separation of oil palm kernel and shell mixture using soil and palm ...
African Journals Online (AJOL)
user
Among the media used, "Ikwube" was found to be comparable to clay at a medium-to-water ratio of 0.30:1 giving 98.93% efficiency. Thus, it is recommended that "Ikwube" can be used in place of clay for wet separation. Key words: Oil Palm Kernel, Kernel Shell, Separation, Clay Soil, “Ikwube” (anthill). 1. INTRODUCTION.
Separation of oil palm kernel and shell mixture using soil and palm ...
African Journals Online (AJOL)
This study investigated the possibility of separating oil palm kernel and shell mixture using media other than clay in wet separation. The separation efficiency of each medium ["Ikwube" (anthill), palm ash and sandy loam soil] was compared with that of clay. The effect of media type, specific gravity of the slurry, pH and slurry ...
Separation of oil palm shell and kernel by using kaolinite media
Sukpong Sirinupong; Manoon Masniyom; Lek Sikong
2003-01-01
The objective of this research is to investigate the possibility of using kaolinite from Ranong province as media in the oil palm shell and kernel separation process by means of heavy media separation. The effect of specific gravity of the slurry, type and amount of dispersant and type of clays on suspension of media and efficiency of separation were studied. It was found that the specific gravity of oil palm shell and kernel are 1.40 and 1.20 respectively. While the average specific gravity ...
Formalisation of a Separation Micro-Kernel for Common Criteria Certification
Butterfield, Andrew; Sanan, David; Hinchey, Mike
2014-08-01
The project Methods and Tools for On-Board Software Engineering (MTOBSE) 1 was a feasibility study into the ability to certify a time- space partitioning kernel aiming at Common Criteria (CC) evaluation assurance level 5+, in conformance with the Separation Kernel Protection Profile (SKPP) [1]. Here we describe the aspects of CC evaluation that involve using formal methods techniques as part of the assurance case. We describe a reference specification we wrote for a Time-Space Partitioning (TSP) operating system kernel, and how we formalised this using the Isabelle/HOL theorem proving framework. We also describe how we obtained a formal Isabelle/HOL model from C code (using XtratuM as a test case), and how this would be related to the formalised specification. We conclude with a discussion of the feasibility and likely cost of such a verification effort, and ideas for the follow-on steps for this activity.
Separation of oil palm shell and kernel by using kaolinite media
Directory of Open Access Journals (Sweden)
Sukpong Sirinupong
2003-05-01
Full Text Available The objective of this research is to investigate the possibility of using kaolinite from Ranong province as media in the oil palm shell and kernel separation process by means of heavy media separation. The effect of specific gravity of the slurry, type and amount of dispersant and type of clays on suspension of media and efficiency of separation were studied. It was found that the specific gravity of oil palm shell and kernel are 1.40 and 1.20 respectively. While the average specific gravity of kaolinite grade MRD-B85, RANONG-325 and commercial clay from Univanich Group. PCL., are 2.54, 2.65 and 2.46 respectively. It was apparent that the viscosity of clay slurry increased with the specific gravity of the slurry. For MRD-B85 and RANONG- 325 clays which have the average particle sizes of 10 and 12 microns, the pH of their slurries of about 5.84 and 6.33 respectively were obtained and at these conditions stability of the slurry rarely occurred and they could not be used for separation. However, these clays can also be utilized as media when dispersant such asCalgon or sodium silicate is applied to their slurries. It was found that the efficiency of separation depends on specific gravity and viscosity of the slurry, type and particle size of kaolinite and dosage of dispersant. The optimum separating conditions for MRD-B85 clay were the dosage of Calgon of 0.15% (or 1.5 kg/t of clay at the specific gravity of the slurry of 1.20-1.24 (27-32% Solids in which a pH of 6.14 and viscosity of 104 cP to very low value (could not be measured were obtained. Thus, kernel yielded 97.57-100% and shell contamination of 1.48-6.32% was achieved. While sodium silicate was applied to the slurry about 0.15% at the specific gravity of 1.22, pH of 6.74 and viscosity of 238 cP were obtained and kernel could be recovered 100% with shell contamination of 8.36%. When 0.15% Calgon or 0.25% sodium silicate was introduced to the RANONG-325 clay slurry at the specific gravity
Dry Separation of Palm Kernel and Palm Shell Using a Novel Five-Stage Winnowing Column System
Directory of Open Access Journals (Sweden)
Rohaya Mohamed Halim
2016-04-01
Full Text Available The conventional separation system for the recovery of palm kernel from its palm shell–kernel mixture using water as process media generates a considerable amount of waste effluent that harms the environment. The aim of this study is to develop a dry separation process for the recovery of palm kernel by using winnowing columns. A commercial system consisting of a series of five winnowing columns was developed and installed at a local palm oil mill. The system parameters, including column height, blower capacity, airflow rate and mesh screen size for shell removal, were studied and optimized to ensure good separation of kernel and shell in the column to enable collection of different sizes of kernel and shell at each column outlet. The performance of the separation process was evaluated in terms of its kernel losses, dirt content and kernel recovery rate. The average kernel losses based on oil palm fresh fruit bunches processed were found to vary from 0.11 to 0.30 wt %, with most of the values obtained being below the targeted limit of 0.30 wt %. The dirt content was in the range 4.56–6.03 wt %, which was mostly below the targeted limit of 5.5 wt %. The kernel recovery rate was in the range 5.69–6.89 wt %, with most of the values achieving the minimum targeted limit of 6.00 wt %. The system operates under completely dry conditions and, therefore, produces zero waste effluent.
Wang, Tao; Lu, Shengmin; Xia, Qile; Fang, Zhongxiang; Johnson, Stuart
2015-01-15
To utilize the low-value thinned bayberry (Myrica rubra Sieb. et Zucc) kernels (TBKs) waste, an efficient method using macroporous adsorption resins (MARs) for separation and purification of amygdalin from TBKs crude extracts was developed. An aqueous crude sample was prepared from a methanol TBK extract, followed by resin separation. A series of MARs were initially screened for adsorption/desorption of amygdalin in the extract, and D101 was selected for characterization and method development. The static adsorption data of amygdalin on D101 was best fitted to the pseudo-second-order kinetics model. The solute affinity toward D101 at 30 °C was described and the equilibrium experimental data were well-fitted to Langmuir and Freundlich isotherms. Through one cycle of dynamic adsorption/desorption, the purity of amygdalin in the extract, determined by HPLC, increased about 17-fold from 4.8% to 82.0%, with 77.9% recovery. The results suggested that D101 resin effectively separate amygdalin from TBKs. Copyright © 2014 Elsevier B.V. All rights reserved.
Axially deformed relativistic Hartree Bogoliubov theory with a separable pairing force
Tian, Yuan; Ma, Zhong-Yu; Ring, P.
2009-08-01
A separable form of pairing interaction in the 1S0 channel has been introduced and successfully applied in the description of both static and dynamic properties of superfluid nuclei. By adjusting the parameters to reproduce the pairing properties of the Gogny force in nuclear matter, this separable pairing force is successful in depicting the pairing properties of ground states and vibrational excitations of spherical nuclei on almost the same footing as the original Gogny force. In this article, we extend these investigations for relativistic Hartree-Bogoliubov theory in deformed nuclei with axial symmetry (RHBZ) using the same separable pairing interaction. To preserve translational invariance we construct one- and two-dimensional Talmi-Moshinsky brackets for the cylindrical harmonic oscillator basis. We show that the matrix elements of this force can then be expanded in a series of separable terms. The convergence of this expansion is investigated for various deformations. We observe a relatively fast convergence. This allows for a considerable reduction in computing time as compared to RHBZ calculations with the full Gogny force in the pairing channel. As an example we solve the RHBZ equations with this separable pairing force for the ground states of the chain of Sm isotopes. Good agreement with the experimental data as well as with other theoretical results is achieved.
Biorefinery methods for separation of protein and oil fractions from rubber seed kernel
Widyarani, R.; Ratnaningsih, E.; Sanders, J.P.M.; Bruins, M.E.
2014-01-01
Biorefinery of rubber seeds can generate additional income for farmers, who already grow rubber trees for latex production. The aim of this study was to find the best method for protein and oil production from rubber seed kernel, with focus on protein recovery. Different pre-treatments and oil
Rebolini, Elisa
2015-01-01
We present a range-separated linear-response time-dependent density-functional theory (TDDFT) which combines a density-functional approximation for the short-range response kernel and a frequency-dependent second-order Bethe-Salpeter approximation for the long-range response kernel. This approach goes beyond the adiabatic approximation usually used in linear-response TDDFT and aims at improving the accuracy of calculations of electronic excitation energies of molecular systems. A detailed derivation of the frequency-dependent second-order Bethe-Salpeter correlation kernel is given using many-body Green-function theory. Preliminary tests of this range-separated TDDFT method are presented for the calculation of excitation energies of four small molecules: N2, CO2, H2CO, and C2H4. The results suggest that the addition of the long-range second-order Bethe-Salpeter correlation kernel overall slightly improves the excitation energies.
Semisupervised kernel matrix learning by kernel propagation.
Hu, Enliang; Chen, Songcan; Zhang, Daoqiang; Yin, Xuesong
2010-11-01
The goal of semisupervised kernel matrix learning (SS-KML) is to learn a kernel matrix on all the given samples on which just a little supervised information, such as class label or pairwise constraint, is provided. Despite extensive research, the performance of SS-KML still leaves some space for improvement in terms of effectiveness and efficiency. For example, a recent pairwise constraints propagation (PCP) algorithm has formulated SS-KML into a semidefinite programming (SDP) problem, but its computation is very expensive, which undoubtedly restricts PCPs scalability in practice. In this paper, a novel algorithm, called kernel propagation (KP), is proposed to improve the comprehensive performance in SS-KML. The main idea of KP is first to learn a small-sized sub-kernel matrix (named seed-kernel matrix) and then propagate it into a larger-sized full-kernel matrix. Specifically, the implementation of KP consists of three stages: 1) separate the supervised sample (sub)set X(l) from the full sample set X; 2) learn a seed-kernel matrix on X(l) through solving a small-scale SDP problem; and 3) propagate the learnt seed-kernel matrix into a full-kernel matrix on X . Furthermore, following the idea in KP, we naturally develop two conveniently realizable out-of-sample extensions for KML: one is batch-style extension, and the other is online-style extension. The experiments demonstrate that KP is encouraging in both effectiveness and efficiency compared with three state-of-the-art algorithms and its related out-of-sample extensions are promising too.
Demianski, Marek
2013-01-01
Relativistic Astrophysics brings together important astronomical discoveries and the significant achievements, as well as the difficulties in the field of relativistic astrophysics. This book is divided into 10 chapters that tackle some aspects of the field, including the gravitational field, stellar equilibrium, black holes, and cosmology. The opening chapters introduce the theories to delineate gravitational field and the elements of relativistic thermodynamics and hydrodynamics. The succeeding chapters deal with the gravitational fields in matter; stellar equilibrium and general relativity
An Analysis of Three Kernel-based Multilevel Security Architectures
National Research Council Canada - National Science Library
Levin, Timothy E; Irvine, Cynthia E; Nguyen, Thuy D
2006-01-01
...). This paper provides an analysis of the relative merits of three architectural types one based on a traditional separation kernel, another based on a security kernel, and a third based on a high...
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.
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.
Kernel Factory: An Ensemble of Kernel Machines
M. BALLINGS; D. VAN DEN POEL
2012-01-01
We propose an ensemble method for kernel machines. The training data is randomly split into a number of mutually exclusive partitions defined by a row and column parameter. Each partition forms an input space and is transformed by a kernel function into a kernel matrix K. Subsequently, each K is used as training data for a base binary classifier (Random Forest). This results in a number of predictions equal to the number of partitions. A weighted average combines the predictions into one fina...
Haba, Z
2009-02-01
We discuss relativistic diffusion in proper time in the approach of Schay (Ph.D. thesis, Princeton University, Princeton, NJ, 1961) and Dudley [Ark. Mat. 6, 241 (1965)]. We derive (Langevin) stochastic differential equations in various coordinates. We show that in some coordinates the stochastic differential equations become linear. We obtain momentum probability distribution in an explicit form. We discuss a relativistic particle diffusing in an external electromagnetic field. We solve the Langevin equations in the case of parallel electric and magnetic fields. We derive a kinetic equation for the evolution of the probability distribution. We discuss drag terms leading to an equilibrium distribution. The relativistic analog of the Ornstein-Uhlenbeck process is not unique. We show that if the drag comes from a diffusion approximation to the master equation then its form is strongly restricted. The drag leading to the Tsallis equilibrium distribution satisfies this restriction whereas the one of the Jüttner distribution does not. We show that any function of the relativistic energy can be the equilibrium distribution for a particle in a static electric field. A preliminary study of the time evolution with friction is presented. It is shown that the problem is equivalent to quantum mechanics of a particle moving on a hyperboloid with a potential determined by the drag. A relation to diffusions appearing in heavy ion collisions is briefly discussed.
Price, R H
1993-01-01
Work reported in the workshop on relativistic astrophysics spanned a wide varicy of topics. Two speciﬁc areas seemed of particular interest. Much attention was focussed on gravitational wave sources, especially on the waveforms they produce, and progress was reported in theoretical and observational aspects of accretion disks.
Sahoo, Raghunath
2016-01-01
This lecture note covers Relativistic Kinematics, which is very useful for the beginners in the field of high-energy physics. A very practical approach has been taken, which answers "why and how" of the kinematics useful for students working in the related areas.
Balog, Matej; Lakshminarayanan, B.; Ghahramani, Zoubin; Roy, DM; Teh, YW
2016-01-01
We introduce the Mondrian kernel, a fast $\\textit{random feature}$ approximation to the Laplace kernel. It is suitable for both batch and online learning, and admits a fast kernel-width-selection procedure as the random features can be re-used efficiently for all kernel widths. The features are constructed by sampling trees via a Mondrian process [Roy and Teh, 2009], and we highlight the connection to Mondrian forests [Lakshminarayanan et al., 2014], where trees are also sampled via a Mondria...
Hakim, Rémi
1994-01-01
Il existe à l'heure actuelle un certain nombre de théories relativistes de la gravitation compatibles avec l'expérience et l'observation. Toutefois, la relativité générale d'Einstein fut historiquement la première à fournir des résultats théoriques corrects en accord précis avec les faits.
PERBANDINGAN PEMULUSAN KERNEL DAN SPLINE
Erfiani Erfiani; Aji Hamim Wigena; Aunuddin Aunuddin
2014-01-01
Pendugaan kepekatan kernel dan spline termasuk pendugaan kepekatan nonparametrik. Perilaku pemulus spline terletak dipertengahan antara pemulus kernel yang konstan dan pemulus kernel yang tidak konstan. Pada kasus n besar dan λ tertentu fungsi pembobot spline dapat didekati oleh fungsi kernel. Perbandingan pemulus spline dan kernel secara empirik dilakukan dengan menggunakan data simulasi yang dicobakan pada berbagai lebar jendela kernel serta fungsi spline pada berbagai jumlah kn...
Relativistic magnetohydrodynamics
Hernandez, Juan; Kovtun, Pavel
2017-05-01
We present the equations of relativistic hydrodynamics coupled to dynamical electromagnetic fields, including the effects of polarization, electric fields, and the derivative expansion. We enumerate the transport coefficients at leading order in derivatives, including electrical conductivities, viscosities, and thermodynamic coefficients. We find the constraints on transport coefficients due to the positivity of entropy production, and derive the corresponding Kubo formulas. For the neutral state in a magnetic field, small fluctuations include Alfvén waves, magnetosonic waves, and the dissipative modes. For the state with a non-zero dynamical charge density in a magnetic field, plasma oscillations gap out all propagating modes, except for Alfvén-like waves with a quadratic dispersion relation. We relate the transport coefficients in the "conventional" magnetohydrodynamics (formulated using Maxwell's equations in matter) to those in the "dual" version of magnetohydrodynamics (formulated using the conserved magnetic flux).
Leardini, Fabrice
2013-01-01
This manuscript presents a problem on special relativity theory (SRT) which embodies an apparent paradox relying on the concept of simultaneity. The problem is represented in the framework of Greek epic poetry and structured in a didactic way. Owing to the characteristic properties of Lorenz transformations, three events which are simultaneous in a given inertial reference system, occur at different times in the other two reference frames. In contrast to the famous twin paradox, in the present case there are three, not two, different inertial observers. This feature provides a better framework to expose some of the main characteristics of SRT, in particular, the concept of velocity and the relativistic rule of addition of velocities.
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
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
Mixture Density Mercer Kernels
National Aeronautics and Space Administration — We present a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture...
Kernelized Bayesian Matrix Factorization.
Gönen, Mehmet; Kaski, Samuel
2014-10-01
We extend kernelized matrix factorization with a full-Bayesian treatment and with an ability to work with multiple side information sources expressed as different kernels. Kernels have been introduced to integrate side information about the rows and columns, which is necessary for making out-of-matrix predictions. We discuss specifically binary output matrices but extensions to realvalued matrices are straightforward. We extend the state of the art in two key aspects: (i) A full-conjugate probabilistic formulation of the kernelized matrix factorization enables an efficient variational approximation, whereas full-Bayesian treatments are not computationally feasible in the earlier approaches. (ii) Multiple side information sources are included, treated as different kernels in multiple kernel learning which additionally reveals which side sources are informative. We then show that the framework can also be used for supervised and semi-supervised multilabel classification and multi-output regression, by considering samples and outputs as the domains where matrix factorization operates. Our method outperforms alternatives in predicting drug-protein interactions on two data sets. On multilabel classification, our algorithm obtains the lowest Hamming losses on 10 out of 14 data sets compared to five state-of-the-art multilabel classification algorithms. We finally show that the proposed approach outperforms alternatives in multi-output regression experiments on a yeast cell cycle data set.
Local Image Descriptors Using Supervised Kernel ICA
Yamazaki, Masaki; Fels, Sidney
PCA-SIFT is an extension to SIFT which aims to reduce SIFT's high dimensionality (128 dimensions) by applying PCA to the gradient image patches. However PCA is not a discriminative representation for recognition due to its global feature nature and unsupervised algorithm. In addition, linear methods such as PCA and ICA can fail in the case of non-linearity. In this paper, we propose a new discriminative method called Supervised Kernel ICA (SKICA) that uses a non-linear kernel approach combined with Supervised ICA-based local image descriptors. Our approach blends the advantages of supervised learning with nonlinear properties of kernels. Using five different test data sets we show that the SKICA descriptors produce better object recognition performance than other related approaches with the same dimensionality. The SKICA-based representation has local sensitivity, non-linear independence and high class separability providing an effective method for local image descriptors.
Cattaneo, Carlo
2011-01-01
This title includes: Pham Mau Quam: Problemes mathematiques en hydrodynamique relativiste; A. Lichnerowicz: Ondes de choc, ondes infinitesimales et rayons en hydrodynamique et magnetohydrodynamique relativistes; A.H. Taub: Variational principles in general relativity; J. Ehlers: General relativistic kinetic theory of gases; K. Marathe: Abstract Minkowski spaces as fibre bundles; and, G. Boillat: Sur la propagation de la chaleur en relativite.
Contingent kernel density estimation.
Directory of Open Access Journals (Sweden)
Scott Fortmann-Roe
Full Text Available Kernel density estimation is a widely used method for estimating a distribution based on a sample of points drawn from that distribution. Generally, in practice some form of error contaminates the sample of observed points. Such error can be the result of imprecise measurements or observation bias. Often this error is negligible and may be disregarded in analysis. In cases where the error is non-negligible, estimation methods should be adjusted to reduce resulting bias. Several modifications of kernel density estimation have been developed to address specific forms of errors. One form of error that has not yet been addressed is the case where observations are nominally placed at the centers of areas from which the points are assumed to have been drawn, where these areas are of varying sizes. In this scenario, the bias arises because the size of the error can vary among points and some subset of points can be known to have smaller error than another subset or the form of the error may change among points. This paper proposes a "contingent kernel density estimation" technique to address this form of error. This new technique adjusts the standard kernel on a point-by-point basis in an adaptive response to changing structure and magnitude of error. In this paper, equations for our contingent kernel technique are derived, the technique is validated using numerical simulations, and an example using the geographic locations of social networking users is worked to demonstrate the utility of the method.
Relativistic methods for chemists
Barysz, Maria
2010-01-01
"Relativistic Methods for Chemists", written by a highly qualified team of authors, is targeted at both experimentalists and theoreticians interested in the area of relativistic effects in atomic and molecular systems and processes and in their consequences for the interpretation of the heavy element's chemistry. The theoretical part of the book focuses on the relativistic methods for molecular calculations discussing relativistic two-component theory, density functional theory, pseudopotentials and correlations. The experimentally oriented chapters describe the use of relativistic methods in different applications focusing on the design of new materials based on heavy element compounds, the role of the spin-orbit coupling in photochemistry and photobiology, and chirality and its relations to relativistic description of matter and radiation. This book is written at an intermediate level in order to appeal to a broader audience than just experts working in the field of relativistic theory.
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...
Adaptive warped kernel estimators
Chagny, Gaëlle
2014-01-01
In this work, we develop a method of adaptive nonparametric estimation, based on "warped" kernels. The aim is to estimate a real-valued function $s$ from a sample of random couples $(X,Y)$. We deal with transformed data $(\\Phi(X),Y)$, with $\\Phi$ a one-to-one function, to build a collection of kernel estimators. The data-driven bandwidth selection is done with a method inspired by Goldenshluger and Lepski~(2011). The method permits to handle various problems such as additive and multiplicativ...
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...... and find a remarkable level of agreement. We identify some features of the high-frequency data, which are challenging for realized kernels. They are when there are local trends in the data, over periods of around 10 minutes, where the prices and quotes are driven up or down. These can be associated...
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.
Energy Technology Data Exchange (ETDEWEB)
Lusanna, Luca, E-mail: lusanna@fi.infn.it [Sezione INFN di Firenze, Polo Scientifico, Via Sansone 1, 50019 Sesto Fiorentino (Italy)
2011-07-08
After a review of the problems induced by the Lorentz signature of Minkowski space-time, like the need of a clock synchronization convention for the definition of 3-space and the complexity of the notion of relativistic center of mass, there is the introduction of a new formulation of relativistic quantum mechanics compatible with the theory of relativistic bound states. In it the zeroth postulate of non-relativistic quantum mechanics is not valid and the physics is described in the rest frame by a Hilbert space containing only relative variables. The non-locality of the Poincare' generators imply a kinematical non-locality and non-separability influencing the theory of relativistic entanglement and not connected with the standard quantum non-locality.
A Heterogeneous Multi-core Architecture with a Hardware Kernel for Control Systems
DEFF Research Database (Denmark)
Li, Gang; Guan, Wei; Sierszecki, Krzysztof
2012-01-01
several advantages over a similar kernel implemented in software: higher-speed processing capability, parallel computation, and separation between the kernel itself and the applications being run. A microbenchmark has been used to compare the hardware kernel with the software kernel, and compare......Rapid industrialisation has resulted in a demand for improved embedded control systems with features such as predictability, high processing performance and low power consumption. Software kernel implementation on a single processor is becoming more difficult to satisfy those constraints....... This paper presents a multi-core architecture incorporating a hardware kernel on FPGAs, intended for high performance applications in control engineering domain. First, the hardware kernel is investigated on the basis of a component-based real-time kernel HARTEX (Hard Real-Time Executive for Control Systems...
Energy Technology Data Exchange (ETDEWEB)
Xiao, Cheng-Liang; Wang, Cong-Zhi; Lan, Jian-Hui; Yuan, Li-Yong; Zhao, Yu-Liang; Shi, Wei-Qun [Chinese Academy of Sciences, Beijing (China). Key Lab. of Nuclear Radiation and Nuclear Energy Technology and Key Lab. for Biomedical Effects of Nanomaterials and Nanosafety; Chai, Zhi-Fang [Chinese Academy of Sciences, Beijing (China). Key Lab. of Nuclear Radiation and Nuclear Energy Technology and Key Lab. for Biomedical Effects of Nanomaterials and Nanosafety; Soochow Univ., Suzhou (China). School of Radiological and Interdisciplinary Sciences
2014-07-01
The complexation properties of Am(III) and Eu(III) with a serial of novel N-heterocyclic tetradentate ligands, 2,9-bis(dialkyl-1,2,4-triazin-3-yl)-1,10-phenanth-rolines (BTPhens), have been calculated by density functional theory (DFT) coupled with relativistic small-core pseudopotential. It is found that the nitrogen atoms in triazine rings favor metal cations more than those in phenanthroline skeleton. The Am-N bond lengths are comparable to or even shorter than those of Eu-N bonds based on the larger radii of Am(III) than Eu(III). The effect of alkyl substituents on the complex structures is limited but they can adjust the complexation reaction and extraction kinetics. Additionally, the solvent effect can decrease the probability of the complexation reactions greatly and the solvation energies of Am(III) and Eu(III) might be the primary driving force in the complexation selectivity. The complexation reactions for forming ML(NO{sub 3}){sub 3} and [ML{sub 2}(NO{sub 3})]{sup 2+} complexes are believed to dominate the selective extraction separation of Am(III) from Eu(III) in nitric acid media, which agrees well with the experimental results. The comparisons of BTPhens with BTBPs in dipoles and electronic structures confirm that the BTPhens exhibit more favourable extraction kinetics and selectivity for minor actinides.
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...
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...
Regular Mittag-Leffler kernels and spectral decomposition of a class of non-selfadjoint operators
Energy Technology Data Exchange (ETDEWEB)
Gubreev, G M [South Ukrainian State K.D.Ushynsky Pedagogical University, Odessa (Ukraine)
2005-02-28
We define abstract Mittag-Leffler kernels with values in a separable Hilbert space. A Mittag-Leffler kernel is said to be c-regular (resp. d-regular) if it generates an integral transform of Fourier-Dzhrbashyan type (resp. if the space has an unconditional basis consisting of values of the kernel). We give a complete description of d-regular and c-regular kernels, which enables us to answer a question of M.G. Krein. We apply the notion of a regular Mittag-Leffler kernel to construct the spectral decomposition for one-dimensional perturbations of fractional powers of dissipative Volterra operators.
Relativistic Linear Restoring Force
Clark, D.; Franklin, J.; Mann, N.
2012-01-01
We consider two different forms for a relativistic version of a linear restoring force. The pair comes from taking Hooke's law to be the force appearing on the right-hand side of the relativistic expressions: d"p"/d"t" or d"p"/d["tau"]. Either formulation recovers Hooke's law in the non-relativistic limit. In addition to these two forces, we…
Relativistic Guiding Center Equations
Energy Technology Data Exchange (ETDEWEB)
White, R. B. [PPPL; Gobbin, M. [Euratom-ENEA Association
2014-10-01
In toroidal fusion devices it is relatively easy that electrons achieve relativistic velocities, so to simulate runaway electrons and other high energy phenomena a nonrelativistic guiding center formalism is not sufficient. Relativistic guiding center equations including flute mode time dependent field perturbations are derived. The same variables as used in a previous nonrelativistic guiding center code are adopted, so that a straightforward modifications of those equations can produce a relativistic version.
The relativistic Boltzmann equation on a spherically symmetric gravitational field
Takou, Etienne; Ciake Ciake, Fidèle L.
2017-10-01
In this paper, we consider the Cauchy problem for the relativistic Boltzmann equation with near vacuum initial data where the distribution function depends on the time, the position and the impulsion. We consider this equation on a spherically symmetric gravitational field spacetime. The collision kernel considered here is for the hard potentials case. We prove the existence of a unique global (in time) mild solution in a suitable weighted space.
Kernel descriptors for chest x-ray analysis
Orbán, Gergely Gy.; Horváth, Gábor
2017-03-01
In this study, we address the problem of lesion classification in radiographic scans. We adapt image kernel functions to be applicable for high-resolution, grayscale images to improve the classification accuracy of a support vector machine. We take existing kernel functions inspired by the histogram of oriented gradients, and derive an approximation that can be evaluated in linear time of the image size instead of the original quadratic complexity, enabling highresolution input. Moreover, we propose a new variant inspired by the matched filter, to better utilize intensity space. The new kernels are improved to be scale-invariant and combined with a Gaussian kernel built from handcrafted image features. We introduce a simple multiple kernel learning framework that is robust when one of the kernels, in the current case the image feature kernel, dominates the others. The combined kernel is input to a support vector classifier. We tested our method on lesion classification both in chest radiographs and digital tomosynthesis scans. The radiographs originated from a database including 364 patients with lung nodules and 150 healthy cases. The digital tomosynthesis scans were obtained by simulation using 91 CT scans from the LIDC-IDRI database as input. The new kernels showed good separation capability: ROC AuC was in [0.827, 0.853] for the radiograph database and 0.763 for the tomosynthesis scans. Adding the new kernels to the image-feature-based classifier significantly improved accuracy: AuC increased from 0.958 to 0.967 and from 0.788 to 0.801 for the two applications.
Relativistic quantum mechanics; Mecanique quantique relativiste
Energy Technology Data Exchange (ETDEWEB)
Ollitrault, J.Y. [CEA Saclay, 91 - Gif-sur-Yvette (France). Service de Physique Theorique]|[Universite Pierre et Marie Curie, 75 - Paris (France)
1998-12-01
These notes form an introduction to relativistic quantum mechanics. The mathematical formalism has been reduced to the minimum in order to enable the reader to calculate elementary physical processes. The second quantification and the field theory are the logical followings of this course. The reader is expected to know analytical mechanics (Lagrangian and Hamiltonian), non-relativistic quantum mechanics and some basis of restricted relativity. The purpose of the first 3 chapters is to define the quantum mechanics framework for already known notions about rotation transformations, wave propagation and restricted theory of relativity. The next 3 chapters are devoted to the application of relativistic quantum mechanics to a particle with 0,1/5 and 1 spin value. The last chapter deals with the processes involving several particles, these processes require field theory framework to be thoroughly described. (A.C.) 2 refs.
Towards relativistic quantum geometry
Directory of Open Access Journals (Sweden)
Luis Santiago Ridao
2015-12-01
Full Text Available We obtain a gauge-invariant relativistic quantum geometry by using a Weylian-like manifold with a geometric scalar field which provides a gauge-invariant relativistic quantum theory in which the algebra of the Weylian-like field depends on observers. An example for a Reissner–Nordström black-hole is studied.
Norbury, John W.
Nuclear fission reactions induced by the electromagnetic field of relativistic nuclei are studied for energies relevant to present and future relativistic heavy ion accelerators. Cross sections are calculated for U-238 and Pu-239 fission induced by C-12, Si-28, Au-197, and U-238 projectiles. It is found that some of the cross sections can exceed 10 b.
Directory of Open Access Journals (Sweden)
Chuang Lin
2013-01-01
Full Text Available Different kernels cause various class discriminations owing to their different geometrical structures of the data in the feature space. In this paper, a method of kernel optimization by maximizing a measure of class separability in the empirical feature space with sparse representation-based classifier (SRC is proposed to solve the problem of automatically choosing kernel functions and their parameters in kernel learning. The proposed method first adopts a so-called data-dependent kernel to generate an efficient kernel optimization algorithm. Then, a constrained optimization function using general gradient descent method is created to find combination coefficients varied with the input data. After that, optimized kernel PCA (KOPCA is obtained via combination coefficients to extract features. Finally, the sparse representation-based classifier is used to perform pattern classification task. Experimental results on MSTAR SAR images show the effectiveness of the proposed method.
Relativistic dynamics, Green function and pseudodifferential operators
Energy Technology Data Exchange (ETDEWEB)
Cirilo-Lombardo, Diego Julio [National Institute of Plasma Physics (INFIP), Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET), Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Buenos Aires 1428 (Argentina); Bogoliubov Laboratory of Theoretical Physics, Joint Institute for Nuclear Research, 141980 Dubna (Russian Federation)
2016-06-15
The central role played by pseudodifferential operators in relativistic dynamics is known very well. In this work, operators like the Schrodinger one (e.g., square root) are treated from the point of view of the non-local pseudodifferential Green functions. Starting from the explicit construction of the Green (semigroup) theoretical kernel, a theorem linking the integrability conditions and their dependence on the spacetime dimensions is given. Relativistic wave equations with arbitrary spin and the causality problem are discussed with the algebraic interpretation of the radical operator and their relation with coherent and squeezed states. Also we perform by means of pure theoretical procedures (based in physical concepts and symmetry) the relativistic position operator which satisfies the conditions of integrability: it is a non-local, Lorentz invariant and does not have the same problems as the “local”position operator proposed by Newton and Wigner. Physical examples, as zitterbewegung and rogue waves, are presented and deeply analyzed in this theoretical framework.
Relativistic Electron Vortices.
Barnett, Stephen M
2017-03-17
The desire to push recent experiments on electron vortices to higher energies leads to some theoretical difficulties. In particular the simple and very successful picture of phase vortices of vortex charge ℓ associated with ℓℏ units of orbital angular momentum per electron is challenged by the facts that (i) the spin and orbital angular momentum are not separately conserved for a Dirac electron, which suggests that the existence of a spin-orbit coupling will complicate matters, and (ii) that the velocity of a Dirac electron is not simply the gradient of a phase as it is in the Schrödinger theory suggesting that, perhaps, electron vortices might not exist at a fundamental level. We resolve these difficulties by showing that electron vortices do indeed exist in the relativistic theory and show that the charge of such a vortex is simply related to a conserved orbital part of the total angular momentum, closely related to the familiar situation for the orbital angular momentum of a photon.
Reproducing Kernels and Variable Bandwidth
Directory of Open Access Journals (Sweden)
R. Aceska
2012-01-01
Full Text Available We show that a modulation space of type ( is a reproducing kernel Hilbert space (RKHS. In particular, we explore the special cases of variable bandwidth spaces Aceska and Feichtinger (2011 with a suitably chosen weight to provide strong enough decay in the frequency direction. The reproducing kernel property is valid even if ( does not coincide with any of the classical Sobolev spaces because unbounded bandwidth (globally is allowed. The reproducing kernel will be described explicitly.
Relativistic versus non-relativistic mean field
Reinhard, Paul-Gerhard
Three variants of the relativistic mean-field model (RMF) and the nonrelativistic Skyrme-Hartree-Fock model (SHF) are compared. Overall quality, predictive power, and correlations between observables are addressed using statistical analysis on the basis of least squares fits. Appropriate density dependence is a crucial ingredient for good performance of RMF. However, SHF shows still more flexibility particularly in the isovector channel.
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....
Metabolisable energy values of whole palm kernel and palm kernel ...
African Journals Online (AJOL)
A series of four experiments were conducted in which 30g DM of whole palm kernel (WPK) and of Palm Kernel Oil Sludge (PKOS) were force-fed to laying hens and adult broiler chickens. The length of the collection periods was the same (24, 30, 48 and 60hr) for both ingredients. The ingredients and their faecal materials ...
The $q \\bar{q}$ relativistic interaction in the Wilson loop approach
Brambilla, Nora; Vairo, Antonio
1997-01-01
We study the $q \\bar{q}$ relativistic interaction starting from the Feynman-Schwinger representation of the gauge-invariant quark-antiquark Green function. We focus on the one-body limit and discuss the obtained non-perturbative interaction kernel of the Dirac equation.
Reproducing kernel Hilbert spaces with odd kernels in price prediction.
Krejník, Miloš; Tyutin, Anton
2012-10-01
For time series of futures contract prices, the expected price change is modeled conditional on past price changes. The proposed model takes the form of regression in a reproducing kernel Hilbert space with the constraint that the regression function must be odd. It is shown how the resulting constrained optimization problem can be reduced to an unconstrained one through appropriate modification of the kernel. In particular, it is shown how odd, even, and other similar kernels emerge naturally as the reproducing kernels of Hilbert subspaces induced by respective symmetry constraints. To test the validity and practical usefulness of the oddness assumption, experiments are run with large real-world datasets on four futures contracts, and it is demonstrated that using odd kernels results in a higher predictive accuracy and a reduced tendency to overfit.
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...
Research on Adjoint Kernelled Quasidifferential
Directory of Open Access Journals (Sweden)
Si-Da Lin
2014-01-01
Full Text Available The quasidifferential of a quasidifferentiable function in the sense of Demyanov and Rubinov is not uniquely defined. Xia proposed the notion of the kernelled quasidifferential, which is expected to be a representative for the equivalence class of quasidifferentials. Although the kernelled quasidifferential is known to have good algebraic properties and geometric structure, it is still not very convenient for calculating the kernelled quasidifferentials of −f and minfi∣i∈a finite index set I, where f and fi are kernelled quasidifferentiable functions. In this paper, the notion of adjoint kernelled quasidifferential, which is well-defined for −f and minfi∣i∈I, is employed as a representative of the equivalence class of quasidifferentials. Some algebraic properties of the adjoint kernelled quasidifferential are given and the existence of the adjoint kernelled quasidifferential is explored by means of the minimal quasidifferential and the Demyanov difference of convex sets. Under some condition, a formula of the adjoint kernelled quasidifferential is presented.
KERNELS THROUGH BIAS REDUCTION TECHNIQUE
African Journals Online (AJOL)
IMPROVING THE CHOICE OF HIGHER ORDER UNIVARIATE. KERNELS THROUGH BIAS REDUCTION TECHNIQUE. J. E. Osemwenkhae and J. I. Odiase. Department of Math ematics. University of Benin. Benin City, Nigeria. ABSTRACT. Within the last two decades, higher order nnivariate kernels ha/ve been under focus ...
Relativistic Length Agony Continued
Redzic, D. V.
2014-06-01
We made an attempt to remedy recent confusing treatments of some basic relativistic concepts and results. Following the argument presented in an earlier paper (Redzic 2008b), we discussed the misconceptions that are recurrent points in the literature devoted to teaching relativity such as: there is no change in the object in Special Relativity, illusory character of relativistic length contraction, stresses and strains induced by Lorentz contraction, and related issues. We gave several examples of the traps of everyday language that lurk in Special Relativity. To remove a possible conceptual and terminological muddle, we made a distinction between the relativistic length reduction and relativistic FitzGerald-Lorentz contraction, corresponding to a passive and an active aspect of length contraction, respectively; we pointed out that both aspects have fundamental dynamical contents. As an illustration of our considerations, we discussed briefly the Dewan-Beran-Bell spaceship paradox and the 'pole in a barn' paradox.
