elastic-scattering cross-section values and thereby reduce or better define its uncertainty, although additional assessment work would be needed to confirm this. (authors)
Thermal transport across solid-solid interfaces enhanced by pre-interface isotope-phonon scattering
Lee, Eungkyu; Luo, Tengfei
2018-01-01
Thermal transport across solid interfaces can play critical roles in the thermal management of electronics. In this letter, we use non-equilibrium molecular dynamics simulations to investigate the isotope effect on the thermal transport across SiC/GaN interfaces. It is found that engineered isotopes (e.g., 10% 15N or 71Ga) in the GaN layer can increase the interfacial thermal conductance compared to the isotopically pure case by as much as 23%. Different isotope doping features, such as the isotope concentration, skin depth of the isotope region, and its distance from the interface, are investigated, and all of them lead to increases in thermal conductance. Studies of spectral temperatures of phonon modes indicate that interfacial thermal transport due to low-frequency phonons (transport. This work may provide insights into interfacial thermal transport and useful guidance to practical material design.
Martins, Murillo L.; Orecchini, Andrea; Aguilera, Luis; Eckert, Juergen; Embs, Jan; Matic, Aleksander; Saeki, Margarida J.; Bordallo, Heloisa N.
2015-01-01
The anticancer drug paclitaxel was encapsulated into a bio-nanocomposite formed by magnetic nanoparticles, chitosan and apatite. The aim of this drug carrier is to provide a new perspective against breast cancer. The dynamics of the pure and encapsulated drug were investigated in order to verify possible molecular changes caused by the encapsulation, as well as to follow which interactions may occur between paclitaxel and the composite. Fourier transformed infrared spectroscopy, thermal analysis, inelastic and quasi-elastic neutron scattering experiments were performed. These very preliminary results suggest the successful encapsulation of the drug.
Joo, H
1999-01-01
Recent test results indicated drawbacks associated with the simple exponential attenuation method (SEAM) as currently applied to neutron radiography measurements to determine vapor fractions in a hydrogenous two-phase flow in a metallic conduit. The scattering component of the neutron beam intensity exiting the flow system is not adequately accounted for by SEAM, and this leads to inaccurate results. To properly account for the scattering effect, a neutron scattering probability method (SPM) is developed. The method applies a neutron-hydrogen scattering kernel to scattered thermal neutrons that leave the incident beam in narrow conduits but eventually show up elsewhere in the measurements. The SPM has been tested with known vapor (void) distributions within an acrylic disk and a water/vapor channel. The vapor (void) fractions deduced by SPM are in good agreement with the known exact values. Details of the scattering correction method and the test results are discussed.
Multidimensional kernel estimation
Milosevic, Vukasin
2015-01-01
Kernel estimation is one of the non-parametric methods used for estimation of probability density function. Its first ROOT implementation, as part of RooFit package, has one major issue, its evaluation time is extremely slow making in almost unusable. The goal of this project was to create a new class (TKNDTree) which will follow the original idea of kernel estimation, greatly improve the evaluation time (using the TKTree class for storing the data and creating different user-controlled modes of evaluation) and add the interpolation option, for 2D case, with the help of the new Delaunnay2D class.
Adaptive metric kernel regression
DEFF Research Database (Denmark)
Goutte, Cyril; Larsen, Jan
2000-01-01
Kernel smoothing is a widely used non-parametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this contribution, we propose an algorithm that adapts the input metric used in multivariate...... regression by minimising a cross-validation estimate of the generalisation error. This allows to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms...
Adaptive Metric Kernel Regression
DEFF Research Database (Denmark)
Goutte, Cyril; Larsen, Jan
1998-01-01
Kernel smoothing is a widely used nonparametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this paper, we propose an algorithm that adapts the input metric used in multivariate regression...... by minimising a cross-validation estimate of the generalisation error. This allows one to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms the standard...
DEFF Research Database (Denmark)
Duer, Karsten; Svendsen, Sv Aa Højgaard
1997-01-01
By providing at the same time thermal insulation and transparency the silica aerogel is a very attractive material for the purpose of improving the thermal performance of windows. Nevertheless a lot of problems have to be solved on the way from concept to the developed product. The B1 Aerogels...... project deals with some of these problems.This report summarizes the work that has been carried out on the subject of characterizing the optical and thermal performance of different types of aerogels and aerogel-like materials for the purpose of using aerogel in clear glazings.All measurements presented...
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Hansen, P. Reinhard; Lunde, Asger
2009-01-01
Realized kernels use high-frequency data to estimate daily volatility of individual stock prices. They can be applied to either trade or quote data. Here we provide the details of how we suggest implementing them in practice. We compare the estimates based on trade and quote data for the same stock...
Eldridge, Jeffrey I.; Spuckler, Charles M.; Markham, James R.
2009-01-01
The temperature dependence of the scattering and absorption coefficients for a set of freestanding plasma-sprayed 8 wt% yttria-stabilized zirconia (8YSZ) thermal barrier coatings (TBCs) was determined at temperatures up to 1360 C in a wavelength range from 1.2 micrometers up to the 8YSZ absorption edge. The scattering and absorption coefficients were determined by fitting the directional-hemispherical reflectance and transmittance values calculated by a four-flux Kubelka Munk method to the experimentally measured hemispherical-directional reflectance and transmittance values obtained for five 8YSZ thicknesses. The scattering coefficient exhibited a continuous decrease with increasing wavelength and showed no significant temperature dependence. The scattering is primarily attributed to the relatively temperature-insensitive refractive index mismatch between the 8YSZ and its internal voids. The absorption coefficient was very low (less than 1 per centimeter) at wavelengths between 2 micrometers and the absorption edge and showed a definite temperature dependence that consisted of a shift of the absorption edge to shorter wavelengths and an increase in the weak absorption below the absorption edge with increasing temperature. The shift in the absorption edge with temperature is attributed to strongly temperature-dependent multiphonon absorption. While TBC hemispherical transmittance beyond the absorption edge can be predicted by a simple exponential decrease with thickness, below the absorption edge, typical TBC thicknesses are well below the thickness range where a simple exponential decrease in hemispherical transmittance with TBC thickness is expected. [Correction added after online publication August 11, 2009: "edge to a shorter wavelengths" has been updated as edge to shorter wavelengths."
Choi, J. H.; Kim, S. W.; Won, J. S.
2017-12-01
The objective of this study is monitoring and evaluating the stability of buildings in Seoul, Korea. This study includes both algorithm development and application to a case study. The development focuses on improving the PSI approach for discriminating various geophysical phase components and separating them from the target displacement phase. A thermal expansion is one of the key components that make it difficult for precise displacement measurement. The core idea is to optimize the thermal expansion factor using air temperature data and to model the corresponding phase by fitting the residual phase. We used TerraSAR-X SAR data acquired over two years from 2011 to 2013 in Seoul, Korea. The temperature fluctuation according to seasons is considerably high in Seoul, Korea. Other problem is the highly-developed skyscrapers in Seoul, which seriously contribute to DEM errors. To avoid a high computational burden and unstable solution of the nonlinear equation due to unknown parameters (a thermal expansion parameter as well as two conventional parameters: linear velocity and DEM errors), we separate a phase model into two main steps as follows. First, multi-baseline pairs with very short time interval in which deformation components and thermal expansion can be negligible were used to estimate DEM errors first. Second, single-baseline pairs were used to estimate two remaining parameters, linear deformation rate and thermal expansion. The thermal expansion of buildings closely correlate with the seasonal temperature fluctuation. Figure 1 shows deformation patterns of two selected buildings in Seoul. In the figures of left column (Figure 1), it is difficult to observe the true ground subsidence due to a large cyclic pattern caused by thermal dilation of the buildings. The thermal dilation often mis-leads the results into wrong conclusions. After the correction by the proposed method, true ground subsidence was able to be precisely measured as in the bottom right figure
Yang, Xiaolong; Li, Wu
2018-01-01
We investigate the evolution of the cross-plane thermal conductivity κ of superlattices (SLs) as interfaces change from perfectly abrupt to totally intermixed, by using nonequilibrium molecular dynamics simulations in combination with the spectral heat current calculations. We highlight the role of surface-interdiffusion-driven intermixing by calculating the κ of SLs with changing interface roughness, whose tuning allows for κ values much lower than the "alloy limit" and the abrupt interface limit in same cases. The interplay between alloy and interface scattering in different frequency ranges provides a physical basis to predict a minimum of thermal conductivity. More specifically, we also explore how the interface roughness affects the thermal conductivities for SL materials with a broad span of atomic mass and bond strength. In particular, we find that (i) only when the "spacer" thickness of SLs increases up to a critical value, κ of rough SLs can break the corresponding "alloy limit," since SLs with different "spacer" thickness have different characteristic length of phonon transport, which is influenced by surface-interdiffusion-driven intermixing to different extend. (ii) Whether κ changes monotonically with interface roughness strongly depends on the period length and intrinsic behavior of phonon transport for SL materials. Especially, for the SL with large period length, there exists an optimal interface roughness that can minimize the thermal conductivity. (iii) Surface-interdiffusion-driven intermixing is more effective in achieving a low κ below the alloy limit for SL materials with large mass mismatch than with small one. (iv) It is possible for SL materials with large lattice mismatch (i.e., bond strength) to design an ideally abrupt interface structure with κ much below the alloy limit. These results have clear implications for optimization of thermal transport for heat management and for the development of thermoelectric materials.
Sandholzer, Michael A; Sui, Tan; Korsunsky, Alexander M; Walmsley, Anthony Damien; Lumley, Philip J; Landini, Gabriel
2014-05-01
Micro- and ultrastructural analysis of burned skeletal remains is crucial for obtaining a reliable estimation of cremation temperature. Earlier studies mainly focused on heat-induced changes in bone tissue, while this study extends this research to human dental tissues using a novel quantitative analytical approach. Twelve tooth sections were burned at 400-900°C (30-min exposure, increments of 100°C). Subsequent combined small- and wide-angle X-ray scattering (SAXS/WAXS) experiments were performed at the Diamond Light Source synchrotron facility, where 28 scattering patterns were collected within each tooth section. In comparison with the control sample, an increase in mean crystal thickness was found in burned dentine (2.8-fold) and enamel (1.4-fold), however at a smaller rate than reported earlier for bone tissue (5-10.7-fold). The results provide a structural reference for traditional X-ray scattering methods and emphasize the need to investigate bone and dental tissues separately to obtain a reliable estimation of cremation temperature. © 2014 American Academy of Forensic Sciences.
Thermal emission from particulate surfaces: A comparison of scattering models with measured spectra
Moersch, J. E.; Christensen, P. R.
1995-01-01
Emissivity spectra of particulate mineral samples are highly dependent on particle size when that size is comparable to the wavelength of light emitted (5-50 micrometers for the midinfrared). Proper geologic interpretation of data from planetary infrared spectrometers will require that these particle size effects be well understood. To address this issue, samples of quartz powders were produced with narrow, well-characterized particle size distributions. Mean particle diameters in these samples ranged from 15 to 227 micrometers. Emission spectra of these powders allow the first detailed comparison of the complex spectral variations with particle size observed in laboratory data with the predictions of radiative transfer models. Four such models are considered here. Hapke's relectance theory (converted to emissivity via Kirchoff's law) is the first model tested. Hapke's more recently published emission theory is also employed. The third model, the 'Mie/Conel' model, uses Mie single scattering with a two-stream approximation for multiple scattering. This model, like the first, is a converted reflec- tance model. Mie scattering assumes particles are both spherical and well separated, which is not true for the quartz powders, but includes diffraction effects. The fourth model uses the Mie solution for single scattering by spheres and inputs those results into the multiple scattering formalism of Hapke's emission theory. The results of the four models are considered in relation to the values of the optical constants n and k. We have grouped these as class 1 (k large), class 2 (k moderate, n is approximately 2), class 3 (k small, n is approximately 2), and class 4 (k small, n is approximately 1). In general, the Mie/Hapke hybrid model does best at predicting variations with grain size. In particular, it predicts changes of the correct pattern, although incorrect magnitude, for class 1 bands, where large increases in emissivity with decreasing grain size are observed
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole; Hansen, Peter Reinhard; Lunde, Asger
We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement noise of certain types and can also handle non-synchronous trading. It is the first estimator...... returns measured over 5 or 10 minutes intervals. We show the new estimator is substantially more precise....
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Hansen, Peter Reinhard; Lunde, Asger
2011-01-01
We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement error of certain types and can also handle non-synchronous trading. It is the first estimator...... returns measured over 5 or 10 min intervals. We show that the new estimator is substantially more precise....
Steerability of Hermite Kernel
Czech Academy of Sciences Publication Activity Database
Yang, Bo; Flusser, Jan; Suk, Tomáš
2013-01-01
Roč. 27, č. 4 (2013), 1354006-1-1354006-25 ISSN 0218-0014 R&D Projects: GA ČR GAP103/11/1552 Institutional support: RVO:67985556 Keywords : Hermite polynomials * Hermite kernel * steerability * adaptive filtering Subject RIV: JD - Computer Applications, Robotics Impact factor: 0.558, year: 2013 http://library.utia.cas.cz/separaty/2013/ZOI/yang-0394387.pdf
Chen, Si; Tong, Xiaoqian; He, Huiwen; Ma, Meng; Shi, Yanqin; Wang, Xu
2017-04-05
A kind of body temperature controlled optical and thermal information storage light scattering display based on super strong liquid crystalline physical gel with special "loofah-like gel network" was successfully prepared. Such liquid crystal (LC) gel was obtained by mixing a dendritic gelator (POSS-G1-BOC), an azobenzene compound (2Azo2), and a phosphor tethered liquid crystalline host (5CB), which could show its best contrast ratio at around human body temperature under UV light because of the phosphor's fluorescence effect. The gel also has quite strong mechanical strength, which could be used in wearable device field especially under sunlight, even under the forcing conditions as harsh as being centrifuged for 10 min at the speed of 2000 r/min. The whole production process of such a display is quite simple and could lead to displays at any size through noncontact writing. We believe it will have wide applications in the future.
Inelastic neutron scattering analysis of the thermal decomposition of kaolinite to metakaolin
Energy Technology Data Exchange (ETDEWEB)
White, Claire E., E-mail: whitece@princeton.edu [Lujan Neutron Scattering Center, Los Alamos National Laboratory, Los Alamos (United States); Physics and Chemistry of Materials, Los Alamos National Laboratory, Los Alamos (United States); Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos (United States); Department of Chemical and Biomolecular Engineering, The University of Melbourne, Parkville (Australia); Kearley, Gordon J. [Bragg Institute, Australian Nuclear Science and Technology Organisation, Lucas Heights (Australia); Provis, John L. [Department of Chemical and Biomolecular Engineering, The University of Melbourne, Parkville (Australia); Department of Materials Science and Engineering, The University of Sheffield, Sheffield (United Kingdom); Riley, Daniel P. [Institute of Materials Engineering, Australian Nuclear Science and Technology Organisation, Lucas Heights (Australia); Department of Mechanical Engineering, The University of Melbourne, Parkville (Australia)
2013-12-12
Highlights: • Kaolinite dehydroxylation studied using inelastic neutron scattering analysis. • Integrated intensities in 200–1200 cm{sup −1} range used for semi-quantitative analysis. • Preferential loss of inner surface hydrogen atoms during reaction. • INS is an ideal tool for studying different hydrogen environments in clays. - Abstract: Understanding the formation of metakaolin via kaolinite dehydroxylation is extremely important for the optimization of various industrial processes. Recent investigations have reported that the different types of hydrogen atoms in kaolinite are removed concurrently during the dehydroxylation process. Here, inelastic neutron scattering (INS) is used to analyze the location and dynamics of hydrogen atoms in kaolinite, together with the changes induced during dehydroxylation. This is achieved by using prior knowledge of how the inner and inner surface hydrogen atoms contribute to the kaolinite INS spectrum in the 200–1200 cm{sup −1} range, in combination with a semi-quantitative analysis of the experimental INS spectra. Overall, it is seen that there is a distinct preferential loss of inner surface hydrogen-atom types during the dehydroxylation process, as determined from analysis of the Al–O–H vibrational modes (consisting of deformation and torsion) in the INS spectrum.
A fast, exact code for scattered thermal radiation compared with a two-stream approximation
International Nuclear Information System (INIS)
Cogley, A.C.; Pandey, D.K.
1980-01-01
A two-stream accuracy study for internally (thermal) driven problems is presented by comparison with a recently developed 'exact' adding/doubling method. The resulting errors in external (or boundary) radiative intensity and flux are usually larger than those for the externally driven problems and vary substantially with the radiative parameters. Error predictions for a specific problem are difficult. An unexpected result is that the exact method is computationally as fast as the two-stream approximation for nonisothermal media
Inelastic neutron scattering analysis of the thermal decomposition of kaolinite to metakaolin
White, Claire E.; Kearley, Gordon J.; Provis, John L.; Riley, Daniel P.
2013-12-01
Understanding the formation of metakaolin via kaolinite dehydroxylation is extremely important for the optimization of various industrial processes. Recent investigations have reported that the different types of hydrogen atoms in kaolinite are removed concurrently during the dehydroxylation process. Here, inelastic neutron scattering (INS) is used to analyze the location and dynamics of hydrogen atoms in kaolinite, together with the changes induced during dehydroxylation. This is achieved by using prior knowledge of how the inner and inner surface hydrogen atoms contribute to the kaolinite INS spectrum in the 200-1200 cm-1 range, in combination with a semi-quantitative analysis of the experimental INS spectra. Overall, it is seen that there is a distinct preferential loss of inner surface hydrogen-atom types during the dehydroxylation process, as determined from analysis of the Al-O-H vibrational modes (consisting of deformation and torsion) in the INS spectrum.
Application of thermal neutron scattering in the research into solids and in industrial practice
International Nuclear Information System (INIS)
Vratislav, S.
1996-01-01
The application of neutron scattering in condensed matter physics in the Czech Republic started in 1966. Research and education activities (both undergraduate and postgraduate courses) in this field of science are fostered by the Neutron Diffraction Laboratory, Faculty of Nuclear Science and Physical Engineering in Prague, using the LVR-15 research reactor operated by the Nuclear Research Institute at Rez. The KSN-2 double-axis powder diffractometer employed for structural and texture experiments is equipped with auxiliary equipment, including a cryogenic apparatus, heater furnace, and TG-1 texture goniometer. Some promising materials were investigated, such as zeolites (light element positions, cation distributions), hexaferrites and high temperature superconductors, and ionic conductors. Applied research included, among other things, 3-D texture analysis of oriented magnetic steel sheets and zirconium alloys. (Z.J.). 1 tab., 4 figs., 36 refs
Smolka, Gert
1994-01-01
Oz is a concurrent language providing for functional, object-oriented, and constraint programming. This paper defines Kernel Oz, a semantically complete sublanguage of Oz. It was an important design requirement that Oz be definable by reduction to a lean kernel language. The definition of Kernel Oz introduces three essential abstractions: the Oz universe, the Oz calculus, and the actor model. The Oz universe is a first-order structure defining the values and constraints Oz computes with. The ...
Multigroup or multipoint thermal neutron data preparation. Programme SIGMA
International Nuclear Information System (INIS)
Matausek, M.V.; Kunc, M.
1974-01-01
When calculating the space energy distribution of thermal neutrons in reactor lattices, in either the multigroup or the multipoint approximation, it is convenient to divide the problem into two independent parts. Firstly, for all material regions of the given reactor lattice cell, the group or the point values of cross sections, scattering kernel and the outer source of thermal neutrons are calculated by a data preparation programme. These quantities are then used as input, by the programme which solves multigroup or multipoint transport equations, to generate the space energy neutron spectra in the cell considered and to determine the related integral quantities, namely the different reaction rates. The present report deals with the first part of the problem. An algorithm for constructing a set of thermal neutron input data, to be used with the multigroup or multipoint version of the code MULTI /1,2,3/, is presented and the new version of the programme SIGMA /4/, written in FORTRAN IV for the CDC-3600 computer, is described. For a given reactor cell material, composed of a number of different isotopes, this programme calculates the group or the point values of the scattering macroscopic absorption cross section, macroscopic scattering cross section, kernel and the outer source of thermal neutrons. Numerous options are foreseen in the programme, concerning the energy variation of cross sections and a scattering kernel, concerning the weighting spectrum in multigroup scheme or the procedure for constructing the scattering matrix in the multipoint scheme and, finally, concerning the organization of output. The details of the calculational algorithm are presented in Section 2 of the paper. Section 3 contains the description of the programme and the instructions for its use (author)
Farid, Sidra; Stroscio, Michael A.; Dutta, Mitra
2018-03-01
Thermal evaporation growth technique is presented as a route to grow cost effective high quality CdS thin films. We have successfully grown high quality CdS thin films on ITO coated glass substrates by thermal evaporation technique and analyzed the effects of annealing and excitation dependent input of CdS thin film using Raman and photoluminescence spectroscopy. LO phonon modes have been analyzed quantitatively considering the contributions due to anneal induced effects on film quality using phonon spatial correlation model, line shape and defect state analysis. Asymmetry in the Raman line shape towards the low frequency side is related to the phonon confinement effects and is modeled by spatial correlation model. Calculations of width (FWHM), integrated intensity, and line shape for the longitudinal (LO) optical phonon modes indicate improved crystalline quality for the annealed films as compared to the as grown films. With increase in laser power, intensity ratio of 2-LO to 1-LO optical phonon modes is found to increase while multiple overtones upto fourth order are observed. Power dependent photoluminescence data indicates direct band-to-band transition in CdS thin films.
High energy asymptotics of the scattering amplitude for the ...
Indian Academy of Sciences (India)
We find an explicit function approximating at high energies the kernel of the scattering matrix with arbitrary accuracy. Moreover, the same function gives all diagonal singularities of the kernel of the scattering matrix in the angular variables. Author Affiliations. D Yafaev1. Department of Mathematics, University Rennes-1, ...
DEFF Research Database (Denmark)
Sommer, Stefan Horst; Lauze, Francois Bernard; Nielsen, Mads
2011-01-01
In the LDDMM framework, optimal warps for image registration are found as end-points of critical paths for an energy functional, and the EPDiff equations describe the evolution along such paths. The Large Deformation Diffeomorphic Kernel Bundle Mapping (LDDKBM) extension of LDDMM allows scale space...... information to be automatically incorporated in registrations and promises to improve the standard framework in several aspects. We present the mathematical foundations of LDDKBM and derive the KB-EPDiff evolution equations, which provide optimal warps in this new framework. To illustrate the resulting...
Clustering via Kernel Decomposition
DEFF Research Database (Denmark)
Have, Anna Szynkowiak; Girolami, Mark A.; Larsen, Jan
2006-01-01
Methods for spectral clustering have been proposed recently which rely on the eigenvalue decomposition of an affinity matrix. In this work it is proposed that the affinity matrix is created based on the elements of a non-parametric density estimator. This matrix is then decomposed to obtain...... posterior probabilities of class membership using an appropriate form of nonnegative matrix factorization. The troublesome selection of hyperparameters such as kernel width and number of clusters can be obtained using standard cross-validation methods as is demonstrated on a number of diverse data sets....
THOR: thermal cross section generation code using ENDF/B data
International Nuclear Information System (INIS)
Andrews, J.B. II; Hassan, N.M.; Wittkopf, W.A.
1975-12-01
THOR processes ENDF/B data files to produce a master thermal library containing multigroup cross sections, scattering kernels, and slowing-down source distributions for use in thermal spectrum calculations. The thermal energy range may be described by up to 80 energy groups, and a weighting spectrum may be either input or calculated by the program for use in obtaining average group coefficients. Resonance contributions to the thermal cross sections are added to the appropriate smooth cross sections to obtain the cross section for each reaction type. Scattering kernels may be produced using either thermal neutron scattering law data or free gas scattering law data, depending on the form of the data present on the ENDF/B data file for the material. Slowing-down source distributions are calculated for each material assuming a 1/E neutron flux in the epithermal energy range. The master thermal library produced by THOR may contain up to 100 materials with coefficient data present at a maximum of 25 temperatures for each material
MACS, Lattice Vibrations Structure Factors for Thermal Neutron Scattering in Moderators
International Nuclear Information System (INIS)
McMurry, H.L.; Suitt, W.J.; Worlton, T.G.; Martin, R.M.
1974-01-01
1 - Description of problem or function: This package of seven related codes is basically aimed at giving maximum capability for calculating slow-neutron scattering by moderators. MACS-C computes crystal vibrations when the potential energy is a sum of parts arising from short-range forces and long-range Coulomb interactions. It also obtains Jacobian matrices for determining adjustments in force constants and ionic charge which can lead to improved agreement with data. Structure factors for neutron inelastic scattering can also be calculated. MACS-J computes the dynamical matrix for the harmonic oscillations of a crystal, its eigenvalues and eigenvectors, the corresponding structure factors for coherent single-phonon scattering of neutrons, and Jacobian matrices for use in adjusting force constants to fit calculated to observed dispersion curves. REVISED-D calculates valance coordinates in terms of mass adjusted atom displacements, together with coordinates which define rigid group rotations. REVISED-MVFC constructs force constant matrices for use in valance force potential functions which are used in other programs dealing with molecular and crystal vibrations. ADJUSTER is a force adjuster program to obtain a least squares fit to observed frequencies of molecules and crystals. DIPOLE-SUM calculates dipole sums for an arbitrary crystal. MODEL-PI calculates crystal vibrations when the potential energy is a sum of short-range and long- or intermediate-range terms in the dipole coordinate approximation. It also obtains Jacobian matrices for use in adjusting input parameters. 2 - Method of solution: In MACS-C, ADJUSTER, and REVISED-D, matrix manipulations are applied to matrices which describe physical conditions. In MACS-J, first-order difference equations are substituted for partial differential equations for Jacobian elements. In MVFC the user employs a set of criteria for defining different types of interactions to prepare by hand the input to the program. For
Global Polynomial Kernel Hazard Estimation
DEFF Research Database (Denmark)
Hiabu, Munir; Miranda, Maria Dolores Martínez; Nielsen, Jens Perch
2015-01-01
This paper introduces a new bias reducing method for kernel hazard estimation. The method is called global polynomial adjustment (GPA). It is a global correction which is applicable to any kernel hazard estimator. The estimator works well from a theoretical point of view as it asymptotically redu...
Classification Using the Zipfian Kernel
Czech Academy of Sciences Publication Activity Database
Jiřina, Marcel; Jiřina jr., M.
2015-01-01
Roč. 32, č. 2 (2015), s. 305-326 ISSN 0176-4268 R&D Projects: GA TA ČR TA01010490 Institutional support: RVO:67985807 Keywords : kernel machine * Zipfian kernel * multivariate data * correlation dimension * harmonic series * classification Subject RIV: JC - Computer Hardware ; Software Impact factor: 1.147, year: 2015
Model Selection in Kernel Ridge Regression
DEFF Research Database (Denmark)
Exterkate, Peter
, including polynomial kernels, the Gaussian kernel, and the Sinc kernel. We interpret the latter two kernels in terms of their smoothing properties, and we relate the tuning parameters associated to all these kernels to smoothness measures of the prediction function and to the signal-to-noise ratio. Based...... applicable, and we recommend their use instead of the popular polynomial kernels in general settings, in which no information on the data-generating process is available....
Viscosity kernel of molecular fluids
DEFF Research Database (Denmark)
Puscasu, Ruslan; Todd, Billy; Daivis, Peter
2010-01-01
forms that fit the wave-vector-dependent kernel data over a large density and wave-vector range have also been tested. Finally, a structural normalization of the kernels in physical space is considered. Overall, the real-space viscosity kernel has a width of roughly 3–6 atomic diameters, which means......The wave-vector dependent shear viscosities for butane and freely jointed chains have been determined. The transverse momentum density and stress autocorrelation functions have been determined by equilibrium molecular dynamics in both atomic and molecular hydrodynamic formalisms. The density......, temperature, and chain length dependencies of the reciprocal and real-space viscosity kernels are presented. We find that the density has a major effect on the shape of the kernel. The temperature range and chain lengths considered here have by contrast less impact on the overall normalized shape. Functional...
Model selection in kernel ridge regression
DEFF Research Database (Denmark)
Exterkate, Peter
2013-01-01
. The influence of the choice of kernel and the setting of tuning parameters on forecast accuracy is investigated. Several popular kernels are reviewed, including polynomial kernels, the Gaussian kernel, and the Sinc kernel. The latter two kernels are interpreted in terms of their smoothing properties...... confirms the practical usefulness of these rules of thumb. Finally, the flexible and smooth functional forms provided by the Gaussian and Sinc kernels makes them widely applicable. Therefore, their use is recommended instead of the popular polynomial kernels in general settings, where no information...
International Nuclear Information System (INIS)
Chukhovskij, F.N.; Nosik, V.L.
1994-01-01
On the base of an exact solution of the dynamic problem of scattering is analyzed the thermal neutron diffraction due to magnetic interaction by the reorientational transition (Morine transition) in a nearly perfect crystal of hematite. It is shown that in dependence on the value and direction of an external magnetic field the diffraction scattering character is changed substantially. Formulae are obtained and calculations are fulfilled of the diffraction integral intensity (DII) as a temperature function near the Morine phase transition. DII calculation results are compared with experimental data
Puig, Julieta; Williams, Roberto J J; Hoppe, Cristina E
2013-09-25
Paraffins are typical organic phase change materials (PCM) used for latent heat storage. For practical applications they must be encapsulated to prevent leakage or agglomeration during fusion. In this study it is shown that eicosane (C20H42 = C20) in the melted state could be dissolved in the hydrophobic domains of poly(dodecyl methacrylate) (PDMA) up to concentrations of 30 wt %, avoiding the need of encapsulation. For a 30 wt % solution, the heat of phase change was close to 69 J/g, a reasonable value for its use as a PCM. The fully converted solution remained transparent at 80 °C with no evidence of phase separation but became opaque by cooling as a consequence of paraffin crystallization. Heating above the melting temperature regenerated a transparent material. A high contrast ratio and abrupt transition between opaque and transparent states was observed for the 30 wt % blends, with a transparent state at 35 °C and an opaque state at 23 °C. This behavior was completely reproducible during consecutive heating/cooling cycles, indicating the possible use of this material as a thermally reversible light scattering (TRLS) film.
Bruemmer, David J [Idaho Falls, ID
2009-11-17
A robot platform includes perceptors, locomotors, and a system controller. The system controller executes a robot intelligence kernel (RIK) that includes a multi-level architecture and a dynamic autonomy structure. The multi-level architecture includes a robot behavior level for defining robot behaviors, that incorporate robot attributes and a cognitive level for defining conduct modules that blend an adaptive interaction between predefined decision functions and the robot behaviors. The dynamic autonomy structure is configured for modifying a transaction capacity between an operator intervention and a robot initiative and may include multiple levels with at least a teleoperation mode configured to maximize the operator intervention and minimize the robot initiative and an autonomous mode configured to minimize the operator intervention and maximize the robot initiative. Within the RIK at least the cognitive level includes the dynamic autonomy structure.
determination of bio-energy potential of palm kernel shell
African Journals Online (AJOL)
88888888
2012-11-03
Nov 3, 2012 ... Keywords: palm kernel shell, bioenergy, thermogravimetric analysis, pyrolysis, gasification ... tain higher energy density fuels. Fast Pyrolysis is the thermal decomposition of biomass for bio-char, bio- oil and combustible gas production in the absence of ... Calorific Value of Coal and Coke) was used for the.
Mixture Density Mercer Kernels: A Method to Learn Kernels
National Aeronautics and Space Administration — This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian...
Brown, D. A.; Chadwick, M. B.; Capote, R.; Kahler, A. C.; Trkov, A.; Herman, M. W.; Sonzogni, A. A.; Danon, Y.; Carlson, A. D.; Dunn, M.; Smith, D. L.; Hale, G. M.; Arbanas, G.; Arcilla, R.; Bates, C. R.; Beck, B.; Becker, B.; Brown, F.; Casperson, R. J.; Conlin, J.; Cullen, D. E.; Descalle, M.-A.; Firestone, R.; Gaines, T.; Guber, K. H.; Hawari, A. I.; Holmes, J.; Johnson, T. D.; Kawano, T.; Kiedrowski, B. C.; Koning, A. J.; Kopecky, S.; Leal, L.; Lestone, J. P.; Lubitz, C.; Márquez Damián, J. I.; Mattoon, C. M.; McCutchan, E. A.; Mughabghab, S.; Navratil, P.; Neudecker, D.; Nobre, G. P. A.; Noguere, G.; Paris, M.; Pigni, M. T.; Plompen, A. J.; Pritychenko, B.; Pronyaev, V. G.; Roubtsov, D.; Rochman, D.; Romano, P.; Schillebeeckx, P.; Simakov, S.; Sin, M.; Sirakov, I.; Sleaford, B.; Sobes, V.; Soukhovitskii, E. S.; Stetcu, I.; Talou, P.; Thompson, I.; van der Marck, S.; Welser-Sherrill, L.; Wiarda, D.; White, M.; Wormald, J. L.; Wright, R. Q.; Zerkle, M.; Žerovnik, G.; Zhu, Y.
2018-02-01
We describe the new ENDF/B-VIII.0 evaluated nuclear reaction data library. ENDF/B-VIII.0 fully incorporates the new IAEA standards, includes improved thermal neutron scattering data and uses new evaluated data from the CIELO project for neutron reactions on 1H, 16O, 56Fe, 235U, 238U and 239Pu described in companion papers in the present issue of Nuclear Data Sheets. The evaluations benefit from recent experimental data obtained in the U.S. and Europe, and improvements in theory and simulation. Notable advances include updated evaluated data for light nuclei, structural materials, actinides, fission energy release, prompt fission neutron and γ-ray spectra, thermal neutron scattering data, and charged-particle reactions. Integral validation testing is shown for a wide range of criticality, reaction rate, and neutron transmission benchmarks. In general, integral validation performance of the library is improved relative to the previous ENDF/B-VII.1 library.
Sakata, Yoshitaro; Terasaki, Nao; Nonaka, Kazuhiro
2017-05-01
Fine polishing techniques, such as a chemical mechanical polishing treatment, are important techniques in glass substrate manufacturing. However, these techniques may cause micro cracks under the surface of glass substrates because they used mechanical friction. A stress-induced light scattering method (SILSM), which was combined with light scattering method and mechanical stress effects, was proposed for inspecting surfaces to detect polishing-induced micro cracks. However, in the conventional SILSM, samples need to be loaded with physical contact, and the loading point is invisible in transparent materials. Here, we introduced a novel non-contact SILSM using a heating device. A glass substrate was heated first, and then the light scattering intensity of micro cracks was detected by a cooled charge-couple device camera during the natural cooling process. Results clearly showed during the decreasing surface temperature of a glass substrate, appropriate thermal stress is generated for detecting micro cracks by using the SILSM and light scattering intensity from micro cracks changes. We confirmed that non-contact thermal SILSM (T-SILSM) can detect micro cracks under the surface of transparent materials.
International Nuclear Information System (INIS)
Orlova, N.S.
1978-01-01
Intensity of diffusion scattering of X-rays from the plane of a monocrystal of indium arsenide has been measured on the monochromatized CuKsub(α)-radiation. The samples are made of Cl indium arsenide monocrystal of the n-type with the 1x10 18 cm -3 concentration of carriers in the form of a plate with the polished parallel cut-off with the +-5' accuracy. The investigations have been carried out on the URS-5 IM X-ray diffractometer at room temperature in vacuum. Intensities of thermal diffusion scattering of the second order have been calculated by the two-atomic chain model with different mass and four interaction paramaters. Based upon the analysis of intensity of single-phonon diffusion scattering the curves of frequencies of atomic oscillations along the direction [100] have been determined. The values of frequencies obtained experimentally on the thermal diffusion scattering of X-rays are in a satisfactory agreement with the calculated data. The frequencies obtained are compared with the results of calculation and the analysis of multiphonon spectra of IR-absorption made elsewhere
Kernel parameter dependence in spatial factor analysis
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg
2010-01-01
kernel PCA. Shawe-Taylor and Cristianini [4] is an excellent reference for kernel methods in general. Bishop [5] and Press et al. [6] describe kernel methods among many other subjects. The kernel version of PCA handles nonlinearities by implicitly transforming data into high (even infinite) dimensional...
Heat kernels and critical limits
Pickrell, Doug
2007-01-01
This paper is an exposition of several questions linking heat kernel measures on infinite dimensional Lie groups, limits associated with critical Sobolev exponents, and Feynmann-Kac measures for sigma models.
Puig, Julieta; Dell' Erba, Ignacio E; Schroeder, Walter F; Hoppe, Cristina E; Williams, Roberto J J
2017-03-29
Alkyl chains of β-hydroxyesters synthesized by the capping of terminal epoxy groups of diglycidylether of bisphenol A (DGEBA) with palmitic (C16), stearic (C18), or behenic (C22) fatty acids self-assemble forming a crystalline phase. Above a particular concentration solutions of these esters in a variety of solvents led to supramolecular (physical) gels below the crystallization temperature of alkyl chains. A form-stable phase change material (FS-PCM) was obtained by blending the ester derived from behenic acid with eicosane. A blend containing 20 wt % ester was stable as a gel up to 53 °C and exhibited a heat storage capacity of 161 J/g, absorbed during the melting of eicosane at 37 °C. Thermally reversible light scattering (TRLS) films were obtained by visible-light photopolymerization of poly(ethylene glycol) dimethacrylate-ester blends (50 wt %) in the gel state at room temperature. The reaction was very fast and not inhibited by oxygen. TRLS films consisted of a cross-linked methacrylic network interpenetrated by the supramolecular network formed by the esters. Above the melting temperature of crystallites formed by alkyl chains, the film was transparent due to the matching between refractive indices of the methacrylic network and the amorphous ester. Below the crystallization temperature, the film was opaque because of light dispersion produced by the organic crystallites uniformly dispersed in the material. Of high significance for application was the fact that the contrast ratio did not depend on heating and cooling rates.
National Research Council Canada - National Science Library
Barton, John
2000-01-01
Theoretical procedures were developed, computer programs were written, and demonstration calculations were performed investigating the modeling and predicted performance of the photothermal modulation of Mie scattering (PMMS...
Modified kernel-based nonlinear feature extraction.
Energy Technology Data Exchange (ETDEWEB)
Ma, J. (Junshui); Perkins, S. J. (Simon J.); Theiler, J. P. (James P.); Ahalt, S. (Stanley)
2002-01-01
Feature Extraction (FE) techniques are widely used in many applications to pre-process data in order to reduce the complexity of subsequent processes. A group of Kernel-based nonlinear FE ( H E ) algorithms has attracted much attention due to their high performance. However, a serious limitation that is inherent in these algorithms -- the maximal number of features extracted by them is limited by the number of classes involved -- dramatically degrades their flexibility. Here we propose a modified version of those KFE algorithms (MKFE), This algorithm is developed from a special form of scatter-matrix, whose rank is not determined by the number of classes involved, and thus breaks the inherent limitation in those KFE algorithms. Experimental results suggest that MKFE algorithm is .especially useful when the training set is small.
Thermal neutron diffusion cooling coefficient for plexiglass
International Nuclear Information System (INIS)
Drozdowicz, K.
