Electromagnetic scattering of a vector Bessel beam in the presence of an impedance cone

KAUST Repository

Salem, Mohamed

2013-07-01

The electromagnetic field scattering of a vector Bessel beam in the presence of an infinite circular cone with an impedance boundary on its surface is considered. The impinging field is normal to the tip of the cone and is expanded in terms of vector spherical wave functions; a Kontorovich-Lebedev (KL) transform is employed to expand the scattered fields. The problem is reduced to a singular integral equation with a variable coefficient of the non-convolution type. The singularities of the spectral function are deduced and representations for the field at the tip of the cone as well as other regions are given together with the conditions of validity of these representations. © 2013 IEEE.

Experimental study of current loss and plasma formation in the Z machine post-hole convolute

Directory of Open Access Journals (Sweden)

M. R. Gomez

2017-01-01

Full Text Available The Z pulsed-power generator at Sandia National Laboratories drives high energy density physics experiments with load currents of up to 26 MA. Z utilizes a double post-hole convolute to combine the current from four parallel magnetically insulated transmission lines into a single transmission line just upstream of the load. Current loss is observed in most experiments and is traditionally attributed to inefficient convolute performance. The apparent loss current varies substantially for z-pinch loads with different inductance histories; however, a similar convolute impedance history is observed for all load types. This paper details direct spectroscopic measurements of plasma density, temperature, and apparent and actual plasma closure velocities within the convolute. Spectral measurements indicate a correlation between impedance collapse and plasma formation in the convolute. Absorption features in the spectra show the convolute plasma consists primarily of hydrogen, which likely forms from desorbed electrode contaminant species such as H_{2}O, H_{2}, and hydrocarbons. Plasma densities increase from 1×10^{16}  cm^{−3} (level of detectability just before peak current to over 1×10^{17}  cm^{−3} at stagnation (tens of ns later. The density seems to be highest near the cathode surface, with an apparent cathode to anode plasma velocity in the range of 35–50  cm/μs. Similar plasma conditions and convolute impedance histories are observed in experiments with high and low losses, suggesting that losses are driven largely by load dynamics, which determine the voltage on the convolute.

Implementation and validation of collapsed cone superposition for radiopharmaceutical dosimetry of photon emitters

Science.gov (United States)

Sanchez-Garcia, Manuel; Gardin, Isabelle; Lebtahi, Rachida; Dieudonné, Arnaud

2015-10-01

Two collapsed cone (CC) superposition algorithms have been implemented for radiopharmaceutical dosimetry of photon emitters. The straight CC (SCC) superposition method uses a water energy deposition kernel (EDKw) for each electron, positron and photon components, while the primary and scatter CC (PSCC) superposition method uses different EDKw for primary and once-scattered photons. PSCC was implemented only for photons originating from the nucleus, precluding its application to positron emitters. EDKw are linearly scaled by radiological distance, taking into account tissue density heterogeneities. The implementation was tested on 100, 300 and 600 keV mono-energetic photons and 18F, 99mTc, 131I and 177Lu. The kernels were generated using the Monte Carlo codes MCNP and EGSnrc. The validation was performed on 6 phantoms representing interfaces between soft-tissues, lung and bone. The figures of merit were γ (3%, 3 mm) and γ (5%, 5 mm) criterions corresponding to the computation comparison on 80 absorbed doses (AD) points per phantom between Monte Carlo simulations and CC algorithms. PSCC gave better results than SCC for the lowest photon energy (100 keV). For the 3 isotopes computed with PSCC, the percentage of AD points satisfying the γ (5%, 5 mm) criterion was always over 99%. A still good but worse result was found with SCC, since at least 97% of AD-values verified the γ (5%, 5 mm) criterion, except a value of 57% for the 99mTc with the lung/bone interface. The CC superposition method for radiopharmaceutical dosimetry is a good alternative to Monte Carlo simulations while reducing computation complexity.

Implementation and validation of collapsed cone superposition for radiopharmaceutical dosimetry of photon emitters.

Science.gov (United States)

Sanchez-Garcia, Manuel; Gardin, Isabelle; Lebtahi, Rachida; Dieudonné, Arnaud

2015-10-21

Two collapsed cone (CC) superposition algorithms have been implemented for radiopharmaceutical dosimetry of photon emitters. The straight CC (SCC) superposition method uses a water energy deposition kernel (EDKw) for each electron, positron and photon components, while the primary and scatter CC (PSCC) superposition method uses different EDKw for primary and once-scattered photons. PSCC was implemented only for photons originating from the nucleus, precluding its application to positron emitters. EDKw are linearly scaled by radiological distance, taking into account tissue density heterogeneities. The implementation was tested on 100, 300 and 600 keV mono-energetic photons and (18)F, (99m)Tc, (131)I and (177)Lu. The kernels were generated using the Monte Carlo codes MCNP and EGSnrc. The validation was performed on 6 phantoms representing interfaces between soft-tissues, lung and bone. The figures of merit were γ (3%, 3 mm) and γ (5%, 5 mm) criterions corresponding to the computation comparison on 80 absorbed doses (AD) points per phantom between Monte Carlo simulations and CC algorithms. PSCC gave better results than SCC for the lowest photon energy (100 keV). For the 3 isotopes computed with PSCC, the percentage of AD points satisfying the γ (5%, 5 mm) criterion was always over 99%. A still good but worse result was found with SCC, since at least 97% of AD-values verified the γ (5%, 5 mm) criterion, except a value of 57% for the (99m)Tc with the lung/bone interface. The CC superposition method for radiopharmaceutical dosimetry is a good alternative to Monte Carlo simulations while reducing computation complexity.

Volcaniclastic dykes tell on fracturing, explosive eruption and lateral collapse at Stromboli volcano (Italy)

Science.gov (United States)

Vezzoli, Luigina; Corazzato, Claudia

2016-05-01

In the upper part of the Stromboli volcano, in the Le Croci and Bastimento areas, two dyke-like bodies of volcanic breccia up to two-metre thick crosscut and intrude the products of Vancori and Neostromboli volcanoes. We describe the lithofacies association of these unusual volcaniclastic dykes, interpret the setting of dyke-forming fractures and the emplacement mechanism of internal deposits, and discuss their probable relationships with the explosive eruption and major lateral collapse events that occurred at the end of the Neostromboli period. The dyke volcaniclastic deposits contain juvenile magmatic fragments (pyroclasts) suggesting a primary volcanic origin. Their petrographic characteristics are coincident with the Neostromboli products. The architecture of the infilling deposits comprises symmetrically-nested volcaniclastic units, separated by sub-vertical boundaries, which are parallel to the dyke margins. The volcanic units are composed of distinctive lithofacies. The more external facies is composed of fine and coarse ash showing sub-vertical laminations, parallel to the contact wall. The central facies comprises stratified, lithic-rich breccia and lapilli-tuff, whose stratification is sub-horizontal and convolute, discordant to the dyke margins. Only at Le Croci dyke, the final unit shows a massive tuff-breccia facies. The volcaniclastic dykes experienced a polyphasic geological evolution comprising three stages. The first phase consisted in fracturing, explosive intrusion related to magma rising and upward injection of magmatic fluids and pyroclasts. The second phase recorded the dilation of fractures and their role as pyroclastic conduits in an explosive eruption possibly coeval with the lateral collapse of the Neostromboli lava cone. Finally, in the third phase, the immediately post-eruption mass-flow remobilization of pyroclastic deposits took place on the volcano slopes.

On the use of Kontorovich-Lebedev transform in electromagnetic diffraction by an impedance cone

KAUST Repository

Salem, Mohamed; Kamel, Aladin Hassan; Bagci, Hakan

2012-01-01

We consider the boundary-value problem for the Helmholtz equation connected with an infinite circular cone with an impedance boundary on its face. The scheme of solution includes applying the Kontorovich-Lebedev (KL) transform to reduce the problem to that of a KL spectral amplitude function satisfying a singular integral equation of the non-convolution type with a variable coefficient. The singularities of the spectral function are deduced and representations for the field at the tip of the cone and in the near and far field regions are given together with the conditions of validity of these representations. © 2012 IEEE.

On the use of Kontorovich-Lebedev transform in electromagnetic diffraction by an impedance cone

KAUST Repository

Salem, Mohamed

2012-08-01

We consider the boundary-value problem for the Helmholtz equation connected with an infinite circular cone with an impedance boundary on its face. The scheme of solution includes applying the Kontorovich-Lebedev (KL) transform to reduce the problem to that of a KL spectral amplitude function satisfying a singular integral equation of the non-convolution type with a variable coefficient. The singularities of the spectral function are deduced and representations for the field at the tip of the cone and in the near and far field regions are given together with the conditions of validity of these representations. © 2012 IEEE.

Fundamentals of convolutional coding

CERN Document Server

Johannesson, Rolf

2015-01-01

Fundamentals of Convolutional Coding, Second Edition, regarded as a bible of convolutional coding brings you a clear and comprehensive discussion of the basic principles of this field * Two new chapters on low-density parity-check (LDPC) convolutional codes and iterative coding * Viterbi, BCJR, BEAST, list, and sequential decoding of convolutional codes * Distance properties of convolutional codes * Includes a downloadable solutions manual

Poster - 07: Investigations of the Advanced Collapsed-cone Engine for HDR Brachytherapy Scalp Treatments

Energy Technology Data Exchange (ETDEWEB)

Cawston-Grant, Brie; Morrison, Hali; Sloboda, Ron; Menon, Geetha [Cross Cancer Institute, University of Alberta, Edmonton (Canada)

2016-08-15

Purpose: To present an investigation of the Advanced Collapsed-cone Engine (ACE) in Oncentraê Brachy (OcB) v4.5 using a tissue equivalent phantom modeling scalp brachytherapy (BT) treatments. Methods: A slab phantom modeling the skin, skull, brain and mold was used. A dose of 400cGy was prescribed to just above the skull layer using TG-43 and was delivered using an HDR afterloader. Measurements were made using Gafchromic™ EBT3 film at four depths within the phantom. The TG-43 planned and film measured doses were compared to the standard (sACE) and high (hACE) accuracy ACE options in OcB between the surface and below the skull. Results: The average difference between the TG-43 calculated and film measured doses was −11.25±3.38% when there was no air gap between the mold and skin; sACE and hACE doses were on average lower than TG-43 calculated doses by 3.41±0.03% and 2.45±0.03%, respectively. With a 3mm air gap between the mold and skin, the difference between the TG-43 calculated and measured doses was −8.28±5.76%; sACE and hACE calculations yielded average doses 1.87±0.03% and 1.78±0.04% greater than TG-43, respectively. Conclusions: TG-43, sACE, and hACE were found to overestimate doses below the skull layer compared to film. With a 3mm air gap between the mold and skin, sACE and hACE more accurately predicted the film dose to the skin surface than TG-43. More clinical variations and their implications are currently being investigated.

Poster - 07: Investigations of the Advanced Collapsed-cone Engine for HDR Brachytherapy Scalp Treatments

International Nuclear Information System (INIS)

Cawston-Grant, Brie; Morrison, Hali; Sloboda, Ron; Menon, Geetha

2016-01-01

Purpose: To present an investigation of the Advanced Collapsed-cone Engine (ACE) in Oncentraê Brachy (OcB) v4.5 using a tissue equivalent phantom modeling scalp brachytherapy (BT) treatments. Methods: A slab phantom modeling the skin, skull, brain and mold was used. A dose of 400cGy was prescribed to just above the skull layer using TG-43 and was delivered using an HDR afterloader. Measurements were made using Gafchromic™ EBT3 film at four depths within the phantom. The TG-43 planned and film measured doses were compared to the standard (sACE) and high (hACE) accuracy ACE options in OcB between the surface and below the skull. Results: The average difference between the TG-43 calculated and film measured doses was −11.25±3.38% when there was no air gap between the mold and skin; sACE and hACE doses were on average lower than TG-43 calculated doses by 3.41±0.03% and 2.45±0.03%, respectively. With a 3mm air gap between the mold and skin, the difference between the TG-43 calculated and measured doses was −8.28±5.76%; sACE and hACE calculations yielded average doses 1.87±0.03% and 1.78±0.04% greater than TG-43, respectively. Conclusions: TG-43, sACE, and hACE were found to overestimate doses below the skull layer compared to film. With a 3mm air gap between the mold and skin, sACE and hACE more accurately predicted the film dose to the skin surface than TG-43. More clinical variations and their implications are currently being investigated.

Convolution based profile fitting

International Nuclear Information System (INIS)

Kern, A.; Coelho, A.A.; Cheary, R.W.

2002-01-01

Full text: In convolution based profile fitting, profiles are generated by convoluting functions together to form the observed profile shape. For a convolution of 'n' functions this process can be written as, Y(2θ)=F 1 (2θ)x F 2 (2θ)x... x F i (2θ)x....xF n (2θ). In powder diffractometry the functions F i (2θ) can be interpreted as the aberration functions of the diffractometer, but in general any combination of appropriate functions for F i (2θ) may be used in this context. Most direct convolution fitting methods are restricted to combinations of F i (2θ) that can be convoluted analytically (e.g. GSAS) such as Lorentzians, Gaussians, the hat (impulse) function and the exponential function. However, software such as TOPAS is now available that can accurately convolute and refine a wide variety of profile shapes numerically, including user defined profiles, without the need to convolute analytically. Some of the most important advantages of modern convolution based profile fitting are: 1) virtually any peak shape and angle dependence can normally be described using minimal profile parameters in laboratory and synchrotron X-ray data as well as in CW and TOF neutron data. This is possible because numerical convolution and numerical differentiation is used within the refinement procedure so that a wide range of functions can easily be incorporated into the convolution equation; 2) it can use physically based diffractometer models by convoluting the instrument aberration functions. This can be done for most laboratory based X-ray powder diffractometer configurations including conventional divergent beam instruments, parallel beam instruments, and diffractometers used for asymmetric diffraction. It can also accommodate various optical elements (e.g. multilayers and monochromators) and detector systems (e.g. point and position sensitive detectors) and has already been applied to neutron powder diffraction systems (e.g. ANSTO) as well as synchrotron based

Comparison of dose calculation algorithms in slab phantoms with cortical bone equivalent heterogeneities

International Nuclear Information System (INIS)

Carrasco, P.; Jornet, N.; Duch, M. A.; Panettieri, V.; Weber, L.; Eudaldo, T.; Ginjaume, M.; Ribas, M.

2007-01-01

To evaluate the dose values predicted by several calculation algorithms in two treatment planning systems, Monte Carlo (MC) simulations and measurements by means of various detectors were performed in heterogeneous layer phantoms with water- and bone-equivalent materials. Percentage depth doses (PDDs) were measured with thermoluminescent dosimeters (TLDs), metal-oxide semiconductor field-effect transistors (MOSFETs), plane parallel and cylindrical ionization chambers, and beam profiles with films. The MC code used for the simulations was the PENELOPE code. Three different field sizes (10x10, 5x5, and 2x2 cm 2 ) were studied in two phantom configurations and a bone equivalent material. These two phantom configurations contained heterogeneities of 5 and 2 cm of bone, respectively. We analyzed the performance of four correction-based algorithms and one based on convolution superposition. The correction-based algorithms were the Batho, the Modified Batho, the Equivalent TAR implemented in the Cadplan (Varian) treatment planning system (TPS), and the Helax-TMS Pencil Beam from the Helax-TMS (Nucletron) TPS. The convolution-superposition algorithm was the Collapsed Cone implemented in the Helax-TMS. All the correction-based calculation algorithms underestimated the dose inside the bone-equivalent material for 18 MV compared to MC simulations. The maximum underestimation, in terms of root-mean-square (RMS), was about 15% for the Helax-TMS Pencil Beam (Helax-TMS PB) for a 2x2 cm 2 field inside the bone-equivalent material. In contrast, the Collapsed Cone algorithm yielded values around 3%. A more complex behavior was found for 6 MV where the Collapsed Cone performed less well, overestimating the dose inside the heterogeneity in 3%-5%. The rebuildup in the interface bone-water and the penumbra shrinking in high-density media were not predicted by any of the calculation algorithms except the Collapsed Cone, and only the MC simulations matched the experimental values within

Comparison of dose calculation algorithms in slab phantoms with cortical bone equivalent heterogeneities.

Science.gov (United States)

Carrasco, P; Jornet, N; Duch, M A; Panettieri, V; Weber, L; Eudaldo, T; Ginjaume, M; Ribas, M

2007-08-01

To evaluate the dose values predicted by several calculation algorithms in two treatment planning systems, Monte Carlo (MC) simulations and measurements by means of various detectors were performed in heterogeneous layer phantoms with water- and bone-equivalent materials. Percentage depth doses (PDDs) were measured with thermoluminescent dosimeters (TLDs), metal-oxide semiconductor field-effect transistors (MOSFETs), plane parallel and cylindrical ionization chambers, and beam profiles with films. The MC code used for the simulations was the PENELOPE code. Three different field sizes (10 x 10, 5 x 5, and 2 x 2 cm2) were studied in two phantom configurations and a bone equivalent material. These two phantom configurations contained heterogeneities of 5 and 2 cm of bone, respectively. We analyzed the performance of four correction-based algorithms and one based on convolution superposition. The correction-based algorithms were the Batho, the Modified Batho, the Equivalent TAR implemented in the Cadplan (Varian) treatment planning system (TPS), and the Helax-TMS Pencil Beam from the Helax-TMS (Nucletron) TPS. The convolution-superposition algorithm was the Collapsed Cone implemented in the Helax-TMS. All the correction-based calculation algorithms underestimated the dose inside the bone-equivalent material for 18 MV compared to MC simulations. The maximum underestimation, in terms of root-mean-square (RMS), was about 15% for the Helax-TMS Pencil Beam (Helax-TMS PB) for a 2 x 2 cm2 field inside the bone-equivalent material. In contrast, the Collapsed Cone algorithm yielded values around 3%. A more complex behavior was found for 6 MV where the Collapsed Cone performed less well, overestimating the dose inside the heterogeneity in 3%-5%. The rebuildup in the interface bone-water and the penumbra shrinking in high-density media were not predicted by any of the calculation algorithms except the Collapsed Cone, and only the MC simulations matched the experimental values

Experimental verification of Advanced Collapsed-cone Engine for use with a multichannel vaginal cylinder applicator.

Science.gov (United States)

Cawston-Grant, Brie; Morrison, Hali; Menon, Geetha; Sloboda, Ron S

2017-05-01

Model-based dose calculation algorithms have recently been incorporated into brachytherapy treatment planning systems, and their introduction requires critical evaluation before clinical implementation. Here, we present an experimental evaluation of Oncentra ® Brachy Advanced Collapsed-cone Engine (ACE) for a multichannel vaginal cylinder (MCVC) applicator using radiochromic film. A uniform dose of 500 cGy was specified to the surface of the MCVC using the TG-43 dose formalism under two conditions: (a) with only the central channel loaded or (b) only the peripheral channels loaded. Film measurements were made at the applicator surface and compared to the doses calculated using TG-43, standard accuracy ACE (sACE), and high accuracy ACE (hACE). When the central channel of the applicator was used, the film measurements showed a dose increase of (11 ± 8)% (k = 2) above the two outer grooves on the applicator surface. This increase in dose was confirmed with the hACE calculations, but was not confirmed with the sACE calculations at the applicator surface. When the peripheral channels were used, a periodic azimuthal variation in measured dose was observed around the applicator. The sACE and hACE calculations confirmed this variation and agreed within 1% of each other at the applicator surface. Additionally for the film measurements with the central channel used, a baseline dose variation of (10 ± 4)% (k = 2) of the mean dose was observed azimuthally around the applicator surface, which can be explained by offset source positioning in the central channel. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Dealiased convolutions for pseudospectral simulations

International Nuclear Information System (INIS)

Roberts, Malcolm; Bowman, John C

2011-01-01

Efficient algorithms have recently been developed for calculating dealiased linear convolution sums without the expense of conventional zero-padding or phase-shift techniques. For one-dimensional in-place convolutions, the memory requirements are identical with the zero-padding technique, with the important distinction that the additional work memory need not be contiguous with the input data. This decoupling of data and work arrays dramatically reduces the memory and computation time required to evaluate higher-dimensional in-place convolutions. The memory savings is achieved by computing the in-place Fourier transform of the data in blocks, rather than all at once. The technique also allows one to dealias the n-ary convolutions that arise on Fourier transforming cubic and higher powers. Implicitly dealiased convolutions can be built on top of state-of-the-art adaptive fast Fourier transform libraries like FFTW. Vectorized multidimensional implementations for the complex and centered Hermitian (pseudospectral) cases have already been implemented in the open-source software FFTW++. With the advent of this library, writing a high-performance dealiased pseudospectral code for solving nonlinear partial differential equations has now become a relatively straightforward exercise. New theoretical estimates of computational complexity and memory use are provided, including corrected timing results for 3D pruned convolutions and further consideration of higher-order convolutions.

Convolutional coding techniques for data protection

Science.gov (United States)

Massey, J. L.

1975-01-01

Results of research on the use of convolutional codes in data communications are presented. Convolutional coding fundamentals are discussed along with modulation and coding interaction. Concatenated coding systems and data compression with convolutional codes are described.

Convolution copula econometrics

CERN Document Server

Cherubini, Umberto; Mulinacci, Sabrina

2016-01-01

This book presents a novel approach to time series econometrics, which studies the behavior of nonlinear stochastic processes. This approach allows for an arbitrary dependence structure in the increments and provides a generalization with respect to the standard linear independent increments assumption of classical time series models. The book offers a solution to the problem of a general semiparametric approach, which is given by a concept called C-convolution (convolution of dependent variables), and the corresponding theory of convolution-based copulas. Intended for econometrics and statistics scholars with a special interest in time series analysis and copula functions (or other nonparametric approaches), the book is also useful for doctoral students with a basic knowledge of copula functions wanting to learn about the latest research developments in the field.

Supervised Convolutional Sparse Coding

KAUST Repository

Affara, Lama Ahmed

2018-04-08

Convolutional Sparse Coding (CSC) is a well-established image representation model especially suited for image restoration tasks. In this work, we extend the applicability of this model by proposing a supervised approach to convolutional sparse coding, which aims at learning discriminative dictionaries instead of purely reconstructive ones. We incorporate a supervised regularization term into the traditional unsupervised CSC objective to encourage the final dictionary elements to be discriminative. Experimental results show that using supervised convolutional learning results in two key advantages. First, we learn more semantically relevant filters in the dictionary and second, we achieve improved image reconstruction on unseen data.

Strongly-MDS convolutional codes

NARCIS (Netherlands)

Gluesing-Luerssen, H; Rosenthal, J; Smarandache, R

Maximum-distance separable (MDS) convolutional codes have the property that their free distance is maximal among all codes of the same rate and the same degree. In this paper, a class of MDS convolutional codes is introduced whose column distances reach the generalized Singleton bound at the

Model structure selection in convolutive mixtures

DEFF Research Database (Denmark)

Dyrholm, Mads; Makeig, S.; Hansen, Lars Kai

2006-01-01

The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimonious represent......The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimonious...... representation in many practical mixtures. The new filter-CICAAR allows Bayesian model selection and can help answer questions like: ’Are we actually dealing with a convolutive mixture?’. We try to answer this question for EEG data....

Separating Underdetermined Convolutive Speech Mixtures

DEFF Research Database (Denmark)

Pedersen, Michael Syskind; Wang, DeLiang; Larsen, Jan

2006-01-01

a method for underdetermined blind source separation of convolutive mixtures. The proposed framework is applicable for separation of instantaneous as well as convolutive speech mixtures. It is possible to iteratively extract each speech signal from the mixture by combining blind source separation...

Verification of an algorithm of cono collapsed through the IAEA TECDOC 1583 protocol and dosimetry with radiochromic films

International Nuclear Information System (INIS)

Martin-Viera Cueto, J. A.; Benitez Villegas, E. M.; Bodineau Gil, C.; Parra Osorio, V.; Garcia Pareja, S.; Casado Villalon, F. J.

2013-01-01

The objective of this study is to verify the characterization of the collapsed cone algorithm of an SP using this Protocol. In addition, given that it only offers details of dose values measured at discrete points, measures are complemented by a gamma test distributions 2D of doses in different cases using film radiochromic. (Author)

Convolution of Distribution-Valued Functions. Applications.

OpenAIRE

BARGETZ, CHRISTIAN

2011-01-01

In this article we examine products and convolutions of vector-valued functions. For nuclear normal spaces of distributions Proposition 25 in [31,p. 120] yields a vector-valued product or convolution if there is a continuous product or convolution mapping in the range of the vector-valued functions. For specific spaces, we generalize this result to hypocontinuous bilinear maps at the expense of generality with respect to the function space. We consider holomorphic, meromorphic and differentia...

Feedback equivalence of convolutional codes over finite rings

Directory of Open Access Journals (Sweden)

DeCastro-García Noemí

2017-12-01

Full Text Available The approach to convolutional codes from the linear systems point of view provides us with effective tools in order to construct convolutional codes with adequate properties that let us use them in many applications. In this work, we have generalized feedback equivalence between families of convolutional codes and linear systems over certain rings, and we show that every locally Brunovsky linear system may be considered as a representation of a code under feedback convolutional equivalence.

Efficient convolutional sparse coding

Science.gov (United States)

Wohlberg, Brendt

2017-06-20

Computationally efficient algorithms may be applied for fast dictionary learning solving the convolutional sparse coding problem in the Fourier domain. More specifically, efficient convolutional sparse coding may be derived within an alternating direction method of multipliers (ADMM) framework that utilizes fast Fourier transforms (FFT) to solve the main linear system in the frequency domain. Such algorithms may enable a significant reduction in computational cost over conventional approaches by implementing a linear solver for the most critical and computationally expensive component of the conventional iterative algorithm. The theoretical computational cost of the algorithm may be reduced from O(M.sup.3N) to O(MN log N), where N is the dimensionality of the data and M is the number of elements in the dictionary. This significant improvement in efficiency may greatly increase the range of problems that can practically be addressed via convolutional sparse representations.

Multithreaded implicitly dealiased convolutions

Science.gov (United States)

Roberts, Malcolm; Bowman, John C.

2018-03-01

Implicit dealiasing is a method for computing in-place linear convolutions via fast Fourier transforms that decouples work memory from input data. It offers easier memory management and, for long one-dimensional input sequences, greater efficiency than conventional zero-padding. Furthermore, for convolutions of multidimensional data, the segregation of data and work buffers can be exploited to reduce memory usage and execution time significantly. This is accomplished by processing and discarding data as it is generated, allowing work memory to be reused, for greater data locality and performance. A multithreaded implementation of implicit dealiasing that accepts an arbitrary number of input and output vectors and a general multiplication operator is presented, along with an improved one-dimensional Hermitian convolution that avoids the loop dependency inherent in previous work. An alternate data format that can accommodate a Nyquist mode and enhance cache efficiency is also proposed.

Discrete convolution-operators and radioactive disintegration. [Numerical solution

Energy Technology Data Exchange (ETDEWEB)

Kalla, S L; VALENTINUZZI, M E [UNIVERSIDAD NACIONAL DE TUCUMAN (ARGENTINA). FACULTAD DE CIENCIAS EXACTAS Y TECNOLOGIA

1975-08-01

The basic concepts of discrete convolution and discrete convolution-operators are briefly described. Then, using the discrete convolution - operators, the differential equations associated with the process of radioactive disintegration are numerically solved. The importance of the method is emphasized to solve numerically, differential and integral equations.

Cone Algorithm of Spinning Vehicles under Dynamic Coning Environment

Directory of Open Access Journals (Sweden)

Shuang-biao Zhang

2015-01-01

Full Text Available Due to the fact that attitude error of vehicles has an intense trend of divergence when vehicles undergo worsening coning environment, in this paper, the model of dynamic coning environment is derived firstly. Then, through investigation of the effect on Euler attitude algorithm for the equivalency of traditional attitude algorithm, it is found that attitude error is actually the roll angle error including drifting error and oscillating error, which is induced directly by dynamic coning environment and further affects the pitch angle and yaw angle through transferring. Based on definition of the cone frame and cone attitude, a cone algorithm is proposed by rotation relationship to calculate cone attitude, and the relationship between cone attitude and Euler attitude of spinning vehicle is established. Through numerical simulations with different conditions of dynamic coning environment, it is shown that the induced error of Euler attitude fluctuates by the variation of precession and nutation, especially by that of nutation, and the oscillating frequency of roll angle error is twice that of pitch angle error and yaw angle error. In addition, the rotation angle is more competent to describe the spinning process of vehicles under coning environment than Euler angle gamma, and the real pitch angle and yaw angle are calculated finally.

A convolutional approach to reflection symmetry

DEFF Research Database (Denmark)

Cicconet, Marcelo; Birodkar, Vighnesh; Lund, Mads

2017-01-01

We present a convolutional approach to reflection symmetry detection in 2D. Our model, built on the products of complex-valued wavelet convolutions, simplifies previous edge-based pairwise methods. Being parameter-centered, as opposed to feature-centered, it has certain computational advantages w...

Spherical convolutions and their application in molecular modelling

DEFF Research Database (Denmark)

Boomsma, Wouter; Frellsen, Jes

2017-01-01

Convolutional neural networks are increasingly used outside the domain of image analysis, in particular in various areas of the natural sciences concerned with spatial data. Such networks often work out-of-the box, and in some cases entire model architectures from image analysis can be carried over...... to other problem domains almost unaltered. Unfortunately, this convenience does not trivially extend to data in non-euclidean spaces, such as spherical data. In this paper, we introduce two strategies for conducting convolutions on the sphere, using either a spherical-polar grid or a grid based...... of spherical convolutions in the context of molecular modelling, by considering structural environments within proteins. We show that the models are capable of learning non-trivial functions in these molecular environments, and that our spherical convolutions generally outperform standard 3D convolutions...

Cold knife cone biopsy

Science.gov (United States)

... biopsy; Pap smear - cone biopsy; HPV - cone biopsy; Human papilloma virus - cone biopsy; Cervix - cone biopsy; Colposcopy - cone biopsy Images Female reproductive anatomy Cold cone biopsy Cold cone removal References Baggish ...

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs.

Science.gov (United States)

Chen, Liang-Chieh; Papandreou, George; Kokkinos, Iasonas; Murphy, Kevin; Yuille, Alan L

2018-04-01

In this work we address the task of semantic image segmentation with Deep Learning and make three main contributions that are experimentally shown to have substantial practical merit. First, we highlight convolution with upsampled filters, or 'atrous convolution', as a powerful tool in dense prediction tasks. Atrous convolution allows us to explicitly control the resolution at which feature responses are computed within Deep Convolutional Neural Networks. It also allows us to effectively enlarge the field of view of filters to incorporate larger context without increasing the number of parameters or the amount of computation. Second, we propose atrous spatial pyramid pooling (ASPP) to robustly segment objects at multiple scales. ASPP probes an incoming convolutional feature layer with filters at multiple sampling rates and effective fields-of-views, thus capturing objects as well as image context at multiple scales. Third, we improve the localization of object boundaries by combining methods from DCNNs and probabilistic graphical models. The commonly deployed combination of max-pooling and downsampling in DCNNs achieves invariance but has a toll on localization accuracy. We overcome this by combining the responses at the final DCNN layer with a fully connected Conditional Random Field (CRF), which is shown both qualitatively and quantitatively to improve localization performance. Our proposed "DeepLab" system sets the new state-of-art at the PASCAL VOC-2012 semantic image segmentation task, reaching 79.7 percent mIOU in the test set, and advances the results on three other datasets: PASCAL-Context, PASCAL-Person-Part, and Cityscapes. All of our code is made publicly available online.

Enhanced online convolutional neural networks for object tracking

Science.gov (United States)

Zhang, Dengzhuo; Gao, Yun; Zhou, Hao; Li, Tianwen

2018-04-01

In recent several years, object tracking based on convolution neural network has gained more and more attention. The initialization and update of convolution filters can directly affect the precision of object tracking effective. In this paper, a novel object tracking via an enhanced online convolution neural network without offline training is proposed, which initializes the convolution filters by a k-means++ algorithm and updates the filters by an error back-propagation. The comparative experiments of 7 trackers on 15 challenging sequences showed that our tracker can perform better than other trackers in terms of AUC and precision.

Convolutional Neural Network for Image Recognition

CERN Document Server

Seifnashri, Sahand

2015-01-01

The aim of this project is to use machine learning techniques especially Convolutional Neural Networks for image processing. These techniques can be used for Quark-Gluon discrimination using calorimeters data, but unfortunately I didn’t manage to get the calorimeters data and I just used the Jet data fromminiaodsim(ak4 chs). The Jet data was not good enough for Convolutional Neural Network which is designed for ’image’ recognition. This report is made of twomain part, part one is mainly about implementing Convolutional Neural Network on unphysical data such as MNIST digits and CIFAR-10 dataset and part 2 is about the Jet data.

Comparison of dose calculation algorithms in phantoms with lung equivalent heterogeneities under conditions of lateral electronic disequilibrium

International Nuclear Information System (INIS)

Carrasco, P.; Jornet, N.; Duch, M.A.; Weber, L.; Ginjaume, M.; Eudaldo, T.; Jurado, D.; Ruiz, A.; Ribas, M.

2004-01-01

An extensive set of benchmark measurement of PDDs and beam profiles was performed in a heterogeneous layer phantom, including a lung equivalent heterogeneity, by means of several detectors and compared against the predicted dose values by different calculation algorithms in two treatment planning systems. PDDs were measured with TLDs, plane parallel and cylindrical ionization chambers and beam profiles with films. Additionally, Monte Carlo simulations by meansof the PENELOPE code were performed. Four different field sizes (10x10, 5x5, 2x2, and1x1 cm 2 ) and two lung equivalent materials (CIRS, ρ e w =0.195 and St. Bartholomew Hospital, London, ρ e w =0.244-0.322) were studied. The performance of four correction-based algorithms and one based on convolution-superposition was analyzed. The correction-based algorithms were the Batho, the Modified Batho, and the Equivalent TAR implemented in the Cadplan (Varian) treatment planning system and the TMS Pencil Beam from the Helax-TMS (Nucletron) treatment planning system. The convolution-superposition algorithm was the Collapsed Cone implemented in the Helax-TMS. The only studied calculation methods that correlated successfully with the measured values with a 2% average inside all media were the Collapsed Cone and the Monte Carlo simulation. The biggest difference between the predicted and the delivered dose in the beam axis was found for the EqTAR algorithm inside the CIRS lung equivalent material in a 2x2 cm 2 18 MV x-ray beam. In these conditions, average and maximum difference against the TLD measurements were 32% and 39%, respectively. In the water equivalent part of the phantom every algorithm correctly predicted the dose (within 2%) everywhere except very close to the interfaces where differences up to 24% were found for 2x2 cm 2 18 MV photon beams. Consistent values were found between the reference detector (ionization chamber in water and TLD in lung) and Monte Carlo simulations, yielding minimal differences (0

Symbol synchronization in convolutionally coded systems

Science.gov (United States)

Baumert, L. D.; Mceliece, R. J.; Van Tilborg, H. C. A.

1979-01-01

Alternate symbol inversion is sometimes applied to the output of convolutional encoders to guarantee sufficient richness of symbol transition for the receiver symbol synchronizer. A bound is given for the length of the transition-free symbol stream in such systems, and those convolutional codes are characterized in which arbitrarily long transition free runs occur.

FPGA-based digital convolution for wireless applications

CERN Document Server

Guan, Lei

2017-01-01

This book presents essential perspectives on digital convolutions in wireless communications systems and illustrates their corresponding efficient real-time field-programmable gate array (FPGA) implementations. Covering these digital convolutions from basic concept to vivid simulation/illustration, the book is also supplemented with MS PowerPoint presentations to aid in comprehension. FPGAs or generic all programmable devices will soon become widespread, serving as the “brains” of all types of real-time smart signal processing systems, like smart networks, smart homes and smart cities. The book examines digital convolution by bringing together the following main elements: the fundamental theory behind the mathematical formulae together with corresponding physical phenomena; virtualized algorithm simulation together with benchmark real-time FPGA implementations; and detailed, state-of-the-art case studies on wireless applications, including popular linear convolution in digital front ends (DFEs); nonlinear...

Incomplete convolutions in production and inventory models

NARCIS (Netherlands)

Houtum, van G.J.J.A.N.; Zijm, W.H.M.

1997-01-01

In this paper, we study incomplete convolutions of continuous distribution functions, as they appear in the analysis of (multi-stage) production and inventory systems. Three example systems are discussed where these incomplete convolutions naturally arise. We derive explicit, nonrecursive formulae

The Urbanik generalized convolutions in the non-commutative ...

Indian Academy of Sciences (India)

−sν(dx) < ∞. Now we apply this construction to the Kendall convolution case, starting with the weakly stable measure δ1. Example 1. Let △ be the Kendall convolution, i.e. the generalized convolution with the probability kernel: δ1△δa = (1 − a)δ1 + aπ2 for a ∈ [0, 1] and π2 be the Pareto distribution with the density π2(dx) =.

An Algorithm for the Convolution of Legendre Series

KAUST Repository

Hale, Nicholas; Townsend, Alex

2014-01-01

An O(N2) algorithm for the convolution of compactly supported Legendre series is described. The algorithm is derived from the convolution theorem for Legendre polynomials and the recurrence relation satisfied by spherical Bessel functions. Combining with previous work yields an O(N 2) algorithm for the convolution of Chebyshev series. Numerical results are presented to demonstrate the improved efficiency over the existing algorithm. © 2014 Society for Industrial and Applied Mathematics.

A Note on Cubic Convolution Interpolation

OpenAIRE

Meijering, E.; Unser, M.

2003-01-01

We establish a link between classical osculatory interpolation and modern convolution-based interpolation and use it to show that two well-known cubic convolution schemes are formally equivalent to two osculatory interpolation schemes proposed in the actuarial literature about a century ago. We also discuss computational differences and give examples of other cubic interpolation schemes not previously studied in signal and image processing.

The general theory of convolutional codes

Science.gov (United States)

Mceliece, R. J.; Stanley, R. P.

1993-01-01

This article presents a self-contained introduction to the algebraic theory of convolutional codes. This introduction is partly a tutorial, but at the same time contains a number of new results which will prove useful for designers of advanced telecommunication systems. Among the new concepts introduced here are the Hilbert series for a convolutional code and the class of compact codes.

Basic processes and factors determining the evolution of collapse sinkholes: a sensitivity study

Science.gov (United States)

Romanov, Douchko; Kaufmann, Georg

2017-04-01

Collapse sinkholes appear as closed depressions at the surface. The origin of these karst features is related to the continuous dissolution of the soluble rock caused by a focussed sub-surface flow. Water flowing along a preferential pathway through fissures and fractures within the phreatic part of a karst aquifer is able to dissolve the rock (limestone, gypsum, anhydrite). With time, the dissolved void volume increases and part of the ceiling above the stream can become unstable, collapses, and accumulates as debris in the flow path. The debris partially blocks the flow and thus activates new pathways. Because of the low compaction of the debris (high hydraulic conductivity), the flow and the dissolution rates within this crushed zone remain high. This allows a relatively fast dissolutional and erosional removal of the crushed material and the development of new empty voids. The void volume expands upwards towards the surface until a collapse sinkhole is formed. The collapse sinkholes exhibit a large variety of shapes (cylindrical, cone-, bowl-shaped), depths (from few to few hundred meters) and diameters (meters up to hundreds of meters). Two major processes are responsible for this diversity: a) the karst evolution of the aquifer - responsible for the dissolutional and erosional removal of material; b) the mechanical evolution of the host rock and the existence of structural features, faults for example, which determine the stability and the magnitude of the subsequent collapses. In this work we demonstrate the influence of the host rock type, the hydrological and geological boundary conditions, the chemical composition of the flowing water, and the geometry and the scale of the crushed zone, on the location and the evolution of the growing sinkhole. We demonstrate the ability of the karst evolution models to explain, at least qualitatively, the growth and the morphology of the collapse sinkholes and to roughly predict their shape and location. Implementing

One weird trick for parallelizing convolutional neural networks

OpenAIRE

Krizhevsky, Alex

2014-01-01

I present a new way to parallelize the training of convolutional neural networks across multiple GPUs. The method scales significantly better than all alternatives when applied to modern convolutional neural networks.

CT of lobar collapse

International Nuclear Information System (INIS)

Suh, D. C.; Im, J. G.; Park, J. H.; Han, M. C.

1987-01-01

The computed tomographic (CT) findings of labor collapse are analysed in an attempt to evaluate the patterns of labor collapse and to get the helpful signs in differentiation between benign and malignant causes of collapse. 43 cases of labor collapse with or without endobronchial obstruction were reviewed. In 29 of 43 cases the collapses were caused by lung cancer. Benign causes of labor collapse included tuberculosis(10), broncholith(2), organizing pneumonia(1) and hamartoma(1). The helpful signs favoring malignant cause of the labor collapse were proximal bulging of the collapsed lobe, low density mass within the collapsed lung, and endobronchial lesion. Above described differential findings were especially applicable in cases of upper lobe collapse

The collapsed cone algorithm for (192)Ir dosimetry using phantom-size adaptive multiple-scatter point kernels.