Bliokh, Konstantin Y; Nori, Franco
2012-03-23
We consider the relativistic deformation of quantum waves and mechanical bodies carrying intrinsic angular momentum (AM). When observed in a moving reference frame, the centroid of the object undergoes an AM-dependent transverse shift. This is the relativistic analogue of the spin-Hall effect, which occurs in free space without any external fields. Remarkably, the shifts of the geometric and energy centroids differ by a factor of 2, and both centroids are crucial for the Lorentz transformations of the AM tensor. We examine manifestations of the relativistic Hall effect in quantum vortices and mechanical flywheels and also discuss various fundamental aspects of this phenomenon. The perfect agreement of quantum and relativistic approaches allows applications at strikingly different scales, from elementary spinning particles, through classical light, to rotating black holes.
Relativistic GLONASS and geodesy
Mazurova, E. M.; Kopeikin, S. M.; Karpik, A. P.
2016-12-01
GNSS technology is playing a major role in applications to civil, industrial and scientific areas. Nowadays, there are two fully functional GNSS: American GPS and Russian GLONASS. Their data processing algorithms have been historically based on the Newtonian theory of space and time with only a few relativistic effects taken into account as small corrections preventing the system from degradation on a fairly long time. Continuously growing accuracy of geodetic measurements and atomic clocks suggests reconsidering the overall approach to the GNSS theoretical model based on the Einstein theory of general relativity. This is essentially more challenging but fundamentally consistent theoretical approach to relativistic space geodesy. In this paper, we overview the basic principles of the relativistic GNSS model and explain the advantages of such a system for GLONASS and other positioning systems. Keywords: relativistic GLONASS, Einstein theory of general relativity.
Energy Technology Data Exchange (ETDEWEB)
Antippa, Adel F [Departement de Physique, Universite du Quebec a Trois-Rivieres, Trois-Rivieres, Quebec G9A 5H7 (Canada)
2009-05-15
We solve the problem of the relativistic rocket by making use of the relation between Lorentzian and Galilean velocities, as well as the laws of superposition of successive collinear Lorentz boosts in the limit of infinitesimal boosts. The solution is conceptually simple, and technically straightforward, and provides an example of a powerful method that can be applied to a wide range of special relativistic problems of linear acceleration.
Exact Relativistic `Antigravity' Propulsion
Felber, Franklin S.
2006-01-01
The Schwarzschild solution is used to find the exact relativistic motion of a payload in the gravitational field of a mass moving with constant velocity. At radial approach or recession speeds faster than 3-1/2 times the speed of light, even a small mass gravitationally repels a payload. At relativistic speeds, a suitable mass can quickly propel a heavy payload from rest nearly to the speed of light with negligible stresses on the payload.
Viscosity kernel of molecular fluids
DEFF Research Database (Denmark)
Puscasu, Ruslan; Todd, Billy; Daivis, Peter
2010-01-01
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...... 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...
Relativistic viscoelastic fluid mechanics.
Fukuma, Masafumi; Sakatani, Yuho
2011-08-01
A detailed study is carried out for the relativistic theory of viscoelasticity which was recently constructed on the basis of Onsager's linear nonequilibrium thermodynamics. After rederiving the theory using a local argument with the entropy current, we show that this theory universally reduces to the standard relativistic Navier-Stokes fluid mechanics in the long time limit. Since effects of elasticity are taken into account, the dynamics at short time scales is modified from that given by the Navier-Stokes equations, so that acausal problems intrinsic to relativistic Navier-Stokes fluids are significantly remedied. We in particular show that the wave equations for the propagation of disturbance around a hydrostatic equilibrium in Minkowski space-time become symmetric hyperbolic for some range of parameters, so that the model is free of acausality problems. This observation suggests that the relativistic viscoelastic model with such parameters can be regarded as a causal completion of relativistic Navier-Stokes fluid mechanics. By adjusting parameters to various values, this theory can treat a wide variety of materials including elastic materials, Maxwell materials, Kelvin-Voigt materials, and (a nonlinearly generalized version of) simplified Israel-Stewart fluids, and thus we expect the theory to be the most universal description of single-component relativistic continuum materials. We also show that the presence of strains and the corresponding change in temperature are naturally unified through the Tolman law in a generally covariant description of continuum mechanics.
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.
Directory of Open Access Journals (Sweden)
Dimitri Nowicki
Full Text Available This paper introduces a new model of associative memory, capable of both binary and continuous-valued inputs. Based on kernel theory, the memory model is on one hand a generalization of Radial Basis Function networks and, on the other, is in feature space, analogous to a Hopfield network. Attractors can be added, deleted, and updated on-line simply, without harming existing memories, and the number of attractors is independent of input dimension. Input vectors do not have to adhere to a fixed or bounded dimensionality; they can increase and decrease it without relearning previous memories. A memory consolidation process enables the network to generalize concepts and form clusters of input data, which outperforms many unsupervised clustering techniques; this process is demonstrated on handwritten digits from MNIST. Another process, reminiscent of memory reconsolidation is introduced, in which existing memories are refreshed and tuned with new inputs; this process is demonstrated on series of morphed faces.
Iterative Reconstruction of Memory Kernels.
Jung, Gerhard; Hanke, Martin; Schmid, Friederike
2017-06-13
In recent years, it has become increasingly popular to construct coarse-grained models with non-Markovian dynamics to account for an incomplete separation of time scales. One challenge of a systematic coarse-graining procedure is the extraction of the dynamical properties, namely, the memory kernel, from equilibrium all-atom simulations. In this article, we propose an iterative method for memory reconstruction from dynamical correlation functions. Compared to previously proposed noniterative techniques, it ensures by construction that the target correlation functions of the original fine-grained systems are reproduced accurately by the coarse-grained system, regardless of time step and discretization effects. Furthermore, we also propose a new numerical integrator for generalized Langevin equations that is significantly more accurate than the more commonly used generalization of the velocity Verlet integrator. We demonstrate the performance of the above-described methods using the example of backflow-induced memory in the Brownian diffusion of a single colloid. For this system, we are able to reconstruct realistic coarse-grained dynamics with time steps about 200 times larger than those used in the original molecular dynamics simulations.
Sparse kernel learning with LASSO and Bayesian inference algorithm.
Gao, Junbin; Kwan, Paul W; Shi, Daming
2010-03-01
Kernelized LASSO (Least Absolute Selection and Shrinkage Operator) has been investigated in two separate recent papers [Gao, J., Antolovich, M., & Kwan, P. H. (2008). L1 LASSO and its Bayesian inference. In W. Wobcke, & M. Zhang (Eds.), Lecture notes in computer science: Vol. 5360 (pp. 318-324); Wang, G., Yeung, D. Y., & Lochovsky, F. (2007). The kernel path in kernelized LASSO. In International conference on artificial intelligence and statistics (pp. 580-587). San Juan, Puerto Rico: MIT Press]. This paper is concerned with learning kernels under the LASSO formulation via adopting a generative Bayesian learning and inference approach. A new robust learning algorithm is proposed which produces a sparse kernel model with the capability of learning regularized parameters and kernel hyperparameters. A comparison with state-of-the-art methods for constructing sparse regression models such as the relevance vector machine (RVM) and the local regularization assisted orthogonal least squares regression (LROLS) is given. The new algorithm is also demonstrated to possess considerable computational advantages. Copyright 2009 Elsevier Ltd. All rights reserved.
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...
Kernel Methods on Riemannian Manifolds with Gaussian RBF Kernels.
Jayasumana, Sadeep; Hartley, Richard; Salzmann, Mathieu; Li, Hongdong; Harandi, Mehrtash
2015-12-01
In this paper, we develop an approach to exploiting kernel methods with manifold-valued data. In many computer vision problems, the data can be naturally represented as points on a Riemannian manifold. Due to the non-Euclidean geometry of Riemannian manifolds, usual Euclidean computer vision and machine learning algorithms yield inferior results on such data. In this paper, we define Gaussian radial basis function (RBF)-based positive definite kernels on manifolds that permit us to embed a given manifold with a corresponding metric in a high dimensional reproducing kernel Hilbert space. These kernels make it possible to utilize algorithms developed for linear spaces on nonlinear manifold-valued data. Since the Gaussian RBF defined with any given metric is not always positive definite, we present a unified framework for analyzing the positive definiteness of the Gaussian RBF on a generic metric space. We then use the proposed framework to identify positive definite kernels on two specific manifolds commonly encountered in computer vision: the Riemannian manifold of symmetric positive definite matrices and the Grassmann manifold, i.e., the Riemannian manifold of linear subspaces of a Euclidean space. We show that many popular algorithms designed for Euclidean spaces, such as support vector machines, discriminant analysis and principal component analysis can be generalized to Riemannian manifolds with the help of such positive definite Gaussian kernels.
National Aeronautics and Space Administration — This data set includes the complete set of SPICE data for one NEAR mission phase in the form of SPICE kernels, which can be accessed using SPICE software available...
Kernelized locality-sensitive hashing.
Kulis, Brian; Grauman, Kristen
2012-06-01
Fast retrieval methods are critical for many large-scale and data-driven vision applications. Recent work has explored ways to embed high-dimensional features or complex distance functions into a low-dimensional Hamming space where items can be efficiently searched. However, existing methods do not apply for high-dimensional kernelized data when the underlying feature embedding for the kernel is unknown. We show how to generalize locality-sensitive hashing to accommodate arbitrary kernel functions, making it possible to preserve the algorithm's sublinear time similarity search guarantees for a wide class of useful similarity functions. Since a number of successful image-based kernels have unknown or incomputable embeddings, this is especially valuable for image retrieval tasks. We validate our technique on several data sets, and show that it enables accurate and fast performance for several vision problems, including example-based object classification, local feature matching, and content-based retrieval.
determining the optimum combination of palm kernel cake
African Journals Online (AJOL)
user
Twenty (20) female grasscutters at 14 months of age were used for the study, which lasted for ten (10) weeks. The grasscutters were separated into five groups of 4 grasscutters each and fed five (5) diets, which differed in their levels of replacement of wheat offal at 0, 25, 50, 75 and 100% levels with palm kernel cake.
Relativistic quantum mechanics
Horwitz, Lawrence P
2015-01-01
This book describes a relativistic quantum theory developed by the author starting from the E.C.G. Stueckelberg approach proposed in the early 40s. In this framework a universal invariant evolution parameter (corresponding to the time originally postulated by Newton) is introduced to describe dynamical evolution. This theory is able to provide solutions for some of the fundamental problems encountered in early attempts to construct a relativistic quantum theory. A relativistically covariant construction is given for which particle spins and angular momenta can be combined through the usual rotation group Clebsch-Gordan coefficients. Solutions are defined for both the classical and quantum two body bound state and scattering problems. The recently developed quantum Lax-Phillips theory of semigroup evolution of resonant states is described. The experiment of Lindner and coworkers on interference in time is discussed showing how the property of coherence in time provides a simple understanding of the results. Th...
Relativistic theories of materials
Bressan, Aldo
1978-01-01
The theory of relativity was created in 1905 to solve a problem concerning electromagnetic fields. That solution was reached by means of profound changes in fundamental concepts and ideas that considerably affected the whole of physics. Moreover, when Einstein took gravitation into account, he was forced to develop radical changes also in our space-time concepts (1916). Relativistic works on heat, thermodynamics, and elasticity appeared as early as 1911. However, general theories having a thermodynamic basis, including heat conduction and constitutive equations, did not appear in general relativity until about 1955 for fluids and appeared only after 1960 for elastic or more general finitely deformed materials. These theories dealt with materials with memory, and in this connection some relativistic versions of the principle of material indifference were considered. Even more recently, relativistic theories incorporating finite deformations for polarizable and magnetizable materials and those in which couple s...
Handbook of relativistic quantum chemistry
Energy Technology Data Exchange (ETDEWEB)
Liu, Wenjian (ed.) [Peking Univ., Beijing (China). Center for Computational Science and Engineering
2017-03-01
This handbook focuses on the foundations of relativistic quantum mechanics and addresses a number of fundamental issues never covered before in a book. For instance: How can many-body theory be combined with quantum electrodynamics? How can quantum electrodynamics be interfaced with relativistic quantum chemistry? What is the most appropriate relativistic many-electron Hamiltonian? How can we achieve relativistic explicit correlation? How can we formulate relativistic properties? - just to name a few. Since relativistic quantum chemistry is an integral component of computational chemistry, this handbook also supplements the ''Handbook of Computational Chemistry''. Generally speaking, it aims to establish the 'big picture' of relativistic molecular quantum mechanics as the union of quantum electrodynamics and relativistic quantum chemistry. Accordingly, it provides an accessible introduction for readers new to the field, presents advanced methodologies for experts, and discusses possible future perspectives, helping readers understand when/how to apply/develop the methodologies.
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole E.
The density function of the gamma distribution is used as shift kernel in Brownian semistationary processes modelling the timewise behaviour of the velocity in turbulent regimes. This report presents exact and asymptotic properties of the second order structure function under such a model......, and relates these to results of von Karmann and Horwath. But first it is shown that the gamma kernel is interpretable as a Green’s function....
Towards Formal Verification of a Separation Microkernel
Butterfield, Andrew; Sanan, David; Hinchey, Mike
2013-08-01
The best approach to verifying an IMA separation kernel is to use a (fixed) time-space partitioning kernel with a multiple independent levels of separation (MILS) architecture. We describe an activity that explores the cost and feasibility of doing a formal verification of such a kernel to the Common Criteria (CC) levels mandated by the Separation Kernel Protection Profile (SKPP). We are developing a Reference Specification of such a kernel, and are using higher-order logic (HOL) to construct formal models of this specification and key separation properties. We then plan to do a dry run of part of a formal proof of those properties using the Isabelle/HOL theorem prover.
Bruce, Adam L
2015-01-01
We show the traditional rocket problem, where the ejecta velocity is assumed constant, can be reduced to an integral quadrature of which the completely non-relativistic equation of Tsiolkovsky, as well as the fully relativistic equation derived by Ackeret, are limiting cases. By expanding this quadrature in series, it is shown explicitly how relativistic corrections to the mass ratio equation as the rocket transitions from the Newtonian to the relativistic regime can be represented as products of exponential functions of the rocket velocity, ejecta velocity, and the speed of light. We find that even low order correction products approximate the traditional relativistic equation to a high accuracy in flight regimes up to $0.5c$ while retaining a clear distinction between the non-relativistic base-case and relativistic corrections. We furthermore use the results developed to consider the case where the rocket is not moving relativistically but the ejecta stream is, and where the ejecta stream is massless.
Relativistic length agony continued
Directory of Open Access Journals (Sweden)
Redžić D.V.
2014-01-01
Full Text Available We made an attempt to remedy recent confusing treatments of some basic relativistic concepts and results. Following the argument presented in an earlier paper (Redžić 2008b, we discussed the misconceptions that are recurrent points in the literature devoted to teaching relativity such as: there is no change in the object in Special Relativity, illusory character of relativistic length contraction, stresses and strains induced by Lorentz contraction, and related issues. We gave several examples of the traps of everyday language that lurk in Special Relativity. To remove a possible conceptual and terminological muddle, we made a distinction between the relativistic length reduction and relativistic FitzGerald-Lorentz contraction, corresponding to a passive and an active aspect of length contraction, respectively; we pointed out that both aspects have fundamental dynamical contents. As an illustration of our considerations, we discussed briefly the Dewan-Beran-Bell spaceship paradox and the ‘pole in a barn’ paradox. [Projekat Ministarstva nauke Republike Srbije, br. 171028
Relativistic configuration interaction approach
Indian Academy of Sciences (India)
level of reliability and accuracy in accounting for both relativistic and correlation effects associated with these properties has gained importance. In this paper, we will compute one of the P, ... this procedure provides reasonable accuracy with small computational cost. Titov and co-workers have also reported the result of Wd.
Antippa, Adel F.
2009-01-01
We solve the problem of the relativistic rocket by making use of the relation between Lorentzian and Galilean velocities, as well as the laws of superposition of successive collinear Lorentz boosts in the limit of infinitesimal boosts. The solution is conceptually simple, and technically straightforward, and provides an example of a powerful…
Indian Academy of Sciences (India)
Home; Journals; Pramana – Journal of Physics; Volume 77; Issue 3. Relativistic stellar models ... Upon specifying particular forms for one of the gravitational potentials and the electric ﬁeld intensity, the condition for pressure isotropy is transformed into a hypergeometric equation with two free parameters. For particular ...
Atkinson, David
A Zenonian supertask involving an infinite number of identical colliding balls is generalized to include balls with different masses. Under the restriction that the total mass of all the balls is finite, classical mechanics leads to velocities that have no upper limit. Relativistic mechanics results
Relativistic Quantum Information Theory
2007-11-20
Relativistic Quantum Information Theory Army Research Office Grant # DAAD -0301-0207 Christoph Adami November 16, 2007 1 Foreword The stated goal of the...the future will allow us to finish the work we started. A List of manuscripts produced under ARO grant # DAAD - 0301-0207 All these manuscripts
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.
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.
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
A relativistic trolley paradox
Matvejev, Vadim N.; Matvejev, Oleg V.; Grøn, Ø.
2016-01-01
We present an apparent paradox within the special theory of relativity, involving a trolley with relativistic velocity and its rolling wheels. Two solutions are given, both making clear the physical reality of the Lorentz contraction, and that the distance on the rails between each time a specific point on the rim touches the rail is not equal to 2 p R ,where R is the radius of the wheel, but 2 p R = ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi...
Numerical Relativistic Quantum Optics
2013-11-08
m is a signed cyclotron frequency, nr is the radial quantum number and ` is the orbital quantum number. The principle quantum number is n ≡ nr...Gordon equation is accomplished via domain decomposition, where each GPGPU advances the solution in a given domain, and MPI is used for commu...other points to the corresponding location in the transfer buffer. Once the ghost cells have been updated, the GPGPU can advance the relativistic wave
The relativistic glider revisited
Bergamin, L.; Delva, P.; Hees, A.
2009-01-01
In this paper we analyze some aspects of the "relativistic glider" proposed by Gu\\'eron and Mosna more in detail. In particular an explicit weak gravity and low velocity expansion is presented, the influence of different initial conditions are studied and the behavior of the glider over a longer integration time is presented. Our results confirm that the system can be used as a glider, but is not able to stop or even revert the fall of an object.
Relativistic tidal disruption events
Directory of Open Access Journals (Sweden)
Levan A.
2012-12-01
Full Text Available In March 2011 Swift detected an extremely luminous and long-lived outburst from the nucleus of an otherwise quiescent, low luminosity (LMC-like galaxy. Named Swift J1644+57, its combination of high-energy luminosity (1048 ergs s−1 at peak, rapid X-ray variability (factors of >100 on timescales of 100 seconds and luminous, rising radio emission suggested that we were witnessing the birth of a moderately relativistic jet (Γ ∼ 2 − 5, created when a star is tidally disrupted by the supermassive black hole in the centre of the galaxy. A second event, Swift J2058+0516, detected two months later, with broadly similar properties lends further weight to this interpretation. Taken together this suggests that a fraction of tidal disruption events do indeed create relativistic outflows, demonstrates their detectability, and also implies that low mass galaxies can host massive black holes. Here, I briefly outline the observational properties of these relativistic tidal flares observed last year, and their evolution over the first year since their discovery.
Parker, Edward
2017-08-01
A nonrelativistic particle released from rest at the edge of a ball of uniform charge density or mass density oscillates with simple harmonic motion. We consider the relativistic generalizations of these situations where the particle can attain speeds arbitrarily close to the speed of light; generalizing the electrostatic and gravitational cases requires special and general relativity, respectively. We find exact closed-form relations between the position, proper time, and coordinate time in both cases, and find that they are no longer harmonic, with oscillation periods that depend on the amplitude. In the highly relativistic limit of both cases, the particle spends almost all of its proper time near the turning points, but almost all of the coordinate time moving through the bulk of the ball. Buchdahl's theorem imposes nontrivial constraints on the general-relativistic case, as a ball of given density can only attain a finite maximum radius before collapsing into a black hole. This article is intended to be pedagogical, and should be accessible to those who have taken an undergraduate course in general relativity.
Gravitationally confined relativistic neutrinos
Vayenas, C. G.; Fokas, A. S.; Grigoriou, D.
2017-09-01
Combining special relativity, the equivalence principle, and Newton’s universal gravitational law with gravitational rather than rest masses, one finds that gravitational interactions between relativistic neutrinos with kinetic energies above 50 MeV are very strong and can lead to the formation of gravitationally confined composite structures with the mass and other properties of hadrons. One may model such structures by considering three neutrinos moving symmetrically on a circular orbit under the influence of their gravitational attraction, and by assuming quantization of their angular momentum, as in the Bohr model of the H atom. The model contains no adjustable parameters and its solution, using a neutrino rest mass of 0.05 eV/c2, leads to composite state radii close to 1 fm and composite state masses close to 1 GeV/c2. Similar models of relativistic rotating electron - neutrino pairs give a mass of 81 GeV/c2, close to that of W bosons. This novel mechanism of generating mass suggests that the Higgs mass generation mechanism can be modeled as a latent gravitational field which gets activated by relativistic neutrinos.
for palm kernel oil extraction
African Journals Online (AJOL)
user
The oil could be used as a lubricant and an emulsifier [6]. It is an ingredient in paint making as a drying base, and in the manufacture of candles and soaps. [6, 7]. ..... of Bio-energy Potential of Palm Kernel Shell by. Physicochemical haracterization”, Nigerian Journal of Technology, Vol. 31, Number 3, pp 329-335. 2012. [4].
Accelerating the Original Profile Kernel.
Hamp, Tobias; Goldberg, Tatyana; Rost, Burkhard
2013-01-01
One of the most accurate multi-class protein classification systems continues to be the profile-based SVM kernel introduced by the Leslie group. Unfortunately, its CPU requirements render it too slow for practical applications of large-scale classification tasks. Here, we introduce several software improvements that enable significant acceleration. Using various non-redundant data sets, we demonstrate that our new implementation reaches a maximal speed-up as high as 14-fold for calculating the same kernel matrix. Some predictions are over 200 times faster and render the kernel as possibly the top contender in a low ratio of speed/performance. Additionally, we explain how to parallelize various computations and provide an integrative program that reduces creating a production-quality classifier to a single program call. The new implementation is available as a Debian package under a free academic license and does not depend on commercial software. For non-Debian based distributions, the source package ships with a traditional Makefile-based installer. Download and installation instructions can be found at https://rostlab.org/owiki/index.php/Fast_Profile_Kernel. Bugs and other issues may be reported at https://rostlab.org/bugzilla3/enter_bug.cgi?product=fastprofkernel.
Accelerating the Original Profile Kernel.
Directory of Open Access Journals (Sweden)
Tobias Hamp
Full Text Available One of the most accurate multi-class protein classification systems continues to be the profile-based SVM kernel introduced by the Leslie group. Unfortunately, its CPU requirements render it too slow for practical applications of large-scale classification tasks. Here, we introduce several software improvements that enable significant acceleration. Using various non-redundant data sets, we demonstrate that our new implementation reaches a maximal speed-up as high as 14-fold for calculating the same kernel matrix. Some predictions are over 200 times faster and render the kernel as possibly the top contender in a low ratio of speed/performance. Additionally, we explain how to parallelize various computations and provide an integrative program that reduces creating a production-quality classifier to a single program call. The new implementation is available as a Debian package under a free academic license and does not depend on commercial software. For non-Debian based distributions, the source package ships with a traditional Makefile-based installer. Download and installation instructions can be found at https://rostlab.org/owiki/index.php/Fast_Profile_Kernel. Bugs and other issues may be reported at https://rostlab.org/bugzilla3/enter_bug.cgi?product=fastprofkernel.
Model selection for Gaussian kernel PCA denoising
DEFF Research Database (Denmark)
Jørgensen, Kasper Winther; Hansen, Lars Kai
2012-01-01
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...
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
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.
Fabrication and Characterization of Surrogate TRISO Particles Using 800μm ZrO_{2} Kernels
Energy Technology Data Exchange (ETDEWEB)
Jolly, Brian C. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Helmreich, Grant [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Cooley, Kevin M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Dyer, John [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Terrani, Kurt [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
2016-07-01
In support of fully ceramic microencapsulated (FCM) fuel development, coating development work is ongoing at Oak Ridge National Laboratory (ORNL) to produce tri-structural isotropic (TRISO) coated fuel particles with both UN kernels and surrogate (uranium-free) kernels. The nitride kernels are used to increase fissile density in these SiC-matrix fuel pellets with details described elsewhere. The surrogate TRISO particles are necessary for separate effects testing and for utilization in the consolidation process development. This report focuses on the fabrication and characterization of surrogate TRISO particles which use 800μm in diameter ZrO_{2} microspheres as the kernel.
Transport models for relativistic heavy-ion collisions at Relativistic ...
Indian Academy of Sciences (India)
2015-04-29
Apr 29, 2015 ... Transport models for relativistic heavy-ion collisions at Relativistic Heavy Ion Collider and Large Hadron Collider. Subrata Pal. Volume 84 Issue 5 May 2015 pp ... Subrata Pal1. Department of Nuclear and Atomic Physics, Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai 400 005, India ...
Relativistic Dynamics of Graphene
Semenoff, Gordon
2011-10-01
Graphene is a one-atom thick layer of carbon atoms where electrons obey an emergent Dirac equation. Only seven years after it first became available in the laboratory, graphene has captured the attention of a wide spectrum of scientists: from particle physicists interested in using graphene's emergent relativistic dynamics to study quantum field theory phenomena to condensed matter physicists fascinated by its unusual electronic propertied and technologists searching for materials for the nest generation of electronic devices. This presentation will review the basics of graphene and some questions, such as the possibility of chiral symmetry breaking, which have overlap with similar ones in strong interaction particle physics.
Relativistic twins or sextuplets?
Sheldon, E S
2003-01-01
A recent study of the relativistic twin 'paradox' by Soni in this journal affirmed that 'A simple solution of the twin paradox also shows anomalous behaviour of rigidly connected distant clocks' but entailed a pedagogic hurdle which the present treatment aims to surmount. Two scenarios are presented: the first 'flight-plan' is akin to that depicted by Soni, with constant-velocity segments, while the second portrays an alternative mission undertaken with sustained acceleration and deceleration, illustrated quantitatively for a two-way spacecraft flight from Earth to Polaris (465.9 light years distant) and back.
Corinaldesi, Ernesto
1963-01-01
Geared toward advanced undergraduate and graduate students of physics, this text provides readers with a background in relativistic wave mechanics and prepares them for the study of field theory. The treatment originated as a series of lectures from a course on advanced quantum mechanics that has been further amplified by student contributions.An introductory section related to particles and wave functions precedes the three-part treatment. An examination of particles of spin zero follows, addressing wave equation, Lagrangian formalism, physical quantities as mean values, translation and rotat
Relativistic dissipative fluids
Geroch, R
1993-01-01
We observe in Nature ﬂuids that manifest dissipation, e.g., the effects of heat conductivity and viscosity. We believe that all physical phenomena are to be described within the framework of General Relativity. What, then, is the appropriate description of a relativistic dissipative ﬂuid? This is not only a question of principle, but also one of practical interest. There exist systems, such as certain neutron stars, in which relativity and dissipation are at the same time signiﬁcant.
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....
Exotic Non-relativistic String
Casalbuoni, Roberto; Longhi, Giorgio
2007-01-01
We construct a classical non-relativistic string model in 3+1 dimensions. The model contains a spurion tensor field that is responsible for the non-commutative structure of the model. Under double dimensional reduction the model reduces to the exotic non-relativistic particle in 2+1 dimensions.
relline: Relativistic line profiles calculation
Dauser, Thomas
2015-05-01
relline calculates relativistic line profiles; it is compatible with the common X-ray data analysis software XSPEC (ascl:9910.005) and ISIS (ascl:1302.002). The two basic forms are an additive line model (RELLINE) and a convolution model to calculate relativistic smearing (RELCONV).
A relativistic trolley paradox
Matvejev, Vadim N.; Matvejev, Oleg V.; Grøn, Ø.
2016-06-01
We present an apparent paradox within the special theory of relativity, involving a trolley with relativistic velocity and its rolling wheels. Two solutions are given, both making clear the physical reality of the Lorentz contraction, and that the distance on the rails between each time a specific point on the rim touches the rail is not equal to 2 π R , where R is the radius of the wheel, but 2 π R / √{ 1 - R 2 Ω 2 / c 2 } , where Ω is the angular velocity of the wheels. In one solution, the wheel radius is constant as the velocity of the trolley increases, and in the other the wheels contract in the radial direction. We also explain two surprising facts. First that the shape of a rolling wheel is elliptical in spite of the fact that the upper part of the wheel moves faster than the lower part, and thus is more Lorentz contracted, and second that a Lorentz contracted wheel with relativistic velocity rolls out a larger distance between two successive touches of a point of the wheel on the rails than the length of a circle with the same radius as the wheels.
Energy Technology Data Exchange (ETDEWEB)
Ujevic, Maximiliano [Universidade Federal do ABC (UFABC), Santo Andre, SP (Brazil). Centro de Ciencias Naturais e Humanas; Letelier, Patricio S.; Vogt, Daniel [Universidade Estadual de Campinas (UNICAMP), SP (Brazil). Inst. de Matematica, Estatistica e Computacao Cientifica. Dept. de Matematica Aplicada
2011-07-01
Full text: Relativistic thick ring models are constructed using previously found analytical Newtonian potential-density pairs for flat rings and toroidal structures obtained from Kuzmin-Toomre family of discs. This was achieved by inflating previously constructed Newtonian ring potentials using the transformation |z|{yields}{radical}z{sup 2} + b{sup 2}, and then finding their relativistic analog. The models presented have infinite extension but the physical quantities decays very fast with the distance, and in principle, one could make a cut-off radius to consider it finite. In particular, we present systems with one ring, two rings and a disc with a ring. Also, the circular velocity of a test particle and its stability when performing circular orbits are presented in all these models. Using the Rayleigh criterion of stability of a fluid at rest in a gravitational field, we find that the different systems studied present a region of non-stability that appears in the intersection of the disc and the ring, and between the rings when they become thinner. (author)
Relativistic Planck-scale polymer
Amelino-Camelia, Giovanni; Arzano, Michele; Da Silva, Malú Maira; Orozco-Borunda, Daniel H.
2017-12-01
Polymer quantum mechanics has been studied as a simplified picture that reflects some of the key properties of Loop Quantum Gravity; however, while the fate of relativistic symmetries in Loop Quantum Gravity is still not established, it is usually assumed that the discrete polymer structure should lead to a breakdown of relativistic symmetries. We here focus for simplicity on a one-spatial-dimension polymer model and show that relativistic symmetries are deformed, rather than being broken. The specific type of deformed relativistic symmetries which we uncover appears to be closely related to analogous descriptions of relativistic symmetries in some noncommutative spacetimes. This also contributes to an ongoing effort attempting to establish whether the ;quantum-Minkowski limit; of Loop Quantum Gravity is a noncommutative spacetime.
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.
Nonlocal viscosity kernel of mixtures
Smith, Ben; Hansen, J. S.; Todd, B. D.
2012-02-01
In this Brief Report we investigate the multiscale hydrodynamical response of a liquid as a function of mixture composition. This is done via a series of molecular dynamics simulations in which the wave-vector-dependent viscosity kernel is computed for three mixtures, each with 7-15 different compositions. We observe that the viscosity kernel is dependent on composition for simple atomic mixtures for all the wave vectors studied here; however, for a molecular mixture the kernel is independent of composition for large wave vectors. The deviation from ideal mixing is also studied. Here it is shown that the Lorentz-Berthelot interaction rule follows ideal mixing surprisingly well for a large range of wave vectors, whereas for both the Kob-Andersen and molecular mixtures large deviations are found. Furthermore, for the molecular system the deviation is wave-vector dependent such that there exists a characteristic correlation length scale at which the ideal mixing goes from underestimating to overestimating the viscosity.
Kelvin-Helmholtz instability for relativistic fluids
Bodo, G.; Mignone, A.; Rosner, R.
2004-09-01
We reexamine the stability of an interface separating two nonmagnetized relativistic fluids in relative motion, showing that, in an appropriate reference frame, it is possible to find analytic solutions to the dispersion relation. Moreover, we show that the critical value of the Mach number, introduced by compressibility, is unchanged from the nonrelativistic case if we redefine the Mach number as M=[β/(1-β2)1/2][βs/(1-βs2)1/2]-1 , where β and βs are, respectively, the speed of the fluid and the speed of sound (in units of the speed of light).
Workshop on foundations of the relativistic theory of atomic structure
Energy Technology Data Exchange (ETDEWEB)
None
1981-03-01
The conference is an attempt to gather state-of-the-art information to understand the theory of relativistic atomic structure beyond the framework of the original Dirac theory. Abstracts of twenty articles from the conference were prepared separately for the data base. (GHT)
Galilean relativistic fluid mechanics
Ván, Péter
2015-01-01
Single component Galilean-relativistic (nonrelativistic) fluids are treated independently of reference frames. The basic fields are given, their balances, thermodynamic relations and the entropy production is calculated. The usual relative basic fields, the mass, momentum and energy densities, the diffusion current density, the pressure tensor and the heat flux are the time- and spacelike components of the third order mass-momentum-energy density tensor according to a velocity field. The transformation rules of the basic fields are derived and prove that the non-equilibrium thermodynamic background theory, that is the Gibbs relation, extensivity condition and the entropy production is absolute, that is independent of the reference frame and also of the fluid velocity. --- Az egykomponensu Galilei-relativisztikus (azaz nemrelativisztikus) disszipativ folyadekokat vonatkoztatasi rendszertol fuggetlenul targyaljuk. Megadjuk az alapmennyisegeket, ezek merlegeit, a termodinamikai osszefuggeseket es kiszamoljuk az ...
Relativistic gauge invariant potentials
Energy Technology Data Exchange (ETDEWEB)
Gonzalez, J.J. (Valladolid Univ. (Spain). Dept. de Fisica Teorica); Negro, J. (Valladolid Univ. (Spain). Dept. de Fisica Teorica); Olmo, M.A. del (Valladolid Univ. (Spain). Dept. de Fisica Teorica)
1995-01-01
A global method characterizing the invariant connections on an abelian principal bundle under a group of transformations is applied in order to get gauge invariant electromagnetic (elm.) potentials in a systematic way. So, we have classified all the elm. gauge invariant potentials under the Poincare subgroups of dimensions 4, 5, and 6, up to conjugation. It is paid attention in particular to the situation where these subgroups do not act transitively on the space-time manifold. We have used the same procedure for some galilean subgroups to get nonrelativistic potentials and study the way they are related to their relativistic partners by means of contractions. Some conformal gauge invariant potentials have also been derived and considered when they are seen as consequence of an enlargement of the Poincare symmetries. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Kipping, David, E-mail: dkipping@astro.columbia.edu [Department of Astronomy, Columbia University, 550 W. 120th St., New York, NY 10027 (United States)
2017-06-01
One proposed method for spacecraft to reach nearby stars is by accelerating sails using either solar radiation pressure or directed energy. This idea constitutes the thesis behind the Breakthrough Starshot project, which aims to accelerate a gram-mass spacecraft up to one-fifth the speed of light toward Proxima Centauri. For such a case, the combination of the sail’s low mass and relativistic velocity renders previous treatments incorrect at the 10% level, including that of Einstein himself in his seminal 1905 paper introducing special relativity. To address this, we present formulae for a sail’s acceleration, first in response to a single photon and then extended to an ensemble. We show how the sail’s motion in response to an ensemble of incident photons is equivalent to that of a single photon of energy equal to that of the ensemble. We use this principle of ensemble equivalence for both perfect and imperfect mirrors, enabling a simple analytic prediction of the sail’s velocity curve. Using our results and adopting putative parameters for Starshot , we estimate that previous relativistic treatments underestimate the spacecraft’s terminal velocity by ∼10% for the same incident energy. Additionally, we use a simple model to predict the sail’s temperature and diffraction beam losses during the laser firing period; this allows us to estimate that, for firing times of a few minutes and operating temperatures below 300°C (573 K), Starshot will require a sail that absorbs less than one in 260,000 photons.
Kipping, David
2017-06-01
One proposed method for spacecraft to reach nearby stars is by accelerating sails using either solar radiation pressure or directed energy. This idea constitutes the thesis behind the Breakthrough Starshot project, which aims to accelerate a gram-mass spacecraft up to one-fifth the speed of light toward Proxima Centauri. For such a case, the combination of the sail’s low mass and relativistic velocity renders previous treatments incorrect at the 10% level, including that of Einstein himself in his seminal 1905 paper introducing special relativity. To address this, we present formulae for a sail’s acceleration, first in response to a single photon and then extended to an ensemble. We show how the sail’s motion in response to an ensemble of incident photons is equivalent to that of a single photon of energy equal to that of the ensemble. We use this principle of ensemble equivalence for both perfect and imperfect mirrors, enabling a simple analytic prediction of the sail’s velocity curve. Using our results and adopting putative parameters for Starshot, we estimate that previous relativistic treatments underestimate the spacecraft’s terminal velocity by ˜10% for the same incident energy. Additionally, we use a simple model to predict the sail’s temperature and diffraction beam losses during the laser firing period; this allows us to estimate that, for firing times of a few minutes and operating temperatures below 300°C (573 K), Starshot will require a sail that absorbs less than one in 260,000 photons.
Image texture analysis of crushed wheat kernels
Zayas, Inna Y.; Martin, C. R.; Steele, James L.; Dempster, Richard E.
1992-03-01
The development of new approaches for wheat hardness assessment may impact the grain industry in marketing, milling, and breeding. This study used image texture features for wheat hardness evaluation. Application of digital imaging to grain for grading purposes is principally based on morphometrical (shape and size) characteristics of the kernels. A composite sample of 320 kernels for 17 wheat varieties were collected after testing and crushing with a single kernel hardness characterization meter. Six wheat classes where represented: HRW, HRS, SRW, SWW, Durum, and Club. In this study, parameters which characterize texture or spatial distribution of gray levels of an image were determined and used to classify images of crushed wheat kernels. The texture parameters of crushed wheat kernel images were different depending on class, hardness and variety of the wheat. Image texture analysis of crushed wheat kernels showed promise for use in class, hardness, milling quality, and variety discrimination.
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...
Kernel support for the Wisconsin Wind Tunnel
Reinhardt, Steven K.; Falsafi, Babak; Wood, David A.
1993-01-01
This paper describes a kernel interface that provides an untrusted user-level process (an executive) with protected access to memory management functions, including the ability to create, manipulate, and execute within subservient contexts (address spaces). Page motion callbacks not only give the executive limited control over physical memory management, but also shift certain responsibilities out of the kernel, greatly reducing kernel state and complexity. The executive interface was motivat...
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.