1992-08-01
The thermal neutron diffusion cooling coefficient is a macroscopic material parameter. It is needed for description of the decay of the thermal neutron pulse in a medium and gives information of the diffusion cooling of the thermal neutron spectrum in a bounded volume. Experimental results from various measurements for plexiglass are overviewed in the paper. A method for theoretical, exact calculation of the parameter is presented. The formula utilizes some other thermal neutron parameters and a cooling function, i.e. the function which describes the deviation of the neutron spectrum in a bounded system from the distribution in an infinite one. The energy dependence of the function is obtained numerically from relations which results from the eigenvalue problem of the scattering operator when both the decay constant and the spectrum of the thermal neutron flux are developed on powers of the geometrical buckling. The case of a 1/ν absorption cross section is considered. The calculation utilizes a synthetic scattering function elaborated for hydrogenous media by GRANADA (1985). The influence of some quantities used in the calculation on the final result is investigated. The obtained value of the diffusion cooling coefficient for plexiglass is C = 6514 cm 4 s -1 at the temperature of 20 degrees C. The uncertainty is estimated to be ± 100 cm 4 s -1 within the physical model of the scattering kernel used. (au)
International Nuclear Information System (INIS)
Yoon, Jinhwan; Heo, Kyuyoung; Oh, Weontae; Jin, Kyeong Sik; Jin, Sangwoo; Kim, Jehan; Kim, Kwang-Woo; Chang, Taihyun; Ree, Moonhor
2006-01-01
The miscibility and the mechanism for thermal nanopore templating in films prepared from spin-coating and subsequent drying of homogenous solutions of curable polymethylsilsesquioxane dielectric precursor and thermally labile, reactive triethoxysilyl-terminated four-armed poly(ε-caprolactone) porogen were investigated in detail by in situ two-dimensional grazing incidence small-angle x-ray scattering analysis. The dielectric precursor and porogen components in the film were fully miscible. On heating, limited aggregations of the porogen, however, took place in only a small temperature range of 100-140 deg. C as a result of phase separation induced by the competition of the curing and hybridization reactions of the dielectric precursor and porogen; higher porogen loading resulted in relatively large porogen aggregates and a greater size distribution. The developed porogen aggregates underwent thermal firing above 300 deg. C without further growth and movement, and ultimately left their individual footprints in the film as spherical nanopores
Three-Dimensional Sensitivity Kernels of Z/H Amplitude Ratios of Surface and Body Waves
Bao, X.; Shen, Y.
2017-12-01
The ellipticity of Rayleigh wave particle motion, or Z/H amplitude ratio, has received increasing attention in inversion for shallow Earth structures. Previous studies of the Z/H ratio assumed one-dimensional (1D) velocity structures beneath the receiver, ignoring the effects of three-dimensional (3D) heterogeneities on wave amplitudes. This simplification may introduce bias in the resulting models. Here we present 3D sensitivity kernels of the Z/H ratio to Vs, Vp, and density perturbations, based on finite-difference modeling of wave propagation in 3D structures and the scattering-integral method. Our full-wave approach overcomes two main issues in previous studies of Rayleigh wave ellipticity: (1) the finite-frequency effects of wave propagation in 3D Earth structures, and (2) isolation of the fundamental mode Rayleigh waves from Rayleigh wave overtones and converted Love waves. In contrast to the 1D depth sensitivity kernels in previous studies, our 3D sensitivity kernels exhibit patterns that vary with azimuths and distances to the receiver. The laterally-summed 3D sensitivity kernels and 1D depth sensitivity kernels, based on the same homogeneous reference model, are nearly identical with small differences that are attributable to the single period of the 1D kernels and a finite period range of the 3D kernels. We further verify the 3D sensitivity kernels by comparing the predictions from the kernels with the measurements from numerical simulations of wave propagation for models with various small-scale perturbations. We also calculate and verify the amplitude kernels for P waves. This study shows that both Rayleigh and body wave Z/H ratios provide vertical and lateral constraints on the structure near the receiver. With seismic arrays, the 3D kernels afford a powerful tool to use the Z/H ratios to obtain accurate and high-resolution Earth models.
Energy Technology Data Exchange (ETDEWEB)
Ghrayeb, Shadi Z. [Pennsylvania State Univ., University Park, PA (United States). Dept. of Mechanical and Nuclear Engineering; Ougouag, Abderrafi M. [Idaho National Laboratory (INL), Idaho Falls, ID (United States); Ouisloumen, Mohamed [Westinghouse Electric Company, Cranberry Township, PA (United States); Ivanov, Kostadin N. [Pennsylvania State Univ., University Park, PA (United States). Dept. of Mechanical and Nuclear Engineering
2014-01-01
A multi-group formulation for the exact neutron elastic scattering kernel is developed. It incorporates the neutron up-scattering effects, stemming from lattice atoms thermal motion and accounts for it within the resulting effective nuclear cross-section data. The effects pertain essentially to resonant scattering off of heavy nuclei. The formulation, implemented into a standalone code, produces effective nuclear scattering data that are then supplied directly into the DRAGON lattice physics code where the effects on Doppler Reactivity and neutron flux are demonstrated. The correct accounting for the crystal lattice effects influences the estimated values for the probability of neutron absorption and scattering, which in turn affect the estimation of core reactivity and burnup characteristics. The results show an increase in values of Doppler temperature feedback coefficients up to -10% for UOX and MOX LWR fuels compared to the corresponding values derived using the traditional asymptotic elastic scattering kernel. This paper also summarizes the results done on this topic to date.
International Nuclear Information System (INIS)
Ghrayeb, Shadi Z.; Ouisloumen, Mohamed; Ivanov, Kostadin N.
2014-01-01
A multi-group formulation for the exact neutron elastic scattering kernel is developed. It incorporates the neutron up-scattering effects, stemming from lattice atoms thermal motion and accounts for it within the resulting effective nuclear cross-section data. The effects pertain essentially to resonant scattering off of heavy nuclei. The formulation, implemented into a standalone code, produces effective nuclear scattering data that are then supplied directly into the DRAGON lattice physics code where the effects on Doppler Reactivity and neutron flux are demonstrated. The correct accounting for the crystal lattice effects influences the estimated values for the probability of neutron absorption and scattering, which in turn affect the estimation of core reactivity and burnup characteristics. The results show an increase in values of Doppler temperature feedback coefficients up to -10% for UOX and MOX LWR fuels compared to the corresponding values derived using the traditional asymptotic elastic scattering kernel. This paper also summarizes the results done on this topic to date
Yang, Yan-Zhuo; Ding, Shuo; Wang, Yong; Li, Cui-Ling; Shen, Yun; Meeley, Robert; McCarty, Donald R; Tan, Bao-Cai
2017-06-01
Vitamin B 6 , an essential cofactor for a range of biochemical reactions and a potent antioxidant, plays important roles in plant growth, development, and stress tolerance. Vitamin B 6 deficiency causes embryo lethality in Arabidopsis ( Arabidopsis thaliana ), but the specific role of vitamin B 6 biosynthesis in endosperm development has not been fully addressed, especially in monocot crops, where endosperm constitutes the major portion of the grain. Through molecular characterization of a small kernel2 ( smk2 ) mutant in maize, we reveal that vitamin B 6 has differential effects on embryogenesis and endosperm development in maize. The B 6 vitamer pyridoxal 5'-phosphate (PLP) is drastically reduced in both the smk2 embryo and the endosperm. However, whereas embryogenesis of the smk2 mutant is arrested at the transition stage, endosperm formation is nearly normal. Cloning reveals that Smk2 encodes the glutaminase subunit of the PLP synthase complex involved in vitamin B 6 biosynthesis de novo. Smk2 partially complements the Arabidopsis vitamin B 6 -deficient mutant pdx2.1 and Saccharomyces cerevisiae pyridoxine auxotrophic mutant MML21. Smk2 is constitutively expressed in the maize plant, including developing embryos. Analysis of B 6 vitamers indicates that the endosperm accumulates a large amount of pyridoxamine 5'-phosphate (PMP). These results indicate that vitamin B 6 is essential to embryogenesis but has a reduced role in endosperm development in maize. The vitamin B 6 required for seed development is synthesized in the seed, and the endosperm accumulates PMP probably as a storage form of vitamin B 6 . © 2017 American Society of Plant Biologists. All Rights Reserved.
Kernel versions of some orthogonal transformations
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg
Kernel versions of orthogonal transformations such as principal components are based on a dual formulation also termed Q-mode analysis in which the data enter into the analysis via inner products in the Gram matrix only. In the kernel version the inner products of the original data are replaced...... by inner products between nonlinear mappings into higher dimensional feature space. Via kernel substitution also known as the kernel trick these inner products between the mappings are in turn replaced by a kernel function and all quantities needed in the analysis are expressed in terms of this kernel...... function. This means that we need not know the nonlinear mappings explicitly. Kernel principal component analysis (PCA) and kernel minimum noise fraction (MNF) analyses handle nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via the kernel function...
International Nuclear Information System (INIS)
Ritenour, R.L.
1989-01-01
The single collision thermalization (SCT) approximation models the thermalization process by assuming that neutrons attain a thermalized distribution with only a single collision within the moderating material, independent of the neutron's incident energy. The physical intuition on which this approximation is based is that the salient properties of neutron thermalization are accounted for in the first collision, and the effects of subsequent collisions tend to average out statistically. The independence of the neutron incident and outscattering energy leads to variable separability in the scattering kernel and, thus, significant simplification of the neutron thermalization problem. The approximation also addresses detailed balance and neutron conservation concerns. All of the tests performed on the SCT approximation yielded excellent results. The significance of the SCT approximation is that it greatly simplifies thermalization calculations for CNS design. Preliminary investigations with cases involving strong absorbers also indicates that this approximation may have broader applicability, as in the upgrading of the thermalization codes
Integral equations with contrasting kernels
Directory of Open Access Journals (Sweden)
Theodore Burton
2008-01-01
Full Text Available In this paper we study integral equations of the form $x(t=a(t-\\int^t_0 C(t,sx(sds$ with sharply contrasting kernels typified by $C^*(t,s=\\ln (e+(t-s$ and $D^*(t,s=[1+(t-s]^{-1}$. The kernel assigns a weight to $x(s$ and these kernels have exactly opposite effects of weighting. Each type is well represented in the literature. Our first project is to show that for $a\\in L^2[0,\\infty$, then solutions are largely indistinguishable regardless of which kernel is used. This is a surprise and it leads us to study the essential differences. In fact, those differences become large as the magnitude of $a(t$ increases. The form of the kernel alone projects necessary conditions concerning the magnitude of $a(t$ which could result in bounded solutions. Thus, the next project is to determine how close we can come to proving that the necessary conditions are also sufficient. The third project is to show that solutions will be bounded for given conditions on $C$ regardless of whether $a$ is chosen large or small; this is important in real-world problems since we would like to have $a(t$ as the sum of a bounded, but badly behaved function, and a large well behaved function.
Model selection for Gaussian kernel PCA denoising
DEFF Research Database (Denmark)
Jørgensen, Kasper Winther; Hansen, Lars Kai
2012-01-01
We propose kernel Parallel Analysis (kPA) for automatic kernel scale and model order selection in Gaussian kernel PCA. Parallel Analysis [1] is based on a permutation test for covariance and has previously been applied for model order selection in linear PCA, we here augment the procedure to also...... tune the Gaussian kernel scale of radial basis function based kernel PCA.We evaluate kPA for denoising of simulated data and the US Postal data set of handwritten digits. We find that kPA outperforms other heuristics to choose the model order and kernel scale in terms of signal-to-noise ratio (SNR...
Kernel learning algorithms for face recognition
Li, Jun-Bao; Pan, Jeng-Shyang
2013-01-01
Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method. This book provides researchers in pattern recognition and machine learning area with advanced face recognition methods and its new
RTOS kernel in portable electrocardiograph
Centeno, C. A.; Voos, J. A.; Riva, G. G.; Zerbini, C.; Gonzalez, E. A.
2011-12-01
This paper presents the use of a Real Time Operating System (RTOS) on a portable electrocardiograph based on a microcontroller platform. All medical device digital functions are performed by the microcontroller. The electrocardiograph CPU is based on the 18F4550 microcontroller, in which an uCOS-II RTOS can be embedded. The decision associated with the kernel use is based on its benefits, the license for educational use and its intrinsic time control and peripherals management. The feasibility of its use on the electrocardiograph is evaluated based on the minimum memory requirements due to the kernel structure. The kernel's own tools were used for time estimation and evaluation of resources used by each process. After this feasibility analysis, the migration from cyclic code to a structure based on separate processes or tasks able to synchronize events is used; resulting in an electrocardiograph running on one Central Processing Unit (CPU) based on RTOS.
DEFF Research Database (Denmark)
Walder, Christian; Henao, Ricardo; Mørup, Morten
We present three generalisations of Kernel Principal Components Analysis (KPCA) which incorporate knowledge of the class labels of a subset of the data points. The first, MV-KPCA, penalises within class variances similar to Fisher discriminant analysis. The second, LSKPCA is a hybrid of least squ...... squares regression and kernel PCA. The final LR-KPCA is an iteratively reweighted version of the previous which achieves a sigmoid loss function on the labeled points. We provide a theoretical risk bound as well as illustrative experiments on real and toy data sets....
Metabolisable energy values of whole palm kernel and palm kernel ...
African Journals Online (AJOL)
4.12 Kcal/kg DM. 4.36 and 4.13 Kcal/kg DM, respectively were the corresponding values for broiler chickens. No interaction between ingredients and birds was found but there were interactions among the bioavailable energy systems and the bird types. Keywords: Metabolisable energy, palm kernel layers, broilers.
Carvalho, José Wilson P; Alves, Fernanda Rosa; Batista, Tatiana; Carvalho, Francisco Adriano O; Santiago, Patrícia S; Tabak, Marcel
2013-11-01
Glossoscolex paulistus (HbGp) hemoglobin is an oligomeric protein, presenting a quaternary structure constituted by 144 globin and 36 non-globin chains (named linkers) with a total molecular mass of 3.6 MDa. SDS effects on the oxy-HbGp thermal stability were studied, by DLS and SAXS, at pH 5.0, 7.0 and 9.0. DLS and SAXS data show that the SDS-oxy-HbGp interactions induce a significant decrease of the protein thermal stability, with the formation of larger aggregates, at pH 5.0. At pH 7.0, oxy-HbGp undergoes complete oligomeric dissociation, with increase of temperature, in the presence of SDS. Besides, oxy-HbGp 3.0mg/mL, pH 7.0, in the presence of SDS, has the oligomeric dissociation process reduced as compared to 0.5mg/mL of protein. At pH 9.0, oxy-HbGp starts to dissociate at 20 °C, and the protein is totally dissociated at 50 °C. The thermal dissociation kinetic data show that oxy-HbGp oligomeric dissociation at pH 7.0, in the presence of SDS, is strongly dependent on the protein concentration. At 0.5mg/mL of protein, the oligomeric dissociation is complete and fast at 40 and 42 °C, with kinetic constants of (2.1 ± 0.2) × 10(-4) and (5.5 ± 0.4) × 10(-4) s(-1), respectively, at 0.6 mmol/L SDS. However, at 3.0mg/mL, the oligomeric dissociation process starts at 46 °C, and only partial dissociation, accompanied by aggregates formation is observed. Moreover, our data show, for the first time, that, for 3.0mg/mL of protein, the oligomeric dissociation, denaturation and aggregation phenomena occur simultaneously, in the presence of SDS. Our present results on the surfactant-HbGp interactions and the protein thermal unfolding process correspond to a step forward in the understanding of SDS effects. Copyright © 2013 Elsevier B.V. All rights reserved.
Gupta, Mayanak K.; Singh, Baltej; Mittal, Ranjan; Zbiri, Mohamed; Cairns, Andrew B.; Goodwin, Andrew L.; Schober, Helmut; Chaplot, Samrath L.
2017-12-01
We present temperature-dependent inelastic-neutron-scattering measurements, accompanied by ab initio calculations of the phonon spectra and elastic properties as a function of pressure to quantitatively explain an unusual combination of negative thermal expansion and negative linear compressibility behavior of ZnAu2(CN) 4 . The mechanism of the negative thermal expansion is identified in terms of specific anharmonic phonon modes that involve bending of the -Zn-NC-Au-CN-Zn- linkage. The soft phonon at the L point at the Brillouin zone boundary quantitatively relates to the high-pressure phase transition at about 2 GPa. The ambient pressure structure is also found to be close to an elastic instability that leads to a weakly first-order transition.
Reducing Kernel Development Complexity in Distributed Environments
Lèbre , Adrien; Lottiaux , Renaud; Focht , Erich; Morin , Christine
2008-01-01
Setting up generic and fully transparent distributed services for clusters implies complex and tedious kernel developments. More flexible approaches such as user-space libraries are usually preferred with the drawback of requiring application recompilation. A second approach consists in using specific kernel modules (such as FUSE in Gnu/Linux system) to transfer kernel complexity into user space. In this paper, we present a new way to design and implement kernel distributed services for clust...
Oops! What about a Million Kernel Oopses?
Guo , Lisong; Senna Tschudin , Peter; Kono , Kenji; Muller , Gilles; Lawall , Julia
2013-01-01
When a failure occurs in the Linux kernel, the kernel emits an "oops", summarizing the execution context of the failure. Kernel oopses describe real Linux errors, and thus can help prioritize debugging efforts and motivate the design of tools to improve the reliability of Linux code. Nevertheless, the information is only meaningful if it is representative and can be interpreted correctly. In this paper, we study a repository of kernel oopses collected over 8 months by Red Hat. We consider the...
Derivative Kernels: Numerics and Applications.
Hosseini, Mahdi S; Plataniotis, Konstantinos N
2017-10-01
A generalized framework for numerical differentiation (ND) is proposed for constructing a finite impulse response (FIR) filter in closed form. The framework regulates the frequency response of ND filters for arbitrary derivative-order and cutoff frequency selected parameters relying on interpolating power polynomials and maximally flat design techniques. Compared with the state-of-the-art solutions, such as Gaussian kernels, the proposed ND filter is sharply localized in the Fourier domain with ripple-free artifacts. Here, we construct 2D MaxFlat kernels for image directional differentiation to calculate image differentials for arbitrary derivative order, cutoff level and steering angle. The resulted kernel library renders a new solution capable of delivering discrete approximation of gradients, Hessian, and higher-order tensors in numerous applications. We tested the utility of this library on three different imaging applications with main focus on the unsharp masking. The reported results highlight the high efficiency of the 2D MaxFlat kernel and its versatility with respect to robustness and parameter control accuracy.
Veto-Consensus Multiple Kernel Learning
Zhou, Y.; Hu, N.; Spanos, C.J.
2016-01-01
We propose Veto-Consensus Multiple Kernel Learning (VCMKL), a novel way of combining multiple kernels such that one class of samples is described by the logical intersection (consensus) of base kernelized decision rules, whereas the other classes by the union (veto) of their complements. The
Paramecium: An Extensible Object-Based Kernel
van Doorn, L.; Homburg, P.; Tanenbaum, A.S.
1995-01-01
In this paper we describe the design of an extensible kernel, called Paramecium. This kernel uses an object-based software architecture which together with instance naming, late binding and explicit overrides enables easy reconfiguration. Determining which components reside in the kernel protection
GRIM : Leveraging GPUs for Kernel integrity monitoring
Koromilas, Lazaros; Vasiliadis, Giorgos; Athanasopoulos, Ilias; Ioannidis, Sotiris
2016-01-01
Kernel rootkits can exploit an operating system and enable future accessibility and control, despite all recent advances in software protection. A promising defense mechanism against rootkits is Kernel Integrity Monitor (KIM) systems, which inspect the kernel text and data to discover any malicious
Integral equations with difference kernels on finite intervals
Sakhnovich, Lev A
2015-01-01
This book focuses on solving integral equations with difference kernels on finite intervals. The corresponding problem on the semiaxis was previously solved by N. Wiener–E. Hopf and by M.G. Krein. The problem on finite intervals, though significantly more difficult, may be solved using our method of operator identities. This method is also actively employed in inverse spectral problems, operator factorization and nonlinear integral equations. Applications of the obtained results to optimal synthesis, light scattering, diffraction, and hydrodynamics problems are discussed in this book, which also describes how the theory of operators with difference kernels is applied to stable processes and used to solve the famous M. Kac problems on stable processes. In this second edition these results are extensively generalized and include the case of all Levy processes. We present the convolution expression for the well-known Ito formula of the generator operator, a convolution expression that has proven to be fruitful...
International Nuclear Information System (INIS)
Martins, M.L.; Orecchini, A.; Aguilera, L.; Matic, A.; Eckert, J.; Saeki, M.J.; Bordallo, H.N.
2015-01-01
The anticancer drug Paclitaxel was encapsulated into a bio-nano-composite formed by magnetic nanoparticles, chitosan and apatite. The aim of this drug carrier is to provide a new perspective against breast cancer. The dynamics of the pure and encapsulated drug were investigated in order to verify possible molecular changes caused by the encapsulation, as well as to follow which interactions may occur between paclitaxel and the composite. Fourier transformed infrared spectroscopy, thermal analysis, inelastic (INS) and quasi-elastic neutron scattering experiments were performed. These very preliminary results suggest the successful encapsulation of the drug. Here we put forward a new idea that by using INS further insight on the local dynamics of the pure drug molecule and how its dynamics is affected by the encapsulation can be obtained. Since neutron scattering is not a surface technique and the sample does not need to be manipulated in order to obtain the data, this probe is extremely suitable for confinement studies. Using neutron scattering we show that a number of vibrational modes are damped indicating that the Paclitaxel molecule is constrained by the encapsulation
Directory of Open Access Journals (Sweden)
Senyue Zhang
2016-01-01
Full Text Available According to the characteristics that the kernel function of extreme learning machine (ELM and its performance have a strong correlation, a novel extreme learning machine based on a generalized triangle Hermitian kernel function was proposed in this paper. First, the generalized triangle Hermitian kernel function was constructed by using the product of triangular kernel and generalized Hermite Dirichlet kernel, and the proposed kernel function was proved as a valid kernel function of extreme learning machine. Then, the learning methodology of the extreme learning machine based on the proposed kernel function was presented. The biggest advantage of the proposed kernel is its kernel parameter values only chosen in the natural numbers, which thus can greatly shorten the computational time of parameter optimization and retain more of its sample data structure information. Experiments were performed on a number of binary classification, multiclassification, and regression datasets from the UCI benchmark repository. The experiment results demonstrated that the robustness and generalization performance of the proposed method are outperformed compared to other extreme learning machines with different kernels. Furthermore, the learning speed of proposed method is faster than support vector machine (SVM methods.
Czech Academy of Sciences Publication Activity Database
Kempa, Martin; Ondrejkovič, Petr; Bourges, P.; Márton, Pavel; Hlinka, Jiří
2014-01-01
Roč. 89, č. 5 (2014), "054308-1"-"054308-5" ISSN 1098-0121 R&D Projects: GA ČR GPP204/11/P404 Institutional support: RVO:68378271 Keywords : NaI * alkali halides * inelastic neutron scattering * discrete breathers Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 3.736, year: 2014
Modelling microwave heating of discrete samples of oil palm kernels
International Nuclear Information System (INIS)
Law, M.C.; Liew, E.L.; Chang, S.L.; Chan, Y.S.; Leo, C.P.
2016-01-01
Highlights: • Microwave (MW) drying of oil palm kernels is experimentally determined and modelled. • MW heating of discrete samples of oil palm kernels (OPKs) is simulated. • OPK heating is due to contact effect, MW interference and heat transfer mechanisms. • Electric field vectors circulate within OPKs sample. • Loosely-packed arrangement improves temperature uniformity of OPKs. - Abstract: Recently, microwave (MW) pre-treatment of fresh palm fruits has showed to be environmentally friendly compared to the existing oil palm milling process as it eliminates the condensate production of palm oil mill effluent (POME) in the sterilization process. Moreover, MW-treated oil palm fruits (OPF) also possess better oil quality. In this work, the MW drying kinetic of the oil palm kernels (OPK) was determined experimentally. Microwave heating/drying of oil palm kernels was modelled and validated. The simulation results show that temperature of an OPK is not the same over the entire surface due to constructive and destructive interferences of MW irradiance. The volume-averaged temperature of an OPK is higher than its surface temperature by 3–7 °C, depending on the MW input power. This implies that point measurement of temperature reading is inadequate to determine the temperature history of the OPK during the microwave heating process. The simulation results also show that arrangement of OPKs in a MW cavity affects the kernel temperature profile. The heating of OPKs were identified to be affected by factors such as local electric field intensity due to MW absorption, refraction, interference, the contact effect between kernels and also heat transfer mechanisms. The thermal gradient patterns of OPKs change as the heating continues. The cracking of OPKs is expected to occur first in the core of the kernel and then it propagates to the kernel surface. The model indicates that drying of OPKs is a much slower process compared to its MW heating. The model is useful
Zhang, Wencan; Leong, Siew Mun; Zhao, Feifei; Zhao, Fangju; Yang, Tiankui; Liu, Shaoquan
2018-05-01
With an interest to enhance the aroma of palm kernel oil (PKO), Viscozyme L, an enzyme complex containing a wide range of carbohydrases, was applied to alter the carbohydrates in palm kernels (PK) to modulate the formation of volatiles upon kernel roasting. After Viscozyme treatment, the content of simple sugars and free amino acids in PK increased by 4.4-fold and 4.5-fold, respectively. After kernel roasting and oil extraction, significantly more 2,5-dimethylfuran, 2-[(methylthio)methyl]-furan, 1-(2-furanyl)-ethanone, 1-(2-furyl)-2-propanone, 5-methyl-2-furancarboxaldehyde and 2-acetyl-5-methylfuran but less 2-furanmethanol and 2-furanmethanol acetate were found in treated PKO; the correlation between their formation and simple sugar profile was estimated by using partial least square regression (PLS1). Obvious differences in pyrroles and Strecker aldehydes were also found between the control and treated PKOs. Principal component analysis (PCA) clearly discriminated the treated PKOs from that of control PKOs on the basis of all volatile compounds. Such changes in volatiles translated into distinct sensory attributes, whereby treated PKO was more caramelic and burnt after aqueous extraction and more nutty, roasty, caramelic and smoky after solvent extraction. Copyright © 2018 Elsevier Ltd. All rights reserved.
Migration of ThO2 kernels under the influence of a temperature gradient
International Nuclear Information System (INIS)
Smith, C.L.
1976-11-01
BISO coated ThO 2 fertile fuel kernels will migrate up the thermal gradients imposed across coated particles during HTGR operation. Thorium dioxide kernel migration has been studied as a function of temperature (1300 to 1700 0 C) and ThO 2 kernel burnup (0.9 to 5.8 percent FIMA) in out-of-pile, postirradiation thermal gradient heating experiments. The studies were conducted to obtain descriptions of migration rates that will be used in core design studies to evaluate the impact of ThO 2 migration on fertile fuel performance in an operating HTGR and to define characteristics needed by any comprehensive model describing ThO 2 kernel migration. The kinetics data generated in these postirradiation studies are consistent with in-pile data collected by investigators at Oak Ridge National Laboratory, which supports use of the more precise postirradiation heating results in HTGR core design studies. Observations of intergranular carbon deposits on the cool side of migrating kernels support the assumption that the kinetics of kernel migration are controlled by solid state diffusion within irradiated ThO 2 kernels. The migration is characterized by a period of no migration (incubation period) followed by migration at the equilibrium rate for ThO 2 . The incubation period decreases with increasing temperature and kernel burnup. The improved understanding of the kinetics of ThO 2 kernel migration provided by this work will contribute to an optimization of HTGR core design and an increased confidence in fuel performance predictions
Testing Infrastructure for Operating System Kernel Development
DEFF Research Database (Denmark)
Walter, Maxwell; Karlsson, Sven
2014-01-01
Testing is an important part of system development, and to test effectively we require knowledge of the internal state of the system under test. Testing an operating system kernel is a challenge as it is the operating system that typically provides access to this internal state information. Multi......-core kernels pose an even greater challenge due to concurrency and their shared kernel state. In this paper, we present a testing framework that addresses these challenges by running the operating system in a virtual machine, and using virtual machine introspection to both communicate with the kernel...... and obtain information about the system. We have also developed an in-kernel testing API that we can use to develop a suite of unit tests in the kernel. We are using our framework for for the development of our own multi-core research kernel....
International Nuclear Information System (INIS)
Kolar, J.; Strizik, L.; Kohoutek, T.; Wagner, T.; Voyiatzis, G. A.; Chrissanthopoulos, A.; Yannopoulos, S. N.
2013-01-01
Photostructural changes—the hallmark of non-crystalline chalcogenides—are in essence the basis of a number of photoinduced effects, i.e., changes of their physical properties, which are exploited in a variety of applications, especially in photonics and optoelectronics. Despite the vast number of investigations of photostructural changes, there is currently lack of systematic studies on how the thermal history, which affects glass structure, modifies the extent of photostructural changes. In this article, we study the role of thermal history on photostructural changes in glassy As 15 S 85 . This particular sulfur-rich composition has been chosen based on the colossal photostructural response it exhibits under near-band gap light irradiation, which inherently originates from its nanoscale phase-separated nature. To control the thermal history, the glass was quenched to various temperatures and each of these quenched products was annealed under four different conditions. Off-resonant Raman scattering was used to study the equilibrium study of each product. Structural changes of interest involve changes of the sulfur atoms participating into S 8 rings and S n chains. Their ratio was found to depend on quenching/annealing conditions. Near-band gap light was used to perturb the rings-to-chain ratio and at the same time to record these changes through Raman scattering, revealing an intricate behavior of photostructural changes. Ab initio calculations were employed to determine the stability of various sulfur clusters/molecules thus aiding the correlation of the particular photo-response of glassy As 15 S 85 with its structural constituents
Invariant scattering convolution networks.
Bruna, Joan; Mallat, Stéphane
2013-08-01
A wavelet scattering network computes a translation invariant image representation which is stable to deformations and preserves high-frequency information for classification. It cascades wavelet transform convolutions with nonlinear modulus and averaging operators. The first network layer outputs SIFT-type descriptors, whereas the next layers provide complementary invariant information that improves classification. The mathematical analysis of wavelet scattering networks explains important properties of deep convolution networks for classification. A scattering representation of stationary processes incorporates higher order moments and can thus discriminate textures having the same Fourier power spectrum. State-of-the-art classification results are obtained for handwritten digits and texture discrimination, with a Gaussian kernel SVM and a generative PCA classifier.
Energy Technology Data Exchange (ETDEWEB)
Ghrayeb, S. Z. [Dept. of Mechanical and Nuclear Engineering, Pennsylvania State Univ., 230 Reber Building, Univ. Park, PA 16802 (United States); Ouisloumen, M. [Westinghouse Electric Company, 1000 Westinghouse Drive, Cranberry Township, PA 16066 (United States); Ougouag, A. M. [Idaho National Laboratory, MS-3860, PO Box 1625, Idaho Falls, ID 83415 (United States); Ivanov, K. N.
2012-07-01
A multi-group formulation for the exact neutron elastic scattering kernel is developed. This formulation is intended for implementation into a lattice physics code. The correct accounting for the crystal lattice effects influences the estimated values for the probability of neutron absorption and scattering, which in turn affect the estimation of core reactivity and burnup characteristics. A computer program has been written to test the formulation for various nuclides. Results of the multi-group code have been verified against the correct analytic scattering kernel. In both cases neutrons were started at various energies and temperatures and the corresponding scattering kernels were tallied. (authors)
International Nuclear Information System (INIS)
Ghrayeb, S. Z.; Ouisloumen, M.; Ougouag, A. M.; Ivanov, K. N.
2012-01-01
A multi-group formulation for the exact neutron elastic scattering kernel is developed. This formulation is intended for implementation into a lattice physics code. The correct accounting for the crystal lattice effects influences the estimated values for the probability of neutron absorption and scattering, which in turn affect the estimation of core reactivity and burnup characteristics. A computer program has been written to test the formulation for various nuclides. Results of the multi-group code have been verified against the correct analytic scattering kernel. In both cases neutrons were started at various energies and temperatures and the corresponding scattering kernels were tallied. (authors)
Investigation of the coherence between Rayleigh scattering and resonant scattering
International Nuclear Information System (INIS)
Moine, Jean Jacques
1962-01-01
This academic work aims at the experimental verification of the coherence between Rayleigh scattering and resonant scattering processes. After some generalities about the Moessbauer Effect, and on thermal agitation and recoil, the author addresses the scattering of protons by atoms and nuclei in a solid body (Rayleigh atomic scattering and resonant nuclear scattering, and interaction between both). He presents the experimental apparatus: gamma ray source, photo detection, diffuser, electronic system. He discusses the expected counting and the experimental results [fr
Fréchet kernels for finite-frequency traveltimes-II. Examples
Hung, S.-H.; Dahlen, F. A.; Nolet, Guust
2000-04-01
3-D Born-Fréchet traveltime kernel theory is recast in the context of scalar-wave propagation in a smooth acoustic medium, for simplicity. The predictions of the theory are in excellent agreement with `ground truth' traveltime shifts, measured by cross-correlation of heterogeneous-medium and homogeneous-medium synthetic seismograms, computed using a parallelized pseudospectral code. Scattering, wave-front healing and other finite-frequency diffraction effects can give rise to cross-correlation traveltime shifts that are in significant disagreement with geometrical ray theory, whenever the cross-path width of wave-speed heterogeneity is of the same order as the width of the banana-doughnut Fréchet kernel surrounding the ray. A concentrated off-path slow or fast anomaly can give rise to a larger traveltime shift than one directly on the ray path, by virtue of the hollow-banana character of the kernel. The often intricate 3-D geometry of the sensitivity kernels of P, PP, PcP, PcP2, PcP3, ≑ and P + pP waves is explored, in a series of colourful cross-sections. The geometries of an absolute PP kernel and a differential PP - P kernel are particularly complicated, because of the minimax nature of the surface-reflected PP wave. The kernel for an overlapping P + pP wave from a shallow-focus source has a banana-doughnut character, like that of an isolated P-wave kernel, even when the teleseismic pulse shape is significantly distorted by the depth phase interference. A numerically economical representation of the 3-D traveltime sensitivity, based upon the paraxial approximation, is in excellent agreement with the `exact' ray-theoretical Fréchet kernel.
A new kernel discriminant analysis framework for electronic nose recognition
International Nuclear Information System (INIS)
Zhang, Lei; Tian, Feng-Chun
2014-01-01
Graphical abstract: - Highlights: • This paper proposes a new discriminant analysis framework for feature extraction and recognition. • The principle of the proposed NDA is derived mathematically. • The NDA framework is coupled with kernel PCA for classification. • The proposed KNDA is compared with state of the art e-Nose recognition methods. • The proposed KNDA shows the best performance in e-Nose experiments. - Abstract: Electronic nose (e-Nose) technology based on metal oxide semiconductor gas sensor array is widely studied for detection of gas components. This paper proposes a new discriminant analysis framework (NDA) for dimension reduction and e-Nose recognition. In a NDA, the between-class and the within-class Laplacian scatter matrix are designed from sample to sample, respectively, to characterize the between-class separability and the within-class compactness by seeking for discriminant matrix to simultaneously maximize the between-class Laplacian scatter and minimize the within-class Laplacian scatter. In terms of the linear separability in high dimensional kernel mapping space and the dimension reduction of principal component analysis (PCA), an effective kernel PCA plus NDA method (KNDA) is proposed for rapid detection of gas mixture components by an e-Nose. The NDA framework is derived in this paper as well as the specific implementations of the proposed KNDA method in training and recognition process. The KNDA is examined on the e-Nose datasets of six kinds of gas components, and compared with state of the art e-Nose classification methods. Experimental results demonstrate that the proposed KNDA method shows the best performance with average recognition rate and total recognition rate as 94.14% and 95.06% which leads to a promising feature extraction and multi-class recognition in e-Nose
RKRD: Runtime Kernel Rootkit Detection
Grover, Satyajit; Khosravi, Hormuzd; Kolar, Divya; Moffat, Samuel; Kounavis, Michael E.
In this paper we address the problem of protecting computer systems against stealth malware. The problem is important because the number of known types of stealth malware increases exponentially. Existing approaches have some advantages for ensuring system integrity but sophisticated techniques utilized by stealthy malware can thwart them. We propose Runtime Kernel Rootkit Detection (RKRD), a hardware-based, event-driven, secure and inclusionary approach to kernel integrity that addresses some of the limitations of the state of the art. Our solution is based on the principles of using virtualization hardware for isolation, verifying signatures coming from trusted code as opposed to malware for scalability and performing system checks driven by events. Our RKRD implementation is guided by our goals of strong isolation, no modifications to target guest OS kernels, easy deployment, minimal infra-structure impact, and minimal performance overhead. We developed a system prototype and conducted a number of experiments which show that the per-formance impact of our solution is negligible.
Kernel Bayesian ART and ARTMAP.
Masuyama, Naoki; Loo, Chu Kiong; Dawood, Farhan
2018-02-01
Adaptive Resonance Theory (ART) is one of the successful approaches to resolving "the plasticity-stability dilemma" in neural networks, and its supervised learning model called ARTMAP is a powerful tool for classification. Among several improvements, such as Fuzzy or Gaussian based models, the state of art model is Bayesian based one, while solving the drawbacks of others. However, it is known that the Bayesian approach for the high dimensional and a large number of data requires high computational cost, and the covariance matrix in likelihood becomes unstable. This paper introduces Kernel Bayesian ART (KBA) and ARTMAP (KBAM) by integrating Kernel Bayes' Rule (KBR) and Correntropy Induced Metric (CIM) to Bayesian ART (BA) and ARTMAP (BAM), respectively, while maintaining the properties of BA and BAM. The kernel frameworks in KBA and KBAM are able to avoid the curse of dimensionality. In addition, the covariance-free Bayesian computation by KBR provides the efficient and stable computational capability to KBA and KBAM. Furthermore, Correntropy-based similarity measurement allows improving the noise reduction ability even in the high dimensional space. The simulation experiments show that KBA performs an outstanding self-organizing capability than BA, and KBAM provides the superior classification ability than BAM, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.
Nonlinear Deep Kernel Learning for Image Annotation.
Jiu, Mingyuan; Sahbi, Hichem
2017-02-08
Multiple kernel learning (MKL) is a widely used technique for kernel design. Its principle consists in learning, for a given support vector classifier, the most suitable convex (or sparse) linear combination of standard elementary kernels. However, these combinations are shallow and often powerless to capture the actual similarity between highly semantic data, especially for challenging classification tasks such as image annotation. In this paper, we redefine multiple kernels using deep multi-layer networks. In this new contribution, a deep multiple kernel is recursively defined as a multi-layered combination of nonlinear activation functions, each one involves a combination of several elementary or intermediate kernels, and results into a positive semi-definite deep kernel. We propose four different frameworks in order to learn the weights of these networks: supervised, unsupervised, kernel-based semisupervised and Laplacian-based semi-supervised. When plugged into support vector machines (SVMs), the resulting deep kernel networks show clear gain, compared to several shallow kernels for the task of image annotation. Extensive experiments and analysis on the challenging ImageCLEF photo annotation benchmark, the COREL5k database and the Banana dataset validate the effectiveness of the proposed method.
Energy Technology Data Exchange (ETDEWEB)
Fomin, B.A. [CPTEC/INPE, Rod. Presidente Dutra, km.40, Cachoeira Paulsta, Sao Paulo, 12630-000 (Brazil)]. E-mail: fomin@cptec.inpe.br
2006-03-15
An algorithm for calculations of the longwave radiation in cloudy and aerosol slab atmospheres is described. It is based on the line-by-line and Monte-Carlo methods and is suitable for accurate treatment of both the gaseous absorption and the particulate multiple scattering in any spectral regions; other published algorithms as accurate as this can only make calculations in narrow spectral regions. It is recommended that this algorithm is well suited for radiation code validations as well as for theoretical investigations of radiative transfer in clouds and aerosols and satellite signal simulations.