Science.gov (United States)

Tedgren, Åsa Carlsson; Plamondon, Mathieu; Beaulieu, Luc

2015-07-07

The aim of this work was to investigate how dose distributions calculated with the collapsed cone (CC) algorithm depend on the size of the water phantom used in deriving the point kernel for multiple scatter. A research version of the CC algorithm equipped with a set of selectable point kernels for multiple-scatter dose that had initially been derived in water phantoms of various dimensions was used. The new point kernels were generated using EGSnrc in spherical water phantoms of radii 5 cm, 7.5 cm, 10 cm, 15 cm, 20 cm, 30 cm and 50 cm. Dose distributions derived with CC in water phantoms of different dimensions and in a CT-based clinical breast geometry were compared to Monte Carlo (MC) simulations using the Geant4-based brachytherapy specific MC code Algebra. Agreement with MC within 1% was obtained when the dimensions of the phantom used to derive the multiple-scatter kernel were similar to those of the calculation phantom. Doses are overestimated at phantom edges when kernels are derived in larger phantoms and underestimated when derived in smaller phantoms (by around 2% to 7% depending on distance from source and phantom dimensions). CC agrees well with MC in the high dose region of a breast implant and is superior to TG43 in determining skin doses for all multiple-scatter point kernel sizes. Increased agreement between CC and MC is achieved when the point kernel is comparable to breast dimensions. The investigated approximation in multiple scatter dose depends on the choice of point kernel in relation to phantom size and yields a significant fraction of the total dose only at distances of several centimeters from a source/implant which correspond to volumes of low doses. The current implementation of the CC algorithm utilizes a point kernel derived in a comparatively large (radius 20 cm) water phantom. A fixed point kernel leads to predictable behaviour of the algorithm with the worst case being a source/implant located well within a patient

Deep multi-scale convolutional neural network for hyperspectral image classification

Science.gov (United States)

Zhang, Feng-zhe; Yang, Xia

2018-04-01

In this paper, we proposed a multi-scale convolutional neural network for hyperspectral image classification task. Firstly, compared with conventional convolution, we utilize multi-scale convolutions, which possess larger respective fields, to extract spectral features of hyperspectral image. We design a deep neural network with a multi-scale convolution layer which contains 3 different convolution kernel sizes. Secondly, to avoid overfitting of deep neural network, dropout is utilized, which randomly sleeps neurons, contributing to improve the classification accuracy a bit. In addition, new skills like ReLU in deep learning is utilized in this paper. We conduct experiments on University of Pavia and Salinas datasets, and obtained better classification accuracy compared with other methods.

Radial Structure Scaffolds Convolution Patterns of Developing Cerebral Cortex

Directory of Open Access Journals (Sweden)

Mir Jalil Razavi

2017-08-01

Full Text Available Commonly-preserved radial convolution is a prominent characteristic of the mammalian cerebral cortex. Endeavors from multiple disciplines have been devoted for decades to explore the causes for this enigmatic structure. However, the underlying mechanisms that lead to consistent cortical convolution patterns still remain poorly understood. In this work, inspired by prior studies, we propose and evaluate a plausible theory that radial convolution during the early development of the brain is sculptured by radial structures consisting of radial glial cells (RGCs and maturing axons. Specifically, the regionally heterogeneous development and distribution of RGCs controlled by Trnp1 regulate the convex and concave convolution patterns (gyri and sulci in the radial direction, while the interplay of RGCs' effects on convolution and axons regulates the convex (gyral convolution patterns. This theory is assessed by observations and measurements in literature from multiple disciplines such as neurobiology, genetics, biomechanics, etc., at multiple scales to date. Particularly, this theory is further validated by multimodal imaging data analysis and computational simulations in this study. We offer a versatile and descriptive study model that can provide reasonable explanations of observations, experiments, and simulations of the characteristic mammalian cortical folding.

Design of convolutional tornado code

Science.gov (United States)

Zhou, Hui; Yang, Yao; Gao, Hongmin; Tan, Lu

2017-09-01

As a linear block code, the traditional tornado (tTN) code is inefficient in burst-erasure environment and its multi-level structure may lead to high encoding/decoding complexity. This paper presents a convolutional tornado (cTN) code which is able to improve the burst-erasure protection capability by applying the convolution property to the tTN code, and reduce computational complexity by abrogating the multi-level structure. The simulation results show that cTN code can provide a better packet loss protection performance with lower computation complexity than tTN code.

An Implementation of Error Minimization Data Transmission in OFDM using Modified Convolutional Code

Directory of Open Access Journals (Sweden)

Hendy Briantoro

2016-04-01

Full Text Available This paper presents about error minimization in OFDM system. In conventional system, usually using channel coding such as BCH Code or Convolutional Code. But, performance BCH Code or Convolutional Code is not good in implementation of OFDM System. Error bits of OFDM system without channel coding is 5.77%. Then, we used convolutional code with code rate 1/2, it can reduce error bitsonly up to 3.85%. So, we proposed OFDM system with Modified Convolutional Code. In this implementation, we used Software Define Radio (SDR, namely Universal Software Radio Peripheral (USRP NI 2920 as the transmitter and receiver. The result of OFDM system using Modified Convolutional Code with code rate is able recover all character received so can decrease until 0% error bit. Increasing performance of Modified Convolutional Code is about 1 dB in BER of 10-4 from BCH Code and Convolutional Code. So, performance of Modified Convolutional better than BCH Code or Convolutional Code. Keywords: OFDM, BCH Code, Convolutional Code, Modified Convolutional Code, SDR, USRP

Dimensional Changes of Fresh Sockets With Reactive Soft Tissue Preservation: A Cone Beam CT Study.

Science.gov (United States)

Crespi, Roberto; Capparé, Paolo; Crespi, Giovanni; Gastaldi, Giorgio; Gherlone, Enrico Felice

2017-06-01

The aim of this study was to assess dimensional changes of the fresh sockets grafted with collagen sheets and maintenance of reactive soft tissue, using cone beam computed tomography (CBCT). Tooth extractions were performed with maximum preservation of the alveolar housing, reactive soft tissue was left into the sockets and collagen sheets filled bone defects. Cone beam computed tomography were performed before and 3 months after extractions. One hundred forty-five teeth, 60 monoradiculars and 85 molars, were extracted. In total, 269 alveoli were evaluated. In Group A, not statistically significant differences were found between monoradiculars, whereas statistically significant differences (P 0.05) for all types of teeth. This study reported an atraumatic tooth extraction, reactive soft tissue left in situ, and grafted collagen sponge may be helpful to reduce fresh socket collapse after extraction procedures.

Semantic segmentation of bioimages using convolutional neural networks

CSIR Research Space (South Africa)

Wiehman, S

2016-07-01

Full Text Available Convolutional neural networks have shown great promise in both general image segmentation problems as well as bioimage segmentation. In this paper, the application of different convolutional network architectures is explored on the C. elegans live...

Accurate convolution/superposition for multi-resolution dose calculation using cumulative tabulated kernels

International Nuclear Information System (INIS)

Lu Weiguo; Olivera, Gustavo H; Chen Mingli; Reckwerdt, Paul J; Mackie, Thomas R

2005-01-01

Convolution/superposition (C/S) is regarded as the standard dose calculation method in most modern radiotherapy treatment planning systems. Different implementations of C/S could result in significantly different dose distributions. This paper addresses two major implementation issues associated with collapsed cone C/S: one is how to utilize the tabulated kernels instead of analytical parametrizations and the other is how to deal with voxel size effects. Three methods that utilize the tabulated kernels are presented in this paper. These methods differ in the effective kernels used: the differential kernel (DK), the cumulative kernel (CK) or the cumulative-cumulative kernel (CCK). They result in slightly different computation times but significantly different voxel size effects. Both simulated and real multi-resolution dose calculations are presented. For simulation tests, we use arbitrary kernels and various voxel sizes with a homogeneous phantom, and assume forward energy transportation only. Simulations with voxel size up to 1 cm show that the CCK algorithm has errors within 0.1% of the maximum gold standard dose. Real dose calculations use a heterogeneous slab phantom, both the 'broad' (5 x 5 cm 2 ) and the 'narrow' (1.2 x 1.2 cm 2 ) tomotherapy beams. Various voxel sizes (0.5 mm, 1 mm, 2 mm, 4 mm and 8 mm) are used for dose calculations. The results show that all three algorithms have negligible difference (0.1%) for the dose calculation in the fine resolution (0.5 mm voxels). But differences become significant when the voxel size increases. As for the DK or CK algorithm in the broad (narrow) beam dose calculation, the dose differences between the 0.5 mm voxels and the voxels up to 8 mm (4 mm) are around 10% (7%) of the maximum dose. As for the broad (narrow) beam dose calculation using the CCK algorithm, the dose differences between the 0.5 mm voxels and the voxels up to 8 mm (4 mm) are around 1% of the maximum dose. Among all three methods, the CCK algorithm

Face recognition: a convolutional neural-network approach.

Science.gov (United States)

Lawrence, S; Giles, C L; Tsoi, A C; Back, A D

1997-01-01

We present a hybrid neural-network for human face recognition which compares favourably with other methods. The system combines local image sampling, a self-organizing map (SOM) neural network, and a convolutional neural network. The SOM provides a quantization of the image samples into a topological space where inputs that are nearby in the original space are also nearby in the output space, thereby providing dimensionality reduction and invariance to minor changes in the image sample, and the convolutional neural network provides partial invariance to translation, rotation, scale, and deformation. The convolutional network extracts successively larger features in a hierarchical set of layers. We present results using the Karhunen-Loeve transform in place of the SOM, and a multilayer perceptron (MLP) in place of the convolutional network for comparison. We use a database of 400 images of 40 individuals which contains quite a high degree of variability in expression, pose, and facial details. We analyze the computational complexity and discuss how new classes could be added to the trained recognizer.

Nuclear norm regularized convolutional Max Pos@Top machine

KAUST Repository

Li, Qinfeng; Zhou, Xiaofeng; Gu, Aihua; Li, Zonghua; Liang, Ru-Ze

2016-01-01

, named as Pos@Top. Our proposed classification model has a convolutional structure that is composed by four layers, i.e., the convolutional layer, the activation layer, the max-pooling layer and the full connection layer. In this paper, we propose

Computational models of stellar collapse and core-collapse supernovae

International Nuclear Information System (INIS)

Ott, Christian D; O'Connor, Evan; Schnetter, Erik; Loeffler, Frank; Burrows, Adam; Livne, Eli

2009-01-01

Core-collapse supernovae are among Nature's most energetic events. They mark the end of massive star evolution and pollute the interstellar medium with the life-enabling ashes of thermonuclear burning. Despite their importance for the evolution of galaxies and life in the universe, the details of the core-collapse supernova explosion mechanism remain in the dark and pose a daunting computational challenge. We outline the multi-dimensional, multi-scale, and multi-physics nature of the core-collapse supernova problem and discuss computational strategies and requirements for its solution. Specifically, we highlight the axisymmetric (2D) radiation-MHD code VULCAN/2D and present results obtained from the first full-2D angle-dependent neutrino radiation-hydrodynamics simulations of the post-core-bounce supernova evolution. We then go on to discuss the new code Zelmani which is based on the open-source HPC Cactus framework and provides a scalable AMR approach for 3D fully general-relativistic modeling of stellar collapse, core-collapse supernovae and black hole formation on current and future massively-parallel HPC systems. We show Zelmani's scaling properties to more than 16,000 compute cores and discuss first 3D general-relativistic core-collapse results.

An Automated Strategy for Unbiased Morphometric Analyses and Classifications of Growth Cones In Vitro.

Science.gov (United States)

Chitsaz, Daryan; Morales, Daniel; Law, Chris; Kania, Artur

2015-01-01

During neural circuit development, attractive or repulsive guidance cue molecules direct growth cones (GCs) to their targets by eliciting cytoskeletal remodeling, which is reflected in their morphology. The experimental power of in vitro neuronal cultures to assay this process and its molecular mechanisms is well established, however, a method to rapidly find and quantify multiple morphological aspects of GCs is lacking. To this end, we have developed a free, easy to use, and fully automated Fiji macro, Conographer, which accurately identifies and measures many morphological parameters of GCs in 2D explant culture images. These measurements are then subjected to principle component analysis and k-means clustering to mathematically classify the GCs as "collapsed" or "extended". The morphological parameters measured for each GC are found to be significantly different between collapsed and extended GCs, and are sufficient to classify GCs as such with the same level of accuracy as human observers. Application of a known collapse-inducing ligand results in significant changes in all parameters, resulting in an increase in 'collapsed' GCs determined by k-means clustering, as expected. Our strategy provides a powerful tool for exploring the relationship between GC morphology and guidance cue signaling, which in particular will greatly facilitate high-throughput studies of the effects of drugs, gene silencing or overexpression, or any other experimental manipulation in the context of an in vitro axon guidance assay.

Geomorphometric variability of "monogenetic" volcanic cones: Evidence from Mauna Kea, Lanzarote and experimental cones

Science.gov (United States)

Kervyn, M.; Ernst, G. G. J.; Carracedo, J.-C.; Jacobs, P.

2012-01-01

Volcanic cones are the most common volcanic constructs on Earth. Their shape can be quantified using two morphometric ratios: the crater/cone base ratio (W cr/W co) and the cone height/width ratio (H co/W co). The average values for these ratios obtained over entire cone fields have been explained by the repose angle of loose granular material (i.e. scoria) controlling cone slopes. The observed variability in these ratios between individual cones has been attributed to the effect of erosional processes or contrasting eruptive conditions on cone morphometry. Using a GIS-based approach, high spatial resolution Digital Elevation Models and airphotos, two new geomorphometry datasets for cone fields at Mauna Kea (Hawaii, USA) and Lanzarote (Canary Islands, Spain) are extracted and analyzed here. The key observation in these datasets is the great variability in morphometric ratios, even for simple-shape and well-preserved cones. Simple analog experiments are presented to analyze factors influencing the morphometric ratios. The formation of a crater is simulated within an analog cone (i.e. a sand pile) by opening a drainage conduit at the cone base. Results from experiments show that variability in the morphometric ratios can be attributed to variations in the width, height and horizontal offset of the drainage point relative to the cone symmetry axis, to the dip of the underlying slope or to the influence of a small proportion of fine cohesive material. GIS analysis and analog experiments, together with specific examples of cones documented in the field, suggest that the morphometric ratios for well-preserved volcanic cones are controlled by a combination of 1) the intrinsic cone material properties, 2) time-dependent eruption conditions, 3) the local setting, and 4) the method used to estimate the cone height. Implications for interpreting cone morphometry solely as either an age or as an eruption condition indicator are highlighted.

Foveal cone spacing and cone photopigment density difference: objective measurements in the same subjects.

Science.gov (United States)

Marcos, S; Tornow, R P; Elsner, A E; Navarro, R

1997-07-01

Foveal cone spacing was measured in vivo using an objective technique: ocular speckle interferometry. Cone packing density was computed from cone spacing data. Foveal cone photopigment density difference was measured in the same subjects using retinal densitometry with a scanning laser ophthalmoscope. Both the cone packing density and cone photopigment density difference decreased sharply with increasing retinal eccentricity. From the comparison of both sets of measurements, the computed amounts of photopigment per cone increased slightly with increasing retinal eccentricity. Consistent with previous results, decreases in cone outer segment length are over-compensated by an increase in the outer segment area, at least in retinal eccentricities up to 1 deg.

Convolutive ICA for Spatio-Temporal Analysis of EEG

DEFF Research Database (Denmark)

Dyrholm, Mads; Makeig, Scott; Hansen, Lars Kai

2007-01-01

in the convolutive model can be correctly detected using Bayesian model selection. We demonstrate a framework for deconvolving an EEG ICA subspace. Initial results suggest that in some cases convolutive mixing may be a more realistic model for EEG signals than the instantaneous ICA model....

Computational models of stellar collapse and core-collapse supernovae

Energy Technology Data Exchange (ETDEWEB)

Ott, Christian D; O' Connor, Evan [TAPIR, Mailcode 350-17, California Institute of Technology, Pasadena, CA (United States); Schnetter, Erik; Loeffler, Frank [Center for Computation and Technology, Louisiana State University, Baton Rouge, LA (United States); Burrows, Adam [Department of Astrophysical Sciences, Princeton University, Princeton, NJ (United States); Livne, Eli, E-mail: cott@tapir.caltech.ed [Racah Institute of Physics, Hebrew University, Jerusalem (Israel)

2009-07-01

Core-collapse supernovae are among Nature's most energetic events. They mark the end of massive star evolution and pollute the interstellar medium with the life-enabling ashes of thermonuclear burning. Despite their importance for the evolution of galaxies and life in the universe, the details of the core-collapse supernova explosion mechanism remain in the dark and pose a daunting computational challenge. We outline the multi-dimensional, multi-scale, and multi-physics nature of the core-collapse supernova problem and discuss computational strategies and requirements for its solution. Specifically, we highlight the axisymmetric (2D) radiation-MHD code VULCAN/2D and present results obtained from the first full-2D angle-dependent neutrino radiation-hydrodynamics simulations of the post-core-bounce supernova evolution. We then go on to discuss the new code Zelmani which is based on the open-source HPC Cactus framework and provides a scalable AMR approach for 3D fully general-relativistic modeling of stellar collapse, core-collapse supernovae and black hole formation on current and future massively-parallel HPC systems. We show Zelmani's scaling properties to more than 16,000 compute cores and discuss first 3D general-relativistic core-collapse results.

CMOS Compressed Imaging by Random Convolution

OpenAIRE

Jacques, Laurent; Vandergheynst, Pierre; Bibet, Alexandre; Majidzadeh, Vahid; Schmid, Alexandre; Leblebici, Yusuf

2009-01-01

We present a CMOS imager with built-in capability to perform Compressed Sensing. The adopted sensing strategy is the random Convolution due to J. Romberg. It is achieved by a shift register set in a pseudo-random configuration. It acts as a convolutive filter on the imager focal plane, the current issued from each CMOS pixel undergoing a pseudo-random redirection controlled by each component of the filter sequence. A pseudo-random triggering of the ADC reading is finally applied to comp...

Towards dropout training for convolutional neural networks.

Science.gov (United States)

Wu, Haibing; Gu, Xiaodong

2015-11-01

Recently, dropout has seen increasing use in deep learning. For deep convolutional neural networks, dropout is known to work well in fully-connected layers. However, its effect in convolutional and pooling layers is still not clear. This paper demonstrates that max-pooling dropout is equivalent to randomly picking activation based on a multinomial distribution at training time. In light of this insight, we advocate employing our proposed probabilistic weighted pooling, instead of commonly used max-pooling, to act as model averaging at test time. Empirical evidence validates the superiority of probabilistic weighted pooling. We also empirically show that the effect of convolutional dropout is not trivial, despite the dramatically reduced possibility of over-fitting due to the convolutional architecture. Elaborately designing dropout training simultaneously in max-pooling and fully-connected layers, we achieve state-of-the-art performance on MNIST, and very competitive results on CIFAR-10 and CIFAR-100, relative to other approaches without data augmentation. Finally, we compare max-pooling dropout and stochastic pooling, both of which introduce stochasticity based on multinomial distributions at pooling stage. Copyright © 2015 Elsevier Ltd. All rights reserved.

Quotient normed cones

Indian Academy of Sciences (India)

general setting of the space CL(X, Y ) of all continuous linear mappings from a normed cone (X, p) to a normed cone (Y, q), extending several well-known results related to open continuous linear mappings between normed linear spaces. Keywords. Normed cone; extended quasi-metric; continuous linear mapping; bicom-.

Review of collapse triggering mechanism of collapsible soils due to wetting

Directory of Open Access Journals (Sweden)

Ping Li

2016-04-01

Full Text Available Loess soil deposits are widely distributed in arid and semi-arid regions and constitute about 10% of land area of the world. These soils typically have a loose honeycomb-type meta-stable structure that is susceptible to a large reduction in total volume or collapse upon wetting. Collapse characteristics contribute to various problems to infrastructures that are constructed on loess soils. For this reason, collapse triggering mechanism for loess soils has been of significant interest for researchers and practitioners all over the world. This paper aims at providing a state-of-the-art review on collapse mechanism with special reference to loess soil deposits. The collapse mechanism studies are summarized under three different categories, i.e. traditional approaches, microstructure approach, and soil mechanics-based approaches. The traditional and microstructure approaches for interpreting the collapse behavior are comprehensively summarized and critically reviewed based on the experimental results from the literature. The soil mechanics-based approaches proposed based on the experimental results of both compacted soils and natural loess soils are reviewed highlighting their strengths and limitations for estimating the collapse behavior. Simpler soil mechanics-based approaches with less parameters or parameters that are easy-to-determine from conventional tests are suggested for future research to better understand the collapse behavior of natural loess soils. Such studies would be more valuable for use in conventional geotechnical engineering practice applications.

Types of collapse calderas

Energy Technology Data Exchange (ETDEWEB)

Aguirre-Diaz, Gerardo J [Centro de Geociencias, Universidad Nacional Autonoma de Mexico, Campus Juriquilla, Queretaro, Qro., 76230 (Mexico)], E-mail: ger@geociencias.unam.mx

2008-10-01

Three main types of collapse calderas can be defined, 1) summit caldera: those formed at the top of large volcanoes, 2) classic caldera: semi-circular to irregular-shaped large structures, several km in diameter and related to relatively large-volume pyroclastic products, and 3) graben caldera: explosive volcano-tectonic collapse structures from which large-volume, ignimbrite-forming eruptions occurred through several fissural vents along the graben master faults and the intra-graben block faults. These in turn can collapse at least with three styles: 1) Piston: when the collapse occurs as a single crustal block; 2) Trap-door: when collapse occurs unevenly along one side while the opposite side remains with no collapse; 3) Piece-meal: when collapse occurs as broken pieces of the crust on top of the magma chamber.

Gradient Flow Convolutive Blind Source Separation

DEFF Research Database (Denmark)

Pedersen, Michael Syskind; Nielsen, Chinton Møller

2004-01-01

Experiments have shown that the performance of instantaneous gradient flow beamforming by Cauwenberghs et al. is reduced significantly in reverberant conditions. By expanding the gradient flow principle to convolutive mixtures, separation in a reverberant environment is possible. By use...... of a circular four microphone array with a radius of 5 mm, and applying convolutive gradient flow instead of just applying instantaneous gradient flow, experimental results show an improvement of up to around 14 dB can be achieved for simulated impulse responses and up to around 10 dB for a hearing aid...

An Improved Convolutional Neural Network on Crowd Density Estimation

Directory of Open Access Journals (Sweden)

Pan Shao-Yun

2016-01-01

Full Text Available In this paper, a new method is proposed for crowd density estimation. An improved convolutional neural network is combined with traditional texture feature. The data calculated by the convolutional layer can be treated as a new kind of features.So more useful information of images can be extracted by different features.In the meantime, the size of image has little effect on the result of convolutional neural network. Experimental results indicate that our scheme has adequate performance to allow for its use in real world applications.

On the Reduction of Computational Complexity of Deep Convolutional Neural Networks

Directory of Open Access Journals (Sweden)

Partha Maji

2018-04-01

Full Text Available Deep convolutional neural networks (ConvNets, which are at the heart of many new emerging applications, achieve remarkable performance in audio and visual recognition tasks. Unfortunately, achieving accuracy often implies significant computational costs, limiting deployability. In modern ConvNets it is typical for the convolution layers to consume the vast majority of computational resources during inference. This has made the acceleration of these layers an important research area in academia and industry. In this paper, we examine the effects of co-optimizing the internal structures of the convolutional layers and underlying implementation of fundamental convolution operation. We demonstrate that a combination of these methods can have a big impact on the overall speedup of a ConvNet, achieving a ten-fold increase over baseline. We also introduce a new class of fast one-dimensional (1D convolutions for ConvNets using the Toom–Cook algorithm. We show that our proposed scheme is mathematically well-grounded, robust, and does not require any time-consuming retraining, while still achieving speedups solely from convolutional layers with no loss in baseline accuracy.

An Automated Strategy for Unbiased Morphometric Analyses and Classifications of Growth Cones In Vitro.

Directory of Open Access Journals (Sweden)

Daryan Chitsaz

Full Text Available During neural circuit development, attractive or repulsive guidance cue molecules direct growth cones (GCs to their targets by eliciting cytoskeletal remodeling, which is reflected in their morphology. The experimental power of in vitro neuronal cultures to assay this process and its molecular mechanisms is well established, however, a method to rapidly find and quantify multiple morphological aspects of GCs is lacking. To this end, we have developed a free, easy to use, and fully automated Fiji macro, Conographer, which accurately identifies and measures many morphological parameters of GCs in 2D explant culture images. These measurements are then subjected to principle component analysis and k-means clustering to mathematically classify the GCs as "collapsed" or "extended". The morphological parameters measured for each GC are found to be significantly different between collapsed and extended GCs, and are sufficient to classify GCs as such with the same level of accuracy as human observers. Application of a known collapse-inducing ligand results in significant changes in all parameters, resulting in an increase in 'collapsed' GCs determined by k-means clustering, as expected. Our strategy provides a powerful tool for exploring the relationship between GC morphology and guidance cue signaling, which in particular will greatly facilitate high-throughput studies of the effects of drugs, gene silencing or overexpression, or any other experimental manipulation in the context of an in vitro axon guidance assay.

Berkeley Lighting Cone

Energy Technology Data Exchange (ETDEWEB)

Lask, Kathleen [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Gadgil, Ashok [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2016-10-24

A lighting cone is a simple metal cone placed on the fuel bed of a stove during ignition to act as a chimney, increasing the draft through the fuel bed. Many stoves tend to be difficult to light due to poor draft through the fuel bed, so lighting cones are used in various parts of the world as an inexpensive accessory to help with ignition.

Detecting atrial fibrillation by deep convolutional neural networks.

Science.gov (United States)

Xia, Yong; Wulan, Naren; Wang, Kuanquan; Zhang, Henggui

2018-02-01

Atrial fibrillation (AF) is the most common cardiac arrhythmia. The incidence of AF increases with age, causing high risks of stroke and increased morbidity and mortality. Efficient and accurate diagnosis of AF based on the ECG is valuable in clinical settings and remains challenging. In this paper, we proposed a novel method with high reliability and accuracy for AF detection via deep learning. The short-term Fourier transform (STFT) and stationary wavelet transform (SWT) were used to analyze ECG segments to obtain two-dimensional (2-D) matrix input suitable for deep convolutional neural networks. Then, two different deep convolutional neural network models corresponding to STFT output and SWT output were developed. Our new method did not require detection of P or R peaks, nor feature designs for classification, in contrast to existing algorithms. Finally, the performances of the two models were evaluated and compared with those of existing algorithms. Our proposed method demonstrated favorable performances on ECG segments as short as 5 s. The deep convolutional neural network using input generated by STFT, presented a sensitivity of 98.34%, specificity of 98.24% and accuracy of 98.29%. For the deep convolutional neural network using input generated by SWT, a sensitivity of 98.79%, specificity of 97.87% and accuracy of 98.63% was achieved. The proposed method using deep convolutional neural networks shows high sensitivity, specificity and accuracy, and, therefore, is a valuable tool for AF detection. Copyright © 2017 Elsevier Ltd. All rights reserved.

Video Super-Resolution via Bidirectional Recurrent Convolutional Networks.

Science.gov (United States)

Huang, Yan; Wang, Wei; Wang, Liang

2018-04-01

Super resolving a low-resolution video, namely video super-resolution (SR), is usually handled by either single-image SR or multi-frame SR. Single-Image SR deals with each video frame independently, and ignores intrinsic temporal dependency of video frames which actually plays a very important role in video SR. Multi-Frame SR generally extracts motion information, e.g., optical flow, to model the temporal dependency, but often shows high computational cost. Considering that recurrent neural networks (RNNs) can model long-term temporal dependency of video sequences well, we propose a fully convolutional RNN named bidirectional recurrent convolutional network for efficient multi-frame SR. Different from vanilla RNNs, 1) the commonly-used full feedforward and recurrent connections are replaced with weight-sharing convolutional connections. So they can greatly reduce the large number of network parameters and well model the temporal dependency in a finer level, i.e., patch-based rather than frame-based, and 2) connections from input layers at previous timesteps to the current hidden layer are added by 3D feedforward convolutions, which aim to capture discriminate spatio-temporal patterns for short-term fast-varying motions in local adjacent frames. Due to the cheap convolutional operations, our model has a low computational complexity and runs orders of magnitude faster than other multi-frame SR methods. With the powerful temporal dependency modeling, our model can super resolve videos with complex motions and achieve well performance.

On the Fresnel sine integral and the convolution

Directory of Open Access Journals (Sweden)

Adem Kılıçman

2003-01-01

Full Text Available The Fresnel sine integral S(x, the Fresnel cosine integral C(x, and the associated functions S+(x, S−(x, C+(x, and C−(x are defined as locally summable functions on the real line. Some convolutions and neutrix convolutions of the Fresnel sine integral and its associated functions with x+r, xr are evaluated.

Progress in light cone physics

International Nuclear Information System (INIS)

Preparata, G.

1973-01-01

A very brief review is given of the progress made in the physics of the light cone in the past year. Included are the light cone expansion, gauge invariance and the consequences of precocious scaling near threshold, the light cone description of the muon pair experiment, light cone expansions, and the assessment and exploitation of analyticity properties in both mass and energy of light cone amplitudes. (U.S.)

Classification of urine sediment based on convolution neural network

Science.gov (United States)

Pan, Jingjing; Jiang, Cunbo; Zhu, Tiantian

2018-04-01

By designing a new convolution neural network framework, this paper breaks the constraints of the original convolution neural network framework requiring large training samples and samples of the same size. Move and cropping the input images, generate the same size of the sub-graph. And then, the generated sub-graph uses the method of dropout, increasing the diversity of samples and preventing the fitting generation. Randomly select some proper subset in the sub-graphic set and ensure that the number of elements in the proper subset is same and the proper subset is not the same. The proper subsets are used as input layers for the convolution neural network. Through the convolution layer, the pooling, the full connection layer and output layer, we can obtained the classification loss rate of test set and training set. In the red blood cells, white blood cells, calcium oxalate crystallization classification experiment, the classification accuracy rate of 97% or more.

Ejecta evolution during cone impact

KAUST Repository

Marston, Jeremy

2014-07-07

We present findings from an experimental investigation into the impact of solid cone-shaped bodies onto liquid pools. Using a variety of cone angles and liquid physical properties, we show that the ejecta formed during the impact exhibits self-similarity for all impact speeds for very low surface tension liquids, whilst for high-surface tension liquids similarity is only achieved at high impact speeds. We find that the ejecta tip can detach from the cone and that this phenomenon can be attributed to the air entrainment phenomenon. We analyse of a range of cone angles, including some ogive cones, and impact speeds in terms of the spatiotemporal evolution of the ejecta tip. Using superhydrophobic cones, we also examine the entry of cones which entrain an air layer.

Object Detection Based on Fast/Faster RCNN Employing Fully Convolutional Architectures

Directory of Open Access Journals (Sweden)

Yun Ren

2018-01-01

Full Text Available Modern object detectors always include two major parts: a feature extractor and a feature classifier as same as traditional object detectors. The deeper and wider convolutional architectures are adopted as the feature extractor at present. However, many notable object detection systems such as Fast/Faster RCNN only consider simple fully connected layers as the feature classifier. In this paper, we declare that it is beneficial for the detection performance to elaboratively design deep convolutional networks (ConvNets of various depths for feature classification, especially using the fully convolutional architectures. In addition, this paper also demonstrates how to employ the fully convolutional architectures in the Fast/Faster RCNN. Experimental results show that a classifier based on convolutional layer is more effective for object detection than that based on fully connected layer and that the better detection performance can be achieved by employing deeper ConvNets as the feature classifier.

A Revised Piecewise Linear Recursive Convolution FDTD Method for Magnetized Plasmas

International Nuclear Information System (INIS)

Liu Song; Zhong Shuangying; Liu Shaobin

2005-01-01

The piecewise linear recursive convolution (PLRC) finite-different time-domain (FDTD) method improves accuracy over the original recursive convolution (RC) FDTD approach and current density convolution (JEC) but retains their advantages in speed and efficiency. This paper describes a revised piecewise linear recursive convolution PLRC-FDTD formulation for magnetized plasma which incorporates both anisotropy and frequency dispersion at the same time, enabling the transient analysis of magnetized plasma media. The technique is illustrated by numerical simulations of the reflection and transmission coefficients through a magnetized plasma layer. The results show that the revised PLRC-FDTD method has improved the accuracy over the original RC FDTD method and JEC FDTD method

Convolutional cylinder-type block-circulant cycle codes

Directory of Open Access Journals (Sweden)

Mohammad Gholami

2013-06-01

Full Text Available In this paper, we consider a class of column-weight two quasi-cyclic low-density paritycheck codes in which the girth can be large enough, as an arbitrary multiple of 8. Then we devote a convolutional form to these codes, such that their generator matrix can be obtained by elementary row and column operations on the parity-check matrix. Finally, we show that the free distance of the convolutional codes is equal to the minimum distance of their block counterparts.

Prevention of gravitational collapse

International Nuclear Information System (INIS)

Moffat, J.W.; Taylor, J.G.

1981-01-01

We apply a new theory of gravitation to the question of gravitational collapse to show that collapse is prevented in this theory under very reasonable conditions. This result also extends to prevent ultimate collapse of the Universe. (orig.)

Correlation Between Cone Penetration Rate And Measured Cone Penetration Parameters In Silty Soils

DEFF Research Database (Denmark)

Poulsen, Rikke; Nielsen, Benjaminn Nordahl; Ibsen, Lars Bo

2013-01-01

This paper shows, how a change in cone penetration rate affects the cone penetration measurements, hence the cone resistance, pore pressure, and sleeve friction in silty soil. The standard rate of penetration is 20 mm/s, and it is generally accepted that undrained penetration occurs in clay while...... drained penetration occurs in sand. When lowering the penetration rate, the soil pore water starts to dissipate and a change in the drainage condition is seen. In intermediate soils such as silty soils, the standard cone penetration rate may result in a drainage condition that could be undrained......, partially or fully drained. However, lowering the penetration rate in silty soils has a great significance because of the soil permeability, and only a small change in penetration rate will result in changed cone penetration measurements. In this paper, analyses will be done on data from 15 field cone...

Gravitational Waves from Gravitational Collapse

Directory of Open Access Journals (Sweden)

Chris L. Fryer

2011-01-01

Full Text Available Gravitational-wave emission from stellar collapse has been studied for nearly four decades. Current state-of-the-art numerical investigations of collapse include those that use progenitors with more realistic angular momentum profiles, properly treat microphysics issues, account for general relativity, and examine non-axisymmetric effects in three dimensions. Such simulations predict that gravitational waves from various phenomena associated with gravitational collapse could be detectable with ground-based and space-based interferometric observatories. This review covers the entire range of stellar collapse sources of gravitational waves: from the accretion-induced collapse of a white dwarf through the collapse down to neutron stars or black holes of massive stars to the collapse of supermassive stars.

Gravitational waves from gravitational collapse

Energy Technology Data Exchange (ETDEWEB)

Fryer, Christopher L [Los Alamos National Laboratory; New, Kimberly C [Los Alamos National Laboratory

2008-01-01

Gravitational wave emission from stellar collapse has been studied for nearly four decades. Current state-of-the-art numerical investigations of collapse include those that use progenitors with more realistic angular momentum profiles, properly treat microphysics issues, account for general relativity, and examine non-axisymmetric effects in three dimensions. Such simulations predict that gravitational waves from various phenomena associated with gravitational collapse could be detectable with ground-based and space-based interferometric observatories. This review covers the entire range of stellar collapse sources of gravitational waves: from the accretion induced collapse of a white dwarf through the collapse down to neutron stars or black holes of massive stars to the collapse of supermassive stars.

Convolution of large 3D images on GPU and its decomposition

Science.gov (United States)

Karas, Pavel; Svoboda, David

2011-12-01

In this article, we propose a method for computing convolution of large 3D images. The convolution is performed in a frequency domain using a convolution theorem. The algorithm is accelerated on a graphic card by means of the CUDA parallel computing model. Convolution is decomposed in a frequency domain using the decimation in frequency algorithm. We pay attention to keeping our approach efficient in terms of both time and memory consumption and also in terms of memory transfers between CPU and GPU which have a significant inuence on overall computational time. We also study the implementation on multiple GPUs and compare the results between the multi-GPU and multi-CPU implementations.

New insights on lithofacies architecture, sedimentological characteristics and volcanological evolution of pre-caldera (> 22 ka), multi-phase, scoria- and spatter-cones at Somma-Vesuvius

Science.gov (United States)

Sparice, Domenico; Scarpati, Claudio; Perrotta, Annamaria; Mazzeo, Fabio Carmine; Calvert, Andrew T.; Lanphere, Marvin A.

2017-11-01

Pre-caldera (> 22 ka) lateral activity at Somma-Vesuvius is related to scoria- and spatter-cone forming events of monogenetic or polygenetic nature. A new stratigraphic, sedimentological, textural and lithofacies investigation was performed on five parasitic cones (Pollena cones, Traianello cone, S. Maria a Castello cone and the recently found Terzigno cone) occurring below the Pomici di Base (22 ka) Plinian products emplaced during the first caldera collapse at Somma-Vesuvius. A new Ar/Ar age of 23.6 ± 0.3 ka obtained for the Traianello cone as well as the absence of a paleosol or reworked material between the S. Maria a Castello cone and the Pomici di Base deposits suggest that such cone-forming eruptions occurred near the upper limit of the pre-caldera period (22-39 ky). The stratigraphy of three of these eccentric cones (Pollena cones and Traianello cone) exhibits erosion surfaces, exotic tephras, volcaniclastic layers, paleosols, unconformity and paraconformity between superimposed eruptive units revealing their multi-phase, polygenetic evolution related to activation of separate vents and periods of quiescence. Such eccentric cones have been described as composed of scoria deposits and pure effusive lavas by previous authors. Lavas are here re-interpreted as welded horizons (lava-like) composed of coalesced spatter fragments whose pyroclastic nature is locally revealed by relicts of original fragments and remnants of clast outlines. These welded horizons show, locally, rheomorphic structures allowing to define them as emplaced as clastogenic lava flows. The lava-like facies is transitional, upward and downward, to less welded facies composed of agglutinated to unwelded spatter horizons in which clasts outlines are increasingly discernible. Such textural characteristics and facies variation are consistent with a continuous fall deposition of Hawaiian fire-fountains episodes alternated with Strombolian phases emplacing loose scoria deposits. High enrichment

Modified Stieltjes Transform and Generalized Convolutions of Probability Distributions

Directory of Open Access Journals (Sweden)

Lev B. Klebanov

2018-01-01

Full Text Available The classical Stieltjes transform is modified in such a way as to generalize both Stieltjes and Fourier transforms. This transform allows the introduction of new classes of commutative and non-commutative generalized convolutions. A particular case of such a convolution for degenerate distributions appears to be the Wigner semicircle distribution.

Efficient forward propagation of time-sequences in convolutional neural networks using Deep Shifting

NARCIS (Netherlands)

K.L. Groenland (Koen); S.M. Bohte (Sander)

2016-01-01

textabstractWhen a Convolutional Neural Network is used for on-the-fly evaluation of continuously updating time-sequences, many redundant convolution operations are performed. We propose the method of Deep Shifting, which remembers previously calculated results of convolution operations in order

An Overview on Impact Behaviour and Energy Absorption of Collapsible Metallic and Non-Metallic Energy Absorbers used in Automotive Applications

Science.gov (United States)

Shinde, R. B.; Mali, K. D.

2018-04-01

Collapsible impact energy absorbers play an important role of protecting automotive components from damage during collision. Collision of the two objects results into the damage to one or both of them. Damage may be in the form of crack, fracture and scratch. Designers must know about how the material and object behave under impact event. Owing to above reasons different types of collapsible impact energy absorbers are developed. In the past different studies were undertaken to improve such collapsible impact energy absorbers. This article highlights such studies on common shapes of collapsible impact energy absorber and their impact behaviour under the axial compression. The literature based on studies and analyses of effects of different geometrical parameters on the crushing behaviour of impact energy absorbers is presented in detail. The energy absorber can be of different shape such as circular tube, square tube, and frustums of cone and pyramids. The crushing behaviour of energy absorbers includes studies on crushing mechanics, modes of deformation, energy absorbing capacity, effect on peak and mean crushing load. In this work efforts are made to cover major outcomes from past studies on such behavioural parameters. Even though the major literature reviewed is related to metallic energy absorbers, emphasis is also laid on covering literature on use of composite tube, fiber metal lamination (FML) member, honeycomb plate and functionally graded thickness (FGT) tube as a collapsible impact energy absorber.

Prediction of Electricity Usage Using Convolutional Neural Networks

OpenAIRE

Hansen, Martin

2017-01-01

Master's thesis Information- and communication technology IKT590 - University of Agder 2017 Convolutional Neural Networks are overwhelmingly accurate when attempting to predict numbers using the famous MNIST-dataset. In this paper, we are attempting to transcend these results for time- series forecasting, and compare them with several regression mod- els. The Convolutional Neural Network model predicted the same value through the entire time lapse in contrast with the other ...

Gravitational Waves from Gravitational Collapse.

Science.gov (United States)

Fryer, Chris L; New, Kimberly C B

2011-01-01

Gravitational-wave emission from stellar collapse has been studied for nearly four decades. Current state-of-the-art numerical investigations of collapse include those that use progenitors with more realistic angular momentum profiles, properly treat microphysics issues, account for general relativity, and examine non-axisymmetric effects in three dimensions. Such simulations predict that gravitational waves from various phenomena associated with gravitational collapse could be detectable with ground-based and space-based interferometric observatories. This review covers the entire range of stellar collapse sources of gravitational waves: from the accretion-induced collapse of a white dwarf through the collapse down to neutron stars or black holes of massive stars to the collapse of supermassive stars. Supplementary material is available for this article at 10.12942/lrr-2011-1.

Single image super-resolution based on convolutional neural networks

Science.gov (United States)

Zou, Lamei; Luo, Ming; Yang, Weidong; Li, Peng; Jin, Liujia

2018-03-01

We present a deep learning method for single image super-resolution (SISR). The proposed approach learns end-to-end mapping between low-resolution (LR) images and high-resolution (HR) images. The mapping is represented as a deep convolutional neural network which inputs the LR image and outputs the HR image. Our network uses 5 convolution layers, which kernels size include 5×5, 3×3 and 1×1. In our proposed network, we use residual-learning and combine different sizes of convolution kernels at the same layer. The experiment results show that our proposed method performs better than the existing methods in reconstructing quality index and human visual effects on benchmarked images.

Texture collapse

International Nuclear Information System (INIS)

Prokopec, T.; Sornborger, A.; Brandenberger, R.H.