The heat kernel for two Aharonov-Bohm solenoids in a uniform magnetic field
Šťovíček, Pavel
2017-01-01
A non-relativistic quantum model is considered with a point particle carrying a charge e and moving in the plane pierced by two infinitesimally thin Aharonov-Bohm solenoids and subjected to a perpendicular uniform magnetic field of magnitude B. Relying on a technique originally due to Schulman, Laidlaw and DeWitt which is applicable to Schrödinger operators on multiply connected configuration manifolds a formula is derived for the corresponding heat kernel. As an application of the heat kernel formula, approximate asymptotic expressions are derived for the lowest eigenvalue lying above the first Landau level and for the corresponding eigenfunction while assuming that | eB | R2 /(ħ c) is large, where R is the distance between the two solenoids.
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.
Directory of Open Access Journals (Sweden)
L. Alfonso
2010-08-01
Full Text Available The kinetic collection equation (KCE has been widely used to describe the evolution of the average droplet spectrum due to the collection process that leads to the development of precipitation in warm clouds. This deterministic, integro-differential equation only has analytic solution for very simple kernels. For more realistic kernels, the KCE needs to be integrated numerically. In this study, the validity time of the KCE for the hydrodynamic kernel is estimated by a direct comparison of Monte Carlo simulations with numerical solutions of the KCE. The simulation results show that when the largest droplet becomes separated from the smooth spectrum, the total mass calculated from the numerical solution of the KCE is not conserved and, thus, the KCE is no longer valid. This result confirms the fact that for kernels appropriate for precipitation development within warm clouds, the KCE can only be applied to the continuous portion of the mass distribution.
Conductivity of a relativistic plasma
Energy Technology Data Exchange (ETDEWEB)
Braams, B.J.; Karney, C.F.F.
1989-03-01
The collision operator for a relativistic plasma is reformulated in terms of an expansion in spherical harmonics. This formulation is used to calculate the electrical conductivity. 13 refs., 1 fig., 1 tab.
Superposition as a Relativistic Filter
Ord, G. N.
2017-07-01
By associating a binary signal with the relativistic worldline of a particle, a binary form of the phase of non-relativistic wavefunctions is naturally produced by time dilation. An analog of superposition also appears as a Lorentz filtering process, removing paths that are relativistically inequivalent. In a model that includes a stochastic component, the free-particle Schrödinger equation emerges from a completely relativistic context in which its origin and function is known. The result establishes the fact that the phase of wavefunctions in Schrödinger's equation and the attendant superposition principle may both be considered remnants of time dilation. This strongly argues that quantum mechanics has its origins in special relativity.
Experiments with stored relativistic exotic nuclei
Energy Technology Data Exchange (ETDEWEB)
Geissel, H.; Radon, T.; Attallah, F. [Gesellschaft fuer Schwerionenforschung mbH, Darmstadt (Germany)] [and others
1998-07-01
Beams of relativistic exotic nuclei were produced, separated and investigated with the combination of the fragment separator FRS and the storage ring ESR. The following experiments are presented: (1) Direct mass measurements of relativistic nickel and bismuth projectile fragments were performed using Schottky spectrometry. Applying electron cooling, the relative velocity spread of the circulating secondary nuclear beams of low intensity was reduced to below 10{sup -6}. The achieved mass resolving power of m/{Delta}m = 6.5 . 10{sup 5} (FWHM) in recent measurements represents an improvement by a factor of two compared to our previous experiments. The previously unknown masses of more than 100 proton-rich isotopes have been measured in the range of 54 {<=} Z {<=} 84. The results are compared with mass models and estimated values based on extrapolations of experimental values. (2) Exotic nuclei with half-lives shorter than the time required for electron cooling can be investigated by time-of-flight measurements with the ESR being operated in the isochronous mode. This novel experimental technique has been successfully applied in a first measurement with nickel fragments. A mass resolving power of m/{Delta}m = 1.5 . 10{sup 5} (FWHM) was achieved in this mode of operation. (3) Nuclear half-lives of stored and cooled bare projectile fragments have been measured to study the influence of the ionic charge state on the beta-decay probability. (orig.)
Reduction of Aflatoxins in Apricot Kernels by Electronic and Manual Color Sorting.
Zivoli, Rosanna; Gambacorta, Lucia; Piemontese, Luca; Solfrizzo, Michele
2016-01-19
The efficacy of color sorting on reducing aflatoxin levels in shelled apricot kernels was assessed. Naturally-contaminated kernels were submitted to an electronic optical sorter or blanched, peeled, and manually sorted to visually identify and sort discolored kernels (dark and spotted) from healthy ones. The samples obtained from the two sorting approaches were ground, homogenized, and analysed by HPLC-FLD for their aflatoxin content. A mass balance approach was used to measure the distribution of aflatoxins in the collected fractions. Aflatoxin B₁ and B₂ were identified and quantitated in all collected fractions at levels ranging from 1.7 to 22,451.5 µg/kg of AFB₁ + AFB₂, whereas AFG₁ and AFG₂ were not detected. Excellent results were obtained by manual sorting of peeled kernels since the removal of discolored kernels (2.6%-19.9% of total peeled kernels) removed 97.3%-99.5% of total aflatoxins. The combination of peeling and visual/manual separation of discolored kernels is a feasible strategy to remove 97%-99% of aflatoxins accumulated in naturally-contaminated samples. Electronic optical sorter gave highly variable results since the amount of AFB₁ + AFB₂ measured in rejected fractions (15%-18% of total kernels) ranged from 13% to 59% of total aflatoxins. An improved immunoaffinity-based HPLC-FLD method having low limits of detection for the four aflatoxins (0.01-0.05 µg/kg) was developed and used to monitor the occurrence of aflatoxins in 47 commercial products containing apricot kernels and/or almonds commercialized in Italy. Low aflatoxin levels were found in 38% of the tested samples and ranged from 0.06 to 1.50 μg/kg for AFB₁ and from 0.06 to 1.79 μg/kg for total aflatoxins.
Relativistic multiwave Cerenkov generator
Bugaev, S. P.; Kanavets, V. I.; Klimov, A. I.; Koshelev, V. I.; Cherepenin, V. A.
1983-11-01
The design and operation of a multiwave Cerenkov generator using a relativistic electron beam are reported. The device comprises a 3-cm-radius tubular graphite cathode fed with a 1-microsec 1-2.5-MW pulse from a Marx generator; a 5.6-cm-radius anode; an increasing 14-32-kG magnetic field; a 3.4-cm-aperture-radius graphite collimating iris; a stainless-steel semitoroidal-iris-loaded slow-wave structure of maximum length 48.6 cm, inside radius 4.2 cm, iris aperture radius 3.0 cm, iris minor radius 3 mm, and period 1.5 cm; a stainless-steel cone collector; and a vacuum-tight 60-cm-radius window. At 2.5 MV and 21 kG, output power at wavelength 3.15 + or - 0.1 cm is measured as about 5 GW, with baseline pulse length 30-50 nsec and efficiency up to about 10 percent.
Generalized Derivative Based Kernelized Learning Vector Quantization
Schleif, Frank-Michael; Villmann, Thomas; Hammer, Barbara; Schneider, Petra; Biehl, Michael; Fyfe, Colin; Tino, Peter; Charles, Darryl; Garcia-Osoro, Cesar; Yin, Hujun
2010-01-01
We derive a novel derivative based version of kernelized Generalized Learning Vector Quantization (KGLVQ) as an effective, easy to interpret, prototype based and kernelized classifier. It is called D-KGLVQ and we provide generalization error bounds, experimental results on real world data, showing
Panel data specifications in nonparametric kernel regression
DEFF Research Database (Denmark)
Czekaj, Tomasz Gerard; Henningsen, Arne
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...
Model selection in kernel ridge regression
DEFF Research Database (Denmark)
Exterkate, Peter
2013-01-01
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...
Ranking Support Vector Machine with Kernel Approximation.
Chen, Kai; Li, Rongchun; Dou, Yong; Liang, Zhengfa; Lv, Qi
2017-01-01
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.
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
Directory of Open Access Journals (Sweden)
Shu-zhi Gao
2016-01-01
Full Text Available In view of the fact that the production process of Polyvinyl chloride (PVC polymerization has more fault types and its type is complex, a fault diagnosis algorithm based on the hybrid Dynamic Kernel Principal Component Analysis-Fisher Discriminant Analysis (DKPCA-FDA method is proposed in this paper. Kernel principal component analysis and Dynamic Kernel Principal Component Analysis are used for fault diagnosis of Polyvinyl chloride (PVC polymerization process, while Fisher Discriminant Analysis (FDA method was adopted to make failure data for further separation. The simulation results show that the Dynamic Kernel Principal Component Analyses to fault diagnosis of Polyvinyl chloride (PVC polymerization process have better diagnostic accuracy, the Fisher Discriminant Analysis (FDA can further realize the fault isolation, and the actual fault in the process of Polyvinyl chloride (PVC polymerization production can be monitored by Dynamic Kernel Principal Component Analysis.
Sarma phase in relativistic and non-relativistic systems
Directory of Open Access Journals (Sweden)
I. Boettcher
2015-03-01
Full Text Available We investigate the stability of the Sarma phase in two-component fermion systems in three spatial dimensions. For this purpose we compare strongly-correlated systems with either relativistic or non-relativistic dispersion relation: relativistic quarks and mesons at finite isospin density and spin-imbalanced ultracold Fermi gases. Using a Functional Renormalization Group approach, we resolve fluctuation effects onto the corresponding phase diagrams beyond the mean-field approximation. We find that fluctuations induce a second-order phase transition at zero temperature, and thus a Sarma phase, in the relativistic setup for large isospin chemical potential. This motivates the investigation of the cold atoms setup with comparable mean-field phase structure, where the Sarma phase could then be realized in experiment. However, for the non-relativistic system we find the stability region of the Sarma phase to be smaller than the one predicted from mean-field theory. It is limited to the BEC side of the phase diagram, and the unitary Fermi gas does not support a Sarma phase at zero temperature. Finally, we propose an ultracold quantum gas with four fermion species that has a good chance to realize a zero-temperature Sarma phase.
Directory of Open Access Journals (Sweden)
M. A. Fazel
2013-09-01
Full Text Available Unsupervised change detection of agricultural lands in seasonal and annual periods is necessary for farming activities and yield estimation. Polarimetric Synthetic Aperture Radar (PolSAR data due to their special characteristics are a powerful source to study temporal behaviour of land cover types. PolSAR data allows building up the powerful observations sensitive to the shape, orientation and dielectric properties of scatterers and allows the development of physical models for identification and separation of scattering mechanisms occurring inside the same region of observed lands. In this paper an unsupervised kernel-based method is introduced for agricultural change detection by PolSAR data. This method works by transforming data into higher dimensional space by kernel functions and clustering them in this space. Kernel based c-means clustering algorithm is employed to separate the changes classes from the no-changes. This method is a non-linear algorithm which considers the contextual information of observations. Using the kernel functions helps to make the non-linear features more separable in a linear space. In addition, use of eigenvectors' parameters as a polarimetric target decomposition technique helps us to consider and benefit physical properties of targets in the PolSAR change detection. Using kernel based c-means clustering with proper initialization of the algorithm makes this approach lead to great results in change detection paradigm.
Kernel Multitask Regression for Toxicogenetics.
Bernard, Elsa; Jiao, Yunlong; Scornet, Erwan; Stoven, Veronique; Walter, Thomas; Vert, Jean-Philippe
2017-10-01
The development of high-throughput in vitro assays to study quantitatively the toxicity of chemical compounds on genetically characterized human-derived cell lines paves the way to predictive toxicogenetics, where one would be able to predict the toxicity of any particular compound on any particular individual. In this paper we present a machine learning-based approach for that purpose, kernel multitask regression (KMR), which combines chemical characterizations of molecular compounds with genetic and transcriptomic characterizations of cell lines to predict the toxicity of a given compound on a given cell line. We demonstrate the relevance of the method on the recent DREAM8 Toxicogenetics challenge, where it ranked among the best state-of-the-art models, and discuss the importance of choosing good descriptors for cell lines and chemicals. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
The heat kernel as the pagerank of a graph
Chung, Fan
2007-01-01
The concept of pagerank was first started as a way for determining the ranking of Web pages by Web search engines. Based on relations in interconnected networks, pagerank has become a major tool for addressing fundamental problems arising in general graphs, especially for large information networks with hundreds of thousands of nodes. A notable notion of pagerank, introduced by Brin and Page and denoted by PageRank, is based on random walks as a geometric sum. In this paper, we consider a notion of pagerank that is based on the (discrete) heat kernel and can be expressed as an exponential sum of random walks. The heat kernel satisfies the heat equation and can be used to analyze many useful properties of random walks in a graph. A local Cheeger inequality is established, which implies that, by focusing on cuts determined by linear orderings of vertices using the heat kernel pageranks, the resulting partition is within a quadratic factor of the optimum. This is true, even if we restrict the volume of the small part separated by the cut to be close to some specified target value. This leads to a graph partitioning algorithm for which the running time is proportional to the size of the targeted volume (instead of the size of the whole graph).
Relativistic quantum mechanics wave equations
Greiner, Walter
1990-01-01
Relativistic Quantum Mechanics - Wave Equations concentrates mainly on the wave equations for spin-0 and spin-12 particles Chapter 1 deals with the Klein-Gordon equation and its properties and applications The chapters that follow introduce the Dirac equation, investigate its covariance properties and present various approaches to obtaining solutions Numerous applications are discussed in detail, including the two-center Dirac equation, hole theory, CPT symmetry, Klein's paradox, and relativistic symmetry principles Chapter 15 presents the relativistic wave equations for higher spin (Proca, Rarita-Schwinger, and Bargmann-Wigner) The extensive presentation of the mathematical tools and the 62 worked examples and problems make this a unique text for an advanced quantum mechanics course
Non-Relativistic Superstring Theories
Energy Technology Data Exchange (ETDEWEB)
Kim, Bom Soo
2007-12-14
We construct a supersymmetric version of the 'critical' non-relativistic bosonic string theory [1] with its manifest global symmetry. We introduce the anticommuting bc CFT which is the super partner of the {beta}{gamma} CFT. The conformal weights of the b and c fields are both 1/2. The action of the fermionic sector can be transformed into that of the relativistic superstring theory. We explicitly quantize the theory with manifest SO(8) symmetry and find that the spectrum is similar to that of Type IIB superstring theory. There is one notable difference: the fermions are non-chiral. We further consider 'noncritical' generalizations of the supersymmetric theory using the superspace formulation. There is an infinite range of possible string theories similar to the supercritical string theories. We comment on the connection between the critical non-relativistic string theory and the lightlike Linear Dilaton theory.
Heat kernel and Weyl anomaly of Schrödinger invariant theory
Pal, Sridip; Grinstein, Benjamín
2017-12-01
We propose a method inspired by discrete light cone quantization to determine the heat kernel for a Schrödinger field theory (Galilean boost invariant with z =2 anisotropic scaling symmetry) living in d +1 dimensions, coupled to a curved Newton-Cartan background, starting from a heat kernel of a relativistic conformal field theory (z =1 ) living in d +2 dimensions. We use this method to show that the Schrödinger field theory of a complex scalar field cannot have any Weyl anomalies. To be precise, we show that the Weyl anomaly Ad+1 G for Schrödinger theory is related to the Weyl anomaly of a free relativistic scalar CFT Ad+2 R via Ad+1 G=2 π δ (m )Ad+2 R , where m is the charge of the scalar field under particle number symmetry. We provide further evidence of the vanishing anomaly by evaluating Feynman diagrams in all orders of perturbation theory. We present an explicit calculation of the anomaly using a regulated Schrödinger operator, without using the null cone reduction technique. We generalize our method to show that a similar result holds for theories with a single time-derivative and with even z >2 .
Robust Metric based Anomaly Detection in Kernel Feature Space
Directory of Open Access Journals (Sweden)
B. Du
2012-07-01
Full Text Available This thesis analyzes the anomalous measurement metric in high dimension feature space, where it is supposed the Gaussian assumption for state-of-art mahanlanobis algorithms is reasonable. The realization of the detector in high dimension feature space is by kernel trick. Besides, the masking and swamping effect is further inhibited by an iterative approach in the feature space. The proposed robust metric based anomaly detection presents promising performance in hyperspectral remote sensing images: the separability between anomalies and background is enlarged; background statistics is more concentrated, and immune to the contamination by anomalies.
Spectra of heavy-light mesons in a relativistic model
Energy Technology Data Exchange (ETDEWEB)
Liu, Jing-Bin; Lue, Cai-Dian [Institute of High Energy Physics, Beijing (China)
2017-05-15
The spectra and wave functions of heavy-light mesons are calculated within a relativistic quark model which is based on a heavy-quark expansion of the instantaneous Bethe-Salpeter equation by applying the Foldy-Wouthuysen transformation. The kernel we choose is the standard combination of linear scalar and Coulombic vector. The effective Hamiltonian for heavy-light quark-antiquark system is calculated up to order 1/m{sub Q}{sup 2}. Our results are in good agreement with available experimental data except for the anomalous D{sub s0}{sup *}(2317) and D{sub s1}(2460) states. The newly observed heavy-light meson states can be accommodated successfully in the relativistic quark model with their assignments presented. The D{sub sJ}{sup *}(2860) can be interpreted as the vertical stroke 1{sup 3/2}D{sub 1} right angle and vertical stroke 1{sup 5/2}D{sub 3} right angle states being members of the 1D family with J{sup P} = 1{sup -} and 3{sup -}. (orig.)
Spectra of heavy-light mesons in a relativistic model
Liu, Jing-Bin; Lü, Cai-Dian
2017-05-01
The spectra and wave functions of heavy-light mesons are calculated within a relativistic quark model which is based on a heavy-quark expansion of the instantaneous Bethe-Salpeter equation by applying the Foldy-Wouthuysen transformation. The kernel we choose is the standard combination of linear scalar and Coulombic vector. The effective Hamiltonian for heavy-light quark-antiquark system is calculated up to order 1/m_Q^2. Our results are in good agreement with available experimental data except for the anomalous D_{s0}^*(2317) and D_{s1}(2460) states. The newly observed heavy-light meson states can be accommodated successfully in the relativistic quark model with their assignments presented. The D_{sJ}^*(2860) can be interpreted as the |1^{3/2}D_1\\rangle and |1^{5/2}D_3\\rangle states being members of the 1D family with J^P=1^- and 3^-.
Kernel adaptive filtering a comprehensive introduction
Liu, Weifeng; Haykin, Simon
2010-01-01
Online learning from a signal processing perspective There is increased interest in kernel learning algorithms in neural networks and a growing need for nonlinear adaptive algorithms in advanced signal processing, communications, and controls. Kernel Adaptive Filtering is the first book to present a comprehensive, unifying introduction to online learning algorithms in reproducing kernel Hilbert spaces. Based on research being conducted in the Computational Neuro-Engineering Laboratory at the University of Florida and in the Cognitive Systems Laboratory at McMaster University, O
Huang, Lulu; Massa, Lou
2010-12-01
The Kernel Energy Method (KEM) provides a way to calculate the ab-initio energy of very large biological molecules. The results are accurate, and the computational time reduced. However, by use of a list of double kernel interactions a significant additional reduction of computational effort may be achieved, still retaining ab-initio accuracy. A numerical comparison of the indices that name the known double interactions in question, allow one to list higher order interactions having the property of topological continuity within the full molecule of interest. When, that list of interactions is unpacked, as a kernel expansion, which weights the relative importance of each kernel in an expression for the total molecular energy, high accuracy, and a further significant reduction in computational effort results. A KEM molecular energy calculation based upon the HF/STO3G chemical model, is applied to the protein insulin, as an illustration.
Relativistic EOS for supernova simulations
Directory of Open Access Journals (Sweden)
Shen H.
2014-03-01
Full Text Available We study the relativistic equation of state (EOS of dense matter covering a wide range of temperature, proton fraction, and baryon density for the use of supernova simulations. This work is based on the relativistic mean-field theory (RMF and the Thomas-Fermi approximation. The Thomas-Fermi approximation in combination with assumed nucleon distribution functions and a free energy minimization is adopted to describe the non-uniform matter, which is composed of a lattice of heavy nuclei. We treat the uniform matter and non-uniform matter consistently using the same RMF theory. We compare the EOS tables in detail.
Frontiers in relativistic celestial mechanics
2014-01-01
Relativistic celestial mechanics – investigating the motion celestial bodies under the influence of general relativity – is a major tool of modern experimental gravitational physics. With a wide range of prominent authors from the field, this two-volume series consists of reviews on a multitude of advanced topics in the area of relativistic celestial mechanics – starting from more classical topics such as the regime of asymptotically-flat spacetime, light propagation and celestial ephemerides, but also including its role in cosmology and alternative theories of gravity as well as modern experiments in this area.
Transport models for relativistic heavy-ion collisions at Relativistic ...
Indian Academy of Sciences (India)
Abstract. We review the transport models that are widely used to study the properties of the quark-gluon plasma formed in relativistic heavy-ion collisions at RHIC and LHC. We show that transport model analysis of two important and complementary observables, the anisotropic flow of bulk hadrons and suppression of ...
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.
Strong-coupling diffusion in relativistic systems
Indian Academy of Sciences (India)
Relativistic heavy-ion collisions; fluctuation phenomena; relativistic diffusion model; net-proton rapidly ... cients on the available relativistic energy, results at 40 A•GeV/c are obtained. Extrapolat- ing to higher ... proached for times t ^τs larger than the time τs that is characteristic for strong coupling. – when all secondary ...
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.
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 ...
Relativistic harmonics for turbulent wakefield diagnostics
Kuramitsu, Yasuhiro; Chen, Shih-Hung
2017-06-01
The propagation properties of relativistic harmonics excited in a plasma with an intense laser pulse is investigated theoretically and numerically. Focusing on the frequency separation, a cold electron fluid model in two spatial dimension is discussed to obtain the harmonic amplitude. The theoretical predictions are verified by performing particle-in-cell simulations in two spatial dimensions. When the laser amplitude is large, the strong ponderomotive force expels the electrons, creating a large amplitude density structures associated with the wakefield. The harmonics propagate obliquely with respect to the laser propagation direction, which is well represented by the structure of the high density layer resulting from the transverse poderomotive force. We also discuss a possible experimental setup to observe the density structures relevant to wakefield.
Hyperellipsoidal statistical classifications in a reproducing kernel Hilbert space.
Liang, Xun; Ni, Zhihao
2011-06-01
Standard support vector machines (SVMs) have kernels based on the Euclidean distance. This brief extends standard SVMs to SVMs with kernels based on the Mahalanobis distance. The extended SVMs become a special case of the Euclidean distance when the covariance matrix in a reproducing kernel Hilbert space is degenerated to an identity. The Mahalanobis distance leads to hyperellipsoidal kernels and the Euclidean distance results in hyperspherical ones. In this brief, the Mahalanobis distance-based kernel in a reproducing kernel Hilbert space is developed systematically. Extensive experiments demonstrate that the hyperellipsoidal kernels slightly outperform the hyperspherical ones, with fewer SVs.
National Aeronautics and Space Administration — This data set includes the complete set of SPICE data for one NEAR mission phase in the form of SPICE kernels, which can be accessed using SPICE software available...
Sparse Bayesian modeling with adaptive kernel learning.
Tzikas, Dimitris G; Likas, Aristidis C; Galatsanos, Nikolaos P
2009-06-01
Sparse kernel methods are very efficient in solving regression and classification problems. The sparsity and performance of these methods depend on selecting an appropriate kernel function, which is typically achieved using a cross-validation procedure. In this paper, we propose an incremental method for supervised learning, which is similar to the relevance vector machine (RVM) but also learns the parameters of the kernels during model training. Specifically, we learn different parameter values for each kernel, resulting in a very flexible model. In order to avoid overfitting, we use a sparsity enforcing prior that controls the effective number of parameters of the model. We present experimental results on artificial data to demonstrate the advantages of the proposed method and we provide a comparison with the typical RVM on several commonly used regression and classification data sets.
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 Cassini SPICE data files (kernel files''), which can be accessed using SPICE software. The SPICE data contains geometric...
Parsimonious Wavelet Kernel Extreme Learning Machine
Directory of Open Access Journals (Sweden)
Wang Qin
2015-11-01
Full Text Available In this study, a parsimonious scheme for wavelet kernel extreme learning machine (named PWKELM was introduced by combining wavelet theory and a parsimonious algorithm into kernel extreme learning machine (KELM. In the wavelet analysis, bases that were localized in time and frequency to represent various signals effectively were used. Wavelet kernel extreme learning machine (WELM maximized its capability to capture the essential features in “frequency-rich” signals. The proposed parsimonious algorithm also incorporated significant wavelet kernel functions via iteration in virtue of Householder matrix, thus producing a sparse solution that eased the computational burden and improved numerical stability. The experimental results achieved from the synthetic dataset and a gas furnace instance demonstrated that the proposed PWKELM is efficient and feasible in terms of improving generalization accuracy and real time performance.
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...
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...
National Aeronautics and Space Administration — This data set includes the complete set of EPOXI SPICE data files (kernel files''), which can be accessed using SPICE software. The SPICE data contains geometric and...
Multiple Kernel Learning with Data Augmentation
2016-11-22
Intelligence and Artificial Neural Networks Symposium (TAINN 96. Citeseer, 1996. Erling D Andersen and Knud D Andersen. The mosek interior point optimizer...Zien, and Sören Sonnen- burg. Efficient and accurate lp-norm multiple kernel learning . In Advances in neural information processing systems, pages 997...JMLR: Workshop and Conference Proceedings 63:49–64, 2016 ACML 2016 Multiple Kernel Learning with Data Augmentation Khanh Nguyen nkhanh@deakin.edu.au
Covariance Kernels from Bayesian Generative Models
Seeger, Matthias
2002-01-01
We propose the framework of mutual information kernels for learning covariance kernels, as used in Support Vector machines and Gaussian process classifiers, from unlabeled task data using Bayesian techniques. We describe an implementation of this framework which uses variational Bayesian mixtures of factor analyzers in order to attack classification problems in high-dimensional spaces where labeled data is sparse, but unlabeled data is abundant.
Future relativistic heavy ion experiments
Energy Technology Data Exchange (ETDEWEB)
Pugh, H.G.
1980-12-01
Equations of state for nuclear matter and ongoing experimental studies are discussed. Relativistic heavy ion physics is the only opportunity to study in the laboratory the properties of extended multiquark systems under conditions such that quarks might run together into new arrangements previously unobserved. Several lines of further study are mentioned. (GHT)
Revisiting non-relativistic limits
Energy Technology Data Exchange (ETDEWEB)
Jensen, Kristan [C.N. Yang Institute for Theoretical Physics, SUNY Stony Brook,Stony Brook, NY 11794-3840 (United States); Karch, Andreas [Department of Physics, University of Washington,Seattle, WA 98195 (United States)
2015-04-28
We show that the full spurionic symmetry of Galilean-invariant field theories can be deduced when those theories are the limits of relativistic parents. Under the limit, the non-relativistic daughter couples to Newton-Cartan geometry together with all of the symmetries advocated in previous work, including the recently revived Milne boosts. Our limit is a covariant version of the usual one, where we start with a gapped relativistic theory with a conserved charge, turn on a chemical potential equal to the rest mass of the lightest charged state, and then zoom in to the low energy sector. This procedure gives a simple physical interpretation for the Milne boosts. Our methods even apply when there is a magnetic moment, which is known to modify the non-relativistic symmetry transformations. We focus on two examples. Free scalars are used to demonstrate the basic procedure, whereas hydrodynamics is used in order to exhibit the power of this approach in a fully dynamical setting, correcting several inaccuracies in the existing literature.
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 ...
Lee, Khiy Wei; Murid, Ali H. M.; Sangawi, Ali W. K.
2017-08-01
We study a numerical approach for solving integral equation with adjoint generalized Neumann kernel related to conformal mapping. Previously, computation of conformal mapping of M + 1 connected regions require solving at least M + 1 integral equations with adjoint generalized Neumann kernel separately. We apply global simpler GMRES which solve nonsymmetric system with multiple right-hand sides to solve M + 1 integral equations simultaneously. We also apply fast multipole method for several matrix vector products in every iteration of global simpler GMRES. Numerical example is given to illustrate the effectiveness of the proposed method.
A new kernel discriminant analysis framework for electronic nose recognition.
Zhang, Lei; Tian, Feng-Chun
2014-03-13
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. Copyright © 2014 Elsevier B.V. All rights reserved.
Hanft, J M; Jones, R J
1986-06-01
Kernels cultured in vitro were induced to abort by high temperature (35 degrees C) and by culturing six kernels/cob piece. Aborting kernels failed to enter a linear phase of dry mass accumulation and had a final mass that was less than 6% of nonaborting field-grown kernels. Kernels induced to abort by high temperature failed to synthesize starch in the endosperm and had elevated sucrose concentrations and low fructose and glucose concentrations in the pedicel during early growth compared to nonaborting kernels. Kernels induced to abort by high temperature also had much lower pedicel soluble acid invertase activities than did nonaborting kernels. These results suggest that high temperature during the lag phase of kernel growth may impair the process of sucrose unloading in the pedicel by indirectly inhibiting soluble acid invertase activity and prevent starch synthesis in the endosperm. Kernels induced to abort by culturing six kernels/cob piece had reduced pedicel fructose, glucose, and sucrose concentrations compared to kernels from field-grown ears. These aborting kernels also had a lower pedicel soluble acid invertase activity compared to nonaborting kernels from the same cob piece and from field-grown ears. The low invertase activity in pedicel tissue of the aborting kernels was probably caused by a lack of substrate (sucrose) for the invertase to cleave due to the intense competition for available assimilates. In contrast to kernels cultured at 35 degrees C, aborting kernels from cob pieces containing all six kernels accumulated starch in a linear fashion. These results indicate that kernels cultured six/cob piece abort because of an inadequate supply of sugar and are similar to apical kernels from field-grown ears that often abort prior to the onset of linear growth.
Li, Yinian; Wang, Jun; Xie, Weizhong; Lu, Daxin; Ding, Weimin
2013-10-01
Physicochemical properties of wheat grains with largest kernel thickness always was lowest than the other sections, examination of microstructure of wheat grains can help us understand this phenomena. Two varieties of wheat, soft white winter wheat Yangmai 11 and hard white winter wheat Zhengmai 9023, were fractionated into five sections by kernel thickness. Then the fractionated wheat grains in 2.7-3.0 mm section were separated into three fractions by kernel specific density sequentially. Microstructure of the fractured surface were evaluated at different scale level to two varieties wheat with different kernel thickness and specific density by using environmental scanning electron microscopy. Compactness and size of endosperm cell tended to decrease with decreasing wheat kernel thickness and specific density. Protein matrix tended to increase with decreasing wheat kernel thickness and specific density. Size of starch granules and proportion for different type starch granules also varied with different wheat kernel thickness and specific density. Those microstructure properties of the fractured surface, formation of endosperm cells, protein matrix and starch granules were close related to rheological properties and pasting properties of wheat grains.
Wheat kernel dimensions: how do they contribute to kernel weight at ...
Indian Academy of Sciences (India)
2011-12-02
Dec 2, 2011 ... Keywords. wheat; kernel dimensions; thousand-kernel weight; conditional QTL mapping; genetic relationship. Journal of Genetics, Vol .... E. 2,. E3 and. E. 4 represent the environments of. 2008–2009 in. T aian,. 2009–2010 in. T aian,. 2009–2010 in. Zaozhuang and. 2009–2010 in. Jining, respectively. c. WJ.
Relativistic quantum mechanics an introduction to relativistic quantum fields
Maiani, Luciano
2016-01-01
Written by two of the world's leading experts on particle physics and the standard model - including an award-winning former Director General of CERN - this textbook provides a completely up-to-date account of relativistic quantum mechanics and quantum field theory. It describes the formal and phenomenological aspects of the standard model of particle physics, and is suitable for advanced undergraduate and graduate students studying both theoretical and experimental physics.
Separate Colors, Separate Minds.
Meyers, Michael; Nidiry, John P.
2002-01-01
Explains that racial separation causes cultural separation, and the way to improve race relations is to continue to move toward integration. Discusses the need to debunk race, examining racial issues in education. Highlights the importance of actively supporting integration and opposing separatism, explaining that for there to be social progress,…
Extended-Maxima Transform Watershed Segmentation Algorithm for Touching Corn Kernels
Directory of Open Access Journals (Sweden)
Yibo Qin
2013-01-01
Full Text Available Touching corn kernels are usually oversegmented by the traditional watershed algorithm. This paper proposes a modified watershed segmentation algorithm based on the extended-maxima transform. Firstly, a distance-transformed image is processed by the extended-maxima transform in the range of the optimized threshold value. Secondly, the binary image obtained by the preceding process is run through the watershed segmentation algorithm, and watershed ridge lines are superimposed on the original image, so that touching corn kernels are separated into segments. Fifty images which all contain 400 corn kernels were tested. Experimental results showed that the effect of segmentation is satisfactory by the improved algorithm, and the accuracy of segmentation is as high as 99.87%.
Numerical integration of a relativistic two-body problem via a multiple scales method
Abouelmagd, Elbaz I.; Elshaboury, S. M.; Selim, H. H.
2016-01-01
We offer an analytical study on the dynamics of a two-body problem perturbed by small post-Newtonian relativistic term. We prove that, while the angular momentum is not conserved, the motion is planar. We also show that the energy is subject to small changes due to the relativistic effect. We also offer a periodic solution to this problem, obtained by a method based on the separation of time scales. We demonstrate that our solution is more general than the method developed in the book by Brumberg (Essential Relativistic Celestial Mechanics, Hilger, Bristol, 1991). The practical applicability of this model may be in studies of the long-term evolution of relativistic binaries (neutron stars or black holes).
Diffraction radiation from relativistic particles
Potylitsyn, Alexander Petrovich; Strikhanov, Mikhail Nikolaevich; Tishchenko, Alexey Alexandrovich
2010-01-01
This book deals with diffraction radiation, which implies the boundary problems of electromagnetic radiation theory. Diffraction radiation is generated when a charged particle moves in a vacuum near a target edge. Diffraction radiation of non-relativistic particles is widely used to design intense emitters in the cm wavelength range. Diffraction radiation from relativistic charged particles is important for noninvasive beam diagnostics and design of free electron lasers based on Smith-Purcell radiation which is diffraction radiation from periodic structures. Different analytical models of diffraction radiation and results of recent experimental studies are presented in this book. The book may also serve as guide to classical electrodynamics applications in beam physics and electrodynamics. It can be of great use for young researchers to develop skills and for experienced scientists to obtain new results.
Kinetic approach to relativistic dissipation
Gabbana, A.; Mendoza, M.; Succi, S.; Tripiccione, R.
2017-08-01
Despite a long record of intense effort, the basic mechanisms by which dissipation emerges from the microscopic dynamics of a relativistic fluid still elude complete understanding. In particular, several details must still be finalized in the pathway from kinetic theory to hydrodynamics mainly in the derivation of the values of the transport coefficients. In this paper, we approach the problem by matching data from lattice-kinetic simulations with analytical predictions. Our numerical results provide neat evidence in favor of the Chapman-Enskog [The Mathematical Theory of Non-Uniform Gases, 3rd ed. (Cambridge University Press, Cambridge, U.K., 1970)] procedure as suggested by recent theoretical analyses along with qualitative hints at the basic reasons why the Chapman-Enskog expansion might be better suited than Grad's method [Commun. Pure Appl. Math. 2, 331 (1949), 10.1002/cpa.3160020403] to capture the emergence of dissipative effects in relativistic fluids.
Relativistic electron beams above thunderclouds
DEFF Research Database (Denmark)
Füellekrug, M.; Roussel-Dupre, R.; Symbalisty, E. M. D.
2011-01-01
Non-luminous relativistic electron beams above thunderclouds have been detected by the radio signals of low frequency similar to 40-400 kHz which they radiate. The electron beams occur similar to 2-9 ms after positive cloud-to-ground lightning discharges at heights between similar to 22-72 km above...... thunderclouds. Intense positive lightning discharges can also cause sprites which occur either above or prior to the electron beam. One electron beam was detected without any luminous sprite which suggests that electron beams may also occur independently of sprites. Numerical simulations show that beams...... of electrons partially discharge the lightning electric field above thunderclouds and thereby gain a mean energy of similar to 7MeV to transport a total charge of similar to-10mC upwards. The impulsive current similar to 3 x 10(-3) Am-2 associated with relativistic electron beams above thunderclouds...
Relativistic stars in bigravity theory
Aoki, Katsuki; Tanabe, Makoto
2016-01-01
Assuming static and spherically symmetric spacetimes in the ghost-free bigravity theory, we find a relativistic star solution, which is very close to that in general relativity. The coupling constants are classified into two classes: Class [I] and Class [II]. Although the Vainshtein screening mechanism is found in the weak gravitational field for both classes, we find that there is no regular solution beyond the critical value of the compactness in Class [I]. This implies that the maximum mass of a neutron star in Class [I] becomes much smaller than that in GR. On the other hand, for the solution in Class [II], the Vainshtein screening mechanism works well even in a relativistic star and the result in GR is recovered.
Special vortex in relativistic hydrodynamics
Chupakhin, A. P.; Yanchenko, A. A.
2017-10-01
An exact solution of the Euler equations governing the flow of a compressible fluid in relativistic hydrodynamics is found and studied. It is a relativistic analogue of the Ovsyannikov vortex (special vortex) investigated earlier for classical gas dynamics. Solutions are partially invariant of Defect 1 and Rank 2 with respect to the rotation group. A theorem on the representation of the factor-system in the form of a union of a non-invariant subsystem for the function determining the deviation of the velocity vector from the meridian, and invariant subsystem for determination of thermodynamic parameters, the Lorentz factor and the radial velocity component is proved. Compatibility conditions for the overdetermined non-invariant subsystem are obtained. A stationary solution of this type is studied in detail. It is proved that its invariant subsystem reduces to an implicit differential equation. For this equation, the manifold of branching of solutions is investigated, and a set of singular points is found.
Towards a relativistic statistical theory
Kaniadakis, G.
2006-06-01
In special relativity the mathematical expressions, defining physical observables as the momentum, the energy etc. emerge as one parameter (light speed) continuous deformations of the corresponding ones of the classical physics. Here, we show that the special relativity imposes a proper one parameter continuous deformation also to the expression of the classical Boltzmann-Gibbs-Shannon entropy. The obtained relativistic entropy permits to construct a coherent and selfconsistent relativistic statistical theory [G. Kaniadakis, Phys. Rev. E 66 (2002) 056125; G. Kaniadakis, Phys. Rev. E 72 (2005) 036108], preserving the main features (maximum entropy principle, thermodynamic stability, Lesche stability, continuity, symmetry, expansivity, decisivity, etc.) of the classical statistical theory, which is recovered in the classical limit. The predicted distribution function is a one-parameter continuous deformation of the classical Maxwell-Boltzmann distribution and has a simple analytic form, showing power-law tails in accordance with the experimental evidence.