Theory of reproducing kernels and applications
Saitoh, Saburou
2016-01-01
This book provides a large extension of the general theory of reproducing kernels published by N. Aronszajn in 1950, with many concrete applications. In Chapter 1, many concrete reproducing kernels are first introduced with detailed information. Chapter 2 presents a general and global theory of reproducing kernels with basic applications in a self-contained way. Many fundamental operations among reproducing kernel Hilbert spaces are dealt with. Chapter 2 is the heart of this book. Chapter 3 is devoted to the Tikhonov regularization using the theory of reproducing kernels with applications to numerical and practical solutions of bounded linear operator equations. In Chapter 4, the numerical real inversion formulas of the Laplace transform are presented by applying the Tikhonov regularization, where the reproducing kernels play a key role in the results. Chapter 5 deals with ordinary differential equations; Chapter 6 includes many concrete results for various fundamental partial differential equations. In Chapt...
Djebbi, Ramzi
2013-08-19
Anisotropy is an inherent character of the Earth subsurface. It should be considered for modeling and inversion. The acoustic VTI wave equation approximates the wave behavior in anisotropic media, and especially it\\'s kinematic characteristics. To analyze which parts of the model would affect the traveltime for anisotropic traveltime inversion methods, especially for wave equation tomography (WET), we drive the sensitivity kernels for anisotropic media using the VTI acoustic wave equation. A Born scattering approximation is first derived using the Fourier domain acoustic wave equation as a function of perturbations in three anisotropy parameters. Using the instantaneous traveltime, which unwraps the phase, we compute the kernels. These kernels resemble those for isotropic media, with the η kernel directionally dependent. They also have a maximum sensitivity along the geometrical ray, which is more realistic compared to the cross-correlation based kernels. Focusing on diving waves, which is used more often, especially recently in waveform inversion, we show sensitivity kernels in anisotropic media for this case.
Swank, C. M.; Petukhov, A. K.; Golub, R.
2016-06-01
The behavior of a spin undergoing Larmor precession in the presence of fluctuating fields is of interest to workers in many fields. The fluctuating fields cause frequency shifts and relaxation which are related to their power spectrum, which can be determined by taking the Fourier transform of the auto-correlation functions of the field fluctuations. Recently we have shown how to calculate these correlation functions for all values of mean-free path (ballistic to diffusive motion) in finite bounded regions by using the model of persistent continuous time random walks (CTRW) for particles subject to scattering by fixed (frozen) scattering centers so that the speed of the moving particles is not changed by the collisions. In this work we show how scattering with energy exchange from an ensemble of scatterers in thermal equilibrium can be incorporated into the CTRW. We present results for 1, 2, and 3 dimensions. The results agree for all these cases contrary to the previously studied "frozen" models. Our results for the velocity autocorrelation function show a long-time tail (˜t-1 /2 ), which we also obtain from conventional diffusion theory, with the same power, independent of dimensionality. Our results are valid for any Markovian scattering kernel as well as for any kernel based on a scattering cross section ˜1 /v .
kFOIL: Learning simple relational kernels
Landwehr, Niels; Passerini, Andrea; De Raedt, Luc; Frasconi, Paolo
2006-01-01
A novel and simple combination of inductive logic programming with kernel methods is presented. The kFOIL algorithm integrates the well-known inductive logic programming system FOIL with kernel methods. The feature space is constructed by leveraging FOIL search for a set of relevant clauses. The search is driven by the performance obtained by a support vector machine based on the resulting kernel. In this way, kFOIL implements a dynamic propositionalization approach. Both classification an...
Convergence of barycentric coordinates to barycentric kernels
Kosinka, Jiří
2016-02-12
We investigate the close correspondence between barycentric coordinates and barycentric kernels from the point of view of the limit process when finer and finer polygons converge to a smooth convex domain. We show that any barycentric kernel is the limit of a set of barycentric coordinates and prove that the convergence rate is quadratic. Our convergence analysis extends naturally to barycentric interpolants and mappings induced by barycentric coordinates and kernels. We verify our theoretical convergence results numerically on several examples.
Process for producing metal oxide kernels and kernels so obtained
International Nuclear Information System (INIS)
Lelievre, Bernard; Feugier, Andre.
1974-01-01
The process desbribed is for producing fissile or fertile metal oxide kernels used in the fabrication of fuels for high temperature nuclear reactors. This process consists in adding to an aqueous solution of at least one metallic salt, particularly actinide nitrates, at least one chemical compound capable of releasing ammonia, in dispersing drop by drop the solution thus obtained into a hot organic phase to gel the drops and transform them into solid particles. These particles are then washed, dried and treated to turn them into oxide kernels. The organic phase used for the gel reaction is formed of a mixture composed of two organic liquids, one acting as solvent and the other being a product capable of extracting the anions from the metallic salt of the drop at the time of gelling. Preferably an amine is used as product capable of extracting the anions. Additionally, an alcohol that causes a part dehydration of the drops can be employed as solvent, thus helping to increase the resistance of the particles [fr
International Nuclear Information System (INIS)
Drozdowicz, K.
1999-01-01
Macroscopic parameters for a description of the thermal neutron transport in finite volumes are considered. A very good correspondence between the theoretical and experimental parameters of hydrogenous media is attained. Thermal neutrons in the medium possess an energy distribution, which is dependent on the size (characterized by the geometric buckling) and on the neutron transport properties of the medium. In a hydrogenous material the thermal neutron transport is dominated by the scattering cross section which is strongly dependent on energy. A monoenergetic treatment of the thermal neutron group (admissible for other materials) leads in this case to a discrepancy between theoretical and experimental results. In the present paper the theoretical definitions of the pulsed thermal neutron parameters (the absorption rate, the diffusion coefficient, and the diffusion cooling coefficient) are based on Nelkin's analysis of the decay of a neutron pulse. Problems of the experimental determination of these parameters for a hydrogenous medium are discussed. A theoretical calculation of the pulsed parameters requires knowledge of the scattering kernel. For thermal neutrons it is individual for each hydrogenous material because neutron scattering on hydrogen nuclei bound in a molecule is affected by the molecular dynamics (characterized with internal energy modes which are comparable to the incident neutron energy). Granada's synthetic model for slow-neutron scattering is used. The complete up-dated formalism of calculation of the energy transfer scattering kernel after this model is presented in the paper. An influence of some minor variants within the model on the calculated differential and integral neutron parameters is shown. The theoretical energy-dependent scattering cross section (of Plexiglas) is compared to experimental results. A particular attention is paid to the calculation of the diffusion cooling coefficient. A solution of an equation, which determines the
Hilbertian kernels and spline functions
Atteia, M
1992-01-01
In this monograph, which is an extensive study of Hilbertian approximation, the emphasis is placed on spline functions theory. The origin of the book was an effort to show that spline theory parallels Hilbertian Kernel theory, not only for splines derived from minimization of a quadratic functional but more generally for splines considered as piecewise functions type. Being as far as possible self-contained, the book may be used as a reference, with information about developments in linear approximation, convex optimization, mechanics and partial differential equations.
7 CFR 51.1403 - Kernel color classification.
2010-01-01
... models of pecan kernels, illustrate the color intensities implied by the terms “golden,” “light brown... Kernel color classification. (a) The skin color of pecan kernels may be described in terms of the color...
Sentiment classification with interpolated information diffusion kernels
Raaijmakers, S.
2007-01-01
Information diffusion kernels - similarity metrics in non-Euclidean information spaces - have been found to produce state of the art results for document classification. In this paper, we present a novel approach to global sentiment classification using these kernels. We carry out a large array of
Ranking Support Vector Machine with Kernel Approximation
Directory of Open Access Journals (Sweden)
Kai Chen
2017-01-01
Full Text Available Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels can give higher accuracy than linear RankSVM (RankSVM with a linear kernel for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.
Evolution kernel for the Dirac field
International Nuclear Information System (INIS)
Baaquie, B.E.
1982-06-01
The evolution kernel for the free Dirac field is calculated using the Wilson lattice fermions. We discuss the difficulties due to which this calculation has not been previously performed in the continuum theory. The continuum limit is taken, and the complete energy eigenfunctions as well as the propagator are then evaluated in a new manner using the kernel. (author)
Modelling Issues in Kernel Ridge Regression
P. Exterkate (Peter)
2011-01-01
textabstractKernel ridge regression is gaining popularity as a data-rich nonlinear forecasting tool, which is applicable in many different contexts. This paper investigates the influence of the choice of kernel and the setting of tuning parameters on forecast accuracy. We review several popular
Kernel method for corrections to scaling.
Harada, Kenji
2015-07-01
Scaling analysis, in which one infers scaling exponents and a scaling function in a scaling law from given data, is a powerful tool for determining universal properties of critical phenomena in many fields of science. However, there are corrections to scaling in many cases, and then the inference problem becomes ill-posed by an uncontrollable irrelevant scaling variable. We propose a new kernel method based on Gaussian process regression to fix this problem generally. We test the performance of the new kernel method for some example cases. In all cases, when the precision of the example data increases, inference results of the new kernel method correctly converge. Because there is no limitation in the new kernel method for the scaling function even with corrections to scaling, unlike in the conventional method, the new kernel method can be widely applied to real data in critical phenomena.
Bayesian Kernel Mixtures for Counts.
Canale, Antonio; Dunson, David B
2011-12-01
Although Bayesian nonparametric mixture models for continuous data are well developed, there is a limited literature on related approaches for count data. A common strategy is to use a mixture of Poissons, which unfortunately is quite restrictive in not accounting for distributions having variance less than the mean. Other approaches include mixing multinomials, which requires finite support, and using a Dirichlet process prior with a Poisson base measure, which does not allow smooth deviations from the Poisson. As a broad class of alternative models, we propose to use nonparametric mixtures of rounded continuous kernels. An efficient Gibbs sampler is developed for posterior computation, and a simulation study is performed to assess performance. Focusing on the rounded Gaussian case, we generalize the modeling framework to account for multivariate count data, joint modeling with continuous and categorical variables, and other complications. The methods are illustrated through applications to a developmental toxicity study and marketing data. This article has supplementary material online.
Song, Hyon Min
2013-01-01
SERS provides great sensitivity at low concentrations of analytes. SERS combined with near infrared (NIR)-resonant gold nanomaterials are important candidates for theranostic agents due to their combined extinction properties and sensing abilities stemming from the deep penetration of laser light in the NIR region. Here, highly branched gold nanoflowers (GNFs) grown from Pd and Pt seeds are prepared and their SERS properties are studied. The growth was performed at 80°C without stirring, and this high temperature growth method is assumed to provide great shape stability of sharp tips in GNFs. We found that seed size must be large enough (>30 nm in diameter) to induce the growth of those SERS-active and thermally stable GNFs. We also found that the addition of silver nitrate (AgNO3) is important to induce sharp tip growth and shape stability. Incubation with Hela cells indicates that GNFs are taken up and reside in the cytoplasm. SERS was observed in those cells incubated with 1,10-phenanthroline (Phen)-loaded GNFs. This journal is © 2013 The Royal Society of Chemistry.
Analysis of total hydrogen content in palm oil and palm kernel oil ...
African Journals Online (AJOL)
A fast and non-destructive technique based on thermal neutron moderation has been used for determining the total hydrogen content in two types of red palm oil (dzomi and amidze) and palm kernel oil produced by traditio-nal methods in Ghana. An equipment consisting of an 241Am-Be neutron source and 3He neutron ...
Meenakshi; Ahuja, Munish
2015-01-01
The purpose of present study was to prepare composite hydrogels of carboxymethyl tamarind kernel polysaccharide and polyvinyl alcohol employing freeze thaw-treatment and evaluate them for release behavior. The effect of concentrations of carboxymethyl tamarind kernel polysaccharide, polyvinyl alcohol, and freeze-thaw cycles on the % release of metronidazole was studied employing central composite experimental design. The result of the study revealed that the concentration of carboxymethyl tamarind kernel polysaccharide and interaction effect of concentrations of carboxymethyl tamarind kernel polysaccharide and polyvinyl alcohol influenced the release of metronidazole significantly. The optimal calculated parameters were concentration of carboxymethyl tamarind kernel polysaccharide-6.0% (w/v), concentration of polyvinyl alcohol-8.53% (w/v) and freeze-thaw cycles-4, which provided cryogels with a release of 75.77% over a period of 6h. The formation of cryogels was confirmed by Fourier-transformed infrared spectroscopy and X-ray diffraction studies. Thermal studies revealed higher thermal stability of cryogel. Copyright © 2014 Elsevier B.V. All rights reserved.
THE 1.6 μm NEAR-INFRARED NUCLEI OF 3C RADIO GALAXIES: JETS, THERMAL EMISSION, OR SCATTERED LIGHT?
International Nuclear Information System (INIS)
Baldi, Ranieri D.; Chiaberge, Marco; Sparks, William; Macchetto, F. Duccio; Capetti, Alessandro; O'Dea, Christopher P.; Axon, David J.; Baum, Stefi A.; Quillen, Alice C.
2010-01-01
Using HST NICMOS 2 observations we have measured 1.6 μm near-infrared nuclear luminosities of 100 3CR radio galaxies with z < 0.3, by modeling and subtracting the extended emission from the host galaxy. We performed a multiwavelength statistical analysis (including optical and radio data) of the properties of the nuclei following classification of the objects into FR I and FR II, and low-ionization galaxies (LIGs), high-ionization galaxies (HIGs), and broad-line objects (BLOs) using the radio morphology and optical spectra, respectively. The correlations among near-infrared, optical, and radio nuclear luminosity support the idea that the near-infrared nuclear emission of FR Is has a non-thermal origin. Despite the difference in radio morphology, the multiwavelength properties of FR II LIG nuclei are statistically indistinguishable from those of FR Is, an indication of a common structure of the central engine. All BLOs show an unresolved near-infrared nucleus and a large near-infrared excess with respect to FR II LIGs and FR Is of equal radio core luminosity. This requires the presence of an additional (and dominant) component other than the non-thermal light. Considering the shape of their spectral energy distribution, we ascribe the origin of their near-infrared light to hot circumnuclear dust. A near-infrared excess is also found in HIGs, but their nuclei are substantially fainter than those of BLO. This result indicates that substantial obscuration along the line of sight to the nuclei is still present at 1.6 μm. Nonetheless, HIG nuclei cannot simply be explained in terms of dust obscuration: a significant contribution from light reflected in a circumnuclear scattering region is needed to account for their multiwavelength properties.
Energy Technology Data Exchange (ETDEWEB)
Murakami, Toshiya; Matsuda, Mitsuaki; Itoh, Chihiro, E-mail: citoh@sys.wakayama-u.ac.jp [Department of Materials Science, Wakayama University, 930 Sakaedani, Wakayama 640-8510 (Japan); Kisoda, Kenji [Department of Physics, Wakayama University, 930 Sakaedani, Wakayama 640-8510 (Japan)
2016-08-15
We have found that a Raman scattering (RS) peak around 1870 cm{sup −1} was produced by the annealing of the X-ray irradiated film of single-walled carbon nanotubes (SWNTs) at 450 {sup o}C. The intensity of 1870-cm{sup −1} peak showed a maximum at the probe energy of 2.3 eV for the RS spectroscopy with various probe lasers. Both the peak position and the probe-energy dependence were almost identical to those of the one-dimensional carbon chains previously reported in multi-walled carbon nanotubes. Consequently, we concluded that the 1870-cm{sup −1} peak found in the present study is attributed to carbon chains. The formation of carbon chains by the annealing at temperature lower than 500 {sup o}C is firstly reported by the present study. The carbon chains would be formed by aggregation of the interstitial carbons, which are formed as a counterpart of carbon vacancies by X-ray irradiation diffused on SWNT walls. The result indicates that the combination of X-ray irradiation and subsequent thermal annealing is a feasible tool for generating new nanostructures in SWNT.
Formalism for neutron cross section covariances in the resonance region using kernel approximation
Energy Technology Data Exchange (ETDEWEB)
Oblozinsky, P.; Cho,Y-S.; Matoon,C.M.; Mughabghab,S.F.
2010-04-09
We describe analytical formalism for estimating neutron radiative capture and elastic scattering cross section covariances in the resolved resonance region. We use capture and scattering kernels as the starting point and show how to get average cross sections in broader energy bins, derive analytical expressions for cross section sensitivities, and deduce cross section covariances from the resonance parameter uncertainties in the recently published Atlas of Neutron Resonances. The formalism elucidates the role of resonance parameter correlations which become important if several strong resonances are located in one energy group. Importance of potential scattering uncertainty as well as correlation between potential scattering and resonance scattering is also examined. Practical application of the formalism is illustrated on {sup 55}Mn(n,{gamma}) and {sup 55}Mn(n,el).
Distance Based Multiple Kernel ELM: A Fast Multiple Kernel Learning Approach
Directory of Open Access Journals (Sweden)
Chengzhang Zhu
2015-01-01
Full Text Available We propose a distance based multiple kernel extreme learning machine (DBMK-ELM, which provides a two-stage multiple kernel learning approach with high efficiency. Specifically, DBMK-ELM first projects multiple kernels into a new space, in which new instances are reconstructed based on the distance of different sample labels. Subsequently, an l2-norm regularization least square, in which the normal vector corresponds to the kernel weights of a new kernel, is trained based on these new instances. After that, the new kernel is utilized to train and test extreme learning machine (ELM. Extensive experimental results demonstrate the superior performance of the proposed DBMK-ELM in terms of the accuracy and the computational cost.
NLO corrections to the Kernel of the BKP-equations
International Nuclear Information System (INIS)
Bartels, J.; Lipatov, L.N.; Vacca, G.P.
2012-01-01
We present results for the NLO kernel of the BKP equations for composite states of three reggeized gluons in the Odderon channel, both in QCD and in N=4 SYM. The NLO kernel consists of the NLO BFKL kernel in the color octet representation and the connected 3→3 kernel, computed in the tree approximation.
21 CFR 176.350 - Tamarind seed kernel powder.
2010-04-01
... 21 Food and Drugs 3 2010-04-01 2009-04-01 true Tamarind seed kernel powder. 176.350 Section 176... Substances for Use Only as Components of Paper and Paperboard § 176.350 Tamarind seed kernel powder. Tamarind... the provisions of this section. (a) Tamarind seed kernel powder is the ground kernel of tamarind seed...
Higher-order Gaussian kernel in bootstrap boosting algorithm ...
African Journals Online (AJOL)
The bootstrap boosting algorithm is a bias reduction scheme. The adoption of higher-order Gaussian kernel in a bootstrap boosting algorithm in kernel density estimation was investigated. The algorithm used the higher-order. Gaussian kernel instead of the regular fixed kernels. A comparison of the scheme with existing ...
Kernel maximum autocorrelation factor and minimum noise fraction transformations
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg
2010-01-01
in hyperspectral HyMap scanner data covering a small agricultural area, and 3) maize kernel inspection. In the cases shown, the kernel MAF/MNF transformation performs better than its linear counterpart as well as linear and kernel PCA. The leading kernel MAF/MNF variates seem to possess the ability to adapt...
Adaptive Kernel in Meshsize Boosting Algorithm in KDE ...
African Journals Online (AJOL)
This paper proposes the use of adaptive kernel in a meshsize boosting algorithm in kernel density estimation. The algorithm is a bias reduction scheme like other existing schemes but uses adaptive kernel instead of the regular fixed kernels. An empirical study for this scheme is conducted and the findings are comparatively ...
Adaptive Kernel In The Bootstrap Boosting Algorithm In KDE ...
African Journals Online (AJOL)
This paper proposes the use of adaptive kernel in a bootstrap boosting algorithm in kernel density estimation. The algorithm is a bias reduction scheme like other existing schemes but uses adaptive kernel instead of the regular fixed kernels. An empirical study for this scheme is conducted and the findings are comparatively ...
Higher-Order Hybrid Gaussian Kernel in Meshsize Boosting Algorithm
African Journals Online (AJOL)
In this paper, we shall use higher-order hybrid Gaussian kernel in a meshsize boosting algorithm in kernel density estimation. Bias reduction is guaranteed in this scheme like other existing schemes but uses the higher-order hybrid Gaussian kernel instead of the regular fixed kernels. A numerical verification of this scheme ...
NLO corrections to the Kernel of the BKP-equations
Energy Technology Data Exchange (ETDEWEB)
Bartels, J. [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Fadin, V.S. [Budker Institute of Nuclear Physics, Novosibirsk (Russian Federation); Novosibirskij Gosudarstvennyj Univ., Novosibirsk (Russian Federation); Lipatov, L.N. [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Petersburg Nuclear Physics Institute, Gatchina, St. Petersburg (Russian Federation); Vacca, G.P. [INFN, Sezione di Bologna (Italy)
2012-10-02
We present results for the NLO kernel of the BKP equations for composite states of three reggeized gluons in the Odderon channel, both in QCD and in N=4 SYM. The NLO kernel consists of the NLO BFKL kernel in the color octet representation and the connected 3{yields}3 kernel, computed in the tree approximation.
Digital signal processing with kernel methods
Rojo-Alvarez, José Luis; Muñoz-Marí, Jordi; Camps-Valls, Gustavo
2018-01-01
A realistic and comprehensive review of joint approaches to machine learning and signal processing algorithms, with application to communications, multimedia, and biomedical engineering systems Digital Signal Processing with Kernel Methods reviews the milestones in the mixing of classical digital signal processing models and advanced kernel machines statistical learning tools. It explains the fundamental concepts from both fields of machine learning and signal processing so that readers can quickly get up to speed in order to begin developing the concepts and application software in their own research. Digital Signal Processing with Kernel Methods provides a comprehensive overview of kernel methods in signal processing, without restriction to any application field. It also offers example applications and detailed benchmarking experiments with real and synthetic datasets throughout. Readers can find further worked examples with Matlab source code on a website developed by the authors. * Presents the necess...
National Aeronautics and Space Administration — This data set includes the complete set of Hayabusa SPICE data files (kernel files'') for the surveying and collection phases of the mission. The SPICE data files,...
Ensemble Approach to Building Mercer Kernels
National Aeronautics and Space Administration — This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive...
Multiple Kernel Spectral Regression for Dimensionality Reduction
Directory of Open Access Journals (Sweden)
Bing Liu
2013-01-01
Full Text Available Traditional manifold learning algorithms, such as locally linear embedding, Isomap, and Laplacian eigenmap, only provide the embedding results of the training samples. To solve the out-of-sample extension problem, spectral regression (SR solves the problem of learning an embedding function by establishing a regression framework, which can avoid eigen-decomposition of dense matrices. Motivated by the effectiveness of SR, we incorporate multiple kernel learning (MKL into SR for dimensionality reduction. The proposed approach (termed MKL-SR seeks an embedding function in the Reproducing Kernel Hilbert Space (RKHS induced by the multiple base kernels. An MKL-SR algorithm is proposed to improve the performance of kernel-based SR (KSR further. Furthermore, the proposed MKL-SR algorithm can be performed in the supervised, unsupervised, and semi-supervised situation. Experimental results on supervised classification and semi-supervised classification demonstrate the effectiveness and efficiency of our algorithm.
National Aeronautics and Space Administration — This data set includes the complete set of MESSENGER SPICE data files (''kernel files''), which can be accessed using SPICE software. The SPICE data contains...
National Aeronautics and Space Administration — This data set includes the complete set of Cassini SPICE data files (kernel files''), which can be accessed using SPICE software. The SPICE data contains geometric...
National Aeronautics and Space Administration — This data set includes the complete set of NEAR SPICE data files (kernel files'), which can be accessed using SPICE software. The SPICE data contain geometric and...
National Aeronautics and Space Administration — This data set includes the complete set of Stardust SPICE data files (kernel files'), which can be accessed using SPICE software. The SPICE data contains geometric...
National Aeronautics and Space Administration — This data set includes the MSL SPICE data files (kernel files''), which can be accessed using SPICE software. The SPICE data contain geometric and other ancillary...
Fermionic NNLO contributions to Bhabha scattering
International Nuclear Information System (INIS)
Actis, S.; Riemann, T.; Czakon, M.; Uniwersytet Slaski, Katowice; Gluza, J.
2007-10-01
We derive the two-loop corrections to Bhabha scattering from heavy fermions using dispersion relations. The double-box contributions are expressed by three kernel functions. Convoluting the perturbative kernels with fermionic threshold functions or with hadronic data allows to determine numerical results for small electron mass m e , combined with arbitrary values of the fermion mass m f in the loop, m 2 e 2 f , or with hadronic insertions. We present numerical results for m f =m μ , m τ ,m top at typical small- and large-angle kinematics ranging from 1 GeV to 500 GeV. (orig.)
Bandwidth Selection for Weighted Kernel Density Estimation
Wang, Bin; Wang, Xiaofeng
2007-01-01
In the this paper, the authors propose to estimate the density of a targeted population with a weighted kernel density estimator (wKDE) based on a weighted sample. Bandwidth selection for wKDE is discussed. Three mean integrated squared error based bandwidth estimators are introduced and their performance is illustrated via Monte Carlo simulation. The least-squares cross-validation method and the adaptive weight kernel density estimator are also studied. The authors also consider the boundary...
Some Remarks on the Symmetry Kernel Test
Baszczyńska, Aleksandra
2013-01-01
The paper presents chosen statistical tests used to verify the hypothesis of the symmetry of random variable’s distribution. Detailed analysis of the symmetry kernel test is made. The properties of the regarded symmetry kernel test are compared with the other symmetry tests using Monte Carlo methods. The symmetry tests are used, as an example, in analysis of the distribution of the Human Development Index (HDI). W pracy przedstawiono wybrane statystyczne testy wykorzystywane w ...
Absorption line profiles in a moving atmosphere - A single scattering linear perturbation theory
Hays, P. B.; Abreu, V. J.
1989-01-01
An integral equation is derived which linearly relates Doppler perturbations in the spectrum of atmospheric absorption features to the wind system which creates them. The perturbation theory is developed using a single scattering model, which is validated against a multiple scattering calculation. The nature and basic properties of the kernels in the integral equation are examined. It is concluded that the kernels are well behaved and that wind velocity profiles can be recovered using standard inversion techniques.
On the Inclusion Relation of Reproducing Kernel Hilbert Spaces
Zhang, Haizhang; Zhao, Liang
2011-01-01
To help understand various reproducing kernels used in applied sciences, we investigate the inclusion relation of two reproducing kernel Hilbert spaces. Characterizations in terms of feature maps of the corresponding reproducing kernels are established. A full table of inclusion relations among widely-used translation invariant kernels is given. Concrete examples for Hilbert-Schmidt kernels are presented as well. We also discuss the preservation of such a relation under various operations of ...
Sitompul, Monica Angelina
2015-01-01
Have been conducted Determination of Iodin Value by method titration to some Hydrogenated Palm Kernel Oil (HPKO) and Refined Bleached Deodorized Palm Kernel Oil (RBDPKO). The result of analysis obtained the Iodin Value in Hydrogenated Palm Kernel Oil (A) = 0,16 gr I2/100gr, Hydrogenated Palm Kernel Oil (B) = 0,20 gr I2/100gr, Hydrogenated Palm Kernel Oil (C) = 0,24 gr I2/100gr. And in Refined Bleached Deodorized Palm Kernel Oil (A) = 17,51 gr I2/100gr, Refined Bleached Deodorized Palm Kernel ...
Kernel principal component and maximum autocorrelation factor analyses for change detection
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg; Canty, Morton John
2009-01-01
Principal component analysis (PCA) has often been used to detect change over time in remotely sensed images. A commonly used technique consists of finding the projections along the eigenvectors for data consisting of pair-wise (perhaps generalized) differences between corresponding spectral bands...... in Nevada acquired on successive passes of the Landsat-5 satellite in August-September 1991. The six-band images (the thermal band is omitted) with 1,000 by 1,000 28.5 m pixels were first processed with the iteratively re-weighted MAD (IR-MAD) algorithm in order to discriminate change. Then the MAD image...... was post-processed with both ordinary and kernel versions of PCA and MAF analysis. Kernel MAF suppresses the noisy no-change background much more successfully than ordinary MAF. The ratio between variances of the ordinary MAF 1 and the kernel MAF 1 (both scaled to unit variance) calculated in a no...
International Nuclear Information System (INIS)
Wehinger, Björn; Krisch, Michael; Bosak, Alexeï; Chernyshov, Dmitry; Bulat, Sergey; Ezhov, Victor
2014-01-01
Single crystals of ice Ih, extracted from the subglacial Lake Vostok accretion ice layer (3621 m depth) were investigated by means of diffuse x-ray scattering and inelastic x-ray scattering. The diffuse scattering was identified as mainly inelastic and rationalized in the frame of ab initio calculations for the ordered ice XI approximant. Together with Monte-Carlo modelling, our data allowed reconsidering previously available neutron diffuse scattering data of heavy ice as the sum of thermal diffuse scattering and static disorder contribution. (paper)
Exact Heat Kernel on a Hypersphere and Its Applications in Kernel SVM
Directory of Open Access Journals (Sweden)
Chenchao Zhao
2018-01-01
Full Text Available Many contemporary statistical learning methods assume a Euclidean feature space. This paper presents a method for defining similarity based on hyperspherical geometry and shows that it often improves the performance of support vector machine compared to other competing similarity measures. Specifically, the idea of using heat diffusion on a hypersphere to measure similarity has been previously proposed and tested by Lafferty and Lebanon [1], demonstrating promising results based on a heuristic heat kernel obtained from the zeroth order parametrix expansion; however, how well this heuristic kernel agrees with the exact hyperspherical heat kernel remains unknown. This paper presents a higher order parametrix expansion of the heat kernel on a unit hypersphere and discusses several problems associated with this expansion method. We then compare the heuristic kernel with an exact form of the heat kernel expressed in terms of a uniformly and absolutely convergent series in high-dimensional angular momentum eigenmodes. Being a natural measure of similarity between sample points dwelling on a hypersphere, the exact kernel often shows superior performance in kernel SVM classifications applied to text mining, tumor somatic mutation imputation, and stock market analysis.
Anato, F M; Sinzogan, A A C; Offenberg, J; Adandonon, A; Wargui, R B; Deguenon, J M; Ayelo, P M; Vayssières, J-F; Kossou, D K
2017-06-01
Weaver ants, Oecophylla spp., are known to positively affect cashew, Anacardium occidentale L., raw nut yield, but their effects on the kernels have not been reported. We compared nut size and the proportion of marketable kernels between raw nuts collected from trees with and without ants. Raw nuts collected from trees with weaver ants were 2.9% larger than nuts from control trees (i.e., without weaver ants), leading to 14% higher proportion of marketable kernels. On trees with ants, the kernel: raw nut ratio from nuts damaged by formic acid was 4.8% lower compared with nondamaged nuts from the same trees. Weaver ants provided three benefits to cashew production by increasing yields, yielding larger nuts, and by producing greater proportions of marketable kernel mass. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Kernel based orthogonalization for change detection in hyperspectral images
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg
matrix only. In the kernel version the inner products are replaced by inner products between nonlinear mappings into higher dimensional feature space of the original data. Via kernel substitution also known as the kernel trick these inner products between the mappings are in turn replaced by a kernel...... function and all quantities needed in the analysis are expressed in terms of this kernel function. This means that we need not know the nonlinear mappings explicitly. Kernel PCA and MNF analyses handle nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via...... the kernel function and then performing a linear analysis in that space. An example shows the successful application of (kernel PCA and) kernel MNF analysis to change detection in HyMap data covering a small agricultural area near Lake Waging-Taching, Bavaria, in Southern Germany. In the change detection...
Analog forecasting with dynamics-adapted kernels
Zhao, Zhizhen; Giannakis, Dimitrios
2016-09-01
Analog forecasting is a nonparametric technique introduced by Lorenz in 1969 which predicts the evolution of states of a dynamical system (or observables defined on the states) by following the evolution of the sample in a historical record of observations which most closely resembles the current initial data. Here, we introduce a suite of forecasting methods which improve traditional analog forecasting by combining ideas from kernel methods developed in harmonic analysis and machine learning and state-space reconstruction for dynamical systems. A key ingredient of our approach is to replace single-analog forecasting with weighted ensembles of analogs constructed using local similarity kernels. The kernels used here employ a number of dynamics-dependent features designed to improve forecast skill, including Takens’ delay-coordinate maps (to recover information in the initial data lost through partial observations) and a directional dependence on the dynamical vector field generating the data. Mathematically, our approach is closely related to kernel methods for out-of-sample extension of functions, and we discuss alternative strategies based on the Nyström method and the multiscale Laplacian pyramids technique. We illustrate these techniques in applications to forecasting in a low-order deterministic model for atmospheric dynamics with chaotic metastability, and interannual-scale forecasting in the North Pacific sector of a comprehensive climate model. We find that forecasts based on kernel-weighted ensembles have significantly higher skill than the conventional approach following a single analog.
Pattern Classification of Signals Using Fisher Kernels
Directory of Open Access Journals (Sweden)
Yashodhan Athavale
2012-01-01
Full Text Available The intention of this study is to gauge the performance of Fisher kernels for dimension simplification and classification of time-series signals. Our research work has indicated that Fisher kernels have shown substantial improvement in signal classification by enabling clearer pattern visualization in three-dimensional space. In this paper, we will exhibit the performance of Fisher kernels for two domains: financial and biomedical. The financial domain study involves identifying the possibility of collapse or survival of a company trading in the stock market. For assessing the fate of each company, we have collected financial time-series composed of weekly closing stock prices in a common time frame, using Thomson Datastream software. The biomedical domain study involves knee signals collected using the vibration arthrometry technique. This study uses the severity of cartilage degeneration for classifying normal and abnormal knee joints. In both studies, we apply Fisher Kernels incorporated with a Gaussian mixture model (GMM for dimension transformation into feature space, which is created as a three-dimensional plot for visualization and for further classification using support vector machines. From our experiments we observe that Fisher Kernel usage fits really well for both kinds of signals, with low classification error rates.
Directory of Open Access Journals (Sweden)
Xin Zhao
2017-01-01
Full Text Available Fungi infection in maize kernels is a major concern worldwide due to its toxic metabolites such as mycotoxins, thus it is necessary to develop appropriate techniques for early detection of fungi infection in maize kernels. Thirty-six sterilised maize kernels were inoculated each day with Aspergillus parasiticus from one to seven days, and then seven groups (D1, D2, D3, D4, D5, D6, D7 were determined based on the incubated time. Another 36 sterilised kernels without inoculation with fungi were taken as control (DC. Hyperspectral images of all kernels were acquired within spectral range of 921–2529 nm. Background, labels and bad pixels were removed using principal component analysis (PCA and masking. Separability computation for discrimination of fungal contamination levels indicated that the model based on the data of the germ region of individual kernels performed more effectively than on that of the whole kernels. Moreover, samples with a two-day interval were separable. Thus, four groups, DC, D1–2 (the group consisted of D1 and D2, D3–4 (D3 and D4, and D5–7 (D5, D6, and D7, were defined for subsequent classification. Two separate sample sets were prepared to verify the influence on a classification model caused by germ orientation, that is, germ up and the mixture of germ up and down with 1:1. Two smooth preprocessing methods (Savitzky-Golay smoothing, moving average smoothing and three scatter-correction methods (normalization, standard normal variate, and multiple scatter correction were compared, according to the performance of the classification model built by support vector machines (SVM. The best model for kernels with germ up showed the promising results with accuracies of 97.92% and 91.67% for calibration and validation data set, respectively, while accuracies of the best model for samples of the mixed kernels were 95.83% and 84.38%. Moreover, five wavelengths (1145, 1408, 1935, 2103, and 2383 nm were selected as the key
Scattering Theory of Gilbert Damping
Brataas, A.; Tserkovnyak, Y.; Bauer, G.E.W.
2008-01-01
The magnetization dynamics of a single domain ferromagnet in contact with a thermal bath is studied by scattering theory.We recover the Landau-Liftshitz-Gilbert equation and express the effective fields and Gilbert damping tensor in terms of the scattering matrix. Dissipation of magnetic energy
Evaluation of a scattering correction method for high energy tomography
Tisseur, David; Bhatia, Navnina; Estre, Nicolas; Berge, Léonie; Eck, Daniel; Payan, Emmanuel
2018-01-01
One of the main drawbacks of Cone Beam Computed Tomography (CBCT) is the contribution of the scattered photons due to the object and the detector. Scattered photons are deflected from their original path after their interaction with the object. This additional contribution of the scattered photons results in increased measured intensities, since the scattered intensity simply adds to the transmitted intensity. This effect is seen as an overestimation in the measured intensity thus corresponding to an underestimation of absorption. This results in artifacts like cupping, shading, streaks etc. on the reconstructed images. Moreover, the scattered radiation provides a bias for the quantitative tomography reconstruction (for example atomic number and volumic mass measurement with dual-energy technique). The effect can be significant and difficult in the range of MeV energy using large objects due to higher Scatter to Primary Ratio (SPR). Additionally, the incident high energy photons which are scattered by the Compton effect are more forward directed and hence more likely to reach the detector. Moreover, for MeV energy range, the contribution of the photons produced by pair production and Bremsstrahlung process also becomes important. We propose an evaluation of a scattering correction technique based on the method named Scatter Kernel Superposition (SKS). The algorithm uses a continuously thickness-adapted kernels method. The analytical parameterizations of the scatter kernels are derived in terms of material thickness, to form continuously thickness-adapted kernel maps in order to correct the projections. This approach has proved to be efficient in producing better sampling of the kernels with respect to the object thickness. This technique offers applicability over a wide range of imaging conditions and gives users an additional advantage. Moreover, since no extra hardware is required by this approach, it forms a major advantage especially in those cases where
Evaluation of a scattering correction method for high energy tomography
Directory of Open Access Journals (Sweden)
Tisseur David
2018-01-01
Full Text Available One of the main drawbacks of Cone Beam Computed Tomography (CBCT is the contribution of the scattered photons due to the object and the detector. Scattered photons are deflected from their original path after their interaction with the object. This additional contribution of the scattered photons results in increased measured intensities, since the scattered intensity simply adds to the transmitted intensity. This effect is seen as an overestimation in the measured intensity thus corresponding to an underestimation of absorption. This results in artifacts like cupping, shading, streaks etc. on the reconstructed images. Moreover, the scattered radiation provides a bias for the quantitative tomography reconstruction (for example atomic number and volumic mass measurement with dual-energy technique. The effect can be significant and difficult in the range of MeV energy using large objects due to higher Scatter to Primary Ratio (SPR. Additionally, the incident high energy photons which are scattered by the Compton effect are more forward directed and hence more likely to reach the detector. Moreover, for MeV energy range, the contribution of the photons produced by pair production and Bremsstrahlung process also becomes important. We propose an evaluation of a scattering correction technique based on the method named Scatter Kernel Superposition (SKS. The algorithm uses a continuously thickness-adapted kernels method. The analytical parameterizations of the scatter kernels are derived in terms of material thickness, to form continuously thickness-adapted kernel maps in order to correct the projections. This approach has proved to be efficient in producing better sampling of the kernels with respect to the object thickness. This technique offers applicability over a wide range of imaging conditions and gives users an additional advantage. Moreover, since no extra hardware is required by this approach, it forms a major advantage especially in those
The Classification of Diabetes Mellitus Using Kernel k-means
Alamsyah, M.; Nafisah, Z.; Prayitno, E.; Afida, A. M.; Imah, E. M.