1992-01-01

We study single-texture collapse using a leapfrog discretization method on a 30x30x30 spatial lattice. We investigate the influence of boundary conditions, physical size of the lattice, type of space-time background (flat, i.e., nonexpanding, vs radiation-dominated and matter-dominated universes), and spatial distribution of the initial texture configuration on collapse time and critical winding. For a spherically symmetric initial configuration of size equal to the horizon size on a lattice containing 12 (30) horizon volumes, the critical winding is found to be 0.621±0.001 (0.602±0.003) (flat case), 0.624±0.002 (0.604±0.005) (radiation era), 0.628±0.002 (0.612±0.003) (matter era). The larger the physical size of the lattice (in units of the horizon size), the smaller is the critical winding, and in the limit of an infinite lattice, we argue that the critical winding approaches 0.5. For radially asymmetric cases, contraction of one axis ( /Ipancake case) slightly reduces collapse time and critical winding, and contraction of two axes (d/Icigar case) reduces collapse time and critical winding significantly

Chloride currents in cones modify feedback from horizontal cells to cones in goldfish retina

Science.gov (United States)

Endeman, Duco; Fahrenfort, Iris; Sjoerdsma, Trijntje; Steijaert, Marvin; ten Eikelder, Huub; Kamermans, Maarten

2012-01-01

In neuronal systems, excitation and inhibition must be well balanced to ensure reliable information transfer. The cone/horizontal cell (HC) interaction in the retina is an example of this. Because natural scenes encompass an enormous intensity range both in temporal and spatial domains, the balance between excitation and inhibition in the outer retina needs to be adaptable. How this is achieved is unknown. Using electrophysiological techniques in the isolated retina of the goldfish, it was found that opening Ca2+-dependent Cl− channels in recorded cones reduced the size of feedback responses measured in both cones and HCs. Furthermore, we show that cones express Cl− channels that are gated by GABA released from HCs. Similar to activation of ICl(Ca), opening of these GABA-gated Cl− channels reduced the size of light-induced feedback responses both in cones and HCs. Conversely, application of picrotoxin, a blocker of GABAA and GABAC receptors, had the opposite effect. In addition, reducing GABA release from HCs by blocking GABA transporters also led to an increase in the size of feedback. Because the independent manipulation of Ca2+-dependent Cl− currents in individual cones yielded results comparable to bath-applied GABA, it was concluded that activation of either Cl− current by itself is sufficient to reduce the size of HC feedback. However, additional effects of GABA on outer retinal processing cannot be excluded. These results can be accounted for by an ephaptic feedback model in which a cone Cl− current shunts the current flow in the synaptic cleft. The Ca2+-dependent Cl− current might be essential to set the initial balance between the feedforward and the feedback signals active in the cone HC synapse. It prevents that strong feedback from HCs to cones flood the cone with Ca2+. Modulation of the feedback strength by GABA might play a role during light/dark adaptation, adjusting the amount of negative feedback to the signal to noise ratio of the

Combining slope stability and groundwater flow models to assess stratovolcano collapse hazard

Science.gov (United States)

Ball, J. L.; Taron, J.; Reid, M. E.; Hurwitz, S.; Finn, C.; Bedrosian, P.

2016-12-01

Flank collapses are a well-documented hazard at volcanoes. Elevated pore-fluid pressures and hydrothermal alteration are invoked as potential causes for the instability in many of these collapses. Because pore pressure is linked to water saturation and permeability of volcanic deposits, hydrothermal alteration is often suggested as a means of creating low-permeability zones in volcanoes. Here, we seek to address the question: What alteration geometries will produce elevated pore pressures in a stratovolcano, and what are the effects of these elevated pressures on slope stability? We initially use a finite element groundwater flow model (a modified version of OpenGeoSys) to simulate `generic' stratovolcano geometries that produce elevated pore pressures. We then input these results into the USGS slope-stability code Scoops3D to investigate the effects of alteration and magmatic intrusion on potential flank failure. This approach integrates geophysical data about subsurface alteration, water saturation and rock mechanical properties with data about precipitation and heat influx at Cascade stratovolcanoes. Our simulations show that it is possible to maintain high-elevation water tables in stratovolcanoes given specific ranges of edifice permeability (ideally between 10-15 and 10-16 m2). Low-permeability layers (10-17 m2, representing altered pyroclastic deposits or altered breccias) in the volcanoes can localize saturated regions close to the surface, but they may actually reduce saturation, pore pressures, and water table levels in the core of the volcano. These conditions produce universally lower factor-of-safety (F) values than at an equivalent dry edifice with the same material properties (lower values of F indicate a higher likelihood of collapse). When magmatic intrusions into the base of the cone are added, near-surface pore pressures increase and F decreases exponentially with time ( 7-8% in the first year). However, while near-surface impermeable layers

The Extraction of Post-Earthquake Building Damage Informatiom Based on Convolutional Neural Network

Science.gov (United States)

Chen, M.; Wang, X.; Dou, A.; Wu, X.

2018-04-01

The seismic damage information of buildings extracted from remote sensing (RS) imagery is meaningful for supporting relief and effective reduction of losses caused by earthquake. Both traditional pixel-based and object-oriented methods have some shortcoming in extracting information of object. Pixel-based method can't make fully use of contextual information of objects. Object-oriented method faces problem that segmentation of image is not ideal, and the choice of feature space is difficult. In this paper, a new stratage is proposed which combines Convolution Neural Network (CNN) with imagery segmentation to extract building damage information from remote sensing imagery. the key idea of this method includes two steps. First to use CNN to predicate the probability of each pixel and then integrate the probability within each segmentation spot. The method is tested through extracting the collapsed building and uncollapsed building from the aerial image which is acquired in Longtoushan Town after Ms 6.5 Ludian County, Yunnan Province earthquake. The results show that the proposed method indicates its effectiveness in extracting damage information of buildings after earthquake.

Model selection for convolutive ICA with an application to spatiotemporal analysis of EEG

DEFF Research Database (Denmark)

Dyrholm, Mads; Makeig, S.; Hansen, Lars Kai

2007-01-01

We present a new algorithm for maximum likelihood convolutive independent component analysis (ICA) in which components are unmixed using stable autoregressive filters determined implicitly by estimating a convolutive model of the mixing process. By introducing a convolutive mixing model...... for the components, we show how the order of the filters in the model can be correctly detected using Bayesian model selection. We demonstrate a framework for deconvolving a subspace of independent components in electroencephalography (EEG). Initial results suggest that in some cases, convolutive mixing may...

Phylogenetic convolutional neural networks in metagenomics.

Science.gov (United States)

Fioravanti, Diego; Giarratano, Ylenia; Maggio, Valerio; Agostinelli, Claudio; Chierici, Marco; Jurman, Giuseppe; Furlanello, Cesare

2018-03-08

Convolutional Neural Networks can be effectively used only when data are endowed with an intrinsic concept of neighbourhood in the input space, as is the case of pixels in images. We introduce here Ph-CNN, a novel deep learning architecture for the classification of metagenomics data based on the Convolutional Neural Networks, with the patristic distance defined on the phylogenetic tree being used as the proximity measure. The patristic distance between variables is used together with a sparsified version of MultiDimensional Scaling to embed the phylogenetic tree in a Euclidean space. Ph-CNN is tested with a domain adaptation approach on synthetic data and on a metagenomics collection of gut microbiota of 38 healthy subjects and 222 Inflammatory Bowel Disease patients, divided in 6 subclasses. Classification performance is promising when compared to classical algorithms like Support Vector Machines and Random Forest and a baseline fully connected neural network, e.g. the Multi-Layer Perceptron. Ph-CNN represents a novel deep learning approach for the classification of metagenomics data. Operatively, the algorithm has been implemented as a custom Keras layer taking care of passing to the following convolutional layer not only the data but also the ranked list of neighbourhood of each sample, thus mimicking the case of image data, transparently to the user.

Invariant moments based convolutional neural networks for image analysis

Directory of Open Access Journals (Sweden)

Vijayalakshmi G.V. Mahesh

2017-01-01

Full Text Available The paper proposes a method using convolutional neural network to effectively evaluate the discrimination between face and non face patterns, gender classification using facial images and facial expression recognition. The novelty of the method lies in the utilization of the initial trainable convolution kernels coefficients derived from the zernike moments by varying the moment order. The performance of the proposed method was compared with the convolutional neural network architecture that used random kernels as initial training parameters. The multilevel configuration of zernike moments was significant in extracting the shape information suitable for hierarchical feature learning to carry out image analysis and classification. Furthermore the results showed an outstanding performance of zernike moment based kernels in terms of the computation time and classification accuracy.

Critical condition for the transformation from Taylor cone to cone-jet

International Nuclear Information System (INIS)

Wei Cheng; Zhao Yang; Gang Tie-Qiang; Chen Li-Jie

2014-01-01

An energy method is proposed to investigate the critical transformation condition from a Taylor cone to a cone-jet. Based on the kinetic theorem, the system power allocation and the electrohydrodynamics stability are discussed. The numerical results indicate that the energy of the liquid cone tip experiences a maximum value during the transformation. With the proposed jetting energy, we give the critical transformation condition under which the derivative of jetting energy with respect to the surface area is greater than or equal to the energy required to form a unit of new liquid surface

Fast space-varying convolution using matrix source coding with applications to camera stray light reduction.

Science.gov (United States)

Wei, Jianing; Bouman, Charles A; Allebach, Jan P

2014-05-01

Many imaging applications require the implementation of space-varying convolution for accurate restoration and reconstruction of images. Here, we use the term space-varying convolution to refer to linear operators whose impulse response has slow spatial variation. In addition, these space-varying convolution operators are often dense, so direct implementation of the convolution operator is typically computationally impractical. One such example is the problem of stray light reduction in digital cameras, which requires the implementation of a dense space-varying deconvolution operator. However, other inverse problems, such as iterative tomographic reconstruction, can also depend on the implementation of dense space-varying convolution. While space-invariant convolution can be efficiently implemented with the fast Fourier transform, this approach does not work for space-varying operators. So direct convolution is often the only option for implementing space-varying convolution. In this paper, we develop a general approach to the efficient implementation of space-varying convolution, and demonstrate its use in the application of stray light reduction. Our approach, which we call matrix source coding, is based on lossy source coding of the dense space-varying convolution matrix. Importantly, by coding the transformation matrix, we not only reduce the memory required to store it; we also dramatically reduce the computation required to implement matrix-vector products. Our algorithm is able to reduce computation by approximately factoring the dense space-varying convolution operator into a product of sparse transforms. Experimental results show that our method can dramatically reduce the computation required for stray light reduction while maintaining high accuracy.

Consensus Convolutional Sparse Coding

KAUST Repository

Choudhury, Biswarup

2017-12-01

Convolutional sparse coding (CSC) is a promising direction for unsupervised learning in computer vision. In contrast to recent supervised methods, CSC allows for convolutional image representations to be learned that are equally useful for high-level vision tasks and low-level image reconstruction and can be applied to a wide range of tasks without problem-specific retraining. Due to their extreme memory requirements, however, existing CSC solvers have so far been limited to low-dimensional problems and datasets using a handful of low-resolution example images at a time. In this paper, we propose a new approach to solving CSC as a consensus optimization problem, which lifts these limitations. By learning CSC features from large-scale image datasets for the first time, we achieve significant quality improvements in a number of imaging tasks. Moreover, the proposed method enables new applications in high-dimensional feature learning that has been intractable using existing CSC methods. This is demonstrated for a variety of reconstruction problems across diverse problem domains, including 3D multispectral demosaicing and 4D light field view synthesis.

Consensus Convolutional Sparse Coding

KAUST Repository

Choudhury, Biswarup

2017-04-11

Convolutional sparse coding (CSC) is a promising direction for unsupervised learning in computer vision. In contrast to recent supervised methods, CSC allows for convolutional image representations to be learned that are equally useful for high-level vision tasks and low-level image reconstruction and can be applied to a wide range of tasks without problem-specific retraining. Due to their extreme memory requirements, however, existing CSC solvers have so far been limited to low-dimensional problems and datasets using a handful of low-resolution example images at a time. In this paper, we propose a new approach to solving CSC as a consensus optimization problem, which lifts these limitations. By learning CSC features from large-scale image datasets for the first time, we achieve significant quality improvements in a number of imaging tasks. Moreover, the proposed method enables new applications in high dimensional feature learning that has been intractable using existing CSC methods. This is demonstrated for a variety of reconstruction problems across diverse problem domains, including 3D multispectral demosaickingand 4D light field view synthesis.

Consensus Convolutional Sparse Coding

KAUST Repository

Choudhury, Biswarup; Swanson, Robin; Heide, Felix; Wetzstein, Gordon; Heidrich, Wolfgang

2017-01-01

Convolutional sparse coding (CSC) is a promising direction for unsupervised learning in computer vision. In contrast to recent supervised methods, CSC allows for convolutional image representations to be learned that are equally useful for high-level vision tasks and low-level image reconstruction and can be applied to a wide range of tasks without problem-specific retraining. Due to their extreme memory requirements, however, existing CSC solvers have so far been limited to low-dimensional problems and datasets using a handful of low-resolution example images at a time. In this paper, we propose a new approach to solving CSC as a consensus optimization problem, which lifts these limitations. By learning CSC features from large-scale image datasets for the first time, we achieve significant quality improvements in a number of imaging tasks. Moreover, the proposed method enables new applications in high-dimensional feature learning that has been intractable using existing CSC methods. This is demonstrated for a variety of reconstruction problems across diverse problem domains, including 3D multispectral demosaicing and 4D light field view synthesis.

Review on resonance cone fields

International Nuclear Information System (INIS)

Ohnuma, Toshiro.

1980-02-01

Resonance cone fields and lower hybrid heating are reviewed in this report. The resonance cone fields were reported by Fisher and Gould, and they proposed the use of the measurement of resonance cones and structure as a diagnostic tool to determine the plasma density and electron temperature in magnetoplasma. After the resonance cone, a wave-like disturbance persists. Ohnuma et al. have measured bending, reflection and ducting of resonance cones in detail. The thermal modes in inhomogeneous magnetoplasma were seen. The reflection of thermal mode near an electron plasma frequency layer and an insulating plate has been observed. The non-linear effects of resonance cones is reported. Monochromatic electron beam produces the noise of broad band whistler mode. Lower hybrid waves have been the subject of propagation from the edge of plasma to the lower hybrid layer. Linear lower hybrid waves were studied. The lower hybrid and ion acoustic waves radiated from a point source were observed. The parametric decay of finite-extent, cold electron plasma waves was studied. The lower hybrid cone radiated from a point source going along magnetic field lines was observed. Several experimental data on the lower hybrid heating in tokamak devices have been reported. The theories on resonance cones and lower hybrid waves are introduced in this report. (Kato, T.)

Human Face Recognition Using Convolutional Neural Networks

Directory of Open Access Journals (Sweden)

Răzvan-Daniel Albu

2009-10-01

Full Text Available In this paper, I present a novel hybrid face recognition approach based on a convolutional neural architecture, designed to robustly detect highly variable face patterns. The convolutional network extracts successively larger features in a hierarchical set of layers. With the weights of the trained neural networks there are created kernel windows used for feature extraction in a 3-stage algorithm. I present experimental results illustrating the efficiency of the proposed approach. I use a database of 796 images of 159 individuals from Reims University which contains quite a high degree of variability in expression, pose, and facial details.

Development and application of deep convolutional neural network in target detection

Science.gov (United States)

Jiang, Xiaowei; Wang, Chunping; Fu, Qiang

2018-04-01

With the development of big data and algorithms, deep convolution neural networks with more hidden layers have more powerful feature learning and feature expression ability than traditional machine learning methods, making artificial intelligence surpass human level in many fields. This paper first reviews the development and application of deep convolutional neural networks in the field of object detection in recent years, then briefly summarizes and ponders some existing problems in the current research, and the future development of deep convolutional neural network is prospected.

Understanding the cone scale in Cupressaceae: insights from seed-cone teratology in Glyptostrobus pensilis.

Science.gov (United States)

Dörken, Veit Martin; Rudall, Paula J

2018-01-01

Both wild-type and teratological seed cones are described in the monoecious conifer Glyptostrobus pensilis and compared with those of other Cupressaceae sensu lato and other conifers. Some Cupressaceae apparently possess a proliferation of axillary structures in their cone scales. In our interpretation, in Glyptostrobus each bract of both typical and atypical seed cones bears two descending accessory shoots, interpreted here as seed scales (ovuliferous scales). The primary seed scale is fertile and forms the ovules, the second is sterile and forms characteristic tooth-like structures. The bract and the two axillary seed scales are each supplied with a single distinct vascular bundle that enters the cone axis as a separate strand; this vasculature also characterises the descending accessory short shoots in the vegetative parts of the crown. In wild-type seed cones, the fertile seed scale is reduced to its ovules, and the ovules are always axillary. In contrast, the ovules of some of the teratological seed cones examined were located at the centre of the cone scale. An additional tissue found on the upper surface of the sterile lower seed scale is here interpreted as the axis of the fertile seed scale. Thus, the central position of the ovules can be explained by recaulescent fusion of the upper fertile and lower sterile seed scales. In several teratological cone scales, the ovules were enveloped by an additional sterile tissue that is uniseriate and represents an epidermal outgrowth of the fertile seed scale. Close to the ovules, the epidermis was detached from lower tissue and surrounded the ovule completely, except at the micropyle. These teratological features are potentially significant in understanding seed-cone homologies among extant conifers.

B→ππ form factors from light-cone sum rules with B-meson distribution amplitudes

Energy Technology Data Exchange (ETDEWEB)

Cheng, Shan; Khodjamirian, Alexander [Theoretische Physik 1, Naturwissenschaftlich-Technische Fakultät,Department Physik, Universität Siegen,Walter-Flex-Strasse 3, 57068 Siegen (Germany); Virto, Javier [Albert Einstein Center for Fundamental Physics,Institute for Theoretical Physics, University of Bern,Sidlerstrasse 5, CH-3012 Bern (Switzerland)

2017-05-30

We study B→ππ form factors using QCD light-cone sum rules with B-meson distribution amplitudes. These form factors describe the semileptonic decay B→ππℓν̄{sub ℓ}, and constitute an essential input in B→ππℓ{sup +}ℓ{sup −} and B→πππ decays. We employ the correlation functions where a dipion isospin-one state is interpolated by the vector light-quark current. We obtain sum rules where convolutions of the P-wave B̄{sup 0}→π{sup +}π{sup 0} form factors with the timelike pion vector form factor are related to universal B-meson distribution amplitudes. These sum rules are valid in the kinematic regime where the dipion state has a large energy and a low invariant mass, and reproduce analytically the known light-cone sum rules for B→ρ form factors in the limit of ρ-dominance and zero width, thus providing a systematics for so far unaccounted corrections to B→ρ transitions. Using data for the pion vector form factor, we estimate finite-width effects and the contribution of excited ρ-resonances to the B→ππ form factors. We find that these contributions amount up to ∼20% in the small dipion mass region where they can be effectively regarded as a nonresonant (P-wave) background to the B→ρ transition.

Traffic sign recognition with deep convolutional neural networks

OpenAIRE

Karamatić, Boris

2016-01-01

The problem of detection and recognition of traffic signs is becoming an important problem when it comes to the development of self driving cars and advanced driver assistance systems. In this thesis we will develop a system for detection and recognition of traffic signs. For the problem of detection we will use aggregate channel features and for the problem of recognition we will use a deep convolutional neural network. We will describe how convolutional neural networks work, how they are co...

Cones for dental radiography

Energy Technology Data Exchange (ETDEWEB)

Butler, M J [National Radiological Protection Board, Harwell (UK)

1977-04-01

Dental radiographic techniques are summarized. The advantages and disadvantages of the use of both the conventional plastic pointer cone and the open-ended cylinders or divergent cones favoured both by the ICRP (Protection against Ionizing Radiation from External Sources, Oxford, Pergamon Press, 1973, ICRP Publication 15), and in the Code of Practice for the Protection of Persons against Ionizing Radiation arising from Medical and Dental Use (1972, 3rd edition, London, HMSO) are discussed. The use of the word 'should' in these recommendations to signify a desirable requirement, not an essential one, is noted. This wording is currently of interest both nationally and internationally in relation to regulations, standards and notes for guidance. The National Radiological Protection Board (NRPB) has been reviewing the position, and has concluded that open-ended cones have disadvantages which may sometimes outweigh their advantages. Although open-ended cones are preferable under some circumstances, the recommendation that they should be used ought not to be followed without an understanding of the issues involved. The hazards associated with the use of interchangeable cones are considered. The NRPB now proposes that the requirement for the replacement of pointer cones (for both new and existing equipment) should be withdrawn.

The f electron collapse revisited

International Nuclear Information System (INIS)

Bennett, B.I.

1987-03-01

A reexamination of the collapse of 4f and 5f electrons in the lanthanide and actinide series is presented. The calculations show the well-known collapse of the f electron density at the thresholds of these series along with an f 2 collapse between thorium and protactinium. The collapse is sensitive to the choice of model for the exchange-correlation potential and the behavior of the potential at large radius

Understanding the cone scale in Cupressaceae: insights from seed-cone teratology in Glyptostrobus pensilis

Directory of Open Access Journals (Sweden)

Veit Martin Dörken

2018-06-01

Full Text Available Both wild-type and teratological seed cones are described in the monoecious conifer Glyptostrobus pensilis and compared with those of other Cupressaceae sensu lato and other conifers. Some Cupressaceae apparently possess a proliferation of axillary structures in their cone scales. In our interpretation, in Glyptostrobus each bract of both typical and atypical seed cones bears two descending accessory shoots, interpreted here as seed scales (ovuliferous scales. The primary seed scale is fertile and forms the ovules, the second is sterile and forms characteristic tooth-like structures. The bract and the two axillary seed scales are each supplied with a single distinct vascular bundle that enters the cone axis as a separate strand; this vasculature also characterises the descending accessory short shoots in the vegetative parts of the crown. In wild-type seed cones, the fertile seed scale is reduced to its ovules, and the ovules are always axillary. In contrast, the ovules of some of the teratological seed cones examined were located at the centre of the cone scale. An additional tissue found on the upper surface of the sterile lower seed scale is here interpreted as the axis of the fertile seed scale. Thus, the central position of the ovules can be explained by recaulescent fusion of the upper fertile and lower sterile seed scales. In several teratological cone scales, the ovules were enveloped by an additional sterile tissue that is uniseriate and represents an epidermal outgrowth of the fertile seed scale. Close to the ovules, the epidermis was detached from lower tissue and surrounded the ovule completely, except at the micropyle. These teratological features are potentially significant in understanding seed-cone homologies among extant conifers.

SU-F-J-148: A Collapsed Cone Algorithm Can Be Used for Quality Assurance for Monaco Treatment Plans for the MR-Linac

Energy Technology Data Exchange (ETDEWEB)

Hackett, S; Asselen, B van; Wolthaus, J; Kotte, A; Bol, G; Lagendijk, J; Raaymakers, B [University Medical Center, Utrecht (Netherlands); Feist, G [Elekta Instrument AB, Stockholm (Sweden); Pencea, S [Elekta Inc., Atlanta, GA (United States); Akhiat, H [Elekta BV, Best (Netherlands)

2016-06-15

Purpose: Treatment plans for the MR-linac, calculated in Monaco v5.19, include direct simulation of the effects of the 1.5T B{sub 0}-field. We tested the feasibility of using a collapsed-cone (CC) algorithm in Oncentra, which does not account for effects of the B{sub 0}-field, as a fast online, independent 3D check of dose calculations. Methods: Treatment plans for six patients were generated in Monaco with a 6 MV FFF beam and the B{sub 0}-field. All plans were recalculated with a CC model of the same beam. Plans for the same patients were also generated in Monaco without the B{sub 0}-field. The mean dose (Dmean) and doses to 10% (D10%) and 90% (D90%) of the volume were determined, as percentages of the prescribed dose, for target volumes and OARs in each calculated dose distribution. Student’s t-tests between paired parameters from Monaco plans and corresponding CC calculations were performed. Results: Figure 1 shows an example of the difference between dose distributions calculated in Monaco, with the B{sub 0}-field, and the CC algorithm. Figure 2 shows distributions of (absolute) difference between parameters for Monaco plans, with the B{sub 0}-field, and CC calculations. The Dmean and D90% values for the CTVs and PTVs were significantly different, but differences in dose distributions arose predominantly at the edges of the target volumes. Inclusion of the B{sub 0}-field had little effect on agreement of the Dmean values, as illustrated by Figure 3, nor on agreement of the D10% and D90% values. Conclusion: Dose distributions recalculated with a CC algorithm show good agreement with those calculated with Monaco, for plans both with and without the B{sub 0}-field, indicating that the CC algorithm could be used to check online treatment planning for the MRlinac. Agreement for a wider range of treatment sites, and the feasibility of using the γ-test as a simple pass/fail criterion, will be investigated.

Light-cone quantization of quantum chromodynamics

International Nuclear Information System (INIS)

Brodsky, S.J.; Pauli, H.C.

1991-06-01

We discuss the light-cone quantization of gauge theories from two perspectives: as a calculational tool for representing hadrons as QCD bound-states of relativistic quarks and gluons, and also as a novel method for simulating quantum field theory on a computer. The light-cone Fock state expansion of wavefunctions at fixed light cone time provides a precise definition of the parton model and a general calculus for hadronic matrix elements. We present several new applications of light-cone Fock methods, including calculations of exclusive weak decays of heavy hadrons, and intrinsic heavy-quark contributions to structure functions. A general nonperturbative method for numerically solving quantum field theories, ''discretized light-cone quantization,'' is outlined and applied to several gauge theories, including QCD in one space and one time dimension, and quantum electrodynamics in physical space-time at large coupling strength. The DLCQ method is invariant under the large class of light-cone Lorentz transformations, and it can be formulated such at ultraviolet regularization is independent of the momentum space discretization. Both the bound-state spectrum and the corresponding relativistic light-cone wavefunctions can be obtained by matrix diagonalization and related techniques. We also discuss the construction of the light-cone Fock basis, the structure of the light-cone vacuum, and outline the renormalization techniques required for solving gauge theories within the light-cone Hamiltonian formalism

Light-cone quantization of quantum chromodynamics

Energy Technology Data Exchange (ETDEWEB)

Brodsky, S.J. (Stanford Linear Accelerator Center, Menlo Park, CA (USA)); Pauli, H.C. (Max-Planck-Institut fuer Kernphysik, Heidelberg (Germany, F.R.))

1991-06-01

We discuss the light-cone quantization of gauge theories from two perspectives: as a calculational tool for representing hadrons as QCD bound-states of relativistic quarks and gluons, and also as a novel method for simulating quantum field theory on a computer. The light-cone Fock state expansion of wavefunctions at fixed light cone time provides a precise definition of the parton model and a general calculus for hadronic matrix elements. We present several new applications of light-cone Fock methods, including calculations of exclusive weak decays of heavy hadrons, and intrinsic heavy-quark contributions to structure functions. A general nonperturbative method for numerically solving quantum field theories, discretized light-cone quantization,'' is outlined and applied to several gauge theories, including QCD in one space and one time dimension, and quantum electrodynamics in physical space-time at large coupling strength. The DLCQ method is invariant under the large class of light-cone Lorentz transformations, and it can be formulated such at ultraviolet regularization is independent of the momentum space discretization. Both the bound-state spectrum and the corresponding relativistic light-cone wavefunctions can be obtained by matrix diagonalization and related techniques. We also discuss the construction of the light-cone Fock basis, the structure of the light-cone vacuum, and outline the renormalization techniques required for solving gauge theories within the light-cone Hamiltonian formalism.

Research of convolutional neural networks for traffic sign recognition

OpenAIRE

Stadalnikas, Kasparas

2017-01-01

In this thesis the convolutional neural networks application for traffic sign recognition is analyzed. Thesis describes the basic operations, techniques that are commonly used to apply in the image classification using convolutional neural networks. Also, this paper describes the data sets used for traffic sign recognition, their problems affecting the final training results. The paper reviews most popular existing technologies – frameworks for developing the solution for traffic sign recogni...

High Performance Implementation of 3D Convolutional Neural Networks on a GPU

Science.gov (United States)

Wang, Zelong; Wen, Mei; Zhang, Chunyuan; Wang, Yijie

2017-01-01

Convolutional neural networks have proven to be highly successful in applications such as image classification, object tracking, and many other tasks based on 2D inputs. Recently, researchers have started to apply convolutional neural networks to video classification, which constitutes a 3D input and requires far larger amounts of memory and much more computation. FFT based methods can reduce the amount of computation, but this generally comes at the cost of an increased memory requirement. On the other hand, the Winograd Minimal Filtering Algorithm (WMFA) can reduce the number of operations required and thus can speed up the computation, without increasing the required memory. This strategy was shown to be successful for 2D neural networks. We implement the algorithm for 3D convolutional neural networks and apply it to a popular 3D convolutional neural network which is used to classify videos and compare it to cuDNN. For our highly optimized implementation of the algorithm, we observe a twofold speedup for most of the 3D convolution layers of our test network compared to the cuDNN version. PMID:29250109

High Performance Implementation of 3D Convolutional Neural Networks on a GPU.

Science.gov (United States)

Lan, Qiang; Wang, Zelong; Wen, Mei; Zhang, Chunyuan; Wang, Yijie

2017-01-01

Convolutional neural networks have proven to be highly successful in applications such as image classification, object tracking, and many other tasks based on 2D inputs. Recently, researchers have started to apply convolutional neural networks to video classification, which constitutes a 3D input and requires far larger amounts of memory and much more computation. FFT based methods can reduce the amount of computation, but this generally comes at the cost of an increased memory requirement. On the other hand, the Winograd Minimal Filtering Algorithm (WMFA) can reduce the number of operations required and thus can speed up the computation, without increasing the required memory. This strategy was shown to be successful for 2D neural networks. We implement the algorithm for 3D convolutional neural networks and apply it to a popular 3D convolutional neural network which is used to classify videos and compare it to cuDNN. For our highly optimized implementation of the algorithm, we observe a twofold speedup for most of the 3D convolution layers of our test network compared to the cuDNN version.

A MacWilliams Identity for Convolutional Codes: The General Case

OpenAIRE

Gluesing-Luerssen, Heide; Schneider, Gert

2008-01-01

A MacWilliams Identity for convolutional codes will be established. It makes use of the weight adjacency matrices of the code and its dual, based on state space realizations (the controller canonical form) of the codes in question. The MacWilliams Identity applies to various notions of duality appearing in the literature on convolutional coding theory.

Down image recognition based on deep convolutional neural network

Directory of Open Access Journals (Sweden)

Wenzhu Yang

2018-06-01

Full Text Available Since of the scale and the various shapes of down in the image, it is difficult for traditional image recognition method to correctly recognize the type of down image and get the required recognition accuracy, even for the Traditional Convolutional Neural Network (TCNN. To deal with the above problems, a Deep Convolutional Neural Network (DCNN for down image classification is constructed, and a new weight initialization method is proposed. Firstly, the salient regions of a down image were cut from the image using the visual saliency model. Then, these salient regions of the image were used to train a sparse autoencoder and get a collection of convolutional filters, which accord with the statistical characteristics of dataset. At last, a DCNN with Inception module and its variants was constructed. To improve the recognition accuracy, the depth of the network is deepened. The experiment results indicate that the constructed DCNN increases the recognition accuracy by 2.7% compared to TCNN, when recognizing the down in the images. The convergence rate of the proposed DCNN with the new weight initialization method is improved by 25.5% compared to TCNN. Keywords: Deep convolutional neural network, Weight initialization, Sparse autoencoder, Visual saliency model, Image recognition

DCMDN: Deep Convolutional Mixture Density Network

Science.gov (United States)

D'Isanto, Antonio; Polsterer, Kai Lars

2017-09-01

Deep Convolutional Mixture Density Network (DCMDN) estimates probabilistic photometric redshift directly from multi-band imaging data by combining a version of a deep convolutional network with a mixture density network. The estimates are expressed as Gaussian mixture models representing the probability density functions (PDFs) in the redshift space. In addition to the traditional scores, the continuous ranked probability score (CRPS) and the probability integral transform (PIT) are applied as performance criteria. DCMDN is able to predict redshift PDFs independently from the type of source, e.g. galaxies, quasars or stars and renders pre-classification of objects and feature extraction unnecessary; the method is extremely general and allows the solving of any kind of probabilistic regression problems based on imaging data, such as estimating metallicity or star formation rate in galaxies.

Geotechnical properties of Egyptian collapsible soils

Directory of Open Access Journals (Sweden)

Khaled E. Gaaver

2012-09-01

Full Text Available The risk of constructing structures on collapsible soils presents significant challenges to geotechnical engineers due to sudden reduction in volume upon wetting. Identifying collapsible soils when encountered in the field and taking the needed precautions should substantially reduce the risk of such problems usually reported in buildings and highways. Collapsible soils are those unsaturated soils that can withstand relatively high pressure without showing significant change in volume, however upon wetting; they are susceptible to a large and sudden reduction in volume. Collapsible soils cover significant areas around the world. In Egypt, collapsible soils were observed within the northern portion of the western desert including Borg El-Arab region, and around the city of Cairo in Six-of-October plateau, and Tenth-of-Ramadan city. Settlements associated with development on untreated collapsible soils usually lead to expensive repairs. One method for treating collapsible soils is to densify their structure by compaction. The ongoing study presents the effect of compaction on the geotechnical properties of the collapsible soils. Undisturbed block samples were recovered from test pits at four sites in Borg El-Arab district, located at about 20 km west of the city of Alexandria, Egypt. The samples were tested in both unsoaked and soaked conditions. Influence of water inundation on the geotechnical properties of collapsible soils was demonstrated. A comparative study between natural undisturbed and compacted samples of collapsible soils was performed. An attempt was made to relate the collapse potential to the initial moisture content. An empirical correlation between California Bearing Ratio of the compacted collapsible soils and liquid limit was adopted. The presented simple relationships should enable the geotechnical engineers to estimate the complex parameters of collapsible soils using simple laboratory tests with a reasonable accuracy.

A New Reverberator Based on Variable Sparsity Convolution

DEFF Research Database (Denmark)

Holm-Rasmussen, Bo; Lehtonen, Heidi-Maria; Välimäki, Vesa

2013-01-01

FIR filter coefficients are selected from a velvet noise sequence, which consists of ones, minus ones, and zeros only. In this application, it is sufficient perceptually to use very sparse velvet noise sequences having only about 0.1 to 0.2% non-zero elements, with increasing sparsity along...... the impulse response. The algorithm yields a parametric approximation of the late part of the impulse response, which is more than 100 times more efficient computationally than the direct convolution. The computational load of the proposed algorithm is comparable to that of FFT-based partitioned convolution...

Spacings and pair correlations for finite Bernoulli convolutions

International Nuclear Information System (INIS)

Benjamini, Itai; Solomyak, Boris

2009-01-01

We consider finite Bernoulli convolutions with a parameter 1/2 N . These sequences are uniformly distributed with respect to the infinite Bernoulli convolution measure ν λ , as N → ∞. Numerical evidence suggests that for a generic λ, the distribution of spacings between appropriately rescaled points is Poissonian. We obtain some partial results in this direction; for instance, we show that, on average, the pair correlations do not exhibit attraction or repulsion in the limit. On the other hand, for certain algebraic λ the behaviour is totally different

Efficient and Invariant Convolutional Neural Networks for Dense Prediction

OpenAIRE

Gao, Hongyang; Ji, Shuiwang

2017-01-01

Convolutional neural networks have shown great success on feature extraction from raw input data such as images. Although convolutional neural networks are invariant to translations on the inputs, they are not invariant to other transformations, including rotation and flip. Recent attempts have been made to incorporate more invariance in image recognition applications, but they are not applicable to dense prediction tasks, such as image segmentation. In this paper, we propose a set of methods...

Mechanisms of cascade collapse

International Nuclear Information System (INIS)

Diaz de la Rubia, T.; Smalinskas, K.; Averback, R.S.; Robertson, I.M.; Hseih, H.; Benedek, R.

1988-12-01

The spontaneous collapse of energetic displacement cascades in metals into vacancy dislocation loops has been investigated by molecular dynamics (MD) computer simulation and transmission electron microscopy (TEM). Simulations of 5 keV recoil events in Cu and Ni provide the following scenario of cascade collapse: atoms are ejected from the central region of the cascade by replacement collision sequences; the central region subsequently melts; vacancies are driven to the center of the cascade during resolidification where they may collapse into loops. Whether or not collapse occurs depends critically on the melting temperature of the metal and the energy density and total energy in the cascade. Results of TEM are presented in support of this mechanism. 14 refs., 4 figs., 1 tab

Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network.

Science.gov (United States)

Du, Xiaofeng; Qu, Xiaobo; He, Yifan; Guo, Di

2018-03-06

Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules. To restore various scales of image details, we enhance the multi-scale inference capability of CNNs by introducing competition among multi-scale convolutional filters, and build up a shallow network under limited computational resources. The proposed network has the following two advantages: (1) the multi-scale convolutional kernel provides the multi-context for image super-resolution, and (2) the maximum competitive strategy adaptively chooses the optimal scale of information for image reconstruction. Our experimental results on image super-resolution show that the performance of the proposed network outperforms the state-of-the-art methods.

Isointense infant brain MRI segmentation with a dilated convolutional neural network

NARCIS (Netherlands)

Moeskops, P.; Pluim, J.P.W.

2017-01-01

Quantitative analysis of brain MRI at the age of 6 months is difficult because of the limited contrast between white matter and gray matter. In this study, we use a dilated triplanar convolutional neural network in combination with a non-dilated 3D convolutional neural network for the segmentation

Nuclear norm regularized convolutional Max Pos@Top machine

KAUST Repository

Li, Qinfeng

2016-11-18

In this paper, we propose a novel classification model for the multiple instance data, which aims to maximize the number of positive instances ranked before the top-ranked negative instances. This method belongs to a recently emerged performance, named as Pos@Top. Our proposed classification model has a convolutional structure that is composed by four layers, i.e., the convolutional layer, the activation layer, the max-pooling layer and the full connection layer. In this paper, we propose an algorithm to learn the convolutional filters and the full connection weights to maximize the Pos@Top measure over the training set. Also, we try to minimize the rank of the filter matrix to explore the low-dimensional space of the instances in conjunction with the classification results. The rank minimization is conducted by the nuclear norm minimization of the filter matrix. In addition, we develop an iterative algorithm to solve the corresponding problem. We test our method on several benchmark datasets. The experimental results show the superiority of our method compared with other state-of-the-art Pos@Top maximization methods.

Cone photoreceptor structure in patients with x-linked cone dysfunction and red-green color vision deficiency

DEFF Research Database (Denmark)

Patterson, Emily J.; Wilk, Melissa; Langlo, Christopher S.

2016-01-01

encoded by exon 4, and two with a novel insertion in exon 2. Foveal cone structure and retinal thickness was disrupted to a variable degree, even among related individuals with the same L/M array. CONCLUSIONS. Our findings provide a direct link between disruption of the cone mosaic and L/ M opsin variants......PURPOSE. Mutations in the coding sequence of the L and M opsin genes are often associated with X-linked cone dysfunction (such as Bornholm Eye Disease, BED), though the exact color vision phenotype associated with these disorders is variable. We examined individuals with L/ M opsin gene mutations...... to clarify the link between color vision deficiency and cone dysfunction.  METHODS. We recruited 17 males for imaging. The thickness and integrity of the photoreceptor layers were evaluated using spectral-domain optical coherence tomography. Cone density was measured using high-resolution images of the cone...

The NLO jet vertex in the small-cone approximation for kt and cone algorithms

International Nuclear Information System (INIS)

Colferai, D.; Niccoli, A.

2015-01-01

We determine the jet vertex for Mueller-Navelet jets and forward jets in the small-cone approximation for two particular choices of jet algoritms: the kt algorithm and the cone algorithm. These choices are motivated by the extensive use of such algorithms in the phenomenology of jets. The differences with the original calculations of the small-cone jet vertex by Ivanov and Papa, which is found to be equivalent to a formerly algorithm proposed by Furman, are shown at both analytic and numerical level, and turn out to be sizeable. A detailed numerical study of the error introduced by the small-cone approximation is also presented, for various observables of phenomenological interest. For values of the jet “radius” R=0.5, the use of the small-cone approximation amounts to an error of about 5% at the level of cross section, while it reduces to less than 2% for ratios of distributions such as those involved in the measure of the azimuthal decorrelation of dijets.

The NLO jet vertex in the small-cone approximation for kt and cone algorithms

Energy Technology Data Exchange (ETDEWEB)

Colferai, D.; Niccoli, A. [Dipartimento di Fisica e Astronomia, Università di Firenze and INFN, Sezione di Firenze, 50019 Sesto Fiorentino (Italy)

2015-04-15

We determine the jet vertex for Mueller-Navelet jets and forward jets in the small-cone approximation for two particular choices of jet algoritms: the kt algorithm and the cone algorithm. These choices are motivated by the extensive use of such algorithms in the phenomenology of jets. The differences with the original calculations of the small-cone jet vertex by Ivanov and Papa, which is found to be equivalent to a formerly algorithm proposed by Furman, are shown at both analytic and numerical level, and turn out to be sizeable. A detailed numerical study of the error introduced by the small-cone approximation is also presented, for various observables of phenomenological interest. For values of the jet “radius” R=0.5, the use of the small-cone approximation amounts to an error of about 5% at the level of cross section, while it reduces to less than 2% for ratios of distributions such as those involved in the measure of the azimuthal decorrelation of dijets.

A digital pixel cell for address event representation image convolution processing

Science.gov (United States)

Camunas-Mesa, Luis; Acosta-Jimenez, Antonio; Serrano-Gotarredona, Teresa; Linares-Barranco, Bernabe

2005-06-01

Address Event Representation (AER) is an emergent neuromorphic interchip communication protocol that allows for real-time virtual massive connectivity between huge number of neurons located on different chips. By exploiting high speed digital communication circuits (with nano-seconds timings), synaptic neural connections can be time multiplexed, while neural activity signals (with mili-seconds timings) are sampled at low frequencies. Also, neurons generate events according to their information levels. Neurons with more information (activity, derivative of activities, contrast, motion, edges,...) generate more events per unit time, and access the interchip communication channel more frequently, while neurons with low activity consume less communication bandwidth. AER technology has been used and reported for the implementation of various type of image sensors or retinae: luminance with local agc, contrast retinae, motion retinae,... Also, there has been a proposal for realizing programmable kernel image convolution chips. Such convolution chips would contain an array of pixels that perform weighted addition of events. Once a pixel has added sufficient event contributions to reach a fixed threshold, the pixel fires an event, which is then routed out of the chip for further processing. Such convolution chips have been proposed to be implemented using pulsed current mode mixed analog and digital circuit techniques. In this paper we present a fully digital pixel implementation to perform the weighted additions and fire the events. This way, for a given technology, there is a fully digital implementation reference against which compare the mixed signal implementations. We have designed, implemented and tested a fully digital AER convolution pixel. This pixel will be used to implement a full AER convolution chip for programmable kernel image convolution processing.