Online Sequential Extreme Learning Machine With Kernels.
Scardapane, Simone; Comminiello, Danilo; Scarpiniti, Michele; Uncini, Aurelio
2015-09-01
The extreme learning machine (ELM) was recently proposed as a unifying framework for different families of learning algorithms. The classical ELM model consists of a linear combination of a fixed number of nonlinear expansions of the input vector. Learning in ELM is hence equivalent to finding the optimal weights that minimize the error on a dataset. The update works in batch mode, either with explicit feature mappings or with implicit mappings defined by kernels. Although an online version has been proposed for the former, no work has been done up to this point for the latter, and whether an efficient learning algorithm for online kernel-based ELM exists remains an open problem. By explicating some connections between nonlinear adaptive filtering and ELM theory, in this brief, we present an algorithm for this task. In particular, we propose a straightforward extension of the well-known kernel recursive least-squares, belonging to the kernel adaptive filtering (KAF) family, to the ELM framework. We call the resulting algorithm the kernel online sequential ELM (KOS-ELM). Moreover, we consider two different criteria used in the KAF field to obtain sparse filters and extend them to our context. We show that KOS-ELM, with their integration, can result in a highly efficient algorithm, both in terms of obtained generalization error and training time. Empirical evaluations demonstrate interesting results on some benchmarking datasets.
Relativistic gravitational deflection of photons
Saca, J M
2002-01-01
A relativistic analysis of the deflection of a light ray due to a massive attractive centre is here developed by solving a differential equation of the orbit of photons. Results are compared with a widely known approximate formula for the deflection obtained by Einstein in 1916. Finally, it is concluded that the results here obtained, although very close to Einstein's values, could stand out as a conclusive reference for comparison with future direct measurements of the deflection.
Relativistic approach to electromagnetic imaging
Budko, Neil
2004-01-01
A novel imaging principle based on the interaction of electromagnetic waves with a beam of relativistic electrons is proposed. Wave-particle interaction is assumed to take place in a small spatial domain, so that each electron is only briefly accelerated by the incident field. In the one-dimensional case the spatial distribution of the source density can be directly observed in the temporal spectrum of the scattered field. Whereas, in the two-dimensional case the relation between the source a...
Pythagoras Theorem and Relativistic Kinematics
Mulaj, Zenun; Dhoqina, Polikron
2010-01-01
In two inertial frames that move in a particular direction, may be registered a light signal that propagates in an angle with this direction. Applying Pythagoras theorem and principles of STR in both systems, we can derive all relativistic kinematics relations like the relativity of simultaneity of events, of the time interval, of the length of objects, of the velocity of the material point, Lorentz transformations, Doppler effect and stellar aberration.
Intense Relativistic Electron Beam Investigations
1979-04-01
dif- fusion pump furnished with the electron beam machine was sized to hold vacuum rathcr thani to ,achieve rapid pump down, we were limited to 2 or...camera and lasers as well as providing an advance synchronized trigger pulse to the oscilloscopes. Since this water filled spark gap switch initiates...Equipment Source NRL 0.5 XeV 7 ohm relativistic "electron beam machine Government furnished Capacitor bank and magnetic field solenoid 4’ long with
A special relativistic heat engine
Directory of Open Access Journals (Sweden)
William S. Cariens
1983-01-01
main concepts taken from themodynamics and special relativity are those of a heat engine and E=mc2 respectively. Central to understanding the operation of this relativistic heat engine is the fact that upon heating a mass, its rest mass increases! This concept is nonexistent in classical thermodynamics. An increase in rest mass means that both the internal energy of a mass and its macroscopic kinetic energy increase!!!
Radiation reaction and relativistic hydrodynamics.
Berezhiani, V I; Hazeltine, R D; Mahajan, S M
2004-05-01
By invoking the radiation reaction force, first perturbatively derived by Landau and Lifschitz, and later shown by Rohrlich to be exact for a single particle, we construct a set of fluid equations obeyed by a relativistic plasma interacting with the radiation field. After showing that this approach reproduces the known results for a locally Maxwellian plasma, we derive and display the basic dynamical equations for a general magnetized plasma in which the radiation reaction force augments the direct Lorentz force.
The Crab Pulsar and Relativistic Wind
Coroniti, F. V.
2017-12-01
The possibility that the Crab pulsar produces a separated ion-dominated and pair-plasma-dominated, magnetically striped relativistic wind is assessed by rough estimates of the polar cap acceleration of the ion and electron primary beams, the pair production of secondary electrons and positrons, and a simple model of the near-magnetosphere-wind zone. For simplicity, only the orthogonal rotator is considered. Below (above) the rotational equator, ions (electrons) are accelerated in a thin sheath, of order (much less than) the width of the polar cap, to Lorentz factor {γ }i≈ (5{--}10)× {10}7({γ }e≈ {10}7). The accelerating parallel electric field is shorted out by ion-photon (curvature synchrotron) pair production. With strong, but fairly reasonable, assumptions, a set of general magnetic geometry relativistic wind equations is derived and shown to reduce to conservation relations that are similar to those of the wind from a magnetic monopole. The strength of the field-aligned currents carried by the primary beams is determined by the wind’s Alfvén critical point condition to be about eight times the Goldreich-Julian value. A simple model for the transition from the dipole region wind to the asymptotic monopole wind zone is developed. The asymptotic ratio of Poynting flux to ion (pair plasma) kinetic energy flux—the wind {σ }w∞ -parameter—is found to be of order {σ }w∞ ≈ 1/2({10}4). The far wind zone is likely to be complex, with the ion-dominated and pair-plasma-dominated magnetic stripes merging, and the oppositely directed azimuthal magnetic fields annihilating.
Relativistic Binaries in Globular Clusters
Directory of Open Access Journals (Sweden)
Benacquista Matthew J.
2006-02-01
Full Text Available The galactic population of globular clusters are old, dense star systems, with a typical cluster containing 10^4 - 10^7 stars. As an old population of stars, globular clusters contain many collapsed and degenerate objects. As a dense population of stars, globular clusters are the scene of many interesting close dynamical interactions between stars. These dynamical interactions can alter the evolution of individual stars and can produce tight binary systems containing one or two compact objects. In this review, we discuss the theoretical models of globular cluster evolution and binary evolution, techniques for simulating this evolution which lead to relativistic binaries, and current and possible future observational evidence for this population. Globular cluster evolution will focus on the properties that boost the production of hard binary systems and on the tidal interactions of the galaxy with the cluster, which tend to alter the structure of the globular cluster with time. The interaction of the components of hard binary systems alters the evolution of both bodies and can lead to exotic objects. Direct N-body integrations and Fokker-Planck simulations of the evolution of globular clusters that incorporate tidal interactions and lead to predictions of relativistic binary populations are also discussed. We discuss the current observational evidence for cataclysmic variables, millisecond pulsars, and low-mass X-ray binaries as well as possible future detection of relativistic binaries with gravitational radiation.
Relativistic Binaries in Globular Clusters
Directory of Open Access Journals (Sweden)
Benacquista Matthew
2002-01-01
Full Text Available The galactic population of globular clusters are old, dense star systems, with a typical cluster containing $10^4 - 10^6$ stars. As an old population of stars, globular clusters contain many collapsed and degenerate objects. As a dense population of stars, globular clusters are the scene of many interesting close dynamical interactions between stars. These dynamical interactions can alter the evolution of individual stars and can produce tight binary systems containing one or two compact objects. In this review, we discuss the theoretical models of globular cluster evolution and binary evolution, techniques for simulating this evolution which lead to relativistic binaries, and current and possible future observational evidence for this population. Globular cluster evolution will focus on the properties that boost the production of hard binary systems and on the tidal interactions of the galaxy with the cluster, which tend to alter the structure of the globular cluster with time. The interaction of the components of hard binary systems alters the evolution of both bodies and can lead to exotic objects. Direct $N$-body integrations and Fokker--Planck simulations of the evolution of globular clusters that incorporate tidal interactions and lead to predictions of relativistic binary populations are also discussed. We discuss the current observational evidence for cataclysmic variables, millisecond pulsars, and low-mass X-ray binaries as well as possible future detection of relativistic binaries with gravitational radiation.
Relativistic Binaries in Globular Clusters
Directory of Open Access Journals (Sweden)
Matthew J. Benacquista
2013-03-01
Full Text Available Galactic globular clusters are old, dense star systems typically containing 10^4 – 10^6 stars. As an old population of stars, globular clusters contain many collapsed and degenerate objects. As a dense population of stars, globular clusters are the scene of many interesting close dynamical interactions between stars. These dynamical interactions can alter the evolution of individual stars and can produce tight binary systems containing one or two compact objects. In this review, we discuss theoretical models of globular cluster evolution and binary evolution, techniques for simulating this evolution that leads to relativistic binaries, and current and possible future observational evidence for this population. Our discussion of globular cluster evolution will focus on the processes that boost the production of tight binary systems and the subsequent interaction of these binaries that can alter the properties of both bodies and can lead to exotic objects. Direct N-body integrations and Fokker–Planck simulations of the evolution of globular clusters that incorporate tidal interactions and lead to predictions of relativistic binary populations are also discussed. We discuss the current observational evidence for cataclysmic variables, millisecond pulsars, and low-mass X-ray binaries as well as possible future detection of relativistic binaries with gravitational radiation.
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
A point kernel algorithm for microbeam radiation therapy
Debus, Charlotte; Oelfke, Uwe; Bartzsch, Stefan
2017-11-01
Microbeam radiation therapy (MRT) is a treatment approach in radiation therapy where the treatment field is spatially fractionated into arrays of a few tens of micrometre wide planar beams of unusually high peak doses separated by low dose regions of several hundred micrometre width. In preclinical studies, this treatment approach has proven to spare normal tissue more effectively than conventional radiation therapy, while being equally efficient in tumour control. So far dose calculations in MRT, a prerequisite for future clinical applications are based on Monte Carlo simulations. However, they are computationally expensive, since scoring volumes have to be small. In this article a kernel based dose calculation algorithm is presented that splits the calculation into photon and electron mediated energy transport, and performs the calculation of peak and valley doses in typical MRT treatment fields within a few minutes. Kernels are analytically calculated depending on the energy spectrum and material composition. In various homogeneous materials peak, valley doses and microbeam profiles are calculated and compared to Monte Carlo simulations. For a microbeam exposure of an anthropomorphic head phantom calculated dose values are compared to measurements and Monte Carlo calculations. Except for regions close to material interfaces calculated peak dose values match Monte Carlo results within 4% and valley dose values within 8% deviation. No significant differences are observed between profiles calculated by the kernel algorithm and Monte Carlo simulations. Measurements in the head phantom agree within 4% in the peak and within 10% in the valley region. The presented algorithm is attached to the treatment planning platform VIRTUOS. It was and is used for dose calculations in preclinical and pet-clinical trials at the biomedical beamline ID17 of the European synchrotron radiation facility in Grenoble, France.
A Kernel-Based Approach for Biomedical Named Entity Recognition
Directory of Open Access Journals (Sweden)
Rakesh Patra
2013-01-01
Full Text Available Support vector machine (SVM is one of the popular machine learning techniques used in various text processing tasks including named entity recognition (NER. The performance of the SVM classifier largely depends on the appropriateness of the kernel function. In the last few years a number of task-specific kernel functions have been proposed and used in various text processing tasks, for example, string kernel, graph kernel, tree kernel and so on. So far very few efforts have been devoted to the development of NER task specific kernel. In the literature we found that the tree kernel has been used in NER task only for entity boundary detection or reannotation. The conventional tree kernel is unable to execute the complete NER task on its own. In this paper we have proposed a kernel function, motivated by the tree kernel, which is able to perform the complete NER task. To examine the effectiveness of the proposed kernel, we have applied the kernel function on the openly available JNLPBA 2004 data. Our kernel executes the complete NER task and achieves reasonable accuracy.
Radiation Hazard of Relativistic Interstellar Flight
Semyonov, Oleg G.
2006-01-01
From the point of view of radiation safety, interstellar space is not an empty void. Interstellar gas and cosmic rays, which consist of hydrogen and helium nucleons, present a severe radiation hazard to crew and electronics aboard a relativistic interstellar ship. Of the two, the oncoming relativistic flow of interstellar gas produces the most intence radiation. A protection shield will be needed to block relativistic interstellar gas that can also absorb most of the cosmic rays which, as a r...
Cost Sensitive Online Multiple Kernel Classification
2016-11-22
dataset built from Android Malware Genome Project which is about classifying apps as malware or not. The other details are given in Table 1. Table 1...attempts to classify page blocks into text or not. The anomaly detection datasets are KDD08 (from KDD Cup 2008 dataset on breast cancer); and Malware ...Datasets D7 KDD08 102294 117 163.20 D8 Malware 208243 122 549.91 4.2. Kernels Different kernels are suitable for different types of data. For example
A kernel version of spatial factor analysis
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg
2009-01-01
Based on work by Pearson in 1901, Hotelling in 1933 introduced principal component analysis (PCA). PCA is often used for general feature generation and linear orthogonalization or compression by dimensionality reduction of correlated multivariate data, see Jolliffe for a comprehensive description...... version of PCA handles 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. In this paper we shall apply kernel versions of PCA, maximum autocorrelation factor (MAF) analysis...
Kernel parameter dependence in spatial factor analysis
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg
2010-01-01
Principal component analysis (PCA) [1] is often used for general feature generation and linear orthogonalization or compression by dimensionality reduction of correlated multivariate data, see Jolliffe [2] for a comprehensive description of PCA and related techniques. Schölkopf et al. [3] introduce...... feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply a kernel version of maximum autocorrelation factor (MAF) [7, 8] analysis to irregularly sampled stream sediment geochemistry data from South Greenland and illustrate the dependence...
Solving a Volterra integral equation with weakly singular kernel in the reproducing kernel space
Directory of Open Access Journals (Sweden)
Fazhan Geng
2010-06-01
Full Text Available In this paper, we will present a new method for a Volterra integralequation with weakly singular kernel in the reproducing kernel space. Firstly the equation is transformed into a new equivalent equation. Its exact solution is represented in the form of series in the reproducing kernel space. In the mean time, the n-term approximation $u_{n}(t$ to the exact solution $u(t$ is obtained. Some numerical examples are studied to demonstrate the accuracy of the present method. Results obtained by the method are compared with the exact solution of each example and are found to be in good agreement with each other.
Physicochemical characteristics of kernel during fruit maturation of ...
African Journals Online (AJOL)
USER
2010-04-05
. At full maturity, coconuts consist of an average of 33% husk, 16% shell, 33% kernel and 18% coconut water. (Konan, 1997). Dried mature coconut kernel, known as copra, contains 6% moisture and is one of the main coco-.
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...
Kernel maximum autocorrelation factor and minimum noise fraction transformations
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg
2010-01-01
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), kernel MAF and kernel MNF analyses handle nonlinearities by implicitly transforming data into high (even infinite......This paper introduces kernel versions of maximum autocorrelation factor (MAF) analysis and minimum noise fraction (MNF) analysis. The kernel versions 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......) dimensional feature space via the kernel function and then performing a linear analysis in that space. Three examples show the very successful application of kernel MAF/MNF analysis to 1) change detection in DLR 3K camera data recorded 0.7 seconds apart over a busy motorway, 2) change detection...
Review and Comparison of Kernel Based Fuzzy Image Segmentation Techniques
Prabhjot Kaur; Pallavi Gupta; Poonam Sharma
2012-01-01
This paper presents a detailed study and comparison of some Kernelized Fuzzy C-means Clustering based image segmentation algorithms Four algorithms have been used Fuzzy Clustering, Fuzzy C-Means(FCM) algorithm, Kernel Fuzzy C-Means(KFCM), Intuitionistic Kernelized Fuzzy C-Means(KIFCM), Kernelized Type-II Fuzzy C-Means(KT2FCM).The four algorithms are studied and analyzed both quantitatively and qualitatively. These algorithms are implemented on synthetic images in case of without noise along ...
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.
Windows Vista Kernel-Mode: Functions, Security Enhancements and Flaws
Mohammed D. ABDULMALIK; Shafi’i M. ABDULHAMID
2008-01-01
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 ...
Directed acyclic graph kernels for structural RNA analysis
Mituyama Toutai; Sato Kengo; Asai Kiyoshi; Sakakibara Yasubumi
2008-01-01
Abstract Background Recent discoveries of a large variety of important roles for non-coding RNAs (ncRNAs) have been reported by numerous researchers. In order to analyze ncRNAs by kernel methods including support vector machines, we propose stem kernels as an extension of string kernels for measuring the similarities between two RNA sequences from the viewpoint of secondary structures. However, applying stem kernels directly to large data sets of ncRNAs is impractical due to their computation...
Magnetogenesis through Relativistic Velocity Shear
Miller, Evan
Magnetic fields at all scales are prevalent in our universe. However, current cosmological models predict that initially the universe was bereft of large-scale fields. Standard magnetohydrodynamics (MHD) does not permit magnetogenesis; in the MHD Faraday's law, the change in magnetic field B depends on B itself. Thus if B is initially zero, it will remain zero for all time. A more accurate physical model is needed to explain the origins of the galactic-scale magnetic fields observed today. In this thesis, I explore two velocity-driven mechanisms for magnetogenesis in 2-fluid plasma. The first is a novel kinematic 'battery' arising from convection of vorticity. A coupling between thermal and plasma oscillations, this non-relativistic mechanism can operate in flows that are incompressible, quasi-neutral and barotropic. The second mechanism results from inclusion of thermal effects in relativistic shear flow instabilities. In such flows, parallel perturbations are ubiquitously unstable at small scales, with growth rates of order with the plasma frequency over a defined range of parameter-space. Of these two processes, instabilities seem far more likely to account for galactic magnetic fields. Stable kinematic effects will, at best, be comparable to an ideal Biermann battery, which is suspected to be orders of magnitude too weak to produce the observed galactic fields. On the other hand, instabilities grow until saturation is reached, a topic that has yet to be explored in detail on cosmological scales. In addition to investigating these magnetogenesis sources, I derive a general dispersion relation for three dimensional, warm, two species plasma with discontinuous shear flow. The mathematics of relativistic plasma, sheared-flow instability and the Biermann battery are also discussed.
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
Localized Multiple Kernel Learning A Convex Approach
2016-11-22
Computational Biology, 4, 2008. Stephen Poythress Boyd and Lieven Vandenberghe. Convex optimization. Cambridge Univ . Press, New York, 2004. Colin Campbell...2011. Gert RG Lanckriet, Nello Cristianini, Peter Bartlett, Laurent El Ghaoui, and Michael I Jordan. Learning the kernel matrix with semidefinite
Model Selection in Kernel Ridge Regression
DEFF Research Database (Denmark)
Exterkate, Peter
on these interpretations, we provide guidelines for selecting the tuning parameters from small grids using cross-validation. A Monte Carlo study 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...
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
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
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...
ACUTE AND SUBCHRONIC TOXICITY STUDIES OF KERNEL ...
African Journals Online (AJOL)
Administrator
1Department of Pure and Applied Chemistry,. 2Department of ... Therefore, this paper reports the evaluation of the safety of seed kernel extract of the .... signs of renal failure (Hassan et al., 2005). ... Medical laboratory manual for tropical countries. ... February, 2011 from www.oecd.org/dataoecd/17/51/1948378.pdf. Ojewole ...
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.)
Structural operational semantics for Kernel Andorra Prolog
S. Haridi (Seif); C. Palamidessi (Catuscia)
1991-01-01
textabstractKernel Andorra Prolog is a framework for nondeterministic concurrent constraint logic programming languages. Many languages, such as Prolog, GHC, Parlog, and Atomic Herbrand, can be seen as instances of this framework, by adding specific constraint systems and constraint operations, and
Convolution kernels for multi-wavelength imaging
Boucaud, A.; Bocchio, M.; Abergel, A.; Orieux, F.; Dole, H.; Hadj-Youcef, M. A.
2016-12-01
Astrophysical images issued from different instruments and/or spectral bands often require to be processed together, either for fitting or comparison purposes. However each image is affected by an instrumental response, also known as point-spread function (PSF), that depends on the characteristics of the instrument as well as the wavelength and the observing strategy. Given the knowledge of the PSF in each band, a straightforward way of processing images is to homogenise them all to a target PSF using convolution kernels, so that they appear as if they had been acquired by the same instrument. We propose an algorithm that generates such PSF-matching kernels, based on Wiener filtering with a tunable regularisation parameter. This method ensures all anisotropic features in the PSFs to be taken into account. We compare our method to existing procedures using measured Herschel/PACS and SPIRE PSFs and simulated JWST/MIRI PSFs. Significant gains up to two orders of magnitude are obtained with respect to the use of kernels computed assuming Gaussian or circularised PSFs. A software to compute these kernels is available at https://github.com/aboucaud/pypher
The scalar field kernel in cosmological spaces
Koksma, J.F.; Prokopec, T.|info:eu-repo/dai/nl/326113398; Rigopoulos, G.I.
2008-01-01
We construct the quantum mechanical evolution operator in the Functional Schrodinger 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
A Fast and Simple Graph Kernel for RDF
de Vries, G.K.D.; de Rooij, S.
2013-01-01
In this paper we study a graph kernel for RDF based on constructing a tree for each instance and counting the number of paths in that tree. In our experiments this kernel shows comparable classification performance to the previously introduced intersection subtree kernel, but is significantly faster
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...
A compact kernel for the calculus of inductive constructions
Indian Academy of Sciences (India)
distributed XML repository of objects respecting the format of the new kernel. The second one is a wrapper around the library of the old kernel implementation. Every time an old object is requested, we type-check it using the old kernel and we translate it to the new format. We also exploit memoization to avoid translating the ...
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...
Symmetries of relativistic world lines
Koch, Benjamin; Muñoz, Enrique; Reyes, Ignacio A.
2017-10-01
Symmetries are essential for a consistent formulation of many quantum systems. In this paper we discuss a fundamental symmetry, which is present for any Lagrangian term that involves x˙2. As a basic model that incorporates the fundamental symmetries of quantum gravity and string theory, we consider the Lagrangian action of the relativistic point particle. A path integral quantization for this seemingly simple system has long presented notorious problems. Here we show that those problems are overcome by taking into account the additional symmetry, leading directly to the exact Klein-Gordon propagator.
Quasiparticle Dynamics in Relativistic Plasmas
Yaffe, Laurence G.
2003-06-01
Quasiparticle dynamics in relativistic plasmas associated with hot, weakly-coupled gauge theories (such as QCD at asymptotically high temperature T) can be described by an effective kinetic theory, valid on sufficiently large time and distance scales. This effective kinetic theory may be used to evaluate observables which are dominantly sensitive to the dynamics of typical ultrarelativistic excitations, to leading order in the running coupling g(T) and all orders in 1/log g(T)-1. Suitable observables include transport coefficients (viscosities and diffusion constants) and energy loss rates. This summary sketches the form of the effective theory and outlines its domain of applicability.
Relativistic atomic beam spectroscopy II
Energy Technology Data Exchange (ETDEWEB)
NONE
1989-12-31
The negative ion of H is one of the simplest 3-body atomic systems. The techniques we have developed for experimental study of atoms moving near speed of light have been productive. This proposal request continuing support for experimental studies of the H{sup -} system, principally at the 800 MeV linear accelerator (LAMPF) at Los Alamos. Four experiments are currently planned: photodetachment of H{sup -} near threshold in electric field, interaction of relativistic H{sup -} ions with matter, high excitations and double charge escape in H{sup -}, and multiphoton detachment of electrons from H{sup -}.
On the Relativistic anisotropic configurations
Shojai, F; Stepanian, A
2016-01-01
In this paper we study anisotropic spherical polytropes within the framework of general relativity. Using the anisotropic Tolman-Oppenheimer-Volkov (TOV) equations, we explore the relativistic anisotropic Lane-Emden equations. We find how the anisotropic pressure affects the boundary conditions of these equations. Also we argue that the behaviour of physical quantities near the center of star changes in the presence of anisotropy. For constant density, a class of exact solution is derived with the aid of a new ansatz and its physical properties are discussed.
Relativistic solitons and superluminal signals
Energy Technology Data Exchange (ETDEWEB)
Maccari, Attilio [Technical Institute ' G. Cardano' , Piazza della Resistenza 1, Monterotondo, Rome 00015 (Italy)]. E-mail: solitone@yahoo.it
2005-02-01
Envelope solitons in the weakly nonlinear Klein-Gordon equation in 1 + 1 dimensions are investigated by the asymptotic perturbation (AP) method. Two different types of solitons are possible according to the properties of the dispersion relation. In the first case, solitons propagate with the group velocity (less than the light speed) of the carrier wave, on the contrary in the second case solitons always move with the group velocity of the carrier wave, but now this velocity is greater than the light speed. Superluminal signals are then possible in classical relativistic nonlinear field equations.
Modelling of the control of heart rate by breathing using a kernel method.
Ahmed, A K; Fakhouri, S Y; Harness, J B; Mearns, A J
1986-03-07
The process of the breathing (input) to the heart rate (output) of man is considered for system identification by the input-output relationship, using a mathematical model expressed as integral equations. The integral equation is considered and fixed so that the identification method reduces to the determination of the values within the integral, called kernels, resulting in an integral equation whose input-output behaviour is nearly identical to that of the system. This paper uses an algorithm of kernel identification of the Volterra series which greatly reduces the computational burden and eliminates the restriction of using white Gaussian input as a test signal. A second-order model is the most appropriate for a good estimate of the system dynamics. The model contains the linear part (first-order kernel) and quadratic part (second-order kernel) in parallel, and so allows for the possibility of separation between the linear and non-linear elements of the process. The response of the linear term exhibits the oscillatory input and underdamped nature of the system. The application of breathing as input to the system produces an oscillatory term which may be attributed to the nature of sinus node of the heart being sensitive to the modulating signal the breathing wave. The negative-on diagonal seems to cause the dynamic asymmetry of the total response of the system which opposes the oscillatory nature of the first kernel related to the restraining force present in the respiratory heart rate system. The presence of the positive-off diagonal of the second-order kernel of respiratory control of heart rate is an indication of an escape-like phenomenon in the system.
Rye kernel breakfast increases satiety in the afternoon - an effect of food structure
Directory of Open Access Journals (Sweden)
Fredriksson Helena
2011-04-01
Full Text Available Abstract Background The structure of whole grain cereals is maintained to varying degrees during processing and preparation of foods. Food structure can influence metabolism, including perceived hunger and satiety. A diet that enhances satiety per calorie may help to prevent excessive calorie intake. The objective of this work was to compare subjective appetite ratings after consumption of intact and milled rye kernels. Methods Two studies were performed using a randomized, cross-over design. Ratings for appetite (hunger, satiety and desire to eat were registered during an 8-h period after consumption of whole and milled rye kernels prepared as breads (study 1, n = 24 and porridges (study 2, n = 20. Sifted wheat bread was used as reference in both study parts and the products were eaten in iso-caloric portions with standardized additional breakfast foods. Breads and porridges were analyzed to determine whether structure (whole vs. milled kernels effected dietary fibre content and composition after preparation of the products. Statistical evaluation of the appetite ratings after intake of the different breakfasts was done by paired t-tests for morning and afternoon ratings separately, with subjects as random effect and type of breakfast and time points as fixed effects. Results All rye breakfasts resulted in higher satiety ratings in the morning and afternoon compared with the iso-caloric reference breakfast with sifted wheat bread. Rye bread with milled or whole kernels affected appetite equally, so no effect of structure was observed. In contrast, after consumption of the rye kernel breakfast, satiety was increased and hunger suppressed in the afternoon compared with the milled rye kernel porridge breakfast. This effect could be related to structural differences alone, because the products were equal in nutritional content including dietary fibre content and composition. Conclusions The study demonstrates that small changes in diet composition
Finite-frequency sensitivity kernels of seismic waves to fault zone structures
Allam, A. A.; Tape, C.; Ben-Zion, Y.
2015-12-01
We analyse the volumetric sensitivity of fault zone seismic head and trapped waves by constructing finite-frequency sensitivity (Fréchet) kernels for these phases using a suite of idealized and tomographically derived velocity models of fault zones. We first validate numerical calculations by waveform comparisons with analytical results for two simple fault zone models: a vertical bimaterial interface separating two solids of differing elastic properties, and a `vertical sandwich' with a vertical low velocity zone surrounded on both sides by higher velocity media. Establishing numerical accuracy up to 12 Hz, we compute sensitivity kernels for various phases that arise in these and more realistic models. In contrast to direct P body waves, which have little or no sensitivity to the internal fault zone structure, the sensitivity kernels for head waves have sharp peaks with high values near the fault in the faster medium. Surface wave kernels show the broadest spatial distribution of sensitivity, while trapped wave kernels are extremely narrow with sensitivity focused entirely inside the low-velocity fault zone layer. Trapped waves are shown to exhibit sensitivity patterns similar to Love waves, with decreasing width as a function of frequency and multiple Fresnel zones of alternating polarity. In models that include smoothing of the boundaries of the low velocity zone, there is little effect on the trapped wave kernels, which are focused in the central core of the low velocity zone. When the source is located outside a shallow fault zone layer, trapped waves propagate through the surrounding medium with body wave sensitivity before becoming confined. The results provide building blocks for full waveform tomography of fault zone regions combining high-frequency head, trapped, body, and surface waves. Such an imaging approach can constrain fault zone structure across a larger range of scales than has previously been possible.
Einstein Never Approved of Relativistic Mass
Hecht, Eugene
2009-01-01
During much of the 20th century it was widely believed that one of the significant insights of special relativity was "relativistic mass." Today there are two schools on that issue: the traditional view that embraces speed-dependent "relativistic mass," and the more modern position that rejects it, maintaining that there is only one mass and it's…
Radiatively-driven general relativistic jets
Indian Academy of Sciences (India)
Mukesh K. Vyas
2018-02-10
Feb 10, 2018 ... of radial jets and solve them using polytropic equation of state of the relativistic gas. We consider curved space- time around black holes and obtain jets with moderately relativistic terminal speeds. In addition, the radiation field from the accretion disc, is able to induce internal shocks in the jet close to the ...
Relativistic heavy-ion physics: Experimental overview
Indian Academy of Sciences (India)
Abstract. The ﬁeld of relativistic heavy-ion physics is reviewed with emphasis on new results and highlights from the ﬁrst run of the relativistic heavy-ion collider at BNL and the 15 year research programme at the super proton synchrotron (SPS) at CERN and the AGS at BNL.
Relativistic corrections to molecular dynamic dipole polarizabilities
DEFF Research Database (Denmark)
Kirpekar, Sheela; Oddershede, Jens; Jensen, Hans Jørgen Aagaard
1995-01-01
Using response function methods we report calculations of the dynamic isotropic polarizability of SnH4 and PbH4 and of the relativistic corrections to it in the random phase approximation and at the correlated multiconfigurational linear response level of approximation. All relativistic correctio...
Compton Effect with Non-Relativistic Kinematics
Shivalingaswamy, T.; Kagali, B. A.
2011-01-01
In deducing the change of wavelength of x-rays scattered by atomic electrons, one normally makes use of relativistic kinematics for electrons. However, recoiling energies of the electrons are of the order of a few keV which is less than 0.2% of their rest energies. Hence the authors may ask whether relativistic formulae are really necessary. In…
Relativistic calculations of coalescing binary neutron stars
Indian Academy of Sciences (India)
We have designed and tested a new relativistic Lagrangian hydrodynamics code, which treats gravity in the conformally flat approximation to general relativity. We have tested the resulting code extensively, finding that it performs well for calculations of equilibrium single-star models, collapsing relativistic dust clouds, and ...
Relativistic calculations of coalescing binary neutron stars
Indian Academy of Sciences (India)
Relativistic calculations of coalescing binary neutron stars. JOSHUA FABER, PHILIPPE GRANDCLÉMENT and FREDERIC RASIO. Department of Physics and Astronomy, Northwestern University, Evanston,. IL 60208-0834, USA. E-mail: rasio@mac.com. Abstract. We have designed and tested a new relativistic Lagrangian ...
Workshop on gravitational waves and relativistic astrophysics
Indian Academy of Sciences (India)
This workshop saw five presentations in the field of gravitational radiation and two on compact, relativistic self-gravitating systems. Gravitational waves (GWs) and black holes (BHs) are two of the most significant predictions of Einstein's relativistic theory of gravity and, as far as their experimental status is concerned, both of ...
Population Density Equations for Stochastic Processes with Memory Kernels
Lai, Yi Ming
2016-01-01
We present a novel method for solving population density equations, where the populations can be subject to non-Markov noise for arbitrary distributions of jump sizes. There are important advantages over earlier methods: instead of introducing an extra dimension, we find that the history of the noise process can always be accounted for by the convolution of a kernel of limited depth with a history of the density, rendering the method more efficient. Excitatory and inhibitory input contributions can be treated on equal footing. Transient results can be modeled accurately, which is of vital importance as population density methods are increasingly used to model neural circuits. This method can be used in network simulations where analytic results are not available. The method cleanly separates deterministic and stochastic processes, leaving only the evolution of the stochastic process to be solved. This allows for a direct incorporation of novel developments in the theory of random walks. We demonstrate this by...
Alba, David; Crater, Horace W.; Lusanna, Luca
2012-01-01
A new formulation of relativistic classical mechanics allows a revisiting of old unsolved problems in relativistic kinetic theory and in relativistic statistical mechanics. In particular a definition of the relativistic micro-canonical partition function is given strictly in terms of the Poincar\\'e generators of an interacting N-particle system both in the inertial and non-inertial rest frames. The non-relativistic limit allows a definition of both the inertial and non-inertial micro-canonica...
Non-relativistic scale anomalies
Energy Technology Data Exchange (ETDEWEB)
Arav, Igal [Raymond and Beverly Sackler School of Physics and Astronomy, Tel-Aviv University,55 Haim Levanon street, Tel-Aviv, 69978 (Israel); Chapman, Shira [Perimeter Institute for Theoretical Physics,31 Caroline Street North, ON N2L 2Y5 (Canada); Oz, Yaron [Raymond and Beverly Sackler School of Physics and Astronomy, Tel-Aviv University,55 Haim Levanon street, Tel-Aviv, 69978 (Israel)
2016-06-27
We extend the cohomological analysis in arXiv:1410.5831 of anisotropic Lifshitz scale anomalies. We consider non-relativistic theories with a dynamical critical exponent z=2 with or without non-relativistic boosts and a particle number symmetry. We distinguish between cases depending on whether the time direction does or does not induce a foliation structure. We analyse both 1+1 and 2+1 spacetime dimensions. In 1+1 dimensions we find no scale anomalies with Galilean boost symmetries. The anomalies in 2+1 dimensions with Galilean boosts and a foliation structure are all B-type and are identical to the Lifshitz case in the purely spatial sector. With Galilean boosts and without a foliation structure we find also an A-type scale anomaly. There is an infinite ladder of B-type anomalies in the absence of a foliation structure with or without Galilean boosts. We discuss the relation between the existence of a foliation structure and the causality of the field theory.
Lecture Series on Relativistic Quantum Information
Fuentes, Ivette
2013-09-01
The insight that the world is fundamentally quantum mechanical inspired the development of quantum information theory. However, the world is not only quantum but also relativistic, and indeed many implementations of quantum information tasks involve truly relativistic systems. In this lecture series I consider relativistic effects on entanglement in flat and curved spacetimes. I will emphasize the qualitative differences to a non-relativistic treatment, and demonstrate that a thorough understanding of quantum information theory requires taking relativity into account. The exploitation of such relativistic effects will likely play an increasing role in the future development of quantum information theory. The relevance of these results extends beyond pure quantum information theory, and applications to foundational questions in cosmology and black hole physics will be presented.
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.
Kernel based orthogonalization for change detection in hyperspectral images
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg
Kernel versions of principal component analysis (PCA) and minimum noise fraction (MNF) analysis are applied to change detection in hyperspectral image (HyMap) data. The kernel versions are based on so-called Q-mode analysis in which the data enter into the analysis via inner products in the Gram...... 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...
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....... via inner products in the Gram 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...
Geodesic exponential kernels: When Curvature and Linearity Conflict
DEFF Research Database (Denmark)
Feragen, Aase; Lauze, François; Hauberg, Søren
2015-01-01
We consider kernel methods on general geodesic metric spaces and provide both negative and positive results. First we show that the common Gaussian kernel can only be generalized to a positive definite kernel on a geodesic metric space if the space is flat. As a result, for data on a Riemannian...... manifold, the geodesic Gaussian kernel is only positive definite if the Riemannian manifold is Euclidean. This implies that any attempt to design geodesic Gaussian kernels on curved Riemannian manifolds is futile. However, we show that for spaces with conditionally negative definite distances the geodesic...... Laplacian kernel can be generalized while retaining positive definiteness. This implies that geodesic Laplacian kernels can be generalized to some curved spaces, including spheres and hyperbolic spaces. Our theoretical results are verified empirically....
Efficient $\\chi ^{2}$ Kernel Linearization via Random Feature Maps.
Yuan, Xiao-Tong; Wang, Zhenzhen; Deng, Jiankang; Liu, Qingshan
2016-11-01
Explicit feature mapping is an appealing way to linearize additive kernels, such as χ2 kernel for training large-scale support vector machines (SVMs). Although accurate in approximation, feature mapping could pose computational challenges in high-dimensional settings as it expands the original features to a higher dimensional space. To handle this issue in the context of χ2 kernel SVMs learning, we introduce a simple yet efficient method to approximately linearize χ2 kernel through random feature maps. The main idea is to use sparse random projection to reduce the dimensionality of feature maps while preserving their approximation capability to the original kernel. We provide approximation error bound for the proposed method. Furthermore, we extend our method to χ2 multiple kernel SVMs learning. Extensive experiments on large-scale image classification tasks confirm that the proposed approach is able to significantly speed up the training process of the χ2 kernel SVMs at almost no cost of testing accuracy.
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...
Relativistic Band Structure and Fermi Surface of PdTe2 by the LMTO Method
DEFF Research Database (Denmark)
Jan, J. P.; Skriver, Hans Lomholt
1977-01-01
The energy bands of the trigonal layer compound PdTe2 have been calculated, using the relativistic linear muffin-tin orbitals method. The bandstructure is separated into three distinct regions with low-lying Te 5s bands, conduction bands formed by Pd 4d and Te 5p states, and high-lying bands formed...