2018-01-01
Diabetes Mellitus is a metabolic disorder which is characterized by chronicle hypertensive glucose. Automatics detection of diabetes mellitus is still challenging. This study detected diabetes mellitus by using kernel k-Means algorithm. Kernel k-means is an algorithm which was developed from k-means algorithm. Kernel k-means used kernel learning that is able to handle non linear separable data; where it differs with a common k-means. The performance of kernel k-means in detecting diabetes mellitus is also compared with SOM algorithms. The experiment result shows that kernel k-means has good performance and a way much better than SOM.
OS X and iOS Kernel Programming
Halvorsen, Ole Henry
2011-01-01
OS X and iOS Kernel Programming combines essential operating system and kernel architecture knowledge with a highly practical approach that will help you write effective kernel-level code. You'll learn fundamental concepts such as memory management and thread synchronization, as well as the I/O Kit framework. You'll also learn how to write your own kernel-level extensions, such as device drivers for USB and Thunderbolt devices, including networking, storage and audio drivers. OS X and iOS Kernel Programming provides an incisive and complete introduction to the XNU kernel, which runs iPhones, i
Scatterer Number Density Considerations in Reference Phantom Based Attenuation Estimation
Rubert, Nicholas; Varghese, Tomy
2014-01-01
Attenuation estimation and imaging has the potential to be a valuable tool for tissue characterization, particularly for indicating the extent of thermal ablation therapy in the liver. Often the performance of attenuation estimation algorithms is characterized with numerical simulations or tissue mimicking phantoms containing a high scatterer number density (SND). This ensures an ultrasound signal with a Rayleigh distributed envelope and an SNR approaching 1.91. However, biological tissue often fails to exhibit Rayleigh scattering statistics. For example, across 1,647 ROI's in 5 ex vivo bovine livers we find an envelope SNR of 1.10 ± 0.12 when imaged with the VFX 9L4 linear array transducer at a center frequency of 6.0 MHz on a Siemens S2000 scanner. In this article we examine attenuation estimation in numerical phantoms, TM phantoms with variable SND's, and ex vivo bovine liver prior to and following thermal coagulation. We find that reference phantom based attenuation estimation is robust to small deviations from Rayleigh statistics. However, in tissue with low SND, large deviations in envelope SNR from 1.91 lead to subsequently large increases in attenuation estimation variance. At the same time, low SND is not found to be a significant source of bias in the attenuation estimate. For example, we find the standard deviation of attenuation slope estimates increases from 0.07 dB/cm MHz to 0.25 dB/cm MHz as the envelope SNR decreases from 1.78 to 1.01 when estimating attenuation slope in TM phantoms with a large estimation kernel size (16 mm axially by 15 mm laterally). Meanwhile, the bias in the attenuation slope estimates is found to be negligible (phantom based attenuation estimates in ex vivo bovine liver and thermally coagulated bovine liver. PMID:24726800
Phenolic constituents of shea (Vitellaria paradoxa) kernels.
Maranz, Steven; Wiesman, Zeev; Garti, Nissim
2003-10-08
Analysis of the phenolic constituents of shea (Vitellaria paradoxa) kernels by LC-MS revealed eight catechin compounds-gallic acid, catechin, epicatechin, epicatechin gallate, gallocatechin, epigallocatechin, gallocatechin gallate, and epigallocatechin gallate-as well as quercetin and trans-cinnamic acid. The mean kernel content of the eight catechin compounds was 4000 ppm (0.4% of kernel dry weight), with a 2100-9500 ppm range. Comparison of the profiles of the six major catechins from 40 Vitellaria provenances from 10 African countries showed that the relative proportions of these compounds varied from region to region. Gallic acid was the major phenolic compound, comprising an average of 27% of the measured total phenols and exceeding 70% in some populations. Colorimetric analysis (101 samples) of total polyphenols extracted from shea butter into hexane gave an average of 97 ppm, with the values for different provenances varying between 62 and 135 ppm of total polyphenols.
Kernel Method for Nonlinear Granger Causality
Marinazzo, Daniele; Pellicoro, Mario; Stramaglia, Sebastiano
2008-04-01
Important information on the structure of complex systems can be obtained by measuring to what extent the individual components exchange information among each other. The linear Granger approach, to detect cause-effect relationships between time series, has emerged in recent years as a leading statistical technique to accomplish this task. Here we generalize Granger causality to the nonlinear case using the theory of reproducing kernel Hilbert spaces. Our method performs linear Granger causality in the feature space of suitable kernel functions, assuming arbitrary degree of nonlinearity. We develop a new strategy to cope with the problem of overfitting, based on the geometry of reproducing kernel Hilbert spaces. Applications to coupled chaotic maps and physiological data sets are presented.
The scalar field kernel in cosmological spaces
Energy Technology Data Exchange (ETDEWEB)
Koksma, Jurjen F; Prokopec, Tomislav [Institute for Theoretical Physics (ITP) and Spinoza Institute, Utrecht University, Postbus 80195, 3508 TD Utrecht (Netherlands); Rigopoulos, Gerasimos I [Helsinki Institute of Physics, University of Helsinki, PO Box 64, FIN-00014 (Finland)], E-mail: J.F.Koksma@phys.uu.nl, E-mail: T.Prokopec@phys.uu.nl, E-mail: gerasimos.rigopoulos@helsinki.fi
2008-06-21
We construct the quantum-mechanical evolution operator in the functional Schroedinger picture-the kernel-for a scalar field in spatially homogeneous FLRW spacetimes when the field is (a) free and (b) coupled to a spacetime-dependent source term. The essential element in the construction is the causal propagator, linked to the commutator of two Heisenberg picture scalar fields. We show that the kernels can be expressed solely in terms of the causal propagator and derivatives of the causal propagator. Furthermore, we show that our kernel reveals the standard light cone structure in FLRW spacetimes. We finally apply the result to Minkowski spacetime, to de Sitter spacetime and calculate the forward time evolution of the vacuum in a general FLRW spacetime.
Fast Generation of Sparse Random Kernel Graphs.
Hagberg, Aric; Lemons, Nathan
2015-01-01
The development of kernel-based inhomogeneous random graphs has provided models that are flexible enough to capture many observed characteristics of real networks, and that are also mathematically tractable. We specify a class of inhomogeneous random graph models, called random kernel graphs, that produces sparse graphs with tunable graph properties, and we develop an efficient generation algorithm to sample random instances from this model. As real-world networks are usually large, it is essential that the run-time of generation algorithms scales better than quadratically in the number of vertices n. We show that for many practical kernels our algorithm runs in time at most (n(logn)2). As a practical example we show how to generate samples of power-law degree distribution graphs with tunable assortativity.
Robust C-Loss Kernel Classifiers.
Xu, Guibiao; Hu, Bao-Gang; Principe, Jose C
2018-03-01
The correntropy-induced loss (C-loss) function has the nice property of being robust to outliers. In this paper, we study the C-loss kernel classifier with the Tikhonov regularization term, which is used to avoid overfitting. After using the half-quadratic optimization algorithm, which converges much faster than the gradient optimization algorithm, we find out that the resulting C-loss kernel classifier is equivalent to an iterative weighted least square support vector machine (LS-SVM). This relationship helps explain the robustness of iterative weighted LS-SVM from the correntropy and density estimation perspectives. On the large-scale data sets which have low-rank Gram matrices, we suggest to use incomplete Cholesky decomposition to speed up the training process. Moreover, we use the representer theorem to improve the sparseness of the resulting C-loss kernel classifier. Experimental results confirm that our methods are more robust to outliers than the existing common classifiers.
Energy Technology Data Exchange (ETDEWEB)
Chamli, D.; Bootello, M.A.; Bouali, I.; Jouhri, S.; Boukhchina, S.; Martínez-Force, S.
2017-07-01
A comparative study was conducted to determine the fatty acids, triacylglycerol compositions and thermal properties of Tunisian kernel oils from the Prunus persica varieties, peach and nectarine, grown in two areas of Tunisia, Gabes and Morneg. Qualitatively, the fatty acids composition and triacylglycerol species were identical for all samples. Oleic acid (67.7-75.0%) was the main fatty acid, followed by linoleic (15.7-22.1%) and palmitic (5.6-6.3%) acids. The major triacylglycerol species were triolein, OOO (38.4-50.5%), followed by OOL (18.2-23.2%), POO (8.3-9.7%) and OLL (6.3-10.1%). The thermal profiles were highly influenced by the high content of triolein due to the importance of oleic acid in these oils. Moreover, the fatty acids distribution in TAG external positions was determined as corresponding to an α asymmetry coefficient that was between 0.10 and 0.12, indicating a high asymmetry in the distribution of saturated fatty acids in the position sn-1 and sn-3 in the TAG species of all samples. [Spanish] Se ha realizado un estudio comparativo de aceites tunecinos obtenidos a partir de las semillas de variedades de Prunus persica, melocotón y nectarina, cultivadas en dos zonas de Túnez, Gabes y Morneg. Cualitativamente, la composición de ácidos grasos y de especies de triglicéridos fueron idénticas para todas las muestras. El ácido oleico (67,7-75,0%) fue el ácido graso principal, seguido del linoleico (15,7-22,1%) y el palmítico (5,6-6,3%). Las especies principales de triacilglicéridos fueron la trioleina, OOO (38,4-50,5%), seguida de OOL (18,2-23,2%), POO (8,3-9,7%) y OLL (6,3-10,1%). Los perfiles térmicos fueron muy influidos por el alto contenido de trioleina debido a la importancia del ácido oleico en estos aceites. Por otra parte, se determinó la distribución de ácidos grasos en las posiciones externas de los TAG correspondiendo a un coeficiente de asimetría α entre 0,10 y 0,12, lo que indica una alta asimetría en la distribuci
Kernel principal component analysis for change detection
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg; Morton, J.C.
2008-01-01
Principal component analysis (PCA) is often used to detect change over time in remotely sensed images. A commonly used technique consists of finding the projections along the two eigenvectors for data consisting of two variables which represent the same spectral band covering the same geographical...... region acquired at two different time points. If change over time does not dominate the scene, the projection of the original two bands onto the second eigenvector will show change over time. In this paper a kernel version of PCA is used to carry out the analysis. Unlike ordinary PCA, kernel PCA...
Panel data specifications in nonparametric kernel regression
DEFF Research Database (Denmark)
Czekaj, Tomasz Gerard; Henningsen, Arne
We discuss nonparametric regression models for panel data. A fully nonparametric panel data specification that uses the time variable and the individual identifier as additional (categorical) explanatory variables is considered to be the most suitable. We use this estimator and conventional...... parametric panel data estimators to analyse the production technology of Polish crop farms. The results of our nonparametric kernel regressions generally differ from the estimates of the parametric models but they only slightly depend on the choice of the kernel functions. Based on economic reasoning, we...... found the estimates of the fully nonparametric panel data model to be more reliable....
Fluidization calculation on nuclear fuel kernel coating
International Nuclear Information System (INIS)
Sukarsono; Wardaya; Indra-Suryawan
1996-01-01
The fluidization of nuclear fuel kernel coating was calculated. The bottom of the reactor was in the from of cone on top of the cone there was a cylinder, the diameter of the cylinder for fluidization was 2 cm and at the upper part of the cylinder was 3 cm. Fluidization took place in the cone and the first cylinder. The maximum and the minimum velocity of the gas of varied kernel diameter, the porosity and bed height of varied stream gas velocity were calculated. The calculation was done by basic program
Kernel abortion in maize. II. Distribution of 14C among kernel carboydrates
International Nuclear Information System (INIS)
Hanft, J.M.; Jones, R.J.
1986-01-01
This study was designed to compare the uptake and distribution of 14 C among fructose, glucose, sucrose, and starch in the cob, pedicel, and endosperm tissues of maize (Zea mays L.) kernels induced to abort by high temperature with those that develop normally. Kernels cultured in vitro at 309 and 35 0 C were transferred to [ 14 C]sucrose media 10 days after pollination. Kernels cultured at 35 0 C aborted prior to the onset of linear dry matter accumulation. Significant uptake into the cob, pedicel, and endosperm of radioactivity associated with the soluble and starch fractions of the tissues was detected after 24 hours in culture on atlageled media. After 8 days in culture on [ 14 C]sucrose media, 48 and 40% of the radioactivity associated with the cob carbohydrates was found in the reducing sugars at 30 and 35 0 C, respectively. Of the total carbohydrates, a higher percentage of label was associated with sucrose and lower percentage with fructose and glucose in pedicel tissue of kernels cultured at 35 0 C compared to kernels cultured at 30 0 C. These results indicate that sucrose was not cleaved to fructose and glucose as rapidly during the unloading process in the pedicel of kernels induced to abort by high temperature. Kernels cultured at 35 0 C had a much lower proportion of label associated with endosperm starch (29%) than did kernels cultured at 30 0 C (89%). Kernels cultured at 35 0 C had a correspondingly higher proportion of 14 C in endosperm fructose, glucose, and sucrose
International Nuclear Information System (INIS)
Russell, K.R.; Saxner, M.; Ahnesjoe, A.; Montelius, A.; Grusell, E.; Dahlgren, C.V.
2000-01-01
The implementation of two algorithms for calculating dose distributions for radiation therapy treatment planning of intermediate energy proton beams is described. A pencil kernel algorithm and a depth penetration algorithm have been incorporated into a commercial three-dimensional treatment planning system (Helax-TMS, Helax AB, Sweden) to allow conformal planning techniques using irregularly shaped fields, proton range modulation, range modification and dose calculation for non-coplanar beams. The pencil kernel algorithm is developed from the Fermi-Eyges formalism and Moliere multiple-scattering theory with range straggling corrections applied. The depth penetration algorithm is based on the energy loss in the continuous slowing down approximation with simple correction factors applied to the beam penumbra region and has been implemented for fast, interactive treatment planning. Modelling of the effects of air gaps and range modifying device thickness and position are implicit to both algorithms. Measured and calculated dose values are compared for a therapeutic proton beam in both homogeneous and heterogeneous phantoms of varying complexity. Both algorithms model the beam penumbra as a function of depth in a homogeneous phantom with acceptable accuracy. Results show that the pencil kernel algorithm is required for modelling the dose perturbation effects from scattering in heterogeneous media. (author)
Directory of Open Access Journals (Sweden)
Kunju Shi
2014-01-01
Full Text Available Dimensionality reduction is a crucial task in machinery fault diagnosis. Recently, as a popular dimensional reduction technology, manifold learning has been successfully used in many fields. However, most of these technologies are not suitable for the task, because they are unsupervised in nature and fail to discover the discriminate structure in the data. To overcome these weaknesses, kernel local linear discriminate (KLLD algorithm is proposed. KLLD algorithm is a novel algorithm which combines the advantage of neighborhood preserving projections (NPP, Floyd, maximum margin criterion (MMC, and kernel trick. KLLD has four advantages. First of all, KLLD is a supervised dimension reduction method that can overcome the out-of-sample problems. Secondly, short-circuit problem can be avoided. Thirdly, KLLD algorithm can use between-class scatter matrix and inner-class scatter matrix more efficiently. Lastly, kernel trick is included in KLLD algorithm to find more precise solution. The main feature of the proposed method is that it attempts to both preserve the intrinsic neighborhood geometry of the increased data and exact the discriminate information. Experiments have been performed to evaluate the new method. The results show that KLLD has more benefits than traditional methods.
On methods to increase the security of the Linux kernel
International Nuclear Information System (INIS)
Matvejchikov, I.V.
2014-01-01
Methods to increase the security of the Linux kernel for the implementation of imposed protection tools have been examined. The methods of incorporation into various subsystems of the kernel on the x86 architecture have been described [ru
Comparative Analysis of Kernel Methods for Statistical Shape Learning
National Research Council Canada - National Science Library
Rathi, Yogesh; Dambreville, Samuel; Tannenbaum, Allen
2006-01-01
.... In this work, we perform a comparative analysis of shape learning techniques such as linear PCA, kernel PCA, locally linear embedding and propose a new method, kernelized locally linear embedding...
Energy Technology Data Exchange (ETDEWEB)
Kostorz, G. [Eidgenoessische Technische Hochschule, Angewandte Physik, Zurich (Switzerland)
1996-12-31
While Bragg scattering is characteristic for the average structure of crystals, static local deviations from the average lattice lead to diffuse elastic scattering around and between Bragg peaks. This scattering thus contains information on the occupation of lattice sites by different atomic species and on static local displacements, even in a macroscopically homogeneous crystalline sample. The various diffuse scattering effects, including those around the incident beam (small-angle scattering), are introduced and illustrated by typical results obtained for some Ni alloys. (author) 7 figs., 41 refs.
Symbol recognition with kernel density matching.
Zhang, Wan; Wenyin, Liu; Zhang, Kun
2006-12-01
We propose a novel approach to similarity assessment for graphic symbols. Symbols are represented as 2D kernel densities and their similarity is measured by the Kullback-Leibler divergence. Symbol orientation is found by gradient-based angle searching or independent component analysis. Experimental results show the outstanding performance of this approach in various situations.
Analytic properties of the Virasoro modular kernel
Energy Technology Data Exchange (ETDEWEB)
Nemkov, Nikita [Moscow Institute of Physics and Technology (MIPT), Dolgoprudny (Russian Federation); Institute for Theoretical and Experimental Physics (ITEP), Moscow (Russian Federation); National University of Science and Technology MISIS, The Laboratory of Superconducting metamaterials, Moscow (Russian Federation)
2017-06-15
On the space of generic conformal blocks the modular transformation of the underlying surface is realized as a linear integral transformation. We show that the analytic properties of conformal block implied by Zamolodchikov's formula are shared by the kernel of the modular transformation and illustrate this by explicit computation in the case of the one-point toric conformal block. (orig.)
42 Variability Bugs in the Linux Kernel
DEFF Research Database (Denmark)
Abal, Iago; Brabrand, Claus; Wasowski, Andrzej
2014-01-01
, serving to evaluate tool implementations of feature-sensitive analyses by testing them on real bugs. We present a qualitative study of 42 variability bugs collected from bug-fixing commits to the Linux kernel repository. We analyze each of the bugs, and record the results in a database. In addition, we...
40 Variability Bugs in the Linux Kernel
DEFF Research Database (Denmark)
Abal Rivas, Iago; Brabrand, Claus; Wasowski, Andrzej
2014-01-01
is a requirement for goal-oriented research, serving to evaluate tool implementations of feature-sensitive analyses by testing them on real bugs. We present a qualitative study of 40 variability bugs collected from bug-fixing commits to the Linux kernel repository. We investigate each of the 40 bugs, recording...
Flexible Scheduling in Multimedia Kernels: An Overview
Jansen, P.G.; Scholten, Johan; Laan, Rene; Chow, W.S.
1999-01-01
Current Hard Real-Time (HRT) kernels have their timely behaviour guaranteed on the cost of a rather restrictive use of the available resources. This makes current HRT scheduling techniques inadequate for use in a multimedia environment where we can make a considerable profit by a better and more
Analytic continuation of weighted Bergman kernels
Czech Academy of Sciences Publication Activity Database
Engliš, Miroslav
2010-01-01
Roč. 94, č. 6 (2010), s. 622-650 ISSN 0021-7824 R&D Projects: GA AV ČR IAA100190802 Keywords : Bergman kernel * analytic continuation * Toeplitz operator Subject RIV: BA - General Mathematics Impact factor: 1.450, year: 2010 http://www.sciencedirect.com/science/article/pii/S0021782410000942
A synthesis of empirical plant dispersal kernels
Czech Academy of Sciences Publication Activity Database
Bullock, J. M.; González, L. M.; Tamme, R.; Götzenberger, Lars; White, S. M.; Pärtel, M.; Hooftman, D. A. P.
2017-01-01
Roč. 105, č. 1 (2017), s. 6-19 ISSN 0022-0477 Institutional support: RVO:67985939 Keywords : dispersal kernel * dispersal mode * probability density function Subject RIV: EH - Ecology, Behaviour OBOR OECD: Ecology Impact factor: 5.813, year: 2016
Graph Bundling by Kernel Density Estimation
Hurter, C.; Ersoy, O.; Telea, A.
We present a fast and simple method to compute bundled layouts of general graphs. For this, we first transform a given graph drawing into a density map using kernel density estimation. Next, we apply an image sharpening technique which progressively merges local height maxima by moving the convolved
Evaluation of different combinations of palm kernel cake - and cotton ...
African Journals Online (AJOL)
... sole palm kernel cake based diets than those fed combinations of palm kernel cake and cottonseed cake. It is concluded that palm kernel cake alone (without any combination with cottonseed cake) is adequate as protein source in compounding protein supplements for West African Dwarf goats for profitable performance.
Enhanced gluten properties in soft kernel durum wheat
Soft kernel durum wheat is a relatively recent development (Morris et al. 2011 Crop Sci. 51:114). The soft kernel trait exerts profound effects on kernel texture, flour milling including break flour yield, milling energy, and starch damage, and dough water absorption (DWA). With the caveat of reduce...
determination of bio-energy potential of palm kernel shell
African Journals Online (AJOL)
88888888
2012-11-03
Nov 3, 2012 ... Palm Kernel Shell (PKS) is an economically and environmentally sustainable raw material for ... oil and palm kernel oil production, palm oil fibre, effluent, kernel shell and empty fruit bunch are re- garded as wastes. According to Luangkiattikhun et ... use as concrete reinforcement in construction indus-.
Dense Medium Machine Processing Method for Palm Kernel/ Shell ...
African Journals Online (AJOL)
ADOWIE PERE
ABSTRACT: A machine processing method for the separation of cracked palm kernel from the shells using ... Cracked palm kernel is a mixture of kernels, broken shells, dusts and other impurities. In order to produce ... Received 31 September 2017, received in revised form 18 October 2017, accepted 29 November 2017.
An Investigation of Kernel Data Attacks and Countermeasures
2017-02-14
demonstrate that attackers can stealthily subvert various kernel security mechanism s and develop a new keylogger , which is more stealthy than existing... keyloggers .. By classifying kernel data into different categories and handling them separately, we propose a defense mechanism and evaluate its...a computer system. 15. SUBJECT TERMS Kernel Data, Rootkit, Keylogger , Countermeasure 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF a. REPORT b
Software correction of scatter coincidence in positron CT
International Nuclear Information System (INIS)
Endo, M.; Iinuma, T.A.
1984-01-01
This paper describes a software correction of scatter coincidence in positron CT which is based on an estimation of scatter projections from true projections by an integral transform. Kernels for the integral transform are projected distributions of scatter coincidences for a line source at different positions in a water phantom and are calculated by Klein-Nishina's formula. True projections of any composite object can be determined from measured projections by iterative applications of the integral transform. The correction method was tested in computer simulations and phantom experiments with Positologica. The results showed that effects of scatter coincidence are not negligible in the quantitation of images, but the correction reduces them significantly. (orig.)
Dielectric properties of Zea mays kernels - studies for microwave power processing applications
Energy Technology Data Exchange (ETDEWEB)
Surducan, Emanoil; Neamtu, Camelia; Surducan, Vasile, E-mail: emanoil.surducan@itim-cj.r [National Institute for Research and Development of Isotopic and Molecular Technologies, 65-103 Donath, 400293 Cluj-Napoca (Romania)
2009-08-01
Microwaves absorption in biological samples can be predicted by their specific dielectrical properties. In this paper, the dielectric properties ({epsilon}' and {epsilon}'') of corn (Zea mays) kernels in the 500 MHz - 20 GHz frequencies range are presented. A short analysis of the microwaves absorption process is also presented, in correlation with the specific thermal properties of the samples, measured by simultaneous TGA-DSC method.
Wheat kernel dimensions: how do they contribute to kernel weight at ...
Indian Academy of Sciences (India)
2011-12-02
Dec 2, 2011 ... Wheat kernel dimensions: how do they contribute to kernel weight at an individual QTL level? FA CUI1, 2†, ANMING DING1†, JUN LI1, 3†, CHUNHUA ZHAO1†, XINGFENG LI1, DESHUN FENG1,. XIUQIN WANG4, LIN WANG1, 5, JURONG GAO1 and HONGGANG WANG1∗. 1State Key Laboratory of Crop ...
Neutron scattering. Experiment manuals
Energy Technology Data Exchange (ETDEWEB)
Brueckel, Thomas; Heger, Gernot; Richter, Dieter; Roth, Georg; Zorn, Reiner (eds.)
2010-07-01
The following topics are dealt with: The thermal triple axis spectrometer PUMA, the high-resolution powder diffractometer SPODI, the hot single-crystal diffractometer HEiDi for structure analysis with neutrons, the backscattering spectrometer SPHERES, neutron polarization analysis with tht time-of-flight spectrometer DNS, the neutron spin-echo spectrometer J-NSE, small-angle neutron scattering with the KWS-1 and KWS-2 diffractometers, the very-small-angle neutron scattering diffractrometer with focusing mirror KWS-3, the resonance spin-echo spectrometer RESEDA, the reflectometer TREFF, the time-of-flight spectrometer TOFTOF. (HSI)
Neutron scattering. Experiment manuals
International Nuclear Information System (INIS)
Brueckel, Thomas; Heger, Gernot; Richter, Dieter; Roth, Georg; Zorn, Reiner
2014-01-01
The following topics are dealt with: The thermal triple-axis spectrometer PUMA, the high-resolution powder diffractometer SPODI, the hot-single-crystal diffractometer HEiDi, the three-axis spectrometer PANDA, the backscattering spectrometer SPHERES, the DNS neutron-polarization analysis, the neutron spin-echo spectrometer J-NSE, small-angle neutron scattering at KWS-1 and KWS-2, a very-small-angle neutron scattering diffractometer with focusing mirror, the reflectometer TREFF, the time-of-flight spectrometer TOFTOF. (HSI)
Neutron scattering. Experiment manuals
International Nuclear Information System (INIS)
Brueckel, Thomas; Heger, Gernot; Richter, Dieter; Roth, Georg; Zorn, Reiner
2010-01-01
The following topics are dealt with: The thermal triple axis spectrometer PUMA, the high-resolution powder diffractometer SPODI, the hot single-crystal diffractometer HEiDi for structure analysis with neutrons, the backscattering spectrometer SPHERES, neutron polarization analysis with tht time-of-flight spectrometer DNS, the neutron spin-echo spectrometer J-NSE, small-angle neutron scattering with the KWS-1 and KWS-2 diffractometers, the very-small-angle neutron scattering diffractrometer with focusing mirror KWS-3, the resonance spin-echo spectrometer RESEDA, the reflectometer TREFF, the time-of-flight spectrometer TOFTOF. (HSI)
Neutron scattering. Experiment manuals
Energy Technology Data Exchange (ETDEWEB)
Brueckel, Thomas; Heger, Gernot; Richter, Dieter; Roth, Georg; Zorn, Reiner (eds.)
2014-07-01
The following topics are dealt with: The thermal triple-axis spectrometer PUMA, the high-resolution powder diffractometer SPODI, the hot-single-crystal diffractometer HEiDi, the three-axis spectrometer PANDA, the backscattering spectrometer SPHERES, the DNS neutron-polarization analysis, the neutron spin-echo spectrometer J-NSE, small-angle neutron scattering at KWS-1 and KWS-2, a very-small-angle neutron scattering diffractometer with focusing mirror, the reflectometer TREFF, the time-of-flight spectrometer TOFTOF. (HSI)
Windows Vista Kernel-Mode: Functions, Security Enhancements and Flaws
Directory of Open Access Journals (Sweden)
Mohammed D. ABDULMALIK
2008-06-01
Full Text Available Microsoft has made substantial enhancements to the kernel of the Microsoft Windows Vista operating system. Kernel improvements are significant because the kernel provides low-level operating system functions, including thread scheduling, interrupt and exception dispatching, multiprocessor synchronization, and a set of routines and basic objects.This paper describes some of the kernel security enhancements for 64-bit edition of Windows Vista. We also point out some weakness areas (flaws that can be attacked by malicious leading to compromising the kernel.
Zero energy scattering calculation in Euclidean space
International Nuclear Information System (INIS)
Carbonell, J.; Karmanov, V.A.
2016-01-01
We show that the Bethe–Salpeter equation for the scattering amplitude in the limit of zero incident energy can be transformed into a purely Euclidean form, as it is the case for the bound states. The decoupling between Euclidean and Minkowski amplitudes is only possible for zero energy scattering observables and allows determining the scattering length from the Euclidean Bethe–Salpeter amplitude. Such a possibility strongly simplifies the numerical solution of the Bethe–Salpeter equation and suggests an alternative way to compute the scattering length in Lattice Euclidean calculations without using the Luscher formalism. The derivations contained in this work were performed for scalar particles and one-boson exchange kernel. They can be generalized to the fermion case and more involved interactions.
Zero energy scattering calculation in Euclidean space
Energy Technology Data Exchange (ETDEWEB)
Carbonell, J. [Institut de Physique Nucléaire, Université Paris-Sud, IN2P3-CNRS, 91406 Orsay Cedex (France); Karmanov, V.A., E-mail: karmanov@sci.lebedev.ru [Lebedev Physical Institute, Leninsky Prospekt 53, 119991 Moscow (Russian Federation)
2016-03-10
We show that the Bethe–Salpeter equation for the scattering amplitude in the limit of zero incident energy can be transformed into a purely Euclidean form, as it is the case for the bound states. The decoupling between Euclidean and Minkowski amplitudes is only possible for zero energy scattering observables and allows determining the scattering length from the Euclidean Bethe–Salpeter amplitude. Such a possibility strongly simplifies the numerical solution of the Bethe–Salpeter equation and suggests an alternative way to compute the scattering length in Lattice Euclidean calculations without using the Luscher formalism. The derivations contained in this work were performed for scalar particles and one-boson exchange kernel. They can be generalized to the fermion case and more involved interactions.
Kernel Methods for Machine Learning with Life Science Applications
DEFF Research Database (Denmark)
Abrahamsen, Trine Julie
Kernel methods refer to a family of widely used nonlinear algorithms for machine learning tasks like classification, regression, and feature extraction. By exploiting the so-called kernel trick straightforward extensions of classical linear algorithms are enabled as long as the data only appear...... models to kernel learning, and means for restoring the generalizability in both kernel Principal Component Analysis and the Support Vector Machine are proposed. Viability is proved on a wide range of benchmark machine learning data sets....... as innerproducts in the model formulation. This dissertation presents research on improving the performance of standard kernel methods like kernel Principal Component Analysis and the Support Vector Machine. Moreover, the goal of the thesis has been two-fold. The first part focuses on the use of kernel Principal...
International Nuclear Information System (INIS)
Ferreira, Ricardo Alberto Neto; Andrade, Antonio Santos; Miranda, Odair; Grossi, Pablo Andrade; Camarano, Denise das Merces; Migliorini, Fabricio Lima; Silva, Egonn Hendrigo Carvalho; Andrade, Roberto Marcio de
2009-01-01
Under compaction pressures ranging from 300 MPa up to 500 MPa, fuel pellets of uranium dioxide were manufactured by the pressing of kernels. These were produced by the sol-gel process developed in Germany by NUKEM for using in high temperature gas cooled reactors, which were absorbed, transferred and implanted at CDTN-Centro de Desenvolvimento da Tecnologia Nuclear. The sintering was performed at 1700 deg C for two hours under argon with 4% hydrogen atmosphere, resulting sintered densities ranging from 9.33 g·cm -3 up to 10.08 g·cm -3 , determined by the xylol penetration-immersion method. Using the flash laser method, the thermophysical properties of the pellets were determined and thermal diffusivity ranging from 2.58 x 10 -6 m 2 ·s -1 up to 2.78 x 10 -6 m 2 ·s -1 and thermal conductivity from 6.22 m -1 ·K -1 up to 7.24 W·m -1 ·K -1 , corresponding to a decreasing of the porosity from 14.88% to 8.05%. The methodology is described and the influence of the compaction pressure on the pellet properties is also analyzed. The thermal conductivity results of this study will be very valuable to a project in development at CDTN, in which uranium dioxide pellets will be produced by the pressing of kernels, with beryllium oxide filling the voids between the kernels in order to enhance the thermal conductivity of the fuel and consequently, the thermal performance of the fuel rod, as required in extended burnup conditions. They will be used as reference to compare and calculate the favorable increase of the thermal conductivity, caused by the addition of beryllium oxide. (author)
International Nuclear Information System (INIS)
Rosa, Cinara Ewerling da; Knackfuss, Rosenei Felippe
2013-01-01
In this work is presented a series of numerical results and graphical comparisons of the physical quantities of interest such as: the velocity profile and the heat on profile. This formulation is developed for the problem of Thermal Creep, where the gas is moving between two parallel plates with different chemical constitutions (heterogeneous plates) due to a temperature gradient. The flow of a rarefied gas, is investigated with special attention to the gas-surface interaction, modeled by the Cercignani-Lampis kernel, that unlike Maxwell's scattering kernel, is defined in terms of two accommodation coefficients (normal and tangential) to represent the physical properties of the gas. The kinetic theory for rarefied gas dynamics, derived from the linearized Boltzmann equation, is developed in an unified approach, to the BGK model, S model, GJ model and MRS model. In the search for solutions to solve the problem of Thermal Creep with kernel of the Cercignani-Lampis, we used a analytical version of the discrete ordinates method (ADO) based on an arbitrary quadrature scheme, under which is determined a problem of eigenvalues and their respective separation constants. Numerical results are developed by the computer program FORTRAN. (author)
International Nuclear Information System (INIS)
Hategan, Cornel; Comisel, Horia; Ionescu, Remus A.
2004-01-01
The quasiresonant scattering consists from a single channel resonance coupled by direct interaction transitions to some competing reaction channels. A description of quasiresonant Scattering, in terms of generalized reduced K-, R- and S- Matrix, is developed in this work. The quasiresonance's decay width is, due to channels coupling, smaller than the width of the ancestral single channel resonance (resonance's direct compression). (author)
Implementation of kernels on the Maestro processor
Suh, Jinwoo; Kang, D. I. D.; Crago, S. P.
Currently, most microprocessors use multiple cores to increase performance while limiting power usage. Some processors use not just a few cores, but tens of cores or even 100 cores. One such many-core microprocessor is the Maestro processor, which is based on Tilera's TILE64 processor. The Maestro chip is a 49-core, general-purpose, radiation-hardened processor designed for space applications. The Maestro processor, unlike the TILE64, has a floating point unit (FPU) in each core for improved floating point performance. The Maestro processor runs at 342 MHz clock frequency. On the Maestro processor, we implemented several widely used kernels: matrix multiplication, vector add, FIR filter, and FFT. We measured and analyzed the performance of these kernels. The achieved performance was up to 5.7 GFLOPS, and the speedup compared to single tile was up to 49 using 49 tiles.
Kernel-based tests for joint independence
DEFF Research Database (Denmark)
Pfister, Niklas; Bühlmann, Peter; Schölkopf, Bernhard
2018-01-01
if the $d$ variables are jointly independent, as long as the kernel is characteristic. Based on an empirical estimate of dHSIC, we define three different non-parametric hypothesis tests: a permutation test, a bootstrap test and a test based on a Gamma approximation. We prove that the permutation test......We investigate the problem of testing whether $d$ random variables, which may or may not be continuous, are jointly (or mutually) independent. Our method builds on ideas of the two variable Hilbert-Schmidt independence criterion (HSIC) but allows for an arbitrary number of variables. We embed...... the $d$-dimensional joint distribution and the product of the marginals into a reproducing kernel Hilbert space and define the $d$-variable Hilbert-Schmidt independence criterion (dHSIC) as the squared distance between the embeddings. In the population case, the value of dHSIC is zero if and only...
Wilson Dslash Kernel From Lattice QCD Optimization
Energy Technology Data Exchange (ETDEWEB)
Joo, Balint [Jefferson Lab, Newport News, VA; Smelyanskiy, Mikhail [Parallel Computing Lab, Intel Corporation, California, USA; Kalamkar, Dhiraj D. [Parallel Computing Lab, Intel Corporation, India; Vaidyanathan, Karthikeyan [Parallel Computing Lab, Intel Corporation, India
2015-07-01
Lattice Quantum Chromodynamics (LQCD) is a numerical technique used for calculations in Theoretical Nuclear and High Energy Physics. LQCD is traditionally one of the first applications ported to many new high performance computing architectures and indeed LQCD practitioners have been known to design and build custom LQCD computers. Lattice QCD kernels are frequently used as benchmarks (e.g. 168.wupwise in the SPEC suite) and are generally well understood, and as such are ideal to illustrate several optimization techniques. In this chapter we will detail our work in optimizing the Wilson-Dslash kernels for Intel Xeon Phi, however, as we will show the technique gives excellent performance on regular Xeon Architecture as well.
International Nuclear Information System (INIS)
Ruehrnschopf and, Ernst-Peter; Klingenbeck, Klaus
2011-01-01
The main components of scatter correction procedures are scatter estimation and a scatter compensation algorithm. This paper completes a previous paper where a general framework for scatter compensation was presented under the prerequisite that a scatter estimation method is already available. In the current paper, the authors give a systematic review of the variety of scatter estimation approaches. Scatter estimation methods are based on measurements, mathematical-physical models, or combinations of both. For completeness they present an overview of measurement-based methods, but the main topic is the theoretically more demanding models, as analytical, Monte-Carlo, and hybrid models. Further classifications are 3D image-based and 2D projection-based approaches. The authors present a system-theoretic framework, which allows to proceed top-down from a general 3D formulation, by successive approximations, to efficient 2D approaches. A widely useful method is the beam-scatter-kernel superposition approach. Together with the review of standard methods, the authors discuss their limitations and how to take into account the issues of object dependency, spatial variance, deformation of scatter kernels, external and internal absorbers. Open questions for further investigations are indicated. Finally, the authors refer on some special issues and applications, such as bow-tie filter, offset detector, truncated data, and dual-source CT.
A Kernel for Protein Secondary Structure Prediction
Guermeur , Yann; Lifchitz , Alain; Vert , Régis
2004-01-01
http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=10338&mode=toc; International audience; Multi-class support vector machines have already proved efficient in protein secondary structure prediction as ensemble methods, to combine the outputs of sets of classifiers based on different principles. In this chapter, their implementation as basic prediction methods, processing the primary structure or the profile of multiple alignments, is investigated. A kernel devoted to the task is in...
Searching and Indexing Genomic Databases via Kernelization
Directory of Open Access Journals (Sweden)
Travis eGagie
2015-02-01
Full Text Available The rapid advance of DNA sequencing technologies has yielded databases of thousands of genomes. To search and index these databases effectively, it is important that we take advantage of the similarity between those genomes. Several authors have recently suggested searching or indexing only one reference genome and the parts of the other genomes where they differ. In this paper we survey the twenty-year history of this idea and discuss its relation to kernelization in parameterized complexity.
Kernel based subspace projection of hyperspectral images
DEFF Research Database (Denmark)
Larsen, Rasmus; Nielsen, Allan Aasbjerg; Arngren, Morten
In hyperspectral image analysis an exploratory approach to analyse the image data is to conduct subspace projections. As linear projections often fail to capture the underlying structure of the data, we present kernel based subspace projections of PCA and Maximum Autocorrelation Factors (MAF......). The MAF projection exploits the fact that interesting phenomena in images typically exhibit spatial autocorrelation. The analysis is based on nearinfrared hyperspectral images of maize grains demonstrating the superiority of the kernelbased MAF method....