QCD on the light cone

International Nuclear Information System (INIS)

Brodsky, S.J.

1992-09-01

The quantization of gauge theory at fixed light-cone time τ = t - z/c provides new perspectives for solving non-perturbative problems in quantum chromodynamics. The light-cone Fock state expansion provides both a precise definition of the relativistic wavefunctions of hadrons as bound-states of quarks and gluons and a general calculus for predicting QCD processes at the amplitude level. Applications to exclusive processes and weak decay amplitudes are discussed. The problem of computing the hadronic spectrum and the corresponding light-cone wavefunctions of QCD in one space and one time dimension has been successfully reduced to the diagonalization of a discrete representation of the light-cone Hamiltonian. The problems confronting the solution of gauge theories in 3 + 1 dimensions in the light-cone quantization formalism,, including zero modes and non-perturbative renormalization, are reviewed

Verification of an algorithm of cono collapsed through the IAEA TECDOC 1583 protocol and dosimetry with radiochromic films; Verificacion de un algoritmo de cono colapso mediante en protocolo IAEA TECDOC 1583 y dosimetria con peliculas radiocromicas

Energy Technology Data Exchange (ETDEWEB)

Martin-Viera Cueto, J. A.; Benitez Villegas, E. M.; Bodineau Gil, C.; Parra Osorio, V.; Garcia Pareja, S.; Casado Villalon, F. J.

2013-07-01

The objective of this study is to verify the characterization of the collapsed cone algorithm of an SP using this Protocol. In addition, given that it only offers details of dose values measured at discrete points, measures are complemented by a gamma test distributions 2D of doses in different cases using film radiochromic. (Author)

A convolutional neural network neutrino event classifier

International Nuclear Information System (INIS)

Aurisano, A.; Sousa, A.; Radovic, A.; Vahle, P.; Rocco, D.; Pawloski, G.; Himmel, A.; Niner, E.; Messier, M.D.; Psihas, F.

2016-01-01

Convolutional neural networks (CNNs) have been widely applied in the computer vision community to solve complex problems in image recognition and analysis. We describe an application of the CNN technology to the problem of identifying particle interactions in sampling calorimeters used commonly in high energy physics and high energy neutrino physics in particular. Following a discussion of the core concepts of CNNs and recent innovations in CNN architectures related to the field of deep learning, we outline a specific application to the NOvA neutrino detector. This algorithm, CVN (Convolutional Visual Network) identifies neutrino interactions based on their topology without the need for detailed reconstruction and outperforms algorithms currently in use by the NOvA collaboration.

The convolution transform

CERN Document Server

Hirschman, Isidore Isaac

2005-01-01

In studies of general operators of the same nature, general convolution transforms are immediately encountered as the objects of inversion. The relation between differential operators and integral transforms is the basic theme of this work, which is geared toward upper-level undergraduates and graduate students. It may be read easily by anyone with a working knowledge of real and complex variable theory. Topics include the finite and non-finite kernels, variation diminishing transforms, asymptotic behavior of kernels, real inversion theory, representation theory, the Weierstrass transform, and

NMNAT1 variants cause cone and cone-rod dystrophy.

Science.gov (United States)

Nash, Benjamin M; Symes, Richard; Goel, Himanshu; Dinger, Marcel E; Bennetts, Bruce; Grigg, John R; Jamieson, Robyn V

2018-03-01

Cone and cone-rod dystrophies (CD and CRD, respectively) are degenerative retinal diseases that predominantly affect the cone photoreceptors. The underlying disease gene is not known in approximately 75% of autosomal recessive cases. Variants in NMNAT1 cause a severe, early-onset retinal dystrophy called Leber congenital amaurosis (LCA). We report two patients where clinical phenotyping indicated diagnoses of CD and CRD, respectively. NMNAT1 variants were identified, with Case 1 showing an extremely rare homozygous variant c.[271G > A] p.(Glu91Lys) and Case 2 compound heterozygous variants c.[53 A > G];[769G > A] p.(Asn18Ser);(Glu257Lys). The detailed variant analysis, in combination with the observation of an associated macular atrophy phenotype, indicated that these variants were disease-causing. This report demonstrates that the variants in NMNAT1 may cause CD or CRD associated with macular atrophy. Genetic investigations of the patients with CD or CRD should include NMNAT1 in the genes examined.

Off-resonance artifacts correction with convolution in k-space (ORACLE).

Science.gov (United States)

Lin, Wei; Huang, Feng; Simonotto, Enrico; Duensing, George R; Reykowski, Arne

2012-06-01

Off-resonance artifacts hinder the wider applicability of echo-planar imaging and non-Cartesian MRI methods such as radial and spiral. In this work, a general and rapid method is proposed for off-resonance artifacts correction based on data convolution in k-space. The acquired k-space is divided into multiple segments based on their acquisition times. Off-resonance-induced artifact within each segment is removed by applying a convolution kernel, which is the Fourier transform of an off-resonance correcting spatial phase modulation term. The field map is determined from the inverse Fourier transform of a basis kernel, which is calibrated from data fitting in k-space. The technique was demonstrated in phantom and in vivo studies for radial, spiral and echo-planar imaging datasets. For radial acquisitions, the proposed method allows the self-calibration of the field map from the imaging data, when an alternating view-angle ordering scheme is used. An additional advantage for off-resonance artifacts correction based on data convolution in k-space is the reusability of convolution kernels to images acquired with the same sequence but different contrasts. Copyright © 2011 Wiley-Liss, Inc.

Minimal-memory realization of pearl-necklace encoders of general quantum convolutional codes

International Nuclear Information System (INIS)

Houshmand, Monireh; Hosseini-Khayat, Saied

2011-01-01

Quantum convolutional codes, like their classical counterparts, promise to offer higher error correction performance than block codes of equivalent encoding complexity, and are expected to find important applications in reliable quantum communication where a continuous stream of qubits is transmitted. Grassl and Roetteler devised an algorithm to encode a quantum convolutional code with a ''pearl-necklace'' encoder. Despite their algorithm's theoretical significance as a neat way of representing quantum convolutional codes, it is not well suited to practical realization. In fact, there is no straightforward way to implement any given pearl-necklace structure. This paper closes the gap between theoretical representation and practical implementation. In our previous work, we presented an efficient algorithm to find a minimal-memory realization of a pearl-necklace encoder for Calderbank-Shor-Steane (CSS) convolutional codes. This work is an extension of our previous work and presents an algorithm for turning a pearl-necklace encoder for a general (non-CSS) quantum convolutional code into a realizable quantum convolutional encoder. We show that a minimal-memory realization depends on the commutativity relations between the gate strings in the pearl-necklace encoder. We find a realization by means of a weighted graph which details the noncommutative paths through the pearl necklace. The weight of the longest path in this graph is equal to the minimal amount of memory needed to implement the encoder. The algorithm has a polynomial-time complexity in the number of gate strings in the pearl-necklace encoder.

Spherical dust collapse in higher dimensions

International Nuclear Information System (INIS)

Goswami, Rituparno; Joshi, Pankaj S.

2004-01-01

We consider here whether it is possible to recover cosmic censorship when a transition is made to higher-dimensional spacetimes, by studying the spherically symmetric dust collapse in an arbitrary higher spacetime dimension. It is pointed out that if only black holes are to result as the end state of a continual gravitational collapse, several conditions must be imposed on the collapsing configuration, some of which may appear to be restrictive, and we need to study carefully if these can be suitably motivated physically in a realistic collapse scenario. It would appear, that, in a generic higher-dimensional dust collapse, both black holes and naked singularities would develop as end states as indicated by the results here. The mathematical approach developed here generalizes and unifies the earlier available results on higher-dimensional dust collapse as we point out. Further, the dependence of black hole or naked singularity end states as collapse outcomes on the nature of the initial data from which the collapse develops is brought out explicitly and in a transparent manner as we show here. Our method also allows us to consider here in some detail the genericity and stability aspects related to the occurrence of naked singularities in gravitational collapse

Spherically symmetric radiation in gravitational collapse

International Nuclear Information System (INIS)

Bridy, D.J.

1983-01-01

This paper investigates a previously neglected mode by which a star may lose energy in the late stages of gravitational collapse to the black hole state. A model consisting of a Schwarzschild exterior matched to a Friedman interior of collapsing pressureless dust is studied. The matter of the collapsing star is taken as the source of a massive vector boson field and a detailed boundary value problem is carried out. Vector mesons are strongly coupled to all nucleons and will be radiated by ordinary matter during the collapse. The time dependent coupling between interior and exterior modes matched across the moving boundary of the collapsing star and the presence of the gravitational fields and their gradients in the field equations may give rise to a parametric amplification mechanism and permit the gravitational field to pump energy into the boson field, greatly enhancing the amount of boson radiation. The significance of a radiative mechanism driven by collapse is that it can react back upon the collapsing source and deprive it of some of the very mass that drives the collapse via its self gravitation. If the mass loss is great enough, this may provide a mechanism to slow or even halt gravitational collapse in some cases

Applying Gradient Descent in Convolutional Neural Networks

Science.gov (United States)

Cui, Nan

2018-04-01

With the development of the integrated circuit and computer science, people become caring more about solving practical issues via information technologies. Along with that, a new subject called Artificial Intelligent (AI) comes up. One popular research interest of AI is about recognition algorithm. In this paper, one of the most common algorithms, Convolutional Neural Networks (CNNs) will be introduced, for image recognition. Understanding its theory and structure is of great significance for every scholar who is interested in this field. Convolution Neural Network is an artificial neural network which combines the mathematical method of convolution and neural network. The hieratical structure of CNN provides it reliable computer speed and reasonable error rate. The most significant characteristics of CNNs are feature extraction, weight sharing and dimension reduction. Meanwhile, combining with the Back Propagation (BP) mechanism and the Gradient Descent (GD) method, CNNs has the ability to self-study and in-depth learning. Basically, BP provides an opportunity for backwardfeedback for enhancing reliability and GD is used for self-training process. This paper mainly discusses the CNN and the related BP and GD algorithms, including the basic structure and function of CNN, details of each layer, the principles and features of BP and GD, and some examples in practice with a summary in the end.

On the dosimetric behaviour of photon dose calculation algorithms in the presence of simple geometric heterogeneities: comparison with Monte Carlo calculations

Science.gov (United States)

Fogliata, Antonella; Vanetti, Eugenio; Albers, Dirk; Brink, Carsten; Clivio, Alessandro; Knöös, Tommy; Nicolini, Giorgia; Cozzi, Luca

2007-03-01

A comparative study was performed to reveal differences and relative figures of merit of seven different calculation algorithms for photon beams when applied to inhomogeneous media. The following algorithms were investigated: Varian Eclipse: the anisotropic analytical algorithm, and the pencil beam with modified Batho correction; Nucletron Helax-TMS: the collapsed cone and the pencil beam with equivalent path length correction; CMS XiO: the multigrid superposition and the fast Fourier transform convolution; Philips Pinnacle: the collapsed cone. Monte Carlo simulations (MC) performed with the EGSnrc codes BEAMnrc and DOSxyznrc from NRCC in Ottawa were used as a benchmark. The study was carried out in simple geometrical water phantoms (ρ = 1.00 g cm-3) with inserts of different densities simulating light lung tissue (ρ = 0.035 g cm-3), normal lung (ρ = 0.20 g cm-3) and cortical bone tissue (ρ = 1.80 g cm-3). Experiments were performed for low- and high-energy photon beams (6 and 15 MV) and for square (13 × 13 cm2) and elongated rectangular (2.8 × 13 cm2) fields. Analysis was carried out on the basis of depth dose curves and transverse profiles at several depths. Assuming the MC data as reference, γ index analysis was carried out distinguishing between regions inside the non-water inserts or inside the uniform water. For this study, a distance to agreement was set to 3 mm while the dose difference varied from 2% to 10%. In general all algorithms based on pencil-beam convolutions showed a systematic deficiency in managing the presence of heterogeneous media. In contrast, complicated patterns were observed for the advanced algorithms with significant discrepancies observed between algorithms in the lighter materials (ρ = 0.035 g cm-3), enhanced for the most energetic beam. For denser, and more clinical, densities a better agreement among the sophisticated algorithms with respect to MC was observed.

Spherical Collapse in Chameleon Models

CERN Document Server

Brax, Ph; Steer, D A

2010-01-01

We study the gravitational collapse of an overdensity of nonrelativistic matter under the action of gravity and a chameleon scalar field. We show that the spherical collapse model is modified by the presence of a chameleon field. In particular, we find that even though the chameleon effects can be potentially large at small scales, for a large enough initial size of the inhomogeneity the collapsing region possesses a thin shell that shields the modification of gravity induced by the chameleon field, recovering the standard gravity results. We analyse the behaviour of a collapsing shell in a cosmological setting in the presence of a thin shell and find that, in contrast to the usual case, the critical density for collapse depends on the initial comoving size of the inhomogeneity.

Spherical collapse in chameleon models

Energy Technology Data Exchange (ETDEWEB)

Brax, Ph. [Institut de Physique Théorique, CEA, IPhT, CNRS, URA 2306, F-91191Gif/Yvette Cedex (France); Rosenfeld, R. [Instituto de Física Teórica, Universidade Estadual Paulista, Rua Dr. Bento T. Ferraz, 271, 01140-070, São Paulo (Brazil); Steer, D.A., E-mail: brax@spht.saclay.cea.fr, E-mail: rosenfel@ift.unesp.br, E-mail: daniele.steer@apc.univ-paris7.fr [APC, UMR 7164, CNRS, Université Paris 7, 10 rue Alice Domon et Léonie Duquet, 75205 Paris Cedex 13 (France)

2010-08-01

We study the gravitational collapse of an overdensity of nonrelativistic matter under the action of gravity and a chameleon scalar field. We show that the spherical collapse model is modified by the presence of a chameleon field. In particular, we find that even though the chameleon effects can be potentially large at small scales, for a large enough initial size of the inhomogeneity the collapsing region possesses a thin shell that shields the modification of gravity induced by the chameleon field, recovering the standard gravity results. We analyse the behaviour of a collapsing shell in a cosmological setting in the presence of a thin shell and find that, in contrast to the usual case, the critical density for collapse in principle depends on the initial comoving size of the inhomogeneity.

Spherical collapse in chameleon models

International Nuclear Information System (INIS)

Brax, Ph.; Rosenfeld, R.; Steer, D.A.

2010-01-01

We study the gravitational collapse of an overdensity of nonrelativistic matter under the action of gravity and a chameleon scalar field. We show that the spherical collapse model is modified by the presence of a chameleon field. In particular, we find that even though the chameleon effects can be potentially large at small scales, for a large enough initial size of the inhomogeneity the collapsing region possesses a thin shell that shields the modification of gravity induced by the chameleon field, recovering the standard gravity results. We analyse the behaviour of a collapsing shell in a cosmological setting in the presence of a thin shell and find that, in contrast to the usual case, the critical density for collapse in principle depends on the initial comoving size of the inhomogeneity

Tracheal collapse in two cats

International Nuclear Information System (INIS)

Hendricks, J.C.; O'Brien, J.A.

1985-01-01

Two cats examined bronchoscopically to discover the cause of tracheal collapse were found to have tracheal obstruction cranial to the collapse. Cats with this unusual sign should be examined bronchoscopically to ascertain whether there is an obstruction, as the cause in these 2 cats was distinct from the diffuse airway abnormality that causes tracheal collapse in dogs

Efficient airport detection using region-based fully convolutional neural networks

Science.gov (United States)

Xin, Peng; Xu, Yuelei; Zhang, Xulei; Ma, Shiping; Li, Shuai; Lv, Chao

2018-04-01

This paper presents a model for airport detection using region-based fully convolutional neural networks. To achieve fast detection with high accuracy, we shared the conv layers between the region proposal procedure and the airport detection procedure and used graphics processing units (GPUs) to speed up the training and testing time. For lack of labeled data, we transferred the convolutional layers of ZF net pretrained by ImageNet to initialize the shared convolutional layers, then we retrained the model using the alternating optimization training strategy. The proposed model has been tested on an airport dataset consisting of 600 images. Experiments show that the proposed method can distinguish airports in our dataset from similar background scenes almost real-time with high accuracy, which is much better than traditional methods.

STELLAR TIDAL DISRUPTION EVENTS BY DIRECT-COLLAPSE BLACK HOLES

Energy Technology Data Exchange (ETDEWEB)

Kashiyama, Kazumi [Theoretical Astrophysics Center, Department of Astronomy, University of California, Berkeley, Berkeley, CA 94720 (United States); Inayoshi, Kohei, E-mail: kashiyama@berkeley.edu, E-mail: inayoshi@astro.columbia.edu [Department of Astronomy, Columbia University, 550 West 120th Street, New York, NY 10027 (United States)

2016-07-20

We analyze the early growth stage of direct-collapse black holes (DCBHs) with ∼10{sup 5} M {sub ⊙}, which are formed by collapse of supermassive stars in atomic-cooling halos at z ≳ 10. A nuclear accretion disk around a newborn DCBH is gravitationally unstable and fragments into clumps with a few × 10 M {sub ⊙} at ∼0.01–0.1 pc from the center. Such clumps evolve into massive Population III stars with a few × 10–10{sup 2} M {sub ⊙} via successive gas accretion, and a nuclear star cluster is formed. Radiative and mechanical feedback from an inner slim disk and the star cluster will significantly reduce the gas accretion rate onto the DCBH within ∼10{sup 6} yr. Some of the nuclear stars can be scattered onto the loss cone orbits also within ≲10{sup 6} yr and tidally disrupted by the central DCBH. The jet luminosity powered by such tidal disruption events can be L {sub j} ≳ 10{sup 50} erg s{sup 1}. The prompt emission will be observed in X-ray bands with a peak duration of δt {sub obs} ∼ 10{sup 5–6}(1 + z ) s followed by a tail ∝ t {sub obs} {sup 5/3}, which can be detectable by Swift BAT and eROSITA even from z ∼ 20. Follow-up observations of the radio afterglows with, e.g., eVLA and the host halos with James Webb Space Telescope could probe the earliest active galactic nucleus feedback from DCBHs.

Solutions to Arithmetic Convolution Equations

Czech Academy of Sciences Publication Activity Database

Glöckner, H.; Lucht, L.G.; Porubský, Štefan

2007-01-01

Roč. 135, č. 6 (2007), s. 1619-1629 ISSN 0002-9939 R&D Projects: GA ČR GA201/04/0381 Institutional research plan: CEZ:AV0Z10300504 Keywords : arithmetic functions * Dirichlet convolution * polynomial equations * analytic equations * topological algebras * holomorphic functional calculus Subject RIV: BA - General Mathematics Impact factor: 0.520, year: 2007

Mach cones in space and laboratory dusty magnetoplasmas

International Nuclear Information System (INIS)

Mamun, A.A.; Shukla, P.K

2004-07-01

We present a rigorous theoretical investigation on the possibility for the formation of Mach cones in both space and laboratory dusty magnetoplasmas. We find the parametric regimes for which different types of Mach cones, such as dust acoustic Mach cones, dust magneto-acoustic Mach cones, oscillonic Mach cones, etc. are formed in space and laboratory dusty magnetoplasmas. We also identify the basic features of such different classes of Mach cones (viz. dust- acoustic, dust magneto-acoustic, oscillonic Mach cones, etc.), and clearly explain how they are relevant to space and laboratory dusty manetoplasmas. (author)

Gas Classification Using Deep Convolutional Neural Networks

Science.gov (United States)

Peng, Pai; Zhao, Xiaojin; Pan, Xiaofang; Ye, Wenbin

2018-01-01

In this work, we propose a novel Deep Convolutional Neural Network (DCNN) tailored for gas classification. Inspired by the great success of DCNN in the field of computer vision, we designed a DCNN with up to 38 layers. In general, the proposed gas neural network, named GasNet, consists of: six convolutional blocks, each block consist of six layers; a pooling layer; and a fully-connected layer. Together, these various layers make up a powerful deep model for gas classification. Experimental results show that the proposed DCNN method is an effective technique for classifying electronic nose data. We also demonstrate that the DCNN method can provide higher classification accuracy than comparable Support Vector Machine (SVM) methods and Multiple Layer Perceptron (MLP). PMID:29316723

Gas Classification Using Deep Convolutional Neural Networks.

Science.gov (United States)

Peng, Pai; Zhao, Xiaojin; Pan, Xiaofang; Ye, Wenbin

2018-01-08

In this work, we propose a novel Deep Convolutional Neural Network (DCNN) tailored for gas classification. Inspired by the great success of DCNN in the field of computer vision, we designed a DCNN with up to 38 layers. In general, the proposed gas neural network, named GasNet, consists of: six convolutional blocks, each block consist of six layers; a pooling layer; and a fully-connected layer. Together, these various layers make up a powerful deep model for gas classification. Experimental results show that the proposed DCNN method is an effective technique for classifying electronic nose data. We also demonstrate that the DCNN method can provide higher classification accuracy than comparable Support Vector Machine (SVM) methods and Multiple Layer Perceptron (MLP).

Clinical Course, Genetic Etiology, and Visual Outcome in Cone and Cone-Rod Dystrophy

NARCIS (Netherlands)

Thiadens, Alberta A. H. J.; Phan, T. My Lan; Zekveld-Vroon, Renate C.; Leroy, Bart P.; van den Born, L. Ingeborgh; Hoyng, Carel B.; Klaver, Caroline C. W.; Roosing, Susanne; Pott, Jan-Willem R.; van Schooneveld, Mary J.; van Moll-Ramirez, Norka; van Genderen, Maria M.; Boon, Camiel J. F.; den Hollander, Anneke I.; Bergen, Arthur A. B.; De Baere, Elfride; Cremers, Frans P. M.; Lotery, Andrew J.

Objective: To evaluate the clinical course, genetic etiology, and visual prognosis in patients with cone dystrophy (CD) and cone-rod dystrophy (CRD). Design: Clinic-based, longitudinal, multicenter study. Participants: Consecutive probands with CD (N = 98), CRD (N = 83), and affected relatives (N =

State-of-the-Art-Review of Collapsible Soils

Directory of Open Access Journals (Sweden)

A. A. AL-Rawas

2000-12-01

Full Text Available Collapsible soils are encountered in arid and semi-arid regions. Such soils cause potential construction problems due to their collapse upon wetting. The collapse phenomenon is primarily related to the open structure of the soil. Several soil collapse classifications based on parameters such as moisture content, dry density, Atterberg limits and clay content have been proposed in the literature as indicators of the soil collapse potential. Direct measurement of the magnitude of collapse, using laboratory and/or field tests, is essential once a soil showed indications of collapse potential. Treatment methods such as soil replacement, compaction control and chemical stabilization showed significant reduction in the settlement of collapsible soils. The design of foundations on collapsible soils depends on the depth of the soil, magnitude of collapse and economics of the design. Strip foundations are commonly used when collapsing soil extends to a shallow depth while piles and drilled piers are recommended in cases where the soil extends to several meters. This paper provides a comprehensive review of collapsible soils. These include the different types of collapsible soils, mechanisms of collapse, identification and classification methods, laboratory and field testing, treatment methods and guidelines for foundation design.

Linear diffusion-wave channel routing using a discrete Hayami convolution method

Science.gov (United States)

Li Wang; Joan Q. Wu; William J. Elliot; Fritz R. Feidler; Sergey. Lapin

2014-01-01

The convolution of an input with a response function has been widely used in hydrology as a means to solve various problems analytically. Due to the high computation demand in solving the functions using numerical integration, it is often advantageous to use the discrete convolution instead of the integration of the continuous functions. This approach greatly reduces...

Convolution equations on lattices: periodic solutions with values in a prime characteristic field

OpenAIRE

Zaidenberg, Mikhail

2006-01-01

These notes are inspired by the theory of cellular automata. A linear cellular automaton on a lattice of finite rank or on a toric grid is a discrete dinamical system generated by a convolution operator with kernel concentrated in the nearest neighborhood of the origin. In the present paper we deal with general convolution operators. We propose an approach via harmonic analysis which works over a field of positive characteristic. It occurs that a standard spectral problem for a convolution op...

Development and degeneration of cone bipolar cells are independent of cone photoreceptors in a mouse model of retinitis pigmentosa.

Directory of Open Access Journals (Sweden)

Miao Chen

Full Text Available Retinal photoreceptors die during retinal synaptogenesis in a portion of retinal degeneration. Whether cone bipolar cells establish regular retinal mosaics and mature morphologies, and resist degeneration are not completely understood. To explore these issues, we backcrossed a transgenic mouse expressing enhanced green fluorescent protein (EGFP in one subset of cone bipolar cells (type 7 into rd1 mice, a classic mouse model of retinal degeneration, to examine the development and survival of cone bipolar cells in a background of retinal degeneration. Our data revealed that both the development and degeneration of cone bipolar cells are independent of the normal activity of cone photoreceptors. We found that type 7 cone bipolar cells achieved a uniform tiling of the retinal surface and developed normal dendritic and axonal arbors without the influence of cone photoreceptor innervation. On the other hand, degeneration of type 7 cone bipolar cells, contrary to our belief of central-to-peripheral progression, was spatially uniform across the retina independent of the spatiotemporal pattern of cone degeneration. The results have important implications for the design of more effective therapies to restore vision in retinal degeneration.

Collapse of large extra dimensions

International Nuclear Information System (INIS)

Geddes, James

2002-01-01

In models of spacetime that are the product of a four-dimensional spacetime with an 'extra' dimension, there is the possibility that the extra dimension will collapse to zero size, forming a singularity. We ask whether this collapse is likely to destroy the spacetime. We argue, by an appeal to the four-dimensional cosmic censorship conjecture, that--at least in the case when the extra dimension is homogeneous--such a collapse will lead to a singularity hidden within a black string. We also construct explicit initial data for a spacetime in which such a collapse is guaranteed to occur and show how the formation of a naked singularity is likely avoided

Design of a trichromatic cone array.

Directory of Open Access Journals (Sweden)

Patrick Garrigan

2010-02-01

Full Text Available Cones with peak sensitivity to light at long (L, medium (M and short (S wavelengths are unequal in number on the human retina: S cones are rare (<10% while increasing in fraction from center to periphery, and the L/M cone proportions are highly variable between individuals. What optical properties of the eye, and statistical properties of natural scenes, might drive this organization? We found that the spatial-chromatic structure of natural scenes was largely symmetric between the L, M and S sensitivity bands. Given this symmetry, short wavelength attenuation by ocular media gave L/M cones a modest signal-to-noise advantage, which was amplified, especially in the denser central retina, by long-wavelength accommodation of the lens. Meanwhile, total information represented by the cone mosaic remained relatively insensitive to L/M proportions. Thus, the observed cone array design along with a long-wavelength accommodated lens provides a selective advantage: it is maximally informative.

Cylindrical collapse and gravitational waves

Energy Technology Data Exchange (ETDEWEB)

Herrera, L [Escuela de FIsica, Faculdad de Ciencias, Universidad Central de Venezuela, Caracas, Venezuela (Venezuela); Santos, N O [Universite Pierre et Marie Curie, CNRS/FRE 2460 LERMA/ERGA, Tour 22-12, 4eme etage, BoIte 142, 4 place Jussieu, 75252 Paris Cedex 05 (France); Laboratorio Nacional de Computacao Cientifica, 25651-070 Petropolis RJ (Brazil); Centro Brasileiro de Pesquisas Fisicas, 22290-180 Rio de Janeiro RJ (Brazil)

2005-06-21

We study the matching conditions for a collapsing anisotropic cylindrical perfect fluid, and we show that its radial pressure is non-zero on the surface of the cylinder and proportional to the time-dependent part of the field produced by the collapsing fluid. This result resembles the one that arises for the radiation-though non-gravitational-in the spherically symmetric collapsing dissipative fluid, in the diffusion approximation.

AFM tip-sample convolution effects for cylinder protrusions

Science.gov (United States)

Shen, Jian; Zhang, Dan; Zhang, Fei-Hu; Gan, Yang

2017-11-01

A thorough understanding about the AFM tip geometry dependent artifacts and tip-sample convolution effect is essential for reliable AFM topographic characterization and dimensional metrology. Using rigid sapphire cylinder protrusions (diameter: 2.25 μm, height: 575 nm) as the model system, a systematic and quantitative study about the imaging artifacts of four types of tips-two different pyramidal tips, one tetrahedral tip and one super sharp whisker tip-is carried out through comparing tip geometry dependent variations in AFM topography of cylinders and constructing the rigid tip-cylinder convolution models. We found that the imaging artifacts and the tip-sample convolution effect are critically related to the actual inclination of the working cantilever, the tip geometry, and the obstructive contacts between the working tip's planes/edges and the cylinder. Artifact-free images can only be obtained provided that all planes and edges of the working tip are steeper than the cylinder sidewalls. The findings reported here will contribute to reliable AFM characterization of surface features of micron or hundreds of nanometers in height that are frequently met in semiconductor, biology and materials fields.

Limitations of a convolution method for modeling geometric uncertainties in radiation therapy. I. The effect of shift invariance

International Nuclear Information System (INIS)

Craig, Tim; Battista, Jerry; Van Dyk, Jake

2003-01-01

Convolution methods have been used to model the effect of geometric uncertainties on dose delivery in radiation therapy. Convolution assumes shift invariance of the dose distribution. Internal inhomogeneities and surface curvature lead to violations of this assumption. The magnitude of the error resulting from violation of shift invariance is not well documented. This issue is addressed by comparing dose distributions calculated using the Convolution method with dose distributions obtained by Direct Simulation. A comparison of conventional Static dose distributions was also made with Direct Simulation. This analysis was performed for phantom geometries and several clinical tumor sites. A modification to the Convolution method to correct for some of the inherent errors is proposed and tested using example phantoms and patients. We refer to this modified method as the Corrected Convolution. The average maximum dose error in the calculated volume (averaged over different beam arrangements in the various phantom examples) was 21% with the Static dose calculation, 9% with Convolution, and reduced to 5% with the Corrected Convolution. The average maximum dose error in the calculated volume (averaged over four clinical examples) was 9% for the Static method, 13% for Convolution, and 3% for Corrected Convolution. While Convolution can provide a superior estimate of the dose delivered when geometric uncertainties are present, the violation of shift invariance can result in substantial errors near the surface of the patient. The proposed Corrected Convolution modification reduces errors near the surface to 3% or less

Cone and Seed Maturation of Southern Pines

Science.gov (United States)

James P. Barnett

1976-01-01

If slightly reduced yields and viability are acceptable, loblolly and slash cone collections can begin 2 to 3 weeks before maturity if the cones are stored before processing. Longleaf(P. palestris Mill.) pine cones should be collected only when mature, as storage decreased germination of seeds from immature cones. Biochemical analyses to determine reducing sugar...

Collapse models with non-white noises

International Nuclear Information System (INIS)

Adler, Stephen L; Bassi, Angelo

2007-01-01

We set up a general formalism for models of spontaneous wavefunction collapse with dynamics represented by a stochastic differential equation driven by general Gaussian noises, not necessarily white in time. In particular, we show that the non-Schroedinger terms of the equation induce the collapse of the wavefunction to one of the common eigenstates of the collapsing operators, and that the collapse occurs with the correct quantum probabilities. We also develop a perturbation expansion of the solution of the equation with respect to the parameter which sets the strength of the collapse process; such an approximation allows one to compute the leading-order terms for the deviations of the predictions of collapse models with respect to those of standard quantum mechanics. This analysis shows that to leading order, the 'imaginary noise' trick can be used for non-white Gaussian noise

Spectral interpolation - Zero fill or convolution. [image processing

Science.gov (United States)

Forman, M. L.

1977-01-01

Zero fill, or augmentation by zeros, is a method used in conjunction with fast Fourier transforms to obtain spectral spacing at intervals closer than obtainable from the original input data set. In the present paper, an interpolation technique (interpolation by repetitive convolution) is proposed which yields values accurate enough for plotting purposes and which lie within the limits of calibration accuracies. The technique is shown to operate faster than zero fill, since fewer operations are required. The major advantages of interpolation by repetitive convolution are that efficient use of memory is possible (thus avoiding the difficulties encountered in decimation in time FFTs) and that is is easy to implement.

Image quality assessment using deep convolutional networks

Science.gov (United States)

Li, Yezhou; Ye, Xiang; Li, Yong

2017-12-01

This paper proposes a method of accurately assessing image quality without a reference image by using a deep convolutional neural network. Existing training based methods usually utilize a compact set of linear filters for learning features of images captured by different sensors to assess their quality. These methods may not be able to learn the semantic features that are intimately related with the features used in human subject assessment. Observing this drawback, this work proposes training a deep convolutional neural network (CNN) with labelled images for image quality assessment. The ReLU in the CNN allows non-linear transformations for extracting high-level image features, providing a more reliable assessment of image quality than linear filters. To enable the neural network to take images of any arbitrary size as input, the spatial pyramid pooling (SPP) is introduced connecting the top convolutional layer and the fully-connected layer. In addition, the SPP makes the CNN robust to object deformations to a certain extent. The proposed method taking an image as input carries out an end-to-end learning process, and outputs the quality of the image. It is tested on public datasets. Experimental results show that it outperforms existing methods by a large margin and can accurately assess the image quality on images taken by different sensors of varying sizes.

Deep Recurrent Convolutional Neural Network: Improving Performance For Speech Recognition

OpenAIRE

Zhang, Zewang; Sun, Zheng; Liu, Jiaqi; Chen, Jingwen; Huo, Zhao; Zhang, Xiao

2016-01-01

A deep learning approach has been widely applied in sequence modeling problems. In terms of automatic speech recognition (ASR), its performance has significantly been improved by increasing large speech corpus and deeper neural network. Especially, recurrent neural network and deep convolutional neural network have been applied in ASR successfully. Given the arising problem of training speed, we build a novel deep recurrent convolutional network for acoustic modeling and then apply deep resid...

MAP-Based Underdetermined Blind Source Separation of Convolutive Mixtures by Hierarchical Clustering and -Norm Minimization

Directory of Open Access Journals (Sweden)

Kellermann Walter

2007-01-01

Full Text Available We address the problem of underdetermined BSS. While most previous approaches are designed for instantaneous mixtures, we propose a time-frequency-domain algorithm for convolutive mixtures. We adopt a two-step method based on a general maximum a posteriori (MAP approach. In the first step, we estimate the mixing matrix based on hierarchical clustering, assuming that the source signals are sufficiently sparse. The algorithm works directly on the complex-valued data in the time-frequency domain and shows better convergence than algorithms based on self-organizing maps. The assumption of Laplacian priors for the source signals in the second step leads to an algorithm for estimating the source signals. It involves the -norm minimization of complex numbers because of the use of the time-frequency-domain approach. We compare a combinatorial approach initially designed for real numbers with a second-order cone programming (SOCP approach designed for complex numbers. We found that although the former approach is not theoretically justified for complex numbers, its results are comparable to, or even better than, the SOCP solution. The advantage is a lower computational cost for problems with low input/output dimensions.

Weed Growth Stage Estimator Using Deep Convolutional Neural Networks

DEFF Research Database (Denmark)

Teimouri, Nima; Dyrmann, Mads; Nielsen, Per Rydahl

2018-01-01

conditions with regards to soil types, resolution and light settings. Then, 9649 of these images were used for training the computer, which automatically divided the weeds into nine growth classes. The performance of this proposed convolutional neural network approach was evaluated on a further set of 2516...... in estimating the number of leaves and 96% accuracy when accepting a deviation of two leaves. These results show that this new method of using deep convolutional neural networks has a relatively high ability to estimate early growth stages across a wide variety of weed species....

High-resolution simulations of cylindrical void collapse in energetic materials: Effect of primary and secondary collapse on initiation thresholds

Science.gov (United States)

Rai, Nirmal Kumar; Schmidt, Martin J.; Udaykumar, H. S.

2017-04-01

Void collapse in energetic materials leads to hot spot formation and enhanced sensitivity. Much recent work has been directed towards simulation of collapse-generated reactive hot spots. The resolution of voids in calculations to date has varied as have the resulting predictions of hot spot intensity. Here we determine the required resolution for reliable cylindrical void collapse calculations leading to initiation of chemical reactions. High-resolution simulations of collapse provide new insights into the mechanism of hot spot generation. It is found that initiation can occur in two different modes depending on the loading intensity: Either the initiation occurs due to jet impact at the first collapse instant or it can occur at secondary lobes at the periphery of the collapsed void. A key observation is that secondary lobe collapse leads to large local temperatures that initiate reactions. This is due to a combination of a strong blast wave from the site of primary void collapse and strong colliding jets and vortical flows generated during the collapse of the secondary lobes. The secondary lobe collapse results in a significant lowering of the predicted threshold for ignition of the energetic material. The results suggest that mesoscale simulations of void fields may suffer from significant uncertainty in threshold predictions because unresolved calculations cannot capture the secondary lobe collapse phenomenon. The implications of this uncertainty for mesoscale simulations are discussed in this paper.

Predicting mining collapse: Superjerks and the appearance of record-breaking events in coal as collapse precursors

Science.gov (United States)

Jiang, Xiang; Liu, Hanlong; Main, Ian G.; Salje, Ekhard K. H.

2017-08-01

The quest for predictive indicators for the collapse of coal mines has led to a robust criterion from scale-model tests in the laboratory. Mechanical collapse under uniaxial stress forms avalanches with a power-law probability distribution function of radiated energy P ˜E-ɛ , with exponent ɛ =1.5 . Impending major collapse is preceded by a reduction of the energy exponent to the mean-field value ɛ =1.32 . Concurrently, the crackling noise increases in intensity and the waiting time between avalanches is reduced when the major collapse is approaching. These latter criteria were so-far deemed too unreliable for safety assessments in coal mines. We report a reassessment of previously collected extensive collapse data sets using "record-breaking analysis," based on the statistical appearance of "superjerks" within a smaller spectrum of collapse events. Superjerks are defined as avalanche signals with energies that surpass those of all previous events. The final major collapse is one such superjerk but other "near collapse" events equally qualify. In this way a very large data set of events is reduced to a sparse sequence of superjerks (21 in our coal sample). The main collapse can be anticipated from the sequence of energies and waiting times of superjerks, ignoring all weaker events. Superjerks are excellent indicators for the temporal evolution, and reveal clear nonstationarity of the crackling noise at constant loading rate, as well as self-similarity in the energy distribution of superjerks as a function of the number of events so far in the sequence Es j˜nδ with δ =1.79 . They are less robust in identifying the precise time of the final collapse, however, than the shift of the energy exponents in the whole data set which occurs only over a short time interval just before the major event. Nevertheless, they provide additional diagnostics that may increase the reliability of such forecasts.

Spectral characteristics of light sources for S-cone stimulation.

Science.gov (United States)

Schlegelmilch, F; Nolte, R; Schellhorn, K; Husar, P; Henning, G; Tornow, R P

2002-11-01

Electrophysiological investigations of the short-wavelength sensitive pathway of the human eye require the use of a suitable light source as a S-cone stimulator. Different light sources with their spectral distribution properties were investigated and compared with the ideal S-cone stimulator. First, the theoretical background of the calculation of relative cone energy absorption from the spectral distribution function of the light source is summarized. From the results of the calculation, the photometric properties of the ideal S-cone stimulator will be derived. The calculation procedure was applied to virtual light sources (computer generated spectral distribution functions with different medium wavelengths and spectrum widths) and to real light sources (blue and green light emitting diodes, blue phosphor of CRT-monitor, multimedia projector, LCD monitor and notebook display). The calculated relative cone absorbencies are compared to the conditions of an ideal S-cone stimulator. Monochromatic light sources with wavelengths of less than 456 nm are close to the conditions of an ideal S-cone stimulator. Spectrum widths up to 21 nm do not affect the S-cone activation significantly (S-cone activation change < 0.2%). Blue light emitting diodes with peak wavelength at 448 nm and spectrum bandwidth of 25 nm are very useful for S-cone stimulation (S-cone activation approximately 95%). A suitable display for S-cone stimulation is the Trinitron computer monitor (S-cone activation approximately 87%). The multimedia projector has a S-cone activation up to 91%, but their spectral distribution properties depends on the selected intensity. LCD monitor and notebook displays have a lower S-cone activation (< or = 74%). Carefully selecting the blue light source for S-cone stimulation can reduce the unwanted L-and M-cone activation down to 4% for M-cones and 1.5% for L-cones.

A convolution method for predicting mean treatment dose including organ motion at imaging

International Nuclear Information System (INIS)

Booth, J.T.; Zavgorodni, S.F.; Royal Adelaide Hospital, SA

2000-01-01

Full text: The random treatment delivery errors (organ motion and set-up error) can be incorporated into the treatment planning software using a convolution method. Mean treatment dose is computed as the convolution of a static dose distribution with a variation kernel. Typically this variation kernel is Gaussian with variance equal to the sum of the organ motion and set-up error variances. We propose a novel variation kernel for the convolution technique that additionally considers the position of the mobile organ in the planning CT image. The systematic error of organ position in the planning CT image can be considered random for each patient over a population. Thus the variance of the variation kernel will equal the sum of treatment delivery variance and organ motion variance at planning for the population of treatments. The kernel is extended to deal with multiple pre-treatment CT scans to improve tumour localisation for planning. Mean treatment doses calculated with the convolution technique are compared to benchmark Monte Carlo (MC) computations. Calculations of mean treatment dose using the convolution technique agreed with MC results for all cases to better than ± 1 Gy in the planning treatment volume for a prescribed 60 Gy treatment. Convolution provides a quick method of incorporating random organ motion (captured in the planning CT image and during treatment delivery) and random set-up errors directly into the dose distribution. Copyright (2000) Australasian College of Physical Scientists and Engineers in Medicine

Stress evolution during caldera collapse

Science.gov (United States)

Holohan, E. P.; Schöpfer, M. P. J.; Walsh, J. J.