Image registration using stationary velocity fields parameterized by norm-minimizing Wendland kernel
DEFF Research Database (Denmark)
Pai, Akshay Sadananda Uppinakudru; Sommer, Stefan Horst; Sørensen, Lauge
Interpolating kernels are crucial to solving a stationary velocity field (SVF) based image registration problem. This is because, velocity fields need to be computed in non-integer locations during integration. The regularity in the solution to the SVF registration problem is controlled by the re...... that Wendland SVF based measures separate (Alzheimer's disease v/s normal controls) better than both B-Spline SVFs (pamygdala) and B-Spline freeform deformation (pamygdala and cortical gray matter)....
Fredholm-Volterra integral equation of the first kind with potential kernel
Directory of Open Access Journals (Sweden)
M. H. Fahmy
2000-05-01
Full Text Available A series method is used to separate the variables of position and time for the Fredholm-Volterra integral equation of the first kind and the solution of the system in L_2 [0,1] × C[0,T], 0 ≤ t ≤ T is obtained, the Fredholm integral equation is discussed using Krein's method. The kernel is written in a Legendre polynomial form. Some important relations are also, established and discussed.
P Aarumugam; P. Saravana Bhavan; Muralisankar, T.; N. Manickam; V. Srinevasan; Radhakrishnan, S.
2013-01-01
The growth promoting potential of fruits wastes, mango seed kernel, banana peel and papaya peel on the freshwater prawn, Macrobrachium rosenbergii post larvae (PL) was evaluated. Basal diet equated to 35% protein was prepared by using soybean meal, groundnut oilcake, horse gram and wheat flour. Each fruit waste powder was separately incorporated with basal diet at a proportion of 10%. Sunflower oil was used as lipid source. Egg albumin and tapioca flour were used as binding agents. Vitamin B-...
Anatomical image-guided fluorescence molecular tomography reconstruction using kernel method
Baikejiang, Reheman; Zhao, Yue; Fite, Brett Z.; Ferrara, Katherine W.; Li, Changqing
2017-05-01
Fluorescence molecular tomography (FMT) is an important in vivo imaging modality to visualize physiological and pathological processes in small animals. However, FMT reconstruction is ill-posed and ill-conditioned due to strong optical scattering in deep tissues, which results in poor spatial resolution. It is well known that FMT image quality can be improved substantially by applying the structural guidance in the FMT reconstruction. An approach to introducing anatomical information into the FMT reconstruction is presented using the kernel method. In contrast to conventional methods that incorporate anatomical information with a Laplacian-type regularization matrix, the proposed method introduces the anatomical guidance into the projection model of FMT. The primary advantage of the proposed method is that it does not require segmentation of targets in the anatomical images. Numerical simulations and phantom experiments have been performed to demonstrate the proposed approach's feasibility. Numerical simulation results indicate that the proposed kernel method can separate two FMT targets with an edge-to-edge distance of 1 mm and is robust to false-positive guidance and inhomogeneity in the anatomical image. For the phantom experiments with two FMT targets, the kernel method has reconstructed both targets successfully, which further validates the proposed kernel method.
Effect of self-pollination monitored by microsatellite markers on maize kernel weight
Directory of Open Access Journals (Sweden)
Marcio Balestre
2007-01-01
Full Text Available The objective of this study was to evaluate the effect of fertilization by autopollen on maize kernel weight. Fivesingle cross hybrids (30F90. A2555, DKB333B, 2223, and 2324 were planted and hybrid leaf samples taken for DNAextraction. The crosses 2223XDKB333B; 2223XA2555; 2324XDKB333B and 2324XP30F90 were performed. Ten kernels ofeach ear of each cross were separated, sown in a greenhouse and the DNA of the respective seedlings was extracted, to identifythe kernel origin. The results obtained here demonstrated that allopollen increased the mean kernel weight by 16.5mg (gainof 4.65%. The proportion of sampled allopollen to self pollen was statistically equal, according to the c2 test, demonstratingthat there were no significant differences between the proportion of fertilized and sampled allopollen and autopollen in the ear.It was concluded that compared to autopollen, allopollen increases the mean weight of fertilized grain.
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.
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....
Relativistic analysis of stochastic kinematics
Giona, Massimiliano
2017-10-01
The relativistic analysis of stochastic kinematics is developed in order to determine the transformation of the effective diffusivity tensor in inertial frames. Poisson-Kac stochastic processes are initially considered. For one-dimensional spatial models, the effective diffusion coefficient measured in a frame Σ moving with velocity w with respect to the rest frame of the stochastic process is inversely proportional to the third power of the Lorentz factor γ (w ) =(1-w2/c2) -1 /2 . Subsequently, higher-dimensional processes are analyzed and it is shown that the diffusivity tensor in a moving frame becomes nonisotropic: The diffusivities parallel and orthogonal to the velocity of the moving frame scale differently with respect to γ (w ) . The analysis of discrete space-time diffusion processes permits one to obtain a general transformation theory of the tensor diffusivity, confirmed by several different simulation experiments. Several implications of the theory are also addressed and discussed.
Magnetohydrodynamic production of relativistic jets.
Meier, D L; Koide, S; Uchida, Y
2001-01-05
A number of astronomical systems have been discovered that generate collimated flows of plasma with velocities close to the speed of light. In all cases, the central object is probably a neutron star or black hole and is either accreting material from other stars or is in the initial violent stages of formation. Supercomputer simulations of the production of relativistic jets have been based on a magnetohydrodynamic model, in which differential rotation in the system creates a magnetic coil that simultaneously expels and pinches some of the infalling material. The model may explain the basic features of observed jets, including their speed and amount of collimation, and some of the details in the behavior and statistics of different jet-producing sources.
A Fast Reduced Kernel Extreme Learning Machine.
Deng, Wan-Yu; Ong, Yew-Soon; Zheng, Qing-Hua
2016-04-01
In this paper, we present a fast and accurate kernel-based supervised algorithm referred to as the Reduced Kernel Extreme Learning Machine (RKELM). In contrast to the work on Support Vector Machine (SVM) or Least Square SVM (LS-SVM), which identifies the support vectors or weight vectors iteratively, the proposed RKELM randomly selects a subset of the available data samples as support vectors (or mapping samples). By avoiding the iterative steps of SVM, significant cost savings in the training process can be readily attained, especially on Big datasets. RKELM is established based on the rigorous proof of universal learning involving reduced kernel-based SLFN. In particular, we prove that RKELM can approximate any nonlinear functions accurately under the condition of support vectors sufficiency. Experimental results on a wide variety of real world small instance size and large instance size applications in the context of binary classification, multi-class problem and regression are then reported to show that RKELM can perform at competitive level of generalized performance as the SVM/LS-SVM at only a fraction of the computational effort incurred. Copyright © 2015 Elsevier Ltd. All rights reserved.
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
Some lessons from relativistic reduction models
Ghirardi, Gian Carlo
1999-01-01
We reconsider some recently proposed relativistic dynamical reduction models and we point out the new conceptual picture about reduction processes that they impose on our considerations. Ignoring the specific technical difficulties of such generalizations we show that the just mentioned picture fits perfectly the natural ontology of the dynamical reduction program and yields a consistent description of macro-objectification in a relativistic and nonlocal context. We consider recent criticisms of the relativistic dynamical reduction program and we show that they are inappropriate, the reason being that they derive from serious misunderstandings of some technical and conceptual points of the theory. (53 refs).
The relativistic Black-Scholes model
Trzetrzelewski, Maciej
2017-02-01
The Black-Scholes equation, after a certain coordinate transformation, is equivalent to the heat equation. On the other hand the relativistic extension of the latter, the telegraphers equation, can be derived from the Euclidean version of the Dirac equation. Therefore, the relativistic extension of the Black-Scholes model follows from relativistic quantum mechanics quite naturally. We investigate this particular model for the case of European vanilla options. Due to the notion of locality incorporated in this way, one finds that the volatility frown-like effect appears when comparing to the original Black-Scholes model.
Relativistic Electron Experiment for the Undergraduate Laboratory
Marvel, Robert E
2011-01-01
We have developed an undergraduate laboratory experiment to make independent measurements of the momentum and kinetic energy of relativistic electrons from a \\beta -source. The momentum measurements are made with a magnetic spectrometer and a silicon surface-barrier detector is used to measure the kinetic energy. A plot of the kinetic energy as a function of momentum compared to the classical and relativistic predictions clearly shows the relativistic nature of the electrons. Accurate values for the rest mass of the electron and the speed of light are also extracted from the data.
Holographic Aspects of a Relativistic Nonconformal Theory
Directory of Open Access Journals (Sweden)
Chanyong Park
2013-01-01
Full Text Available We study a general D-dimensional Schwarzschild-type black brane solution of the Einstein-dilaton theory and derive, by using the holographic renormalization, its thermodynamics consistent with the geometric results. Using the membrane paradigm, we calculate the several hydrodynamic transport coefficients and compare them with the results obtained by the Kubo formula, which shows the self-consistency of the gauge/gravity duality in the relativistic nonconformal theory. In order to understand more about the relativistic non-conformal theory, we further investigate the binding energy, drag force, and holographic entanglement entropy of the relativistic non-conformal theory.
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.
Application of kernel method in fluorescence molecular tomography
Zhao, Yue; Baikejiang, Reheman; Li, Changqing
2017-02-01
Reconstruction of fluorescence molecular tomography (FMT) is an ill-posed inverse problem. Anatomical guidance in the FMT reconstruction can improve FMT reconstruction efficiently. We have developed a kernel method to introduce the anatomical guidance into FMT robustly and easily. The kernel method is from machine learning for pattern analysis and is an efficient way to represent anatomical features. For the finite element method based FMT reconstruction, we calculate a kernel function for each finite element node from an anatomical image, such as a micro-CT image. Then the fluorophore concentration at each node is represented by a kernel coefficient vector and the corresponding kernel function. In the FMT forward model, we have a new system matrix by multiplying the sensitivity matrix with the kernel matrix. Thus, the kernel coefficient vector is the unknown to be reconstructed following a standard iterative reconstruction process. We convert the FMT reconstruction problem into the kernel coefficient reconstruction problem. The desired fluorophore concentration at each node can be calculated accordingly. Numerical simulation studies have demonstrated that the proposed kernel-based algorithm can improve the spatial resolution of the reconstructed FMT images. In the proposed kernel method, the anatomical guidance can be obtained directly from the anatomical image and is included in the forward modeling. One of the advantages is that we do not need to segment the anatomical image for the targets and background.
[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.
Directed acyclic graph kernels for structural RNA analysis
Directory of Open Access Journals (Sweden)
Mituyama Toutai
2008-07-01
Full Text Available Abstract Background Recent discoveries of a large variety of important roles for non-coding RNAs (ncRNAs have been reported by numerous researchers. In order to analyze ncRNAs by kernel methods including support vector machines, we propose stem kernels as an extension of string kernels for measuring the similarities between two RNA sequences from the viewpoint of secondary structures. However, applying stem kernels directly to large data sets of ncRNAs is impractical due to their computational complexity. Results We have developed a new technique based on directed acyclic graphs (DAGs derived from base-pairing probability matrices of RNA sequences that significantly increases the computation speed of stem kernels. Furthermore, we propose profile-profile stem kernels for multiple alignments of RNA sequences which utilize base-pairing probability matrices for multiple alignments instead of those for individual sequences. Our kernels outperformed the existing methods with respect to the detection of known ncRNAs and kernel hierarchical clustering. Conclusion Stem kernels can be utilized as a reliable similarity measure of structural RNAs, and can be used in various kernel-based applications.
Directed acyclic graph kernels for structural RNA analysis.
Sato, Kengo; Mituyama, Toutai; Asai, Kiyoshi; Sakakibara, Yasubumi
2008-07-22
Recent discoveries of a large variety of important roles for non-coding RNAs (ncRNAs) have been reported by numerous researchers. In order to analyze ncRNAs by kernel methods including support vector machines, we propose stem kernels as an extension of string kernels for measuring the similarities between two RNA sequences from the viewpoint of secondary structures. However, applying stem kernels directly to large data sets of ncRNAs is impractical due to their computational complexity. We have developed a new technique based on directed acyclic graphs (DAGs) derived from base-pairing probability matrices of RNA sequences that significantly increases the computation speed of stem kernels. Furthermore, we propose profile-profile stem kernels for multiple alignments of RNA sequences which utilize base-pairing probability matrices for multiple alignments instead of those for individual sequences. Our kernels outperformed the existing methods with respect to the detection of known ncRNAs and kernel hierarchical clustering. Stem kernels can be utilized as a reliable similarity measure of structural RNAs, and can be used in various kernel-based applications.
Lee, Yi-Hsuan; von Davier, Alina A.
2008-01-01
The kernel equating method (von Davier, Holland, & Thayer, 2004) is based on a flexible family of equipercentile-like equating functions that use a Gaussian kernel to continuize the discrete score distributions. While the classical equipercentile, or percentile-rank, equating method carries out the continuization step by linear interpolation,…
Relativistic Thermodynamics: A Modern 4-Vector Approach
Directory of Open Access Journals (Sweden)
J. Güémez
2011-01-01
Full Text Available Using the Minkowski relativistic 4-vector formalism, based on Einstein's equation, and the relativistic thermodynamics asynchronous formulation (Grøn (1973, the isothermal compression of an ideal gas is analyzed, considering an electromagnetic origin for forces applied to it. This treatment is similar to the description previously developed by Van Kampen (van Kampen (1969 and Hamity (Hamity (1969. In this relativistic framework Mechanics and Thermodynamics merge in the first law of relativistic thermodynamics expressed, using 4-vector notation, such as ΔUμ = Wμ + Qμ, in Lorentz covariant formulation, which, with the covariant formalism for electromagnetic forces, constitutes a complete Lorentz covariant formulation for classical physics.
Relativistic transformation of phase-space distributions
Directory of Open Access Journals (Sweden)
R. A. Treumann
2011-07-01
Full Text Available We investigate the transformation of the distribution function in the relativistic case, a problem of interest in plasma when particles with high (relativistic velocities come into play as for instance in radiation belt physics, in the electron-cyclotron maser radiation theory, in the vicinity of high-Mach number shocks where particles are accelerated to high speeds, and generally in solar and astrophysical plasmas. We show that the phase-space volume element is a Lorentz constant and construct the general particle distribution function from first principles. Application to thermal equilibrium lets us derive a modified version of the isotropic relativistic thermal distribution, the modified Jüttner distribution corrected for the Lorentz-invariant phase-space volume element. Finally, we discuss the relativistic modification of a number of plasma parameters.
Coherent states for the relativistic harmonic oscillator
Aldaya, Victor; Guerrero, J.
1995-01-01
Recently we have obtained, on the basis of a group approach to quantization, a Bargmann-Fock-like realization of the Relativistic Harmonic Oscillator as well as a generalized Bargmann transform relating fock wave functions and a set of relativistic Hermite polynomials. Nevertheless, the relativistic creation and annihilation operators satisfy typical relativistic commutation relations of the Lie product (vector-z, vector-z(sup dagger)) approximately equals Energy (an SL(2,R) algebra). Here we find higher-order polarization operators on the SL(2,R) group, providing canonical creation and annihilation operators satisfying the Lie product (vector-a, vector-a(sup dagger)) = identity vector 1, the eigenstates of which are 'true' coherent states.
Kersten, K.; Cattell, C. A.; Breneman, A.; Goetz, K.; Kellogg, P. J.; Wygant, J. R.; Wilson, L. B., III; Blake, J. B.; Looper, M. D.; Roth, I.
2011-01-01
We present multi-satellite observations of large amplitude radiation belt whistler-mode waves and relativistic electron precipitation. On separate occasions during the Wind petal orbits and STEREO phasing orbits, Wind and STEREO recorded intense whistler-mode waves in the outer nightside equatorial radiation belt with peak-to-peak amplitudes exceeding 300 mV/m. During these intervals of intense wave activity, SAMPEX recorded relativistic electron microbursts in near magnetic conjunction with Wind and STEREO. This evidence of microburst precipitation occurring at the same time and at nearly the same magnetic local time and L-shell with a bursty temporal structure similar to that of the observed large amplitude wave packets suggests a causal connection between the two phenomena. Simulation studies corroborate this idea, showing that nonlinear wave.particle interactions may result in rapid energization and scattering on timescales comparable to those of the impulsive relativistic electron precipitation.
Ultra-low-frequency wave-driven diffusion of radiation belt relativistic electrons.
Su, Zhenpeng; Zhu, Hui; Xiao, Fuliang; Zong, Q-G; Zhou, X-Z; Zheng, Huinan; Wang, Yuming; Wang, Shui; Hao, Y-X; Gao, Zhonglei; He, Zhaoguo; Baker, D N; Spence, H E; Reeves, G D; Blake, J B; Wygant, J R
2015-12-22
Van Allen radiation belts are typically two zones of energetic particles encircling the Earth separated by the slot region. How the outer radiation belt electrons are accelerated to relativistic energies remains an unanswered question. Recent studies have presented compelling evidence for the local acceleration by very-low-frequency (VLF) chorus waves. However, there has been a competing theory to the local acceleration, radial diffusion by ultra-low-frequency (ULF) waves, whose importance has not yet been determined definitively. Here we report a unique radiation belt event with intense ULF waves but no detectable VLF chorus waves. Our results demonstrate that the ULF waves moved the inner edge of the outer radiation belt earthward 0.3 Earth radii and enhanced the relativistic electron fluxes by up to one order of magnitude near the slot region within about 10 h, providing strong evidence for the radial diffusion of radiation belt relativistic electrons.
Limits and signatures of relativistic spaceflight
Yurtsever, Ulvi; Wilkinson, Steven
2018-01-01
While special relativity imposes an absolute speed limit at the speed of light, our Universe is not empty Minkowski spacetime. The constituents that fill the interstellar/intergalactic vacuum, including the cosmic microwave background photons, impose a lower speed limit on any object travelling at relativistic velocities. Scattering of cosmic microwave photons from an ultra-relativistic object may create radiation with a characteristic signature allowing the detection of such objects at large distances.
Nuclear curvature energy in relativistic models
Energy Technology Data Exchange (ETDEWEB)
Centelles, M.; Vinas, X. [Departament dEstructura i Constituents de la Materia, Facultat de Fisica, Universitat de Barcelona, Diagonal 647, E-08028 Barcelona (Spain); Schuck, P. [Institut National de Physique Nucleaire et de Physique des Particules, Centre National de la Recherche Scientifique (CNRS--IN2P3), Universite Joseph Fourier, Institut des Sciences Nucleaires, 53 Avenue des Martyrs, F-38026 Grenoble Cedex (France)
1996-02-01
The difficulties arising in the calculation of the nuclear curvature energy are analyzed in detail, especially with reference to relativistic models. It is underlined that the implicit dependence on curvature of the quantal wave functions is directly accessible only in a semiclassical framework. It is shown that also in the relativistic models quantal and semiclassical calculations of the curvature energy are in good agreement. {copyright} {ital 1996 The American Physical Society.}
Relativistic DNLS and Kaup-Newell Hierarchy
Pashaev, Oktay K.; Lee, Jyh-Hao
2017-07-01
By the recursion operator of the Kaup-Newell hierarchy we construct the relativistic derivative NLS (RDNLS) equation and the corresponding Lax pair. In the nonrelativistic limit c → ∞ it reduces to DNLS equation and preserves integrability at any order of relativistic corrections. The compact explicit representation of the linear problem for this equation becomes possible due to notions of the q-calculus with two bases, one of which is the recursion operator, and another one is the spectral parameter.
Q-oscillators and relativistic position operators
Energy Technology Data Exchange (ETDEWEB)
Arik, M. (Dept. of Mathematics, Istanbul Technical Univ. (Turkey)); Mungan, M. (Dept. of Physics, Bogazici Univ., Istanbul (Turkey))
1992-05-21
We investigate the multi-dimensional q-oscillator whose commutation relations are invariant under the quantum group. The no-interaction limit corresponds to a contraction of the q-oscillator algebra and yields relativistic position operators which can be expressed in terms of the generators of the Poincare group. This leads to the interpretation of the interacting q-oscillator as an relativistic quantum system and results in a hamiltonian whose spectrum is exactly exponential. (orig.).
Directory of Open Access Journals (Sweden)
A Parvazian
2010-12-01
Full Text Available Fast ignition is a new method for inertial confinement fusion (ICF in which the compression and ignition steps are separated. In the first stage, fuel is compressed by laser or ion beams. In the second phase, relativistic electrons are generated by pettawat laser in the fuel. Also, in the second phase 5-35 MeV protons can be generated in the fuel. Electrons or protons can penetrate in to the ultra-dense fuel and deposit their energy in the fuel . More recently, cylindrical rather than spherical fuel chambers with magnetic control in the plasma domain have been also considered. This is called magnetized target fusion (MTF. Magnetic field has effects on relativistic electrons energy deposition rate in fuel. In this work, fast ignition method in cylindrical fuel chambers is investigated and transportation of the relativistic electrons and protons is calculated using MCNPX and FLUKA codes with 0. 25 and 0. 5 tesla magnetic field in single and dual hot spot. Furthermore, the transfer rate of relativistic electrons and high energy protons to the fuel and fusion gain are calculated. The results show that the presence of external magnetic field guarantees higher fusion gain, and relativistic electrons are much more appropriate objects for ignition. MTF in dual hot spot can be considered as an appropriate substitution for the current ICF techniques.
Relativistic entropy and related Boltzmann kinetics
Energy Technology Data Exchange (ETDEWEB)
Kaniadakis, G. [Politecnico di Torino (Italy). Dipartimento di Fisica
2009-06-15
It is well known that the particular form of the two-particle correlation function, in the collisional integral of the classical Boltzmann equation, fixes univocally the entropy of the system, which turns out to be the Boltzmann-Gibbs-Shannon entropy. In the ordinary relativistic Boltzmann equation, some standard generalizations, with respect to its classical version, imposed by the special relativity, are customarily performed. The only ingredient of the equation, which tacitly remains in its original classical form, is the two-particle correlation function, and this fact imposes that also the relativistic kinetics is governed by the Boltzmann-Gibbs-Shannon entropy. Indeed the ordinary relativistic Boltzmann equation admits as stationary stable distribution, the exponential Juttner distribution. Here, we show that the special relativity laws and the maximum entropy principle suggest a relativistic generalization also of the two-particle correlation function and then of the entropy. The so obtained, fully relativistic Boltzmann equation, obeys the H-theorem and predicts a stationary stable distribution, presenting power law tails in the high-energy region. The ensued relativistic kinetic theory preserves the main features of the classical kinetics, which recovers in the c{yields}{infinity} limit. (orig.)
The relativistic geoid: redshift and acceleration potential
Philipp, Dennis; Lämmerzahl, Claus; Puetzfeld, Dirk; Hackmann, Eva; Perlick, Volker
2017-04-01
We construct a relativistic geoid based on a time-independent redshift potential, which foliates the spacetime into isochronometric surfaces. This relativistic potential coincides with the acceleration potential for isometric congruences. We show that the a- and u- geoid, defined in a post-Newtonian framework, coincide also in a more general setup. Known Newtonian and post-Newtonian results are recovered in the respective limits. Our approach offers a relativistic definition of the Earth's geoid as well as a description of the Earth itself (or observers on its surface) in terms of an isometric congruence. Being fully relativistic, this notion of a geoid can also be applied to other compact objects such as neutron stars. By definition, this relativistic geoid can be determined by a congruence of Killing observers equipped with standard clocks by comparing their frequencies as well as by measuring accelerations of objects that follow the congruence. The redshift potential gives the correct result also for frequency comparison through optical fiber links as long as the fiber is at rest w.r.t. the congruence. We give explicit expressions for the relativistic geoid in the Kerr spacetime and the Weyl class of spacetimes. To investigate the influence of higher order mass multipole moments we compare the results for the Schwarzschild case to those obtained for the Erez-Rosen and q-metric spacetimes.
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 individua...... and specificity of 0.95 and 0.93). Both feature extraction methods can be recommended for classification of maize kernels on production scale....
Chemical and nutrition evaluation of the seed kernel of Balanites ...
African Journals Online (AJOL)
... a chemical score of 34.10%. The protein efficiency ration (PER) and net protein ratio (NPR) for the boiled seed kernel (0.18 and 1.09 respectively) were significantly higher (P<0.05) than the values for unboiled seed kernel (-0.61 and 0.40 respectively). The seed kernel may be a good source of protein in livestock feeds.
Generation of Debugging Interfaces for Linux Kernel Services
Bissyandé, Tegawendé; Réveillère, Laurent; Lawall, Julia L.; Muller, Gilles
2011-01-01
The Linux kernel does not export a stable, well-defined kernel interface, complicating the development of kernel-level services, such as device drivers and file systems. While there does exist a set of functions that are exported to external modules, these are continually changing, and have implicit, ill-documented reconditions, which, if not satisfied, can cause the entire system to crash or hang. However, no specific debugging support is provided. In this paper, we present Diagnosys, an app...
Open Problem: Kernel methods on manifolds and metric spaces
DEFF Research Database (Denmark)
Feragen, Aasa; Hauberg, Søren
2016-01-01
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....
Energy Technology Data Exchange (ETDEWEB)
Leitão, Sofia, E-mail: sofia.leitao@tecnico.ulisboa.pt [CFTP, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Stadler, Alfred, E-mail: stadler@uevora.pt [Departamento de Física, Universidade de Évora, 7000-671 Évora (Portugal); CFTP, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Peña, M.T., E-mail: teresa.pena@tecnico.ulisboa.pt [Departamento de Física, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); CFTP, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Biernat, Elmar P., E-mail: elmar.biernat@tecnico.ulisboa.pt [CFTP, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal)
2017-01-10
The Covariant Spectator Theory (CST) is used to calculate the mass spectrum and vertex functions of heavy–light and heavy mesons in Minkowski space. The covariant kernel contains Lorentz scalar, pseudoscalar, and vector contributions. The numerical calculations are performed in momentum space, where special care is taken to treat the strong singularities present in the confining kernel. The observed meson spectrum is very well reproduced after fitting a small number of model parameters. Remarkably, a fit to a few pseudoscalar meson states only, which are insensitive to spin–orbit and tensor forces and do not allow to separate the spin–spin from the central interaction, leads to essentially the same model parameters as a more general fit. This demonstrates that the covariance of the chosen interaction kernel is responsible for the very accurate prediction of the spin-dependent quark–antiquark interactions.
Simulation of relativistically colliding laser-generated electron flows
Yang, Xiaohu; Sarri, Gianluca; Borghesi, Marco
2012-01-01
The plasma dynamics resulting from the simultaneous impact, of two equal, ultra-intense laser pulses, in two spatially separated spots, onto a dense target is studied via particle-in-cell (PIC) simulations. The simulations show that electrons accelerated to relativistic speeds, cross the target and exit at its rear surface. Most energetic electrons are bound to the rear surface by the ambipolar electric field and expand along it. Their current is closed by a return current in the target, and this current configuration generates strong surface magnetic fields. The two electron sheaths collide at the midplane between the laser impact points. The magnetic repulsion between the counter-streaming electron beams separates them along the surface normal direction, before they can thermalize through other beam instabilities. This magnetic repulsion is also the driving mechanism for the beam-Weibel (filamentation) instability, which is thought to be responsible for magnetic field growth close to the internal shocks of ...
Denoising by semi-supervised kernel PCA preimaging
DEFF Research Database (Denmark)
Hansen, Toke Jansen; Abrahamsen, Trine Julie; Hansen, Lars Kai
2014-01-01
are used to improve the denoising. Moreover, by warping the Reproducing Kernel Hilbert Space (RKHS) we also account for the intrinsic manifold structure yielding a Kernel PCA basis that also benefit from unlabeled data points. Our two main contributions are; (1) a generalization of Kernel PCA......-image problem where denoised feature space points are mapped back into input space. This problem is inherently ill-posed due to the non-bijective feature space mapping. We present a semi-supervised denoising scheme based on kernel PCA and the pre-image problem, where class labels on a subset of the data points...
Visualization of nonlinear kernel models in neuroimaging by sensitivity maps
DEFF Research Database (Denmark)
Rasmussen, Peter Mondrup; Hansen, Lars Kai; Madsen, Kristoffer Hougaard
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...
General construction of reproducing kernels on a quaternionic Hilbert space
Thirulogasanthar, K.; Ali, S. Twareque
A general theory of reproducing kernels and reproducing kernel Hilbert spaces on a right quaternionic Hilbert space is presented. Positive operator-valued measures and their connection to a class of generalized quaternionic coherent states are examined. A Naimark type extension theorem associated with the positive operator-valued measures is proved in a right quaternionic Hilbert space. As illustrative examples, real, complex and quaternionic reproducing kernels and reproducing kernel Hilbert spaces arising from Hermite and Laguerre polynomials are presented. In particular, in the Laguerre case, the Naimark type extension theorem on the associated quaternionic Hilbert space is indicated.
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....
Occurrence of aflatoxin contamination in maize kernels and ...
African Journals Online (AJOL)
Occurrence of aflatoxin contamination in maize kernels and molecular characterization of the producing organism, Aspergillus. Muthusamy Karthikeyan, Arumugam Karthikeyan, Rethinasamy Velazhahan, Srinivasan Madhavan, Thangamuthu Jayaraj ...
Relativistic mean-field mass models
Energy Technology Data Exchange (ETDEWEB)
Pena-Arteaga, D.; Goriely, S.; Chamel, N. [Universite Libre de Bruxelles, Institut d' Astronomie et d' Astrophysique, CP-226, Brussels (Belgium)
2016-10-15
We present a new effort to develop viable mass models within the relativistic mean-field approach with density-dependent meson couplings, separable pairing and microscopic estimations for the translational and rotational correction energies. Two interactions, DD-MEB1 and DD-MEB2, are fitted to essentially all experimental masses, and also to charge radii and infinite nuclear matter properties as determined by microscopic models using realistic interactions. While DD-MEB1 includes the σ, ω and ρ meson fields, DD-MEB2 also considers the δ meson. Both mass models describe the 2353 experimental masses with a root mean square deviation of about 1.1 MeV and the 882 measured charge radii with a root mean square deviation of 0.029 fm. In addition, we show that the Pb isotopic shifts and moments of inertia are rather well reproduced, and the equation of state in pure neutron matter as well as symmetric nuclear matter are in relatively good agreement with existing realistic calculations. Both models predict a maximum neutron-star mass of more than 2.6 solar masses, and thus are able to accommodate the heaviest neutron stars observed so far. However, the new Lagrangians, like all previously determined RMF models, present the drawback of being characterized by a low effective mass, which leads to strong shell effects due to the strong coupling between the spin-orbit splitting and the effective mass. Complete mass tables have been generated and a comparison with other mass models is presented. (orig.)
Estimation of kernels mass ratio to total in-shell peanuts using low-cost RF impedance meter
Kandala, Chari V.; Sundaram, Jaya; Hinson, Brad
2010-04-01
In this study percentage of total kernel mass within a given mass of in-shell peanuts was determined nondestructively using a low-cost RF impedance meter. Peanut samples were divided into two groups, one the calibration and the other the validation group. Each group contained 50 samples of about 100 g of peanuts. Capacitance (C), phase angle (θ) and impedance (Z) measurements on in-shell peanut samples were made at frequencies 1 MHz, 5 MHz and 9 MHz. Ten measurements on each sample set were made, to minimize the errors due to the orientation of the peanuts as they settle between the electrodes of the impedance meter, by emptying and refilling the samples after each measurement. After completing the measurements on each set, the peanuts from that set were shelled, kernels were separated and weighed. Multi linear regression (MLR) calibration equation was developed by correlating the percentage of the kernel mass in a given peanut sample set with the measured capacitance, impedance and phase angle values. This equation was used to predict the kernel mass ratio of the samples from the validation group. The fitness of the MLR equation was verified using Standard Error of Prediction (SEP) and Root Mean Square Error of Prediction (RMSEP). Also, the predictability of total kernel mass ratio was calculated by comparing the mass ratio predicted using MLR model with the actual mass ratio determined using the conventional standard method of visual determination.
Robust kernel collaborative representation for face recognition
Huang, Wei; Wang, Xiaohui; Ma, Yanbo; Jiang, Yuzheng; Zhu, Yinghui; Jin, Zhong
2015-05-01
One of the greatest challenges of representation-based face recognition is that the training samples are usually insufficient. In other words, the training set usually does not include enough samples to show varieties of high-dimensional face images caused by illuminations, facial expressions, and postures. When the test sample is significantly different from the training samples of the same subject, the recognition performance will be sharply reduced. We propose a robust kernel collaborative representation based on virtual samples for face recognition. We think that the virtual training set conveys some reasonable and possible variations of the original training samples. Hence, we design a new object function to more closely match the representation coefficients generated from the original and virtual training sets. In order to further improve the robustness, we implement the corresponding representation-based face recognition in kernel space. It is noteworthy that any kind of virtual training samples can be used in our method. We use noised face images to obtain virtual face samples. The noise can be approximately viewed as a reflection of the varieties of illuminations, facial expressions, and postures. Our work is a simple and feasible way to obtain virtual face samples to impose Gaussian noise (and other types of noise) specifically to the original training samples to obtain possible variations of the original samples. Experimental results on the FERET, Georgia Tech, and ORL face databases show that the proposed method is more robust than two state-of-the-art face recognition methods, such as CRC and Kernel CRC.
Observation of relativistic antihydrogen atoms
Energy Technology Data Exchange (ETDEWEB)
Blanford, Glenn DelFosse
1998-01-01
An observation of relativistic antihydrogen atoms is reported in this dissertation. Experiment 862 at Fermi National Accelerator Laboratory observed antihydrogen atoms produced by the interaction of a circulating beam of high momentum (3 < p < 9 GeV/c) antiprotons and a jet of molecular hydrogen gas. Since the neutral antihydrogen does not bend in the antiproton source magnets, the detectors could be located far from the interaction point on a beamline tangent to the storage ring. The detection of the antihydrogen is accomplished by ionizing the atoms far from the interaction point. The positron is deflected by a magnetic spectrometer and detected, as are the back to back photons resulting from its annihilation. The antiproton travels a distance long enough for its momentum and time of flight to be measured accurately. A statistically significant sample of 101 antihydrogen atoms has been observed. A measurement of the cross section for {bar H}{sup 0} production is outlined within. The cross section corresponds to the process where a high momentum antiproton causes e{sup +} e{sup -} pair creation near a nucleus with the e{sup +} being captured by the antiproton. Antihydrogen is the first atom made exclusively of antimatter to be detected. The observation experiment's results are the first step towards an antihydrogen spectroscopy experiment which would measure the n = 2 Lamb shift and fine structure.
Kernel-based tests for joint independence
DEFF Research Database (Denmark)
Pfister, Niklas; Bühlmann, Peter; Schölkopf, Bernhard
2018-01-01
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......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...
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.
40 Variability Bugs in the Linux Kernel
DEFF Research Database (Denmark)
Abal Rivas, Iago; Brabrand, Claus; Wasowski, Andrzej
2014-01-01
Feature-sensitive verification is a recent field that pursues the effective analysis of the exponential number of variants of a program family. Today researchers lack examples of concrete bugs induced by variability, and occurring in real large-scale software. Such a collection of bugs...... variability affects and increases the complexity of software bugs....... 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...
Characterization of Flour from Avocado Seed Kernel
Macey A. Mahawan; Ma. Francia N. Tenorio; Jaycel A. Gomez; Rosenda A. Bronce
2015-01-01
The study focused on the Characterization of Flour from Avocado Seed Kernel. Based on the findings of the study the percentages of crude protein, crude fiber, crude fat, total carbohydrates, ash and moisture were 7.75, 4.91, 0.71, 74.65, 2.83 and 14.05 respectively. On the other hand the falling number was 495 seconds while gluten was below the detection limit of the method used. Moreover, the sensory evaluation in terms of color, texture and aroma in 0% proportion of Avocado seed flour was m...
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...
Kernel-Phase Interferometry for Super-Resolution Detection of Faint Companions
Factor, Samuel M.; Kraus, Adam L.
2017-06-01
Direct detection of close in companions (exoplanets or binary systems) is notoriously difficult. While coronagraphs and point spread function (PSF) subtraction can be used to reduce contrast and dig out signals of companions under the PSF, there are still significant limitations in separation and contrast near λ/D. Non-redundant aperture masking (NRM) interferometry can be used to detect companions well inside the PSF of a diffraction limited image, though the mask discards ˜ 95% of the light gathered by the telescope and thus the technique is severely flux limited. Kernel-phase analysis applies interferometric techniques similar to NRM to a diffraction limited image utilizing the full aperture. Instead of non-redundant closure-phases, kernel-phases are constructed from a grid of points on the full aperture, simulating a redundant interferometer. I have developed a new, easy to use, faint companion detection pipeline which analyzes kernel-phases utilizing Bayesian model comparison. I demonstrate this pipeline on archival images from HST/NICMOS, searching for new companions in order to constrain binary formation models at separations inaccessible to previous techniques. Using this method, it is possible to detect a companion well within the classical λ/D Rayleigh diffraction limit using a fraction of the telescope time as NRM. Since the James Webb Space Telescope (JWST) will be able to perform NRM observations, further development and characterization of kernel-phase analysis will allow efficient use of highly competitive JWST telescope time. As no mask is needed, this technique can easily be applied to archival data and even target acquisition images (e.g. from JWST), making the detection of close in companions cheap and simple as no additional observations are needed.
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.
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. PMID:25611971
Generalized Langevin equation with tempered memory kernel
Liemert, André; Sandev, Trifce; Kantz, Holger
2017-01-01
We study a generalized Langevin equation for a free particle in presence of a truncated power-law and Mittag-Leffler memory kernel. It is shown that in presence of truncation, the particle from subdiffusive behavior in the short time limit, turns to normal diffusion in the long time limit. The case of harmonic oscillator is considered as well, and the relaxation functions and the normalized displacement correlation function are represented in an exact form. By considering external time-dependent periodic force we obtain resonant behavior even in case of a free particle due to the influence of the environment on the particle movement. Additionally, the double-peak phenomenon in the imaginary part of the complex susceptibility is observed. It is obtained that the truncation parameter has a huge influence on the behavior of these quantities, and it is shown how the truncation parameter changes the critical frequencies. The normalized displacement correlation function for a fractional generalized Langevin equation is investigated as well. All the results are exact and given in terms of the three parameter Mittag-Leffler function and the Prabhakar generalized integral operator, which in the kernel contains a three parameter Mittag-Leffler function. Such kind of truncated Langevin equation motion can be of high relevance for the description of lateral diffusion of lipids and proteins in cell membranes.
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.
Some estimates of the Bergman kernel of minimal bounded homogeneous domains
Ishi, Hideyuki; Yamaji, Satoshi
2010-01-01
We describe the Bergman kernel of any bounded homogeneous domain in a minimal realization relating to the Bergman kernels of the Siegel disks. Taking advantage of this expression, we obtain substantial estimates of the Bergman kernel of the homogeneous domain.