Multiple Kernel Learning with Data Augmentation
2016-11-22
et al., 2010; Sun et al., 2010). Particularly, Sun et al. (2010) developed an efficient method based on sequential minimal optimization (SMO). The...http://www.robots.ox.ac.uk/~vgg/data/ flowers /17/ 58 Multiple Kernel Learning with Data Augmentation Algorithm 2 MKL with Data Augmentation approach for...Maria-Elena Nilsback and Andrew Zisserman. A visual vocabulary for flower classification. In Com- puter Vision and Pattern Recognition, 2006 IEEE Computer
Multiple Kernel Spectral Regression for Dimensionality Reduction
Liu, Bing; Xia, Shixiong; Zhou, Yong
2013-01-01
Traditional manifold learning algorithms, such as locally linear embedding, Isomap, and Laplacian eigenmap, only provide the embedding results of the training samples. To solve the out-of-sample extension problem, spectral regression (SR) solves the problem of learning an embedding function by establishing a regression framework, which can avoid eigen-decomposition of dense matrices. Motivated by the effectiveness of SR, we incorporate multiple kernel learning (MKL) into SR for dimensionality...
Searching and Indexing Genomic Databases via Kernelization.
Gagie, Travis; Puglisi, Simon J
2015-01-01
The rapid advance of DNA sequencing technologies has yielded databases of thousands of genomes. To search and index these databases effectively, it is important that we take advantage of the similarity between those genomes. Several authors have recently suggested searching or indexing only one reference genome and the parts of the other genomes where they differ. In this paper, we survey the 20-year history of this idea and discuss its relation to kernelization in parameterized complexity.
Scalar contribution to the BFKL kernel
International Nuclear Information System (INIS)
Gerasimov, R. E.; Fadin, V. S.
2010-01-01
The contribution of scalar particles to the kernel of the Balitsky-Fadin-Kuraev-Lipatov (BFKL) equation is calculated. A great cancellation between the virtual and real parts of this contribution, analogous to the cancellation in the quark contribution in QCD, is observed. The reason of this cancellation is discovered. This reason has a common nature for particles with any spin. Understanding of this reason permits to obtain the total contribution without the complicated calculations, which are necessary for finding separate pieces.
Weighted Bergman Kernels for Logarithmic Weights
Czech Academy of Sciences Publication Activity Database
Engliš, Miroslav
2010-01-01
Roč. 6, č. 3 (2010), s. 781-813 ISSN 1558-8599 R&D Projects: GA AV ČR IAA100190802 Keywords : Bergman kernel * Toeplitz operator * logarithmic weight * pseudodifferential operator Subject RIV: BA - General Mathematics Impact factor: 0.462, year: 2010 http://www.intlpress.com/site/pub/pages/journals/items/pamq/content/vols/0006/0003/a008/
Heat kernels and zeta functions on fractals
International Nuclear Information System (INIS)
Dunne, Gerald V
2012-01-01
On fractals, spectral functions such as heat kernels and zeta functions exhibit novel features, very different from their behaviour on regular smooth manifolds, and these can have important physical consequences for both classical and quantum physics in systems having fractal properties. This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical in honour of Stuart Dowker's 75th birthday devoted to ‘Applications of zeta functions and other spectral functions in mathematics and physics’. (paper)
International Nuclear Information System (INIS)
Moeller, K.
1977-03-01
A system of three spinless particles interacting via separable Yamaguchi potential is considered. For the Faddeev equation kernel of this system a method is proposed for calculating the eigenvalues on the nonphysical sheet of the three-particle cms-energy. The method is based on an extension to complex energies of the known contour deformation technique applied earlier to solve the three-particle scattering problem. The method proposed can be used to investigate resonance phenomena in three-particle systems. (author)
Signaling in Early Maize Kernel Development.
Doll, Nicolas M; Depège-Fargeix, Nathalie; Rogowsky, Peter M; Widiez, Thomas
2017-03-06
Developing the next plant generation within the seed requires the coordination of complex programs driving pattern formation, growth, and differentiation of the three main seed compartments: the embryo (future plant), the endosperm (storage compartment), representing the two filial tissues, and the surrounding maternal tissues. This review focuses on the signaling pathways and molecular players involved in early maize kernel development. In the 2 weeks following pollination, functional tissues are shaped from single cells, readying the kernel for filling with storage compounds. Although the overall picture of the signaling pathways regulating embryo and endosperm development remains fragmentary, several types of molecular actors, such as hormones, sugars, or peptides, have been shown to be involved in particular aspects of these developmental processes. These molecular actors are likely to be components of signaling pathways that lead to transcriptional programming mediated by transcriptional factors. Through the integrated action of these components, multiple types of information received by cells or tissues lead to the correct differentiation and patterning of kernel compartments. In this review, recent advances regarding the four types of molecular actors (hormones, sugars, peptides/receptors, and transcription factors) involved in early maize development are presented. Copyright © 2017 The Author. Published by Elsevier Inc. All rights reserved.
Multiple kernel learning for dimensionality reduction.
Lin, Yen-Yu; Liu, Tyng-Luh; Fuh, Chiou-Shann
2011-06-01
In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. The resulting data representations are typically high-dimensional and assume diverse forms. Hence, finding a way of transforming them into a unified space of lower dimension generally facilitates the underlying tasks such as object recognition or clustering. To this end, the proposed approach (termed MKL-DR) generalizes the framework of multiple kernel learning for dimensionality reduction, and distinguishes itself with the following three main contributions: first, our method provides the convenience of using diverse image descriptors to describe useful characteristics of various aspects about the underlying data. Second, it extends a broad set of existing dimensionality reduction techniques to consider multiple kernel learning, and consequently improves their effectiveness. Third, by focusing on the techniques pertaining to dimensionality reduction, the formulation introduces a new class of applications with the multiple kernel learning framework to address not only the supervised learning problems but also the unsupervised and semi-supervised ones.
Exploiting graph kernels for high performance biomedical relation extraction.
Panyam, Nagesh C; Verspoor, Karin; Cohn, Trevor; Ramamohanarao, Kotagiri
2018-01-30
Relation extraction from biomedical publications is an important task in the area of semantic mining of text. Kernel methods for supervised relation extraction are often preferred over manual feature engineering methods, when classifying highly ordered structures such as trees and graphs obtained from syntactic parsing of a sentence. Tree kernels such as the Subset Tree Kernel and Partial Tree Kernel have been shown to be effective for classifying constituency parse trees and basic dependency parse graphs of a sentence. Graph kernels such as the All Path Graph kernel (APG) and Approximate Subgraph Matching (ASM) kernel have been shown to be suitable for classifying general graphs with cycles, such as the enhanced dependency parse graph of a sentence. In this work, we present a high performance Chemical-Induced Disease (CID) relation extraction system. We present a comparative study of kernel methods for the CID task and also extend our study to the Protein-Protein Interaction (PPI) extraction task, an important biomedical relation extraction task. We discuss novel modifications to the ASM kernel to boost its performance and a method to apply graph kernels for extracting relations expressed in multiple sentences. Our system for CID relation extraction attains an F-score of 60%, without using external knowledge sources or task specific heuristic or rules. In comparison, the state of the art Chemical-Disease Relation Extraction system achieves an F-score of 56% using an ensemble of multiple machine learning methods, which is then boosted to 61% with a rule based system employing task specific post processing rules. For the CID task, graph kernels outperform tree kernels substantially, and the best performance is obtained with APG kernel that attains an F-score of 60%, followed by the ASM kernel at 57%. The performance difference between the ASM and APG kernels for CID sentence level relation extraction is not significant. In our evaluation of ASM for the PPI task, ASM
A new method by steering kernel-based Richardson–Lucy algorithm for neutron imaging restoration
International Nuclear Information System (INIS)
Qiao, Shuang; Wang, Qiao; Sun, Jia-ning; Huang, Ji-peng
2014-01-01
Motivated by industrial applications, neutron radiography has become a powerful tool for non-destructive investigation techniques. However, resulted from a combined effect of neutron flux, collimated beam, limited spatial resolution of detector and scattering, etc., the images made with neutrons are degraded severely by blur and noise. For dealing with it, by integrating steering kernel regression into Richardson–Lucy approach, we present a novel restoration method in this paper, which is capable of suppressing noise while restoring details of the blurred imaging result efficiently. Experimental results show that compared with the other methods, the proposed method can improve the restoration quality both visually and quantitatively
A new method by steering kernel-based Richardson-Lucy algorithm for neutron imaging restoration
Qiao, Shuang; Wang, Qiao; Sun, Jia-ning; Huang, Ji-peng
2014-01-01
Motivated by industrial applications, neutron radiography has become a powerful tool for non-destructive investigation techniques. However, resulted from a combined effect of neutron flux, collimated beam, limited spatial resolution of detector and scattering, etc., the images made with neutrons are degraded severely by blur and noise. For dealing with it, by integrating steering kernel regression into Richardson-Lucy approach, we present a novel restoration method in this paper, which is capable of suppressing noise while restoring details of the blurred imaging result efficiently. Experimental results show that compared with the other methods, the proposed method can improve the restoration quality both visually and quantitatively.
Identification of Fusarium damaged wheat kernels using image analysis
Directory of Open Access Journals (Sweden)
Ondřej Jirsa
2011-01-01
Full Text Available Visual evaluation of kernels damaged by Fusarium spp. pathogens is labour intensive and due to a subjective approach, it can lead to inconsistencies. Digital imaging technology combined with appropriate statistical methods can provide much faster and more accurate evaluation of the visually scabby kernels proportion. The aim of the present study was to develop a discrimination model to identify wheat kernels infected by Fusarium spp. using digital image analysis and statistical methods. Winter wheat kernels from field experiments were evaluated visually as healthy or damaged. Deoxynivalenol (DON content was determined in individual kernels using an ELISA method. Images of individual kernels were produced using a digital camera on dark background. Colour and shape descriptors were obtained by image analysis from the area representing the kernel. Healthy and damaged kernels differed significantly in DON content and kernel weight. Various combinations of individual shape and colour descriptors were examined during the development of the model using linear discriminant analysis. In addition to basic descriptors of the RGB colour model (red, green, blue, very good classification was also obtained using hue from the HSL colour model (hue, saturation, luminance. The accuracy of classification using the developed discrimination model based on RGBH descriptors was 85 %. The shape descriptors themselves were not specific enough to distinguish individual kernels.
[Study of genetic models of maize kernel traits].
Zhang, H W; Kong, F L
2000-01-01
Two sets of NCII mating design including 21 different maize inbreds were used to study the genetic models of five maize kernel traits--kernel length, width, ratio of kernel length and width, kernel thickness and weight per 100 kernels. Ten generations including P1, P2, F1, F2, B1, B2 and their reciprocal crosses RF1, RF2, RB1, RB2 were obtained. Three years' data were obtained and analyzed using mainly two methods: (1) precision identification for single cross and (2) mixed liner model MINQUE approach for diallel design. Method 1 showed that kernel traits were primarily controlled by maternal dominance, endosperm additive and dominance effect (maternal dominance > endosperm additive > endosperm dominance). Cytoplasmic effect was detected in one of the two crosses studied. Method 2 revealed that in the total variance of kernel traits, maternal genotypic effect contributed more than 60%, endosperm genotypic effect contributed less than 40%. Cytoplasmic effect only existed in kernel length and 100 kernel weight, with the range of 10% to 30%. The results indicated that kernel genetic performance was quite largely controlled by maternal genotypic effect.
Directory of Open Access Journals (Sweden)
Vlad Mureşan
2015-11-01
Full Text Available Sunflower is the basic oil-crop in Central and Eastern Europe. As sunflower seeds are mainly used for oil production, the most of the kernels available on the market show high oil content (>55%. Consequently, when sunflower kernel paste (tahini is used in different food products, oil exudation occurs.The aim of current work was to use entirely the sunflower seeds by partially defatting and obtaining different fat content sunflower pastes with multiple food applications, while using the husks for developing an ecological package. Sunflower kernels were industrially roasted in a continuous roasting drum. Raw and roasted kernels were pressed at pilot plant scale by using a laboratory expeller. Partially defatted sunflower paste was obtained from the press cakes by employing a ball mill. Different fat content tahini samples were obtained by adding the required amount of oil to the partially defatted paste. Tahini samples fat content ranged from 45 to 60%. Tahini and halva were chosen as a study model. Decreasing tahini oil content increased its colloidal stability during storage, a similar trend being noticed when halva samples were stored. Moreover, halva texture analysis and sensory characteristics were assessed for selecting the optimum tahini oil content and thermal treatment. Various sunflower kernel food applications were proposed by obtaining the related prototypes at pilot plant scale: roasted sunflower kernel biscuits, sunflower spreadable cream filled biscuits, hummus, sunflower paste coated in chocolate, sunflower kernel chikki and bars, as well as an innovative ecological package based on the resulting sunflower husks and a starch adhesive.
International Nuclear Information System (INIS)
Sitenko, A.
1991-01-01
This book emerged out of graduate lectures given by the author at the University of Kiev and is intended as a graduate text. The fundamentals of non-relativistic quantum scattering theory are covered, including some topics, such as the phase-function formalism, separable potentials, and inverse scattering, which are not always coverded in textbooks on scattering theory. Criticisms of the text are minor, but the reviewer feels an inadequate index is provided and the citing of references in the Russian language is a hindrance in a graduate text
Kernel based subspace projection of near infrared hyperspectral images of maize kernels
DEFF Research Database (Denmark)
Larsen, Rasmus; Arngren, Morten; Hansen, Per Waaben
2009-01-01
In this paper we present an exploratory analysis of hyper- spectral 900-1700 nm images of maize kernels. The imaging device is a line scanning hyper spectral camera using a broadband NIR illumi- nation. In order to explore the hyperspectral data we compare a series of subspace projection methods...... including principal component analysis and maximum autocorrelation factor analysis. The latter utilizes the fact that interesting phenomena in images exhibit spatial autocorrelation. However, linear projections often fail to grasp the underlying variability on the data. Therefore we propose to use so......- tor transform outperform the linear methods as well as kernel principal components in producing interesting projections of the data....
Energy Technology Data Exchange (ETDEWEB)
Dimits, A M; Wang, C; Caflisch, R; Cohen, B I; Huang, Y
2008-08-06
We investigate the accuracy of and assumptions underlying the numerical binary Monte-Carlo collision operator due to Nanbu [K. Nanbu, Phys. Rev. E 55 (1997)]. The numerical experiments that resulted in the parameterization of the collision kernel used in Nanbu's operator are argued to be an approximate realization of the Coulomb-Lorentz pitch-angle scattering process, for which an analytical solution for the collision kernel is available. It is demonstrated empirically that Nanbu's collision operator quite accurately recovers the effects of Coulomb-Lorentz pitch-angle collisions, or processes that approximate these (such interspecies Coulomb collisions with very small mass ratio) even for very large values of the collisional time step. An investigation of the analytical solution shows that Nanbu's parameterized kernel is highly accurate for small values of the normalized collision time step, but loses some of its accuracy for larger values of the time step. Careful numerical and analytical investigations are presented, which show that the time dependence of the relaxation of a temperature anisotropy by Coulomb-Lorentz collisions has a richer structure than previously thought, and is not accurately represented by an exponential decay with a single decay rate. Finally, a practical collision algorithm is proposed that for small-mass-ratio interspecies Coulomb collisions improves on the accuracy of Nanbu's algorithm.
Classification of maize kernels using NIR hyperspectral imaging
DEFF Research Database (Denmark)
Williams, Paul; Kucheryavskiy, Sergey V.
2016-01-01
NIR hyperspectral imaging was evaluated to classify maize kernels of three hardness categories: hard, medium and soft. Two approaches, pixel-wise and object-wise, were investigated to group kernels according to hardness. The pixel-wise classification assigned a class to every pixel from individual...... kernels and did not give acceptable results because of high misclassification. However by using a predefined threshold and classifying entire kernels based on the number of correctly predicted pixels, improved results were achieved (sensitivity and specificity of 0.75 and 0.97). Object-wise classification...... was performed using two methods for feature extraction — score histograms and mean spectra. The model based on score histograms performed better for hard kernel classification (sensitivity and specificity of 0.93 and 0.97), while that of mean spectra gave better results for medium kernels (sensitivity...
Object classification and detection with context kernel descriptors
DEFF Research Database (Denmark)
Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping
2014-01-01
Context information is important in object representation. By embedding context cue of image attributes into kernel descriptors, we propose a set of novel kernel descriptors called Context Kernel Descriptors (CKD) for object classification and detection. The motivation of CKD is to use spatial...... consistency of image attributes or features defined within a neighboring region to improve the robustness of descriptor matching in kernel space. For feature selection, Kernel Entropy Component Analysis (KECA) is exploited to learn a subset of discriminative CKD. Different from Kernel Principal Component...... Analysis (KPCA) that only keeps features contributing mostly to image reconstruction, KECA selects the CKD that contribute mostly to the Rényi entropy of the image. These CKD are discriminative as they relate to the density distribution of the histogram of image attributes. We report superior performance...
International Nuclear Information System (INIS)
Stirling, W.G.; Perry, S.C.
1996-01-01
We outline the theoretical and experimental background to neutron scattering studies of critical phenomena at magnetic and structural phase transitions. The displacive phase transition of SrTiO 3 is discussed, along with examples from recent work on magnetic materials from the rare-earth (Ho, Dy) and actinide (NpAs, NpSb, USb) classes. The impact of synchrotron X-ray scattering is discussed in conclusion. (author) 13 figs., 18 refs
Energy Technology Data Exchange (ETDEWEB)
Stirling, W.G. [Liverpool Univ., Dep. of Physics, Liverpool (United Kingdom); Perry, S.C. [Keele Univ. (United Kingdom). Dept. of Physics
1996-12-31
We outline the theoretical and experimental background to neutron scattering studies of critical phenomena at magnetic and structural phase transitions. The displacive phase transition of SrTiO{sub 3} is discussed, along with examples from recent work on magnetic materials from the rare-earth (Ho, Dy) and actinide (NpAs, NpSb, USb) classes. The impact of synchrotron X-ray scattering is discussed in conclusion. (author) 13 figs., 18 refs.
Visualization of nonlinear kernel models in neuroimaging by sensitivity maps
DEFF Research Database (Denmark)
Rasmussen, Peter Mondrup; Hansen, Lars Kai; Madsen, Kristoffer Hougaard
show that the performance of linear models is reduced for certain scan labelings/categorizations in this data set, while the nonlinear models provide more flexibility. We show that the sensitivity map can be used to visualize nonlinear versions of kernel logistic regression, the kernel Fisher...... discriminant, and the SVM, and conclude that the sensitivity map is a versatile and computationally efficient tool for visualization of nonlinear kernel models in neuroimaging...
Nonlinear Forecasting with Many Predictors using Kernel Ridge Regression
Peter Exterkate; Patrick J.F. Groenen; Christiaan Heij; Dick van Dijk
2011-01-01
textabstractThis paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related nonlinearly to the target variable. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation of the predictive regression model is based on a shrinkage estimator to avoid overfitting. We extend the kernel ridge regression methodology to enable its use for economic time-series forecasting, by ...
Dose point kernels for beta-emitting radioisotopes
International Nuclear Information System (INIS)
Prestwich, W.V.; Chan, L.B.; Kwok, C.S.; Wilson, B.
1986-01-01
Knowledge of the dose point kernel corresponding to a specific radionuclide is required to calculate the spatial dose distribution produced in a homogeneous medium by a distributed source. Dose point kernels for commonly used radionuclides have been calculated previously using as a basis monoenergetic dose point kernels derived by numerical integration of a model transport equation. The treatment neglects fluctuations in energy deposition, an effect which has been later incorporated in dose point kernels calculated using Monte Carlo methods. This work describes new calculations of dose point kernels using the Monte Carlo results as a basis. An analytic representation of the monoenergetic dose point kernels has been developed. This provides a convenient method both for calculating the dose point kernel associated with a given beta spectrum and for incorporating the effect of internal conversion. An algebraic expression for allowed beta spectra has been accomplished through an extension of the Bethe-Bacher approximation, and tested against the exact expression. Simplified expression for first-forbidden shape factors have also been developed. A comparison of the calculated dose point kernel for 32 P with experimental data indicates good agreement with a significant improvement over the earlier results in this respect. An analytic representation of the dose point kernel associated with the spectrum of a single beta group has been formulated. 9 references, 16 figures, 3 tables
Parameter optimization in the regularized kernel minimum noise fraction transformation
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg; Vestergaard, Jacob Schack
2012-01-01
Based on the original, linear minimum noise fraction (MNF) transformation and kernel principal component analysis, a kernel version of the MNF transformation was recently introduced. Inspired by we here give a simple method for finding optimal parameters in a regularized version of kernel MNF...... analysis. We consider the model signal-to-noise ratio (SNR) as a function of the kernel parameters and the regularization parameter. In 2-4 steps of increasingly refined grid searches we find the parameters that maximize the model SNR. An example based on data from the DLR 3K camera system is given....
Kernel methods in orthogonalization of multi- and hypervariate data
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg
2009-01-01
A kernel version of maximum autocorrelation factor (MAF) analysis is described very briefly and applied to change detection in remotely sensed hyperspectral image (HyMap) data. The kernel version is based on a dual formulation also termed Q-mode analysis in which the data enter into the analysis......) dimensional feature space via the kernel function and then performing a linear analysis in that space. An example shows the successful application of kernel MAF analysis to change detection in HyMap data covering a small agricultural area near Lake Waging-Taching, Bavaria, Germany....
Visualization of nonlinear kernel models in neuroimaging by sensitivity maps
DEFF Research Database (Denmark)
Rasmussen, P.M.; Madsen, Kristoffer H; Lund, T.E.
on visualization of such nonlinear kernel models. Specifically, we investigate the sensitivity map as a technique for generation of global summary maps of kernel classification methods. We illustrate the performance of the sensitivity map on functional magnetic resonance (fMRI) data based on visual stimuli. We...... show that the performance of linear models is reduced for certain scan labelings/categorizations in this data set, while the nonlinear models provide more flexibility. We show that the sensitivity map can be used to visualize nonlinear versions of kernel logistic regression, the kernel Fisher...
Robust visual tracking via speedup multiple kernel ridge regression
Qian, Cheng; Breckon, Toby P.; Li, Hui
2015-09-01
Most of the tracking methods attempt to build up feature spaces to represent the appearance of a target. However, limited by the complex structure of the distribution of features, the feature spaces constructed in a linear manner cannot characterize the nonlinear structure well. We propose an appearance model based on kernel ridge regression for visual tracking. Dense sampling is fulfilled around the target image patches to collect the training samples. In order to obtain a kernel space in favor of describing the target appearance, multiple kernel learning is introduced into the selection of kernels. Under the framework, instead of a single kernel, a linear combination of kernels is learned from the training samples to create a kernel space. Resorting to the circulant property of a kernel matrix, a fast interpolate iterative algorithm is developed to seek coefficients that are assigned to these kernels so as to give an optimal combination. After the regression function is learned, all candidate image patches gathered are taken as the input of the function, and the candidate with the maximal response is regarded as the object image patch. Extensive experimental results demonstrate that the proposed method outperforms other state-of-the-art tracking methods.
Fixed kernel regression for voltammogram feature extraction
International Nuclear Information System (INIS)
Acevedo Rodriguez, F J; López-Sastre, R J; Gil-Jiménez, P; Maldonado Bascón, S; Ruiz-Reyes, N
2009-01-01
Cyclic voltammetry is an electroanalytical technique for obtaining information about substances under analysis without the need for complex flow systems. However, classifying the information in voltammograms obtained using this technique is difficult. In this paper, we propose the use of fixed kernel regression as a method for extracting features from these voltammograms, reducing the information to a few coefficients. The proposed approach has been applied to a wine classification problem with accuracy rates of over 98%. Although the method is described here for extracting voltammogram information, it can be used for other types of signals
Index-free Heat Kernel Coefficients
van de Ven, Anton E. M.
1997-01-01
Using index-free notation, we present the diagonal values of the first five heat kernel coefficients associated with a general Laplace-type operator on a compact Riemannian space without boundary. The fifth coefficient appears here for the first time. For a flat space with a gauge connection, the sixth coefficient is given too. Also provided are the leading terms for any coefficient, both in ascending and descending powers of the Yang-Mills and Riemann curvatures, to the same order as require...
Localized Multiple Kernel Learning A Convex Approach
2016-11-22
1/2 . Theorem 9 (CLMKL Generalization Error Bounds) Assume that km(x, x) ≤ B, ∀m ∈ NM , x ∈ X . Suppose the loss function ℓ is L- Lipschitz and...mathematical foundation (e.g., Schölkopf and Smola, 2002). The performance of such algorithms, however, crucially depends on the involved kernel function ...approaches to localized MKL (reviewed in Section 1.1) optimize non-convex objective functions . This puts their generalization ability into doubt. Indeed
Learning Rotation for Kernel Correlation Filter
Hamdi, Abdullah
2017-08-11
Kernel Correlation Filters have shown a very promising scheme for visual tracking in terms of speed and accuracy on several benchmarks. However it suffers from problems that affect its performance like occlusion, rotation and scale change. This paper tries to tackle the problem of rotation by reformulating the optimization problem for learning the correlation filter. This modification (RKCF) includes learning rotation filter that utilizes circulant structure of HOG feature to guesstimate rotation from one frame to another and enhance the detection of KCF. Hence it gains boost in overall accuracy in many of OBT50 detest videos with minimal additional computation.
X-Ray-Scattering Measurements Of Strain In PEEK
Cebe, Peggy; Lowry, Lynn E.; Chung, Shirley Y.; Yavrouian, Andre H.; Gupta, Amitava
1988-01-01
Internal stress relieved by heating above glass-transition temperature. Report describes wide-angle x-ray scattering and differential scanning calorimetry of specimens of poly(etheretherketone) having undergone various thermal treatments. Wide-angle x-ray scattering particularly useful in determining distances between atoms, crystallinity, and related microstructurally generated phenomena, as thermal expansion and strain. Calorimetric measurements aid interpretation of scattering measurements by enabling correlation with thermal effects.
International Nuclear Information System (INIS)
Li, Xiaodong; Lee, Kyong Sei; Shaw, J.J.; Bahri, C.
1990-01-01
Electron scattering is one of the best probes available to us to probe the nucleus. It has revealed to us, with unprecedented accuracy, the charge and current distributions of nuclei. It has provided us with positive evidence for meson exchange currents. It was used to 'discover' the quark and it revealed to us that nucleons may be modified in the nuclear environment (EMC Effect). In short, electron scattering has revolutionized the study of nuclear physics. Several recent developments will insure that electron beams which will soon become availabe at CEBAF, Bates and elsewhere will make high-precision coincidence experiments possible. As the technology is becoming available, we are just beginning to exploit polarization degrees of freedom in our experiments. In this paper, we will introduce the formalism of electron scattering, review what we have learned in the past and look ahead toward the future
Pareto-path multitask multiple kernel learning.
Li, Cong; Georgiopoulos, Michael; Anagnostopoulos, Georgios C
2015-01-01
A traditional and intuitively appealing Multitask Multiple Kernel Learning (MT-MKL) method is to optimize the sum (thus, the average) of objective functions with (partially) shared kernel function, which allows information sharing among the tasks. We point out that the obtained solution corresponds to a single point on the Pareto Front (PF) of a multiobjective optimization problem, which considers the concurrent optimization of all task objectives involved in the Multitask Learning (MTL) problem. Motivated by this last observation and arguing that the former approach is heuristic, we propose a novel support vector machine MT-MKL framework that considers an implicitly defined set of conic combinations of task objectives. We show that solving our framework produces solutions along a path on the aforementioned PF and that it subsumes the optimization of the average of objective functions as a special case. Using the algorithms we derived, we demonstrate through a series of experimental results that the framework is capable of achieving a better classification performance, when compared with other similar MTL approaches.
Index-free heat kernel coefficients
van de Ven, Anton E. M.
1998-08-01
Using index-free notation, we present the diagonal values 0264-9381/15/8/014/img1 of the first five heat kernel coefficients 0264-9381/15/8/014/img2 associated with a general Laplace-type operator on a compact Riemannian space without boundary. The fifth coefficient 0264-9381/15/8/014/img3 appears here for the first time. For the special case of a flat space, but with a gauge connection, the sixth coefficient is given too. Also provided are the leading terms for any coefficient, both in ascending and descending powers of the Yang-Mills and Riemann curvatures, to the same order as required for the fourth coefficient. These results are obtained by directly solving the relevant recursion relations, working in the Fock-Schwinger gauge and Riemann normal coordinates. Our procedure is thus non-covariant, but we show that for any coefficient the `gauged', respectively `curved', version is found from the corresponding `non-gauged', respectively `flat', coefficient by making some simple covariant substitutions. These substitutions being understood, the coefficients retain their `flat' form and size. In this sense the fifth and sixth coefficient have only 26 and 75 terms, respectively, allowing us to write them down. Using index-free notation also clarifies the general structure of the heat kernel coefficients. In particular, in flat space we find that from the fifth coefficient onward, certain scalars are absent. This may be relevant for the anomalies of quantum field theories in ten or more dimensions.
The Kernel Estimation in Biosystems Engineering
Directory of Open Access Journals (Sweden)
Esperanza Ayuga Téllez
2008-04-01
Full Text Available In many fields of biosystems engineering, it is common to find works in which statistical information is analysed that violates the basic hypotheses necessary for the conventional forecasting methods. For those situations, it is necessary to find alternative methods that allow the statistical analysis considering those infringements. Non-parametric function estimation includes methods that fit a target function locally, using data from a small neighbourhood of the point. Weak assumptions, such as continuity and differentiability of the target function, are rather used than "a priori" assumption of the global target function shape (e.g., linear or quadratic. In this paper a few basic rules of decision are enunciated, for the application of the non-parametric estimation method. These statistical rules set up the first step to build an interface usermethod for the consistent application of kernel estimation for not expert users. To reach this aim, univariate and multivariate estimation methods and density function were analysed, as well as regression estimators. In some cases the models to be applied in different situations, based on simulations, were defined. Different biosystems engineering applications of the kernel estimation are also analysed in this review.
Kernelized rank learning for personalized drug recommendation.
He, Xiao; Folkman, Lukas; Borgwardt, Karsten
2018-03-08
Large-scale screenings of cancer cell lines with detailed molecular profiles against libraries of pharmacological compounds are currently being performed in order to gain a better understanding of the genetic component of drug response and to enhance our ability to recommend therapies given a patient's molecular profile. These comprehensive screens differ from the clinical setting in which (1) medical records only contain the response of a patient to very few drugs, (2) drugs are recommended by doctors based on their expert judgment, and (3) selecting the most promising therapy is often more important than accurately predicting the sensitivity to all potential drugs. Current regression models for drug sensitivity prediction fail to account for these three properties. We present a machine learning approach, named Kernelized Rank Learning (KRL), that ranks drugs based on their predicted effect per cell line (patient), circumventing the difficult problem of precisely predicting the sensitivity to the given drug. Our approach outperforms several state-of-the-art predictors in drug recommendation, particularly if the training dataset is sparse, and generalizes to patient data. Our work phrases personalized drug recommendation as a new type of machine learning problem with translational potential to the clinic. The Python implementation of KRL and scripts for running our experiments are available at https://github.com/BorgwardtLab/Kernelized-Rank-Learning. xiao.he@bsse.ethz.ch, lukas.folkman@bsse.ethz.ch. Supplementary data are available at Bioinformatics online.
Scientific Computing Kernels on the Cell Processor
Energy Technology Data Exchange (ETDEWEB)
Williams, Samuel W.; Shalf, John; Oliker, Leonid; Kamil, Shoaib; Husbands, Parry; Yelick, Katherine
2007-04-04
The slowing pace of commodity microprocessor performance improvements combined with ever-increasing chip power demands has become of utmost concern to computational scientists. As a result, the high performance computing community is examining alternative architectures that address the limitations of modern cache-based designs. In this work, we examine the potential of using the recently-released STI Cell processor as a building block for future high-end computing systems. Our work contains several novel contributions. First, we introduce a performance model for Cell and apply it to several key scientific computing kernels: dense matrix multiply, sparse matrix vector multiply, stencil computations, and 1D/2D FFTs. The difficulty of programming Cell, which requires assembly level intrinsics for the best performance, makes this model useful as an initial step in algorithm design and evaluation. Next, we validate the accuracy of our model by comparing results against published hardware results, as well as our own implementations on a 3.2GHz Cell blade. Additionally, we compare Cell performance to benchmarks run on leading superscalar (AMD Opteron), VLIW (Intel Itanium2), and vector (Cray X1E) architectures. Our work also explores several different mappings of the kernels and demonstrates a simple and effective programming model for Cell's unique architecture. Finally, we propose modest microarchitectural modifications that could significantly increase the efficiency of double-precision calculations. Overall results demonstrate the tremendous potential of the Cell architecture for scientific computations in terms of both raw performance and power efficiency.
Delimiting areas of endemism through kernel interpolation.
Oliveira, Ubirajara; Brescovit, Antonio D; Santos, Adalberto J
2015-01-01
We propose a new approach for identification of areas of endemism, the Geographical Interpolation of Endemism (GIE), based on kernel spatial interpolation. This method differs from others in being independent of grid cells. This new approach is based on estimating the overlap between the distribution of species through a kernel interpolation of centroids of species distribution and areas of influence defined from the distance between the centroid and the farthest point of occurrence of each species. We used this method to delimit areas of endemism of spiders from Brazil. To assess the effectiveness of GIE, we analyzed the same data using Parsimony Analysis of Endemism and NDM and compared the areas identified through each method. The analyses using GIE identified 101 areas of endemism of spiders in Brazil GIE demonstrated to be effective in identifying areas of endemism in multiple scales, with fuzzy edges and supported by more synendemic species than in the other methods. The areas of endemism identified with GIE were generally congruent with those identified for other taxonomic groups, suggesting that common processes can be responsible for the origin and maintenance of these biogeographic units.
Delimiting areas of endemism through kernel interpolation.
Directory of Open Access Journals (Sweden)
Ubirajara Oliveira
Full Text Available We propose a new approach for identification of areas of endemism, the Geographical Interpolation of Endemism (GIE, based on kernel spatial interpolation. This method differs from others in being independent of grid cells. This new approach is based on estimating the overlap between the distribution of species through a kernel interpolation of centroids of species distribution and areas of influence defined from the distance between the centroid and the farthest point of occurrence of each species. We used this method to delimit areas of endemism of spiders from Brazil. To assess the effectiveness of GIE, we analyzed the same data using Parsimony Analysis of Endemism and NDM and compared the areas identified through each method. The analyses using GIE identified 101 areas of endemism of spiders in Brazil GIE demonstrated to be effective in identifying areas of endemism in multiple scales, with fuzzy edges and supported by more synendemic species than in the other methods. The areas of endemism identified with GIE were generally congruent with those identified for other taxonomic groups, suggesting that common processes can be responsible for the origin and maintenance of these biogeographic units.
Energy Technology Data Exchange (ETDEWEB)
Botto, D.J.; Pratt, R.H.
1979-05-01
The current status of Compton scattering, both experimental observations and the theoretical predictions, is examined. Classes of experiments are distinguished and the results obtained are summarized. The validity of the incoherent scattering function approximation and the impulse approximation is discussed. These simple theoretical approaches are compared with predictions of the nonrelativistic dipole formula of Gavrila and with the relativistic results of Whittingham. It is noted that the A/sup -2/ based approximations fail to predict resonances and an infrared divergence, both of which have been observed. It appears that at present the various available theoretical approaches differ significantly in their predictions and that further and more systematic work is required.
Predictive Model Equations for Palm Kernel (Elaeis guneensis J ...
African Journals Online (AJOL)
A 3-factor experimental design was used to determine the influence of moisture content, roasting duration and temperature on palm kernel and sesame oil colours. Four levels each of these parameters were used. The data obtained were used to develop prediction models for palm kernel and sesame oil colours. Coefficient ...
Evaluation of enzyme supplementation of palm kernel meal-based ...
African Journals Online (AJOL)
Journal of Agriculture, Forestry and the Social Sciences ... The results of this study showed that broilers can tolerate 20% inclusion rate of palm kernel meal in their rations without enzyme supplementation and partially replacing maize with palm kernel meal at that level of inclusion can reduce the cost of production of ...
Nonlinear Forecasting With Many Predictors Using Kernel Ridge Regression
DEFF Research Database (Denmark)
Exterkate, Peter; Groenen, Patrick J.F.; Heij, Christiaan
This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related nonlinearly to the target variable. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation of the predi...
Efficient methods for robust classification under uncertainty in kernel matrices
Ben-Tal, A.; Bhadra, S.; Bhattacharyya, C.; Nemirovski, A.
2012-01-01
In this paper we study the problem of designing SVM classifiers when the kernel matrix, K , is affected by uncertainty. Specifically K is modeled as a positive affine combination of given positive semi definite kernels, with the coefficients ranging in a norm-bounded uncertainty set. We treat the
Design and construction of palm kernel cracking and separation ...
African Journals Online (AJOL)
Design and construction of palm kernel cracking and separation machines. ... Username, Password, Remember me, or Register. DOWNLOAD FULL TEXT Open Access DOWNLOAD FULL TEXT Subscription or Fee Access. Design and construction of palm kernel cracking and separation machines. JO Nordiana, K ...
Homotopy deform method for reproducing kernel space for ...
Indian Academy of Sciences (India)
In this paper, the combination of homotopy deform method (HDM) and simplified reproducing kernel method (SRKM) is introduced for solving the boundary value problems (BVPs) of nonlinear differential equations. The solution methodology is based on Adomian decomposition and reproducing kernel method (RKM).
Replacement Value of Palm Kernel Meal for Maize on Carcass ...
African Journals Online (AJOL)
This study was conducted to evaluate the effect of replacing maize with palm kernel meal on nutrient composition, fatty acid profile and sensory qualities of the meat of turkeys fed the dietary treatments. Six dietary treatments were formulated using palm kernel meal to replace maize at 0, 20, 40, 60, 80 and 100 percent.
Effect of Palm Kernel Cake Replacement and Enzyme ...
African Journals Online (AJOL)
A feeding trial which lasted for twelve weeks was conducted to study the performance of finisher pigs fed five different levels of palm kernel cake replacement for maize (0%, 40%, 40%, 60%, 60%) in a maize-palm kernel cake based ration with or without enzyme supplementation. It was a completely randomized design ...
Extracting Feature Model Changes from the Linux Kernel Using FMDiff
Dintzner, N.J.R.; Van Deursen, A.; Pinzger, M.
2014-01-01
The Linux kernel feature model has been studied as an example of large scale evolving feature model and yet details of its evolution are not known. We present here a classification of feature changes occurring on the Linux kernel feature model, as well as a tool, FMDiff, designed to automatically
Denoising by semi-supervised kernel PCA preimaging
DEFF Research Database (Denmark)
Hansen, Toke Jansen; Abrahamsen, Trine Julie; Hansen, Lars Kai
2014-01-01
Kernel Principal Component Analysis (PCA) has proven a powerful tool for nonlinear feature extraction, and is often applied as a pre-processing step for classification algorithms. In denoising applications Kernel PCA provides the basis for dimensionality reduction, prior to the so-called pre-imag...