2015-07-01

The mechanics of caldera collapse are subject of long-running debate. Particular uncertainties concern how stresses around a magma reservoir relate to fracturing as the reservoir roof collapses, and how roof collapse in turn impacts upon the reservoir. We used two-dimensional Distinct Element Method models to characterise the evolution of stress around a depleting sub-surface magma body during gravity-driven collapse of its roof. These models illustrate how principal stress orientations rotate during progressive deformation so that roof fracturing transitions from initial reverse faulting to later normal faulting. They also reveal four end-member stress paths to fracture, each corresponding to a particular location within the roof. Analysis of these paths indicates that fractures associated with ultimate roof failure initiate in compression (i.e. as shear fractures). We also report on how mechanical and geometric conditions in the roof affect pre-failure unloading and post-failure reloading of the reservoir. In particular, the models show how residual friction within a failed roof could, without friction reduction mechanisms or fluid-derived counter-effects, inhibit a return to a lithostatically equilibrated pressure in the magma reservoir. Many of these findings should be transferable to other gravity-driven collapse processes, such as sinkhole formation, mine collapse and subsidence above hydrocarbon reservoirs.

Convolutional Neural Networks - Generalizability and Interpretations

DEFF Research Database (Denmark)

Malmgren-Hansen, David

from data despite it being limited in amount or context representation. Within Machine Learning this thesis focuses on Convolutional Neural Networks for Computer Vision. The research aims to answer how to explore a model's generalizability to the whole population of data samples and how to interpret...

Light-cone observables and gauge-invariance in the geodesic light-cone formalism

Energy Technology Data Exchange (ETDEWEB)

Scaccabarozzi, Fulvio; Yoo, Jaiyul, E-mail: fulvio@physik.uzh.ch, E-mail: jyoo@physik.uzh.ch [Center for Theoretical Astrophysics and Cosmology, Institute for Computational Science, University of Zürich, Winterthurerstrasse 190, CH-8057, Zürich (Switzerland)

2017-06-01

The remarkable properties of the geodesic light-cone (GLC) coordinates allow analytic expressions for the light-cone observables, providing a new non-perturbative way for calculating the effects of inhomogeneities in our Universe. However, the gauge-invariance of these expressions in the GLC formalism has not been shown explicitly. Here we provide this missing part of the GLC formalism by proving the gauge-invariance of the GLC expressions for the light-cone observables, such as the observed redshift, the luminosity distance, and the physical area and volume of the observed sources. Our study provides a new insight on the properties of the GLC coordinates and it complements the previous work by the GLC collaboration, leading to a comprehensive description of light propagation in the GLC representation.

Convolutional Codes with Maximum Column Sum Rank for Network Streaming

OpenAIRE

Mahmood, Rafid; Badr, Ahmed; Khisti, Ashish

2015-01-01

The column Hamming distance of a convolutional code determines the error correction capability when streaming over a class of packet erasure channels. We introduce a metric known as the column sum rank, that parallels column Hamming distance when streaming over a network with link failures. We prove rank analogues of several known column Hamming distance properties and introduce a new family of convolutional codes that maximize the column sum rank up to the code memory. Our construction invol...

Plasma microinstabilities driven by loss-cone distributions

International Nuclear Information System (INIS)

Summers, D.; Thorne, R.M.

1995-01-01

Electromagnetic and electrostatic instabilities driven by loss-cone particle distributions have been invoked to explain a variety of plasma phenomena observed in space and in the laboratory. In this paper we analyse how the loss-cone feature (as determined by the loss-cone index or indices) influences the growth of such instabilities in a fully ionized, homogeneous, hot plasma in a uniform magnetic field. Specifically, we consider three loss-cone distributions: a generalized Lorentzian (kappa) loss-cone distribution, the Dory-Guest-Harris distribution and the Ashour-Abdalla-Kennel distribution (involving a subtracted Maxwellian). Our findings are common to all three distributions. We find that, for parallel propagation, electromagnetic instabilities are only affected by the loss-cone indices in terms of their occurrence in the temperature anisotropy. However, for oblique propagation, even including propagation at small angles to the ambient magnetic field, the loss-cone indices do independently affect the growth of instabilities for electromagnetic waves, in contrast to certain claims in the literature. For electrostatic waves such that 1/2(κ perpendicular to ρ L σ 2 L σ is the Larmor radius for particle species σ, we find that the loss-cone indices only enter the dispersion equation via the temperature anisotropy, and so in this case the loss-cone feature and perpendicular effective thermal speed do not independently affect wave growth. (Author)

Variability of silver fir (Abies alba Mill. cones – variability of cone parameters

Directory of Open Access Journals (Sweden)

Aniszewska Monika

2016-09-01

Full Text Available This study aimed at determining the shape of closed silver fir cones from the Jawor Forest District (Wroclaw, based purely on measurements of their length and thickness. Using these two parameters, the most accurate estimations were achieved with a fourth-degree polynomial fitting function. We then calculated the cones’ surface area and volume in three different ways: 1 Using the fourth-degree polynomial shape estimation, 2 Introducing indicators of compliance (k1, k2, k3 to calculate the volume and then comparing it to its actual value as measured in a pitcher filled with water, 3 Comparing the surface area of the cones as calculated with the polynomial function to the value obtained from ratios of indicators of compliance (ratios k4 and k5. We found that the calculated surface area and volume were substantially higher than the corresponding measured values. Test values of cone volume and surface area as calculated by our model were 8% and 5% lower, respectively, compared to direct measurements. We also determined the fir cones apparent density to be 0.8 g·cm-3on average. The gathered data on cone surface area, volume and bulk density is a valuable tool for optimizing the thermal peeling process in mill cabinets to acquire high quality seeds.

Méthode analytique généralisée pour le calcul du coning. Nouvelle solution pour calculer le coning de gaz, d'eau et double coning dans les puits verticaux et horizontaux Generalized Analytical Method for Coning Calculation. New Solution to Calculation Both the Gas Coning, Water Coning and Dual Coning for Vertical and Horizontal Wells

Directory of Open Access Journals (Sweden)

Pietraru V.

2006-11-01

Full Text Available Une nouvelle méthode analytique d'évaluation du coning d'eau par bottom water drive et/ou de gaz par gas-cap drive dans les puits horizontaux et verticaux a été développée pour les réservoirs infinis [1]. Dans cet article, une généralisation de cette méthode est présentée pour les réservoirs confinés d'extension limitée dont le toit est horizontal. La généralisation proposée est basée sur la résolution des équations différentielles de la diffusivité avec prise en compte des effets de drainage par gravité et des conditions aux limites pour un réservoir confiné. La méthode est applicable aux réservoirs isotropes ou anisotropes. L'hypothèse de pression constante à la limite de l'aire de drainage dans l'eau et/ou dans le gaz a été adoptée. Les pertes de charge dans l'aquifère et dans le gas-cap sont donc négligées. Les principales contributions de cet article sont : - L'introduction de la notion de rayon de cône, différent du rayon de puits. La hauteur du cône et le débit critique dépendent du rayon de cône alors qu'ils sont indépendants du rayon du puits. - Une nouvelle corrélation pour le calcul du débit critique sous forme adimensionnelle en fonction de trois paramètres : le temps, la longueur du drain horizontal (nulle pour un puits vertical et le rayon de drainage. - Des corrélations pour le calcul du rapport des débits gaz/huile (GOR ou de la fraction en eau (fw, pendant les périodes critique et postcritique, qui tiennent compte de la pression capillaire et des perméabilités relatives. - Des corrélations pour le calcul des rapports de débits gaz/huile et eau/huile pendant les périodes pré, post et supercritique en double coning. - Des critères pour le calcul du temps de percée au puits en simple coning de gaz ou d'eau, ou en double coning de gaz et d'eau. A new analytical method for assessing water and/or gas coning in horizontal and vertical wells has been developed for infinite

Fire-induced collapses of steel structures

DEFF Research Database (Denmark)

Dondera, Alexandru; Giuliani, Luisa

Single-story steel buildings such as car parks and industrial halls are often characterised by stiff beams and flexible columns and may experience an outward (sway) collapse during a fire, endangering people and properties outside the building. It is therefore a current interest of the research...... to investigate the collapse behaviour of single-story steel frames and identify relevant structural characteristics that influence the collapse mode. In this paper, a parametric study on the collapse a steel beam-column assembly with beam hinged connection and fixed column support is carried out under...... on the beam. By means of those tables, a simple method for the assessment and the countermeasure of unsafe collapse mode of single-story steel buildings can be derived....

Granular Silo collapse: an experimental study

Science.gov (United States)

Clement, Eric; Gutierriez, Gustavo; Boltenhagen, Philippe; Lanuza, Jose

2008-03-01

We present an experimental work that develop some basic insight into the pre-buckling behavior and the buckling transition toward plastic collapse of a granular silo. We study different patterns of deformation generated on thin paper cylindrical shells during granular discharge. We study the collapse threshold for different bed height, flow rates and grain sizes. We compare the patterns that appear during the discharge of spherical beads, with those obtained in the axially compressed cylindrical shells. When the height of the granular column is close to the collapse threshold, we describe a ladder like pattern that rises around the cylinder surface in a spiral path of diamond shaped localizations, and develops into a plastic collapsing fold that grows around the collapsing silo.

Convolution-deconvolution in DIGES

International Nuclear Information System (INIS)

Philippacopoulos, A.J.; Simos, N.

1995-01-01

Convolution and deconvolution operations is by all means a very important aspect of SSI analysis since it influences the input to the seismic analysis. This paper documents some of the convolution/deconvolution procedures which have been implemented into the DIGES code. The 1-D propagation of shear and dilatational waves in typical layered configurations involving a stack of layers overlying a rock is treated by DIGES in a similar fashion to that of available codes, e.g. CARES, SHAKE. For certain configurations, however, there is no need to perform such analyses since the corresponding solutions can be obtained in analytic form. Typical cases involve deposits which can be modeled by a uniform halfspace or simple layered halfspaces. For such cases DIGES uses closed-form solutions. These solutions are given for one as well as two dimensional deconvolution. The type of waves considered include P, SV and SH waves. The non-vertical incidence is given special attention since deconvolution can be defined differently depending on the problem of interest. For all wave cases considered, corresponding transfer functions are presented in closed-form. Transient solutions are obtained in the frequency domain. Finally, a variety of forms are considered for representing the free field motion both in terms of deterministic as well as probabilistic representations. These include (a) acceleration time histories, (b) response spectra (c) Fourier spectra and (d) cross-spectral densities

A convolutional neural network to filter artifacts in spectroscopic MRI.

Science.gov (United States)

Gurbani, Saumya S; Schreibmann, Eduard; Maudsley, Andrew A; Cordova, James Scott; Soher, Brian J; Poptani, Harish; Verma, Gaurav; Barker, Peter B; Shim, Hyunsuk; Cooper, Lee A D

2018-03-09

Proton MRSI is a noninvasive modality capable of generating volumetric maps of in vivo tissue metabolism without the need for ionizing radiation or injected contrast agent. Magnetic resonance spectroscopic imaging has been shown to be a viable imaging modality for studying several neuropathologies. However, a key hurdle in the routine clinical adoption of MRSI is the presence of spectral artifacts that can arise from a number of sources, possibly leading to false information. A deep learning model was developed that was capable of identifying and filtering out poor quality spectra. The core of the model used a tiled convolutional neural network that analyzed frequency-domain spectra to detect artifacts. When compared with a panel of MRS experts, our convolutional neural network achieved high sensitivity and specificity with an area under the curve of 0.95. A visualization scheme was implemented to better understand how the convolutional neural network made its judgement on single-voxel or multivoxel MRSI, and the convolutional neural network was embedded into a pipeline capable of producing whole-brain spectroscopic MRI volumes in real time. The fully automated method for assessment of spectral quality provides a valuable tool to support clinical MRSI or spectroscopic MRI studies for use in fields such as adaptive radiation therapy planning. © 2018 International Society for Magnetic Resonance in Medicine.

Use of RI-cone penetrometer in clay foundations

International Nuclear Information System (INIS)

Mimura, Mamoru; Shibata, Toru; Shrivastava, A.K.

1993-01-01

RI cone penetrometer tests are carried out at four different sites. The foundation grounds discussed here mainly consist of clayey materials. The measured results by RI cone penetrometers are shown for Kyobashi, Hachirougata, Kurihama and Kinkai Bay site. According to comparison of water content and density profiles by RI cone measurement with the conventional testing results, RI cone penetrometers are proved to be versatile tools for site investigation. Settlement assessment by RI cone penetrometer is also discussed by exemplifying the embankment at Kinkai Bay site. Elasto-vis-coplastic finite element analysis correspondingly performed strongly supports the RI cone based assessment. Repeated use of RI cone penetrometer with the advance of construction enables us to assess the consolidation process of the clay foundation. (author)

QCDNUM: Fast QCD evolution and convolution

Science.gov (United States)

Botje, M.

2011-02-01

The QCDNUM program numerically solves the evolution equations for parton densities and fragmentation functions in perturbative QCD. Un-polarised parton densities can be evolved up to next-to-next-to-leading order in powers of the strong coupling constant, while polarised densities or fragmentation functions can be evolved up to next-to-leading order. Other types of evolution can be accessed by feeding alternative sets of evolution kernels into the program. A versatile convolution engine provides tools to compute parton luminosities, cross-sections in hadron-hadron scattering, and deep inelastic structure functions in the zero-mass scheme or in generalised mass schemes. Input to these calculations are either the QCDNUM evolved densities, or those read in from an external parton density repository. Included in the software distribution are packages to calculate zero-mass structure functions in un-polarised deep inelastic scattering, and heavy flavour contributions to these structure functions in the fixed flavour number scheme. Program summaryProgram title: QCDNUM version: 17.00 Catalogue identifier: AEHV_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEHV_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU Public Licence No. of lines in distributed program, including test data, etc.: 45 736 No. of bytes in distributed program, including test data, etc.: 911 569 Distribution format: tar.gz Programming language: Fortran-77 Computer: All Operating system: All RAM: Typically 3 Mbytes Classification: 11.5 Nature of problem: Evolution of the strong coupling constant and parton densities, up to next-to-next-to-leading order in perturbative QCD. Computation of observable quantities by Mellin convolution of the evolved densities with partonic cross-sections. Solution method: Parametrisation of the parton densities as linear or quadratic splines on a discrete grid, and evolution of the spline

Geophysical observations at cavity collapse

Science.gov (United States)

Jousset, Philippe; Bazargan-Sabet, Behrooz; Lebert, François; Bernardie, Séverine; Gourry, Jean-Christophe

2010-05-01

In Lorraine region (France) salt layers at about 200 meters depth are exploited by Solvay using solution mining methodology which consists in extracting the salt by dissolution, collapsing the cavern overburden during the exploitation phase and finally reclaiming the landscape by creating a water area. In this process, one of the main challenges for the exploiting company is to control the initial 120-m diameter collapse so as to minimize possible damages. In order to detect potential precursors and understand processes associated with such collapses, a wide series of monitoring techniques including micro seismics, broad-band seismology, hydro-acoustic, electromagnetism, gas probing, automatic leveling, continuous GPS, continuous gravity and borehole extensometry was set-up in the frame of an in-situ study carried out by the "Research Group for the Impact and Safety of Underground Works" (GISOS, France). Equipments were set-up well before the final collapse, giving a unique opportunity to analyze a great deal of information prior to and during the collapse process which has been successfully achieved on February the 13th, 2009 by controlling the cavity internal pressure. In this work, we present the results of data recorded by a network of 3 broadband seismometers, 2 accelerometers, 2 tilt-meters and a continuously gravity meter. We relate the variations of the brine pumping rate with the evolutions of the induced geophysical signals and finally we propose a first mechanical model for describing the controlled collapse. Beyond the studied case, extrapolation of the results obtained might contribute to the understanding of uncontrolled cavity collapses, such as pit-craters or calderas at volcanoes.

Implementation of Tuy's cone-beam inversion formula

International Nuclear Information System (INIS)

Zeng, G.L.; Clack, R.; Gullberg, G.T.

1994-01-01

Tuy's cone-beam inversion formula was modified to develop a cone-beam reconstruction algorithm. The algorithm was implemented for a cone-beam vertex orbit consisting of a circle and two orthogonal lines. This orbit geometry satisfies the cone-beam data sufficiency condition and is easy to implement on commercial single photon emission computed tomography (SPECT) systems. The algorithm which consists of two derivative steps, one rebinning step, and one three-dimensional backprojection step, was verified by computer simulations and by reconstructing physical phantom data collected on a clinical SPECT system. The proposed algorithm gives equivalent results and is as efficient as other analytical cone-beam reconstruction algorithms. (Author)

Application of structured support vector machine backpropagation to a convolutional neural network for human pose estimation.

Science.gov (United States)

Witoonchart, Peerajak; Chongstitvatana, Prabhas

2017-08-01

In this study, for the first time, we show how to formulate a structured support vector machine (SSVM) as two layers in a convolutional neural network, where the top layer is a loss augmented inference layer and the bottom layer is the normal convolutional layer. We show that a deformable part model can be learned with the proposed structured SVM neural network by backpropagating the error of the deformable part model to the convolutional neural network. The forward propagation calculates the loss augmented inference and the backpropagation calculates the gradient from the loss augmented inference layer to the convolutional layer. Thus, we obtain a new type of convolutional neural network called an Structured SVM convolutional neural network, which we applied to the human pose estimation problem. This new neural network can be used as the final layers in deep learning. Our method jointly learns the structural model parameters and the appearance model parameters. We implemented our method as a new layer in the existing Caffe library. Copyright © 2017 Elsevier Ltd. All rights reserved.

Handling data redundancy in helical cone beam reconstruction with a cone-angle-based window function and its asymptotic approximation

International Nuclear Information System (INIS)

Tang Xiangyang; Hsieh Jiang

2007-01-01

A cone-angle-based window function is defined in this manuscript for image reconstruction using helical cone beam filtered backprojection (CB-FBP) algorithms. Rather than defining the window boundaries in a two-dimensional detector acquiring projection data for computed tomographic imaging, the cone-angle-based window function deals with data redundancy by selecting rays with the smallest cone angle relative to the reconstruction plane. To be computationally efficient, an asymptotic approximation of the cone-angle-based window function is also given and analyzed in this paper. The benefit of using such an asymptotic approximation also includes the avoidance of functional discontinuities that cause artifacts in reconstructed tomographic images. The cone-angle-based window function and its asymptotic approximation provide a way, equivalent to the Tam-Danielsson-window, for helical CB-FBP reconstruction algorithms to deal with data redundancy, regardless of where the helical pitch is constant or dynamically variable during a scan. By taking the cone-parallel geometry as an example, a computer simulation study is conducted to evaluate the proposed window function and its asymptotic approximation for helical CB-FBP reconstruction algorithm to handle data redundancy. The computer simulated Forbild head and thorax phantoms are utilized in the performance evaluation, showing that the proposed cone-angle-based window function and its asymptotic approximation can deal with data redundancy very well in cone beam image reconstruction from projection data acquired along helical source trajectories. Moreover, a numerical study carried out in this paper reveals that the proposed cone-angle-based window function is actually equivalent to the Tam-Danielsson-window, and rigorous mathematical proofs are being investigated

Double Dirac cones in phononic crystals

KAUST Repository

Li, Yan

2014-07-07

A double Dirac cone is realized at the center of the Brillouin zone of a two-dimensional phononic crystal (PC) consisting of a triangular array of core-shell-structure cylinders in water. The double Dirac cone is induced by the accidental degeneracy of two double-degenerate Bloch states. Using a perturbation method, we demonstrate that the double Dirac cone is composed of two identical and overlapping Dirac cones whose linear slopes can also be accurately predicted from the method. Because the double Dirac cone occurs at a relatively low frequency, a slab of the PC can be mapped onto a slab of zero refractive index material by using a standard retrieval method. Total transmission without phase change and energy tunneling at the double Dirac point frequency are unambiguously demonstrated by two examples. Potential applications can be expected in diverse fields such as acoustic wave manipulations and energy flow control.

Double Dirac cones in phononic crystals

KAUST Repository

Li, Yan; Wu, Ying; Mei, Jun

2014-01-01

A double Dirac cone is realized at the center of the Brillouin zone of a two-dimensional phononic crystal (PC) consisting of a triangular array of core-shell-structure cylinders in water. The double Dirac cone is induced by the accidental degeneracy of two double-degenerate Bloch states. Using a perturbation method, we demonstrate that the double Dirac cone is composed of two identical and overlapping Dirac cones whose linear slopes can also be accurately predicted from the method. Because the double Dirac cone occurs at a relatively low frequency, a slab of the PC can be mapped onto a slab of zero refractive index material by using a standard retrieval method. Total transmission without phase change and energy tunneling at the double Dirac point frequency are unambiguously demonstrated by two examples. Potential applications can be expected in diverse fields such as acoustic wave manipulations and energy flow control.

Unifying Research on Social-Ecological Resilience and Collapse.

Science.gov (United States)

Cumming, Graeme S; Peterson, Garry D

2017-09-01

Ecosystems influence human societies, leading people to manage ecosystems for human benefit. Poor environmental management can lead to reduced ecological resilience and social-ecological collapse. We review research on resilience and collapse across different systems and propose a unifying social-ecological framework based on (i) a clear definition of system identity; (ii) the use of quantitative thresholds to define collapse; (iii) relating collapse processes to system structure; and (iv) explicit comparison of alternative hypotheses and models of collapse. Analysis of 17 representative cases identified 14 mechanisms, in five classes, that explain social-ecological collapse. System structure influences the kind of collapse a system may experience. Mechanistic theories of collapse that unite structure and process can make fundamental contributions to solving global environmental problems. Copyright © 2017. Published by Elsevier Ltd.

Deformable image registration using convolutional neural networks

NARCIS (Netherlands)

Eppenhof, Koen A.J.; Lafarge, Maxime W.; Moeskops, Pim; Veta, Mitko; Pluim, Josien P.W.

2018-01-01

Deformable image registration can be time-consuming and often needs extensive parameterization to perform well on a specific application. We present a step towards a registration framework based on a three-dimensional convolutional neural network. The network directly learns transformations between

Collapse settlement in compacted soils

CSIR Research Space (South Africa)

Booth, AR

1977-01-01

Full Text Available Research into collapse settlement in compacted soils is described, with special reference to recent cases in Southern Africa where collapse settlement occurred in road embankments following wetting of the soil. The laboratory work described...

Cone-based Electrical Resistivity Tomography

Science.gov (United States)

Pidlisecky, A.; Knight, R.; Haber, E.

2005-05-01

Determining the 3D spatial distribution of subsurface properties is a critical part of managing the clean-up of contaminated sites. Most standard hydrologic methods sample small regions immediately adjacent to wells or testing devices. This provides data which are not representative of the entire region of interest. Furthermore, at many contaminated sites invasive methods are not acceptable, due to the risks associated with contacting and spreading the contaminants. To address these issues, we have developed a minimally invasive technology that provides information about the 3D distribution of electrical conductivity. This new technique, cone-based electrical resistivity tomography (C-bert), involves placing several permanent current electrodes in the subsurface and using electrodes mounted on a cone penetrometer to measure the resultant potential field while advancing the cone into the subsurface. In addition to potential field measurements, we obtain the standard suite of cone-penetration measurements, including high resolution resistivity logs; these data can then be used to constrain the inversion of the potential field data. A major challenge of working with these data is that the cone penetrometer is highly conductive, and thus presents a large local perturbation around the measurement location. As the cone is very small (approximately 30mm in diameter) with respect to the total model space, explicitly modeling the cone is computationally demanding. We developed a method for solving the forward model that reduces computational time by an order of magnitude. This solution method, iteratively determined boundary conditions, makes it possible to correct for the cone effect before inversion of the data. Results from synthetic experiments suggest that the C-bert method of data acquisition can result in high quality electrical conductivity images of the subsurface. We tested the practicality of this technique by performing a field test of the C-bert system to image

Convolutional over Recurrent Encoder for Neural Machine Translation

Directory of Open Access Journals (Sweden)

Dakwale Praveen

2017-06-01

Full Text Available Neural machine translation is a recently proposed approach which has shown competitive results to traditional MT approaches. Standard neural MT is an end-to-end neural network where the source sentence is encoded by a recurrent neural network (RNN called encoder and the target words are predicted using another RNN known as decoder. Recently, various models have been proposed which replace the RNN encoder with a convolutional neural network (CNN. In this paper, we propose to augment the standard RNN encoder in NMT with additional convolutional layers in order to capture wider context in the encoder output. Experiments on English to German translation demonstrate that our approach can achieve significant improvements over a standard RNN-based baseline.

Managing the effects of accelerated glacial melting on volcanic collapse and debris flows: Planchon-Peteroa Volcano, Southern Andes

Science.gov (United States)

Tormey, Daniel

2010-11-01

Glaciated mountains are among the most sensitive environments to climatic changes, and recent work has shown that large-scale glacial melting, including at the end of the Pleistocene, caused a significant increase in the incidence of large volcanic sector collapse and debris flows on then-active volcanoes. With current accelerated rates of glacial melting, glaciated active volcanoes are at an increasing risk of sector collapse, debris flow and landslide. These catastrophic events are Earth's most damaging erosion phenomenon, causing extensive property damage and loss of life. This paper illustrates these effects in well-studied settings, focusing on the end-Pleistocene to Holocene glaciovolcanic growth and destruction of the cone of the active volcano Planchon-Peteroa in the Andean Southern Volcanic Zone at latitude 35° 15' S, along the border between Chile and Argentina. The development of the volcano over the last 14,000 years illustrates how glacial melting and magmatic activity can trigger landslides and sector collapses. Planchon had a large sector collapse that produced a highly mobile and erosive debris avalanche 11,000 years BP, and other slope instabilities during the end-Pleistocene/early Holocene deglaciation. The summit amphitheater left after the sector collapse was subject to alternating periods of glaciation and melting-induced lake formation. Breaching of the moraine dams then formed lahars and landslides originating at the western edge of the summit amphitheater, and the deposits are preserved along the western flank of the volcano. Deep incision of moraine deposits further down the western slope of the volcano indicates that the lahars and landslides were water-rich and had high erosive power. As illustrated by Planchon-Peteroa, the interplay among glacial growth and melting, magmatic activity, and slope stability is complex, but must be accounted for in volcanic hazard assessment. Planchon-Peteroa currently has the southernmost temperate zone

Dirac cones in isogonal hexagonal metallic structures

Science.gov (United States)

Wang, Kang

2018-03-01

A honeycomb hexagonal metallic lattice is equivalent to a triangular atomic one and cannot create Dirac cones in its electromagnetic wave spectrum. We study in this work the low-frequency electromagnetic band structures in isogonal hexagonal metallic lattices that are directly related to the honeycomb one and show that such structures can create Dirac cones. The band formation can be described by a tight-binding model that allows investigating, in terms of correlations between local resonance modes, the condition for the Dirac cones and the consequence of the third structure tile sustaining an extra resonance mode in the unit cell that induces band shifts and thus nonlinear deformation of the Dirac cones following the wave vectors departing from the Dirac points. We show further that, under structure deformation, the deformations of the Dirac cones result from two different correlation mechanisms, both reinforced by the lattice's metallic nature, which directly affects the resonance mode correlations. The isogonal structures provide new degrees of freedom for tuning the Dirac cones, allowing adjustment of the cone shape by modulating the structure tiles at the local scale without modifying the lattice periodicity and symmetry.

Deep Galaxy: Classification of Galaxies based on Deep Convolutional Neural Networks

OpenAIRE

Khalifa, Nour Eldeen M.; Taha, Mohamed Hamed N.; Hassanien, Aboul Ella; Selim, I. M.

2017-01-01

In this paper, a deep convolutional neural network architecture for galaxies classification is presented. The galaxy can be classified based on its features into main three categories Elliptical, Spiral, and Irregular. The proposed deep galaxies architecture consists of 8 layers, one main convolutional layer for features extraction with 96 filters, followed by two principles fully connected layers for classification. It is trained over 1356 images and achieved 97.272% in testing accuracy. A c...

Spherically symmetric scalar field collapse

Indian Academy of Sciences (India)

2013-03-01

Mar 1, 2013 ... The very recent interest in scalar field collapse stems from a cosmological ... The objective of the present investigation is to explore the collapsing modes of a simple ..... The authors thank the BRNS (DAE) for financial support.

g-Weak Contraction in Ordered Cone Rectangular Metric Spaces

Directory of Open Access Journals (Sweden)

S. K. Malhotra

2013-01-01

Full Text Available We prove some common fixed-point theorems for the ordered g-weak contractions in cone rectangular metric spaces without assuming the normality of cone. Our results generalize some recent results from cone metric and cone rectangular metric spaces into ordered cone rectangular metric spaces. Examples are provided which illustrate the results.

Progressive Collapse of High-Rise Buildings from Fire

Directory of Open Access Journals (Sweden)

Pershakov Valerii

2016-01-01

Full Text Available Considers ensuring the stability of structures of high-rise buildings against progressive collapse due to fire, proposed measures to ensure the stability of high-rise buildings due to progressive collapse. The analysis of large fires in high-rise buildings with progressive collapse and review of the literature on the issue of progressive collapse. The analysis of the Ukrainian normative documents on progressive collapse resistance.

Traffic sign recognition based on deep convolutional neural network

Science.gov (United States)

Yin, Shi-hao; Deng, Ji-cai; Zhang, Da-wei; Du, Jing-yuan

2017-11-01

Traffic sign recognition (TSR) is an important component of automated driving systems. It is a rather challenging task to design a high-performance classifier for the TSR system. In this paper, we propose a new method for TSR system based on deep convolutional neural network. In order to enhance the expression of the network, a novel structure (dubbed block-layer below) which combines network-in-network and residual connection is designed. Our network has 10 layers with parameters (block-layer seen as a single layer): the first seven are alternate convolutional layers and block-layers, and the remaining three are fully-connected layers. We train our TSR network on the German traffic sign recognition benchmark (GTSRB) dataset. To reduce overfitting, we perform data augmentation on the training images and employ a regularization method named "dropout". The activation function we employ in our network adopts scaled exponential linear units (SELUs), which can induce self-normalizing properties. To speed up the training, we use an efficient GPU to accelerate the convolutional operation. On the test dataset of GTSRB, we achieve the accuracy rate of 99.67%, exceeding the state-of-the-art results.

Epileptiform spike detection via convolutional neural networks

DEFF Research Database (Denmark)

Johansen, Alexander Rosenberg; Jin, Jing; Maszczyk, Tomasz

2016-01-01

The EEG of epileptic patients often contains sharp waveforms called "spikes", occurring between seizures. Detecting such spikes is crucial for diagnosing epilepsy. In this paper, we develop a convolutional neural network (CNN) for detecting spikes in EEG of epileptic patients in an automated...

Very deep recurrent convolutional neural network for object recognition

Science.gov (United States)

Brahimi, Sourour; Ben Aoun, Najib; Ben Amar, Chokri

2017-03-01

In recent years, Computer vision has become a very active field. This field includes methods for processing, analyzing, and understanding images. The most challenging problems in computer vision are image classification and object recognition. This paper presents a new approach for object recognition task. This approach exploits the success of the Very Deep Convolutional Neural Network for object recognition. In fact, it improves the convolutional layers by adding recurrent connections. This proposed approach was evaluated on two object recognition benchmarks: Pascal VOC 2007 and CIFAR-10. The experimental results prove the efficiency of our method in comparison with the state of the art methods.

Deep Convolutional Neural Networks: Structure, Feature Extraction and Training

Directory of Open Access Journals (Sweden)

Namatēvs Ivars

2017-12-01

Full Text Available Deep convolutional neural networks (CNNs are aimed at processing data that have a known network like topology. They are widely used to recognise objects in images and diagnose patterns in time series data as well as in sensor data classification. The aim of the paper is to present theoretical and practical aspects of deep CNNs in terms of convolution operation, typical layers and basic methods to be used for training and learning. Some practical applications are included for signal and image classification. Finally, the present paper describes the proposed block structure of CNN for classifying crucial features from 3D sensor data.

A frequency bin-wise nonlinear masking algorithm in convolutive mixtures for speech segregation.

Science.gov (United States)

Chi, Tai-Shih; Huang, Ching-Wen; Chou, Wen-Sheng

2012-05-01

A frequency bin-wise nonlinear masking algorithm is proposed in the spectrogram domain for speech segregation in convolutive mixtures. The contributive weight from each speech source to a time-frequency unit of the mixture spectrogram is estimated by a nonlinear function based on location cues. For each sound source, a non-binary mask is formed from the estimated weights and is multiplied to the mixture spectrogram to extract the sound. Head-related transfer functions (HRTFs) are used to simulate convolutive sound mixtures perceived by listeners. Simulation results show our proposed method outperforms convolutive independent component analysis and degenerate unmixing and estimation technique methods in almost all test conditions.

Face recognition via Gabor and convolutional neural network

Science.gov (United States)

Lu, Tongwei; Wu, Menglu; Lu, Tao

2018-04-01

In recent years, the powerful feature learning and classification ability of convolutional neural network have attracted widely attention. Compared with the deep learning, the traditional machine learning algorithm has a good explanatory which deep learning does not have. Thus, In this paper, we propose a method to extract the feature of the traditional algorithm as the input of convolution neural network. In order to reduce the complexity of the network, the kernel function of Gabor wavelet is used to extract the feature from different position, frequency and direction of target image. It is sensitive to edge of image which can provide good direction and scale selection. The extraction of the image from eight directions on a scale are as the input of network that we proposed. The network have the advantage of weight sharing and local connection and texture feature of the input image can reduce the influence of facial expression, gesture and illumination. At the same time, we introduced a layer which combined the results of the pooling and convolution can extract deeper features. The training network used the open source caffe framework which is beneficial to feature extraction. The experiment results of the proposed method proved that the network structure effectively overcame the barrier of illumination and had a good robustness as well as more accurate and rapid than the traditional algorithm.

Isointense infant brain MRI segmentation with a dilated convolutional neural network

OpenAIRE

Moeskops, Pim; Pluim, Josien P. W.

2017-01-01

Quantitative analysis of brain MRI at the age of 6 months is difficult because of the limited contrast between white matter and gray matter. In this study, we use a dilated triplanar convolutional neural network in combination with a non-dilated 3D convolutional neural network for the segmentation of white matter, gray matter and cerebrospinal fluid in infant brain MR images, as provided by the MICCAI grand challenge on 6-month infant brain MRI segmentation.

Learning text representation using recurrent convolutional neural network with highway layers

OpenAIRE

Wen, Ying; Zhang, Weinan; Luo, Rui; Wang, Jun

2016-01-01

Recently, the rapid development of word embedding and neural networks has brought new inspiration to various NLP and IR tasks. In this paper, we describe a staged hybrid model combining Recurrent Convolutional Neural Networks (RCNN) with highway layers. The highway network module is incorporated in the middle takes the output of the bi-directional Recurrent Neural Network (Bi-RNN) module in the first stage and provides the Convolutional Neural Network (CNN) module in the last stage with the i...

Light cone thermodynamics

Science.gov (United States)

De Lorenzo, Tommaso; Perez, Alejandro

2018-02-01

We show that null surfaces defined by the outgoing and infalling wave fronts emanating from and arriving at a sphere in Minkowski spacetime have thermodynamical properties that are in strict formal correspondence with those of black hole horizons in curved spacetimes. Such null surfaces, made of pieces of light cones, are bifurcate conformal Killing horizons for suitable conformally stationary observers. They can be extremal and nonextremal depending on the radius of the shining sphere. Such conformal Killing horizons have a constant light cone (conformal) temperature, given by the standard expression in terms of the generalization of surface gravity for conformal Killing horizons. Exchanges of conformally invariant energy across the horizon are described by a first law where entropy changes are given by 1 /(4 ℓp2) of the changes of a geometric quantity with the meaning of horizon area in a suitable conformal frame. These conformal horizons satisfy the zeroth to the third laws of thermodynamics in an appropriate way. In the extremal case they become light cones associated with a single event; these have vanishing temperature as well as vanishing entropy.

A locality aware convolutional neural networks accelerator

NARCIS (Netherlands)

Shi, R.; Xu, Z.; Sun, Z.; Peemen, M.C.J.; Li, A.; Corporaal, H.; Wu, D.

2015-01-01

The advantages of Convolutional Neural Networks (CNNs) with respect to traditional methods for visual pattern recognition have changed the field of machine vision. The main issue that hinders broad adoption of this technique is the massive computing workload in CNN that prevents real-time

Cone dystrophy with "supernormal" rod ERG: psychophysical testing shows comparable rod and cone temporal sensitivity losses with no gain in rod function.

Science.gov (United States)

Stockman, Andrew; Henning, G Bruce; Michaelides, Michel; Moore, Anthony T; Webster, Andrew R; Cammack, Jocelyn; Ripamonti, Caterina

2014-02-10

We report a psychophysical investigation of 5 observers with the retinal disorder "cone dystrophy with supernormal rod ERG," caused by mutations in the gene KCNV2 that encodes a voltage-gated potassium channel found in rod and cone photoreceptors. We compared losses for rod- and for cone-mediated vision to further investigate the disorder and to assess whether the supernormal ERG is associated with any visual benefit. L-cone, S-cone, and rod temporal acuity (critical flicker fusion frequency) were measured as a function of target irradiance; L-cone temporal contrast sensitivity was measured as a function of temporal frequency. Temporal acuity measures revealed that losses for vision mediated by rods, S-cones, and L-cones are roughly equivalent. Further, the gain in rod function implied by the supernormal ERG provides no apparent benefit to near-threshold rod-mediated visual performance. The L-cone temporal contrast sensitivity function in affected observers was similar in shape to the mean normal function but only after the mean function was compressed by halving the logarithmic sensitivities. The name of this disorder is potentially misleading because the comparable losses found across rod and cone vision suggest that the disorder is a generalized cone-rod dystrophy. Temporal acuity and temporal contrast sensitivity measures are broadly consistent with the defect in the voltage-gated potassium channel producing a nonlinear distortion of the photoreceptor response but after otherwise normal transduction processes.

The convolution integral for the forward-backward asymmetry in e+e- annihilation

International Nuclear Information System (INIS)

Bardin, D.; Bilenky, M.; Chizhov, A.; Sazonov, A.; Sedykh, Yu.; Riemann, T.; Sachwitz, M.

1989-01-01

The complete convolution integral for the forward-backward asymmetry in A FB in e + e - annihilation is obtained in order O(α) with soft photon exponentiation. The influence of these QED corrections on A FB in the vicinity of the Z peak is discussed. The results are used to comment on a recent ad hoc ansatz using convolution weights derived for the total cross section. (orig.)

Black hole formation in perfect fluid collapse

International Nuclear Information System (INIS)

Goswami, Rituparno; Joshi, Pankaj S

2004-01-01

We construct here a special class of perfect fluid collapse models which generalizes the homogeneous dust collapse solution in order to include nonzero pressures and inhomogeneities into evolution. It is shown that a black hole is necessarily generated as the end product of continued gravitational collapse, rather than a naked singularity. We examine the nature of the central singularity forming as a result of endless collapse and it is shown that no nonspacelike trajectories can escape from the central singularity. Our results provide some insights into how the dynamical collapse works and into the possible formulations of the cosmic censorship hypothesis, which is as yet a major unsolved problem in black hole physics

A Fast Numerical Method for Max-Convolution and the Application to Efficient Max-Product Inference in Bayesian Networks.

Science.gov (United States)

Serang, Oliver

2015-08-01

Observations depending on sums of random variables are common throughout many fields; however, no efficient solution is currently known for performing max-product inference on these sums of general discrete distributions (max-product inference can be used to obtain maximum a posteriori estimates). The limiting step to max-product inference is the max-convolution problem (sometimes presented in log-transformed form and denoted as "infimal convolution," "min-convolution," or "convolution on the tropical semiring"), for which no O(k log(k)) method is currently known. Presented here is an O(k log(k)) numerical method for estimating the max-convolution of two nonnegative vectors (e.g., two probability mass functions), where k is the length of the larger vector. This numerical max-convolution method is then demonstrated by performing fast max-product inference on a convolution tree, a data structure for performing fast inference given information on the sum of n discrete random variables in O(nk log(nk)log(n)) steps (where each random variable has an arbitrary prior distribution on k contiguous possible states). The numerical max-convolution method can be applied to specialized classes of hidden Markov models to reduce the runtime of computing the Viterbi path from nk(2) to nk log(k), and has potential application to the all-pairs shortest paths problem.

Gravitational collapse and the vacuum energy

International Nuclear Information System (INIS)

Campos, M

2014-01-01

To explain the accelerated expansion of the universe, models with interacting dark components (dark energy and dark matter) have been considered recently in the literature. Generally, the dark energy component is physically interpreted as the vacuum energy of the all fields that fill the universe. As the other side of the same coin, the influence of the vacuum energy on the gravitational collapse is of great interest. We study such collapse adopting different parameterizations for the evolution of the vacuum energy. We discuss the homogeneous collapsing star fluid, that interacts with a vacuum energy component, using the stiff matter case as example. We conclude this work with a discussion of the Cahill-McVittie mass for the collapsed object.

Simple Analytic Models of Gravitational Collapse

Energy Technology Data Exchange (ETDEWEB)

Adler, R.

2005-02-09

Most general relativity textbooks devote considerable space to the simplest example of a black hole containing a singularity, the Schwarzschild geometry. However only a few discuss the dynamical process of gravitational collapse, by which black holes and singularities form. We present here two types of analytic models for this process, which we believe are the simplest available; the first involves collapsing spherical shells of light, analyzed mainly in Eddington-Finkelstein coordinates; the second involves collapsing spheres filled with a perfect fluid, analyzed mainly in Painleve-Gullstrand coordinates. Our main goal is pedagogical simplicity and algebraic completeness, but we also present some results that we believe are new, such as the collapse of a light shell in Kruskal-Szekeres coordinates.

Design and Implementation of Behavior Recognition System Based on Convolutional Neural Network

Directory of Open Access Journals (Sweden)

Yu Bo

2017-01-01

Full Text Available We build a set of human behavior recognition system based on the convolution neural network constructed for the specific human behavior in public places. Firstly, video of human behavior data set will be segmented into images, then we process the images by the method of background subtraction to extract moving foreground characters of body. Secondly, the training data sets are trained into the designed convolution neural network, and the depth learning network is constructed by stochastic gradient descent. Finally, the various behaviors of samples are classified and identified with the obtained network model, and the recognition results are compared with the current mainstream methods. The result show that the convolution neural network can study human behavior model automatically and identify human’s behaviors without any manually annotated trainings.