... an injury to the ligaments that hold your collarbone (clavicle) to your shoulder blade. In a mild separated ... tenderness or pain near the end of your collarbone. Causes The most common cause of a separated ...
Alba, David; Crater, Horace W.; Lusanna, Luca
2015-03-01
A new formulation of relativistic classical mechanics allows a reconsideration of old unsolved problems in relativistic kinetic theory and in relativistic statistical mechanics. In particular a definition of the relativistic micro-canonical partition function is given strictly in terms of the Poincaré generators of an interacting N-particle system both in the inertial and non-inertial rest frames. The non-relativistic limit allows a definition of both the inertial and non-inertial micro-canonical ensemble in terms of the Galilei generators.
Chaos and maps in relativistic rynamical systems
Directory of Open Access Journals (Sweden)
L. P. Horwitz
2000-01-01
Full Text Available The basic work of Zaslavskii et al showed that the classical non-relativistic electromagnetically kicked oscillator can be cast into the form of an iterative map on the phase space; the resulting evolution contains a stochastic flow to unbounded energy. Subsequent studies have formulated the problem in terms of a relativistic charged particle in interaction with the electromagnetic field. We review the structure of the covariant Lorentz force used to study this problem. We show that the Lorentz force equation can be derived as well from the manifestly covariant mechanics of Stueckelberg in the presence of a standard Maxwell field, establishing a connection between these equations and mass shell constraints. We argue that these relativistic generalizations of the problem are intrinsically inaccurate due to an inconsistency in the structure of the relativistic Lorentz force, and show that a reformulation of the relativistic problem, permitting variations (classically in both the particle mass and the effective “mass” of the interacting electromagnetic field, provides a consistent system of classical equations for describing such processes.
Relativistic mixtures of charged and uncharged particles
Energy Technology Data Exchange (ETDEWEB)
Kremer, Gilberto M. [Departamento de Física, Universidade Federal do Paraná, Curitiba (Brazil)
2014-01-14
Mixtures of relativistic gases within the framework of Boltzmann equation are analyzed. Three systems are considered. The first one refers to a mixture of uncharged particles by using Grad’s moment method, where the relativistic mixture is characterized by the moments of the distribution functions: particle four-flows, energy-momentum tensors, and third-order moment tensors. In the second Fick’s law for a mixture of relativistic gases of non-disparate rest masses in a Schwarzschild metric are derived from an extension of Marle and McCormack model equations applied to a relativistic truncated Grad’s distribution function, where it is shown the dependence of the diffusion coefficient on the gravitational potential. The third one consists in the derivation of the relativistic laws of Ohm and Fourier for a binary mixtures of electrons with protons and electrons with photons subjected to external electromagnetic fields and in presence of gravitational fields by using the Anderson and Witting model of the Boltzmann equation.
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).
Linear and kernel methods for multi- and hypervariate change detection
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg; Canty, Morton J.
2010-01-01
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...
Evidence-Based Kernels: Fundamental Units of Behavioral Influence
Embry, Dennis D.; Biglan, Anthony
2008-01-01
This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior-influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of…
Screening of the kernels of Pentadesma butyracea from various ...
African Journals Online (AJOL)
Gwla10
butyracea was used to retard the ageing of skin in patented cosmetic preparation (Courtin, 1986). So far, the processing of the P. butyracea kernels into butter is artisanal and rather a tedious activity done by rural women (Sinsin and Sinadouwirou, 2003). Basically, the butter extraction from the P. butyracea kernel involves ...
Oven-drying reduces ruminal starch degradation in maize kernels
Ali, M.; Cone, J.W.; Hendriks, W.H.; Struik, P.C.
2014-01-01
The degradation of starch largely determines the feeding value of maize (Zea mays L.) for dairy cows. Normally, maize kernels are dried and ground before chemical analysis and determining degradation characteristics, whereas cows eat and digest fresh material. Drying the moist maize kernels
Nutritional status of palm kernel meal inoculated with Trichoderma ...
African Journals Online (AJOL)
The ability of Trichoderma harzanium to improve the nutritional status of palm kernel meal (P K M) was assessed over forty days of fermentation. Fermentation within this time period induced various changes in the proximate and mineral analysis of the palm kernel meal. Comparatively, the highest crude protein and ether ...
Visualization of nonlinear kernel models in neuroimaging by sensitivity maps
DEFF Research Database (Denmark)
Rasmussen, Peter Mondrup; Madsen, Kristoffer Hougaard; Lund, Torben Ellegaard
2011-01-01
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...
Ambered kernels in stenospermocarpic fruit of eastern black walnut
Michele R. Warmund; J.W. Van Sambeek
2014-01-01
"Ambers" is a term used to describe poorly filled, shriveled eastern black walnut (Juglans nigra L.) kernels with a dark brown or black-colored pellicle that are unmarketable. Studies were conducted to determine the incidence of ambered black walnut kernels and to ascertain when symptoms were apparent in specific tissues. The occurrence of...
Capturing option anomalies with a variance-dependent pricing kernel
Christoffersen, P.; Heston, S.; Jacobs, K.
2013-01-01
We develop a GARCH option model with a variance premium by combining the Heston-Nandi (2000) dynamic with a new pricing kernel that nests Rubinstein (1976) and Brennan (1979). While the pricing kernel is monotonic in the stock return and in variance, its projection onto the stock return is
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.
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
Knowledge-Based Green's Kernel for Support Vector Regression
Directory of Open Access Journals (Sweden)
Tahir Farooq
2010-01-01
Full Text Available This paper presents a novel prior knowledge-based Green's kernel for support vector regression (SVR. After reviewing the correspondence between support vector kernels used in support vector machines (SVMs and regularization operators used in regularization networks and the use of Green's function of their corresponding regularization operators to construct support vector kernels, a mathematical framework is presented to obtain the domain knowledge about magnitude of the Fourier transform of the function to be predicted and design a prior knowledge-based Green's kernel that exhibits optimal regularization properties by using the concept of matched filters. The matched filter behavior of the proposed kernel function makes it suitable for signals corrupted with noise that includes many real world systems. We conduct several experiments mostly using benchmark datasets to compare the performance of our proposed technique with the results already published in literature for other existing support vector kernel over a variety of settings including different noise levels, noise models, loss functions, and SVM variations. Experimental results indicate that knowledge-based Green's kernel could be seen as a good choice among the other candidate kernel functions.
Palm kernel agar: An alternative culture medium for rapid detection ...
African Journals Online (AJOL)
Palm kernel agar: An alternative culture medium for rapid detection of aflatoxins in agricultural commodities. ... a pink background and blue or blue green fluorescence of palm kernel agar Under long wave UV light (366nm) as against the white background of DCA, which often interferes with fluorescence with corresponding ...
Palm kernel shell as aggregate for light weight concrete | Idah ...
African Journals Online (AJOL)
In this study, the effect of replacing the conventional gravel with palm. kernel shell as aggregates in making concrete was inquired into. Several . volumes of palm kernel shells were used in two (4) different proportions with the other constituents and the strength of the concretes produced were tested to ascertain the effect of ...
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.
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...
Base catalyzed transesterification of wild apricot kernel oil for ...
African Journals Online (AJOL)
Prunus armeniaca L. grows wildly and is also cultivated at higher altitudes in temperate regions of Pakistan. Its kernel is a rich source of oil but its biodiesel production properties have not yet been exploited. During the present investigation, some quality parameters of kernel oil like acid value, free fatty acid content (as oleic ...
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.
CRKSPH - A Conservative Reproducing Kernel Smoothed Particle Hydrodynamics Scheme
Frontiere, Nicholas; Owen, J Michael
2016-01-01
We present a formulation of smoothed particle hydrodynamics (SPH) that employs a first-order consistent reproducing kernel function, exactly interpolating linear fields with particle tracers. Previous formulations using reproducing kernel (RK) interpolation have had difficulties maintaining conservation of momentum due to the fact the RK kernels are not, in general, spatially symmetric. Here, we utilize a reformulation of the fluid equations such that mass, momentum, and energy are all manifestly conserved without any assumption about kernel symmetries. Additionally, by exploiting the increased accuracy of the RK method's gradient, we formulate a simple limiter for the artificial viscosity that reduces the excess diffusion normally incurred by the ordinary SPH artificial viscosity. Collectively, we call our suite of modifications to the traditional SPH scheme Conservative Reproducing Kernel SPH, or CRKSPH. CRKSPH retains the benefits of traditional SPH methods (such as preserving Galilean invariance and manif...
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....
WKB analysis of relativistic Stern-Gerlach measurements
Palmer, Matthew C.; Takahashi, Maki; Westman, Hans F.
2013-09-01
Spin is an important quantum degree of freedom in relativistic quantum information theory. This paper provides a first-principles derivation of the observable corresponding to a Stern-Gerlach measurement with relativistic particle velocity. The specific mathematical form of the Stern-Gerlach operator is established using the transformation properties of the electromagnetic field. To confirm that this is indeed the correct operator we provide a detailed analysis of the Stern-Gerlach measurement process. We do this by applying a WKB approximation to the minimally coupled Dirac equation describing an interaction between a massive fermion and an electromagnetic field. Making use of the superposition principle we show that the +1 and -1 spin eigenstates of the proposed spin operator are split into separate packets due to the inhomogeneity of the Stern-Gerlach magnetic field. The operator we obtain is dependent on the momentum between particle and Stern-Gerlach apparatus, and is mathematically distinct from two other commonly used operators. The consequences for quantum tomography are considered.
Image quality of mixed convolution kernel in thoracic computed tomography
Neubauer, Jakob; Spira, Eva Maria; Strube, Juliane; Langer, Mathias; Voss, Christian; Kotter, Elmar
2016-01-01
Abstract The mixed convolution kernel alters his properties geographically according to the depicted organ structure, especially for the lung. Therefore, we compared the image quality of the mixed convolution kernel to standard soft and hard kernel reconstructions for different organ structures in thoracic computed tomography (CT) images. Our Ethics Committee approved this prospective study. In total, 31 patients who underwent contrast-enhanced thoracic CT studies were included after informed consent. Axial reconstructions were performed with hard, soft, and mixed convolution kernel. Three independent and blinded observers rated the image quality according to the European Guidelines for Quality Criteria of Thoracic CT for 13 organ structures. The observers rated the depiction of the structures in all reconstructions on a 5-point Likert scale. Statistical analysis was performed with the Friedman Test and post hoc analysis with the Wilcoxon rank-sum test. Compared to the soft convolution kernel, the mixed convolution kernel was rated with a higher image quality for lung parenchyma, segmental bronchi, and the border between the pleura and the thoracic wall (P < 0.03). Compared to the hard convolution kernel, the mixed convolution kernel was rated with a higher image quality for aorta, anterior mediastinal structures, paratracheal soft tissue, hilar lymph nodes, esophagus, pleuromediastinal border, large and medium sized pulmonary vessels and abdomen (P < 0.004) but a lower image quality for trachea, segmental bronchi, lung parenchyma, and skeleton (P < 0.001). The mixed convolution kernel cannot fully substitute the standard CT reconstructions. Hard and soft convolution kernel reconstructions still seem to be mandatory for thoracic CT. PMID:27858910
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.
Image quality of mixed convolution kernel in thoracic computed tomography.
Neubauer, Jakob; Spira, Eva Maria; Strube, Juliane; Langer, Mathias; Voss, Christian; Kotter, Elmar
2016-11-01
The mixed convolution kernel alters his properties geographically according to the depicted organ structure, especially for the lung. Therefore, we compared the image quality of the mixed convolution kernel to standard soft and hard kernel reconstructions for different organ structures in thoracic computed tomography (CT) images.Our Ethics Committee approved this prospective study. In total, 31 patients who underwent contrast-enhanced thoracic CT studies were included after informed consent. Axial reconstructions were performed with hard, soft, and mixed convolution kernel. Three independent and blinded observers rated the image quality according to the European Guidelines for Quality Criteria of Thoracic CT for 13 organ structures. The observers rated the depiction of the structures in all reconstructions on a 5-point Likert scale. Statistical analysis was performed with the Friedman Test and post hoc analysis with the Wilcoxon rank-sum test.Compared to the soft convolution kernel, the mixed convolution kernel was rated with a higher image quality for lung parenchyma, segmental bronchi, and the border between the pleura and the thoracic wall (P < 0.03). Compared to the hard convolution kernel, the mixed convolution kernel was rated with a higher image quality for aorta, anterior mediastinal structures, paratracheal soft tissue, hilar lymph nodes, esophagus, pleuromediastinal border, large and medium sized pulmonary vessels and abdomen (P < 0.004) but a lower image quality for trachea, segmental bronchi, lung parenchyma, and skeleton (P < 0.001).The mixed convolution kernel cannot fully substitute the standard CT reconstructions. Hard and soft convolution kernel reconstructions still seem to be mandatory for thoracic CT.
Relativistic Scott correction for atoms and molecules
DEFF Research Database (Denmark)
Solovej, Jan Philip; Sørensen, Thomas Østergaard; Spitzer, Wolfgang Ludwig
2010-01-01
We prove the first correction to the leading Thomas-Fermi energy for the ground state energy of atoms and molecules in a model where the kinetic energy of the electrons is treated relativistically. The leading Thomas-Fermi energy, established in [25], as well as the correction given here, are of ......We prove the first correction to the leading Thomas-Fermi energy for the ground state energy of atoms and molecules in a model where the kinetic energy of the electrons is treated relativistically. The leading Thomas-Fermi energy, established in [25], as well as the correction given here......, are of semiclassical nature. Our result on atoms and molecules is proved from a general semiclassical estimate for relativistic operators with potentials with Coulomb-like singularities. This semiclassical estimate is obtained using the coherent state calculus introduced in [36]. The paper contains a unified treatment...
Anisotropic Particle Acceleration in Relativistic Shear Layers
Boettcher, Markus; Liang, Edison P.; Fu, Wen
2017-08-01
We present results of Particle in Cell (PIC) simulations of relativistic shear layers as relevant to the relativistic jets of acive galactic nuclei and gamma-ray bursts. We study the self-generation of electro-magnetic fields and particle acceleration for various different plasma compositions (electron-ion vs. electron-positron pair vs. hybrid). Special emphasis is placed on the angular distribution of accelerated particles. We find that electron-ion shear layers lead to highly anisotropic particle distributions in the frame of the fast-moving inner spine. The beaming pattern of the highest-energy particles is much narrower than the characteristic beaming angle of 1/Gamma resulting from relativistic aberration of a co-moving isotropic distribution. This may pose a possible solution to the Lorentz-Factor crisis in blazars and explain very hard X-ray / soft gamma-ray spectra of some gamma-ray bursts.
Exact quantisation of the relativistic Hopfield model
Energy Technology Data Exchange (ETDEWEB)
Belgiorno, F., E-mail: francesco.belgiorno@polimi.it [Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo 32, IT-20133 Milano (Italy); INdAM-GNFM (Italy); Cacciatori, S.L., E-mail: sergio.cacciatori@uninsubria.it [Department of Science and High Technology, Università dell’Insubria, Via Valleggio 11, IT-22100 Como (Italy); INFN sezione di Milano, via Celoria 16, IT-20133 Milano (Italy); Dalla Piazza, F., E-mail: f.dallapiazza@gmail.com [Università “La Sapienza”, Dipartimento di Matematica, Piazzale A. Moro 2, I-00185, Roma (Italy); Doronzo, M., E-mail: m.doronzo@uninsubria.it [Department of Science and High Technology, Università dell’Insubria, Via Valleggio 11, IT-22100 Como (Italy)
2016-11-15
We investigate the quantisation in the Heisenberg representation of a relativistically covariant version of the Hopfield model for dielectric media, which entails the interaction of the quantum electromagnetic field with the matter dipole fields, represented by a mesoscopic polarisation field. A full quantisation of the model is provided in a covariant gauge, with the aim of maintaining explicit relativistic covariance. Breaking of the Lorentz invariance due to the intrinsic presence in the model of a preferred reference frame is also taken into account. Relativistic covariance forces us to deal with the unphysical (scalar and longitudinal) components of the fields, furthermore it introduces, in a more tricky form, the well-known dipole ghost of standard QED in a covariant gauge. In order to correctly dispose of this contribution, we implement a generalised Lautrup trick. Furthermore, causality and the relation of the model with the Wightman axioms are also discussed.
Nonlinear relativistic plasma resonance: Renormalization group approach
Energy Technology Data Exchange (ETDEWEB)
Metelskii, I. I., E-mail: metelski@lebedev.ru [Russian Academy of Sciences, Lebedev Physical Institute (Russian Federation); Kovalev, V. F., E-mail: vfkvvfkv@gmail.com [Dukhov All-Russian Research Institute of Automatics (Russian Federation); Bychenkov, V. Yu., E-mail: bychenk@lebedev.ru [Russian Academy of Sciences, Lebedev Physical Institute (Russian Federation)
2017-02-15
An analytical solution to the nonlinear set of equations describing the electron dynamics and electric field structure in the vicinity of the critical density in a nonuniform plasma is constructed using the renormalization group approach with allowance for relativistic effects of electron motion. It is demonstrated that the obtained solution describes two regimes of plasma oscillations in the vicinity of the plasma resonance— stationary and nonstationary. For the stationary regime, the spatiotemporal and spectral characteristics of the resonantly enhanced electric field are investigated in detail and the effect of the relativistic nonlinearity on the spatial localization of the energy of the plasma relativistic field is considered. The applicability limits of the obtained solution, which are determined by the conditions of plasma wave breaking in the vicinity of the resonance, are established and analyzed in detail for typical laser and plasma parameters. The applicability limits of the earlier developed nonrelativistic theories are refined.
Theory of relativistic radiation reflection from plasmas
Gonoskov, Arkady
2018-01-01
We consider the reflection of relativistically strong radiation from plasma and identify the physical origin of the electrons' tendency to form a thin sheet, which maintains its localisation throughout its motion. Thereby, we justify the principle of relativistic electronic spring (RES) proposed in [Gonoskov et al., Phys. Rev. E 84, 046403 (2011)]. Using the RES principle, we derive a closed set of differential equations that describe the reflection of radiation with arbitrary variation of polarization and intensity from plasma with an arbitrary density profile for an arbitrary angle of incidence. We confirm with ab initio PIC simulations that the developed theory accurately describes laser-plasma interactions in the regime where the reflection of relativistically strong radiation is accompanied by significant, repeated relocation of plasma electrons. In particular, the theory can be applied for the studies of plasma heating and coherent and incoherent emissions in the RES regime of high-intensity laser-plasma interaction.
Heat kernel for Newton-Cartan trace anomalies
Energy Technology Data Exchange (ETDEWEB)
Auzzi, Roberto [Dipartimento di Matematica e Fisica, Università Cattolica del Sacro Cuore, Via Musei 41, Brescia, 25121 (Italy); INFN Sezione di Perugia, Via A. Pascoli, Perugia, 06123 (Italy); Nardelli, Giuseppe [Dipartimento di Matematica e Fisica, Università Cattolica del Sacro Cuore, Via Musei 41, Brescia, 25121 (Italy); TIFPA - INFN, Università di Trento,c/o Dipartimento di Fisica, Povo, TN, 38123 (Italy)
2016-07-11
We compute the leading part of the trace anomaly for a free non-relativistic scalar in 2+1 dimensions coupled to a background Newton-Cartan metric. The anomaly is proportional to 1/m, where m is the mass of the scalar. We comment on the implications of a conjectured a-theorem for non-relativistic theories with boost invariance.
General relativistic tidal heating for Moller pseudotensor
So, Lau Loi
2015-01-01
Thorne elucidated that the relativistic tidal heating is the same as the Newtonian theory. Moreover, Thorne also claimed that the tidal heating is independent of how one localizes gravitational energy and is unambiguously given by a certain formula. Purdue and Favata calculated the tidal heating for different classical pseudotensors including Moller and obtained the results all matched with the Newtonian perspective. After re-examined this Moller pseudotensor, we find that there does not exist any tidal heating value. Thus we claim that the relativistic tidal heating is pseudotensor independent under the condition that if the peusdotensor is a Freud typed superpotential.
Relativistic quantum mechanics of a Dirac oscillator
Martines y Romero, R P; Salas-Brito, A L
1995-01-01
The Dirac oscillator is an exactly soluble model recently introduced in the context of many particle models in relativistic quantum mechanics. The model has been also considered as an interaction term for modelling quark confinement in quantum chromodynamics. These considerations should be enough for demonstrating that the Dirac oscillator can be an excellent example in relativistic quantum mechanics. In this paper we offer a solution to the problem and discuss some of its properties. We also discuss a physical picture for the Dirac oscillator's non-standard interaction, showing how it arises on describing the behaviour of a neutral particle carrying an anomalous magnetic moment and moving inside a uniformly charged sphere. (author)
Fermi Acceleration in driven relativistic billiards
Energy Technology Data Exchange (ETDEWEB)
Pinto, Rafael S., E-mail: rsoaresp@ifi.unicamp.br [Instituto de Fisica ' Gleb Wataghin' , Universidade Estadual de Campinas, 13083-970, Campinas, SP (Brazil); Letelier, Patricio S. [Departamento de Matematica Aplicada, Instituto de Matematica, Estatistica e Computacao Cientifica, Universidade Estadual de Campinas, 13083-859, Campinas, SP (Brazil)
2011-08-29
We show numerical experiments of driven billiards using special relativity. We have the remarkable fact that for the relativistic driven circular and annular concentric billiards, depending on initial conditions and parameters, we observe Fermi Acceleration, absent in the Newtonian case. The velocity for these cases tends to the speed of light very quickly. We find that for the annular eccentric billiard the initial velocity grows for a much longer time than the concentric annular billiard until it asymptotically reach c. -- Highlights: → Fermi Acceleration is studied for relativistic driven billiards. → We studied regular and chaotic billiards with different parameters. → Fermi Acceleration is present even for static regular billiards.
Level density parameter in relativistic models
Energy Technology Data Exchange (ETDEWEB)
Centelles, M. (Dept. d' Estructura i Constituents de la Materia, Facultat de Fisica, Univ. de Barcelona (Spain)); Vinas, X. (Dept. d' Estructura i Constituents de la Materia, Facultat de Fisica, Univ. de Barcelona (Spain)); Schuck, P. (Inst. des Sciences Nucleaires, 38 Grenoble (France))
1994-01-24
The level density parameter for finite nuclei is studied in the framework of the relativistic mean field theory. Systematic self-consistent calculations are performed in the Thomas-Fermi approximation using [sigma]-[omega] models that include scalar meson self-couplings. For realistic nuclear matter properties, the level density parameter turns out to be in the range of values obtained in non-relativistic calculations with Skyrme interactions, and thus it is smaller than the global trend of the experimental data. The implications for the level density parameter of including vacuum fluctuations and exchange corrections in the mean field theory are also investigated. (orig.)
Relativistic Celestial Mechanics of the Solar System
Kopeikin, Sergei; Kaplan, George
2011-01-01
This authoritative book presents the theoretical development of gravitational physics as it applies to the dynamics of celestial bodies and the analysis of precise astronomical observations. In so doing, it fills the need for a textbook that teaches modern dynamical astronomy with a strong emphasis on the relativistic aspects of the subject produced by the curved geometry of four-dimensional spacetime. The first three chapters review the fundamental principles of celestial mechanics and of special and general relativity. This background material forms the basis for understanding relativistic r
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 ...
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.
KernelADASYN: Kernel Based Adaptive Synthetic Data Generation for Imbalanced Learning
2015-08-17
In Section III, we test the proposed adaptive over-sampling method incorporated into naive Bayes and decision tree classifiers on various real- life...hence the new data set is fully balanced. We further use naive Bayes classifier as base classifier to evaluate performance in Fig. 3. Both Fig. 2 and...fic at io n er ro r ra te s SMOTE ADASYN KernelADASYN Fig. 3: The performance comparison for different coefficients β using naive Bayes as base
Labeled Graph Kernel for Behavior Analysis.
Zhao, Ruiqi; Martinez, Aleix M
2016-08-01
Automatic behavior analysis from video is a major topic in many areas of research, including computer vision, multimedia, robotics, biology, cognitive science, social psychology, psychiatry, and linguistics. Two major problems are of interest when analyzing behavior. First, we wish to automatically categorize observed behaviors into a discrete set of classes (i.e., classification). For example, to determine word production from video sequences in sign language. Second, we wish to understand the relevance of each behavioral feature in achieving this classification (i.e., decoding). For instance, to know which behavior variables are used to discriminate between the words apple and onion in American Sign Language (ASL). The present paper proposes to model behavior using a labeled graph, where the nodes define behavioral features and the edges are labels specifying their order (e.g., before, overlaps, start). In this approach, classification reduces to a simple labeled graph matching. Unfortunately, the complexity of labeled graph matching grows exponentially with the number of categories we wish to represent. Here, we derive a graph kernel to quickly and accurately compute this graph similarity. This approach is very general and can be plugged into any kernel-based classifier. Specifically, we derive a Labeled Graph Support Vector Machine (LGSVM) and a Labeled Graph Logistic Regressor (LGLR) that can be readily employed to discriminate between many actions (e.g., sign language concepts). The derived approach can be readily used for decoding too, yielding invaluable information for the understanding of a problem (e.g., to know how to teach a sign language). The derived algorithms allow us to achieve higher accuracy results than those of state-of-the-art algorithms in a fraction of the time. We show experimental results on a variety of problems and datasets, including multimodal data.
Probability-confidence-kernel-based localized multiple kernel learning with lp norm.
Han, Yina; Liu, Guizhong
2012-06-01
Localized multiple kernel learning (LMKL) is an attractive strategy for combining multiple heterogeneous features in terms of their discriminative power for each individual sample. However, models excessively fitting to a specific sample would obstacle the extension to unseen data, while a more general form is often insufficient for diverse locality characterization. Hence, both learning sample-specific local models for each training datum and extending the learned models to unseen test data should be equally addressed in designing LMKL algorithm. In this paper, for an integrative solution, we propose a probability confidence kernel (PCK), which measures per-sample similarity with respect to probabilistic-prediction-based class attribute: The class attribute similarity complements the spatial-similarity-based base kernels for more reasonable locality characterization, and the predefined form of involved class probability density function facilitates the extension to the whole input space and ensures its statistical meaning. Incorporating PCK into support-vectormachine-based LMKL framework, we propose a new PCK-LMKL with arbitrary l(p)-norm constraint implied in the definition of PCKs, where both the parameters in PCK and the final classifier can be efficiently optimized in a joint manner. Evaluations of PCK-LMKL on both benchmark machine learning data sets (ten University of California Irvine (UCI) data sets) and challenging computer vision data sets (15-scene data set and Caltech-101 data set) have shown to achieve state-of-the-art performances.
Celluclast 1.5L pretreatment enhanced aroma of palm kernels and oil after kernel roasting.
Zhang, Wencan; Zhao, Fangju; Yang, Tiankui; Zhao, Feifei; Liu, Shaoquan
2017-04-23
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.
Is a Relativistic Thermodynamics possible?; Es posible una Termodinamica Relativista?
Energy Technology Data Exchange (ETDEWEB)
Guemez, J.
2010-07-01
A brief historical review the literature on developing the concept of Thermodynamics Relativistic. We analyze two examples of application of the Galilean and Relativistic Thermodynamics discussed under what circumstances could build a relativistic Thermodynamics Lorentz covariant with physical sense. (Author) 19 refs.
Quantum ion-acoustic solitary waves in weak relativistic plasma
Indian Academy of Sciences (India)
A linear dispersion relation is also obtained taking into account the relativistic effect. The properties of quantum ion-acoustic solitary waves, obtained from the deformed KdV equation, are studied taking into account the quantum mechanical effects in the weak relativistic limit. It is found that relativistic effects signiﬁcantly ...
On the Raman instability in degenerate relativistic plasmas
Chanturia, G. T.; Berezhiani, V. I.; Mahajan, S. M.
2017-07-01
The stimulated Raman scattering instability in a fully degenerate electron plasma is studied applying relativistic hydrodynamic and Maxwell equations. We demonstrated that the instability develops for weakly and strongly relativistic degenerate plasmas. It is shown that in the field of strong radiation, a degenerate relativistic plasma effectively responses as in the case of weak degeneracy.
Application of an inverse kernel concept to Monte Carlo based IMRT.
Bogner, Ludwig; Hartmann, Matthias; Rickhey, Mark; Moravek, Zdenek
2006-12-01
Inverse treatment planning by means of pencil beam algorithms can lead to errors in the calculation of dose in areas without secondary electron equilibrium. Monte Carlo (MC) simulations give accurate results in such areas but result in increased computation times. We present a new, so-called inverse kernel concept that offers MC precision in inverse treatment planning with acceptable computation times and memory consumption. Inverse kernels are matrices that describe the dose contribution from all bixels of a beam to a distinct voxel of the patient phantom. The concept is similar to other generalized pencil-beam concepts, except that inverse kernel elements are precalculated using a single MC simulation and stored as binary trees. In this procedure a modified MC code (XVMC) is applied to trace the photon history for each dose deposition. Iterative optimization is then applied in a second step. The inverse process is separated into (i) a slower MC simulation and (ii) a faster iterative optimization, followed by (iii) the segmentation procedure, and (iv) a final MC dose calculation step including a segment weight reoptimization. Inverse kernel optimization, or IKO, with segmentation and reoptimization steps is demonstrated by means of a lung cancer case. To demonstrate the superiority of an inverse MC system over pencil-beam or collapsed-cone based systems, the final result of the IKO is compared to plans where all segments have been calculated by pencil beam or collapsed cone, respectively. Dose-volume histograms and dose-difference histograms show remarkable differences, which can be attributed to systematic errors in both algorithms. IKO is a precise, nonhybrid, inverse MC treatment planning system which suits current clinical needs, as several optimization steps can follow one single MC-simulation step for a distinct beam setup.
Enhanced Data Representation by Kernel Metric Learning for Dementia Diagnosis.
Cárdenas-Peña, David; Collazos-Huertas, Diego; Castellanos-Dominguez, German
2017-01-01
Alzheimer's disease (AD) is the kind of dementia that affects the most people around the world. Therefore, an early identification supporting effective treatments is required to increase the life quality of a wide number of patients. Recently, computer-aided diagnosis tools for dementia using Magnetic Resonance Imaging scans have been successfully proposed to discriminate between patients with AD, mild cognitive impairment, and healthy controls. Most of the attention has been given to the clinical data, provided by initiatives as the ADNI, supporting reliable researches on intervention, prevention, and treatments of AD. Therefore, there is a need for improving the performance of classification machines. In this paper, we propose a kernel framework for learning metrics that enhances conventional machines and supports the diagnosis of dementia. Our framework aims at building discriminative spaces through the maximization of center kernel alignment function, aiming at improving the discrimination of the three considered neurological classes. The proposed metric learning performance is evaluated on the widely-known ADNI database using three supervised classification machines ( k -nn, SVM and NNs) for multi-class and bi-class scenarios from structural MRIs. Specifically, from ADNI collection 286 AD patients, 379 MCI patients and 231 healthy controls are used for development and validation of our proposed metric learning framework. For the experimental validation, we split the data into two subsets: 30% of subjects used like a blindfolded assessment and 70% employed for parameter tuning. Then, in the preprocessing stage, each structural MRI scan a total of 310 morphological measurements are automatically extracted from by FreeSurfer software package and concatenated to build an input feature matrix. Obtained test performance results, show that including a supervised metric learning improves the compared baseline classifiers in both scenarios. In the multi-class scenario
Enhanced Data Representation by Kernel Metric Learning for Dementia Diagnosis
Directory of Open Access Journals (Sweden)
David Cárdenas-Peña
2017-07-01
Full Text Available Alzheimer's disease (AD is the kind of dementia that affects the most people around the world. Therefore, an early identification supporting effective treatments is required to increase the life quality of a wide number of patients. Recently, computer-aided diagnosis tools for dementia using Magnetic Resonance Imaging scans have been successfully proposed to discriminate between patients with AD, mild cognitive impairment, and healthy controls. Most of the attention has been given to the clinical data, provided by initiatives as the ADNI, supporting reliable researches on intervention, prevention, and treatments of AD. Therefore, there is a need for improving the performance of classification machines. In this paper, we propose a kernel framework for learning metrics that enhances conventional machines and supports the diagnosis of dementia. Our framework aims at building discriminative spaces through the maximization of center kernel alignment function, aiming at improving the discrimination of the three considered neurological classes. The proposed metric learning performance is evaluated on the widely-known ADNI database using three supervised classification machines (k-nn, SVM and NNs for multi-class and bi-class scenarios from structural MRIs. Specifically, from ADNI collection 286 AD patients, 379 MCI patients and 231 healthy controls are used for development and validation of our proposed metric learning framework. For the experimental validation, we split the data into two subsets: 30% of subjects used like a blindfolded assessment and 70% employed for parameter tuning. Then, in the preprocessing stage, each structural MRI scan a total of 310 morphological measurements are automatically extracted from by FreeSurfer software package and concatenated to build an input feature matrix. Obtained test performance results, show that including a supervised metric learning improves the compared baseline classifiers in both scenarios. In the multi
Gauge invariance and Compton scattering from relativistic composite systems
Energy Technology Data Exchange (ETDEWEB)
Ito, H. [George Washington Univ., Washington, DC (United States). Center for Nuclear Studies; Gross, F. [Continuous Electron Beam Accelerator Facility, Newport News, VA (United States)]|[College of William and Mary, Williamsburg, VA (United States). Dept. of Physics
1993-09-01
Using the Ward-Takahashi (W-T) identity and the Bethe-Salpeter (B-S) wave equation, we investigate the dynamical requirements imposed by electromagnetic gauge invariance on Compton scattering from relativistic composite system. The importance of off-shell rescattering in intermediate states, which is equivalent to final state interactions in inclusive processes, is clarified in the context of current conservation. It is shown that, if the nuclear force is nonlocal, there will be both two-photon interaction currents and rescattering contributions to terms involving one-photon interaction currents. We derive the two-body W-T identity for the two-photon interaction currents, and obtain explicit forms for the interaction current operators for three illustrative models of nuclear forces: (a) two-pion exchange forces with baryon resonances, (b) covariant separable forces, and (c) charged one-pion exchange.
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.
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.
Dropping macadamia nuts-in-shell reduces kernel roasting quality.
Walton, David A; Wallace, Helen M
2010-10-01
Macadamia nuts ('nuts-in-shell') are subjected to many impacts from dropping during postharvest handling, resulting in damage to the raw kernel. The effect of dropping on roasted kernel quality is unknown. Macadamia nuts-in-shell were dropped in various combinations of moisture content, number of drops and receiving surface in three experiments. After dropping, samples from each treatment and undropped controls were dry oven-roasted for 20 min at 130 °C, and kernels were assessed for colour, mottled colour and surface damage. Dropping nuts-in-shell onto a bed of nuts-in-shell at 3% moisture content or 20% moisture content increased the percentage of dark roasted kernels. Kernels from nuts dropped first at 20%, then 10% moisture content, onto a metal plate had increased mottled colour. Dropping nuts-in-shell at 3% moisture content onto nuts-in-shell significantly increased surface damage. Similarly, surface damage increased for kernels dropped onto a metal plate at 20%, then at 10% moisture content. Postharvest dropping of macadamia nuts-in-shell causes concealed cellular damage to kernels, the effects not evident until roasting. This damage provides the reagents needed for non-enzymatic browning reactions. Improvements in handling, such as reducing the number of drops and improving handling equipment, will reduce cellular damage and after-roast darkening. Copyright © 2010 Society of Chemical Industry.
Effects of sample size on KERNEL home range estimates
Seaman, D.E.; Millspaugh, J.J.; Kernohan, Brian J.; Brundige, Gary C.; Raedeke, Kenneth J.; Gitzen, Robert A.
1999-01-01
Kernel methods for estimating home range are being used increasingly in wildlife research, but the effect of sample size on their accuracy is not known. We used computer simulations of 10-200 points/home range and compared accuracy of home range estimates produced by fixed and adaptive kernels with the reference (REF) and least-squares cross-validation (LSCV) methods for determining the amount of smoothing. Simulated home ranges varied from simple to complex shapes created by mixing bivariate normal distributions. We used the size of the 95% home range area and the relative mean squared error of the surface fit to assess the accuracy of the kernel home range estimates. For both measures, the bias and variance approached an asymptote at about 50 observations/home range. The fixed kernel with smoothing selected by LSCV provided the least-biased estimates of the 95% home range area. All kernel methods produced similar surface fit for most simulations, but the fixed kernel with LSCV had the lowest frequency and magnitude of very poor estimates. We reviewed 101 papers published in The Journal of Wildlife Management (JWM) between 1980 and 1997 that estimated animal home ranges. A minority of these papers used nonparametric utilization distribution (UD) estimators, and most did not adequately report sample sizes. We recommend that home range studies using kernel estimates use LSCV to determine the amount of smoothing, obtain a minimum of 30 observations per animal (but preferably a?Y50), and report sample sizes in published results.
A relativistic mean-ﬁeld study of magic numbers in light nuclei from ...
Indian Academy of Sciences (India)
In an axially deformed relativistic mean-ﬁeld calculation of single-particle energy spectra of = 8 (Li–Mg) and = 14, 16 (C–Mg) isotonic chain and the one- and two-neutron separation energies of various isotopes of Li–Mg, new magic numbers are found to exist at = 6 and = 16 and/or = 14, which are in addition to the ...
Ultra-low-frequency wave-driven diffusion of radiation belt relativistic electrons
Su, Zhenpeng; Zhu, Hui; Xiao, Fuliang; Zong, Q.-G.; Zhou, X.-Z.; Zheng, Huinan; Wang, Yuming; Wang, Shui; Hao, Y.-X.; Gao, Zhonglei; He, Zhaoguo; Baker, D. N.; Spence, H. E.; Reeves, G. D.; Blake, J. B.
2015-01-01
Van Allen radiation belts are typically two zones of energetic particles encircling the Earth separated by the slot region. How the outer radiation belt electrons are accelerated to relativistic energies remains an unanswered question. Recent studies have presented compelling evidence for the local acceleration by very-low-frequency (VLF) chorus waves. However, there has been a competing theory to the local acceleration, radial diffusion by ultra-low-frequency (ULF) waves, whose importance ha...
The N body problem. Relativistic approach; Le probleme a N corps. Approches relativistes
Energy Technology Data Exchange (ETDEWEB)
Mathiot, Jean-Francois [Laboratoire de Physique Corpusculaire, IN2P3/CNRS, Universite Blaise Pascal, F-63177 Aubiere Cedex (France); Collaboration: La Direction des Sciences de la Matiere du CEA (FR); Le Fonds National de la Recherche Scientifique de Belgique (BE)
1998-12-31
We shall detail in a first part the physical motivation of relativistic approaches by investigating the underlying elementary mechanisms. The second part will be devoted to the understanding of nuclear matter and finite nuclei in these approaches. We shall see, in particular, how one can easily derive an effective interaction of Skyrme type from these relativistic approaches. We shall discuss, in the third part, some recent results obtained in nuclear structure. (author) 20 refs., 8 figs., 2 tabs.