High-power asymptotics of some weighted harmonic Bergman kernels
Czech Academy of Sciences Publication Activity Database
Engliš, Miroslav
2016-01-01
Roč. 271, č. 5 (2016), s. 1243-1261 ISSN 0022-1236 Institutional support: RVO:67985840 Keywords : Bergman kernel * harmonic Bergman kernel * asymptotic expansion Subject RIV: BA - General Mathematics Impact factor: 1.254, year: 2016 http://www.sciencedirect.com/science/article/pii/S0022123616301513
Efficient Kernel-based 2DPCA for Smile Stages Recognition
Directory of Open Access Journals (Sweden)
Fitri Damayanti
2012-03-01
Full Text Available Recently, an approach called two-dimensional principal component analysis (2DPCA has been proposed for smile stages representation and recognition. The essence of 2DPCA is that it computes the eigenvectors of the so-called image covariance matrix without matrix-to-vector conversion so the size of the image covariance matrix are much smaller, easier to evaluate covariance matrix, computation cost is reduced and the performance is also improved than traditional PCA. In an effort to improve and perfect the performance of smile stages recognition, in this paper, we propose efficient Kernel based 2DPCA concepts. The Kernelization of 2DPCA can be benefit to develop the nonlinear structures in the input data. This paper discusses comparison of standard Kernel based 2DPCA and efficient Kernel based 2DPCA for smile stages recognition. The results of experiments show that Kernel based 2DPCA achieve better performance in comparison with the other approaches. While the use of efficient Kernel based 2DPCA can speed up the training procedure of standard Kernel based 2DPCA thus the algorithm can achieve much more computational efficiency and remarkably save the memory consuming compared to the standard Kernel based 2DPCA.
Nutritional evaluation of palm kernel meal types: 1. Proximate ...
African Journals Online (AJOL)
Studies were conducted to determine the proximate composition and metabolizable energy values of palm kernel meal (PKM) types. The PKM types studied were obtained from Okomu, Presco and Envoy Oil Mills and were either mechanically or solvent extracted using different varieties of palm kernels. Samples of PKM ...
A multi-scale kernel bundle for LDDMM
DEFF Research Database (Denmark)
Sommer, Stefan Horst; Nielsen, Mads; Lauze, Francois Bernard
2011-01-01
The Large Deformation Diffeomorphic Metric Mapping framework constitutes a widely used and mathematically well-founded setup for registration in medical imaging. At its heart lies the notion of the regularization kernel, and the choice of kernel greatly affects the results of registrations...
Screening of the kernels of Pentadesma butyracea from various ...
African Journals Online (AJOL)
Gwla10
Pentadesma butyracea Sabine (Clusiaceae) is a ligneous forest species of multipurpose uses. It is widely distributed in Africa from Guinea-Bissau to the West of the Democratic Republic of Congo. This study screened the kernel of P. butyracea on the basis of their physico-chemical properties. Six types of kernels were ...
Kernel Function Tuning for Single-Layer Neural Networks
Czech Academy of Sciences Publication Activity Database
Vidnerová, Petra; Neruda, Roman
-, accepted 28.11. 2017 (2018) ISSN 2278-0149 R&D Projects: GA ČR GA15-18108S Institutional support: RVO:67985807 Keywords : single-layer neural networks * kernel methods * kernel function * optimisation Subject RIV: IN - Informatics, Computer Science http://www.ijmerr.com/
Boundary singularity of Poisson and harmonic Bergman kernels
Czech Academy of Sciences Publication Activity Database
Engliš, Miroslav
2015-01-01
Roč. 429, č. 1 (2015), s. 233-272 ISSN 0022-247X R&D Projects: GA AV ČR IAA100190802 Institutional support: RVO:67985840 Keywords : harmonic Bergman kernel * Poisson kernel * pseudodifferential boundary operators Subject RIV: BA - General Mathematics Impact factor: 1.014, year: 2015 http://www.sciencedirect.com/science/article/pii/S0022247X15003170
Real time kernel performance monitoring with SystemTap
CERN. Geneva
2018-01-01
SystemTap is a dynamic method of monitoring and tracing the operation of a running Linux kernel. In this talk I will present a few practical use cases where SystemTap allowed me to turn otherwise complex userland monitoring tasks in simple kernel probes.
Commutators of Integral Operators with Variable Kernels on Hardy ...
Indian Academy of Sciences (India)
Home; Journals; Proceedings – Mathematical Sciences; Volume 115; Issue 4. Commutators of Integral Operators with Variable Kernels on Hardy Spaces. Pu Zhang Kai Zhao. Volume 115 Issue 4 November 2005 pp 399-410 ... Keywords. Singular and fractional integrals; variable kernel; commutator; Hardy space.
Nonlinear Forecasting with Many Predictors using Kernel Ridge Regression
P. Exterkate (Peter); P.J.F. Groenen (Patrick); C. Heij (Christiaan); D.J.C. van Dijk (Dick)
2011-01-01
textabstractThis paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related nonlinearly to the target variable. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation of
Commutators of integral operators with variable kernels on Hardy ...
Indian Academy of Sciences (India)
Home; Journals; Proceedings – Mathematical Sciences; Volume 115; Issue 4. Commutators of Integral Operators with Variable Kernels on Hardy Spaces. Pu Zhang Kai Zhao. Volume 115 Issue 4 November 2005 pp 399-410 ... Keywords. Singular and fractional integrals; variable kernel; commutator; Hardy space.
Evaluation of palm kernel fibers (PKFs for production of asbestos-free automotive brake pads
Directory of Open Access Journals (Sweden)
K.K. Ikpambese
2016-01-01
Full Text Available In this study, asbestos-free automotive brake pads produced from palm kernel fibers with epoxy-resin binder was evaluated. Resins varied in formulations and properties such as friction coefficient, wear rate, hardness test, porosity, noise level, temperature, specific gravity, stopping time, moisture effects, surface roughness, oil and water absorptions rates, and microstructure examination were investigated. Other basic engineering properties of mechanical overload, thermal deformation fading behaviour shear strength, cracking resistance, over-heat recovery, and effect on rotor disc, caliper pressure, pad grip effect and pad dusting effect were also investigated. The results obtained indicated that the wear rate, coefficient of friction, noise level, temperature, and stopping time of the produced brake pads increased as the speed increases. The results also show that porosity, hardness, moisture content, specific gravity, surface roughness, and oil and water absorption rates remained constant with increase in speed. The result of microstructure examination revealed that worm surfaces were characterized by abrasion wear where the asperities were ploughed thereby exposing the white region of palm kernel fibers, thus increasing the smoothness of the friction materials. Sample S6 with composition of 40% epoxy-resin, 10% palm wastes, 6% Al2O3, 29% graphite, and 15% calcium carbonate gave better properties. The result indicated that palm kernel fibers can be effectively used as a replacement for asbestos in brake pad production.
3-D waveform tomography sensitivity kernels for anisotropic media
Djebbi, Ramzi
2014-01-01
The complications in anisotropic multi-parameter inversion lie in the trade-off between the different anisotropy parameters. We compute the tomographic waveform sensitivity kernels for a VTI acoustic medium perturbation as a tool to investigate this ambiguity between the different parameters. We use dynamic ray tracing to efficiently handle the expensive computational cost for 3-D anisotropic models. Ray tracing provides also the ray direction information necessary for conditioning the sensitivity kernels to handle anisotropy. The NMO velocity and η parameter kernels showed a maximum sensitivity for diving waves which results in a relevant choice of those parameters in wave equation tomography. The δ parameter kernel showed zero sensitivity; therefore it can serve as a secondary parameter to fit the amplitude in the acoustic anisotropic inversion. Considering the limited penetration depth of diving waves, migration velocity analysis based kernels are introduced to fix the depth ambiguity with reflections and compute sensitivity maps in the deeper parts of the model.
Open Problem: Kernel methods on manifolds and metric spaces
DEFF Research Database (Denmark)
Feragen, Aasa; Hauberg, Søren
2016-01-01
Radial kernels are well-suited for machine learning over general geodesic metric spaces, where pairwise distances are often the only computable quantity available. We have recently shown that geodesic exponential kernels are only positive definite for all bandwidths when the input space has strong...... linear properties. This negative result hints that radial kernel are perhaps not suitable over geodesic metric spaces after all. Here, however, we present evidence that large intervals of bandwidths exist where geodesic exponential kernels have high probability of being positive definite over finite...... datasets, while still having significant predictive power. From this we formulate conjectures on the probability of a positive definite kernel matrix for a finite random sample, depending on the geometry of the data space and the spread of the sample....
Compactly Supported Basis Functions as Support Vector Kernels for Classification.
Wittek, Peter; Tan, Chew Lim
2011-10-01
Wavelet kernels have been introduced for both support vector regression and classification. Most of these wavelet kernels do not use the inner product of the embedding space, but use wavelets in a similar fashion to radial basis function kernels. Wavelet analysis is typically carried out on data with a temporal or spatial relation between consecutive data points. We argue that it is possible to order the features of a general data set so that consecutive features are statistically related to each other, thus enabling us to interpret the vector representation of an object as a series of equally or randomly spaced observations of a hypothetical continuous signal. By approximating the signal with compactly supported basis functions and employing the inner product of the embedding L2 space, we gain a new family of wavelet kernels. Empirical results show a clear advantage in favor of these kernels.
Triso coating development progress for uranium nitride kernels
Energy Technology Data Exchange (ETDEWEB)
Jolly, Brian C. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Lindemer, Terrence [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Terrani, Kurt A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
2015-08-01
In support of fully ceramic matrix (FCM) fuel development [1-2], coating development work is ongoing at the Oak Ridge National Laboratory (ORNL) to produce tri-structural isotropic (TRISO) coated fuel particles with UN kernels [3]. The nitride kernels are used to increase fissile density in these SiC-matrix fuel pellets with details described elsewhere [4]. The advanced gas reactor (AGR) program at ORNL used fluidized bed chemical vapor deposition (FBCVD) techniques for TRISO coating of UCO (two phase mixture of UO2 and UCx) kernels [5]. Similar techniques were employed for coating of the UN kernels, however significant changes in processing conditions were required to maintain acceptable coating properties due to physical property and dimensional differences between the UCO and UN kernels (Table 1).
Systematic study on nuclear resonant scattering
International Nuclear Information System (INIS)
Suarez, A.A.; Freitas, M.L.
1974-01-01
New resonant scattering effect of thermal neutron capture gamma rays from Ti and Fe on Sb, Cu, Se and Ce target were observed. These results together with those published by other authors are summarized and discussed in terms of a possible systematic search for new resonant scattering effects
A weighted string kernel for protein fold recognition.
Nojoomi, Saghi; Koehl, Patrice
2017-08-25
Alignment-free methods for comparing protein sequences have proved to be viable alternatives to approaches that first rely on an alignment of the sequences to be compared. Much work however need to be done before those methods provide reliable fold recognition for proteins whose sequences share little similarity. We have recently proposed an alignment-free method based on the concept of string kernels, SeqKernel (Nojoomi and Koehl, BMC Bioinformatics, 2017, 18:137). In this previous study, we have shown that while Seqkernel performs better than standard alignment-based methods, its applications are potentially limited, because of biases due mostly to sequence length effects. In this study, we propose improvements to SeqKernel that follows two directions. First, we developed a weighted version of the kernel, WSeqKernel. Second, we expand the concept of string kernels into a novel framework for deriving information on amino acids from protein sequences. Using a dataset that only contains remote homologs, we have shown that WSeqKernel performs remarkably well in fold recognition experiments. We have shown that with the appropriate weighting scheme, we can remove the length effects on the kernel values. WSeqKernel, just like any alignment-based sequence comparison method, depends on a substitution matrix. We have shown that this matrix can be optimized so that sequence similarity scores correlate well with structure similarity scores. Starting from no information on amino acid similarity, we have shown that we can derive a scoring matrix that echoes the physico-chemical properties of amino acids. We have made progress in characterizing and parametrizing string kernels as alignment-based methods for comparing protein sequences, and we have shown that they provide a framework for extracting sequence information from structure.
3-D sensitivity kernels of the Rayleigh wave ellipticity
Maupin, Valérie
2017-10-01
The ellipticity of the Rayleigh wave at the surface depends on the seismic structure beneath and in the vicinity of the seismological station where it is measured. We derive here the expression and compute the 3-D kernels that describe this dependence with respect to S-wave velocity, P-wave velocity and density. Near-field terms as well as coupling to Love waves are included in the expressions. We show that the ellipticity kernels are the difference between the amplitude kernels of the radial and vertical components of motion. They show maximum values close to the station, but with a complex pattern, even when smoothing in a finite-frequency range is used to remove the oscillatory pattern present in mono-frequency kernels. In order to follow the usual data processing flow, we also compute and analyse the kernels of the ellipticity averaged over incoming wave backazimuth. The kernel with respect to P-wave velocity has the simplest lateral variation and is in good agreement with commonly used 1-D kernels. The kernels with respect to S-wave velocity and density are more complex and we have not been able to find a good correlation between the 3-D and 1-D kernels. Although it is clear that the ellipticity is mostly sensitive to the structure within half-a-wavelength of the station, the complexity of the kernels within this zone prevents simple approximations like a depth dependence times a lateral variation to be useful in the inversion of the ellipticity.
A method for manufacturing kernels of metallic oxides and the thus obtained kernels
International Nuclear Information System (INIS)
Lelievre Bernard; Feugier, Andre.
1973-01-01
A method is described for manufacturing fissile or fertile metal oxide kernels, consisting in adding at least a chemical compound capable of releasing ammonia to an aqueous solution of actinide nitrates dispersing the thus obtained solution dropwise in a hot organic phase so as to gelify the drops and transform them into solid particles, washing drying and treating said particles so as to transform them into oxide kernels. Such a method is characterized in that the organic phase used in the gel-forming reactions comprises a mixture of two organic liquids, one of which acts as a solvent, whereas the other is a product capable of extracting the metal-salt anions from the drops while the gel forming reaction is taking place. This can be applied to the so-called high temperature nuclear reactors [fr
Machado, K D; de Lima, J C; Campos, C E M; Grandi, T A; Pizani, P S
2004-01-01
The short- and intermediate-range orders of an amorphous Ge30Se70 alloy produced by mechanical alloying were studied by reverse Monte Carlo simulations of its x-ray total structure factor, Raman scattering, and differential scanning calorimetry. The simulations were used to compute the G(Ge-Ge) (RMC)(r), G(Ge-Se) (RMC)(r), and G(Se-Se) (RMC)(r) partial distribution functions and the S(Ge-Ge) (RMC)(K), S(Ge-Se) (RMC)(K), and S(Se-Se) (RMC)(K) partial structure factors. We calculated the coordination numbers and interatomic distances for the first and second neighbors and the bond-angle distribution functions Theta(ijl)(cos theta). The data obtained indicate that the structure of the alloy has important differences when compared to alloys prepared by other techniques. There are a high number of Se-Se pairs in the first shell, and some of the tetrahedral units formed seemed to be connected by Se-Se bridges. (c) 2004 American Institute of Physics
Learning molecular energies using localized graph kernels
Ferré, Grégoire; Haut, Terry; Barros, Kipton
2017-03-01
Recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturally incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. We benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.
Heat kernel methods for Lifshitz theories
Barvinsky, Andrei O.; Blas, Diego; Herrero-Valea, Mario; Nesterov, Dmitry V.; Pérez-Nadal, Guillem; Steinwachs, Christian F.
2017-06-01
We study the one-loop covariant effective action of Lifshitz theories using the heat kernel technique. The characteristic feature of Lifshitz theories is an anisotropic scaling between space and time. This is enforced by the existence of a preferred foliation of space-time, which breaks Lorentz invariance. In contrast to the relativistic case, covariant Lifshitz theories are only invariant under diffeomorphisms preserving the foliation structure. We develop a systematic method to reduce the calculation of the effective action for a generic Lifshitz operator to an algorithm acting on known results for relativistic operators. In addition, we present techniques that drastically simplify the calculation for operators with special properties. We demonstrate the efficiency of these methods by explicit applications.
Heat kernel method and its applications
Avramidi, Ivan G
2015-01-01
The heart of the book is the development of a short-time asymptotic expansion for the heat kernel. This is explained in detail and explicit examples of some advanced calculations are given. In addition some advanced methods and extensions, including path integrals, jump diffusion and others are presented. The book consists of four parts: Analysis, Geometry, Perturbations and Applications. The first part shortly reviews of some background material and gives an introduction to PDEs. The second part is devoted to a short introduction to various aspects of differential geometry that will be needed later. The third part and heart of the book presents a systematic development of effective methods for various approximation schemes for parabolic differential equations. The last part is devoted to applications in financial mathematics, in particular, stochastic differential equations. Although this book is intended for advanced undergraduate or beginning graduate students in, it should also provide a useful reference ...
Celluclast 1.5L pretreatment enhanced aroma of palm kernels and oil after kernel roasting.
Zhang, Wencan; Zhao, Fangju; Yang, Tiankui; Zhao, Feifei; Liu, Shaoquan
2017-12-01
The aroma of palm kernel oil (PKO) affects its applications. Little information is available on how enzymatic modification of palm kernels (PK) affects PK and PKO aroma after kernel roasting. Celluclast (cellulase) pretreatment of PK resulted in a 2.4-fold increment in the concentration of soluble sugars, with glucose being increased by 6.0-fold. Higher levels of 1.7-, 1.8- and 1.9-fold of O-heterocyclic volatile compounds were found in the treated PK after roasting at 180 °C for 8, 14 and 20 min respectively relative to the corresponding control, with furfural, 5-methyl-2-furancarboxaldehyde, 2-furanmethanol and maltol in particularly higher amounts. Volatile differences between PKOs from control and treated PK were also found, though less obvious owing to the aqueous extraction process. Principal component analysis based on aroma-active compounds revealed that upon the proceeding of roasting, the differentiation between control and treated PK was enlarged while that of corresponding PKOs was less clear-cut. Celluclast pretreatment enabled the medium roasted PK to impart more nutty, roasty and caramelic odor and the corresponding PKO to impart more caramelic but less roasty and burnt notes. Celluclast pretreatment of PK followed by roasting may be a promising new way of improving PKO aroma. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.
International Nuclear Information System (INIS)
Friedrich, Harald
2013-01-01
Written by the author of the widely acclaimed textbook. Theoretical Atomic Physics Includes sections on quantum reflection, tunable Feshbach resonances and Efimov states. Useful for advanced students and researchers. This book presents a concise and modern coverage of scattering theory. It is motivated by the fact that experimental advances have shifted and broadened the scope of applications where concepts from scattering theory are used, e.g. to the field of ultracold atoms and molecules, which has been experiencing enormous growth in recent years, largely triggered by the successful realization of Bose-Einstein condensates of dilute atomic gases in 1995. In the present treatment, special attention is given to the role played by the long-range behaviour of the projectile-target interaction, and a theory is developed, which is well suited to describe near-threshold bound and continuum states in realistic binary systems such as diatomic molecules or molecular ions. The level of abstraction is kept as low as at all possible, and deeper questions related to mathematical foundations of scattering theory are passed by. The book should be understandable for anyone with a basic knowledge of nonrelativistic quantum mechanics. It is intended for advanced students and researchers, and it is hoped that it will be useful for theorists and experimentalists alike.
Friedrich, Harald
2016-01-01
This corrected and updated second edition of "Scattering Theory" presents a concise and modern coverage of the subject. In the present treatment, special attention is given to the role played by the long-range behaviour of the projectile-target interaction, and a theory is developed, which is well suited to describe near-threshold bound and continuum states in realistic binary systems such as diatomic molecules or molecular ions. It is motivated by the fact that experimental advances have shifted and broadened the scope of applications where concepts from scattering theory are used, e.g. to the field of ultracold atoms and molecules, which has been experiencing enormous growth in recent years, largely triggered by the successful realization of Bose-Einstein condensates of dilute atomic gases in 1995. The book contains sections on special topics such as near-threshold quantization, quantum reflection, Feshbach resonances and the quantum description of scattering in two dimensions. The level of abstraction is k...
International Nuclear Information System (INIS)
1991-02-01
The annual report on hand gives an overview of the research work carried out in the Laboratory for Neutron Scattering (LNS) of the ETH Zuerich in 1990. Using the method of neutron scattering, it is possible to examine in detail the static and dynamic properties of the condensed material. In accordance with the multidisciplined character of the method, the LNS has for years maintained a system of intensive co-operation with numerous institutes in the areas of biology, chemistry, solid-state physics, crystallography and materials research. In 1990 over 100 scientists from more than 40 research groups both at home and abroad took part in the experiments. It was again a pleasure to see the number of graduate students present, who were studying for a doctorate and who could be introduced into the neutron scattering during their stay at the LNS and thus were in the position to touch on central ways of looking at a problem in their dissertation using this modern experimental method of solid-state research. In addition to the numerous and interesting ways of formulating the questions to explain the structure, nowadays the scientific programme increasingly includes particularly topical studies in connection with high temperature-supraconductors and materials research
Multiple kernel boosting framework based on information measure for classification
International Nuclear Information System (INIS)
Qi, Chengming; Wang, Yuping; Tian, Wenjie; Wang, Qun
2016-01-01
The performance of kernel-based method, such as support vector machine (SVM), is greatly affected by the choice of kernel function. Multiple kernel learning (MKL) is a promising family of machine learning algorithms and has attracted many attentions in recent years. MKL combines multiple sub-kernels to seek better results compared to single kernel learning. In order to improve the efficiency of SVM and MKL, in this paper, the Kullback–Leibler kernel function is derived to develop SVM. The proposed method employs an improved ensemble learning framework, named KLMKB, which applies Adaboost to learning multiple kernel-based classifier. In the experiment for hyperspectral remote sensing image classification, we employ feature selected through Optional Index Factor (OIF) to classify the satellite image. We extensively examine the performance of our approach in comparison to some relevant and state-of-the-art algorithms on a number of benchmark classification data sets and hyperspectral remote sensing image data set. Experimental results show that our method has a stable behavior and a noticeable accuracy for different data set.
Stochastic subset selection for learning with kernel machines.
Rhinelander, Jason; Liu, Xiaoping P
2012-06-01
Kernel machines have gained much popularity in applications of machine learning. Support vector machines (SVMs) are a subset of kernel machines and generalize well for classification, regression, and anomaly detection tasks. The training procedure for traditional SVMs involves solving a quadratic programming (QP) problem. The QP problem scales super linearly in computational effort with the number of training samples and is often used for the offline batch processing of data. Kernel machines operate by retaining a subset of observed data during training. The data vectors contained within this subset are referred to as support vectors (SVs). The work presented in this paper introduces a subset selection method for the use of kernel machines in online, changing environments. Our algorithm works by using a stochastic indexing technique when selecting a subset of SVs when computing the kernel expansion. The work described here is novel because it separates the selection of kernel basis functions from the training algorithm used. The subset selection algorithm presented here can be used in conjunction with any online training technique. It is important for online kernel machines to be computationally efficient due to the real-time requirements of online environments. Our algorithm is an important contribution because it scales linearly with the number of training samples and is compatible with current training techniques. Our algorithm outperforms standard techniques in terms of computational efficiency and provides increased recognition accuracy in our experiments. We provide results from experiments using both simulated and real-world data sets to verify our algorithm.
Deep Restricted Kernel Machines Using Conjugate Feature Duality.
Suykens, Johan A K
2017-08-01
The aim of this letter is to propose a theory of deep restricted kernel machines offering new foundations for deep learning with kernel machines. From the viewpoint of deep learning, it is partially related to restricted Boltzmann machines, which are characterized by visible and hidden units in a bipartite graph without hidden-to-hidden connections and deep learning extensions as deep belief networks and deep Boltzmann machines. From the viewpoint of kernel machines, it includes least squares support vector machines for classification and regression, kernel principal component analysis (PCA), matrix singular value decomposition, and Parzen-type models. A key element is to first characterize these kernel machines in terms of so-called conjugate feature duality, yielding a representation with visible and hidden units. It is shown how this is related to the energy form in restricted Boltzmann machines, with continuous variables in a nonprobabilistic setting. In this new framework of so-called restricted kernel machine (RKM) representations, the dual variables correspond to hidden features. Deep RKM are obtained by coupling the RKMs. The method is illustrated for deep RKM, consisting of three levels with a least squares support vector machine regression level and two kernel PCA levels. In its primal form also deep feedforward neural networks can be trained within this framework.
Localized Multiple Kernel Learning Via Sample-Wise Alternating Optimization.
Han, Yina; Yang, Kunde; Ma, Yuanliang; Liu, Guizhong
2014-01-01
Our objective is to train support vector machines (SVM)-based localized multiple kernel learning (LMKL), using the alternating optimization between the standard SVM solvers with the local combination of base kernels and the sample-specific kernel weights. The advantage of alternating optimization developed from the state-of-the-art MKL is the SVM-tied overall complexity and the simultaneous optimization on both the kernel weights and the classifier. Unfortunately, in LMKL, the sample-specific character makes the updating of kernel weights a difficult quadratic nonconvex problem. In this paper, starting from a new primal-dual equivalence, the canonical objective on which state-of-the-art methods are based is first decomposed into an ensemble of objectives corresponding to each sample, namely, sample-wise objectives. Then, the associated sample-wise alternating optimization method is conducted, in which the localized kernel weights can be independently obtained by solving their exclusive sample-wise objectives, either linear programming (for l1-norm) or with closed-form solutions (for lp-norm). At test time, the learnt kernel weights for the training data are deployed based on the nearest-neighbor rule. Hence, to guarantee their generality among the test part, we introduce the neighborhood information and incorporate it into the empirical loss when deriving the sample-wise objectives. Extensive experiments on four benchmark machine learning datasets and two real-world computer vision datasets demonstrate the effectiveness and efficiency of the proposed algorithm.
Per-Sample Multiple Kernel Approach for Visual Concept Learning
Directory of Open Access Journals (Sweden)
Ling-Yu Duan
2010-01-01
Full Text Available Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL methods have shown great advantages in visual concept learning. As a visual concept often exhibits great appearance variance, a canonical MKL approach may not generate satisfactory results when a uniform kernel combination is applied over the input space. In this paper, we propose a per-sample multiple kernel learning (PS-MKL approach to take into account intraclass diversity for improving discrimination. PS-MKL determines sample-wise kernel weights according to kernel functions and training samples. Kernel weights as well as kernel-based classifiers are jointly learned. For efficient learning, PS-MKL employs a sample selection strategy. Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07. PS-MKL has achieved encouraging performance, comparable to the state of the art, which has outperformed a canonical MKL.
Training Lp norm multiple kernel learning in the primal.
Liang, Zhizheng; Xia, Shixiong; Zhou, Yong; Zhang, Lei
2013-10-01
Some multiple kernel learning (MKL) models are usually solved by utilizing the alternating optimization method where one alternately solves SVMs in the dual and updates kernel weights. Since the dual and primal optimization can achieve the same aim, it is valuable in exploring how to perform Lp norm MKL in the primal. In this paper, we propose an Lp norm multiple kernel learning algorithm in the primal where we resort to the alternating optimization method: one cycle for solving SVMs in the primal by using the preconditioned conjugate gradient method and other cycle for learning the kernel weights. It is interesting to note that the kernel weights in our method can obtain analytical solutions. Most importantly, the proposed method is well suited for the manifold regularization framework in the primal since solving LapSVMs in the primal is much more effective than solving LapSVMs in the dual. In addition, we also carry out theoretical analysis for multiple kernel learning in the primal in terms of the empirical Rademacher complexity. It is found that optimizing the empirical Rademacher complexity may obtain a type of kernel weights. The experiments on some datasets are carried out to demonstrate the feasibility and effectiveness of the proposed method. Copyright © 2013 Elsevier Ltd. All rights reserved.
Per-Sample Multiple Kernel Approach for Visual Concept Learning
Directory of Open Access Journals (Sweden)
Tian Yonghong
2010-01-01
Full Text Available Abstract Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL methods have shown great advantages in visual concept learning. As a visual concept often exhibits great appearance variance, a canonical MKL approach may not generate satisfactory results when a uniform kernel combination is applied over the input space. In this paper, we propose a per-sample multiple kernel learning (PS-MKL approach to take into account intraclass diversity for improving discrimination. PS-MKL determines sample-wise kernel weights according to kernel functions and training samples. Kernel weights as well as kernel-based classifiers are jointly learned. For efficient learning, PS-MKL employs a sample selection strategy. Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07. PS-MKL has achieved encouraging performance, comparable to the state of the art, which has outperformed a canonical MKL.
A new treatment of nonlocality in scattering process
Upadhyay, N. J.; Bhagwat, A.; Jain, B. K.
2018-01-01
Nonlocality in the scattering potential leads to an integro-differential equation. In this equation nonlocality enters through an integral over the nonlocal potential kernel. The resulting Schrödinger equation is usually handled by approximating r,{r}{\\prime }-dependence of the nonlocal kernel. The present work proposes a novel method to solve the integro-differential equation. The method, using the mean value theorem of integral calculus, converts the nonhomogeneous term to a homogeneous term. The effective local potential in this equation turns out to be energy independent, but has relative angular momentum dependence. This method is accurate and valid for any form of nonlocality. As illustrative examples, the total and differential cross sections for neutron scattering off 12C, 56Fe and 100Mo nuclei are calculated with this method in the low energy region (up to 10 MeV) and are found to be in reasonable accord with the experiments.
Gilkey-de Witt heat kernel expansion and zero modes
International Nuclear Information System (INIS)
Alonso-Izquierdo, A.; Mateos Guilarte, J.
2013-01-01
In this paper we propose a generalization of the Gilkey-de Witt heat kernel expansion, designed to provide us with a precise estimation of the heat trace of non-negative Schr¨odinger type differential operators with non-trivial kernel over all the domain of its “inverse temperature” variable β. We apply this modified approach to compute effectively the one-loop kink mass shift for some models whose kink fluctuation operator spectrum is unknown and the only alternative to estimate this magnitude is the use of the heat kernel expansion techniques.
Visualization of nonlinear kernel models in neuroimaging by sensitivity maps
DEFF Research Database (Denmark)
Rasmussen, P.M.; Madsen, Kristoffer H; Lund, T.E.
There is significant current interest in decoding mental states from neuroimages. In this context kernel methods, e.g., support vector machines (SVM) are frequently adopted to learn statistical relations between patterns of brain activation and experimental conditions. In this paper we focus...... on visualization of such nonlinear kernel models. Specifically, we investigate the sensitivity map as a technique for generation of global summary maps of kernel classification methods. We illustrate the performance of the sensitivity map on functional magnetic resonance (fMRI) data based on visual stimuli. We...
Flour quality and kernel hardness connection in winter wheat
Directory of Open Access Journals (Sweden)
Szabó B. P.
2016-12-01
Full Text Available Kernel hardness is controlled by friabilin protein and it depends on the relation between protein matrix and starch granules. Friabilin is present in high concentration in soft grain varieties and in low concentration in hard grain varieties. The high gluten, hard wheat our generally contains about 12.0–13.0% crude protein under Mid-European conditions. The relationship between wheat protein content and kernel texture is usually positive and kernel texture influences the power consumption during milling. Hard-textured wheat grains require more grinding energy than soft-textured grains.
A Truly Jitter-Free Real-Time Kernel
DEFF Research Database (Denmark)
Marian, Nicolae; Jiang, Peng
2008-01-01
Hardware-Software co-design is a powerful method nowadays for the embedded system development. Reducing time to the market, more accuracy and interactivity with the whole system by the co-design developments are available. The paper considers and investigates a co-design solution applied to a real-time...... kernel (RTK) named HARTEX. The objective was to even more improve the timing performances of the kernel in terms of minimized, constant overhead (jitter free), in an application transparent manner. The co-design solution partitions the kernel between a pure software part, with constant overhead...
Robust Learning With Kernel Mean $p$-Power Error Loss.
Chen, Badong; Xing, Lei; Wang, Xin; Qin, Jing; Zheng, Nanning
2017-07-25
Correntropy is a second order statistical measure in kernel space, which has been successfully applied in robust learning and signal processing. In this paper, we define a nonsecond order statistical measure in kernel space, called the kernel mean-p power error (KMPE), including the correntropic loss (C-Loss) as a special case. Some basic properties of KMPE are presented. In particular, we apply the KMPE to extreme learning machine (ELM) and principal component analysis (PCA), and develop two robust learning algorithms, namely ELM-KMPE and PCA-KMPE. Experimental results on synthetic and benchmark data show that the developed algorithms can achieve better performance when compared with some existing methods.
Multiple small-angle neutron scattering studies of anisotropic materials
Allen, A J; Long, G G; Ilavsky, J
2002-01-01
Building on previous work that considered spherical scatterers and randomly oriented spheroidal scatterers, we describe a multiple small-angle neutron scattering (MSANS) analysis for nonrandomly oriented spheroids. We illustrate this with studies of the multi-component void morphologies found in plasma-spray thermal barrier coatings. (orig.)
Unified connected theory of few-body reaction mechanisms in N-body scattering theory
Polyzou, W. N.; Redish, E. F.
1978-01-01
A unified treatment of different reaction mechanisms in nonrelativistic N-body scattering is presented. The theory is based on connected kernel integral equations that are expected to become compact for reasonable constraints on the potentials. The operators T/sub +-//sup ab/(A) are approximate transition operators that describe the scattering proceeding through an arbitrary reaction mechanism A. These operators are uniquely determined by a connected kernel equation and satisfy an optical theorem consistent with the choice of reaction mechanism. Connected kernel equations relating T/sub +-//sup ab/(A) to the full T/sub +-//sup ab/ allow correction of the approximate solutions for any ignored process to any order. This theory gives a unified treatment of all few-body reaction mechanisms with the same dynamic simplicity of a model calculation, but can include complicated reaction mechanisms involving overlapping configurations where it is difficult to formulate models.
Effects of kernel weight and source-limitation on wheat grain yield ...
African Journals Online (AJOL)
Also, source levels were manipulated through 50% spikelet removal at anthesis to evaluate cultivar source/sink limitations to kernel growth. The results depicted that grain yield, kernel number per spike and 1000 kernel weight were reduced by 24.1%, 9.2% and 23.7% in warmer environment, respectively. Hence, kernel ...
Generation of gamma-ray streaming kernels through cylindrical ducts via Monte Carlo method
International Nuclear Information System (INIS)
Kim, Dong Su
1992-02-01
Since radiation streaming through penetrations is often the critical consideration in protection against exposure of personnel in a nuclear facility, it has been of great concern in radiation shielding design and analysis. Several methods have been developed and applied to the analysis of the radiation streaming in the past such as ray analysis method, single scattering method, albedo method, and Monte Carlo method. But they may be used for order-of-magnitude calculations and where sufficient margin is available, except for the Monte Carlo method which is accurate but requires a lot of computing time. This study developed a Monte Carlo method and constructed a data library of solutions using the Monte Carlo method for radiation streaming through a straight cylindrical duct in concrete walls of a broad, mono-directional, monoenergetic gamma-ray beam of unit intensity. The solution named as plane streaming kernel is the average dose rate at duct outlet and was evaluated for 20 source energies from 0 to 10 MeV, 36 source incident angles from 0 to 70 degrees, 5 duct radii from 10 to 30 cm, and 16 wall thicknesses from 0 to 100 cm. It was demonstrated that average dose rate due to an isotropic point source at arbitrary positions can be well approximated using the plane streaming kernel with acceptable error. Thus, the library of the plane streaming kernels can be used for the accurate and efficient analysis of radiation streaming through a straight cylindrical duct in concrete walls due to arbitrary distributions of gamma-ray sources
International Nuclear Information System (INIS)
Thilagam, L.; Subbaiah, K.V.
2008-01-01
Brachytherapy treatment planning systems (TPS) are always recommended to account for the effect of tissue, applicator and shielding material heterogeneities exist in Intracavitary brachytherapy (ICBT) applicators. Most of the commercially available brachytherapy TPS softwares estimate the absorbed dose at a point, only taking care of the contributions of individual sources and the source distribution, neglecting the dose perturbations arising from the applicator design and construction. So the doses estimated by them are not much accurate under realistic clinical conditions. In this regard, interactive point kernel rode (BrachyTPS) has been developed to perform independent dose calculations by taking into account the effect of these heterogeneities, using two regions build up factors, proposed by Kalos. As primary input data, the code takes patients' planning data including the source specifications, dwell positions, dwell times and it computes the doses at reference points by dose point kernel formalisms, with multi-layer shield build-up factors accounting for the contributions from scattered radiation. In addition to performing dose distribution calculations, this code package is capable of displaying an isodose distribution curve into the patient anatomy images. The primary aim of this study is to validate the developed point kernel code integrated with treatment planning systems against the other tools which are available in the market. In the present work, three brachytherapy applicators commonly used in the treatment of uterine cervical carcinoma, Board of Radiation Isotope and Technology (BRIT) made low dose rate (LDR) applicator, Fletcher Green type LDR applicator and Fletcher Williamson high dose rate (HDR) applicator were studied to test the accuracy of the software
Virtual Compton Scattering At High Energy
Zhang, C
2000-01-01
In this dissertation we develop a theoretical framework in the context of perturbative QuantumChromoDynamics (pQCD) for studying non-forward scattering processes. In particular, we investigate a non-forward unequal mass virtual Compton scattering amplitude by performing the general operator product expansion (OPE) and the formal renormalization group (RG) analysis. We discuss the general tensorial decomposition of the amplitude to obtain the invariant amplitudes in the non- forward kinematic region. We study the OPE to identify the relevant operators and their reduced matrix elements, as well as the corresponding Wilson coefficients. We find that the OPE now should be done in double moments with new moment variables. There are in the expansion new sets of leading twist operators which have overall derivatives. They mix under renormalization in a well- defined way. We compute the evolution kernels from which the anomalous dimensions for these operators can be extracted. We also obtain explicitly the lowest ord...
NEW HORIZONS SPICE KERNELS V1.0
National Aeronautics and Space Administration — This data set includes the complete set of New Horizons (NH) SPICE data files (kernel files'), which can be accessed using SPICE software. The SPICE data contain...
Kernel based collaborative recommender system for e-purchasing
Indian Academy of Sciences (India)
Home; Journals; Sadhana; Volume 35; Issue 5. Kernel based collaborative recommender system for -purchasing ... Recommender system a new marketing strategy plays an important role particularly in an electronic commerce environment. Among the various recommender systems, collaborative recommender system ...
Homotopy deform method for reproducing kernel space for ...
Indian Academy of Sciences (India)
2016-09-23
Sep 23, 2016 ... Nonlinear differential equations; the homotopy deform method; the simplified reproducing kernel ... an equivalent integro differential equation. ... an algorithm for solving nonlinear multipoint BVPs by combining homotopy perturbation and variational iteration methods. Most recently, Duan and Rach [12].
Quantitative trait locus (QTL) mapping for 100-kernel weight of ...
African Journals Online (AJOL)
hope&shola
2010-12-06
Zea mays L.), related to yield. To realize its ... Key words: Maize (Zea mays L.), 100-kernel weight, quantitative trait locus (QTL), recombinant inbred line. (RIL), nitrogen ... cient approach to realize genetic basis of trait, some.
Homotopy deform method for reproducing kernel space for ...
Indian Academy of Sciences (India)
2016-09-23
s12043-016-1269-8. Homotopy deform method for reproducing kernel space for nonlinear boundary value problems. MIN-QIANG XU. ∗ and YING-ZHEN LIN. School of Science, Zhuhai Campus, Beijing Institute of Technology, ...
MARS EXPLORATION ROVER 2 SPICE KERNELS V1.0
National Aeronautics and Space Administration — This data set includes the complete set of Mars Exploration Rover 2 SPICE data files (kernel files'), which can be accessed using SPICE software. The SPICE data...