On the Induced Gravitational Collapse

Directory of Open Access Journals (Sweden)

M. Becerra Laura

2018-01-01

Full Text Available The induced gravitational collapse (IGC paradigm has been applied to explain the long gamma ray burst (GRB associated with type Ic supernova, and recently the Xray flashes (XRFs. The progenitor is a binary systems of a carbon-oxygen core (CO and a neutron star (NS. The CO core collapses and undergoes a supernova explosion which triggers the hypercritical accretion onto the NS companion (up to 10-2 M⊙s-1. For the binary driven hypernova (BdHNe, the binary system is enough bound, the NS reach its critical mass, and collapse to a black hole (BH with a GRB emission characterized by an isotropic energy Eiso > 1052 erg. Otherwise, for binary systems with larger binary separations, the hypercritical accretion onto the NS is not sufficient to induced its gravitational collapse, a X-ray flash is produced with Eiso < 1052 erg. We’re going to focus in identify the binary parameters that limits the BdHNe systems with the XRFs systems.

Gravity induced wave function collapse

Science.gov (United States)

Gasbarri, G.; Toroš, M.; Donadi, S.; Bassi, A.

2017-11-01

Starting from an idea of S. L. Adler [in Quantum Nonlocality and Reality: 50 Years of Bell's Theorem, edited by M. Bell and S. Gao (Cambridge University Press, Cambridge, England 2016)], we develop a novel model of gravity induced spontaneous wave function collapse. The collapse is driven by complex stochastic fluctuations of the spacetime metric. After deriving the fundamental equations, we prove the collapse and amplification mechanism, the two most important features of a consistent collapse model. Under reasonable simplifying assumptions, we constrain the strength ξ of the complex metric fluctuations with available experimental data. We show that ξ ≥10-26 in order for the model to guarantee classicality of macro-objects, and at the same time ξ ≤10-20 in order not to contradict experimental evidence. As a comparison, in the recent discovery of gravitational waves in the frequency range 35 to 250 Hz, the (real) metric fluctuations reach a peak of ξ ˜10-21.

Nonlinear wave collapse and strong turbulence

International Nuclear Information System (INIS)

Robinson, P.A.

1997-01-01

The theory and applications of wave self-focusing, collapse, and strongly nonlinear wave turbulence are reviewed. In the last decade, the theory of these phenomena and experimental realizations have progressed rapidly. Various nonlinear wave systems are discussed, but the simplest case of collapse and strong turbulence of Langmuir waves in an unmagnetized plasma is primarily used in explaining the theory and illustrating the main ideas. First, an overview of the basic physics of linear waves and nonlinear wave-wave interactions is given from an introductory perspective. Wave-wave processes are then considered in more detail. Next, an introductory overview of the physics of wave collapse and strong turbulence is provided, followed by a more detailed theoretical treatment. Later sections cover numerical simulations of Langmuir collapse and strong turbulence and experimental applications to space, ionospheric, and laboratory plasmas, including laser-plasma and beam-plasma interactions. Generalizations to self-focusing, collapse, and strong turbulence of waves in other systems are also discussed, including nonlinear optics, solid-state systems, magnetized auroral and astrophysical plasmas, and deep-water waves. The review ends with a summary of the main ideas of wave collapse and strong-turbulence theory, a collection of open questions in the field, and a brief discussion of possible future research directions. copyright 1997 The American Physical Society

Neutrinos and supernova collapse

International Nuclear Information System (INIS)

Colgate, S.A.; Petschek, A.G.

1980-01-01

The neutrino emission resulting from stellar collapse and supernova formation is reviewed. The electron capture and consequent neutronization of the collapsing stellar matter at the end of evolution determines both the initial adiabat of core collapse as well as the trapped lepton fraction. The initial lepton fraction, Y/sub l/ = .48 supplies the pressure for neutral support of the star at the Chandrasekhar limit. High trapping values, Y/sub l/ = .4, lead to soft core collapses; low values to harder collapses. The value of Y/sub l/ is presently in dispute. The neutrino emission from initial electron capture is relatively small. A strong core-bounce shock releases both electron neutrino as well as thermal muon and tau neutrinos. Subsequent neutrino emission and cooling can sometimes lead to an unstable buoyancy gradient in the core in which case unstable core overturn is expected. Calculations have already shown the importance of the largest possible eddy or equivalently the lowest mode of overturn. Present models of low lepton trapping ratio lead to high entropy creation by the reflected shock and the stabilization of the core matter against overturn. In such cases the exterior matter must cool below an entropy of approximately s/k approx. = 2 to become unstable. This may require too long a time approximately one second for neutrino cooling from a neutrinosphere at rho approx. = 2 x 10 12 g cm -3 . On the other hand, high values of Y/sub l/ such as .4 lead to softer bounces at lower density and values of the critical stabilizing entropy of 3 or higher. Under such circumstances, core overturn can still occur

Factorization, the light-cone distribution amplitude of the B-meson and the radiative decay $B \\to \\gamma l \

CERN Document Server

Descotes-Genon, S

2003-01-01

We study the radiative decay B -> gamma l nu_l in the framework of QCD factorization. We demonstrate explicitly that, in the heavy-quark limit and at one-loop order in perturbation theory, the amplitude does factorize, i.e. that it can be written as a convolution of a perturbatively calculable hard-scattering amplitude with the (non-perturbative) light-cone distribution amplitude of the B-meson. We evaluate the hard-scattering amplitude at one-loop order and verify that the large logarithms are those expected from a study of the b->u transition in the Soft-Collinear Effective Theory. Assuming that this is also the case at higher orders, we resum the large logarithms and perform an exploratory phenomenological analysis. The questions addressed in this study are also relevant for the applications of the QCD factorization formalism to two-body non-leptonic B-decays, in particular to the component of the amplitude arising from hard spectator interactions.

Rock images classification by using deep convolution neural network

Science.gov (United States)

Cheng, Guojian; Guo, Wenhui

2017-08-01

Granularity analysis is one of the most essential issues in authenticate under microscope. To improve the efficiency and accuracy of traditional manual work, an convolutional neural network based method is proposed for granularity analysis from thin section image, which chooses and extracts features from image samples while build classifier to recognize granularity of input image samples. 4800 samples from Ordos basin are used for experiments under colour spaces of HSV, YCbCr and RGB respectively. On the test dataset, the correct rate in RGB colour space is 98.5%, and it is believable in HSV and YCbCr colour space. The results show that the convolution neural network can classify the rock images with high reliability.

CRALBP supports the mammalian retinal visual cycle and cone vision.

Science.gov (United States)

Xue, Yunlu; Shen, Susan Q; Jui, Jonathan; Rupp, Alan C; Byrne, Leah C; Hattar, Samer; Flannery, John G; Corbo, Joseph C; Kefalov, Vladimir J

2015-02-01

Mutations in the cellular retinaldehyde-binding protein (CRALBP, encoded by RLBP1) can lead to severe cone photoreceptor-mediated vision loss in patients. It is not known how CRALBP supports cone function or how altered CRALBP leads to cone dysfunction. Here, we determined that deletion of Rlbp1 in mice impairs the retinal visual cycle. Mice lacking CRALBP exhibited M-opsin mislocalization, M-cone loss, and impaired cone-driven visual behavior and light responses. Additionally, M-cone dark adaptation was largely suppressed in CRALBP-deficient animals. While rearing CRALBP-deficient mice in the dark prevented the deterioration of cone function, it did not rescue cone dark adaptation. Adeno-associated virus-mediated restoration of CRALBP expression specifically in Müller cells, but not retinal pigment epithelial (RPE) cells, rescued the retinal visual cycle and M-cone sensitivity in knockout mice. Our results identify Müller cell CRALBP as a key component of the retinal visual cycle and demonstrate that this pathway is important for maintaining normal cone-driven vision and accelerating cone dark adaptation.

High Order Tensor Formulation for Convolutional Sparse Coding

KAUST Repository

Bibi, Adel Aamer; Ghanem, Bernard

2017-01-01

Convolutional sparse coding (CSC) has gained attention for its successful role as a reconstruction and a classification tool in the computer vision and machine learning community. Current CSC methods can only reconstruct singlefeature 2D images

A cone-beam reconstruction algorithm using shift-variant filtering and cone-beam backprojection

International Nuclear Information System (INIS)

Defrise, M.; Clack, R.

1994-01-01

An exact inversion formula written in the form of shift-variant filtered-backprojection (FBP) is given for reconstruction from cone-beam data taken from any orbit satisfying Tuy's sufficiency conditions. The method is based on a result of Grangeat, involving the derivative of the three-dimensional (3-D) Radon transform, but unlike Grangeat's algorithm, no 3D rebinning step is required. Data redundancy, which occurs when several cone-beam projections supply the same values in the Radon domain, is handled using an elegant weighting function and without discarding data. The algorithm is expressed in a convenient cone-beam detector reference frame, and a specific example for the case of a dual orthogonal circular orbit is presented. When the method is applied to a single circular orbit, it is shown to be equivalent to the well-known algorithm of Feldkamp et al

Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture.

Science.gov (United States)

Meszlényi, Regina J; Buza, Krisztian; Vidnyánszky, Zoltán

2017-01-01

Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our CCNN model can efficiently distinguish between subject groups. We also show that the connectome-convolutional network is capable to combine information from diverse functional connectivity metrics and that models using a combination of different connectivity descriptors are able to outperform classifiers using only one metric. From this flexibility follows that our proposed CCNN model can be easily adapted to a wide range of connectome based classification or regression tasks, by varying which connectivity descriptor combinations are used to train the network.

Edgeworth Expansion Based Model for the Convolutional Noise pdf

Directory of Open Access Journals (Sweden)

Yonatan Rivlin

2014-01-01

Full Text Available Recently, the Edgeworth expansion up to order 4 was used to represent the convolutional noise probability density function (pdf in the conditional expectation calculations where the source pdf was modeled with the maximum entropy density approximation technique. However, the applied Lagrange multipliers were not the appropriate ones for the chosen model for the convolutional noise pdf. In this paper we use the Edgeworth expansion up to order 4 and up to order 6 to model the convolutional noise pdf. We derive the appropriate Lagrange multipliers, thus obtaining new closed-form approximated expressions for the conditional expectation and mean square error (MSE as a byproduct. Simulation results indicate hardly any equalization improvement with Edgeworth expansion up to order 4 when using optimal Lagrange multipliers over a nonoptimal set. In addition, there is no justification for using the Edgeworth expansion up to order 6 over the Edgeworth expansion up to order 4 for the 16QAM and easy channel case. However, Edgeworth expansion up to order 6 leads to improved equalization performance compared to the Edgeworth expansion up to order 4 for the 16QAM and hard channel case as well as for the case where the 64QAM is sent via an easy channel.

Convolutional Neural Networks for SAR Image Segmentation

DEFF Research Database (Denmark)

Malmgren-Hansen, David; Nobel-Jørgensen, Morten

2015-01-01

Segmentation of Synthetic Aperture Radar (SAR) images has several uses, but it is a difficult task due to a number of properties related to SAR images. In this article we show how Convolutional Neural Networks (CNNs) can easily be trained for SAR image segmentation with good results. Besides...

Karst collapse in cities and mining areas, China

International Nuclear Information System (INIS)

Jian Chen

1988-01-01

Karst collapse is a dynamic geological phenomenon, in which the rock mass or deposits overlying the karstified zone subsides down along the karst cavity, resulting in a collapse pit or sinkhole. After discussing the typical examples of collapse emerging in the karst cities and mines in provinces and regions of South China, such as Guangdong, Guangxi, Hunan, Hubei, Zhejiang, Yunnan, Guizhou, and Jiangxi, it is considered that human activities of economy and production have become a major effect in causing karst collapse. Man-made collapses make 66.4 percent of the total, whereas natural ones 33.6 percent. Most of the collapses occurred to the area with soil overburden (96.7 percent), only a few in areas of bedrock overburden (3.3 percent). The karst collapses have a close relationship with the extent of karst development, the character and the thickness of overburden, and the dynamic condition of underground water. Collapse usually occurs in those parts of an area that are more intensely karstified, with soil thickness less than 5 m and a high amplitude of water table fluctuation. Many kinds of mechanical effects are caused by pumping or draining on the over-burden and destroying its equilibrium, leading to the collapse. These effects included the support loss and load-added effect, penetrating suffusion, gas explosion, water-hammer, suction pressure erosion, and liquefaction effects. The collapses are the result of varied comprehensive effects, particularly the support loss and load-added, and penetrating suffusion

Dimensionality-varied convolutional neural network for spectral-spatial classification of hyperspectral data

Science.gov (United States)

Liu, Wanjun; Liang, Xuejian; Qu, Haicheng

2017-11-01

Hyperspectral image (HSI) classification is one of the most popular topics in remote sensing community. Traditional and deep learning-based classification methods were proposed constantly in recent years. In order to improve the classification accuracy and robustness, a dimensionality-varied convolutional neural network (DVCNN) was proposed in this paper. DVCNN was a novel deep architecture based on convolutional neural network (CNN). The input of DVCNN was a set of 3D patches selected from HSI which contained spectral-spatial joint information. In the following feature extraction process, each patch was transformed into some different 1D vectors by 3D convolution kernels, which were able to extract features from spectral-spatial data. The rest of DVCNN was about the same as general CNN and processed 2D matrix which was constituted by by all 1D data. So that the DVCNN could not only extract more accurate and rich features than CNN, but also fused spectral-spatial information to improve classification accuracy. Moreover, the robustness of network on water-absorption bands was enhanced in the process of spectral-spatial fusion by 3D convolution, and the calculation was simplified by dimensionality varied convolution. Experiments were performed on both Indian Pines and Pavia University scene datasets, and the results showed that the classification accuracy of DVCNN improved by 32.87% on Indian Pines and 19.63% on Pavia University scene than spectral-only CNN. The maximum accuracy improvement of DVCNN achievement was 13.72% compared with other state-of-the-art HSI classification methods, and the robustness of DVCNN on water-absorption bands noise was demonstrated.

On a Generalized Hankel Type Convolution of Generalized Functions

Indian Academy of Sciences (India)

Generalized Hankel type transformation; Parserval relation; generalized ... The classical generalized Hankel type convolution are defined and extended to a class of generalized functions. ... Proceedings – Mathematical Sciences | News.

Convoluted laminations in waterlain sediments:three examples from Eastern Canada and their relevance to neotectonics

International Nuclear Information System (INIS)

Macdougall, D.A.; Broster, B.E.

1995-10-01

The catastrophic disturbance of unconsolidated sediment produces a wide variety of deformation structures, particularly if the sediment is water-saturated at the time of disturbance. Layers, originally deposited as sub-horizontal, can become stretched or distended resulting in convoluted laminations. Faulted beds, slumped units, or dewatering structures may also occur in association with the disturbance. Convolutions were studied in five examples of Pleistocene glaciomarine deltas, at three locations in eastern Canada. Results from this study indicate that similar structures were produced in each of the sediment deposits, but some are especially common in specific facies (e.g. bottomset, foreset, topset). However, the particular cause of the convolutions varied within each deposit, and the origin could be better assessed when studied in relationship to other structures. None of the convolutions found could be attributed, categorically, to a seismic origin. However, neither could a seismic origin be dismissed for structures associated with convolutions occurring in deposits at: St. George, New Brunswick; Economy Point, Nova Scotia; and Lanark, Ontario. Of these deposits, the deformed structures at Economy Point are apparently post-glacial. (author). 24 refs., 58 figs

Cascaded K-means convolutional feature learner and its application to face recognition

Science.gov (United States)

Zhou, Daoxiang; Yang, Dan; Zhang, Xiaohong; Huang, Sheng; Feng, Shu

2017-09-01

Currently, considerable efforts have been devoted to devise image representation. However, handcrafted methods need strong domain knowledge and show low generalization ability, and conventional feature learning methods require enormous training data and rich parameters tuning experience. A lightened feature learner is presented to solve these problems with application to face recognition, which shares similar topology architecture as a convolutional neural network. Our model is divided into three components: cascaded convolution filters bank learning layer, nonlinear processing layer, and feature pooling layer. Specifically, in the filters learning layer, we use K-means to learn convolution filters. Features are extracted via convoluting images with the learned filters. Afterward, in the nonlinear processing layer, hyperbolic tangent is employed to capture the nonlinear feature. In the feature pooling layer, to remove the redundancy information and incorporate the spatial layout, we exploit multilevel spatial pyramid second-order pooling technique to pool the features in subregions and concatenate them together as the final representation. Extensive experiments on four representative datasets demonstrate the effectiveness and robustness of our model to various variations, yielding competitive recognition results on extended Yale B and FERET. In addition, our method achieves the best identification performance on AR and labeled faces in the wild datasets among the comparative methods.

Cone rod dystrophies

Science.gov (United States)

Hamel, Christian P

2007-01-01

Cone rod dystrophies (CRDs) (prevalence 1/40,000) are inherited retinal dystrophies that belong to the group of pigmentary retinopathies. CRDs are characterized by retinal pigment deposits visible on fundus examination, predominantly localized to the macular region. In contrast to typical retinitis pigmentosa (RP), also called the rod cone dystrophies (RCDs) resulting from the primary loss in rod photoreceptors and later followed by the secondary loss in cone photoreceptors, CRDs reflect the opposite sequence of events. CRD is characterized by primary cone involvement, or, sometimes, by concomitant loss of both cones and rods that explains the predominant symptoms of CRDs: decreased visual acuity, color vision defects, photoaversion and decreased sensitivity in the central visual field, later followed by progressive loss in peripheral vision and night blindness. The clinical course of CRDs is generally more severe and rapid than that of RCDs, leading to earlier legal blindness and disability. At end stage, however, CRDs do not differ from RCDs. CRDs are most frequently non syndromic, but they may also be part of several syndromes, such as Bardet Biedl syndrome and Spinocerebellar Ataxia Type 7 (SCA7). Non syndromic CRDs are genetically heterogeneous (ten cloned genes and three loci have been identified so far). The four major causative genes involved in the pathogenesis of CRDs are ABCA4 (which causes Stargardt disease and also 30 to 60% of autosomal recessive CRDs), CRX and GUCY2D (which are responsible for many reported cases of autosomal dominant CRDs), and RPGR (which causes about 2/3 of X-linked RP and also an undetermined percentage of X-linked CRDs). It is likely that highly deleterious mutations in genes that otherwise cause RP or macular dystrophy may also lead to CRDs. The diagnosis of CRDs is based on clinical history, fundus examination and electroretinogram. Molecular diagnosis can be made for some genes, genetic counseling is always advised. Currently

Cone rod dystrophies

Directory of Open Access Journals (Sweden)

Hamel Christian P

2007-02-01

Full Text Available Abstract Cone rod dystrophies (CRDs (prevalence 1/40,000 are inherited retinal dystrophies that belong to the group of pigmentary retinopathies. CRDs are characterized by retinal pigment deposits visible on fundus examination, predominantly localized to the macular region. In contrast to typical retinitis pigmentosa (RP, also called the rod cone dystrophies (RCDs resulting from the primary loss in rod photoreceptors and later followed by the secondary loss in cone photoreceptors, CRDs reflect the opposite sequence of events. CRD is characterized by primary cone involvement, or, sometimes, by concomitant loss of both cones and rods that explains the predominant symptoms of CRDs: decreased visual acuity, color vision defects, photoaversion and decreased sensitivity in the central visual field, later followed by progressive loss in peripheral vision and night blindness. The clinical course of CRDs is generally more severe and rapid than that of RCDs, leading to earlier legal blindness and disability. At end stage, however, CRDs do not differ from RCDs. CRDs are most frequently non syndromic, but they may also be part of several syndromes, such as Bardet Biedl syndrome and Spinocerebellar Ataxia Type 7 (SCA7. Non syndromic CRDs are genetically heterogeneous (ten cloned genes and three loci have been identified so far. The four major causative genes involved in the pathogenesis of CRDs are ABCA4 (which causes Stargardt disease and also 30 to 60% of autosomal recessive CRDs, CRX and GUCY2D (which are responsible for many reported cases of autosomal dominant CRDs, and RPGR (which causes about 2/3 of X-linked RP and also an undetermined percentage of X-linked CRDs. It is likely that highly deleterious mutations in genes that otherwise cause RP or macular dystrophy may also lead to CRDs. The diagnosis of CRDs is based on clinical history, fundus examination and electroretinogram. Molecular diagnosis can be made for some genes, genetic counseling is

Neutrinos from gravitational collapse

International Nuclear Information System (INIS)

Mayle, R.; Wilson, J.R.; Schramm, D.N.

1986-05-01

Detailed calculations are made of the neutrino spectra emitted during gravitational collapse events (Type II supernovae). Those aspects of the neutrino signal which are relatively independent of the collapse model and those aspects which are sensitive to model details are discussed. The easier-to-detect high energy tail of the emitted neutrinos has been calculated using the Boltzmann equation which is compared with the result of the traditional multi-group flux limited diffusion calculations. 8 figs., 28 refs

Deep learning for steganalysis via convolutional neural networks

Science.gov (United States)

Qian, Yinlong; Dong, Jing; Wang, Wei; Tan, Tieniu

2015-03-01

Current work on steganalysis for digital images is focused on the construction of complex handcrafted features. This paper proposes a new paradigm for steganalysis to learn features automatically via deep learning models. We novelly propose a customized Convolutional Neural Network for steganalysis. The proposed model can capture the complex dependencies that are useful for steganalysis. Compared with existing schemes, this model can automatically learn feature representations with several convolutional layers. The feature extraction and classification steps are unified under a single architecture, which means the guidance of classification can be used during the feature extraction step. We demonstrate the effectiveness of the proposed model on three state-of-theart spatial domain steganographic algorithms - HUGO, WOW, and S-UNIWARD. Compared to the Spatial Rich Model (SRM), our model achieves comparable performance on BOSSbase and the realistic and large ImageNet database.

Developing empirical collapse fragility functions for global building types

Science.gov (United States)

Jaiswal, K.; Wald, D.; D'Ayala, D.

2011-01-01

Building collapse is the dominant cause of casualties during earthquakes. In order to better predict human fatalities, the U.S. Geological Survey’s Prompt Assessment of Global Earthquakes for Response (PAGER) program requires collapse fragility functions for global building types. The collapse fragility is expressed as the probability of collapse at discrete levels of the input hazard defined in terms of macroseismic intensity. This article provides a simple procedure for quantifying collapse fragility using vulnerability criteria based on the European Macroseismic Scale (1998) for selected European building types. In addition, the collapse fragility functions are developed for global building types by fitting the beta distribution to the multiple experts’ estimates for the same building type (obtained from EERI’s World Housing Encyclopedia (WHE)-PAGER survey). Finally, using the collapse probability distributions at each shaking intensity level as a prior and field-based collapse-rate observations as likelihood, it is possible to update the collapse fragility functions for global building types using the Bayesian procedure.

An upper bound on the number of errors corrected by a convolutional code

DEFF Research Database (Denmark)

Justesen, Jørn

2000-01-01

The number of errors that a convolutional codes can correct in a segment of the encoded sequence is upper bounded by the number of distinct syndrome sequences of the relevant length.......The number of errors that a convolutional codes can correct in a segment of the encoded sequence is upper bounded by the number of distinct syndrome sequences of the relevant length....

Using convolutional decoding to improve time delay and phase estimation in digital communications

Science.gov (United States)

Ormesher, Richard C [Albuquerque, NM; Mason, John J [Albuquerque, NM

2010-01-26

The time delay and/or phase of a communication signal received by a digital communication receiver can be estimated based on a convolutional decoding operation that the communication receiver performs on the received communication signal. If the original transmitted communication signal has been spread according to a spreading operation, a corresponding despreading operation can be integrated into the convolutional decoding operation.

CRALBP supports the mammalian retinal visual cycle and cone vision

OpenAIRE

Xue, Yunlu; Shen, Susan Q.; Jui, Jonathan; Rupp, Alan C.; Byrne, Leah C.; Hattar, Samer; Flannery, John G.; Corbo, Joseph C.; Kefalov, Vladimir J.

2015-01-01

Mutations in the cellular retinaldehyde-binding protein (CRALBP, encoded by RLBP1) can lead to severe cone photoreceptor-mediated vision loss in patients. It is not known how CRALBP supports cone function or how altered CRALBP leads to cone dysfunction. Here, we determined that deletion of Rlbp1 in mice impairs the retinal visual cycle. Mice lacking CRALBP exhibited M-opsin mislocalization, M-cone loss, and impaired cone-driven visual behavior and light responses. Additionally, M-cone dark ad...

Four tails problems for dynamical collapse theories

Science.gov (United States)

McQueen, Kelvin J.

2015-02-01

The primary quantum mechanical equation of motion entails that measurements typically do not have determinate outcomes, but result in superpositions of all possible outcomes. Dynamical collapse theories (e.g. GRW) supplement this equation with a stochastic Gaussian collapse function, intended to collapse the superposition of outcomes into one outcome. But the Gaussian collapses are imperfect in a way that leaves the superpositions intact. This is the tails problem. There are several ways of making this problem more precise. But many authors dismiss the problem without considering the more severe formulations. Here I distinguish four distinct tails problems. The first (bare tails problem) and second (structured tails problem) exist in the literature. I argue that while the first is a pseudo-problem, the second has not been adequately addressed. The third (multiverse tails problem) reformulates the second to account for recently discovered dynamical consequences of collapse. Finally the fourth (tails problem dilemma) shows that solving the third by replacing the Gaussian with a non-Gaussian collapse function introduces new conflict with relativity theory.

Convolution of second order linear recursive sequences II.

Directory of Open Access Journals (Sweden)

Szakács Tamás

2017-12-01

Full Text Available We continue the investigation of convolutions of second order linear recursive sequences (see the first part in [1]. In this paper, we focus on the case when the characteristic polynomials of the sequences have common root.

Evolutionary image simplification for lung nodule classification with convolutional neural networks.

Science.gov (United States)

Lückehe, Daniel; von Voigt, Gabriele

2018-05-29

Understanding decisions of deep learning techniques is important. Especially in the medical field, the reasons for a decision in a classification task are as crucial as the pure classification results. In this article, we propose a new approach to compute relevant parts of a medical image. Knowing the relevant parts makes it easier to understand decisions. In our approach, a convolutional neural network is employed to learn structures of images of lung nodules. Then, an evolutionary algorithm is applied to compute a simplified version of an unknown image based on the learned structures by the convolutional neural network. In the simplified version, irrelevant parts are removed from the original image. In the results, we show simplified images which allow the observer to focus on the relevant parts. In these images, more than 50% of the pixels are simplified. The simplified pixels do not change the meaning of the images based on the learned structures by the convolutional neural network. An experimental analysis shows the potential of the approach. Besides the examples of simplified images, we analyze the run time development. Simplified images make it easier to focus on relevant parts and to find reasons for a decision. The combination of an evolutionary algorithm employing a learned convolutional neural network is well suited for the simplification task. From a research perspective, it is interesting which areas of the images are simplified and which parts are taken as relevant.

Acral melanoma detection using a convolutional neural network for dermoscopy images.

Science.gov (United States)

Yu, Chanki; Yang, Sejung; Kim, Wonoh; Jung, Jinwoong; Chung, Kee-Yang; Lee, Sang Wook; Oh, Byungho

2018-01-01

Acral melanoma is the most common type of melanoma in Asians, and usually results in a poor prognosis due to late diagnosis. We applied a convolutional neural network to dermoscopy images of acral melanoma and benign nevi on the hands and feet and evaluated its usefulness for the early diagnosis of these conditions. A total of 724 dermoscopy images comprising acral melanoma (350 images from 81 patients) and benign nevi (374 images from 194 patients), and confirmed by histopathological examination, were analyzed in this study. To perform the 2-fold cross validation, we split them into two mutually exclusive subsets: half of the total image dataset was selected for training and the rest for testing, and we calculated the accuracy of diagnosis comparing it with the dermatologist's and non-expert's evaluation. The accuracy (percentage of true positive and true negative from all images) of the convolutional neural network was 83.51% and 80.23%, which was higher than the non-expert's evaluation (67.84%, 62.71%) and close to that of the expert (81.08%, 81.64%). Moreover, the convolutional neural network showed area-under-the-curve values like 0.8, 0.84 and Youden's index like 0.6795, 0.6073, which were similar score with the expert. Although further data analysis is necessary to improve their accuracy, convolutional neural networks would be helpful to detect acral melanoma from dermoscopy images of the hands and feet.

The collapse of interstellar gas clouds

International Nuclear Information System (INIS)

McNally, D.; Settle, J.J.

1980-01-01

The stability of spherically symmetric free-fall collapse to small radial perturbations is examined for non-uniform clouds. It is concluded that fragmentation of the central region of a collapsing gas cloud is possible if: (a) the density distribution is sufficiently smooth; and (b) the collapse is nearly free fall. Generally, perturbations enjoy only finite amplification during the collapse, and the amplification tends to decrease with increasing distance from the centre of the cloud. Unlimited amplification occurs only for uniform density clouds. Fragmentation is therefore unlikely to result from dynamical instability in the outer parts of a non-uniform cloud. Isothermal clouds are also briefly considered and, while it is argued that an earlier suggestion of their instability to fragmentation is unfounded, no general conclusion on the instability of such clouds could be drawn. (author)

Creep collapse of TAPS fuel cladding

International Nuclear Information System (INIS)

Chaudhry, S.M.; Anand, A.K.

1975-01-01

Densification of UO 2 can cause axial gaps between fuel pelets and cladding in unsupported (internally) at these regions. An analysis is carried out regarding the possibility of creep collapse in these regions. The analysis is based on Timoshenko's theory of collapse. At various times during the residence of fuel in reactor following parameters are calculated : (1) inelastic collapse of perfectly circular tubes (2) plastic instability in oval tubes (3) effect of creep on ovality. Creep is considered to be a non-linear combination of the following : (a) thermal creep (b) intresenic creep (c) stress aided radiation enhanced (d) stress free growth (4) Critical pressure ratio. The results obtained are compared with G.E. predictions. The results do not predict collapse of TAPS fuel cladding for five year residence time. (author)

Explosive eruptive history of Pantelleria, Italy: Repeated caldera collapse and ignimbrite emplacement at a peralkaline volcano

Science.gov (United States)

Jordan, Nina J.; Rotolo, Silvio G.; Williams, Rebecca; Speranza, Fabio; McIntosh, William C.; Branney, Michael J.; Scaillet, Stéphane

2018-01-01

A new, pre-Green Tuff (46 ka) volcanic stratigraphy is presented for the peralkaline Pantelleria Volcano, Italy. New 40Ar/39Ar and paleomagnetic data are combined with detailed field studies to develop a comprehensive stratigraphic reconstruction of the island. We find that the pre-46 ka succession is characterised by eight silica-rich peralkaline (trachyte to pantellerite) ignimbrites, many of which blanketed the entire island. The ignimbrites are typically welded to rheomorphic, and are commonly associated with lithic breccias and/or pumice deposits. They record sustained radial pyroclastic density currents fed by low pyroclastic fountains. The onset of ignimbrite emplacement is typically preceded (more rarely followed) by pumice fallout with limited dispersal, and some eruptions lack any associated pumice fall deposit, suggesting the absence of tall eruption columns. Particular attention is given to the correlation of well-developed lithic breccias in the ignimbrites, interpreted as probable tracers of caldera collapses. They record as many as five caldera collapse events, in contrast to the two events reported to date. Inter-ignimbrite periods are characterised by explosive and effusive eruptions with limited dispersal, such as small pumice cones, as well as pedogenesis. These periods have similar characteristics as the current post-Green Tuff activity on the island, and, while not imminent, it is reasonable to postulate the occurrence of another ignimbrite-forming eruption sometime in the future.

Collapse of nonlinear Langmuir waves

International Nuclear Information System (INIS)

Malkin, V.M.

1986-01-01

The dispersion of sufficiently intensive Langmuir waves is determined by intrinsic (electron) nonlinearity. During Langmuir collapse the wave energy density required for the appearance of electron nonlinearity is attained, generally speaking, prior to the development of dissipative processes. Up to now, the effect of electron nonlinearity on the collapse dynamics and spectrum of strong Langmuir turbulence ( which may be very appreciable ) has not been studied extensively because of the difficulty of describing nonlinear Langmuir waves. In the present paper the positive determinacy of the electron nonlinear hamiltonian is proven, the increment of modulation instability of a nonlinear Langmuir wave cluster localized in a cavity is calculated, and the universal law of their collapse is found

REAL-TIME VIDEO SCALING BASED ON CONVOLUTION NEURAL NETWORK ARCHITECTURE

Directory of Open Access Journals (Sweden)

S Safinaz

2017-08-01

Full Text Available In recent years, video super resolution techniques becomes mandatory requirements to get high resolution videos. Many super resolution techniques researched but still video super resolution or scaling is a vital challenge. In this paper, we have presented a real-time video scaling based on convolution neural network architecture to eliminate the blurriness in the images and video frames and to provide better reconstruction quality while scaling of large datasets from lower resolution frames to high resolution frames. We compare our outcomes with multiple exiting algorithms. Our extensive results of proposed technique RemCNN (Reconstruction error minimization Convolution Neural Network shows that our model outperforms the existing technologies such as bicubic, bilinear, MCResNet and provide better reconstructed motioning images and video frames. The experimental results shows that our average PSNR result is 47.80474 considering upscale-2, 41.70209 for upscale-3 and 36.24503 for upscale-4 for Myanmar dataset which is very high in contrast to other existing techniques. This results proves our proposed model real-time video scaling based on convolution neural network architecture’s high efficiency and better performance.

Digital Tomosynthesis System Geometry Analysis Using Convolution-Based Blur-and-Add (BAA) Model.

Science.gov (United States)

Wu, Meng; Yoon, Sungwon; Solomon, Edward G; Star-Lack, Josh; Pelc, Norbert; Fahrig, Rebecca

2016-01-01

Digital tomosynthesis is a three-dimensional imaging technique with a lower radiation dose than computed tomography (CT). Due to the missing data in tomosynthesis systems, out-of-plane structures in the depth direction cannot be completely removed by the reconstruction algorithms. In this work, we analyzed the impulse responses of common tomosynthesis systems on a plane-to-plane basis and proposed a fast and accurate convolution-based blur-and-add (BAA) model to simulate the backprojected images. In addition, the analysis formalism describing the impulse response of out-of-plane structures can be generalized to both rotating and parallel gantries. We implemented a ray tracing forward projection and backprojection (ray-based model) algorithm and the convolution-based BAA model to simulate the shift-and-add (backproject) tomosynthesis reconstructions. The convolution-based BAA model with proper geometry distortion correction provides reasonably accurate estimates of the tomosynthesis reconstruction. A numerical comparison indicates that the simulated images using the two models differ by less than 6% in terms of the root-mean-squared error. This convolution-based BAA model can be used in efficient system geometry analysis, reconstruction algorithm design, out-of-plane artifacts suppression, and CT-tomosynthesis registration.

Alternate symbol inversion for improved symbol synchronization in convolutionally coded systems

Science.gov (United States)

Simon, M. K.; Smith, J. G.

1980-01-01

Inverting alternate symbols of the encoder output of a convolutionally coded system provides sufficient density of symbol transitions to guarantee adequate symbol synchronizer performance, a guarantee otherwise lacking. Although alternate symbol inversion may increase or decrease the average transition density, depending on the data source model, it produces a maximum number of contiguous symbols without transition for a particular class of convolutional codes, independent of the data source model. Further, this maximum is sufficiently small to guarantee acceptable symbol synchronizer performance for typical applications. Subsequent inversion of alternate detected symbols permits proper decoding.

Adaptive Graph Convolutional Neural Networks

OpenAIRE

Li, Ruoyu; Wang, Sheng; Zhu, Feiyun; Huang, Junzhou

2018-01-01

Graph Convolutional Neural Networks (Graph CNNs) are generalizations of classical CNNs to handle graph data such as molecular data, point could and social networks. Current filters in graph CNNs are built for fixed and shared graph structure. However, for most real data, the graph structures varies in both size and connectivity. The paper proposes a generalized and flexible graph CNN taking data of arbitrary graph structure as input. In that way a task-driven adaptive graph is learned for eac...

Heavy-to-light correlators beyond the light cone

International Nuclear Information System (INIS)

Lucha, W.; Melikhov, D. I.; Simula, S.

2008-01-01

We present the first systematic analysis of the off-light-cone effects in correlators relevant for the extraction of the heavy-to-light form factors within the method of light-cone sum rules. In a model with scalar constituents, the correlator is calculated in two different ways: (i) by performing the expansion of the Bethe-Salpeter amplitude of the light meson near the light cone x 2 = 0 and (ii) by adopting the known solution for the Bethe-Salpeter amplitude which allows one to calculate the correlator without invoking any expansion. We demonstrate that the contributions to the correlator from the off-light-cone terms x 2 ≠ 0 are not suppressed by any large parameter compared to the contribution of the light-cone term x 2 0. For decays of heavy particles of mass in the range 1.5-5 GeV, the light-cone correlator is shown to systematically overestimate the full correlator, numerically the difference being 10-20%

Heavy-to-light correlators beyond the light cone

International Nuclear Information System (INIS)

Lucha, W.; Melikhov, D. I.; Simula, S.

2008-01-01

We present the first systematic analysis of the off-light-cone effects in correlators relevant for the extraction of the heavy-to-light form factors within the method of light-cone sum rules. In a model with scalar constituents, the correlator is calculated in two different ways: (i) by performing the expansion of the Bethe-Salpeter amplitude of the light meson near the light cone x 2 = 0 and (ii) by adopting the known solution for the Bethe-Salpeter amplitude which allows one to calculate the correlator without invoking any expansion. We demonstrate that the contributions to the correlator from the off-light-cone terms x 2 ≠ 0 are not suppressed by any large parameter compared to the contribution of the light-cone term x 2 = 0. For decays of heavy particles of mass in the range 1.5–5 GeV, the light-cone correlator is shown to systematically overestimate the full correlator, numerically the difference being 10–20%.

Strain engineering of Dirac cones in graphyne

Energy Technology Data Exchange (ETDEWEB)

Wang, Gaoxue; Kumar, Ashok; Pandey, Ravindra, E-mail: pandey@mtu.edu [Department of Physics, Michigan Technological University, Houghton, Michigan 49931 (United States); Si, Mingsu [Key Laboratory for Magnetism and Magnetic Materials of the Ministry of Education, Lanzhou University, Lanzhou 730000 (China)

2014-05-26

6,6,12-graphyne, one of the two-dimensional carbon allotropes with the rectangular lattice structure, has two kinds of non-equivalent anisotropic Dirac cones in the first Brillouin zone. We show that Dirac cones can be tuned independently by the uniaxial compressive strain applied to graphyne, which induces n-type and p-type self-doping effect, by shifting the energy of the Dirac cones in the opposite directions. On the other hand, application of the tensile strain results into a transition from gapless to finite gap system for the monolayer. For the AB-stacked bilayer, the results predict tunability of Dirac-cones by in-plane strains as well as the strain applied perpendicular to the plane. The group velocities of the Dirac cones show enhancement in the resistance anisotropy for bilayer relative to the case of monolayer. Such tunable and direction-dependent electronic properties predicted for 6,6,12-graphyne make it to be competitive for the next-generation electronic devices at nanoscale.

Plate Tearing by a Cone

DEFF Research Database (Denmark)

Simonsen, Bo Cerup

1997-01-01

The present paper is concerned with steady-state plate tearing by a cone. This is a scenario where a cone is forced through a ductile metal plate with a constant lateral tip penetration in a motion in the plane of the plate. The considered process could be an idealisaton of the damage, which...... as for the out-of-plane reaction force....

Six collapses

International Nuclear Information System (INIS)

Miller, R.H.; Smith, B.F.

1979-01-01

The self-consistent dynamical development of six stellar systems, started from rotating spherical configurations, has been studied by means of a fully three-dimensional n-body integration. The six examples had different initial angular velocities and velocity dispersions. All settled down into prolate bars rotating about a short axis within two initial rotation periods. The bars are long-lived, robust, and stable. Bars are the natural form toward which rapidly rotating stellar dynamical systems develop, instead of the flattened axisymmetric disks that had been expected.The early stages of each collapse are reasonably well described by a theoretical model according to which a collapse passes through a sequence of rigidly rotating, uniform-density spheroids. The first significant departures from spheroidal form were axisymmetric in all cases. Rings formed in some examples, sheets in others, with transition cases between these extremes. Nonaxisymmetry forms developed from these intermediate stages

Collapsed Dark Matter Structures

Science.gov (United States)

Buckley, Matthew R.; DiFranzo, Anthony

2018-02-01

The distributions of dark matter and baryons in the Universe are known to be very different: The dark matter resides in extended halos, while a significant fraction of the baryons have radiated away much of their initial energy and fallen deep into the potential wells. This difference in morphology leads to the widely held conclusion that dark matter cannot cool and collapse on any scale. We revisit this assumption and show that a simple model where dark matter is charged under a "dark electromagnetism" can allow dark matter to form gravitationally collapsed objects with characteristic mass scales much smaller than that of a Milky-Way-type galaxy. Though the majority of the dark matter in spiral galaxies would remain in the halo, such a model opens the possibility that galaxies and their associated dark matter play host to a significant number of collapsed substructures. The observational signatures of such structures are not well explored but potentially interesting.

Collapsed Dark Matter Structures.

Science.gov (United States)

Buckley, Matthew R; DiFranzo, Anthony

2018-02-02

The distributions of dark matter and baryons in the Universe are known to be very different: The dark matter resides in extended halos, while a significant fraction of the baryons have radiated away much of their initial energy and fallen deep into the potential wells. This difference in morphology leads to the widely held conclusion that dark matter cannot cool and collapse on any scale. We revisit this assumption and show that a simple model where dark matter is charged under a "dark electromagnetism" can allow dark matter to form gravitationally collapsed objects with characteristic mass scales much smaller than that of a Milky-Way-type galaxy. Though the majority of the dark matter in spiral galaxies would remain in the halo, such a model opens the possibility that galaxies and their associated dark matter play host to a significant number of collapsed substructures. The observational signatures of such structures are not well explored but potentially interesting.