Workshop on gravitational waves and relativistic astrophysics
Indian Academy of Sciences (India)
Discussions related to gravitational wave experiments viz. LIGO and LISA as well as to observations of supermassive black holes dominated the workshop sessions on gravitational waves and relativistic astrophysics in the ICGC-2004. A summary of seven papers that were presented in these workshop sessions has been ...
Deriving relativistic Bohmian quantum potential using variational ...
Indian Academy of Sciences (India)
Deriving relativistic Bohmian quantum potential using variational method and conformal transformations ... We obtain this potential by using variational method. Then ... Department of Physics, Ferdowsi University of Mashhad, Azadi Sq., Mashhad, Iran; School of Physics, Institute for Research in Fundamental Science (IPM), ...
Photon and gluon emission in relativistic plasmas
Arnold, Peter; Moore, Guy D.; Yaffe, Laurence G.
2002-06-01
We recently derived, using diagrammatic methods, the leading-order hard photon emission rate in ultra-relativistic plasmas. This requires a correct treatment of multiple scattering effects which limit the coherence length of emitted radiation (the Landau-Pomeranchuk-Migdal effect). In this paper, we provide a more physical derivation of this result, and extend the treatment to the case of gluon radiation.
Relativistic atomic physics at the SSC
Energy Technology Data Exchange (ETDEWEB)
NONE
1990-12-31
This report discusses the following proposed work for relativistic atomic physics at the Superconducting Super Collider: Beam diagnostics; atomic physics research; staffing; education; budget information; statement concerning matching funds; description and justification of major items of equipment; statement of current and pending support; and assurance of compliance.
Deriving relativistic Bohmian quantum potential using variational ...
Indian Academy of Sciences (India)
ever, this postulate (locality) breaks down and opens new windows for understanding our. Universe. 2.2 Relativistic quantum potential for a spinless particle. Following Bohm, we substitute the polar form of the wave function into the Klein–Gordon equation to derive the quantum mechanical Hamilton–Jacobi equation for a ...
Instabilities in a Relativistic Viscous Fluid
Corona-Galindo, M. G.; Klapp, J.; Vazquez, A.
1990-11-01
RESUMEN. Las ecuaciones hidrodinamicas de un fluido imperfecto relativista son resueltas, y los modos hidrodinamicos son analizados con el prop6sito de estabiecer correlaciones con las estructuras cosmol6gicas. ABSTRACT The hydrodynamical equations of a relativistic imperfect fluid are solved, and the hydrodynamical modes are analysed with the aim to establish correlations with cosmological structures. Ke, words: COSMOLOGY - HYDRODYNAMICS - RELATIVITY
Solutions to the relativistic precession model
Ingram, A.; Motta, S.
2014-01-01
The relativistic precession model (RPM) can be used to obtain a precise measurement of the mass and spin of a black hole when the appropriate set of quasi-periodic oscillations is detected in the power-density spectrum of an accreting black hole. However, in previous studies, the solution of the RPM
Kinematical Diagrams for Conical Relativistic Jets
Indian Academy of Sciences (India)
... a variety of radio observations of blazar jets. In addition to uniform jet flows (i.e., those having a uniform bulk Lorentz factor, ), computational results are also presented for stratified jets where an ultra-relativistic central spine along the jet axis is surrounded by a slower moving sheath, possibly arising from a velocity shear.
Relativistic energy loss in a dispersive medium
DEFF Research Database (Denmark)
Houlrik, Jens Madsen
2002-01-01
The electron energy loss in a dispersive medium is obtained using macroscopic electrodynamics taking advantage of a static frame of reference. Relativistic corrections are described in terms of a dispersive Lorentz factor obtained by replacing the vacuum velocity c by the characteristic phase...
Astrophysical Applications of Relativistic Shear Flows
Liang, Edison
2017-10-01
We review recent PIC simulation results of relativistic collisionless shear flows in both 2D and 3D. We apply these results to spine-sheath jet models of blazars and gamma-ray-bursters, and to shear flows near the horizon of rapidly spinning black holes. We will discuss magnetic field generation, particle energization and radiation processes, and their observational consequences.
Relativistic heavy-ion physics: Experimental overview
Indian Academy of Sciences (India)
highlights from the first run of the relativistic heavy-ion collider at BNL and the 15 year research programme at the super ... The energy dependence of the charged particle density dNch/dη, normalized to the num- ..... meson both in the dropping mass and the collision broadening scenarios, is almost as high at RHIC as at ...
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.
Noise kernels of stochastic gravity in conformally-flat spacetimes
Cho, H. T.; Hu, B. L.
2015-03-01
The central object in the theory of semiclassical stochastic gravity is the noise kernel, which is the symmetric two point correlation function of the stress-energy tensor. Using the corresponding Wightman functions in Minkowski, Einstein and open Einstein spaces, we construct the noise kernels of a conformally coupled scalar field in these spacetimes. From them we show that the noise kernels in conformally-flat spacetimes, including the Friedmann-Robertson-Walker universes, can be obtained in closed analytic forms by using a combination of conformal and coordinate transformations.
Deep kernel learning method for SAR image target recognition
Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao
2017-10-01
With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.
Linear and kernel methods for multivariate change detection
DEFF Research Database (Denmark)
Canty, Morton J.; Nielsen, Allan Aasbjerg
2012-01-01
), 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...
Structure and thermodynamic properties of relativistic electron gases.
Liu, Yu; Wu, Jianzhong
2014-07-01
Relativistic effect is important in many quantum systems but theoretically complicated from both fundamental and practical perspectives. Herein we introduce an efficient computational procedure to predict the structure and energetic properties of relativistic quantum systems by mapping the Pauli principle into an effective pairwise-additive potential such that the properties of relativistic nonquantum systems can be readily predicted from conventional liquid-state methods. We applied our theoretical procedure to relativistic uniform electron gases and compared the pair correlation functions with those for systems of nonrelativistic electrons. A simple analytical expression has been developed to correlate the exchange-correlation free energy of relativistic uniform electron systems.
Advanced relativistic VLBI model for geodesy
Soffel, Michael; Kopeikin, Sergei; Han, Wen-Biao
2017-07-01
Our present relativistic part of the geodetic VLBI model for Earthbound antennas is a consensus model which is considered as a standard for processing high-precision VLBI observations. It was created as a compromise between a variety of relativistic VLBI models proposed by different authors as documented in the IERS Conventions 2010. The accuracy of the consensus model is in the picosecond range for the group delay but this is not sufficient for current geodetic purposes. This paper provides a fully documented derivation of a new relativistic model having an accuracy substantially higher than one picosecond and based upon a well accepted formalism of relativistic celestial mechanics, astrometry and geodesy. Our new model fully confirms the consensus model at the picosecond level and in several respects goes to a great extent beyond it. More specifically, terms related to the acceleration of the geocenter are considered and kept in the model, the gravitational time-delay due to a massive body (planet, Sun, etc.) with arbitrary mass and spin-multipole moments is derived taking into account the motion of the body, and a new formalism for the time-delay problem of radio sources located at finite distance from VLBI stations is presented. Thus, the paper presents a substantially elaborated theoretical justification of the consensus model and its significant extension that allows researchers to make concrete estimates of the magnitude of residual terms of this model for any conceivable configuration of the source of light, massive bodies, and VLBI stations. The largest terms in the relativistic time delay which can affect the current VLBI observations are from the quadrupole and the angular momentum of the gravitating bodies that are known from the literature. These terms should be included in the new geodetic VLBI model for improving its consistency.
Leading order relativistic chiral nucleon-nucleon interaction
Ren, Xiu-Lei; Li, Kai-Wen; Geng, Li-Sheng; Long, Bingwei; Ring, Peter; Meng, Jie
2018-01-01
Motivated by the successes of relativistic theories in studies of atomic/molecular and nuclear systems and the need for a relativistic chiral force in relativistic nuclear structure studies, we explore a new relativistic scheme to construct the nucleon-nucleon interaction in the framework of covariant chiral effective field theory. The chiral interaction is formulated up to leading order with covariant power counting and a Lorentz invariant chiral Lagrangian. We find that the relativistic scheme induces all six spin operators needed to describe the nuclear force. A detailed investigation of the partial wave potentials shows a better description of the {}1S0 and {}3P0 phase shifts than the leading order Weinberg approach, and similar to that of the next-to-leading order Weinberg approach. For the other partial waves with angular momenta J≥slant 1, the relativistic results are almost the same as their leading order non-relativistic counterparts. )
Skarstrom, C.
1959-03-10
A centrifugal separator is described for separating gaseous mixtures where the temperature gradients both longitudinally and radially of the centrifuge may be controlled effectively to produce a maximum separation of the process gases flowing through. Tbe invention provides for the balancing of increases and decreases in temperature in various zones of the centrifuge chamber as the result of compression and expansions respectively, of process gases and may be employed effectively both to neutralize harmful temperature gradients and to utilize beneficial temperaturc gradients within the centrifuge.
Bylesjö, Max; Rantalainen, Mattias; Nicholson, Jeremy K; Holmes, Elaine; Trygg, Johan
2008-02-19
Kernel-based classification and regression methods have been successfully applied to modelling a wide variety of biological data. The Kernel-based Orthogonal Projections to Latent Structures (K-OPLS) method offers unique properties facilitating separate modelling of predictive variation and structured noise in the feature space. While providing prediction results similar to other kernel-based methods, K-OPLS features enhanced interpretational capabilities; allowing detection of unanticipated systematic variation in the data such as instrumental drift, batch variability or unexpected biological variation. We demonstrate an implementation of the K-OPLS algorithm for MATLAB and R, licensed under the GNU GPL and available at http://www.sourceforge.net/projects/kopls/. The package includes essential functionality and documentation for model evaluation (using cross-validation), training and prediction of future samples. Incorporated is also a set of diagnostic tools and plot functions to simplify the visualisation of data, e.g. for detecting trends or for identification of outlying samples. The utility of the software package is demonstrated by means of a metabolic profiling data set from a biological study of hybrid aspen. The properties of the K-OPLS method are well suited for analysis of biological data, which in conjunction with the availability of the outlined open-source package provides a comprehensive solution for kernel-based analysis in bioinformatics applications.
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, ...
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...... 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...
Intelligent classification methods of grain kernels using computer vision analysis
Lee, Choon Young; Yan, Lei; Wang, Tianfeng; Lee, Sang Ryong; Park, Cheol Woo
2011-06-01
In this paper, a digital image analysis method was developed to classify seven kinds of individual grain kernels (common rice, glutinous rice, rough rice, brown rice, buckwheat, common barley and glutinous barley) widely planted in Korea. A total of 2800 color images of individual grain kernels were acquired as a data set. Seven color and ten morphological features were extracted and processed by linear discriminant analysis to improve the efficiency of the identification process. The output features from linear discriminant analysis were used as input to the four-layer back-propagation network to classify different grain kernel varieties. The data set was divided into three groups: 70% for training, 20% for validation, and 10% for testing the network. The classification experimental results show that the proposed method is able to classify the grain kernel varieties efficiently.
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 eigenvalue-decomposition methods for analysing ham
DEFF Research Database (Denmark)
Christiansen, Asger Nyman; Nielsen, Allan Aasbjerg; Møller, Flemming
2010-01-01
methods, such as PCA, MAF or MNF. We therefore investigated the applicability of kernel based versions of these transformation. This meant implementing the kernel based methods and developing new theory, since kernel based MAF and MNF is not described in the literature yet. The traditional methods only...... have two factors that are useful for segmentation and none of them can be used to segment the two types of meat. The kernel based methods have a lot of useful factors and they are able to capture the subtle differences in the images. This is illustrated in Figure 1. You can see a comparison of the most...... conditions and finding useful additives to hinder the color to change rapidly. To be able to prove which methods of storing and additives work, Danisco wants to monitor the development of the color of meat in a slice of ham as a function of time, environment and ingredients. We have chosen to use multi...
A kernel adaptive algorithm for quaternion-valued inputs.
Paul, Thomas K; Ogunfunmi, Tokunbo
2015-10-01
The use of quaternion data can provide benefit in applications like robotics and image recognition, and particularly for performing transforms in 3-D space. Here, we describe a kernel adaptive algorithm for quaternions. A least mean square (LMS)-based method was used, resulting in the derivation of the quaternion kernel LMS (Quat-KLMS) algorithm. Deriving this algorithm required describing the idea of a quaternion reproducing kernel Hilbert space (RKHS), as well as kernel functions suitable with quaternions. A modified HR calculus for Hilbert spaces was used to find the gradient of cost functions defined on a quaternion RKHS. In addition, the use of widely linear (or augmented) filtering is proposed to improve performance. The benefit of the Quat-KLMS and widely linear forms in learning nonlinear transformations of quaternion data are illustrated with simulations.
On the asymptotic expansion of the Bergman kernel
Seto, Shoo
Let (L, h) → (M, o) be a polarized Kahler manifold. We define the Bergman kernel for H0(M, Lk), holomorphic sections of the high tensor powers of the line bundle L. In this thesis, we will study the asymptotic expansion of the Bergman kernel. We will consider the on-diagonal, near-diagonal and far off-diagonal, using L2 estimates to show the existence of the asymptotic expansion and computation of the coefficients for the on and near-diagonal case, and a heat kernel approach to show the exponential decay of the off-diagonal of the Bergman kernel for noncompact manifolds assuming only a lower bound on Ricci curvature and C2 regularity of the metric.
Automated skin lesion segmentation with kernel density estimation
Pardo, A.; Real, E.; Fernandez-Barreras, G.; Madruga, F. J.; López-Higuera, J. M.; Conde, O. M.
2017-07-01
Skin lesion segmentation is a complex step for dermoscopy pathological diagnosis. Kernel density estimation is proposed as a segmentation technique based on the statistic distribution of color intensities in the lesion and non-lesion regions.
Screening of the kernels of Pentadesma butyracea from various ...
African Journals Online (AJOL)
Gwla10
). Recent works on the biological activities of P. butyracea showed that the xanthone isolated from their roots and stem bark present some antiproliferative ... Basically, the butter extraction from the P. butyracea kernel involves the seeds boiling, ...
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...
Explicit signal to noise ratio in reproducing kernel Hilbert spaces
DEFF Research Database (Denmark)
Gomez-Chova, Luis; Nielsen, Allan Aasbjerg; Camps-Valls, Gustavo
2011-01-01
an alternative kernel MNF (KMNF) in which the noise is explicitly estimated in the reproducing kernel Hilbert space. This enables KMNF dealing with non-linear relations between the noise and the signal features jointly. Results show that the proposed KMNF provides the most noise-free features when confronted...... with PCA, MNF, KPCA, and the previous version of KMNF. Extracted features with the explicit KMNF also improve hyperspectral image classification....
Sparse Event Modeling with Hierarchical Bayesian Kernel Methods
2016-01-05
data, is it equally important to analyze the prediction power of a statistical model if it is going to be used for forecasting purposes. Prediction...Poisson Bayesian Kernel Methods for Modeling Count Data, Computational Statistics and Data Analysis (04 2016) TOTAL: 1 Books Number of Manuscripts...factors into the assessment of a rehabilitation project. Conclusions Bayesian kernel methods are powerful tools in forecasting data. These models make
Optimizing kernel methods for Poisson integrals on a uniform grid
Gabay, D.; Boag, A.; Natan, A.
2017-06-01
We analyze the error and error propagation in the calculation of the Poisson integral on a uniform grid within Density Functional Theory (DFT) real-space calculations. We suggest and examine several schemes for near neighbors' interaction correction for the Green's function kernel to improve the accuracy. Finally, we demonstrate the effect of the different kernels on DFT eigenvalues and Hartree energy accuracy in systems such as C60 and C40H82.
The Weighted Super Bergman Kernels Over the Supermatrix Spaces
Feng, Zhiming
2015-12-01
The purpose of this paper is threefold. Firstly, using Howe duality for , we obtain integral formulas of the super Schur functions with respect to the super standard Gaussian distributions. Secondly, we give explicit expressions of the super Szegö kernels and the weighted super Bergman kernels for the Cartan superdomains of type I. Thirdly, combining these results, we obtain duality relations of integrals over the unitary groups and the Cartan superdomains, and the marginal distributions of the weighted measure.
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.
Resummed memory kernels in generalized system-bath master equations
Energy Technology Data Exchange (ETDEWEB)
Mavros, Michael G.; Van Voorhis, Troy, E-mail: tvan@mit.edu [Department of Chemistry, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, Massachusetts 02139 (United States)
2014-08-07
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.
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....
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.
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.
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.
Characterization of Flour from Avocado Seed Kernel
Directory of Open Access Journals (Sweden)
Macey A. Mahawan
2015-11-01
Full Text Available The study focused on the Characterization of Flour from Avocado Seed Kernel. Based on the findings of the study the percentages of crude protein, crude fiber, crude fat, total carbohydrates, ash and moisture were 7.75, 4.91, 0.71, 74.65, 2.83 and 14.05 respectively. On the other hand the falling number was 495 seconds while gluten was below the detection limit of the method used. Moreover, the sensory evaluation in terms of color, texture and aroma in 0% proportion of Avocado seed flour was moderate like and slight like for 25% and 50% proportions of Avocado seed flour. On the otherhand, the taste of the biscuits prepared with 0% Avocado seed flour was moderate like, in 25% proportion of Avocado seed flour were slight like and in 50% proportion was neither liked nor disliked. The overall acceptability results for 0% proportion of Avocado seed flour was moderate like and slight like for 25% and 50% proportions of Avocado seed flour. Furthermore, the computed p values for the comparison of the level of acceptability in terms of color, texture, aroma, taste and overall acceptability of biscuits using 0%, 25%, and 50% avocado seed flour were lower than 0.05. Thus the null hypothesis is rejected.
Salus: Kernel Support for Secure Process Compartments
Directory of Open Access Journals (Sweden)
Raoul Strackx
2015-01-01
Full Text Available Consumer devices are increasingly being used to perform security and privacy critical tasks. The software used to perform these tasks is often vulnerable to attacks, due to bugs in the application itself or in included software libraries. Recent work proposes the isolation of security-sensitive parts of applications into protected modules, each of which can be accessed only through a predefined public interface. But most parts of an application can be considered security-sensitive at some level, and an attacker who is able to gain inapplication level access may be able to abuse services from protected modules. We propose Salus, a Linux kernel modification that provides a novel approach for partitioning processes into isolated compartments sharing the same address space. Salus significantly reduces the impact of insecure interfaces and vulnerable compartments by enabling compartments (1 to restrict the system calls they are allowed to perform, (2 to authenticate their callers and callees and (3 to enforce that they can only be accessed via unforgeable references. We describe the design of Salus, report on a prototype implementation and evaluate it in terms of security and performance. We show that Salus provides a significant security improvement with a low performance overhead, without relying on any non-standard hardware support.
DEFF Research Database (Denmark)
Arenas-Garcia, J.; Petersen, K.; Camps-Valls, G.
2013-01-01
correlation analysis (CCA), and orthonormalized PLS (OPLS), as well as their nonlinear extensions derived by means of the theory of reproducing kernel Hilbert spaces (RKHSs). We also review their connections to other methods for classification and statistical dependence estimation and introduce some recent...... developments to deal with the extreme cases of large-scale and low-sized problems. To illustrate the wide applicability of these methods in both classification and regression problems, we analyze their performance in a benchmark of publicly available data sets and pay special attention to specific real...
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......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 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 including lags of the dependent variable or other individual variables as predictors, as typically desired...... in macroeconomic and financial applications. Monte Carlo simulations as well as an empirical application to various key measures of real economic activity confirm that kernel ridge regression can produce more accurate forecasts than traditional linear and nonlinear methods for dealing with many predictors based...
Kernels by Monochromatic Paths and Color-Perfect Digraphs
Directory of Open Access Journals (Sweden)
Galeana-Śanchez Hortensia
2016-05-01
Full Text Available For a digraph D, V (D and A(D will denote the sets of vertices and arcs of D respectively. In an arc-colored digraph, a subset K of V(D is said to be kernel by monochromatic paths (mp-kernel if (1 for any two different vertices x, y in N there is no monochromatic directed path between them (N is mp-independent and (2 for each vertex u in V (D \\ N there exists v ∈ N such that there is a monochromatic directed path from u to v in D (N is mp-absorbent. If every arc in D has a different color, then a kernel by monochromatic paths is said to be a kernel. Two associated digraphs to an arc-colored digraph are the closure and the color-class digraph CC(D. In this paper we will approach an mp-kernel via the closure of induced subdigraphs of D which have the property of having few colors in their arcs with respect to D. We will introduce the concept of color-perfect digraph and we are going to prove that if D is an arc-colored digraph such that D is a quasi color-perfect digraph and CC(D is not strong, then D has an mp-kernel. Previous interesting results are generalized, as for example Richardson′s Theorem.
Ruchin, Vyacheslav; Vacaru, Olivia; Vacaru, Sergiu I.
2017-03-01
Using double 2+2 and 3+1 nonholonomic fibrations on Lorentz manifolds, we extend the concept of W-entropy for gravitational fields in general relativity (GR). Such F- and W-functionals were introduced in the Ricci flow theory of three dimensional (3-d) Riemannian metrics by Perelman (the entropy formula for the Ricci flow and its geometric applications. arXiv:math.DG/0211159). Non-relativistic 3-d Ricci flows are characterized by associated statistical thermodynamical values determined by W-entropy. Generalizations for geometric flows of 4-d pseudo-Riemannian metrics are considered for models with local thermodynamical equilibrium and separation of dissipative and non-dissipative processes in relativistic hydrodynamics. The approach is elaborated in the framework of classical field theories (relativistic continuum and hydrodynamic models) without an underlying kinetic description, which will be elaborated in other work. The 3+1 splitting allows us to provide a general relativistic definition of gravitational entropy in the Lyapunov-Perelman sense. It increases monotonically as structure forms in the Universe. We can formulate a thermodynamic description of exact solutions in GR depending, in general, on all spacetime coordinates. A corresponding 2+2 splitting with nonholonomic deformation of linear connection and frame structures is necessary for generating in very general form various classes of exact solutions of the Einstein and general relativistic geometric flow equations. Finally, we speculate on physical macrostates and microstate interpretations of the W-entropy in GR, geometric flow theories and possible connections to string theory (a second unsolved problem also contained in Perelman's work) in Polyakov's approach.
Relativistic-microwave theory of ball lightning
Wu, H.-C.
2016-06-01
Ball lightning, a fireball sometimes observed during lightnings, has remained unexplained. Here we present a comprehensive theory for the phenomenon: At the tip of a lightning stroke reaching the ground, a relativistic electron bunch can be produced, which in turn excites intense microwave radiation. The latter ionizes the local air and the radiation pressure evacuates the resulting plasma, forming a spherical plasma bubble that stably traps the radiation. This mechanism is verified by particle simulations. The many known properties of ball lightning, such as the occurrence site, relation to the lightning channels, appearance in aircraft, its shape, size, sound, spark, spectrum, motion, as well as the resulting injuries and damages, are also explained. Our theory suggests that ball lighting can be created in the laboratory or triggered during thunderstorms. Our results should be useful for lightning protection and aviation safety, as well as stimulate research interest in the relativistic regime of microwave physics.
Relativistic quantum chemistry on quantum computers
DEFF Research Database (Denmark)
Veis, L.; Visnak, J.; Fleig, T.
2012-01-01
The past few years have witnessed a remarkable interest in the application of quantum computing for solving problems in quantum chemistry more efficiently than classical computers allow. Very recently, proof-of-principle experimental realizations have been reported. However, so far only...... the nonrelativistic regime (i.e., the Schrodinger equation) has been explored, while it is well known that relativistic effects can be very important in chemistry. We present a quantum algorithm for relativistic computations of molecular energies. We show how to efficiently solve the eigenproblem of the Dirac......-Coulomb Hamiltonian on a quantum computer and demonstrate the functionality of the proposed procedure by numerical simulations of computations of the spin-orbit splitting in the SbH molecule. Finally, we propose quantum circuits with three qubits and nine or ten controlled-NOT (CNOT) gates, which implement a proof...
Formation of Hypernuclei in Relativistic Ion Collisions
Botvina, Alexander; Bleicher, Marcus; Pochodzalla, Josef; Steinheimer, Jan
We develop a versatile model of hypernuclei production in relativistic hadron and ion collisions. Within a hybrid approach we use transport, coalescence and statistical models to describe the whole process. We demonstrate that heavy hypernuclei are coming mostly from projectile and target residues, whereas light hypernuclei can be produced at all rapidities. The yields of hypernuclei increase considerably above the energy threshold for the hyperon production, and there is a tendency to saturation of yields of hypernuclei with increasing the beam energy. There are unique opportunities in relativistic ion collisions which are difficult to realize in traditional hypernuclear experiments: The produced hypernuclei have a broad distribution in masses and isospin, and the production of multi-strange nuclei including new excited states is quite abundant. In addition, we can directly get an information on the hypermatter both at high and low temperatures.
Hyperbolic Triangle Centers The Special Relativistic Approach
Ungar, A.A
2010-01-01
After A. Ungar had introduced vector algebra and Cartesian coordinates into hyperbolic geometry in his earlier books, along with novel applications in Einstein’s special theory of relativity, the purpose of his new book is to introduce hyperbolic barycentric coordinates, another important concept to embed Euclidean geometry into hyperbolic geometry. It will be demonstrated that, in full analogy to classical mechanics where barycentric coordinates are related to the Newtonian mass, barycentric coordinates are related to the Einsteinian relativistic mass in hyperbolic geometry. Contrary to general belief, Einstein’s relativistic mass hence meshes up extraordinarily well with Minkowski’s four-vector formalism of special relativity. In Euclidean geometry, barycentric coordinates can be used to determine various triangle centers. While there are many known Euclidean triangle centers, only few hyperbolic triangle centers are known, and none of the known hyperbolic triangle centers has been determined analytic...
Newtonian view of general relativistic stars
Energy Technology Data Exchange (ETDEWEB)
Oliveira, A.M. [Instituto Federal do Espirito Santo (IFES), Grupo de Ciencias Ambientais e Recursos Naturais, Guarapari (Brazil); Velten, H.E.S.; Fabris, J.C. [Universidade Federal do Espirito Santo (UFES), Departamento de Fisica, Vitoria (Brazil); Salako, I.G. [Institut de Mathematiques et de Sciences Physiques (IMSP), Porto-Novo (Benin)
2014-11-15
Although general relativistic cosmological solutions, even in the presence of pressure, can be mimicked by using neo-Newtonian hydrodynamics, it is not clear whether there exists the same Newtonian correspondence for spherical static configurations. General relativity solutions for stars are known as the Tolman-Oppenheimer-Volkoff (TOV) equations. On the other hand, the Newtonian description does not take into account the total pressure effects and therefore cannot be used in strong field regimes. We discuss how to incorporate pressure in the stellar equilibrium equations within the neo-Newtonian framework. We compare the Newtonian, neo-Newtonian, and the full relativistic theory by solving the equilibrium equations for both three approaches and calculating the mass-radius diagrams for some simple neutron stars' equations of state. (orig.)
Exact Relativistic Magnetized Haloes around Rotating Disks
Directory of Open Access Journals (Sweden)
Antonio C. Gutiérrez-Piñeres
2015-01-01
Full Text Available The study of the dynamics of magnetic fields in galaxies is one of important problems in formation and evolution of galaxies. In this paper, we present the exact relativistic treatment of a rotating disk surrounded by a magnetized material halo. The features of the halo and disk are described by the distributional energy-momentum tensor of a general fluid in canonical form. All the relevant quantities and the metric and electromagnetic potentials are exactly determined by an arbitrary harmonic function only. For instance, the generalized Kuzmin-disk potential is used. The particular class of solutions obtained is asymptotically flat and satisfies all the energy conditions. Moreover, the motion of a charged particle on the halo is described. As far as we know, this is the first relativistic model describing analytically the magnetized halo of a rotating disk.
Anomalous magnetohydrodynamics in the extreme relativistic domain
Giovannini, Massimo
2016-01-01
The evolution equations of anomalous magnetohydrodynamics are derived in the extreme relativistic regime and contrasted with the treatment of hydromagnetic nonlinearities pioneered by Lichnerowicz in the absence of anomalous currents. In particular we explore the situation where the conventional vector currents are complemented by the axial-vector currents arising either from the pseudo Nambu-Goldstone bosons of a spontaneously broken symmetry or because of finite fermionic density effects. After expanding the generally covariant equations in inverse powers of the conductivity, the relativistic analog of the magnetic diffusivity equation is derived in the presence of vortical and magnetic currents. While the anomalous contributions are generally suppressed by the diffusivity, they are shown to disappear in the perfectly conducting limit. When the flow is irrotational, boost-invariant and with vanishing four-acceleration the corresponding evolution equations are explicitly integrated so that the various physic...
Hydrodynamics of ultra-relativistic bubble walls
Directory of Open Access Journals (Sweden)
Leonardo Leitao
2016-04-01
Full Text Available In cosmological first-order phase transitions, gravitational waves are generated by the collisions of bubble walls and by the bulk motions caused in the fluid. A sizeable signal may result from fast-moving walls. In this work we study the hydrodynamics associated to the fastest propagation modes, namely, ultra-relativistic detonations and runaway solutions. We compute the energy injected by the phase transition into the fluid and the energy which accumulates in the bubble walls. We provide analytic approximations and fits as functions of the net force acting on the wall, which can be readily evaluated for specific models. We also study the back-reaction of hydrodynamics on the wall motion, and we discuss the extrapolation of the friction force away from the ultra-relativistic limit. We use these results to estimate the gravitational wave signal from detonations and runaway walls.
Directory of Open Access Journals (Sweden)
Seyed Hamidreza Ziaolhagh
2017-05-01
Full Text Available Roasting has considerable effects on the quality of cream made of nuts. In this study, the roasting conditions of walnut kernels were optimized based on the stability parameters of the produced cream. Temperatures of 100-150°C for 10-30 minutes were used to roast walnut kernels. The amount of oil separation, peroxide, acidity and Thiobarbituric acid values of the cream, as well as color parameters were determined after three months of storage at 25°C. The results showed that the oil separation increased with temperature and time of roasting (from 4.16% at 100°C/10min to 7.85% at 150°C/30min. Peroxide, acidity and thiobarbituric acid values were significantly affected by temperature and time of roasting. In addition, it was shown that as the temperature increased, the redness and yellowness increased, but the lightness of the samples decreased. Finally, the temperature of 116°C for 12 minutes was chosen as the optimized roasting conditions for producing walnut cream.
DANCING IN THE DARK: NEW BROWN DWARF BINARIES FROM KERNEL PHASE INTERFEROMETRY
Energy Technology Data Exchange (ETDEWEB)
Pope, Benjamin; Tuthill, Peter [Sydney Institute for Astronomy, School of Physics, University of Sydney, NSW 2226 (Australia); Martinache, Frantz, E-mail: bjsp@physics.usyd.edu.au, E-mail: p.tuthill@physics.usyd.edu.au, E-mail: frantz@naoj.org [National Astronomical Observatory of Japan, Subaru Telescope, Hilo, HI 96720 (United States)
2013-04-20
This paper revisits a sample of ultracool dwarfs in the solar neighborhood previously observed with the Hubble Space Telescope's NICMOS NIC1 instrument. We have applied a novel high angular resolution data analysis technique based on the extraction and fitting of kernel phases to archival data. This was found to deliver a dramatic improvement over earlier analysis methods, permitting a search for companions down to projected separations of {approx}1 AU on NIC1 snapshot images. We reveal five new close binary candidates and present revised astrometry on previously known binaries, all of which were recovered with the technique. The new candidate binaries have sufficiently close separation to determine dynamical masses in a short-term observing campaign. We also present four marginal detections of objects which may be very close binaries or high-contrast companions. Including only confident detections within 19 pc, we report a binary fraction of at least #Greek Lunate Epsilon Symbol#{sub b} = 17.2{sub -3.7}{sup +5.7}%. The results reported here provide new insights into the population of nearby ultracool binaries, while also offering an incisive case study of the benefits conferred by the kernel phase approach in the recovery of companions within a few resolution elements of the point-spread function core.
Non-relativistic quantum mechanics
Puri, Ravinder R
2017-01-01
This book develops and simplifies the concept of quantum mechanics based on the postulates of quantum mechanics. The text discusses the technique of disentangling the exponential of a sum of operators, closed under the operation of commutation, as the product of exponentials to simplify calculations of harmonic oscillator and angular momentum. Based on its singularity structure, the Schrödinger equation for various continuous potentials is solved in terms of the hypergeometric or the confluent hypergeometric functions. The forms of the potentials for which the one-dimensional Schrödinger equation is exactly solvable are derived in detail. The problem of identifying the states of two-level systems which have no classical analogy is addressed by going beyond Bell-like inequalities and separability. The measures of quantumness of mutual information in two two-level systems is also covered in detail. Offers a new approach to learning quantum mechanics based on the history of quantum mechanics and its postu...
Transient effects in a relativistic quantum system
Energy Technology Data Exchange (ETDEWEB)
Sadurni, E.; Moshinsky, M. [IFUNAM, Departamento de Fisica Teorica, A.P. 20-364, 01000 Mexico D.F. (Mexico)]. e-mail: sadurni@fisica.unam.mx
2007-12-15
The spectral decomposition of propagators is useful in the study of dynamical problems in the Schroedinger picture. However, relativistic problems exhibit complicated spectra containing positive and negative energies. In this work we write an appropriate spectral decomposition for the propagator of the Dirac oscillator. With such propagator we study the dynamical problem of sudden frequency change related to processes in which the isospin projection of the particle is modified. (Author)
Collective dynamics in relativistic nuclear collisions
Energy Technology Data Exchange (ETDEWEB)
Niemi, Harri [Department of Physics, University of Jyväskylä, P.O. Box 35, FI-40014 University of Jyväskylä (Finland); Helsinki Institute of Physics, P.O. Box 64, FI-00014 University of Helsinki (Finland)
2014-11-15
I will review the current status of describing spacetime evolution of the relativistic nuclear collisions with fluid dynamics, and of determining the transport coefficients of strongly interacting matter. The fluid dynamical models suggest that shear viscosity to entropy density ratio of the matter is small. However, there are still considerable challenges in determining the transport coefficients, and especially their temperature dependence is still poorly constrained.
Relativistic-microwave theory of ball lightning
H.-C. Wu
2016-01-01
Ball lightning, a fireball sometimes observed during lightnings, has remained unexplained. Here we present a comprehensive theory for the phenomenon: At the tip of a lightning stroke reaching the ground, a relativistic electron bunch can be produced, which in turn excites intense microwave radiation. The latter ionizes the local air and the radiation pressure evacuates the resulting plasma, forming a spherical plasma bubble that stably traps the radiation. This mechanism is verified by partic...
q-Deformed Relativistic Fermion Scattering
Directory of Open Access Journals (Sweden)
Hadi Sobhani
2017-01-01
Full Text Available In this article, after introducing a kind of q-deformation in quantum mechanics, first, q-deformed form of Dirac equation in relativistic quantum mechanics is derived. Then, three important scattering problems in physics are studied. All results have satisfied what we had expected before. Furthermore, effects of all parameters in the problems on the reflection and transmission coefficients are calculated and shown graphically.
Supersymmetric solutions for non-relativistic holography
Energy Technology Data Exchange (ETDEWEB)
Donos, Aristomenis [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Gauntlett, Jerome P. [Blackett Laboratory, Imperial College, London (United Kingdom)]|[Institute for Mathematical Sciences, Imperial College, London (United Kingdom)
2009-01-15
We construct families of supersymmetric solutions of type IIB and D=11 supergravity that are invariant under the non-relativistic conformal algebra for various values of dynamical exponent z{>=}4 and z{>=}3, respectively. The solutions are based on five- and seven-dimensional Sasaki-Einstein manifolds and generalise the known solutions with dynamical exponent z=4 for the type IIB case and z=3 for the D=11 case, respectively. (orig.)
On relativistic models of strange stars
Indian Academy of Sciences (India)
The superdense stars with mass-to-size ratio exceeding 0.3 are expected to be made of strange matter. Assuming that the 3-space of the interior space-time of a strange star is that of a three-paraboloid immersed in a four-dimensional Euclidean space, we obtain a two-parameter family of their physically viable relativistic ...
Relativistic quantum teleportation with superconducting circuits.
Friis, N; Lee, A R; Truong, K; Sabín, C; Solano, E; Johansson, G; Fuentes, I
2013-03-15
We study the effects of relativistic motion on quantum teleportation and propose a realizable experiment where our results can be tested. We compute bounds on the optimal fidelity of teleportation when one of the observers undergoes nonuniform motion for a finite time. The upper bound to the optimal fidelity is degraded due to the observer's motion. However, we discuss how this degradation can be corrected. These effects are observable for experimental parameters that are within reach of cutting-edge superconducting technology.
Relativistic Quantum Transport in Graphene Systems
2015-07-09
way similar to that for conventional two-dimensional semiconductor quantum dot systems. However, the magnetic properties of graphene are quite... semiconductor 2DEG and graphene systems, as shown in Fig. 8. Details of this work can be found in • R. Yang, L. Huang, Y.-C. Lai, C. Grebogi, and L. M...AFRL-OSR-VA-TR-2015-0158 Relativistic Quantum Transport in Graphene Systems Ying Cheng Lai ARIZONA STATE UNIVERSITY Final Report 07/09/2015
Relativistic timescale analysis suggests lunar theory revision
Deines, Steven D.; Williams, Carol A.
1995-01-01
The SI second of the atomic clock was calibrated to match the Ephemeris Time (ET) second in a mutual four year effort between the National Physical Laboratory (NPL) and the United States Naval Observatory (USNO). The ephemeris time is 'clocked' by observing the elapsed time it takes the Moon to cross two positions (usually occultation of stars relative to a position on Earth) and dividing that time span into the predicted seconds according to the lunar equations of motion. The last revision of the equations of motion was the Improved Lunar Ephemeris (ILE), which was based on E. W. Brown's lunar theory. Brown classically derived the lunar equations from a purely Newtonian gravity with no relativistic compensations. However, ET is very theory dependent and is affected by relativity, which was not included in the ILE. To investigate the relativistic effects, a new, noninertial metric for a gravitated, translationally accelerated and rotating reference frame has three sets of contributions, namely (1) Earth's velocity, (2) the static solar gravity field and (3) the centripetal acceleration from Earth's orbit. This last term can be characterized as a pseudogravitational acceleration. This metric predicts a time dilation calculated to be -0.787481 seconds in one year. The effect of this dilation would make the ET timescale run slower than had been originally determined. Interestingly, this value is within 2 percent of the average leap second insertion rate, which is the result of the divergence between International Atomic Time (TAI) and Earth's rotational time called Universal Time (UT or UTI). Because the predictions themselves are significant, regardless of the comparison to TAI and UT, the authors will be rederiving the lunar ephemeris model in the manner of Brown with the relativistic time dilation effects from the new metric to determine a revised, relativistic ephemeris timescale that could be used to determine UT free of leap second adjustments.