ROSETTA ORBITER/LANDER SPICE KERNELS V1.0
National Aeronautics and Space Administration — This data set includes the complete set of Rosetta mission SPICE data files (kernel files''), which can be accessed using SPICE software. The SPICE data contains...
National Aeronautics and Space Administration — This data set includes the complete set of Mars Global Surveyor SPICE data files (kernel files''), which can be accessed using SPICE software. The SPICE data...
MARS EXPLORATION ROVER 1 SPICE KERNELS V1.0
National Aeronautics and Space Administration — This data set includes the complete set of Mars Exploration Rover 1 SPICE data files (kernel files''), which can be accessed using SPICE software. The SPICE data...
Linear and kernel methods for multi- and hypervariate change detection
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg; Canty, Morton J.
2010-01-01
The iteratively re-weighted multivariate alteration detection (IR-MAD) algorithm may be used both for unsuper- vised change detection in multi- and hyperspectral remote sensing imagery as well as for automatic radiometric normalization of multi- or hypervariate multitemporal image sequences...... code exists which allows for fast data exploration and experimentation with smaller datasets. Computationally demanding kernelization of test data with training data and kernel image projections have been programmed to run on massively parallel CUDA-enabled graphics processors, when available, giving....... Principal component analysis (PCA) as well as maximum autocorrelation factor (MAF) and minimum noise fraction (MNF) analyses of IR-MAD images, both linear and kernel-based (which are nonlinear), may further enhance change signals relative to no-change background. The kernel versions are based on a dual...
DEEP SPACE 1 SPICE KERNELS V1.0
National Aeronautics and Space Administration — This data set includes the complete set of Deep Space 1 (DS1) SPICE data files (kernel files''), which can be accessed using SPICE software. The SPICE data contains...
CLEMENTINE MOON SPICE KERNELS V1.0
National Aeronautics and Space Administration — This data set includes the complete set of Clementine SPICE data files (kernel files''), which can be accessed using SPICE software. The SPICE data contains...
7 CFR 981.401 - Adjusted kernel weight.
2010-01-01
... weight of delivery 10,000 10,000 2. Percent of edible kernel weight 53.0 84.0 3. Less weight loss in processing 1 1.00 0 4. Less excess moisture of edible kernels (excess moisture×line 2) 1.06 1.68 5. Net... Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing...
Palm kernel shell as aggregate for light weight concrete | Idah ...
African Journals Online (AJOL)
The palm kernel, cement, sand and gravel were mixed and cast in steel or cast iron moulds of 150mm2 cubes. The results show that the PK1 with ratio of 1 :2:3: 1· of cement, sand, gravel. and palm kernel shells respectively gave the highest compressive strength of 8.03N/mm2 after 28 days of curing. Comparing the results ...
Mathematical Modelling of Thin Layer Dried Cashew Kernels | Asiru ...
African Journals Online (AJOL)
In this paper mathematical models describing thin layer drying of cashew kernels in a batch dryer were presented. The range of drying air temperature was 70 – 110°C. The initial moisture content of the cashew kernels was 9.29% (d.b.) and the final moisture content was in the range of 3.5 to 4.6% dry-basis. Seven different ...
Assessing Gamma kernels and BSS/LSS processes
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole E.
This paper reviews the roles of gamma type kernels in the theory and modelling for Brownian and Lévy semistationary processes. Applications to financial econometrics and the physics of turbulence are pointed out.......This paper reviews the roles of gamma type kernels in the theory and modelling for Brownian and Lévy semistationary processes. Applications to financial econometrics and the physics of turbulence are pointed out....
MULTITASKER, Multitasking Kernel for C and FORTRAN Under UNIX
International Nuclear Information System (INIS)
Brooks, E.D. III
1988-01-01
1 - Description of program or function: MULTITASKER implements a multitasking kernel for the C and FORTRAN programming languages that runs under UNIX. The kernel provides a multitasking environment which serves two purposes. The first is to provide an efficient portable environment for the development, debugging, and execution of production multiprocessor programs. The second is to provide a means of evaluating the performance of a multitasking program on model multiprocessor hardware. The performance evaluation features require no changes in the application program source and are implemented as a set of compile- and run-time options in the kernel. 2 - Method of solution: The FORTRAN interface to the kernel is identical in function to the CRI multitasking package provided for the Cray XMP. This provides a migration path to high speed (but small N) multiprocessors once the application has been coded and debugged. With use of the UNIX m4 macro preprocessor, source compatibility can be achieved between the UNIX code development system and the target Cray multiprocessor. The kernel also provides a means of evaluating a program's performance on model multiprocessors. Execution traces may be obtained which allow the user to determine kernel overhead, memory conflicts between various tasks, and the average concurrency being exploited. The kernel may also be made to switch tasks every cpu instruction with a random execution ordering. This allows the user to look for unprotected critical regions in the program. These features, implemented as a set of compile- and run-time options, cause extra execution overhead which is not present in the standard production version of the kernel
Commutators of integral operators with variable kernels on Hardy ...
Indian Academy of Sciences (India)
(1.2). Then T ,0 is the singular integral with variable kernel, and we simply write it as T . The. Lp-boundedness of the singular integral operator with variable kernel appears in [1] (see also [3,7]). It turns out that such kind of operators are much more closely related to the elliptic partial differential equations of second order with ...
Resummed memory kernels in generalized system-bath master equations
Mavros, Michael G.; Van Voorhis, Troy
2014-08-01
Generalized master equations provide a concise formalism for studying reduced population dynamics. Usually, these master equations require a perturbative expansion of the memory kernels governing the dynamics; in order to prevent divergences, these expansions must be resummed. Resummation techniques of perturbation series are ubiquitous in physics, but they have not been readily studied for the time-dependent memory kernels used in generalized master equations. In this paper, we present a comparison of different resummation techniques for such memory kernels up to fourth order. We study specifically the spin-boson Hamiltonian as a model system bath Hamiltonian, treating the diabatic coupling between the two states as a perturbation. A novel derivation of the fourth-order memory kernel for the spin-boson problem is presented; then, the second- and fourth-order kernels are evaluated numerically for a variety of spin-boson parameter regimes. We find that resumming the kernels through fourth order using a Padé approximant results in divergent populations in the strong electronic coupling regime due to a singularity introduced by the nature of the resummation, and thus recommend a non-divergent exponential resummation (the "Landau-Zener resummation" of previous work). The inclusion of fourth-order effects in a Landau-Zener-resummed kernel is shown to improve both the dephasing rate and the obedience of detailed balance over simpler prescriptions like the non-interacting blip approximation, showing a relatively quick convergence on the exact answer. The results suggest that including higher-order contributions to the memory kernel of a generalized master equation and performing an appropriate resummation can provide a numerically-exact solution to system-bath dynamics for a general spectral density, opening the way to a new class of methods for treating system-bath dynamics.
Local Kernel for Brains Classification in Schizophrenia
Castellani, U.; Rossato, E.; Murino, V.; Bellani, M.; Rambaldelli, G.; Tansella, M.; Brambilla, P.
In this paper a novel framework for brain classification is proposed in the context of mental health research. A learning by example method is introduced by combining local measurements with non linear Support Vector Machine. Instead of considering a voxel-by-voxel comparison between patients and controls, we focus on landmark points which are characterized by local region descriptors, namely Scale Invariance Feature Transform (SIFT). Then, matching is obtained by introducing the local kernel for which the samples are represented by unordered set of features. Moreover, a new weighting approach is proposed to take into account the discriminative relevance of the detected groups of features. Experiments have been performed including a set of 54 patients with schizophrenia and 54 normal controls on which region of interest (ROI) have been manually traced by experts. Preliminary results on Dorso-lateral PreFrontal Cortex (DLPFC) region are promising since up to 75% of successful classification rate has been obtained with this technique and the performance has improved up to 85% when the subjects have been stratified by sex.
Kernel spectral clustering with memory effect
Langone, Rocco; Alzate, Carlos; Suykens, Johan A. K.
2013-05-01
Evolving graphs describe many natural phenomena changing over time, such as social relationships, trade markets, metabolic networks etc. In this framework, performing community detection and analyzing the cluster evolution represents a critical task. Here we propose a new model for this purpose, where the smoothness of the clustering results over time can be considered as a valid prior knowledge. It is based on a constrained optimization formulation typical of Least Squares Support Vector Machines (LS-SVM), where the objective function is designed to explicitly incorporate temporal smoothness. The latter allows the model to cluster the current data well and to be consistent with the recent history. We also propose new model selection criteria in order to carefully choose the hyper-parameters of our model, which is a crucial issue to achieve good performances. We successfully test the model on four toy problems and on a real world network. We also compare our model with Evolutionary Spectral Clustering, which is a state-of-the-art algorithm for community detection of evolving networks, illustrating that the kernel spectral clustering with memory effect can achieve better or equal performances.
KERNEL MAD ALGORITHM FOR RELATIVE RADIOMETRIC NORMALIZATION
Directory of Open Access Journals (Sweden)
Y. Bai
2016-06-01
Full Text Available The multivariate alteration detection (MAD algorithm is commonly used in relative radiometric normalization. This algorithm is based on linear canonical correlation analysis (CCA which can analyze only linear relationships among bands. Therefore, we first introduce a new version of MAD in this study based on the established method known as kernel canonical correlation analysis (KCCA. The proposed method effectively extracts the non-linear and complex relationships among variables. We then conduct relative radiometric normalization experiments on both the linear CCA and KCCA version of the MAD algorithm with the use of Landsat-8 data of Beijing, China, and Gaofen-1(GF-1 data derived from South China. Finally, we analyze the difference between the two methods. Results show that the KCCA-based MAD can be satisfactorily applied to relative radiometric normalization, this algorithm can well describe the nonlinear relationship between multi-temporal images. This work is the first attempt to apply a KCCA-based MAD algorithm to relative radiometric normalization.
Calpain cleavage prediction using multiple kernel learning.
Directory of Open Access Journals (Sweden)
David A DuVerle
Full Text Available Calpain, an intracellular Ca²⁺-dependent cysteine protease, is known to play a role in a wide range of metabolic pathways through limited proteolysis of its substrates. However, only a limited number of these substrates are currently known, with the exact mechanism of substrate recognition and cleavage by calpain still largely unknown. While previous research has successfully applied standard machine-learning algorithms to accurately predict substrate cleavage by other similar types of proteases, their approach does not extend well to calpain, possibly due to its particular mode of proteolytic action and limited amount of experimental data. Through the use of Multiple Kernel Learning, a recent extension to the classic Support Vector Machine framework, we were able to train complex models based on rich, heterogeneous feature sets, leading to significantly improved prediction quality (6% over highest AUC score produced by state-of-the-art methods. In addition to producing a stronger machine-learning model for the prediction of calpain cleavage, we were able to highlight the importance and role of each feature of substrate sequences in defining specificity: primary sequence, secondary structure and solvent accessibility. Most notably, we showed there existed significant specificity differences across calpain sub-types, despite previous assumption to the contrary. Prediction accuracy was further successfully validated using, as an unbiased test set, mutated sequences of calpastatin (endogenous inhibitor of calpain modified to no longer block calpain's proteolytic action. An online implementation of our prediction tool is available at http://calpain.org.
Liu, Yongbin; He, Bing; Liu, Fang; Lu, Siliang; Zhao, Yilei
2016-12-01
Fault pattern identification is a crucial step for the intelligent fault diagnosis of real-time health conditions in monitoring a mechanical system. However, many challenges exist in extracting the effective feature from vibration signals for fault recognition. A new feature fusion method is proposed in this study to extract new features using kernel joint approximate diagonalization of eigen-matrices (KJADE). In the method, the input space that is composed of original features is mapped into a high-dimensional feature space by nonlinear mapping. Then, the new features can be estimated through the eigen-decomposition of the fourth-order cumulative kernel matrix obtained from the feature space. Therefore, the proposed method could be used to reduce data redundancy because it extracts the inherent pattern structure of different fault classes as it is nonlinear by nature. The integration evaluation factor of between-class and within-class scatters (SS) is employed to depict the clustering performance quantitatively, and the new feature subset extracted by the proposed method is fed into a multi-class support vector machine for fault pattern identification. Finally, the effectiveness of the proposed method is verified by experimental vibration signals with different bearing fault types and severities. Results of several cases show that the KJADE algorithm is efficient in feature fusion for bearing fault identification.
A Distributed Learning Method for ℓ 1 -Regularized Kernel Machine over Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Xinrong Ji
2016-07-01
Full Text Available In wireless sensor networks, centralized learning methods have very high communication costs and energy consumption. These are caused by the need to transmit scattered training examples from various sensor nodes to the central fusion center where a classifier or a regression machine is trained. To reduce the communication cost, a distributed learning method for a kernel machine that incorporates ℓ 1 norm regularization ( ℓ 1 -regularized is investigated, and a novel distributed learning algorithm for the ℓ 1 -regularized kernel minimum mean squared error (KMSE machine is proposed. The proposed algorithm relies on in-network processing and a collaboration that transmits the sparse model only between single-hop neighboring nodes. This paper evaluates the proposed algorithm with respect to the prediction accuracy, the sparse rate of model, the communication cost and the number of iterations on synthetic and real datasets. The simulation results show that the proposed algorithm can obtain approximately the same prediction accuracy as that obtained by the batch learning method. Moreover, it is significantly superior in terms of the sparse rate of model and communication cost, and it can converge with fewer iterations. Finally, an experiment conducted on a wireless sensor network (WSN test platform further shows the advantages of the proposed algorithm with respect to communication cost.
Proteome analysis of the almond kernel (Prunus dulcis).
Li, Shugang; Geng, Fang; Wang, Ping; Lu, Jiankang; Ma, Meihu
2016-08-01
Almond (Prunus dulcis) is a popular tree nut worldwide and offers many benefits to human health. However, the importance of almond kernel proteins in the nutrition and function in human health requires further evaluation. The present study presents a systematic evaluation of the proteins in the almond kernel using proteomic analysis. The nutrient and amino acid content in almond kernels from Xinjiang is similar to that of American varieties; however, Xinjiang varieties have a higher protein content. Two-dimensional electrophoresis analysis demonstrated a wide distribution of molecular weights and isoelectric points of almond kernel proteins. A total of 434 proteins were identified by LC-MS/MS, and most were proteins that were experimentally confirmed for the first time. Gene ontology (GO) analysis of the 434 proteins indicated that proteins involved in primary biological processes including metabolic processes (67.5%), cellular processes (54.1%), and single-organism processes (43.4%), the main molecular function of almond kernel proteins are in catalytic activity (48.0%), binding (45.4%) and structural molecule activity (11.9%), and proteins are primarily distributed in cell (59.9%), organelle (44.9%), and membrane (22.8%). Almond kernel is a source of a wide variety of proteins. This study provides important information contributing to the screening and identification of almond proteins, the understanding of almond protein function, and the development of almond protein products. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.
Exploration of Shorea robusta (Sal seeds, kernels and its oil
Directory of Open Access Journals (Sweden)
Shashi Kumar C.
2016-12-01
Full Text Available Physical, mechanical, and chemical properties of Shorea robusta seed with wing, seed without wing, and kernel were investigated in the present work. The physico-chemical composition of sal oil was also analyzed. The physico-mechanical properties and proximate composition of seed with wing, seed without wing, and kernel at three moisture contents of 9.50% (w.b, 9.54% (w.b, and 12.14% (w.b, respectively, were studied. The results show that the moisture content of the kernel was highest as compared to seed with wing and seed without wing. The sphericity of the kernel was closer to that of a sphere as compared to seed with wing and seed without wing. The hardness of the seed with wing (32.32, N/mm and seed without wing (42.49, N/mm was lower than the kernels (72.14, N/mm. The proximate composition such as moisture, protein, carbohydrates, oil, crude fiber, and ash content were also determined. The kernel (30.20%, w/w contains higher oil percentage as compared to seed with wing and seed without wing. The scientific data from this work are important for designing of equipment and processes for post-harvest value addition of sal seeds.
Self-organization as an iterative kernel smoothing process.
Mulier, F; Cherkassky, V
1995-11-01
Kohonen's self-organizing map, when described in a batch processing mode, can be interpreted as a statistical kernel smoothing problem. The batch SOM algorithm consists of two steps. First, the training data are partitioned according to the Voronoi regions of the map unit locations. Second, the units are updated by taking weighted centroids of the data falling into the Voronoi regions, with the weighing function given by the neighborhood. Then, the neighborhood width is decreased and steps 1, 2 are repeated. The second step can be interpreted as a statistical kernel smoothing problem where the neighborhood function corresponds to the kernel and neighborhood width corresponds to kernel span. To determine the new unit locations, kernel smoothing is applied to the centroids of the Voronoi regions in the topological space. This interpretation leads to some new insights concerning the role of the neighborhood and dimensionality reduction. It also strengthens the algorithm's connection with the Principal Curve algorithm. A generalized self-organizing algorithm is proposed, where the kernel smoothing step is replaced with an arbitrary nonparametric regression method.
Sun, Yueping; Zhang, Yu; Li, Jiao
2017-01-01
Chemical-induced disease relations (CID) are crucial in various biomedical tasks. In the CID task of Biocreative V, no classifiers with multiple kernels have been developed. In this study, a multiple kernel learning-boosting (MKLB) method is proposed. Different kernel functions according to different types of features were constucted and boosted, each of which were learned with multiple kernels. Our multiple kernel learning-boosting (MKLB) method achieved a F1 score of 0.5068 without incorporating knowledge bases.
Diffuse scattering and the fundamental properties of materials
EIce, Gene; Barabash, Rozaliya
2009-01-01
Diffuse Scattering-the use of off-specular X-Rays and neutrons from surfaces and interfaces-has grown rapidly as a tool for characterizing the surface properties of materials and related fundamental structural properties. It has proven to be especially useful in the understanding of local properties within materials. This book reflects the efforts of physicists and materials scientists around the world who have helped to refine the techniques and applications of diffuse scattering. Major topics specifically covered include: -- Scattering in Low Dimensions -- Elastic and Thermal Diffuse Scattering from Alloys -- Scattering from Complex and Disordered Materials -- Scattering from Distorted Crystals.
Directory of Open Access Journals (Sweden)
Xiong Luo
2017-07-01
Full Text Available Recently, inspired by correntropy, kernel risk-sensitive loss (KRSL has emerged as a novel nonlinear similarity measure defined in kernel space, which achieves a better computing performance. After applying the KRSL to adaptive filtering, the corresponding minimum kernel risk-sensitive loss (MKRSL algorithm has been developed accordingly. However, MKRSL as a traditional kernel adaptive filter (KAF method, generates a growing radial basis functional (RBF network. In response to that limitation, through the use of online vector quantization (VQ technique, this article proposes a novel KAF algorithm, named quantized MKRSL (QMKRSL to curb the growth of the RBF network structure. Compared with other quantized methods, e.g., quantized kernel least mean square (QKLMS and quantized kernel maximum correntropy (QKMC, the efficient performance surface makes QMKRSL converge faster and filter more accurately, while maintaining the robustness to outliers. Moreover, considering that QMKRSL using traditional gradient descent method may fail to make full use of the hidden information between the input and output spaces, we also propose an intensified QMKRSL using a bilateral gradient technique named QMKRSL_BG, in an effort to further improve filtering accuracy. Short-term chaotic time-series prediction experiments are conducted to demonstrate the satisfactory performance of our algorithms.
Moghadam, Maryam Khazaee; Asl, Alireza Kamali; Geramifar, Parham; Zaidi, Habib
2016-01-01
Purpose: The aim of this work is to evaluate the application of tissue-specific dose kernels instead of water dose kernels to improve the accuracy of patient-specific dosimetry by taking tissue heterogeneities into consideration. Materials and Methods: Tissue-specific dose point kernels (DPKs) and
Multi-parameter Analysis and Inversion for Anisotropic Media Using the Scattering Integral Method
Djebbi, Ramzi
2017-10-24
The main goal in seismic exploration is to identify locations of hydrocarbons reservoirs and give insights on where to drill new wells. Therefore, estimating an Earth model that represents the right physics of the Earth\\'s subsurface is crucial in identifying these targets. Recent seismic data, with long offsets and wide azimuth features, are more sensitive to anisotropy. Accordingly, multiple anisotropic parameters need to be extracted from the recorded data on the surface to properly describe the model. I study the prospect of applying a scattering integral approach for multi-parameter inversion for a transversely isotropic model with a vertical axis of symmetry. I mainly analyze the sensitivity kernels to understand the sensitivity of seismic data to anisotropy parameters. Then, I use a frequency domain scattering integral approach to invert for the optimal parameterization. The scattering integral approach is based on the explicit computation of the sensitivity kernels. I present a new method to compute the traveltime sensitivity kernels for wave equation tomography using the unwrapped phase. I show that the new kernels are a better alternative to conventional cross-correlation/Rytov kernels. I also derive and analyze the sensitivity kernels for a transversely isotropic model with a vertical axis of symmetry. The kernels structure, for various opening/scattering angles, highlights the trade-off regions between the parameters. For a surface recorded data, I show that the normal move-out velocity vn, ƞ and δ parameterization is suitable for a simultaneous inversion of diving waves and reflections. Moreover, when seismic data is inverted hierarchically, the horizontal velocity vh, ƞ and ϵ is the parameterization with the least trade-off. In the frequency domain, the hierarchical inversion approach is naturally implemented using frequency continuation, which makes vh, ƞ and ϵ parameterization attractive. I formulate the multi-parameter inversion using the
Energy Technology Data Exchange (ETDEWEB)
Brueckel, Thomas; Heger, Gernot; Richter, Dieter; Roth, Georg; Zorn, Reiner (eds.)
2012-07-01
The following topics are dealt with: Neutron scattering in contemporary research, neutron sources, symmetry of crystals, diffraction, nanostructures investigated by small-angle neutron scattering, the structure of macromolecules, spin dependent and magnetic scattering, structural analysis, neutron reflectometry, magnetic nanostructures, inelastic scattering, strongly correlated electrons, dynamics of macromolecules, applications of neutron scattering. (HSI)
International Nuclear Information System (INIS)
Brueckel, Thomas; Heger, Gernot; Richter, Dieter; Roth, Georg; Zorn, Reiner
2012-01-01
The following topics are dealt with: Neutron scattering in contemporary research, neutron sources, symmetry of crystals, diffraction, nanostructures investigated by small-angle neutron scattering, the structure of macromolecules, spin dependent and magnetic scattering, structural analysis, neutron reflectometry, magnetic nanostructures, inelastic scattering, strongly correlated electrons, dynamics of macromolecules, applications of neutron scattering. (HSI)
Protein fold recognition using geometric kernel data fusion.
Zakeri, Pooya; Jeuris, Ben; Vandebril, Raf; Moreau, Yves
2014-07-01
Various approaches based on features extracted from protein sequences and often machine learning methods have been used in the prediction of protein folds. Finding an efficient technique for integrating these different protein features has received increasing attention. In particular, kernel methods are an interesting class of techniques for integrating heterogeneous data. Various methods have been proposed to fuse multiple kernels. Most techniques for multiple kernel learning focus on learning a convex linear combination of base kernels. In addition to the limitation of linear combinations, working with such approaches could cause a loss of potentially useful information. We design several techniques to combine kernel matrices by taking more involved, geometry inspired means of these matrices instead of convex linear combinations. We consider various sequence-based protein features including information extracted directly from position-specific scoring matrices and local sequence alignment. We evaluate our methods for classification on the SCOP PDB-40D benchmark dataset for protein fold recognition. The best overall accuracy on the protein fold recognition test set obtained by our methods is ∼ 86.7%. This is an improvement over the results of the best existing approach. Moreover, our computational model has been developed by incorporating the functional domain composition of proteins through a hybridization model. It is observed that by using our proposed hybridization model, the protein fold recognition accuracy is further improved to 89.30%. Furthermore, we investigate the performance of our approach on the protein remote homology detection problem by fusing multiple string kernels. The MATLAB code used for our proposed geometric kernel fusion frameworks are publicly available at http://people.cs.kuleuven.be/∼raf.vandebril/homepage/software/geomean.php?menu=5/. © The Author 2014. Published by Oxford University Press.
Unsupervised multiple kernel learning for heterogeneous data integration.
Mariette, Jérôme; Villa-Vialaneix, Nathalie
2018-03-15
Recent high-throughput sequencing advances have expanded the breadth of available omics datasets and the integrated analysis of multiple datasets obtained on the same samples has allowed to gain important insights in a wide range of applications. However, the integration of various sources of information remains a challenge for systems biology since produced datasets are often of heterogeneous types, with the need of developing generic methods to take their different specificities into account. We propose a multiple kernel framework that allows to integrate multiple datasets of various types into a single exploratory analysis. Several solutions are provided to learn either a consensus meta-kernel or a meta-kernel that preserves the original topology of the datasets. We applied our framework to analyse two public multi-omics datasets. First, the multiple metagenomic datasets, collected during the TARA Oceans expedition, was explored to demonstrate that our method is able to retrieve previous findings in a single kernel PCA as well as to provide a new image of the sample structures when a larger number of datasets are included in the analysis. To perform this analysis, a generic procedure is also proposed to improve the interpretability of the kernel PCA in regards with the original data. Second, the multi-omics breast cancer datasets, provided by The Cancer Genome Atlas, is analysed using a kernel Self-Organizing Maps with both single and multi-omics strategies. The comparison of these two approaches demonstrates the benefit of our integration method to improve the representation of the studied biological system. Proposed methods are available in the R package mixKernel, released on CRAN. It is fully compatible with the mixOmics package and a tutorial describing the approach can be found on mixOmics web site http://mixomics.org/mixkernel/. jerome.mariette@inra.fr or nathalie.villa-vialaneix@inra.fr. Supplementary data are available at Bioinformatics online.
Local coding based matching kernel method for image classification.
Directory of Open Access Journals (Sweden)
Yan Song
Full Text Available This paper mainly focuses on how to effectively and efficiently measure visual similarity for local feature based representation. Among existing methods, metrics based on Bag of Visual Word (BoV techniques are efficient and conceptually simple, at the expense of effectiveness. By contrast, kernel based metrics are more effective, but at the cost of greater computational complexity and increased storage requirements. We show that a unified visual matching framework can be developed to encompass both BoV and kernel based metrics, in which local kernel plays an important role between feature pairs or between features and their reconstruction. Generally, local kernels are defined using Euclidean distance or its derivatives, based either explicitly or implicitly on an assumption of Gaussian noise. However, local features such as SIFT and HoG often follow a heavy-tailed distribution which tends to undermine the motivation behind Euclidean metrics. Motivated by recent advances in feature coding techniques, a novel efficient local coding based matching kernel (LCMK method is proposed. This exploits the manifold structures in Hilbert space derived from local kernels. The proposed method combines advantages of both BoV and kernel based metrics, and achieves a linear computational complexity. This enables efficient and scalable visual matching to be performed on large scale image sets. To evaluate the effectiveness of the proposed LCMK method, we conduct extensive experiments with widely used benchmark datasets, including 15-Scenes, Caltech101/256, PASCAL VOC 2007 and 2011 datasets. Experimental results confirm the effectiveness of the relatively efficient LCMK method.
Schumacher, Florian; Friederich, Wolfgang; Lamara, Samir; Gutt, Phillip; Paffrath, Marcel
2015-04-01
We present a seismic full waveform inversion concept for applications ranging from seismological to enineering contexts, based on sensitivity kernels for full waveforms. The kernels are derived from Born scattering theory as the Fréchet derivatives of linearized frequency-domain full waveform data functionals, quantifying the influence of elastic earth model parameters and density on the data values. For a specific source-receiver combination, the kernel is computed from the displacement and strain field spectrum originating from the source evaluated throughout the inversion domain, as well as the Green function spectrum and its strains originating from the receiver. By storing the wavefield spectra of specific sources/receivers, they can be re-used for kernel computation for different specific source-receiver combinations, optimizing the total number of required forward simulations. In the iterative inversion procedure, the solution of the forward problem, the computation of sensitivity kernels and the derivation of a model update is held completely separate. In particular, the model description for the forward problem and the description of the inverted model update are kept independent. Hence, the resolution of the inverted model as well as the complexity of solving the forward problem can be iteratively increased (with increasing frequency content of the inverted data subset). This may regularize the overall inverse problem and optimizes the computational effort of both, solving the forward problem and computing the model update. The required interconnection of arbitrary unstructured volume and point grids is realized by generalized high-order integration rules and 3D-unstructured interpolation methods. The model update is inferred solving a minimization problem in a least-squares sense, resulting in Gauss-Newton convergence of the overall inversion process. The inversion method was implemented in the modularized software package ASKI (Analysis of Sensitivity
Spine labeling in axial magnetic resonance imaging via integral kernels.
Miles, Brandon; Ben Ayed, Ismail; Hojjat, Seyed-Parsa; Wang, Michael H; Li, Shuo; Fenster, Aaron; Garvin, Gregory J
2016-12-01
This study investigates a fast integral-kernel algorithm for classifying (labeling) the vertebra and disc structures in axial magnetic resonance images (MRI). The method is based on a hierarchy of feature levels, where pixel classifications via non-linear probability product kernels (PPKs) are followed by classifications of 2D slices, individual 3D structures and groups of 3D structures. The algorithm further embeds geometric priors based on anatomical measurements of the spine. Our classifier requires evaluations of computationally expensive integrals at each pixel, and direct evaluations of such integrals would be prohibitively time consuming. We propose an efficient computation of kernel density estimates and PPK evaluations for large images and arbitrary local window sizes via integral kernels. Our method requires a single user click for a whole 3D MRI volume, runs nearly in real-time, and does not require an intensive external training. Comprehensive evaluations over T1-weighted axial lumbar spine data sets from 32 patients demonstrate a competitive structure classification accuracy of 99%, along with a 2D slice classification accuracy of 88%. To the best of our knowledge, such a structure classification accuracy has not been reached by the existing spine labeling algorithms. Furthermore, we believe our work is the first to use integral kernels in the context of medical images. Copyright Â© 2016 Elsevier Ltd. All rights reserved.
Structured Kernel Dictionary Learning with Correlation Constraint for Object Recognition.
Wang, Zhengjue; Wang, Yinghua; Liu, Hongwei; Zhang, Hao
2017-06-21
In this paper, we propose a new discriminative non-linear dictionary learning approach, called correlation constrained structured kernel KSVD, for object recognition. The objective function for dictionary learning contains a reconstructive term and a discriminative term. In the reconstructive term, signals are implicitly non-linearly mapped into a space, where a structured kernel dictionary, each sub-dictionary of which lies in the span of the mapped signals from the corresponding class, is established. In the discriminative term, by analyzing the classification mechanism, the correlation constraint is proposed in kernel form, constraining the correlations between different discriminative codes, and restricting the coefficient vectors to be transformed into a feature space, where the features are highly correlated inner-class and nearly independent between-classes. The objective function is optimized by the proposed structured kernel KSVD. During the classification stage, the specific form of the discriminative feature is needless to be known, while the inner product of the discriminative feature with kernel matrix embedded is available, and is suitable for a linear SVM classifier. Experimental results demonstrate that the proposed approach outperforms many state-of-the-art dictionary learning approaches for face, scene and synthetic aperture radar (SAR) vehicle target recognition.
Interest Extraction Using Relevance Feedback with Kernel Method
Hidekazu, Yanagimoto; Sigeru, Omatu
In this paper, we propose interest extraction using the relevance feedback with the kernel method. In the field of machine learning, the kernel method has been used. Since the classifier using the kernel method creates a discriminant function in a feature space, the discriminant function is a nonlinear function in a input space. The kernel method is used for the Support Vector Machine (SVM), the Kernel PCA, and so on. The SVM set a discriminant hyperplane between positive data and negative data. Hence, a distance between the hyperplane and a training sample is not important in the SVM. It is difficult to use the SVM to score other samples. Our goal is to create a method which scores the other samples in the feature space. We propose the relevance feedback which is carried out in the feature space. Hence, this relevance feedback can deal with nonlinearity of data. We compare the proposed method with the common relevance feedback using test collection NTCIR2. Finally, we comfirm the proposed method is superior to the common method through simulations.
Mixed kernel function support vector regression for global sensitivity analysis
Cheng, Kai; Lu, Zhenzhou; Wei, Yuhao; Shi, Yan; Zhou, Yicheng
2017-11-01
Global sensitivity analysis (GSA) plays an important role in exploring the respective effects of input variables on an assigned output response. Amongst the wide sensitivity analyses in literature, the Sobol indices have attracted much attention since they can provide accurate information for most models. In this paper, a mixed kernel function (MKF) based support vector regression (SVR) model is employed to evaluate the Sobol indices at low computational cost. By the proposed derivation, the estimation of the Sobol indices can be obtained by post-processing the coefficients of the SVR meta-model. The MKF is constituted by the orthogonal polynomials kernel function and Gaussian radial basis kernel function, thus the MKF possesses both the global characteristic advantage of the polynomials kernel function and the local characteristic advantage of the Gaussian radial basis kernel function. The proposed approach is suitable for high-dimensional and non-linear problems. Performance of the proposed approach is validated by various analytical functions and compared with the popular polynomial chaos expansion (PCE). Results demonstrate that the proposed approach is an efficient method for global sensitivity analysis.
CELLULOSE EXTRACTION FROM PALM KERNEL CAKE USING LIQUID PHASE OXIDATION
Directory of Open Access Journals (Sweden)
FARM YAN YAN
2009-03-01
Full Text Available Cellulose is widely used in many aspect and industries such as food industry, pharmaceutical, paint, polymers, and many more. Due to the increasing demand in the market, studies and work to produce cellulose are still rapidly developing. In this work, liquid phase oxidation was used to extract cellulose from palm kernel cake to separate hemicellulose, cellulose and lignin. The method is basically a two-step process. Palm kernel cake was pretreated in hot water at 180°C and followed by liquid oxidation process with 30% H2O2 at 60°C at atmospheric pressure. The process parameters are hot water treatment time, ratio of palm kernel cake to H2O2, liquid oxidation reaction temperature and time. Analysis of the process parameters on production cellulose from palm kernel cake was performed by using Response Surface Methodology. The recovered cellulose was further characterized by Fourier Transform Infrared (FTIR. Through the hot water treatment, hemicellulose in the palm kernel cake was successfully recovered as saccharides and thus leaving lignin and cellulose. Lignin was converted to water soluble compounds in liquid oxidation step which contains small molecular weight fatty acid as HCOOH and CH3COOH and almost pure cellulose was recovered.
Semi-supervised learning for ordinal Kernel Discriminant Analysis.
Pérez-Ortiz, M; Gutiérrez, P A; Carbonero-Ruz, M; Hervás-Martínez, C
2016-12-01
Ordinal classification considers those classification problems where the labels of the variable to predict follow a given order. Naturally, labelled data is scarce or difficult to obtain in this type of problems because, in many cases, ordinal labels are given by a user or expert (e.g. in recommendation systems). Firstly, this paper develops a new strategy for ordinal classification where both labelled and unlabelled data are used in the model construction step (a scheme which is referred to as semi-supervised learning). More specifically, the ordinal version of kernel discriminant learning is extended for this setting considering the neighbourhood information of unlabelled data, which is proposed to be computed in the feature space induced by the kernel function. Secondly, a new method for semi-supervised kernel learning is devised in the context of ordinal classification, which is combined with our developed classification strategy to optimise the kernel parameters. The experiments conducted compare 6 different approaches for semi-supervised learning in the context of ordinal classification in a battery of 30 datasets, showing (1) the good synergy of the ordinal version of discriminant analysis and the use of unlabelled data and (2) the advantage of computing distances in the feature space induced by the kernel function. Copyright © 2016 Elsevier Ltd. All rights reserved.
Multiple kernel sparse representations for supervised and unsupervised learning.
Thiagarajan, Jayaraman J; Ramamurthy, Karthikeyan Natesan; Spanias, Andreas
2014-07-01
In complex visual recognition tasks, it is typical to adopt multiple descriptors, which describe different aspects of the images, for obtaining an improved recognition performance. Descriptors that have diverse forms can be fused into a unified feature space in a principled manner using kernel methods. Sparse models that generalize well to the test data can be learned in the unified kernel space, and appropriate constraints can be incorporated for application in supervised and unsupervised learning. In this paper, we propose to perform sparse coding and dictionary learning in the multiple kernel space, where the weights of the ensemble kernel are tuned based on graph-embedding principles such that class discrimination is maximized. In our proposed algorithm, dictionaries are inferred using multiple levels of 1D subspace clustering in the kernel space, and the sparse codes are obtained using a simple levelwise pursuit scheme. Empirical results for object recognition and image clustering show that our algorithm outperforms existing sparse coding based approaches, and compares favorably to other state-of-the-art methods.
Bidirectional optical scattering facility
Federal Laboratory Consortium — Goniometric optical scatter instrument (GOSI)The bidirectional reflectance distribution function (BRDF) quantifies the angular distribution of light scattered from a...
An Efficient Kernel Optimization Method for Radar High-Resolution Range Profile Recognition
Directory of Open Access Journals (Sweden)
Chen Bo
2007-01-01
Full Text Available A kernel optimization method based on fusion kernel for high-resolution range profile (HRRP is proposed in this paper. Based on the fusion of -norm and -norm Gaussian kernels, our method combines the different characteristics of them so that not only is the kernel function optimized but also the speckle fluctuations of HRRP are restrained. Then the proposed method is employed to optimize the kernel of kernel principle component analysis (KPCA and the classification performance of extracted features is evaluated via support vector machines (SVMs classifier. Finally, experimental results on the benchmark and radar-measured data sets are compared and analyzed to demonstrate the efficiency of our method.
Gianfrani, Carmen; Mamone, Gianfranco; la Gatta, Barbara; Camarca, Alessandra; Di Stasio, Luigia; Maurano, Francesco; Picascia, Stefania; Capozzi, Vito; Perna, Giuseppe; Picariello, Gianluca; Di Luccia, Aldo
2017-03-01
Microwave based treatment (MWT) of wet wheat kernels induced a striking reduction of gluten, up to gluten-free. In contrast, analysis of gluten peptides by G12 antibody-based ELISA, mass spectrometry-based proteomics and in vitro assay with T cells of celiac subjects, indicated no difference of antigenicity before and after MWT. SDS-PAGE analysis and Raman spectroscopy demonstrated that MWT simply induced conformational modifications, reducing alcohol solubility of gliadins and altering the access of R5-antibody to the gluten epitopes. Thus, MWT neither destroys gluten nor modifies chemically the toxic epitopes, contradicting the preliminary claims that MWT of wheat kernels detoxifies gluten. This study provides evidence that R5-antibody ELISA alone is not effective to determine gluten in thermally treated wheat products. Gluten epitopes in processed wheat should be monitored using strategies based on combined immunoassays with T cells from celiacs, G12-antibody ELISA after proteolysis and proper molecular characterization. Copyright © 2017 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Premuda, F.; Zucchini, A.
1984-01-01
A transport method was developed in view of benchmark calculations of the eigenvalues and flux distributions for monoenergetic neutrons anisotropically colliding in a critical cylinder of finite radius and half-height. For the kernels appearing in the system of integral equations for spherical harmonic moments of the angular flux we proposed a factorized form that accounted for the anisotropy of scattering and worked in the original Euclidean space, extending to cylinder geometry, of interest for pratical reactor calculations, a technique previously adopted for the simpler parallelepiped geometry. This treatment of the two-dimensional kernels allows representations typical in one dimensional problems for the matrix formulation to which the problem reduces by the introduction of a corresponding projectional technique. Optimal in view of an appropriate matrix formulation appears also the representation of the unknown spherical harmonics moments in terms of special jacobi polynomials, coinciding with a Legrendre polynomials expansion for the total flux in the case of isotropic scattering. The high accuracy of the results obtained in this case for both eigenvalues and fluxes is finally tested by internal convergence studies and heights as well as for the limiting cases or ratios of radius to height going to zero or to infinity
The spinor heat kernel in maximally symmetric spaces
International Nuclear Information System (INIS)
Camporesi, R.