Dynamic Control of Collapse in a Vortex Airy Beam

Science.gov (United States)

Chen, Rui-Pin; Chew, Khian-Hooi; He, Sailing

2013-01-01

Here we study systematically the self-focusing dynamics and collapse of vortex Airy optical beams in a Kerr medium. The collapse is suppressed compared to a non-vortex Airy beam in a Kerr medium due to the existence of vortex fields. The locations of collapse depend sensitively on the initial power, vortex order, and modulation parameters. The collapse may occur in a position where the initial field is nearly zero, while no collapse appears in the region where the initial field is mainly distributed. Compared with a non-vortex Airy beam, the collapse of a vortex Airy beam can occur at a position away from the area of the initial field distribution. Our study shows the possibility of controlling and manipulating the collapse, especially the precise position of collapse, by purposely choosing appropriate initial power, vortex order or modulation parameters of a vortex Airy beam. PMID:23518858

No-reference image quality assessment based on statistics of convolution feature maps

Science.gov (United States)

Lv, Xiaoxin; Qin, Min; Chen, Xiaohui; Wei, Guo

2018-04-01

We propose a Convolutional Feature Maps (CFM) driven approach to accurately predict image quality. Our motivation bases on the finding that the Nature Scene Statistic (NSS) features on convolution feature maps are significantly sensitive to distortion degree of an image. In our method, a Convolutional Neural Network (CNN) is trained to obtain kernels for generating CFM. We design a forward NSS layer which performs on CFM to better extract NSS features. The quality aware features derived from the output of NSS layer is effective to describe the distortion type and degree an image suffered. Finally, a Support Vector Regression (SVR) is employed in our No-Reference Image Quality Assessment (NR-IQA) model to predict a subjective quality score of a distorted image. Experiments conducted on two public databases demonstrate the promising performance of the proposed method is competitive to state of the art NR-IQA methods.

Fast Automatic Airport Detection in Remote Sensing Images Using Convolutional Neural Networks

Directory of Open Access Journals (Sweden)

Fen Chen

2018-03-01

Full Text Available Fast and automatic detection of airports from remote sensing images is useful for many military and civilian applications. In this paper, a fast automatic detection method is proposed to detect airports from remote sensing images based on convolutional neural networks using the Faster R-CNN algorithm. This method first applies a convolutional neural network to generate candidate airport regions. Based on the features extracted from these proposals, it then uses another convolutional neural network to perform airport detection. By taking the typical elongated linear geometric shape of airports into consideration, some specific improvements to the method are proposed. These approaches successfully improve the quality of positive samples and achieve a better accuracy in the final detection results. Experimental results on an airport dataset, Landsat 8 images, and a Gaofen-1 satellite scene demonstrate the effectiveness and efficiency of the proposed method.

DOS cones along atomic chains

International Nuclear Information System (INIS)

Kwapiński, Tomasz

2017-01-01

The electron transport properties of a linear atomic chain are studied theoretically within the tight-binding Hamiltonian and the Green’s function method. Variations of the local density of states (DOS) along the chain are investigated. They are crucial in scanning tunnelling experiments and give important insight into the electron transport mechanism and charge distribution inside chains. It is found that depending on the chain parity the local DOS at the Fermi level can form cone-like structures (DOS cones) along the chain. The general condition for the local DOS oscillations is obtained and the linear behaviour of the local density function is confirmed analytically. DOS cones are characterized by a linear decay towards the chain which is in contrast to the propagation properties of charge density waves, end states and Friedel oscillations in one-dimensional systems. We find that DOS cones can appear due to non-resonant electron transport, the spin–orbit scattering or for chains fabricated on a substrate with localized electrons. It is also shown that for imperfect chains (e.g. with a reduced coupling strength between two neighboring sites) a diamond-like structure of the local DOS along the chain appears. (paper)

DOS cones along atomic chains

Science.gov (United States)

Kwapiński, Tomasz

2017-03-01

The electron transport properties of a linear atomic chain are studied theoretically within the tight-binding Hamiltonian and the Green’s function method. Variations of the local density of states (DOS) along the chain are investigated. They are crucial in scanning tunnelling experiments and give important insight into the electron transport mechanism and charge distribution inside chains. It is found that depending on the chain parity the local DOS at the Fermi level can form cone-like structures (DOS cones) along the chain. The general condition for the local DOS oscillations is obtained and the linear behaviour of the local density function is confirmed analytically. DOS cones are characterized by a linear decay towards the chain which is in contrast to the propagation properties of charge density waves, end states and Friedel oscillations in one-dimensional systems. We find that DOS cones can appear due to non-resonant electron transport, the spin-orbit scattering or for chains fabricated on a substrate with localized electrons. It is also shown that for imperfect chains (e.g. with a reduced coupling strength between two neighboring sites) a diamond-like structure of the local DOS along the chain appears.

Sharper criteria for the wave collapse

DEFF Research Database (Denmark)

Kuznetsov, E.A.; Juul Rasmussen, J.; Rypdal, K.

1995-01-01

Sharper criteria for three-dimensional wave collapse described by the Nonlinear Schrodinger Equation (NLSE) are derived. The collapse threshold corresponds to the ground state soliton which is known to be unstable. Thus, for nonprefocusing distributions this represents the separatrix between...

Hanford waste tank cone penetrometer

International Nuclear Information System (INIS)

Seda, R.Y.

1995-12-01

A new tool is being developed to characterize tank waste at the Hanford Reservation. This tool, known as the cone penetrometer, is capable of obtaining chemical and physical properties in situ. For the past 50 years, this tool has been used extensively in soil applications and now has been modified for usage in Hanford Underground Storage tanks. These modifications include development of new ''waste'' data models as well as hardware design changes to accommodate the hazardous and radioactive environment of the tanks. The modified cone penetrometer is scheduled to be deployed at Hanford by Fall 1996. At Hanford, the cone penetrometer will be used as an instrumented pipe which measures chemical and physical properties as it pushes through tank waste. Physical data, such as tank waste stratification and mechanical properties, is obtained through three sensors measuring tip pressure, sleeve friction and pore pressure. Chemical data, such as chemical speciation, is measured using a Raman spectroscopy sensor. The sensor package contains other instrumentation as well, including a tip and side temperature sensor, tank bottom detection and an inclinometer. Once the cone penetrometer has reached the bottom of the tank, a moisture probe will be inserted into the pipe. This probe is used to measure waste moisture content, water level, waste surface moisture and tank temperature. This paper discusses the development of this new measurement system. Data from the cone penetrometer will aid in the selection of sampling tools, waste tank retrieval process, and addressing various tank safety issues. This paper will explore various waste models as well as the challenges associated with tank environment

Design and Implementation of Convolutional Encoder and Viterbi Decoder Using FPGA.

Directory of Open Access Journals (Sweden)

Riham Ali Zbaid

2018-01-01

Full Text Available Keeping  the  fineness of data is the most significant thing in communication.There are many factors that affect the accuracy of the data when it is transmitted over the communication channel such as noise etc. to overcome these effects are encoding channels encryption.In this paper is used for one type of channel coding is convolutional codes. Convolution encoding is a Forward Error Correction (FEC method used in incessant one-way and real time communication links .It can offer a great development in the error bit rates so that small, low energy, and devices cheap transmission when used in applications such as satellites. In this paper highlight the design, simulation and implementation of convolution encoder and Viterbi decoder by using MATLAB- program (2011. SIMULINK HDL coder is used to convert MATLAB-SIMULINK models to VHDL using plates Altera Cyclone II code DE2-70. Simulation and evaluation of the implementation of the results coincided with the results of the design show the coinciding with the designed results.

Enhancement of digital radiography image quality using a convolutional neural network.

Science.gov (United States)

Sun, Yuewen; Li, Litao; Cong, Peng; Wang, Zhentao; Guo, Xiaojing

2017-01-01

Digital radiography system is widely used for noninvasive security check and medical imaging examination. However, the system has a limitation of lower image quality in spatial resolution and signal to noise ratio. In this study, we explored whether the image quality acquired by the digital radiography system can be improved with a modified convolutional neural network to generate high-resolution images with reduced noise from the original low-quality images. The experiment evaluated on a test dataset, which contains 5 X-ray images, showed that the proposed method outperformed the traditional methods (i.e., bicubic interpolation and 3D block-matching approach) as measured by peak signal to noise ratio (PSNR) about 1.3 dB while kept highly efficient processing time within one second. Experimental results demonstrated that a residual to residual (RTR) convolutional neural network remarkably improved the image quality of object structural details by increasing the image resolution and reducing image noise. Thus, this study indicated that applying this RTR convolutional neural network system was useful to improve image quality acquired by the digital radiography system.

Collapsing dynamics of attractive Bose-Einstein condensates

DEFF Research Database (Denmark)

Bergé, L.; Juul Rasmussen, J.

2002-01-01

The self-similar collapse of 3D and quasi-2D atom condensates with negative scattering length is examined. 3D condensates are shown to blow up following the scenario of weak collapse, for which 3-body recombination weakly dissipates the atoms. In contrast, 2D condensates undergo a strong collapse......, that absorbs a significant amount of particles. (C) 2002 Elsevier Science B.V. All rights reserved....

Tandem mass spectrometry data quality assessment by self-convolution

Directory of Open Access Journals (Sweden)

Tham Wai

2007-09-01

Full Text Available Abstract Background Many algorithms have been developed for deciphering the tandem mass spectrometry (MS data sets. They can be essentially clustered into two classes. The first performs searches on theoretical mass spectrum database, while the second based itself on de novo sequencing from raw mass spectrometry data. It was noted that the quality of mass spectra affects significantly the protein identification processes in both instances. This prompted the authors to explore ways to measure the quality of MS data sets before subjecting them to the protein identification algorithms, thus allowing for more meaningful searches and increased confidence level of proteins identified. Results The proposed method measures the qualities of MS data sets based on the symmetric property of b- and y-ion peaks present in a MS spectrum. Self-convolution on MS data and its time-reversal copy was employed. Due to the symmetric nature of b-ions and y-ions peaks, the self-convolution result of a good spectrum would produce a highest mid point intensity peak. To reduce processing time, self-convolution was achieved using Fast Fourier Transform and its inverse transform, followed by the removal of the "DC" (Direct Current component and the normalisation of the data set. The quality score was defined as the ratio of the intensity at the mid point to the remaining peaks of the convolution result. The method was validated using both theoretical mass spectra, with various permutations, and several real MS data sets. The results were encouraging, revealing a high percentage of positive prediction rates for spectra with good quality scores. Conclusion We have demonstrated in this work a method for determining the quality of tandem MS data set. By pre-determining the quality of tandem MS data before subjecting them to protein identification algorithms, spurious protein predictions due to poor tandem MS data are avoided, giving scientists greater confidence in the

Tandem mass spectrometry data quality assessment by self-convolution.

Science.gov (United States)

Choo, Keng Wah; Tham, Wai Mun

2007-09-20

Many algorithms have been developed for deciphering the tandem mass spectrometry (MS) data sets. They can be essentially clustered into two classes. The first performs searches on theoretical mass spectrum database, while the second based itself on de novo sequencing from raw mass spectrometry data. It was noted that the quality of mass spectra affects significantly the protein identification processes in both instances. This prompted the authors to explore ways to measure the quality of MS data sets before subjecting them to the protein identification algorithms, thus allowing for more meaningful searches and increased confidence level of proteins identified. The proposed method measures the qualities of MS data sets based on the symmetric property of b- and y-ion peaks present in a MS spectrum. Self-convolution on MS data and its time-reversal copy was employed. Due to the symmetric nature of b-ions and y-ions peaks, the self-convolution result of a good spectrum would produce a highest mid point intensity peak. To reduce processing time, self-convolution was achieved using Fast Fourier Transform and its inverse transform, followed by the removal of the "DC" (Direct Current) component and the normalisation of the data set. The quality score was defined as the ratio of the intensity at the mid point to the remaining peaks of the convolution result. The method was validated using both theoretical mass spectra, with various permutations, and several real MS data sets. The results were encouraging, revealing a high percentage of positive prediction rates for spectra with good quality scores. We have demonstrated in this work a method for determining the quality of tandem MS data set. By pre-determining the quality of tandem MS data before subjecting them to protein identification algorithms, spurious protein predictions due to poor tandem MS data are avoided, giving scientists greater confidence in the predicted results. We conclude that the algorithm performs well

Finite element analysis of the collapse and post-collapse behavior of steel pipes applications to the oil industry

CERN Document Server

Dvorkin, Eduardo N

2013-01-01

This book presents a detailed discussion of the models that were developed to simulate the collapse and post-collapse behavior of steel pipes. The finite element method offers to engineers the possibility of developing models to simulate the collapse behavior of casings inside oil wells and the collapse behavior of deepwater pipelines. However, if technological decisions are going to be reached from these model results, with implications for the economic success of industrial operations, for the occupational safety and health and for the environment, the engineering models need to be highly reliable. Using these models engineers can quantify the effect of manufacturing tolerances, wear, corrosion, etc. This book describes in great details the experimental programs that are developed to validate the numerical results.

Discrete singular convolution for the generalized variable-coefficient ...

African Journals Online (AJOL)

Numerical solutions of the generalized variable-coefficient Korteweg-de Vries equation are obtained using a discrete singular convolution and a fourth order singly diagonally implicit Runge-Kutta method for space and time discretisation, respectively. The theoretical convergence of the proposed method is rigorously ...

Symbol Stream Combining in a Convolutionally Coded System

Science.gov (United States)

Mceliece, R. J.; Pollara, F.; Swanson, L.

1985-01-01

Symbol stream combining has been proposed as a method for arraying signals received at different antennas. If convolutional coding and Viterbi decoding are used, it is shown that a Viterbi decoder based on the proposed weighted sum of symbol streams yields maximum likelihood decisions.

DeepFix: A Fully Convolutional Neural Network for Predicting Human Eye Fixations.

Science.gov (United States)

Kruthiventi, Srinivas S S; Ayush, Kumar; Babu, R Venkatesh

2017-09-01

Understanding and predicting the human visual attention mechanism is an active area of research in the fields of neuroscience and computer vision. In this paper, we propose DeepFix, a fully convolutional neural network, which models the bottom-up mechanism of visual attention via saliency prediction. Unlike classical works, which characterize the saliency map using various hand-crafted features, our model automatically learns features in a hierarchical fashion and predicts the saliency map in an end-to-end manner. DeepFix is designed to capture semantics at multiple scales while taking global context into account, by using network layers with very large receptive fields. Generally, fully convolutional nets are spatially invariant-this prevents them from modeling location-dependent patterns (e.g., centre-bias). Our network handles this by incorporating a novel location-biased convolutional layer. We evaluate our model on multiple challenging saliency data sets and show that it achieves the state-of-the-art results.

Convolutional Encoder and Viterbi Decoder Using SOPC For Variable Constraint Length

DEFF Research Database (Denmark)

Kulkarni, Anuradha; Dnyaneshwar, Mantri; Prasad, Neeli R.

2013-01-01

Convolution encoder and Viterbi decoder are the basic and important blocks in any Code Division Multiple Accesses (CDMA). They are widely used in communication system due to their error correcting capability But the performance degrades with variable constraint length. In this context to have...... detailed analysis, this paper deals with the implementation of convolution encoder and Viterbi decoder using system on programming chip (SOPC). It uses variable constraint length of 7, 8 and 9 bits for 1/2 and 1/3 code rates. By analyzing the Viterbi algorithm it is seen that our algorithm has a better...

Collapse of Electrostatic Waves in Magnetoplasmas

DEFF Research Database (Denmark)

Shukla, P. K.; Yu, M. Y.; Juul Rasmussen, Jens

1984-01-01

The two-fluid model is employed to investigate the collapse of electrostatic waves in magnetized plasmas. It is found that nonlinear interaction of ion cyclotron, upper-, and lower-hybrid waves with adiabatic particle motion along the external magnetic field can cause wave-field collapse....

Plate Tearing by a Cone

DEFF Research Database (Denmark)

Simonsen, Bo Cerup

1998-01-01

The present paper is concerned with steady-state plate tearing by a cone. This is a scenario where a cone is forced through a ductile metal plate with a constant lateral tip penetration in a motion in the plane of the plate. The considered process could be an idealisation of the damage, which...... as for the out-of-plane reaction force. (C) 1998 Elsevier Science Ltd. All rights reserved....

Improving the Separability of Deep Features with Discriminative Convolution Filters for RSI Classification

Directory of Open Access Journals (Sweden)

Na Liu

2018-03-01

Full Text Available The extraction of activation vectors (or deep features from the fully connected layers of a convolutional neural network (CNN model is widely used for remote sensing image (RSI representation. In this study, we propose to learn discriminative convolution filter (DCF based on class-specific separability criteria for linear transformation of deep features. In particular, two types of pretrained CNN called CaffeNet and VGG-VD16 are introduced to illustrate the generality of the proposed DCF. The activation vectors extracted from the fully connected layers of a CNN are rearranged into the form of an image matrix, from which a spatial arrangement of local patches is extracted using sliding window strategy. DCF learning is then performed on each local patch individually to obtain the corresponding discriminative convolution kernel through generalized eigenvalue decomposition. The proposed DCF learning characterizes that a convolutional kernel with small size (e.g., 3 × 3 pixels can be effectively learned on a small-size local patch (e.g., 8 × 8 pixels, thereby ensuring that the linear transformation of deep features can maintain low computational complexity. Experiments on two RSI datasets demonstrate the effectiveness of DCF in improving the classification performances of deep features without increasing dimensionality.

Gravitational radiation from stellar collapse: The initial burst

International Nuclear Information System (INIS)

Shapiro, S.L.

1977-01-01

The burst of gravitational radiation emitted during the initial collapse and rebound of a homogeneous, uniformly rotating spheroid with internal pressure is analyzed numerically. The surface of the collapsing spheroid is assumed to start at rest from infinity with negligible eccentricity (''zero-energy collapse''). The adopted internal pressure function is constant on self-similar spheroidal surfaces, and its central value is described by a polytropic law with index n< or =3. The Newtonian equations of motion are integrated numerically to follow the initial collapse and rebound of the configuration for the special case in which the collapse is time-reversal invariant about the moment of maximum compression, and the total energy and frequency spectrum of the emitted quadrupole radiation are computed. The results are employed to estimate the (approx.minimum) total energy and frequency distribution of the initial burst of gravitational radiation emitted during the formation of low-mass (Mapproximately-less-thanM/sub sun/) neutron stars and during the collapse of supermassive gas clouds

Topology-optimized dual-polarization Dirac cones

Science.gov (United States)

Lin, Zin; Christakis, Lysander; Li, Yang; Mazur, Eric; Rodriguez, Alejandro W.; Lončar, Marko

2018-02-01

We apply a large-scale computational technique, known as topology optimization, to the inverse design of photonic Dirac cones. In particular, we report on a variety of photonic crystal geometries, realizable in simple isotropic dielectric materials, which exhibit dual-polarization Dirac cones. We present photonic crystals of different symmetry types, such as fourfold and sixfold rotational symmetries, with Dirac cones at different points within the Brillouin zone. The demonstrated and related optimization techniques open avenues to band-structure engineering and manipulating the propagation of light in periodic media, with possible applications to exotic optical phenomena such as effective zero-index media and topological photonics.

Demise of light cone field theory

International Nuclear Information System (INIS)

Hagen, C.R.

1977-01-01

It is shown that the massive spin one-half field is noncovariant in two dimensional light cone coordinates. It is shown that spin one-half is noncovariant in four dimensions as well. It is concluded that since the case of the spin one-half field is an absolute necessity if one is to build a world containing fermions. It seems safe to infer that light cone quantization cannot be useful in the quark binding problem as currently conceived. It is suggested that further work on light cone quantization be focused solely upon the questions of consistency as discussed rather than on applications to model building. 9 references

Plant species classification using deep convolutional neural network

DEFF Research Database (Denmark)

Dyrmann, Mads; Karstoft, Henrik; Midtiby, Henrik Skov

2016-01-01

Information on which weed species are present within agricultural fields is important for site specific weed management. This paper presents a method that is capable of recognising plant species in colour images by using a convolutional neural network. The network is built from scratch trained an...

Integrity of the cone photoreceptor mosaic in oligocone trichromacy

DEFF Research Database (Denmark)

Michaelides, Michel; Rha, Jungtae; Dees, Elise W

2011-01-01

Oligocone trichromacy (OT) is an unusual cone dysfunction syndrome characterized by reduced visual acuity, mild photophobia, reduced amplitude of the cone electroretinogram with normal rod responses, normal fundus appearance, and normal or near-normal color vision. It has been proposed that these...... that these patients have a reduced number of normal functioning cones (oligocone). This paper has sought to evaluate the integrity of the cone photoreceptor mosaic in four patients previously described as having OT....

Cloud Detection by Fusing Multi-Scale Convolutional Features

Science.gov (United States)

Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang

2018-04-01

Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.

Is Kinesio Taping to Generate Skin Convolutions Effective for Increasing Local Blood Circulation?

OpenAIRE

Yang, Jae-Man; Lee, Jung-Hoon

2018-01-01

Background It is unclear whether traditional application of Kinesio taping, which produces wrinkles in the skin, is effective for improving blood circulation. This study investigated local skin temperature changes after the application of an elastic therapeutic tape using convolution and non-convolution taping methods (CTM/NCTM). Material/Methods Twenty-eight pain-free men underwent CTM and NCTM randomly applied to the right and left sides of the lower back. Using infrared thermography, skin ...

Segmentation of Drosophila Heart in Optical Coherence Microscopy Images Using Convolutional Neural Networks

OpenAIRE

Duan, Lian; Qin, Xi; He, Yuanhao; Sang, Xialin; Pan, Jinda; Xu, Tao; Men, Jing; Tanzi, Rudolph E.; Li, Airong; Ma, Yutao; Zhou, Chao

2018-01-01

Convolutional neural networks are powerful tools for image segmentation and classification. Here, we use this method to identify and mark the heart region of Drosophila at different developmental stages in the cross-sectional images acquired by a custom optical coherence microscopy (OCM) system. With our well-trained convolutional neural network model, the heart regions through multiple heartbeat cycles can be marked with an intersection over union (IOU) of ~86%. Various morphological and dyn...

Current status of relativistic core collapse simulations

Energy Technology Data Exchange (ETDEWEB)

Font, Jose A [Departamento de Astronomia y Astrofisica, Universidad de Valencia, Dr. Moliner 50, 46100 Burjassot (Valencia) (Spain)

2007-05-15

With the first generation of ground-based gravitational wave laser interferometers already taking data, the availability of reliable waveform templates from astrophysical sources, which may help extract the signal from the anticipated noisy data, is urgently required. Gravitational stellar core collapse supernova has traditionally been considered among the most important astrophysical sources of potentially detectable gravitational radiation. Only very recently the first multidimensional simulations of relativistic rotational core collapse have been possible (albeit for models with simplified input physics), thanks to the use of conservative formulations of the hydrodynamics equations and advanced numerical methodology, as well as stable formulations of Einstein's equations. In this paper, the current status of relativistic core collapse simulations is discussed, with the emphasis given to the modelling of the collapse dynamics and to the computation of the gravitational radiation in the existing numerical approaches. Work employing the conformally-flat approximation (CFC) of the 3+1 Einstein's equations is reported, as well as extensions of this approximation (CFC+) and investigations within the framework of the so-called BSSN formulation of the 3+1 gravitational field equations (with no approximation for the spacetime dynamics). On the other hand, the incorporation of magnetic fields and the MHD equations in numerical codes to improve the realism of core collapse simulations in general relativity, is currently an emerging field where significant progress is bound to be soon achieved. The paper also contains a brief discussion of magneto-rotational simulations of core collapse, aiming at addressing the effects of magnetic fields on the collapse dynamics and on the gravitational waveforms.

Current status of relativistic core collapse simulations

International Nuclear Information System (INIS)

Font, Jose A

2007-01-01

With the first generation of ground-based gravitational wave laser interferometers already taking data, the availability of reliable waveform templates from astrophysical sources, which may help extract the signal from the anticipated noisy data, is urgently required. Gravitational stellar core collapse supernova has traditionally been considered among the most important astrophysical sources of potentially detectable gravitational radiation. Only very recently the first multidimensional simulations of relativistic rotational core collapse have been possible (albeit for models with simplified input physics), thanks to the use of conservative formulations of the hydrodynamics equations and advanced numerical methodology, as well as stable formulations of Einstein's equations. In this paper, the current status of relativistic core collapse simulations is discussed, with the emphasis given to the modelling of the collapse dynamics and to the computation of the gravitational radiation in the existing numerical approaches. Work employing the conformally-flat approximation (CFC) of the 3+1 Einstein's equations is reported, as well as extensions of this approximation (CFC+) and investigations within the framework of the so-called BSSN formulation of the 3+1 gravitational field equations (with no approximation for the spacetime dynamics). On the other hand, the incorporation of magnetic fields and the MHD equations in numerical codes to improve the realism of core collapse simulations in general relativity, is currently an emerging field where significant progress is bound to be soon achieved. The paper also contains a brief discussion of magneto-rotational simulations of core collapse, aiming at addressing the effects of magnetic fields on the collapse dynamics and on the gravitational waveforms

Contagious cooperation, temptation, and ecosystem collapse

NARCIS (Netherlands)

Richter, A.; van Soest, D.P.; Grasman, J.

2013-01-01

Real world observations suggest that social norms of cooperation can be effective in overcoming social dilemmas such as the joint management of a common pool resource—but also that they can be subject to slow erosion and sudden collapse. We show that these patterns of erosion and collapse emerge

How summit calderas collapse on basaltic volcanoes: new insights from the April 2007 caldera collapse of Piton de la Fournaise volcano

Energy Technology Data Exchange (ETDEWEB)

Michon, Laurent; Catry, Thibault; Merle, Olivier [Laboratoire GeoSciences Reunion, Universite de la Reunion, Institut de Physique du Globe de Paris, CNRS, UMR 7154 - Geologie des Systemes Volcaniques, 15 avenue Rene Cassin, 97715 Saint Denis (France); Villeneuve, Nicolas [Institut de Recherche pour le Developpement, US 140, BP172, 97492 Sainte-Clotilde cedex (France)], E-mail: laurent.michon@univ-reunion.fr

2008-10-01

In April 2007, Piton de la Fournaise volcano experienced a caldera collapse during its largest historical eruption. We present here the resulting deformation and a synthesis of the seismicity recorded during recent caldera collapses. It allows us to propose a unifying mechanism that explains the pulsating collapse dynamics.

HIERARCHICAL GRAVITATIONAL FRAGMENTATION. I. COLLAPSING CORES WITHIN COLLAPSING CLOUDS

Energy Technology Data Exchange (ETDEWEB)

Naranjo-Romero, Raúl; Vázquez-Semadeni, Enrique; Loughnane, Robert M. [Instituto de Radioastronomía y Astrofísica, Universidad Nacional Autónoma de México, Apdo. Postal 3-72, Morelia, Michoacán, 58089, México (Mexico)

2015-11-20

We investigate the Hierarchical Gravitational Fragmentation scenario through numerical simulations of the prestellar stages of the collapse of a marginally gravitationally unstable isothermal sphere immersed in a strongly gravitationally unstable, uniform background medium. The core developes a Bonnor–Ebert (BE)-like density profile, while at the time of singularity (the protostar) formation the envelope approaches a singular-isothermal-sphere (SIS)-like r{sup −2} density profile. However, these structures are never hydrostatic. In this case, the central flat region is characterized by an infall speed, while the envelope is characterized by a uniform speed. This implies that the hydrostatic SIS initial condition leading to Shu's classical inside-out solution is not expected to occur, and therefore neither should the inside-out solution. Instead, the solution collapses from the outside-in, naturally explaining the observation of extended infall velocities. The core, defined by the radius at which it merges with the background, has a time-variable mass, and evolves along the locus of the ensemble of observed prestellar cores in a plot of M/M{sub BE} versus M, where M is the core's mass and M{sub BE} is the critical BE mass, spanning the range from the “stable” to the “unstable” regimes, even though it is collapsing at all times. We conclude that the presence of an unstable background allows a core to evolve dynamically from the time when it first appears, even when it resembles a pressure-confined, stable BE-sphere. The core can be thought of as a ram-pressure confined BE-sphere, with an increasing mass due to the accretion from the unstable background.

Timescales of isotropic and anisotropic cluster collapse

Science.gov (United States)

Bartelmann, M.; Ehlers, J.; Schneider, P.

1993-12-01

From a simple estimate for the formation time of galaxy clusters, Richstone et al. have recently concluded that the evidence for non-virialized structures in a large fraction of observed clusters points towards a high value for the cosmological density parameter Omega0. This conclusion was based on a study of the spherical collapse of density perturbations, assumed to follow a Gaussian probability distribution. In this paper, we extend their treatment in several respects: first, we argue that the collapse does not start from a comoving motion of the perturbation, but that the continuity equation requires an initial velocity perturbation directly related to the density perturbation. This requirement modifies the initial condition for the evolution equation and has the effect that the collapse proceeds faster than in the case where the initial velocity perturbation is set to zero; the timescale is reduced by a factor of up to approximately equal 0.5. Our results thus strengthens the conclusion of Richstone et al. for a high Omega0. In addition, we study the collapse of density fluctuations in the frame of the Zel'dovich approximation, using as starting condition the analytically known probability distribution of the eigenvalues of the deformation tensor, which depends only on the (Gaussian) width of the perturbation spectrum. Finally, we consider the anisotropic collapse of density perturbations dynamically, again with initial conditions drawn from the probability distribution of the deformation tensor. We find that in both cases of anisotropic collapse, in the Zel'dovich approximation and in the dynamical calculations, the resulting distribution of collapse times agrees remarkably well with the results from spherical collapse. We discuss this agreement and conclude that it is mainly due to the properties of the probability distribution for the eigenvalues of the Zel'dovich deformation tensor. Hence, the conclusions of Richstone et al. on the value of Omega0 can be

CRYOVOLCANISM AND THE MYSTERY OF THE PATOM CONE

Directory of Open Access Journals (Sweden)

Vladimir R. Alekseyev

2012-01-01

Full Text Available In the Earth’s regions with cold climate, cryovolcanism is widespread. This phenomena is manifested as eruptions of material due to freezing of closed-type or open-type water-bearing systems which is accompanied by generation of effusive topographic forms, such as «pingo». The Patom cone is a typical structure created by cryovolcanism in fractured bedrocksof the Proterozoic age. The cone was shaped a result of the long-term, possibly multistage freezing of the hydrogeological structure during continuous and complicated phase of cryo- and speleo-genesis. The ice-saturated breccia containing limestone, sandstone and shale, which composed the cone, was subject to slow spreading due to its plastic properties; the top of the mound developed into a subsidence cone bordered by ring-shaped ramparts and a knoll in the middle, while thelongitudinal profile took on an asymmetric form. The absence of soil and vegetation cover on the surface of the cone, and a relatively weak degree of weathering of the rudaceous deposits bear no evidence that the geological object is young. The question as to the age of the cone is still open.

A reconstruction algorithms for helical cone-beam SPECT

International Nuclear Information System (INIS)

Weng, Y.; Zeng, G.L.; Gullberg, G.T.

1993-01-01

Cone-beam SPECT provides improved sensitivity for imaging small organs like the brain and heart. However, current cone-beam tomography with the focal point traversing a planar orbit does not acquire sufficient data to give an accurate reconstruction. In this paper, the authors employ a data-acquisition method which obtains complete data for cone-beam SPECT by simultaneously rotating the gamma camera and translating the patient bed, so that cone-beam projections can be obtained with the focal point traversing a helix surrounding the patient. An implementation of Grangeat's algorithm for helical cone-beam projections is developed. The algorithm requires a rebinning step to convert cone-beam data to parallel-beam data which are then reconstructed using the 3D Radon inversion. A fast new rebinning scheme is developed which uses all of the detected data to reconstruct the image and properly normalizes any multiply scanned data. This algorithm is shown to produce less artifacts than the commonly used Feldkamp algorithm when applied to either a circular planar orbit or a helical orbit acquisition. The algorithm can easily be extended to any arbitrary orbit

Thermal duality and gravitational collapse

International Nuclear Information System (INIS)

Hewitt, Michael

2015-01-01

Thermal duality is a relationship between the behaviour of heterotic string models of the E(8)×E(8) or SO(32) types at inversely related temperatures, a variant of T duality in the Euclidean regime. This duality would have consequences for the nature of the Hagedorn transition in these string models. We propose that the vacuum admits a family of deformations in situations where there are closed surfaces of constant area but high radial acceleration (a string regularized version of a Penrose trapped surface), such as would be formed in situations of extreme gravitational collapse. This would allow a radical resolution of the firewall paradox by allowing quantum effects to significantly modify the spacetime geometry around a collapsed object. A string bremsstrahlung process would convert the kinetic energy of infalling matter in extreme gravitational collapse to form a region of the deformed vacuum, which would be equivalent to forming a high temperature string phase. A heuristic criterion for the conversion process is presented, relating Newtonian gravity to the string tension, suggesting an upper limit to the strength of the gravitational interaction. This conversion process might have observable consequences for charged particles falling into a rotating collapsed object by producing high energy particles via a variant of the Penrose process. (paper)

Hydrogen-Poor Core-Collapse Supernovae

Science.gov (United States)

Pian, Elena; Mazzali, Paolo A.

Hydrogen-poor core-collapse supernovae (SNe) signal the explosive death of stars more massive than the progenitors of hydrogen-rich core-collapse supernovae, i.e., approximately in the range 15-50 M⊙ in main sequence. Since hydrogen-poor core-collapse supernovae include those that accompany gamma-ray bursts (GRBs), which were all rigorously identified with type Ic supernovae, their explosion energies cover almost two decades. The light curves and spectra are consequently very heterogeneous and often bear the signature of an asymmetric, i.e., aspherical, explosion. Asphericity is best traced by early-time (within days of the explosion) optical spectropolarimetry and by late-epoch (more than ˜ 100 days after explosion) low-resolution spectroscopy. While the relationship between hydrogen-poor core-collapse supernovae to hydrogen-poor super-luminous supernovae is not understood, a known case of association between an ultra-long gamma-ray burst and a very luminous hydrogen-poor supernova may help unraveling the connection. This is tantalizingly pointing to a magnetar powering source for both phenomena, although this scenario is still highly speculative. Host galaxies of hydrogen-poor supernovae are always star forming; in those of completely stripped supernovae and gamma-ray burst supernovae, the spatial distribution of the explosions follows the blue/ultraviolet light, with a correlation that is more than linear.

Understanding Core-Collapse Supernovae

Science.gov (United States)

Hix, W. R.; Lentz, E. J.; Baird, M.; Messer, O. E. B.; Mezzacappa, A.; Lee, C.-T.; Bruenn, S. W.; Blondin, J. M.; Marronetti, P.

2010-03-01

Our understanding of core-collapse supernovae continues to improve as better microphysics is included in increasingly realistic neutrino-radiationhydrodynamic simulations. Recent multi-dimensional models with spectral neutrino transport, which slowly develop successful explosions for a range of progenitors between 12 and 25 solar mass, have motivated changes in our understanding of the neutrino reheating mechanism. In a similar fashion, improvements in nuclear physics, most notably explorations of weak interactions on nuclei and the nuclear equation of state, continue to refine our understanding of how supernovae explode. Recent progresses on both the macroscopic and microscopic effects that affect core-collapse supernovae are discussed.

Magnetic tension and gravitational collapse

International Nuclear Information System (INIS)

Tsagas, Christos G

2006-01-01

The gravitational collapse of a magnetized medium is investigated by studying qualitatively the convergence of a timelike family of non-geodesic worldlines in the presence of a magnetic field. Focusing on the field's tension, we illustrate how the winding of the magnetic forcelines due to the fluid's rotation assists the collapse, while shear-like distortions in the distribution of the field's gradients resist contraction. We also show that the relativistic coupling between magnetism and geometry, together with the tension properties of the field, lead to a magneto-curvature stress that opposes the collapse. This tension stress grows stronger with increasing curvature distortion, which means that it could potentially dominate over the gravitational pull of the matter. If this happens, a converging family of non-geodesic worldlines can be prevented from focusing without violating the standard energy conditions

On the quantum corrected gravitational collapse

International Nuclear Information System (INIS)

Torres, Ramón; Fayos, Francesc

2015-01-01

Based on a previously found general class of quantum improved exact solutions composed of non-interacting (dust) particles, we model the gravitational collapse of stars. As the modeled star collapses a closed apparent 3-horizon is generated due to the consideration of quantum effects. The effect of the subsequent emission of Hawking radiation related to this horizon is taken into consideration. Our computations lead us to argue that a total evaporation could be reached. The inferred global picture of the spacetime corresponding to gravitational collapse is devoid of both event horizons and shell-focusing singularities. As a consequence, there is no information paradox and no need of firewalls

On the quantum corrected gravitational collapse

Directory of Open Access Journals (Sweden)

Ramón Torres

2015-07-01

Full Text Available Based on a previously found general class of quantum improved exact solutions composed of non-interacting (dust particles, we model the gravitational collapse of stars. As the modeled star collapses a closed apparent 3-horizon is generated due to the consideration of quantum effects. The effect of the subsequent emission of Hawking radiation related to this horizon is taken into consideration. Our computations lead us to argue that a total evaporation could be reached. The inferred global picture of the spacetime corresponding to gravitational collapse is devoid of both event horizons and shell-focusing singularities. As a consequence, there is no information paradox and no need of firewalls.

On the quantum corrected gravitational collapse

Science.gov (United States)

Torres, Ramón; Fayos, Francesc

2015-07-01

Based on a previously found general class of quantum improved exact solutions composed of non-interacting (dust) particles, we model the gravitational collapse of stars. As the modeled star collapses a closed apparent 3-horizon is generated due to the consideration of quantum effects. The effect of the subsequent emission of Hawking radiation related to this horizon is taken into consideration. Our computations lead us to argue that a total evaporation could be reached. The inferred global picture of the spacetime corresponding to gravitational collapse is devoid of both event horizons and shell-focusing singularities. As a consequence, there is no information paradox and no need of firewalls.

Histopathological Breast-Image Classification Using Local and Frequency Domains by Convolutional Neural Network

Directory of Open Access Journals (Sweden)

Abdullah-Al Nahid

2018-01-01

Full Text Available Identification of the malignancy of tissues from Histopathological images has always been an issue of concern to doctors and radiologists. This task is time-consuming, tedious and moreover very challenging. Success in finding malignancy from Histopathological images primarily depends on long-term experience, though sometimes experts disagree on their decisions. However, Computer Aided Diagnosis (CAD techniques help the radiologist to give a second opinion that can increase the reliability of the radiologist’s decision. Among the different image analysis techniques, classification of the images has always been a challenging task. Due to the intense complexity of biomedical images, it is always very challenging to provide a reliable decision about an image. The state-of-the-art Convolutional Neural Network (CNN technique has had great success in natural image classification. Utilizing advanced engineering techniques along with the CNN, in this paper, we have classified a set of Histopathological Breast-Cancer (BC images utilizing a state-of-the-art CNN model containing a residual block. Conventional CNN operation takes raw images as input and extracts the global features; however, the object oriented local features also contain significant information—for example, the Local Binary Pattern (LBP represents the effective textural information, Histogram represent the pixel strength distribution, Contourlet Transform (CT gives much detailed information about the smoothness about the edges, and Discrete Fourier Transform (DFT derives frequency-domain information from the image. Utilizing these advantages, along with our proposed novel CNN model, we have examined the performance of the novel CNN model as Histopathological image classifier. To do so, we have introduced five cases: (a Convolutional Neural Network Raw Image (CNN-I; (b Convolutional Neural Network CT Histogram (CNN-CH; (c Convolutional Neural Network CT LBP (CNN-CL; (d Convolutional

Estimating the number of sources in a noisy convolutive mixture using BIC

DEFF Research Database (Denmark)

Olsson, Rasmus Kongsgaard; Hansen, Lars Kai

2004-01-01

The number of source signals in a noisy convolutive mixture is determined based on the exact log-likelihoods of the candidate models. In (Olsson and Hansen, 2004), a novel probabilistic blind source separator was introduced that is based solely on the time-varying second-order statistics of the s......The number of source signals in a noisy convolutive mixture is determined based on the exact log-likelihoods of the candidate models. In (Olsson and Hansen, 2004), a novel probabilistic blind source separator was introduced that is based solely on the time-varying second-order statistics...

The Application of Real Convolution for Analytically Evaluating Fermi-Dirac-Type and Bose-Einstein-Type Integrals

Directory of Open Access Journals (Sweden)

Jerry P. Selvaggi

2018-01-01

Full Text Available The Fermi-Dirac-type or Bose-Einstein-type integrals can be transformed into two convergent real-convolution integrals. The transformation simplifies the integration process and may ultimately produce a complete analytical solution without recourse to any mathematical approximations. The real-convolution integrals can either be directly integrated or be transformed into the Laplace Transform inversion integral in which case the full power of contour integration becomes available. Which method is employed is dependent upon the complexity of the real-convolution integral. A number of examples are introduced which will illustrate the efficacy of the analytical approach.

Integrity of the cone photoreceptor mosaic in oligocone trichromacy

DEFF Research Database (Denmark)

Michaelides, Michel; Rha, Jungtae; Dees, Elise W

2011-01-01

Oligocone trichromacy (OT) is an unusual cone dysfunction syndrome characterized by reduced visual acuity, mild photophobia, reduced amplitude of the cone electroretinogram with normal rod responses, normal fundus appearance, and normal or near-normal color vision. It has been proposed that these......Oligocone trichromacy (OT) is an unusual cone dysfunction syndrome characterized by reduced visual acuity, mild photophobia, reduced amplitude of the cone electroretinogram with normal rod responses, normal fundus appearance, and normal or near-normal color vision. It has been proposed...