Experimental tests of relativistic gravitation theories
Anderson, J. D.
1971-01-01
Experimental tests were studied for determining the potential uses of future deep space missions in studies of relativistic gravity. The extensions to the parametrized post-Newtonian framework to take explicit account of the solar system's center of mass relative to the mean rest frame of the Universe is reported. Discoveries reported include the Machian effects of motion relative to the universal rest frame. Summaries of the JPL research are included.
Relativistic Magnetron Priming Experiments and Theory
2010-03-29
Radiological Scinces dept. University of Michigan Ann Arbor, MI 48109 University of Nevada Reno, Reno NV 10-1 Air Force Office of Scientific Research...versus 30% in the simulation). Due to the idealizations used in the magnetic priming simulations of the UM/L-3 Titan relativistic magnetron, direct ...Laboratory, High Power Microwave Division, Directed Energy Directorate, Kirtland AFB, Albuquerque, NM 87117 USA Abstract Using a hybrid approach, three
On the Relativistic Formulation of Matter
Vishwakarma, Ram Gopal
2012-01-01
A critical analysis of the relativistic formulation of matter reveals some surprising inconsistencies and paradoxes. Corrections are discovered which lead to the long-sought-after equality of the gravitational and inertial masses, which are otherwise different in general relativity. Realizing the potentially great impact of the discovered corrections, an overview of the situation is provided resulting from the newly discovered crisis, amid the evidences defending the theory.
Bartlett, Rodney J.; Morrey, John R.
1978-01-01
A method and apparatus is described for separating gas molecules containing one isotope of an element from gas molecules containing other isotopes of the same element in which all of the molecules of the gas are at the same electronic state in their ground state. Gas molecules in a gas stream containing one of the isotopes are selectively excited to a different electronic state while leaving the other gas molecules in their original ground state. Gas molecules containing one of the isotopes are then deflected from the other gas molecules in the stream and thus physically separated.
Bacon, C.G.
1958-08-26
An improvement is presented in the structure of an isotope separation apparatus and, in particular, is concerned with a magnetically operated shutter associated with a window which is provided for the purpose of enabling the operator to view the processes going on within the interior of the apparatus. The shutier is mounted to close under the force of gravity in the absence of any other force. By closing an electrical circuit to a coil mouated on the shutter the magnetic field of the isotope separating apparatus coacts with the magnetic field of the coil to force the shutter to the open position.
Considerations of acceleration effects in relativistic kinematics
Caviness, Kenneth Edwin
An extended special-relativistic formalism incorporating non-inertial frames undergoing constant proper acceleration is developed as a natural outgrowth of Einstein's 1905 and 1907 treatises. Based on the so-called clock hypothesis, tacitly used by Einstein, and enunciated by von Laue in 1913, which states that the rate of a ideal clock is independent of its momentary acceleration, extended special relativity (ESR) makes use of the Moeller transformation and generalizes the work of Brehme to form a consistent mathematical framework, revealing a number of hitherto hidden features. From this basis, a number of highly interesting kinematic phenomena are considered, among which are: the nonconstancy of the speed of light and the variation of time rates within an accelerated system; the Doppler shift and aberration of light in a noninertial system, viewed by an inertial observer; the curved path of a light signal, preparatory to a treatment of the spatial and temporal Terrell effects in the ESR formalism. The ensuing equations are compared with special relativistic results, and in each case the role of acceleration in the formulae is defined. Quantitative calculations were made, and the results shown in graph form. The ESR formalism is then shown to be a particular case of the general-relativistic formalism. The limits of the accelerated observer's universe and the limits of the theory are discussed.
General Relativistic Effects in Atom Interferometry
Energy Technology Data Exchange (ETDEWEB)
Dimopoulos, Savas; /Stanford U., Phys. Dept.; Graham, Peter W.; /SLAC /Stanford U., Phys. Dept.; Hogan, Jason M.; Kasevich, Mark A.; /Stanford U., Phys. Dept.
2008-03-17
Atom interferometry is now reaching sufficient precision to motivate laboratory tests of general relativity. We begin by explaining the non-relativistic calculation of the phase shift in an atom interferometer and deriving its range of validity. From this we develop a method for calculating the phase shift in general relativity. This formalism is then used to find the relativistic effects in an atom interferometer in a weak gravitational field for application to laboratory tests of general relativity. The potentially testable relativistic effects include the non-linear three-graviton coupling, the gravity of kinetic energy, and the falling of light. We propose experiments, one currently under construction, that could provide a test of the principle of equivalence to 1 part in 10{sup 15} (300 times better than the present limit), and general relativity at the 10% level, with many potential future improvements. We also consider applications to other metrics including the Lense-Thirring effect, the expansion of the universe, and preferred frame and location effects.
Relativistically strong electromagnetic radiation in a plasma
Bulanov, S. V.; Esirkepov, T. Zh.; Kando, M.; Kiriyama, H.; Kondo, K.
2016-03-01
Physical processes in a plasma under the action of relativistically strong electromagnetic waves generated by high-power lasers have been briefly reviewed. These processes are of interest in view of the development of new methods for acceleration of charged particles, creation of sources of bright hard electromagnetic radiation, and investigation of macroscopic quantum-electrodynamical processes. Attention is focused on nonlinear waves in a laser plasma for the creation of compact electron accelerators. The acceleration of plasma bunches by the radiation pressure of light is the most efficient regime of ion acceleration. Coherent hard electromagnetic radiation in the relativistic plasma is generated in the form of higher harmonics and/or electromagnetic pulses, which are compressed and intensified after reflection from relativistic mirrors created by nonlinear waves. In the limit of extremely strong electromagnetic waves, radiation friction, which accompanies the conversion of radiation from the optical range to the gamma range, fundamentally changes the behavior of the plasma. This process is accompanied by the production of electron-positron pairs, which is described within quantum electrodynamics theory.
Substructures in Simulations of Relativistic Jet Formation
Garcia, Raphael de Oliveira; Oliveira, Samuel Rocha de
2017-04-01
We present a set of simulations of relativistic jets from accretion disk initial setup with numerical solutions of a system of general-relativistic magnetohydrodynamics (GRMHD) partial differential equations in a fixed black hole (BH) spacetime which is able to show substructures formations inside the jet as well as lobe formation on the jet head. For this, we used a central scheme of finite volume method without dimensional split and with no Riemann solvers namely the Nessyahu-Tadmor method. Thus, we were able to obtain stable numerical solutions with spurious oscillations under control and with no excessive numerical dissipation. Therefore, we developed some setups for initial conditions capable of simulating the formation of relativistic jets from the accretion disk falling onto central black hole until its ejection, both immersed in a magnetosphere. In our simulations, we were able to observe some substructure of a jet created from an accretion initial disk, namely, jet head, knots, cocoon, and lobe. Also, we present an explanation for cocoon formation and lobe formation. Each initial scenario was determined by ratio between disk density and magnetosphere density, showing that this relation is very important for the shape of the jet and its substructures.
Ejection of stars with relativistic velocities
Dryomova, G.; Dryomov, V.; Tutukov, A.
We present the results of numerical simulations performed in terms of modified Hills' scenario involving two supermassive black holes (SMBHs). In contrast to the classic Hills scenario (Hills 1988), here one component of the ordinary stellar binary system is replaced with a SMBH that provides a kinetic resource for ejecting a star (the secondary component of the binary) with relativistic velocity (RVS). We examine the conditions that favor relativistic ejections of stars, depending on the pericentric approach, the mass ratio of two SMBHs, and the orbital configuration of the binary system. Applying the simple criteria helped us to sort out the results of numerical simulations by the outcome: conservation of the orbital configuration of the binary system, dynamic recapture of the star by the central SMBH, emission of hypervelocity stars (HVSs), and RVS ejection. In the framework of N-body simulations we estimate the probability for a star to survive in the cross-field of two SMBHs during the ejection with relativistic velocity, and discuss the probability of the detection of RVSs in our Galaxy in the cases where such stars are generated in distant interacting galaxies undergoing a merger of their central parts occupied by SMBHs.
Thermal-to-visible face recognition using multiple kernel learning
Hu, Shuowen; Gurram, Prudhvi; Kwon, Heesung; Chan, Alex L.
2014-06-01
Recognizing faces acquired in the thermal spectrum from a gallery of visible face images is a desired capability for the military and homeland security, especially for nighttime surveillance and intelligence gathering. However, thermal-tovisible face recognition is a highly challenging problem, due to the large modality gap between thermal and visible imaging. In this paper, we propose a thermal-to-visible face recognition approach based on multiple kernel learning (MKL) with support vector machines (SVMs). We first subdivide the face into non-overlapping spatial regions or blocks using a method based on coalitional game theory. For comparison purposes, we also investigate uniform spatial subdivisions. Following this subdivision, histogram of oriented gradients (HOG) features are extracted from each block and utilized to compute a kernel for each region. We apply sparse multiple kernel learning (SMKL), which is a MKLbased approach that learns a set of sparse kernel weights, as well as the decision function of a one-vs-all SVM classifier for each of the subjects in the gallery. We also apply equal kernel weights (non-sparse) and obtain one-vs-all SVM models for the same subjects in the gallery. Only visible images of each subject are used for MKL training, while thermal images are used as probe images during testing. With subdivision generated by game theory, we achieved Rank-1 identification rate of 50.7% for SMKL and 93.6% for equal kernel weighting using a multimodal dataset of 65 subjects. With uniform subdivisions, we achieved a Rank-1 identification rate of 88.3% for SMKL, but 92.7% for equal kernel weighting.
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.
Propagation of an ultrashort, intense laser pulse in a relativistic plasma
Energy Technology Data Exchange (ETDEWEB)
Ritchie, B.; Decker, C.D. [Lawrence Livermore National Lab., CA (United States)
1997-12-31
A Maxwell-relativistic fluid model is developed for the propagation of an ultrashort, intense laser pulse through an underdense plasma. The separability of plasma and optical frequencies ({omega}{sub p} and {omega} respectively) for small {omega}{sub p}/{omega} is not assumed; thus the validity of multiple-scales theory (MST) can be tested. The theory is valid when {omega}{sub p}/{omega} is of order unity or for cases in which {omega}{sub p}/{omega} {much_lt} 1 but strongly relativistic motion causes higher-order plasma harmonics to be generated which overlap the region of the first-order laser harmonic, such that MST would not expected to be valid although its principal validity criterion {omega}{sub p}/{omega} {much_lt} 1 holds.
Fuerst, Steven V.; Mizuno, Yosuke; Nishikawa, Ken-Ichi; Wu, Kinwah
2007-01-01
We have calculated the emission from relativistic flows in black hole systems using a fully general relativistic radiative transfer, with flow structures obtained by general relativistic magnetohydrodynamic simulations. We consider thermal free-free emission and thermal synchrotron emission. Bright filament-like features are found protruding (visually) from the accretion disk surface, which are enhancements of synchrotron emission when the magnetic field is roughly aligned with the line-of-sight in the co-moving frame. The features move back and forth as the accretion flow evolves, but their visibility and morphology are robust. We propose that variations and location drifts of the features are responsible for certain X-ray quasi-periodic oscillations (QPOs) observed in black-hole X-ray binaries.
Formulation of the relativistic quantum Hall effect and parity anomaly
Yonaga, Kouki; Hasebe, Kazuki; Shibata, Naokazu
2016-06-01
We present a relativistic formulation of the quantum Hall effect on Haldane sphere. An explicit form of the pseudopotential is derived for the relativistic quantum Hall effect with/without mass term. We clarify particular features of the relativistic quantum Hall states with the use of the exact diagonalization study of the pseudopotential Hamiltonian. Physical effects of the mass term to the relativistic quantum Hall states are investigated in detail. The mass term acts as an interpolating parameter between the relativistic and nonrelativistic quantum Hall effects. It is pointed out that the mass term unevenly affects the many-body physics of the positive and negative Landau levels as a manifestation of the "parity anomaly." In particular, we explicitly demonstrate the instability of the Laughlin state of the positive first relativistic Landau level with the reduction of the charge gap.
Anthraquinones isolated from the browned Chinese chestnut kernels (Castanea mollissima blume)
Zhang, Y. L.; Qi, J. H.; Qin, L.; Wang, F.; Pang, M. X.
2016-08-01
Anthraquinones (AQS) represent a group of secondary metallic products in plants. AQS are often naturally occurring in plants and microorganisms. In a previous study, we found that AQS were produced by enzymatic browning reaction in Chinese chestnut kernels. To find out whether non-enzymatic browning reaction in the kernels could produce AQS too, AQS were extracted from three groups of chestnut kernels: fresh kernels, non-enzymatic browned kernels, and browned kernels, and the contents of AQS were determined. High performance liquid chromatography (HPLC) and nuclear magnetic resonance (NMR) methods were used to identify two compounds of AQS, rehein(1) and emodin(2). AQS were barely exists in the fresh kernels, while both browned kernel groups sample contained a high amount of AQS. Thus, we comfirmed that AQS could be produced during both enzymatic and non-enzymatic browning process. Rhein and emodin were the main components of AQS in the browned kernels.
A fast numerical integrator for relativistic charged particle tracking
Qiang, Ji
2017-09-01
In this paper, we report on a fast second-order numerical integrator to solve the Lorentz force equations of a relativistic charged particle in electromagnetic fields. This numerical integrator shows less numerical error than the popular Boris algorithm in tracking the relativistic particle subject to electric and magnetic space-charge fields and requires less number of operations than another recently proposed relativistic integrator.
Relativistic quantum mechanics and introduction to field theory
Energy Technology Data Exchange (ETDEWEB)
Yndurain, F.J. [Universidad Autonoma de Madrid (Spain). Dept. de Fisica Teorica
1996-12-01
The following topics were dealt with: relativistic transformations, the Lorentz group, Klein-Gordon equation, spinless particles, spin 1/2 particles, Dirac particle in a potential, massive spin 1 particles, massless spin 1 particles, relativistic collisions, S matrix, cross sections, decay rates, partial wave analysis, electromagnetic field quantization, interaction of radiation with matter, interactions in quantum field theory and relativistic interactions with classical sources.
Simulations of Relativistic Effects, Relativistic Time, and the Constancy of Light Velocity
Matveev, Vadim N.; Matvejev, Oleg V.
2013-09-01
Based on pre-Einstein classical mechanics, a theoretical model is constructed that describes the behavior of objects in a liquid environment that conduct themselves in accordance with the formal laws of the special theory of relativity. This model reproduces Lorentz contraction, time dilation, the relativity of simultaneity, the Doppler effect in its symmetrical relativistic form, the twin paradox effects, Bell effect, the relativistic addition of velocities. The model makes it possible to obtain Lorentz transforms and to simulate Minkowski four-dimensional space-time.
Coupled kernel embedding for low resolution face image recognition.
Ren, Chuan-Xian; Dai, Dao-Qing; Yan, Hong
2012-08-01
Practical video scene and face recognition systems are sometimes confronted with low-resolution (LR) images. The faces may be very small even if the video is clear, thus it is difficult to directly measure the similarity between the faces and the high-resolution (HR) training samples. Traditional super-resolution (SR) methods based face recognition usually have limited performance because the target of SR may not be consistent with that of classification, and time-consuming SR algorithms are not suitable for real-time applications. In this paper, a new feature extraction method called Coupled Kernel Embedding (CKE) is proposed for LR face recognition without any SR preprocessing. In this method, the final kernel matrix is constructed by concatenating two individual kernel matrices in the diagonal direction, and the (semi-)positively definite properties are preserved for optimization. CKE addresses the problem of comparing multi-modal data that are difficult for conventional methods in practice due to the lack of an efficient similarity measure. Particularly, different kernel types (e.g., linear, Gaussian, polynomial) can be integrated into an uniformed optimization objective, which cannot be achieved by simple linear methods. CKE solves this problem by minimizing the dissimilarities captured by their kernel Gram matrices in the low- and high-resolution spaces. In the implementation, the nonlinear objective function is minimized by a generalized eigenvalue decomposition. Experiments on benchmark and real databases show that our CKE method indeed improves the recognition performance.
Sliding Window Generalized Kernel Affine Projection Algorithm Using Projection Mappings
Slavakis, Konstantinos; Theodoridis, Sergios
2008-12-01
Very recently, a solution to the kernel-based online classification problem has been given by the adaptive projected subgradient method (APSM). The developed algorithm can be considered as a generalization of a kernel affine projection algorithm (APA) and the kernel normalized least mean squares (NLMS). Furthermore, sparsification of the resulting kernel series expansion was achieved by imposing a closed ball (convex set) constraint on the norm of the classifiers. This paper presents another sparsification method for the APSM approach to the online classification task by generating a sequence of linear subspaces in a reproducing kernel Hilbert space (RKHS). To cope with the inherent memory limitations of online systems and to embed tracking capabilities to the design, an upper bound on the dimension of the linear subspaces is imposed. The underlying principle of the design is the notion of projection mappings. Classification is performed by metric projection mappings, sparsification is achieved by orthogonal projections, while the online system's memory requirements and tracking are attained by oblique projections. The resulting sparsification scheme shows strong similarities with the classical sliding window adaptive schemes. The proposed design is validated by the adaptive equalization problem of a nonlinear communication channel, and is compared with classical and recent stochastic gradient descent techniques, as well as with the APSM's solution where sparsification is performed by a closed ball constraint on the norm of the classifiers.
Sliding Window Generalized Kernel Affine Projection Algorithm Using Projection Mappings
Directory of Open Access Journals (Sweden)
Sergios Theodoridis
2008-05-01
Full Text Available Very recently, a solution to the kernel-based online classification problem has been given by the adaptive projected subgradient method (APSM. The developed algorithm can be considered as a generalization of a kernel affine projection algorithm (APA and the kernel normalized least mean squares (NLMS. Furthermore, sparsification of the resulting kernel series expansion was achieved by imposing a closed ball (convex set constraint on the norm of the classifiers. This paper presents another sparsification method for the APSM approach to the online classification task by generating a sequence of linear subspaces in a reproducing kernel Hilbert space (RKHS. To cope with the inherent memory limitations of online systems and to embed tracking capabilities to the design, an upper bound on the dimension of the linear subspaces is imposed. The underlying principle of the design is the notion of projection mappings. Classification is performed by metric projection mappings, sparsification is achieved by orthogonal projections, while the online system's memory requirements and tracking are attained by oblique projections. The resulting sparsification scheme shows strong similarities with the classical sliding window adaptive schemes. The proposed design is validated by the adaptive equalization problem of a nonlinear communication channel, and is compared with classical and recent stochastic gradient descent techniques, as well as with the APSM's solution where sparsification is performed by a closed ball constraint on the norm of the classifiers.
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.
Boundary conditions for gas flow problems from anisotropic scattering kernels
To, Quy-Dong; Vu, Van-Huyen; Lauriat, Guy; Léonard, Céline
2015-10-01
The paper presents an interface model for gas flowing through a channel constituted of anisotropic wall surfaces. Using anisotropic scattering kernels and Chapman Enskog phase density, the boundary conditions (BCs) for velocity, temperature, and discontinuities including velocity slip and temperature jump at the wall are obtained. Two scattering kernels, Dadzie and Méolans (DM) kernel, and generalized anisotropic Cercignani-Lampis (ACL) are examined in the present paper, yielding simple BCs at the wall fluid interface. With these two kernels, we rigorously recover the analytical expression for orientation dependent slip shown in our previous works [Pham et al., Phys. Rev. E 86, 051201 (2012) and To et al., J. Heat Transfer 137, 091002 (2015)] which is in good agreement with molecular dynamics simulation results. More important, our models include both thermal transpiration effect and new equations for the temperature jump. While the same expression depending on the two tangential accommodation coefficients is obtained for slip velocity, the DM and ACL temperature equations are significantly different. The derived BC equations associated with these two kernels are of interest for the gas simulations since they are able to capture the direction dependent slip behavior of anisotropic interfaces.
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.
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.
Phase discontinuity predictions using a machine-learning trained kernel.
Sawaf, Firas; Groves, Roger M
2014-08-20
Phase unwrapping is one of the key steps of interferogram analysis, and its accuracy relies primarily on the correct identification of phase discontinuities. This can be especially challenging for inherently noisy phase fields, such as those produced through shearography and other speckle-based interferometry techniques. We showed in a recent work how a relatively small 10×10 pixel kernel was trained, through machine learning methods, for predicting the locations of phase discontinuities within noisy wrapped phase maps. We describe here how this kernel can be applied in a sliding-window fashion, such that each pixel undergoes 100 phase-discontinuity examinations--one test for each of its possible positions relative to its neighbors within the kernel's extent. We explore how the resulting predictions can be accumulated, and aggregated through a voting system, and demonstrate that the reliability of this method outperforms processing the image by segmenting it into more conventional 10×10 nonoverlapping tiles. When used in this way, we demonstrate that our 10×10 pixel kernel is large enough for effective processing of full-field interferograms. Avoiding, thus, the need for substantially more formidable computational resources which otherwise would have been necessary for training a kernel of a significantly larger size.
Mass spectrum bound state systems with relativistic corrections
Energy Technology Data Exchange (ETDEWEB)
Dineykhan, M; Zhaugasheva, S A [Bogoliubov Laboratory of Theoretical Physics, Joint Institute for Nuclear Research, Dubna (Russian Federation); Toinbaeva, N Sh; Jakhanshir, A [al-Farabi Kazak National University, 480012 Almaty (Kazakhstan)
2009-07-28
Based on the investigation of the asymptotic behaviour of the polarization loop function for charged n scalar particles in an external gauge field, we determine the interaction Hamiltonian including relativistic corrections. The mass spectrum of the bound state is analytically derived. The mechanism for arising of the constituent mass of the relativistic bound-state forming particles is explained. The mass and the constituent mass of the two-, three- and n-body relativistic bound states are calculated taking into account relativistic corrections. The corrections arising due to the one- and two-loop electron polarization to the energy spectrum of muonic hydrogen with orbital and radial excitations are calculated.
Theoretical study of the relativistic molecular rotational g-tensor
Energy Technology Data Exchange (ETDEWEB)
Aucar, I. Agustín, E-mail: agustin.aucar@conicet.gov.ar; Gomez, Sergio S., E-mail: ssgomez@exa.unne.edu.ar [Institute for Modeling and Technological Innovation, IMIT (CONICET-UNNE) and Faculty of Exact and Natural Sciences, Northeastern University of Argentina, Avenida Libertad 5400, W3404AAS Corrientes (Argentina); Giribet, Claudia G.; Ruiz de Azúa, Martín C. [Physics Department, Faculty of Exact and Natural Sciences, University of Buenos Aires and IFIBA CONICET, Ciudad Universitaria, Pab. I, 1428 Buenos Aires (Argentina)
2014-11-21
An original formulation of the relativistic molecular rotational g-tensor valid for heavy atom containing compounds is presented. In such formulation, the relevant terms of a molecular Hamiltonian for non-relativistic nuclei and relativistic electrons in the laboratory system are considered. Terms linear and bilinear in the nuclear rotation angular momentum and an external uniform magnetic field are considered within first and second order (relativistic) perturbation theory to obtain the rotational g-tensor. Relativistic effects are further analyzed by carrying out the linear response within the elimination of the small component expansion. Quantitative results for model systems HX (X=F, Cl, Br, I), XF (X=Cl, Br, I), and YH{sup +} (Y=Ne, Ar, Kr, Xe, Rn) are obtained both at the RPA and density functional theory levels of approximation. Relativistic effects are shown to be small for this molecular property. The relation between the rotational g-tensor and susceptibility tensor which is valid in the non-relativistic theory does not hold within the relativistic framework, and differences between both molecular parameters are analyzed for the model systems under study. It is found that the non-relativistic relation remains valid within 2% even for the heavy HI, IF, and XeH{sup +} systems. Only for the sixth-row Rn atom a significant deviation of this relation is found.
Hossein Gorji, M.; Jenny, Patrick
2014-12-01
This work presents a kinetic wall boundary model for diatomic gas molecules. The model is derived by generalizing the Cercignani-Lampis-Lord gas-surface interaction kernel in order to account for the gas internal degrees of freedom. Here, opposed to the extensions by Lord ["Some extensions to the Cercignani-Lampis gas-surface scattering kernel," Phys. Fluids 3, 706-710 (1991)], energy exchange between different molecular modes is honored and thus, different physical phenomena arising from inelastic gas-surface collisions can be described. For practical implementations of the model, a Monte-Carlo algorithm was devised, which significantly reduces the computational cost associated with sampling. Comparisons of model predictions with experimental and molecular dynamics data exhibit good agreement. Moreover, simulation studies are performed to demonstrate how energy transfers between different modes due to wall collisions can be exploited for gas separation.
2016-01-01
Footage of the 90 and 60 degree ISOLDE HRS separator magnets in the HRS separator zone. In the two vacuum sectors HRS20 and HRS30 equipment such as the HRS slits SL240, the HRS faraday cup FC300 and wiregrid WG210 can be spotted. Vacuum valves, turbo pumps, beamlines, quadrupoles, water and compressed air connections, DC and signal cabling can be seen throughout the video. The HRS main and user beamgate in the beamline between MAG90 and MAG60 and its switchboxes as well as all vacuum bellows and flanges are shown. Instrumentation such as the HRS scanner unit 482 / 483, the HRS WG470 wiregrid and slits piston can be seen. The different quadrupoles and supports are shown as well as the RILIS guidance tubes and installation at the magnets and the different radiation monitors.
2016-01-01
Footage of the 70 degree ISOLDE GPS separator magnet MAG70 as well as the switchyard for the Central Mass and GLM (GPS Low Mass) and GHM (GPS High Mass) beamlines in the GPS separator zone. In the GPS20 vacuum sector equipment such as the long GPS scanner 482 / 483 unit, faraday cup FC 490, vacuum valves and wiregrid piston WG210 and WG475 and radiation monitors can also be seen. Also the RILIS laser guidance and trajectory can be seen, the GPS main beamgate switch box and the actual GLM, GHM and Central Beamline beamgates in the beamlines as well as the first electrostatic quadrupoles for the GPS lines. Close up of the GHM deflector plates motor and connections and the inspection glass at the GHM side of the switchyard.
Rubin, Leslie S.
1986-01-01
A separation system for dewatering radioactive waste materials includes a disposal container, drive structure for receiving the container, and means for releasably attaching the container to the drive structure. Separation structure disposed in the container adjacent the inner surface of the side wall structure retains solids while allowing passage of liquids. Inlet port structure in the container top wall is normally closed by first valve structure that is centrifugally actuated to open the inlet port and discharge port structure at the container periphery receives liquid that passes through the separation structure and is normally closed by second valve structure that is centrifugally actuated to open the discharge ports. The container also includes coupling structure for releasable engagement with the centrifugal drive structure. Centrifugal force produced when the container is driven in rotation by the drive structure opens the valve structures, and radioactive waste material introduced into the container through the open inlet port is dewatered, and the waste is compacted. The ports are automatically closed by the valves when the container drum is not subjected to centrifugal force such that containment effectiveness is enhanced and exposure of personnel to radioactive materials is minimized.
Design, development and evaluation of a divergent roller sizer for almond kernels
Directory of Open Access Journals (Sweden)
D Ghanbarian
2015-09-01
Full Text Available Introduction: Iran is one of the major producers of almonds. According to the statistics released by FAO (2011, Iran with more than 110000 tons of almonds is the third in rank throughout the world. However, most Iranian almonds are presented as an unsorted and unpackaged product. Some producers sort their products by hand which is very time-consuming and labor-intensive. So, there is an essential need for suitable grading and packaging machines especially for the export of almond kernels.Grading, which is sometimes called sorting, is basically separating the material in different homogenous groups according to its specific characteristics like size, shape, color and on the basis of quality. Weighing is one of the best methods for grading agricultural products based on size, but due to its high cost and complexity of operations, usage of weigh size sorting machines is practically limited. So, sizing of most agricultural products is accomplished based on their dimensional attributes such as diameter, length, thickness or a combination of them. Field study shows that recently vibrating sizing machines are used for grading almond kernels. This type of sizing machine is huge, expensive, noisy and it consumes a lot of energy. Thus, the main objective of the present study was the design, development and evaluation of a new prototype of an almond kernel sizing machine. Materials and methods: It is important that the machine could resolve defects of existing vibrating machines. It should provide efficient and cost effective sizing for a wide range of kernel sizes and shapes. Furthermore, it should be of simple construction and be able to accept manual feeding. Previously conducted experiments showed that the thickness of the kernel is the most appropriate dimension for its sizing. Among the different types of dimensional sizing machines, the divergent roller grader which grades the products based on their thickness is considered to be one of the simplest
Fredholm-Volterra integral equation with potential kernel
Directory of Open Access Journals (Sweden)
M. A. Abdou
2001-01-01
Full Text Available A method is used to solve the Fredholm-Volterra integral equation of the first kind in the space L2(Ω×C(0,T, Ω={(x,y:x2+y2≤a}, z=0, and T<∞. The kernel of the Fredholm integral term considered in the generalized potential form belongs to the class C([Ω]×[Ω], while the kernel of Volterra integral term is a positive and continuous function that belongs to the class C[0,T]. Also in this work the solution of Fredholm integral equation of the second and first kind with a potential kernel is discussed. Many interesting cases are derived and established in the paper.
Extreme Kernel Sparse Learning for Tactile Object Recognition.
Liu, Huaping; Qin, Jie; Sun, Fuchun; Guo, Di
2016-10-19
Tactile sensors play very important role for robot perception in the dynamic or unknown environment. However, the tactile object recognition exhibits great challenges in practical scenarios. In this paper, we address this problem by developing an extreme kernel sparse learning methodology. This method combines the advantages of extreme learning machine and kernel sparse learning by simultaneously addressing the dictionary learning and the classifier design problems. Furthermore, to tackle the intrinsic difficulties which are introduced by the representer theorem, we develop a reduced kernel dictionary learning method by introducing row-sparsity constraint. A globally convergent algorithm is developed to solve the optimization problem and the theoretical proof is provided. Finally, we perform extensive experimental validations on some public available tactile sequence datasets and show the advantages of the proposed method.
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....
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.
Gámez-Meza, Nohemí; Alday-Lara, Perla P; Makkar, Harinder P S; Becker, Klaus; Medina-Juárez, Luis A
2013-05-01
Jatropha cordata and Jatropha cardiophylla are native to northwestern Mexico and are adapted to arid and semi-arid conditions (antinutrients in the defatted kernel meals of these species. Kernels of J. cordata and J. cardiophylla seeds analysed in this study were rich in crude protein (283 and 289 g kg(-1) respectively) and lipid (517 and 537 g kg(-1) respectively). The main fatty acids in J. cordata and J. cardiophylla oils were linoleic and oleic acids. High levels of trypsin inhibitor and phytates and low levels of saponins were present in the meals. The phorbol ester contents in J. cordata and J. cardiophylla kernel meals were 2.73 and 1.46 mg g(-1) respectively. For both J. cordata and J. cardiophylla it could be inferred that (a) the oil and kernel meal were toxic and the kernel meal could be used as livestock feed only after detoxification, (b) the oil could be used for non-alimentary purposes, i.e. biodiesel production, and (c) the seed or oil could be used for isolating various bioactive compounds for pharmaceutical and agricultural applications. © 2012 Society of Chemical Industry.
Directory of Open Access Journals (Sweden)
Edward Bormashenko
2007-09-01
Full Text Available It is demonstrated that the entropy of the ideal mono-atomic gas comprisingidentical spherical atoms is not conserved under the Planck-Einstein like relativistictemperature transformation, as a result of the change in the number of atomic degrees offreedom. This fact supports the idea that there is no universal relativistic temperaturetransformation.
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.
Relativistic hydrodynamic jets in the intracluster medium
Choi, Eunwoo
2017-08-01
We have performed the first three-dimensional relativistic hydrodynamic simulations of extragalactic jets of pure leptonic and baryonic plasma compositions propagating into a hydrostatic intracluster medium (ICM) environment. The numerical simulations use a general equation of state for a multicomponent relativistic gas, which closely reproduces the Synge equation of state for a relativistic perfect gas. We find that morphological and dynamical differences between leptonic and baryonic jets are much less evident than those between hot and cold jets. In all these models, the jets first propagate with essentially constant velocities within the core radius of the ICM and then accelerate progressively so as to increase the jet advance velocity by a factor of between 1.2 and 1.6 at the end of simulations, depending upon the models. The temporal evolution of the average cavity pressure is not consistent with that expected by the extended theoretical model even if the average cavity pressure decreases as a function of time with a power law. Our simulations produce synthetic radio images that are dominated by bright hot spots and appear similar to observations of the extended radio galaxies with collimated radio jets. These bright radio lobes would be visible as dark regions in X-ray images and are morphologically similar to observed X-ray cavities in the ICM. This supports the expectation that the bow shock surrounding the head of the jet is important mechanism for producing X-ray cavities in the ICM. Although there are quantitative differences among the models, the total radio and X-ray intensity curves show qualitatively similar trends in all of them.
Gollan, A.
1988-03-29
Feed gas is directed tangentially along the non-skin surface of gas separation membrane modules comprising a cylindrical bundle of parallel contiguous hollow fibers supported to allow feed gas to flow from an inlet at one end of a cylindrical housing through the bores of the bundled fibers to an outlet at the other end while a component of the feed gas permeates through the fibers, each having the skin side on the outside, through a permeate outlet in the cylindrical casing. 3 figs.
1975-11-01
perfomanoas que oette oirconstance peut entrainer, soit encore, d’un point de vue plus fondamental par la recherche dM phenomknas qui caracterisent 1M...dtfoolleoent, dont le m^canlsme de formation eat en tout point sen- blable h celui qui a etc döcrit § 2.2. XL se caracterise par la presence d’une onde...during orbital maneuvers with the Reaction Control System (RCS) and later plume induced separation leading to aerodynamic heating and control problems
Large-Scale Training of SVMs with Automata Kernels
Allauzen, Cyril; Cortes, Corinna; Mohri, Mehryar
This paper presents a novel application of automata algorithms to machine learning. It introduces the first optimization solution for support vector machines used with sequence kernels that is purely based on weighted automata and transducer algorithms, without requiring any specific solver. The algorithms presented apply to a family of kernels covering all those commonly used in text and speech processing or computational biology. We show that these algorithms have significantly better computational complexity than previous ones and report the results of large-scale experiments demonstrating a dramatic reduction of the training time, typically by several orders of magnitude.
Epileptic seizure detection based on the kernel extreme learning machine.
Liu, Qi; Zhao, Xiaoguang; Hou, Zengguang; Liu, Hongguang
2017-07-20
This paper presents a pattern recognition model using multiple features and the kernel extreme learning machine (ELM), improving the accuracy of automatic epilepsy diagnosis. After simple preprocessing, temporal- and wavelet-based features are extracted from epileptic EEG signals. A combined kernel-function-based ELM approach is then proposed for feature classification. To further reduce the computation, Cholesky decomposition is introduced during the process of calculating the output weights. The experimental results show that the proposed method can achieve satisfactory accuracy with less computation time.
Rebootless Linux Kernel Patching with Ksplice Uptrack at BNL
Hollowell, Christopher; Pryor, James; Smith, Jason
2012-12-01
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.
Introduction to the relativistic string theory
Barbashov, B M
1990-01-01
This book presents a systematic and detailed account of the classical and quantum theory of the relativistic string and some of its modifications. Main attention is paid to the first-quantized string theory with possible applications to the string models of hadrons as well as to the superstring approach to unifications of all the fundamental interactions in the elementary particle physics and to the "cosmic" strings. Some new aspects are provided such as the consideration of the string in an external electromagnetic field and in the space-time of constant curvature (the de Sitter universe), th
Relativistic field theory and chaotic dynamics
Energy Technology Data Exchange (ETDEWEB)
Tanaka, Yosuke
2005-01-01
We have studied the relativistic equations and chaotic motions of gravitational field on the basis of the theory of relativity and chaos. Friedmann equation (the space component) shows the chaotic behaviours in case of the inflation universe (G/G>0) and shows the non-chaotic behaviours in case of the flat and contraction universe (G/G {<=} 0). With the use of Kerr metric, we have discussed the non-diagonal tensor effect on gravitational field and chaotic dynamics. We have also discussed the dimension of the universe on the basis of E infinity theory.
Foil focusing of relativistic electron beams
Energy Technology Data Exchange (ETDEWEB)
Ekdahl, Jr., Carl August [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-10-26
When an intense relativistic electron beams (IREB) passes through a grounded metal foil, the transverse electric field due to the beam space charge is locally shorted out, and the beam is focused by the magnetic field of its current. The effect can be treated as focusing by a thin lens with first order aberration. Expressions for the focal length and aberration coefficient of the equivalent thin lens are developed in this note. These are then applied to practical examples representative of IREB research at Los Alamos National Laboratory.
A Relativistic Symmetrical Interpretation of Quantum Mechanics
Heaney, Michael B.
This poster describes a relativistic symmetrical interpretation (RSI) which postulates: quantum mechanics is intrinsically time-symmetric, with no arrow of time; the fundamental objects of quantum mechanics are transitions; a transition is fully described by a complex transition amplitude density with specified initial and final boundary conditions, and; transition amplitude densities never collapse. This RSI is compared to the Copenhagen Interpretation (CI) for the analysis of Einstein's bubble experiment using both the Dirac and Klein-Gordon equations. The RSI has no zitterbewegung in the particle's rest frame, resolves some inconsistencies of the CI, and gives intuitive explanations of some previously mysterious quantum effects.
Proton relativistic model; Modelo relativistico do proton
Energy Technology Data Exchange (ETDEWEB)
Araujo, Wilson Roberto Barbosa de
1995-12-31
In this dissertation, we present a model for the nucleon, which is composed by three relativistic quarks interacting through a contract force. The nucleon wave-function was obtained from the Faddeev equation in the null-plane. The covariance of the model under kinematical null-plane boots is discussed. The electric proton form-factor, calculated from the Faddeev wave-function, was in agreement with the data for low-momentum transfers and described qualitatively the asymptotic region for momentum transfers around 2 GeV. (author) 42 refs., 22 figs., 1 tab.