1992-01-01
The heat kernel K(x, x', t) of the iterated Dirac operator on an N-dimensional simply connected maximally symmetric Riemannian manifold is calculated. On the odd-dimensional hyperbolic spaces K is a Minakshisundaram-DeWitt expansion which terminates to the coefficient a (N-1)/2 and is exact. On the odd spheres the heat kernel may be written as an image sum of WKB kernels, each term corresponding to a classical path (geodesic). In the even dimensional case the WKB approximation is not exact, but a closed form of K is derived both in terms of (spherical) eigenfunctions and of a 'sum over classical paths'. The spinor Plancherel measure μ(λ) and ζ function in the hyperbolic case are also calculated. A simple relation between the analytic structure of μ on H N and the degeneracies of the Dirac operator on S N is found. (orig.)
Purification and characterization of riproximin from Ximenia americana fruit kernels.
Bayer, Helene; Ey, Noreen; Wattenberg, Andreas; Voss, Cristina; Berger, Martin R
2012-03-01
Highly pure riproximin was isolated from the fruit kernels of Ximenia americana, a defined, seasonally available and potentially unlimited herbal source. The newly established purification procedure included an initial aqueous extraction, removal of lipids with chloroform and subsequent chromatographic purification steps on a strong anion exchange resin and lactosyl-Sepharose. Consistent purity and stable biological properties were shown over several purification batches. The purified, kernel-derived riproximin was characterized in comparison to the African plant material riproximin and revealed highly similar biochemical and biological properties but differences in the electrophoresis pattern and mass spectrometry peptide profile. Our results suggest that although the purified fruit kernel riproximin consists of a mixture of closely related isoforms, it provides a reliable basis for further research and development of this type II ribosome inactivating protein (RIP). Copyright Â© 2011 Elsevier Inc. All rights reserved.
Reconstruction of noisy and blurred images using blur kernel
Ellappan, Vijayan; Chopra, Vishal
2017-11-01
Blur is a common in so many digital images. Blur can be caused by motion of the camera and scene object. In this work we proposed a new method for deblurring images. This work uses sparse representation to identify the blur kernel. By analyzing the image coordinates Using coarse and fine, we fetch the kernel based image coordinates and according to that observation we get the motion angle of the shaken or blurred image. Then we calculate the length of the motion kernel using radon transformation and Fourier for the length calculation of the image and we use Lucy Richardson algorithm which is also called NON-Blind(NBID) Algorithm for more clean and less noisy image output. All these operation will be performed in MATLAB IDE.
Heat Kernel Asymptotics of Zaremba Boundary Value Problem
Energy Technology Data Exchange (ETDEWEB)
Avramidi, Ivan G. [Department of Mathematics, New Mexico Institute of Mining and Technology (United States)], E-mail: iavramid@nmt.edu
2004-03-15
The Zaremba boundary-value problem is a boundary value problem for Laplace-type second-order partial differential operators acting on smooth sections of a vector bundle over a smooth compact Riemannian manifold with smooth boundary but with discontinuous boundary conditions, which include Dirichlet boundary conditions on one part of the boundary and Neumann boundary conditions on another part of the boundary. We study the heat kernel asymptotics of Zaremba boundary value problem. The construction of the asymptotic solution of the heat equation is described in detail and the heat kernel is computed explicitly in the leading approximation. Some of the first nontrivial coefficients of the heat kernel asymptotic expansion are computed explicitly.
Optimized data fusion for kernel k-means clustering.
Yu, Shi; Tranchevent, Léon-Charles; Liu, Xinhai; Glänzel, Wolfgang; Suykens, Johan A K; De Moor, Bart; Moreau, Yves
2012-05-01
This paper presents a novel optimized kernel k-means algorithm (OKKC) to combine multiple data sources for clustering analysis. The algorithm uses an alternating minimization framework to optimize the cluster membership and kernel coefficients as a nonconvex problem. In the proposed algorithm, the problem to optimize the cluster membership and the problem to optimize the kernel coefficients are all based on the same Rayleigh quotient objective; therefore the proposed algorithm converges locally. OKKC has a simpler procedure and lower complexity than other algorithms proposed in the literature. Simulated and real-life data fusion applications are experimentally studied, and the results validate that the proposed algorithm has comparable performance, moreover, it is more efficient on large-scale data sets. (The Matlab implementation of OKKC algorithm is downloadable from http://homes.esat.kuleuven.be/~sistawww/bio/syu/okkc.html.).
Rational kernels for Arabic Root Extraction and Text Classification
Directory of Open Access Journals (Sweden)
Attia Nehar
2016-04-01
Full Text Available In this paper, we address the problems of Arabic Text Classification and root extraction using transducers and rational kernels. We introduce a new root extraction approach on the basis of the use of Arabic patterns (Pattern Based Stemmer. Transducers are used to model these patterns and root extraction is done without relying on any dictionary. Using transducers for extracting roots, documents are transformed into finite state transducers. This document representation allows us to use and explore rational kernels as a framework for Arabic Text Classification. Root extraction experiments are conducted on three word collections and yield 75.6% of accuracy. Classification experiments are done on the Saudi Press Agency dataset and N-gram kernels are tested with different values of N. Accuracy and F1 report 90.79% and 62.93% respectively. These results show that our approach, when compared with other approaches, is promising specially in terms of accuracy and F1.
Regularized Embedded Multiple Kernel Dimensionality Reduction for Mine Signal Processing
Li, Shuang; Liu, Bing; Zhang, Chen
2016-01-01
Traditional multiple kernel dimensionality reduction models are generally based on graph embedding and manifold assumption. But such assumption might be invalid for some high-dimensional or sparse data due to the curse of dimensionality, which has a negative influence on the performance of multiple kernel learning. In addition, some models might be ill-posed if the rank of matrices in their objective functions was not high enough. To address these issues, we extend the traditional graph embedding framework and propose a novel regularized embedded multiple kernel dimensionality reduction method. Different from the conventional convex relaxation technique, the proposed algorithm directly takes advantage of a binary search and an alternative optimization scheme to obtain optimal solutions efficiently. The experimental results demonstrate the effectiveness of the proposed method for supervised, unsupervised, and semisupervised scenarios. PMID:27247562
Regularized Embedded Multiple Kernel Dimensionality Reduction for Mine Signal Processing.
Li, Shuang; Liu, Bing; Zhang, Chen
2016-01-01
Traditional multiple kernel dimensionality reduction models are generally based on graph embedding and manifold assumption. But such assumption might be invalid for some high-dimensional or sparse data due to the curse of dimensionality, which has a negative influence on the performance of multiple kernel learning. In addition, some models might be ill-posed if the rank of matrices in their objective functions was not high enough. To address these issues, we extend the traditional graph embedding framework and propose a novel regularized embedded multiple kernel dimensionality reduction method. Different from the conventional convex relaxation technique, the proposed algorithm directly takes advantage of a binary search and an alternative optimization scheme to obtain optimal solutions efficiently. The experimental results demonstrate the effectiveness of the proposed method for supervised, unsupervised, and semisupervised scenarios.
Regularized Embedded Multiple Kernel Dimensionality Reduction for Mine Signal Processing
Directory of Open Access Journals (Sweden)
Shuang Li
2016-01-01
Full Text Available Traditional multiple kernel dimensionality reduction models are generally based on graph embedding and manifold assumption. But such assumption might be invalid for some high-dimensional or sparse data due to the curse of dimensionality, which has a negative influence on the performance of multiple kernel learning. In addition, some models might be ill-posed if the rank of matrices in their objective functions was not high enough. To address these issues, we extend the traditional graph embedding framework and propose a novel regularized embedded multiple kernel dimensionality reduction method. Different from the conventional convex relaxation technique, the proposed algorithm directly takes advantage of a binary search and an alternative optimization scheme to obtain optimal solutions efficiently. The experimental results demonstrate the effectiveness of the proposed method for supervised, unsupervised, and semisupervised scenarios.
Capturing Option Anomalies with a Variance-Dependent Pricing Kernel
DEFF Research Database (Denmark)
Christoffersen, Peter; Heston, Steven; Jacobs, Kris
2013-01-01
We develop a GARCH option model with a new pricing kernel allowing for a variance premium. While the pricing kernel is monotonic in the stock return and in variance, its projection onto the stock return is nonmonotonic. A negative variance premium makes it U shaped. We present new semiparametric...... evidence to confirm this U-shaped relationship between the risk-neutral and physical probability densities. The new pricing kernel substantially improves our ability to reconcile the time-series properties of stock returns with the cross-section of option prices. It provides a unified explanation...... for the implied volatility puzzle, the overreaction of long-term options to changes in short-term variance, and the fat tails of the risk-neutral return distribution relative to the physical distribution....
Heat kernel analysis for Bessel operators on symmetric cones
DEFF Research Database (Denmark)
Möllers, Jan
2014-01-01
. The heat kernel is explicitly given in terms of a multivariable $I$-Bessel function on $Ω$. Its corresponding heat kernel transform defines a continuous linear operator between $L^p$-spaces. The unitary image of the $L^2$-space under the heat kernel transform is characterized as a weighted Bergmann space...... on the complexification $G_{\\mathbb C}/K_{\\mathbb C}$ of $Ω$, the weight being expressed explicitly in terms of a multivariable $K$-Bessel function on $Ω$. Even in the special case of the symmetric cone $Ω=\\mathbb{R}_+$ these results seem to be new.......We investigate the heat equation corresponding to the Bessel operators on a symmetric cone $Ω=G/K$. These operators form a one-parameter family of elliptic self-adjoint second order differential operators and occur in the Lie algebra action of certain unitary highest weight representations...
Linear and kernel methods for multivariate change detection
DEFF Research Database (Denmark)
Canty, Morton J.; Nielsen, Allan Aasbjerg
2012-01-01
The iteratively reweighted multivariate alteration detection (IR-MAD) algorithm may be used both for unsupervised change detection in multi- and hyperspectral remote sensing imagery and for automatic radiometric normalization of multitemporal image sequences. Principal components analysis (PCA......), as well as maximum autocorrelation factor (MAF) and minimum noise fraction (MNF) analyses of IR-MAD images, both linear and kernel-based (nonlinear), may further enhance change signals relative to no-change background. IDL (Interactive Data Language) implementations of IR-MAD, automatic radiometric...... normalization, and kernel PCA/MAF/MNF transformations are presented that function as transparent and fully integrated extensions of the ENVI remote sensing image analysis environment. The train/test approach to kernel PCA is evaluated against a Hebbian learning procedure. Matlab code is also available...
Semisupervised kernel marginal Fisher analysis for face recognition.
Wang, Ziqiang; Sun, Xia; Sun, Lijun; Huang, Yuchun
2013-01-01
Dimensionality reduction is a key problem in face recognition due to the high-dimensionality of face image. To effectively cope with this problem, a novel dimensionality reduction algorithm called semisupervised kernel marginal Fisher analysis (SKMFA) for face recognition is proposed in this paper. SKMFA can make use of both labelled and unlabeled samples to learn the projection matrix for nonlinear dimensionality reduction. Meanwhile, it can successfully avoid the singularity problem by not calculating the matrix inverse. In addition, in order to make the nonlinear structure captured by the data-dependent kernel consistent with the intrinsic manifold structure, a manifold adaptive nonparameter kernel is incorporated into the learning process of SKMFA. Experimental results on three face image databases demonstrate the effectiveness of our proposed algorithm.
Weighted Feature Gaussian Kernel SVM for Emotion Recognition.
Wei, Wei; Jia, Qingxuan
2016-01-01
Emotion recognition with weighted feature based on facial expression is a challenging research topic and has attracted great attention in the past few years. This paper presents a novel method, utilizing subregion recognition rate to weight kernel function. First, we divide the facial expression image into some uniform subregions and calculate corresponding recognition rate and weight. Then, we get a weighted feature Gaussian kernel function and construct a classifier based on Support Vector Machine (SVM). At last, the experimental results suggest that the approach based on weighted feature Gaussian kernel function has good performance on the correct rate in emotion recognition. The experiments on the extended Cohn-Kanade (CK+) dataset show that our method has achieved encouraging recognition results compared to the state-of-the-art methods.
Weighted Feature Gaussian Kernel SVM for Emotion Recognition
Directory of Open Access Journals (Sweden)
Wei Wei
2016-01-01
Full Text Available Emotion recognition with weighted feature based on facial expression is a challenging research topic and has attracted great attention in the past few years. This paper presents a novel method, utilizing subregion recognition rate to weight kernel function. First, we divide the facial expression image into some uniform subregions and calculate corresponding recognition rate and weight. Then, we get a weighted feature Gaussian kernel function and construct a classifier based on Support Vector Machine (SVM. At last, the experimental results suggest that the approach based on weighted feature Gaussian kernel function has good performance on the correct rate in emotion recognition. The experiments on the extended Cohn-Kanade (CK+ dataset show that our method has achieved encouraging recognition results compared to the state-of-the-art methods.
Anomalous inelastic neutron scattering from calcite
International Nuclear Information System (INIS)
Dove, M.T.; Harris, M.J.; Winkler, B.; Hagen, M.E.; Keele Univ.; Powell, B.M.; Steigenberger, U.
1992-01-01
Inelastic neutron scattering measurements on calcite (CaCO 3 ) in its low temperature phase have revealed the existence of an unusual column of inelastic scattering at the wavevector corresponding to the F point of the high temperature Brillouin zone. At the same wavevector there is also a transverse acoustic soft mode and the column of scattering ranges in energy from zero up to the soft mode. The intensity of the anomalous scattering increases rapidly with temperature, and is consistent with an Arrhenius relation of the form exp(-T * /T), where T * = 1035 K. We speculate that this scattering arises from thermal fluctuations of the calcite structure into a different ordered structure, which is related to an ordering instability at the F point. Evidence for this possibility has also been obtained from lattice energy calculations. (author)
Single aflatoxin contaminated corn kernel analysis with fluorescence hyperspectral image
Yao, Haibo; Hruska, Zuzana; Kincaid, Russell; Ononye, Ambrose; Brown, Robert L.; Cleveland, Thomas E.
2010-04-01
Aflatoxins are toxic secondary metabolites of the fungi Aspergillus flavus and Aspergillus parasiticus, among others. Aflatoxin contaminated corn is toxic to domestic animals when ingested in feed and is a known carcinogen associated with liver and lung cancer in humans. Consequently, aflatoxin levels in food and feed are regulated by the Food and Drug Administration (FDA) in the US, allowing 20 ppb (parts per billion) limits in food and 100 ppb in feed for interstate commerce. Currently, aflatoxin detection and quantification methods are based on analytical tests including thin-layer chromatography (TCL) and high performance liquid chromatography (HPLC). These analytical tests require the destruction of samples, and are costly and time consuming. Thus, the ability to detect aflatoxin in a rapid, nondestructive way is crucial to the grain industry, particularly to corn industry. Hyperspectral imaging technology offers a non-invasive approach toward screening for food safety inspection and quality control based on its spectral signature. The focus of this paper is to classify aflatoxin contaminated single corn kernels using fluorescence hyperspectral imagery. Field inoculated corn kernels were used in the study. Contaminated and control kernels under long wavelength ultraviolet excitation were imaged using a visible near-infrared (VNIR) hyperspectral camera. The imaged kernels were chemically analyzed to provide reference information for image analysis. This paper describes a procedure to process corn kernels located in different images for statistical training and classification. Two classification algorithms, Maximum Likelihood and Binary Encoding, were used to classify each corn kernel into "control" or "contaminated" through pixel classification. The Binary Encoding approach had a slightly better performance with accuracy equals to 87% or 88% when 20 ppb or 100 ppb was used as classification threshold, respectively.
Uusijärvi, Helena; Chouin, Nicolas; Bernhardt, Peter; Ferrer, Ludovic; Bardiès, Manuel; Forssell-Aronsson, Eva
2009-08-01
Point kernels describe the energy deposited at a certain distance from an isotropic point source and are useful for nuclear medicine dosimetry. They can be used for absorbed-dose calculations for sources of various shapes and are also a useful tool when comparing different Monte Carlo (MC) codes. The aim of this study was to compare point kernels calculated by using the mixed MC code, PENELOPE (v. 2006), with point kernels calculated by using the condensed-history MC codes, ETRAN, GEANT4 (v. 8.2), and MCNPX (v. 2.5.0). Point kernels for electrons with initial energies of 10, 100, 500, and 1 MeV were simulated with PENELOPE. Spherical shells were placed around an isotropic point source at distances from 0 to 1.2 times the continuous-slowing-down-approximation range (R(CSDA)). Detailed (event-by-event) simulations were performed for electrons with initial energies of less than 1 MeV. For 1-MeV electrons, multiple scattering was included for energy losses less than 10 keV. Energy losses greater than 10 keV were simulated in a detailed way. The point kernels generated were used to calculate cellular S-values for monoenergetic electron sources. The point kernels obtained by using PENELOPE and ETRAN were also used to calculate cellular S-values for the high-energy beta-emitter, 90Y, the medium-energy beta-emitter, 177Lu, and the low-energy electron emitter, 103mRh. These S-values were also compared with the Medical Internal Radiation Dose (MIRD) cellular S-values. The greatest differences between the point kernels (mean difference calculated for distances, electrons was 1.4%, 2.5%, and 6.9% for ETRAN, GEANT4, and MCNPX, respectively, compared to PENELOPE, if omitting the S-values when the activity was distributed on the cell surface for 10-keV electrons. The largest difference between the cellular S-values for the radionuclides, between PENELOPE and ETRAN, was seen for 177Lu (1.2%). There were large differences between the MIRD cellular S-values and those obtained from
Rebootless Linux Kernel Patching with Ksplice Uptrack at BNL
International Nuclear Information System (INIS)
Hollowell, Christopher; Pryor, James; Smith, Jason
2012-01-01
Ksplice/Oracle Uptrack is a software tool and update subscription service which allows system administrators to apply security and bug fix patches to the Linux kernel running on servers/workstations without rebooting them. The RHIC/ATLAS Computing Facility (RACF) at Brookhaven National Laboratory (BNL) has deployed Uptrack on nearly 2,000 hosts running Scientific Linux and Red Hat Enterprise Linux. The use of this software has minimized downtime, and increased our security posture. In this paper, we provide an overview of Ksplice's rebootless kernel patch creation/insertion mechanism, and our experiences with Uptrack.
Aflatoxin detection in whole corn kernels using hyperspectral methods
Casasent, David; Chen, Xue-Wen
2004-03-01
Hyperspectral (HS) data for the inspection of whole corn kernels for aflatoxin is considered. The high-dimensionality of HS data requires feature extraction or selection for good classifier generalization. For fast and inexpensive data collection, only several features (λ responses) can be used. These are obtained by feature selection from the full HS response. A new high dimensionality branch and bound (HDBB) feature selection algorithm is used; it is found to be optimum, fast and very efficient. Initial results indicate that HS data is very promising for aflatoxin detection in whole kernel corn.
Source identity and kernel functions for Inozemtsev-type systems
Energy Technology Data Exchange (ETDEWEB)
Langmann, Edwin [Department of Theoretical Physics, Royal Institute of Technology KTH, SE-106 91 Stockholm (Sweden); Takemura, Kouichi [Department of Mathematics, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo 112-8551 (Japan)
2012-08-15
The Inozemtsev Hamiltonian is an elliptic generalization of the differential operator defining the BC{sub N} trigonometric quantum Calogero-Sutherland model, and its eigenvalue equation is a natural many-variable generalization of the Heun differential equation. We present kernel functions for Inozemtsev Hamiltonians and Chalykh-Feigin-Veselov-Sergeev-type deformations thereof. Our main result is a solution of a heat-type equation for a generalized Inozemtsev Hamiltonian which is the source of all these kernel functions. Applications are given, including a derivation of simple exact eigenfunctions and eigenvalues of the Inozemtsev Hamiltonian.
Q-branch Raman scattering and modern kinetic thoery
Energy Technology Data Exchange (ETDEWEB)
Monchick, L. [The Johns Hopkins Univ., Laurel, MD (United States)
1993-12-01
The program is an extension of previous APL work whose general aim was to calculate line shapes of nearly resonant isolated line transitions with solutions of a popular quantum kinetic equation-the Waldmann-Snider equation-using well known advanced solution techniques developed for the classical Boltzmann equation. The advanced techniques explored have been a BGK type approximation, which is termed the Generalized Hess Method (GHM), and conversion of the collision operator to a block diagonal matrix of symmetric collision kernels which then can be approximated by discrete ordinate methods. The latter method, which is termed the Collision Kernel method (CC), is capable of the highest accuracy and has been used quite successfully for Q-branch Raman scattering. The GHM method, not quite as accurate, is applicable over a wider range of pressures and has proven quite useful.
Energy Technology Data Exchange (ETDEWEB)
Brueckel, Thomas; Heger, Gernot; Richter, Dieter; Roth, Georg; Zorn, Reiner (eds.)
2010-07-01
The following topics are dealt with: Neutron sources, symmetry of crystals, diffraction, nanostructures investigated by small-angle neutron scattering, the structure of macromolecules, spin dependent and magnetic scattering, structural analysis, neutron reflectometry, magnetic nanostructures, inelastic scattering, strongly correlated electrons, dynamics of macromolecules, applications of neutron scattering. (HSI)
Energy Technology Data Exchange (ETDEWEB)
Brueckel, Thomas; Heger, Gernot; Richter, Dieter; Roth, Georg; Zorn, Reiner (eds.)
2013-07-01
The following topics are dealt with: Neutron sources, symmetry of crystals, nanostructures investigated by small-angle neutron scattering, structure of macromolecules, spin dependent and magnetic scattering, structural analysis, neutron reflectometry, magnetic nanostructures, inelastic neutron scattering, strongly correlated electrons, polymer dynamics, applications of neutron scattering. (HSI)
International Nuclear Information System (INIS)
Brueckel, Thomas; Heger, Gernot; Richter, Dieter; Roth, Georg; Zorn, Reiner
2010-01-01
The following topics are dealt with: Neutron sources, symmetry of crystals, diffraction, nanostructures investigated by small-angle neutron scattering, the structure of macromolecules, spin dependent and magnetic scattering, structural analysis, neutron reflectometry, magnetic nanostructures, inelastic scattering, strongly correlated electrons, dynamics of macromolecules, applications of neutron scattering. (HSI)
International Nuclear Information System (INIS)
Brueckel, Thomas; Heger, Gernot; Richter, Dieter; Roth, Georg; Zorn, Reiner
2013-01-01
The following topics are dealt with: Neutron sources, symmetry of crystals, nanostructures investigated by small-angle neutron scattering, structure of macromolecules, spin dependent and magnetic scattering, structural analysis, neutron reflectometry, magnetic nanostructures, inelastic neutron scattering, strongly correlated electrons, polymer dynamics, applications of neutron scattering. (HSI)
Directory of Open Access Journals (Sweden)
Chuang Lin
2015-01-01
Full Text Available Kernel Locality Preserving Projection (KLPP algorithm can effectively preserve the neighborhood structure of the database using the kernel trick. We have known that supervised KLPP (SKLPP can preserve within-class geometric structures by using label information. However, the conventional SKLPP algorithm endures the kernel selection which has significant impact on the performances of SKLPP. In order to overcome this limitation, a method named supervised kernel optimized LPP (SKOLPP is proposed in this paper, which can maximize the class separability in kernel learning. The proposed method maps the data from the original space to a higher dimensional kernel space using a data-dependent kernel. The adaptive parameters of the data-dependent kernel are automatically calculated through optimizing an objective function. Consequently, the nonlinear features extracted by SKOLPP have larger discriminative ability compared with SKLPP and are more adaptive to the input data. Experimental results on ORL, Yale, AR, and Palmprint databases showed the effectiveness of the proposed method.
Directory of Open Access Journals (Sweden)
Hailun Wang
2017-01-01
Full Text Available Support vector regression algorithm is widely used in fault diagnosis of rolling bearing. A new model parameter selection method for support vector regression based on adaptive fusion of the mixed kernel function is proposed in this paper. We choose the mixed kernel function as the kernel function of support vector regression. The mixed kernel function of the fusion coefficients, kernel function parameters, and regression parameters are combined together as the parameters of the state vector. Thus, the model selection problem is transformed into a nonlinear system state estimation problem. We use a 5th-degree cubature Kalman filter to estimate the parameters. In this way, we realize the adaptive selection of mixed kernel function weighted coefficients and the kernel parameters, the regression parameters. Compared with a single kernel function, unscented Kalman filter (UKF support vector regression algorithms, and genetic algorithms, the decision regression function obtained by the proposed method has better generalization ability and higher prediction accuracy.
Ignition parameters and early flame kernel development of laser-ignited combustible gas mixtures
International Nuclear Information System (INIS)
Kopecek, H.; Wintner, E.; Ruedisser, D.; Iskra, K.; Neger, T.
2002-01-01
Full text: Laser induced breakdown of focused pulsed laser radiation, the subsequent plasma formation and thermalization offers a possibility of ignition of combustible gas mixtures free from electrode interferences, an arbitrary choice of the location within the medium and exact timing regardless of the degree of turbulence. The development and the decreasing costs of solid state laser technologies approach the pay-off for the higher complexity of such an ignition system due to several features unique to laser ignition. The feasability of laser ignition was demonstrated in an 1.5 MW(?) natural gas engine, and several investigations were performed to determine optimal ignition energies, focus shapes and laser wavelengths. The early flame kernel development was investigated by time resolved planar laser induced fluorescence of the OH-radical which occurs predominantly in the flame front. The flame front propagation showed typical features like toroidal initial flame development, flame front return and highly increased flame speed along the laser focus axis. (author)
Bound states and scattering in four-body systems
International Nuclear Information System (INIS)
Narodetsky, I.M.
1979-01-01
It is the purpose of this review to provide the clear and elementary introduction in the integral equation method and to demonstrate explicitely its usefulness for the physical applications. The existing results concerning the application of the integral equation technique for the four-nucleon bound states and scattering are reviewed.The treatment is based on the quasiparticle approach that permits the simple interpretation of the equations in terms of quasiparticle scattering. The mathematical basis for the quasiparticle approach is the Hilbert-Schmidt theorem of the Fredholm integral equation theory. This paper contains the detailed discussion of the Hilbert-Schmidt expansion as applied to the 2-particle amplitudes and to the 3 + 1 and 2 + 2 amplitudes which are the kernels of the four-body equations. The review contains essentially the discussion of the four-body quasiparticle equations and results obtained for bound states and scattering
The boundary sources method with arbitrary order anisotropic scattering
International Nuclear Information System (INIS)
Gert Van den, Eynde; Beauwens, R.; Mund, E.
2005-01-01
The Boundary Sources Method (BSM) is an integral method for solving the one-speed neutron transport equation that makes capital out of the exact knowledge of a transport kernel for the classical geometries: planar, spherical and cylindrical. We have developed a slab (multi-region) BSM code that allows for arbitrary order anisotropic scattering. The basic ingredient of our method is the calculation of (angular moments of) infinite medium Green's functions. We have used the singular Eigen-expansion (SEE) method developed for anisotropic scattering by Mika and Case and have developed a robust and accurate method to calculate its two parts: the discrete and continuum spectrum. We use several one-dimensional neutron transport benchmarks to show its high accuracy. We have treated 3 types of problems: 2-cell (U-H 2 O) disadvantage factors, the Reed problem and an extreme scattering problem
Collinear limits beyond the leading order from the scattering equations
Energy Technology Data Exchange (ETDEWEB)
Nandan, Dhritiman; Plefka, Jan; Wormsbecher, Wadim [Institut für Physik and IRIS Adlershof, Humboldt-Universität zu Berlin,Zum Großen Windkanal 6, D-12489 Berlin (Germany)
2017-02-08
The structure of tree-level scattering amplitudes for collinear massless bosons is studied beyond their leading splitting function behavior. These near-collinear limits at sub-leading order are best studied using the Cachazo-He-Yuan (CHY) formulation of the S-matrix based on the scattering equations. We compute the collinear limits for gluons, gravitons and scalars. It is shown that the CHY integrand for an n-particle gluon scattering amplitude in the collinear limit at sub-leading order is expressed as a convolution of an (n−1)-particle gluon integrand and a collinear kernel integrand, which is universal. Our representation is shown to obey recently proposed amplitude relations in which the collinear gluons of same helicity are replaced by a single graviton. Finally, we extend our analysis to effective field theories and study the collinear limit of the non-linear sigma model, Einstein-Maxwell-Scalar and Yang-Mills-Scalar theory.
The dipole form of the gluon part of the BFKL kernel
International Nuclear Information System (INIS)
Fadin, V.S.; Fiore, R.; Grabovsky, A.V.; Papa, A.
2007-01-01
The dipole form of the gluon part of the color singlet BFKL kernel in the next-to-leading order (NLO) is obtained in the coordinate representation by direct transfer from the momentum representation, where the kernel was calculated before. With this paper the transformation of the NLO BFKL kernel to the dipole form, started a few months ago with the quark part of the kernel, is completed
Pest development possibility in storage on the kernels and spikes of spelt wheat (Triticum spelta)
Almaši, Radmila; Poslončec, Danijela
2012-01-01
Storing the spelt wheat (Triticum spelta) depends of the type of storage. If we stored spikes, which contains two kernel of spelt tightly wrapped with tailings, development and reproduction of the most important pests is limited or impossible. Great impacts on the stored pests progeny and percentage of damaged kernels have the number of available kernel and the way of storage (kernels-spikes). Grain moth (Sitotroga cerealella Oliv.) developed more numerous progeny when spelt wheat stores in k...
Energy Technology Data Exchange (ETDEWEB)
Brueckel, Thomas; Heger, Gernot; Richter, Dieter; Roth, Georg; Zorn, Reiner (eds.)
2010-07-01
The following topics are dealt with: Neutron sources, neutron properties and elastic scattering, correlation functions measured by scattering experiments, symmetry of crystals, applications of neutron scattering, polarized-neutron scattering and polarization analysis, structural analysis, magnetic and lattice excitation studied by inelastic neutron scattering, macromolecules and self-assembly, dynamics of macromolecules, correlated electrons in complex transition-metal oxides, surfaces, interfaces, and thin films investigated by neutron reflectometry, nanomagnetism. (HSI)
International Nuclear Information System (INIS)
Brueckel, Thomas; Heger, Gernot; Richter, Dieter; Roth, Georg; Zorn, Reiner
2010-01-01
The following topics are dealt with: Neutron sources, neutron properties and elastic scattering, correlation functions measured by scattering experiments, symmetry of crystals, applications of neutron scattering, polarized-neutron scattering and polarization analysis, structural analysis, magnetic and lattice excitation studied by inelastic neutron scattering, macromolecules and self-assembly, dynamics of macromolecules, correlated electrons in complex transition-metal oxides, surfaces, interfaces, and thin films investigated by neutron reflectometry, nanomagnetism. (HSI)
Effects of substituting groundnut cake with acacia seed kernel meal ...
African Journals Online (AJOL)
The study examined the effects of replacing groundnut cake (GNC) with Acacia nilotica seed kernel meal (ASKM) in the diets of broilers and the effects of such on ... Serum metabolites were not affected by the treatment except alkaline phosphatasc and billirubin that were significantly (P < 0.05) lowered by 20% inclusion of ...
Production of glycerol from palm kernel oil | Antia | Nigerian Journal ...
African Journals Online (AJOL)
Glycerol production using Palm Kernel Oil (PKO) as a potential raw material was investigated. PKO was optimally hydrolyzed at 268 °C and 500psi (34 atm) pressure using only water. A 96.85 percent maximum yield of the extent of hydrolysis at 61.86 percent water and 38.14 percent oil was achieved The percentage Df ...
Acetolactate Synthase Activity in Developing Maize (Zea mays L.) Kernels
Muhitch, Michael J.
1988-01-01
Acetolactate synthase (EC 4.1.3.18) activity was examined in maize (Zea mays L.) endosperm and embryos as a function of kernel development. When assayed using unpurified homogenates, embryo acetolactate synthase activity appeared less sensitive to inhibition by leucine + valine and by the imidazolinone herbicide imazapyr than endosperm acetolactate synthase activity. Evidence is presented to show that pyruvate decarboxylase contributes to apparent acetolactate synthase activity in crude embryo extracts and a modification of the acetolactate synthase assay is proposed to correct for the presence of pyruvate decarboxylase in unpurified plant homogenates. Endosperm acetolactate synthase activity increased rapidly during early kernel development, reaching a maximum of 3 micromoles acetoin per hour per endosperm at 25 days after pollination. In contrast, embryo activity was low in young kernels and steadily increased throughout development to a maximum activity of 0.24 micromole per hour per embryo by 45 days after pollination. The sensitivity of both endosperm and embryo acetolactate synthase activities to feedback inhibition by leucine + valine did not change during kernel development. The results are compared to those found for other enzymes of nitrogen metabolism and discussed with respect to the potential roles of the embryo and endosperm in providing amino acids for storage protein synthesis. PMID:16665871
Structured Kernel Subspace Learning for Autonomous Robot Navigation.
Kim, Eunwoo; Choi, Sungjoon; Oh, Songhwai
2018-02-14
This paper considers two important problems for autonomous robot navigation in a dynamic environment, where the goal is to predict pedestrian motion and control a robot with the prediction for safe navigation. While there are several methods for predicting the motion of a pedestrian and controlling a robot to avoid incoming pedestrians, it is still difficult to safely navigate in a dynamic environment due to challenges, such as the varying quality and complexity of training data with unwanted noises. This paper addresses these challenges simultaneously by proposing a robust kernel subspace learning algorithm based on the recent advances in nuclear-norm and l 1 -norm minimization. We model the motion of a pedestrian and the robot controller using Gaussian processes. The proposed method efficiently approximates a kernel matrix used in Gaussian process regression by learning low-rank structured matrix (with symmetric positive semi-definiteness) to find an orthogonal basis, which eliminates the effects of erroneous and inconsistent data. Based on structured kernel subspace learning, we propose a robust motion model and motion controller for safe navigation in dynamic environments. We evaluate the proposed robust kernel learning in various tasks, including regression, motion prediction, and motion control problems, and demonstrate that the proposed learning-based systems are robust against outliers and outperform existing regression and navigation methods.
Music emotion detection using hierarchical sparse kernel machines.
Chin, Yu-Hao; Lin, Chang-Hong; Siahaan, Ernestasia; Wang, Jia-Ching
2014-01-01
For music emotion detection, this paper presents a music emotion verification system based on hierarchical sparse kernel machines. With the proposed system, we intend to verify if a music clip possesses happiness emotion or not. There are two levels in the hierarchical sparse kernel machines. In the first level, a set of acoustical features are extracted, and principle component analysis (PCA) is implemented to reduce the dimension. The acoustical features are utilized to generate the first-level decision vector, which is a vector with each element being a significant value of an emotion. The significant values of eight main emotional classes are utilized in this paper. To calculate the significant value of an emotion, we construct its 2-class SVM with calm emotion as the global (non-target) side of the SVM. The probability distributions of the adopted acoustical features are calculated and the probability product kernel is applied in the first-level SVMs to obtain first-level decision vector feature. In the second level of the hierarchical system, we merely construct a 2-class relevance vector machine (RVM) with happiness as the target side and other emotions as the background side of the RVM. The first-level decision vector is used as the feature with conventional radial basis function kernel. The happiness verification threshold is built on the probability value. In the experimental results, the detection error tradeoff (DET) curve shows that the proposed system has a good performance on verifying if a music clip reveals happiness emotion.
Recent sea level change analysed with kernel EOF
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg; Andersen, Ole Baltazar; Knudsen, Per
2009-01-01
-2008. Preliminary analysis shows some interesting features related to climate change and particularly the pulsing of the El Niño/Southern Oscillation. Large scale ocean events associated with the El Niño/Southern Oscillation related signals are conveniently concentrated in the first SSH kernel EOF modes....
Effect of Coconut ( cocus Nucifera ) and Palm Kernel ( eleasis ...
African Journals Online (AJOL)
Effect of Coconut ( cocus Nucifera ) and Palm Kernel ( eleasis Guinensis ) Oil Supplmented Diets on Serum Lipid Profile of Albino Wistar Rats. ... were fed normal rat pellet. At the end of the feeding period, animals were anaesthetized under chloroform vapor, dissected and blood obtained via cardiac puncture into tubes.
potential use of mangifera indica seed kernel and citrus aurantiifolia ...
African Journals Online (AJOL)
HOD
*Corresponding author tel: + 234 – 803 – 823 – 1628, currently a doctoral student at the Department of Civil. Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, GHANA. POTENTIAL USE OF MANGIFERA INDICA SEED KERNEL AND CITRUS. AURANTIIFOLIA SEED IN WATER DISINFECTION.
Briquetting of Palm Kernel Shell | Ugwu | Journal of Applied ...
African Journals Online (AJOL)
In several developing countries, briquettes from agricultural residues contribute significantly to the energy mix especially for small scale and household requirements. In this work, briquettes were produced from Palm kernel shell. This was achieved by carbonising the shell to get the charcoal followed by the pulverization of ...
Hollow microspheres with a tungsten carbide kernel for PEMFC application.
d'Arbigny, Julien Bernard; Taillades, Gilles; Marrony, Mathieu; Jones, Deborah J; Rozière, Jacques
2011-07-28
Tungsten carbide microspheres comprising an outer shell and a compact kernel prepared by a simple hydrothermal method exhibit very high surface area promoting a high dispersion of platinum nanoparticles, and an exceptionally high electrochemically active surface area (EAS) stability compared to the usual Pt/C electrocatalysts used for PEMFC application.
Moderate deviations principles for the kernel estimator of ...
African Journals Online (AJOL)
Abstract. The aim of this paper is to provide pointwise and uniform moderate deviations principles for the kernel estimator of a nonrandom regression function. Moreover, we give an application of these moderate deviations principles to the construction of condence regions for the regression function. Resume. L'objectif de ...
Matrix kernels for MEG and EEG source localization and imaging
Energy Technology Data Exchange (ETDEWEB)
Mosher, J.C.; Lewis, P.S. [Los Alamos National Lab., NM (United States); Leahy, R.M. [University of Southern California, Los Angeles, CA (United States)
1994-12-31
The most widely used model for electroencephalography (EEG) and magnetoencephalography (MEG) assumes a quasi-static approximation of Maxwell`s equations and a piecewise homogeneous conductor model. Both models contain an incremental field element that linearly relates an incremental source element (current dipole) to the field or voltage at a distant point. The explicit form of the field element is dependent on the head modeling assumptions and sensor configuration. Proper characterization of this incremental element is crucial to the inverse problem. The field element can be partitioned into the product of a vector dependent on sensor characteristics and a matrix kernel dependent only on head modeling assumptions. We present here the matrix kernels for the general boundary element model (BEM) and for MEG spherical models. We show how these kernels are easily interchanged in a linear algebraic framework that includes sensor specifics such as orientation and gradiometer configuration. We then describe how this kernel is easily applied to ``gain`` or ``transfer`` matrices used in multiple dipole and source imaging models.