Simulation analysis of the effects of an initial cone position and opening angle on a cone-guided implosion

Energy Technology Data Exchange (ETDEWEB)

Yanagawa, T. [Department of Physics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8602 (Japan); Sakagami, H. [Fundamental Physics Simulation Division, National Institute for Fusion Science, Oroshi-cho, Toki, Gifu 509-5292 (Japan); Nagatomo, H. [Institute of Laser Engineering, Osaka University, Suita, Osaka 565-0871 (Japan)

2013-10-15

In inertial confinement fusion, the implosion process is important in forming a high-density plasma core. In the case of a fast ignition scheme using a cone-guided target, the fuel target is imploded with a cone inserted. This scheme is advantageous for efficiently heating the imploded fuel core; however, asymmetric implosion is essentially inevitable. Moreover, the effect of cone position and opening angle on implosion also becomes critical. Focusing on these problems, the effect of the asymmetric implosion, the initial position, and the opening angle on the compression rate of the fuel is investigated using a three-dimensional pure hydrodynamic code.

Adversarial training and dilated convolutions for brain MRI segmentation

NARCIS (Netherlands)

Moeskops, P.; Veta, M.; Lafarge, M.W.; Eppenhof, K.A.J.; Pluim, J.P.W.

2017-01-01

Convolutional neural networks (CNNs) have been applied to various automatic image segmentation tasks in medical image analysis, including brain MRI segmentation. Generative adversarial networks have recently gained popularity because of their power in generating images that are difficult to

a Novel Deep Convolutional Neural Network for Spectral-Spatial Classification of Hyperspectral Data

Science.gov (United States)

Li, N.; Wang, C.; Zhao, H.; Gong, X.; Wang, D.

2018-04-01

Spatial and spectral information are obtained simultaneously by hyperspectral remote sensing. Joint extraction of these information of hyperspectral image is one of most import methods for hyperspectral image classification. In this paper, a novel deep convolutional neural network (CNN) is proposed, which extracts spectral-spatial information of hyperspectral images correctly. The proposed model not only learns sufficient knowledge from the limited number of samples, but also has powerful generalization ability. The proposed framework based on three-dimensional convolution can extract spectral-spatial features of labeled samples effectively. Though CNN has shown its robustness to distortion, it cannot extract features of different scales through the traditional pooling layer that only have one size of pooling window. Hence, spatial pyramid pooling (SPP) is introduced into three-dimensional local convolutional filters for hyperspectral classification. Experimental results with a widely used hyperspectral remote sensing dataset show that the proposed model provides competitive performance.

Quantifying the interplay effect in prostate IMRT delivery using a convolution-based method

International Nuclear Information System (INIS)

Li, Haisen S.; Chetty, Indrin J.; Solberg, Timothy D.

2008-01-01

The authors present a segment-based convolution method to account for the interplay effect between intrafraction organ motion and the multileaf collimator position for each particular segment in intensity modulated radiation therapy (IMRT) delivered in a step-and-shoot manner. In this method, the static dose distribution attributed to each segment is convolved with the probability density function (PDF) of motion during delivery of the segment, whereas in the conventional convolution method (''average-based convolution''), the static dose distribution is convolved with the PDF averaged over an entire fraction, an entire treatment course, or even an entire patient population. In the case of IMRT delivered in a step-and-shoot manner, the average-based convolution method assumes that in each segment the target volume experiences the same motion pattern (PDF) as that of population. In the segment-based convolution method, the dose during each segment is calculated by convolving the static dose with the motion PDF specific to that segment, allowing both intrafraction motion and the interplay effect to be accounted for in the dose calculation. Intrafraction prostate motion data from a population of 35 patients tracked using the Calypso system (Calypso Medical Technologies, Inc., Seattle, WA) was used to generate motion PDFs. These were then convolved with dose distributions from clinical prostate IMRT plans. For a single segment with a small number of monitor units, the interplay effect introduced errors of up to 25.9% in the mean CTV dose compared against the planned dose evaluated by using the PDF of the entire fraction. In contrast, the interplay effect reduced the minimum CTV dose by 4.4%, and the CTV generalized equivalent uniform dose by 1.3%, in single fraction plans. For entire treatment courses delivered in either a hypofractionated (five fractions) or conventional (>30 fractions) regimen, the discrepancy in total dose due to interplay effect was negligible

Cone penetrometer moisture probe acceptance test report

International Nuclear Information System (INIS)

Barnes, G.A.

1996-01-01

This Acceptance Test Report (ATR) documents the results of WHC-SD-WM-ATP-146 (Prototype Cone Penetrometer Moisture Probe Acceptance Test Procedure) and WHC-SD-WM-ATP-145 (Cone Penetrometer Moisture Probe Acceptance Test Procedure). The master copy of WHC-SD-WM-ATP-145 can be found in Appendix A and the master copy of WHC-SD-WM-ATP-146 can be found in Appendix B. Also included with this report is a matrix showing design criteria of the cone penetrometer moisture probe and the verification method used (Appendix C)

Concatenated coding systems employing a unit-memory convolutional code and a byte-oriented decoding algorithm

Science.gov (United States)

Lee, L.-N.

1977-01-01

Concatenated coding systems utilizing a convolutional code as the inner code and a Reed-Solomon code as the outer code are considered. In order to obtain very reliable communications over a very noisy channel with relatively modest coding complexity, it is proposed to concatenate a byte-oriented unit-memory convolutional code with an RS outer code whose symbol size is one byte. It is further proposed to utilize a real-time minimal-byte-error probability decoding algorithm, together with feedback from the outer decoder, in the decoder for the inner convolutional code. The performance of the proposed concatenated coding system is studied, and the improvement over conventional concatenated systems due to each additional feature is isolated.

Space-Time Convolutional Codes over Finite Fields and Rings for Systems with Large Diversity Order

Directory of Open Access Journals (Sweden)

B. F. Uchôa-Filho

2008-06-01

Full Text Available We propose a convolutional encoder over the finite ring of integers modulo pk,ℤpk, where p is a prime number and k is any positive integer, to generate a space-time convolutional code (STCC. Under this structure, we prove three properties related to the generator matrix of the convolutional code that can be used to simplify the code search procedure for STCCs over ℤpk. Some STCCs of large diversity order (≥4 designed under the trace criterion for n=2,3, and 4 transmit antennas are presented for various PSK signal constellations.

Techniques for optimizing nanotips derived from frozen taylor cones

Science.gov (United States)

Hirsch, Gregory

2017-12-05

Optimization techniques are disclosed for producing sharp and stable tips/nanotips relying on liquid Taylor cones created from electrically conductive materials with high melting points. A wire substrate of such a material with a preform end in the shape of a regular or concave cone, is first melted with a focused laser beam. Under the influence of a high positive potential, a Taylor cone in a liquid/molten state is formed at that end. The cone is then quenched upon cessation of the laser power, thus freezing the Taylor cone. The tip of the frozen Taylor cone is reheated by the laser to allow its precise localized melting and shaping. Tips thus obtained yield desirable end-forms suitable as electron field emission sources for a variety of applications. In-situ regeneration of the tip is readily accomplished. These tips can also be employed as regenerable bright ion sources using field ionization/desorption of introduced chemical species.

Shock-induced nanobubble collapse and its applications

Science.gov (United States)

Vedadi, Mohammad Hossein

The shock-induced collapse of nanobubbles in water is investigated using molecular dynamics simulations based on a reactive force field. Monitoring the collapse of a cavitation nanobubble, we observe a focused nanojet at the onset of bubble shrinkage and a water hammer shock wave upon bubble collapse. The nanojet length scales linearly with the nanobubble radius, as observed in experiments on micron-to-millimeter size bubbles. The shock induces dramatic structural changes, including an ice-VII-like structural motif at a particle velocity of approximately 1 km/s. The incipient ice VII formation and the calculated Hugoniot curve are in good agreement with experimental results. Moreover, a substantial number of positive and negative ions appear when the nanojet hits the distal side of the nanobubble and the water hammer shock forms. Furthermore, two promising applications of shock-induced nanobubble collapse have been explored. Our simulations of poration in lipid bilayers due to shock-induced collapse of nanobubbles reveal penetration of nanojets into lipid bilayers. The nanojet impact generates shear flow of water on bilayer leaflets and pressure gradients across them, which transiently enhance the bilayer permeability by creating nanopores through which water molecules translocate across the bilayer. The effects of nanobubble size and temperature on the porosity of lipid bilayers are examined. Finally, the shock-induced collapse of CO2-filled nanobubbles in water is investigated. The energetic nanojet and high-pressure water hammer shock formed during and after collapse of the nanobubble trigger mechano-chemical H2O-CO2 reactions, some of which lead to splitting of water molecules. The dominant pathways through which splitting of water molecules occur are identified.

An Analysis Model for Water Cone Subsidence in Bottom Water Drive Reservoirs

Science.gov (United States)

Wang, Jianjun; Xu, Hui; Wu, Shucheng; Yang, Chao; Kong, lingxiao; Zeng, Baoquan; Xu, Haixia; Qu, Tailai

2017-12-01

Water coning in bottom water drive reservoirs, which will result in earlier water breakthrough, rapid increase in water cut and low recovery level, has drawn tremendous attention in petroleum engineering field. As one simple and effective method to inhibit bottom water coning, shut-in coning control is usually preferred in oilfield to control the water cone and furthermore to enhance economic performance. However, most of the water coning researchers just have been done on investigation of the coning behavior as it grows up, the reported studies for water cone subsidence are very scarce. The goal of this work is to present an analytical model for water cone subsidence to analyze the subsidence of water cone when the well shut in. Based on Dupuit critical oil production rate formula, an analytical model is developed to estimate the initial water cone shape at the point of critical drawdown. Then, with the initial water cone shape equation, we propose an analysis model for water cone subsidence in bottom water reservoir reservoirs. Model analysis and several sensitivity studies are conducted. This work presents accurate and fast analytical model to perform the water cone subsidence in bottom water drive reservoirs. To consider the recent interests in development of bottom drive reservoirs, our approach provides a promising technique for better understanding the subsidence of water cone.

Quality assessment and enhancement for cone-beam computed tomography in dental imaging

International Nuclear Information System (INIS)

Jeon, Sung Chae

2006-02-01

Cone-beam CT will become increasingly important in diagnostic imaging modality in the dental practice over the next decade. For dental diagnostic imaging, cone-beam computed tomography (CBCT) system based on large area flat panel imager has been designed and developed for three-dimensional volumetric image. The new CBCT system can provide a 3-D volumetric image during only one circular scanning with relatively short times (20-30 seconds) and requires less radiation dose than that of conventional CT. To reconstruct volumetric image from 2-D projection images, FDK algorithm was employed. The prototype of our CBCT system gives the promising results that can be efficiently diagnosed. This dissertation deals with assessment, enhancement, and optimization for dental cone-beam computed tomography with high performance. A new blur estimation method was proposed, namely model based estimation algorithm. Based on the empirical model of the PSF, an image restoration is applied to radiological images. The accuracy of the PSF estimation under Poisson noise and readout electronic noise is significantly better for the R-L estimator than the Wiener estimator. In the image restoration experiment, the result showed much better improvement in the low and middle range of spatial frequency. Our proposed algorithm is more simple and effective method to determine 2-D PSF of the x-ray imaging system than traditional methods. Image based scatter correction scheme to reduce the scatter effects was proposed. This algorithm corrects scatter on projection images based on convolution, scatter fraction, and angular interpolation. The scatter signal was estimated by convolving a projection image with scatter point spread function (SPSF) followed by multiplication with scatter fraction. Scatter fraction was estimated using collimator which is similar to SPECS method. This method does not require extra x-ray dose and any additional phantom. Maximum estimated error for interpolation was less than 7

Combining morphometric features and convolutional networks fusion for glaucoma diagnosis

Science.gov (United States)

Perdomo, Oscar; Arevalo, John; González, Fabio A.

2017-11-01

Glaucoma is an eye condition that leads to loss of vision and blindness. Ophthalmoscopy exam evaluates the shape, color and proportion between the optic disc and physiologic cup, but the lack of agreement among experts is still the main diagnosis problem. The application of deep convolutional neural networks combined with automatic extraction of features such as: the cup-to-disc distance in the four quadrants, the perimeter, area, eccentricity, the major radio, the minor radio in optic disc and cup, in addition to all the ratios among the previous parameters may help with a better automatic grading of glaucoma. This paper presents a strategy to merge morphological features and deep convolutional neural networks as a novel methodology to support the glaucoma diagnosis in eye fundus images.

Airplane detection in remote sensing images using convolutional neural networks

Science.gov (United States)

Ouyang, Chao; Chen, Zhong; Zhang, Feng; Zhang, Yifei

2018-03-01

Airplane detection in remote sensing images remains a challenging problem and has also been taking a great interest to researchers. In this paper we propose an effective method to detect airplanes in remote sensing images using convolutional neural networks. Deep learning methods show greater advantages than the traditional methods with the rise of deep neural networks in target detection, and we give an explanation why this happens. To improve the performance on detection of airplane, we combine a region proposal algorithm with convolutional neural networks. And in the training phase, we divide the background into multi classes rather than one class, which can reduce false alarms. Our experimental results show that the proposed method is effective and robust in detecting airplane.

Convolute laminations — a theoretical analysis: example of a Pennsylvanian sandstone

Science.gov (United States)

Visher, Glenn S.; Cunningham, Russ D.

1981-03-01

Data from an outcropping laminated interval were collected and analyzed to test the applicability of a theoretical model describing instability of layered systems. Rayleigh—Taylor wave perturbations result at the interface between fluids of contrasting density, viscosity, and thickness. In the special case where reverse density and viscosity interlaminations are developed, the deformation response produces a single wave with predictable amplitudes, wavelengths, and amplification rates. Physical measurements from both the outcropping section and modern sediments suggest the usefulness of the model for the interpretation of convolute laminations. Internal characteristics of the stratigraphic interval, and the developmental sequence of convoluted beds, are used to document the developmental history of these structures.

Cone Penetrometer N Factor Determination Testing Results

Energy Technology Data Exchange (ETDEWEB)

Follett, Jordan R.

2014-03-05

This document contains the results of testing activities to determine the empirical 'N Factor' for the cone penetrometer in kaolin clay simulant. The N Factor is used to releate resistance measurements taken with the cone penetrometer to shear strength.

Lung lobe collapse: pathophysiology and radiologic significance

International Nuclear Information System (INIS)

Lord, P.F.; Gomez, J.A.

1985-01-01

The radiographic changes caused by collapse of lung lobes in pulmonary disease, pneumothorax, and pleural effusion depend on the lobar recoiling force and local pleural pressure. Differences in the tendency of normal lung lobes or regions to collapse depend on the relative surface-to-volume ratio, determined by shape and size of the region or lobe. This ratio affects the physiologic parameters of pulmonary interdependence, compliance, and collateral air flow. Pulmonary surfactant increases compliance, particularly at low volumes, maintains alveolar stability, and assists in maintaining capillary patency and preventing pulmonary edema. Its loss due to lung injury increases collapsing forces. In the presence of pneumothorax or pleural effusion, diseases that cause lobar collapse produce localized air or fluid entrapment that is a diagnostic sign of the presence of the underlying pulmonary disease

Collapse and stability of single- and multi-wall carbon nanotubes

International Nuclear Information System (INIS)

Xiao, J; Liu, B; Huang, Y; Zuo, J; Hwang, K-C; Yu, M-F

2007-01-01

The collapse and stability of carbon nanotubes (CNTs) have important implications for their synthesis and applications. While nanotube collapse has been observed experimentally, the conditions for the collapse, especially its dependence on tube structures, are not clear. We have studied the energetics of the collapse of single- and multi-wall CNTs via atomistic simulations. The collapse is governed by the number of walls and the radius of the inner-most wall. The collapsed structure is energetically favored about a certain diameter, which is 4.12, 4.96 and 5.76 nm for single-, double- and triple-wall CNTs, respectively. The CNT chirality also has a strong influence on the collapsed structure, leading to flat, warped and twisted CNTs, depending on the chiral angle

Preparation of Au cone for fast ignition target

International Nuclear Information System (INIS)

Du Kai; Zhou Lan; Zhang Lin; Wan Xiaobo; Xiao Jiang

2005-01-01

Cone-shell target is typically used for the fast ignition experiments of inertial confinement fusion. In order to fabricate cone-shell target the Au cones with different angles were produced by electroplating and precise machining. The Au electroplating process was introduced in the paper, and the dependence of coating quality on the parameters, such as composition, temperature, pH of electroplating bath, current density and tip effect, were discussed. (author)

Loss and gain of cone types in vertebrate ciliary photoreceptor evolution.

Science.gov (United States)

Musser, Jacob M; Arendt, Detlev

2017-11-01

Ciliary photoreceptors are a diverse cell type family that comprises the rods and cones of the retina and other related cell types such as pineal photoreceptors. Ciliary photoreceptor evolution has been dynamic during vertebrate evolution with numerous gains and losses of opsin and phototransduction genes, and changes in their expression. For example, early mammals lost all but two cone opsins, indicating loss of cone receptor types in response to nocturnal lifestyle. Our review focuses on the comparison of specifying transcription factors and cell type-specific transcriptome data in vertebrate retinae to build and test hypotheses on ciliary photoreceptor evolution. Regarding cones, recent data reveal that a combination of factors specific for long-wavelength sensitive opsin (Lws)- cones in non-mammalian vertebrates (Thrb and Rxrg) is found across all differentiating cone photoreceptors in mice. This suggests that mammalian ancestors lost all but one ancestral cone type, the Lws-cone. We test this hypothesis by a correlation analysis of cone transcriptomes in mouse and chick, and find that, indeed, transcriptomes of all mouse cones are most highly correlated to avian Lws-cones. These findings underscore the importance of specifying transcription factors in tracking cell type evolution, and shed new light on the mechanisms of cell type loss and gain in retina evolution. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Alcoholism Detection by Data Augmentation and Convolutional Neural Network with Stochastic Pooling.

Science.gov (United States)

Wang, Shui-Hua; Lv, Yi-Ding; Sui, Yuxiu; Liu, Shuai; Wang, Su-Jing; Zhang, Yu-Dong

2017-11-17

Alcohol use disorder (AUD) is an important brain disease. It alters the brain structure. Recently, scholars tend to use computer vision based techniques to detect AUD. We collected 235 subjects, 114 alcoholic and 121 non-alcoholic. Among the 235 image, 100 images were used as training set, and data augmentation method was used. The rest 135 images were used as test set. Further, we chose the latest powerful technique-convolutional neural network (CNN) based on convolutional layer, rectified linear unit layer, pooling layer, fully connected layer, and softmax layer. We also compared three different pooling techniques: max pooling, average pooling, and stochastic pooling. The results showed that our method achieved a sensitivity of 96.88%, a specificity of 97.18%, and an accuracy of 97.04%. Our method was better than three state-of-the-art approaches. Besides, stochastic pooling performed better than other max pooling and average pooling. We validated CNN with five convolution layers and two fully connected layers performed the best. The GPU yielded a 149× acceleration in training and a 166× acceleration in test, compared to CPU.

Feedback-induced glutamate spillover enhances negative feedback from horizontal cells to cones

NARCIS (Netherlands)

Vroman, Rozan; Kamermans, M.

2015-01-01

KEY POINTS: In the retina, horizontal cells feed back negatively to cone photoreceptors. Glutamate released from cones can spill over to neighbouring cones. Here we show that cone glutamate release induced by negative feedback can also spill over to neighbouring cones. This glutamate activates the

Feedback-induced glutamate spillover enhances negative feedback from horizontal cells to cones

NARCIS (Netherlands)

Vroman, Rozan; Kamermans, Maarten

2015-01-01

In the retina, horizontal cells feed back negatively to cone photoreceptors. Glutamate released from cones can spill over to neighbouring cones. Here we show that cone glutamate release induced by negative feedback can also spill over to neighbouring cones. This glutamate activates the glutamate

Cardiac cone-beam CT

International Nuclear Information System (INIS)

Manzke, Robert

2005-01-01

This doctoral thesis addresses imaging of the heart with retrospectively gated helical cone-beam computed tomography (CT). A thorough review of the CT reconstruction literature is presented in combination with a historic overview of cardiac CT imaging and a brief introduction to other cardiac imaging modalities. The thesis includes a comprehensive chapter about the theory of CT reconstruction, familiarizing the reader with the problem of cone-beam reconstruction. The anatomic and dynamic properties of the heart are outlined and techniques to derive the gating information are reviewed. With the extended cardiac reconstruction (ECR) framework, a new approach is presented for the heart-rate-adaptive gated helical cardiac cone-beam CT reconstruction. Reconstruction assessment criteria such as the temporal resolution, the homogeneity in terms of the cardiac phase, and the smoothness at cycle-to-cycle transitions are developed. Several reconstruction optimization approaches are described: An approach for the heart-rate-adaptive optimization of the temporal resolution is presented. Streak artifacts at cycle-to-cycle transitions can be minimized by using an improved cardiac weighting scheme. The optimal quiescent cardiac phase for the reconstruction can be determined automatically with the motion map technique. Results for all optimization procedures applied to ECR are presented and discussed based on patient and phantom data. The ECR algorithm is analyzed for larger detector arrays of future cone-beam systems throughout an extensive simulation study based on a four-dimensional cardiac CT phantom. The results of the scientific work are summarized and an outlook proposing future directions is given. The presented thesis is available for public download at www.cardiac-ct.net

Hierarchical Recurrent Neural Hashing for Image Retrieval With Hierarchical Convolutional Features.

Science.gov (United States)

Lu, Xiaoqiang; Chen, Yaxiong; Li, Xuelong

Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep

Diffraction and Dirchlet problem for parameter-elliptic convolution ...

African Journals Online (AJOL)

In this paper we evaluate the difference between the inverse operators of a Dirichlet problem and of a diffraction problem for parameter-elliptic convolution operators with constant symbols. We prove that the inverse operator of a Dirichlet problem can be obtained as a limit case of such a diffraction problem. Quaestiones ...

Cone calorimeter tests of wood composites

Science.gov (United States)

Robert H. White; Kuma Sumathipala

2013-01-01

The cone calorimeter is widely used for the determination of the heat release rate (HRR) of building products and other materials. As part of an effort to increase the availability of cone calorimeter data on wood products, the U.S. Forest Products Laboratory and the American Wood Council conducted this study on composite wood products in cooperation with the Composite...

Transfer Learning with Convolutional Neural Networks for Classification of Abdominal Ultrasound Images.

Science.gov (United States)

Cheng, Phillip M; Malhi, Harshawn S

2017-04-01

The purpose of this study is to evaluate transfer learning with deep convolutional neural networks for the classification of abdominal ultrasound images. Grayscale images from 185 consecutive clinical abdominal ultrasound studies were categorized into 11 categories based on the text annotation specified by the technologist for the image. Cropped images were rescaled to 256 × 256 resolution and randomized, with 4094 images from 136 studies constituting the training set, and 1423 images from 49 studies constituting the test set. The fully connected layers of two convolutional neural networks based on CaffeNet and VGGNet, previously trained on the 2012 Large Scale Visual Recognition Challenge data set, were retrained on the training set. Weights in the convolutional layers of each network were frozen to serve as fixed feature extractors. Accuracy on the test set was evaluated for each network. A radiologist experienced in abdominal ultrasound also independently classified the images in the test set into the same 11 categories. The CaffeNet network classified 77.3% of the test set images accurately (1100/1423 images), with a top-2 accuracy of 90.4% (1287/1423 images). The larger VGGNet network classified 77.9% of the test set accurately (1109/1423 images), with a top-2 accuracy of VGGNet was 89.7% (1276/1423 images). The radiologist classified 71.7% of the test set images correctly (1020/1423 images). The differences in classification accuracies between both neural networks and the radiologist were statistically significant (p convolutional neural networks may be used to construct effective classifiers for abdominal ultrasound images.

Trajectory Generation Method with Convolution Operation on Velocity Profile

Energy Technology Data Exchange (ETDEWEB)

Lee, Geon [Hanyang Univ., Seoul (Korea, Republic of); Kim, Doik [Korea Institute of Science and Technology, Daejeon (Korea, Republic of)

2014-03-15

The use of robots is no longer limited to the field of industrial robots and is now expanding into the fields of service and medical robots. In this light, a trajectory generation method that can respond instantaneously to the external environment is strongly required. Toward this end, this study proposes a method that enables a robot to change its trajectory in real-time using a convolution operation. The proposed method generates a trajectory in real time and satisfies the physical limits of the robot system such as acceleration and velocity limit. Moreover, a new way to improve the previous method, which generates inefficient trajectories in some cases owing to the characteristics of the trapezoidal shape of trajectories, is proposed by introducing a triangle shape. The validity and effectiveness of the proposed method is shown through a numerical simulation and a comparison with the previous convolution method.

Field Experiment on Soaking Characteristics of Collapsible Loess

Directory of Open Access Journals (Sweden)

Zhichao Wang

2017-01-01

Full Text Available In collapsible loess area, migration of soil moisture often causes the temporal discontinuity and spatial nonuniformity of collapsibility, which leads to great damage for infrastructures. Therefore, the research on water infiltration is the key to solving the problem of collapsibility. The aim of this paper is to investigate the spatiotemporal evolution of infiltration characteristics of collapsible loess. A field soaking experiment was conducted on collapsible loess in western China, in which a soaking pool with diameter of 15 m was built. Time-Domain-Reflectometry (TDR system and soil sampling were employed to measure the water content within the depth of 12 m. Then the saturation isograms were drawn for visualization of the process of infiltration. Also, a pilot tunnel was excavated to investigate how the free face can affect the infiltration behaviors. The experimental results revealed the characteristics of infiltration in both horizontal and vertical directions. Moreover, the response of free face on infiltration behaviors was also found. These findings of research could provide the data for the infiltration laws of unsaturated loess and thereby provide the basis for integrated treatment of collapsible loess.

Correlated random walks induced by dynamical wavefunction collapse

Science.gov (United States)

Bedingham, Daniel

2015-03-01

Wavefunction collapse models modify Schrödinger's equation so that it describes the collapse of a superposition of macroscopically distinguishable states as a genuine physical process [PRA 42, 78 (1990)]. This provides a basis for the resolution of the quantum measurement problem. An additional generic consequence of the collapse mechanism is that it causes particles to exhibit a tiny random diffusive motion. Furthermore, the diffusions of two sufficiently nearby particles are positively correlated -- it is more likely that the particles diffuse in the same direction than would happen if they behaved independently [PRA 89, 032713 (2014)]. The use of this effect is proposed as an experimental test of wave function collapse models in which pairs of nanoparticles are simultaneously released from nearby traps and allowed a brief period of free fall. The random displacements of the particles are then measured. The experiment must be carried out at sufficiently low temperature and pressure for the collapse effects to dominate over the ambient environmental noise. It is argued that these constraints can be satisfied by current technologies for a large class of viable wavefunction collapse models. Work supported by the Templeton World Charity Foundation.

Cone penetrometer demonstration standard startup review checklist

International Nuclear Information System (INIS)

KRIEG, S.A.

1998-01-01

Startup readiness for the Cone Penetrometer Demonstration in AX Tank Farm will be verified through the application of a Standard Startup Review Checklist. This is a listing of those items essential to demonstrating readiness to start the Cone Penetrometer Demonstration in AX Tank Farm

Revision total knee arthroplasty with the use of trabecular metal cones

DEFF Research Database (Denmark)

Jensen, Claus L; Petersen, Michael Mygind; Schrøder, Henrik

2012-01-01

"Trabecular Metal Cone" (TM Cone) (Zimmer, Inc, Warsaw, Ind) for reconstruction of bone loss in the proximal tibia during revision total knee arthroplasty is now optional. Forty patients were randomized to receive revision total knee arthroplasty with or without TM Cone (No TM Cone). The Anderson...

Derivation of the gauge link in light cone gauge

International Nuclear Information System (INIS)

Gao Jianhua

2010-01-01

In light cone gauge, a gauge link at light cone infinity is necessary for transverse momentum-dependent parton distribution to restore the gauge invariance in some specific boundary conditions. We derive such transverse gauge link in a more regular and general method. We find the gauge link at light cone infinity naturally arises from the contribution of the pinched poles: one is from the quark propagator and the other is hidden in the gauge vector field in light cone gauge. Actually, in the amplitude level, we have obtained a more general gauge link over the hypersurface at light cone infinity which is beyond the transverse direction. The difference of such gauge link between semi-inclusive deep inelastic scattering and Drell-Yan processes can also be obtained directly and clearly in our derivation.

Cooperation, cheating, and collapse in biological populations

Science.gov (United States)

Gore, Jeff

2014-03-01

Natural populations can collapse suddenly in response to small changes in environmental conditions, and recovery from such a collapse can be difficult. We have used laboratory microbial ecosystems to directly measure theoretically proposed early warning signals of impending population collapse. Yeast cooperatively break down the sugar sucrose, meaning that below a critical size the population cannot sustain itself. We have demonstrated experimentally that changes in the fluctuations of the population size can serve as an early warning signal that the population is close to collapse. The cooperative nature of yeast growth on sucrose suggests that the population may be susceptible to ``cheater'' cells, which do not contribute to the public good and instead merely take advantage of the cooperative cells. We confirm this possibility experimentally and find that such social parasitism decreases the resilience of the population.

The onset of coherence collapse in DBR lasers

International Nuclear Information System (INIS)

Woodward, S.L.; Koch, T.L.; Koren, U.

1990-01-01

The authors investigate how the onset of coherence collapse depends on laser output power. The lasers were three-section multiquantum-well distributed-Bragg-reflector (MQW-DBR) lasers. The fraction of light reflected back into the lasing mode was varied, and the point at which the transition to coherence collapse occurred was measured. This feedback level varies approximately linearly with laser output power. For these lasers, when the output power is 1 mW, the transition to coherence collapse beings when the optical feedback into the lasing mode is below - 40 dBm; when the feedback power is - 35 dBm the laser line is completely collapsed

Venomics-Accelerated Cone Snail Venom Peptide Discovery

Science.gov (United States)

Himaya, S. W. A.

2018-01-01

Cone snail venoms are considered a treasure trove of bioactive peptides. Despite over 800 species of cone snails being known, each producing over 1000 venom peptides, only about 150 unique venom peptides are structurally and functionally characterized. To overcome the limitations of the traditional low-throughput bio-discovery approaches, multi-omics systems approaches have been introduced to accelerate venom peptide discovery and characterisation. This “venomic” approach is starting to unravel the full complexity of cone snail venoms and to provide new insights into their biology and evolution. The main challenge for venomics is the effective integration of transcriptomics, proteomics, and pharmacological data and the efficient analysis of big datasets. Novel database search tools and visualisation techniques are now being introduced that facilitate data exploration, with ongoing advances in related omics fields being expected to further enhance venomics studies. Despite these challenges and future opportunities, cone snail venomics has already exponentially expanded the number of novel venom peptide sequences identified from the species investigated, although most novel conotoxins remain to be pharmacologically characterised. Therefore, efficient high-throughput peptide production systems and/or banks of miniaturized discovery assays are required to overcome this bottleneck and thus enhance cone snail venom bioprospecting and accelerate the identification of novel drug leads. PMID:29522462

Venomics-Accelerated Cone Snail Venom Peptide Discovery

Directory of Open Access Journals (Sweden)

S. W. A. Himaya

2018-03-01

Full Text Available Cone snail venoms are considered a treasure trove of bioactive peptides. Despite over 800 species of cone snails being known, each producing over 1000 venom peptides, only about 150 unique venom peptides are structurally and functionally characterized. To overcome the limitations of the traditional low-throughput bio-discovery approaches, multi-omics systems approaches have been introduced to accelerate venom peptide discovery and characterisation. This “venomic” approach is starting to unravel the full complexity of cone snail venoms and to provide new insights into their biology and evolution. The main challenge for venomics is the effective integration of transcriptomics, proteomics, and pharmacological data and the efficient analysis of big datasets. Novel database search tools and visualisation techniques are now being introduced that facilitate data exploration, with ongoing advances in related omics fields being expected to further enhance venomics studies. Despite these challenges and future opportunities, cone snail venomics has already exponentially expanded the number of novel venom peptide sequences identified from the species investigated, although most novel conotoxins remain to be pharmacologically characterised. Therefore, efficient high-throughput peptide production systems and/or banks of miniaturized discovery assays are required to overcome this bottleneck and thus enhance cone snail venom bioprospecting and accelerate the identification of novel drug leads.

Quasi-cyclic unit memory convolutional codes

DEFF Research Database (Denmark)

Justesen, Jørn; Paaske, Erik; Ballan, Mark

1990-01-01

Unit memory convolutional codes with generator matrices, which are composed of circulant submatrices, are introduced. This structure facilitates the analysis of efficient search for good codes. Equivalences among such codes and some of the basic structural properties are discussed. In particular......, catastrophic encoders and minimal encoders are characterized and dual codes treated. Further, various distance measures are discussed, and a number of good codes, some of which result from efficient computer search and some of which result from known block codes, are presented...

Galileon radiation from a spherical collapsing shell

Energy Technology Data Exchange (ETDEWEB)

Martín-García, Javier [Instituto de Física Teórica UAM/CSIC,C/ Nicolás Cabrera 15, E-28049 Madrid (Spain); Vázquez-Mozo, Miguel Á. [Instituto Universitario de Física Fundamental y Matemáticas (IUFFyM),Universidad de Salamanca, Plaza de la Merced s/n, E-37008 Salamanca (Spain)

2017-01-17

Galileon radiation in the collapse of a thin spherical shell of matter is analyzed. In the framework of a cubic Galileon theory, we compute the field profile produced at large distances by a short collapse, finding that the radiated field has two peaks traveling ahead of light fronts. The total energy radiated during the collapse follows a power law scaling with the shell’s physical width and results from two competing effects: a Vainshtein suppression of the emission and an enhancement due to the thinness of the shell.

Avian cone photoreceptors tile the retina as five independent, self-organizing mosaics.

Directory of Open Access Journals (Sweden)

Yoseph A Kram

2010-02-01

Full Text Available The avian retina possesses one of the most sophisticated cone photoreceptor systems among vertebrates. Birds have five types of cones including four single cones, which support tetrachromatic color vision and a double cone, which is thought to mediate achromatic motion perception. Despite this richness, very little is known about the spatial organization of avian cones and its adaptive significance. Here we show that the five cone types of the chicken independently tile the retina as highly ordered mosaics with a characteristic spacing between cones of the same type. Measures of topological order indicate that double cones are more highly ordered than single cones, possibly reflecting their posited role in motion detection. Although cones show spacing interactions that are cell type-specific, all cone types use the same density-dependent yardstick to measure intercone distance. We propose a simple developmental model that can account for these observations. We also show that a single parameter, the global regularity index, defines the regularity of all five cone mosaics. Lastly, we demonstrate similar cone distributions in three additional avian species, suggesting that these patterning principles are universal among birds. Since regular photoreceptor spacing is critical for uniform sampling of visual space, the cone mosaics of the avian retina represent an elegant example of the emergence of adaptive global patterning secondary to simple local interactions between individual photoreceptors. Our results indicate that the evolutionary pressures that gave rise to the avian retina's various adaptations for enhanced color discrimination also acted to fine-tune its spatial sampling of color and luminance.

The collapse of acoustic waves in dispersive media

International Nuclear Information System (INIS)

Kuznetsov, E.A.; Musher, S.L.; Shafarenko, A.V.

1983-01-01

The existence of the collapse of acoustic waves with a positive dispersion is demonstrated. A qualitative description of wave collapse, based on the analysis of invariants, is proposed. Through the use of a numerical simulation, it is established that, in the Kadomtsev-Petviashvili three-dimensional equation, collapse is accompanied by the formation of a weakly turbulent background by the wave radiation from the cavity

Finding strong lenses in CFHTLS using convolutional neural networks

Science.gov (United States)

Jacobs, C.; Glazebrook, K.; Collett, T.; More, A.; McCarthy, C.

2017-10-01

We train and apply convolutional neural networks, a machine learning technique developed to learn from and classify image data, to Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) imaging for the identification of potential strong lensing systems. An ensemble of four convolutional neural networks was trained on images of simulated galaxy-galaxy lenses. The training sets consisted of a total of 62 406 simulated lenses and 64 673 non-lens negative examples generated with two different methodologies. An ensemble of trained networks was applied to all of the 171 deg2 of the CFHTLS wide field image data, identifying 18 861 candidates including 63 known and 139 other potential lens candidates. A second search of 1.4 million early-type galaxies selected from the survey catalogue as potential deflectors, identified 2465 candidates including 117 previously known lens candidates, 29 confirmed lenses/high-quality lens candidates, 266 novel probable or potential lenses and 2097 candidates we classify as false positives. For the catalogue-based search we estimate a completeness of 21-28 per cent with respect to detectable lenses and a purity of 15 per cent, with a false-positive rate of 1 in 671 images tested. We predict a human astronomer reviewing candidates produced by the system would identify 20 probable lenses and 100 possible lenses per hour in a sample selected by the robot. Convolutional neural networks are therefore a promising tool for use in the search for lenses in current and forthcoming surveys such as the Dark Energy Survey and the Large Synoptic Survey Telescope.

Classification of stroke disease using convolutional neural network

Science.gov (United States)

Marbun, J. T.; Seniman; Andayani, U.

2018-03-01

Stroke is a condition that occurs when the blood supply stop flowing to the brain because of a blockage or a broken blood vessel. A symptoms that happen when experiencing stroke, some of them is a dropped consciousness, disrupted vision and paralyzed body. The general examination is being done to get a picture of the brain part that have stroke using Computerized Tomography (CT) Scan. The image produced from CT will be manually checked and need a proper lighting by doctor to get a type of stroke. That is why it needs a method to classify stroke from CT image automatically. A method proposed in this research is Convolutional Neural Network. CT image of the brain is used as the input for image processing. The stage before classification are image processing (Grayscaling, Scaling, Contrast Limited Adaptive Histogram Equalization, then the image being classified with Convolutional Neural Network. The result then showed that the method significantly conducted was able to be used as a tool to classify stroke disease in order to distinguish the type of stroke from CT image.

Image Classification Based on Convolutional Denoising Sparse Autoencoder

Directory of Open Access Journals (Sweden)

Shuangshuang Chen

2017-01-01

Full Text Available Image classification aims to group images into corresponding semantic categories. Due to the difficulties of interclass similarity and intraclass variability, it is a challenging issue in computer vision. In this paper, an unsupervised feature learning approach called convolutional denoising sparse autoencoder (CDSAE is proposed based on the theory of visual attention mechanism and deep learning methods. Firstly, saliency detection method is utilized to get training samples for unsupervised feature learning. Next, these samples are sent to the denoising sparse autoencoder (DSAE, followed by convolutional layer and local contrast normalization layer. Generally, prior in a specific task is helpful for the task solution. Therefore, a new pooling strategy—spatial pyramid pooling (SPP fused with center-bias prior—is introduced into our approach. Experimental results on the common two image datasets (STL-10 and CIFAR-10 demonstrate that our approach is effective in image classification. They also demonstrate that none of these three components: local contrast normalization, SPP fused with center-prior, and l2 vector normalization can be excluded from our proposed approach. They jointly improve image representation and classification performance.

Enhancing neutron beam production with a convoluted moderator

Energy Technology Data Exchange (ETDEWEB)

Iverson, E.B., E-mail: iversoneb@ornl.gov [Spallation Neutron Source, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Baxter, D.V. [Center for the Exploration of Energy and Matter, Indiana University, Bloomington, IN 47408 (United States); Muhrer, G. [Lujan Neutron Scattering Center, Los Alamos National Laboratory, P.O. Box 1663, Los Alamos, NM 87545 (United States); Ansell, S.; Dalgliesh, R. [ISIS Facility, Rutherford Appleton Laboratory, Chilton (United Kingdom); Gallmeier, F.X. [Spallation Neutron Source, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Kaiser, H. [Center for the Exploration of Energy and Matter, Indiana University, Bloomington, IN 47408 (United States); Lu, W. [Spallation Neutron Source, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States)

2014-10-21

We describe a new concept for a neutron moderating assembly resulting in the more efficient production of slow neutron beams. The Convoluted Moderator, a heterogeneous stack of interleaved moderating material and nearly transparent single-crystal spacers, is a directionally enhanced neutron beam source, improving beam emission over an angular range comparable to the range accepted by neutron beam lines and guides. We have demonstrated gains of 50% in slow neutron intensity for a given fast neutron production rate while simultaneously reducing the wavelength-dependent emission time dispersion by 25%, both coming from a geometric effect in which the neutron beam lines view a large surface area of moderating material in a relatively small volume. Additionally, we have confirmed a Bragg-enhancement effect arising from coherent scattering within the single-crystal spacers. We have not observed hypothesized refractive effects leading to additional gains at long wavelength. In addition to confirmation of the validity of the Convoluted Moderator concept, our measurements provide a series of benchmark experiments suitable for developing simulation and analysis techniques for practical optimization and eventual implementation at slow neutron source facilities.

Multi-Input Convolutional Neural Network for Flower Grading

Directory of Open Access Journals (Sweden)

Yu Sun

2017-01-01

Full Text Available Flower grading is a significant task because it is extremely convenient for managing the flowers in greenhouse and market. With the development of computer vision, flower grading has become an interdisciplinary focus in both botany and computer vision. A new dataset named BjfuGloxinia contains three quality grades; each grade consists of 107 samples and 321 images. A multi-input convolutional neural network is designed for large scale flower grading. Multi-input CNN achieves a satisfactory accuracy of 89.6% on the BjfuGloxinia after data augmentation. Compared with a single-input CNN, the accuracy of multi-input CNN is increased by 5% on average, demonstrating that multi-input convolutional neural network is a promising model for flower grading. Although data augmentation contributes to the model, the accuracy is still limited by lack of samples diversity. Majority of misclassification is derived from the medium class. The image processing based bud detection is useful for reducing the misclassification, increasing the accuracy of flower grading to approximately 93.9%.

A Convolution Tree with Deconvolution Branches: Exploiting Geometric Relationships for Single Shot Keypoint Detection

OpenAIRE

Kumar, Amit; Chellappa, Rama

2017-01-01

Recently, Deep Convolution Networks (DCNNs) have been applied to the task of face alignment and have shown potential for learning improved feature representations. Although deeper layers can capture abstract concepts like pose, it is difficult to capture the geometric relationships among the keypoints in DCNNs. In this paper, we propose a novel convolution-deconvolution network for facial keypoint detection. Our model predicts the 2D locations of the keypoints and their individual visibility ...

Homoclinic phenomena in the gravitational collapse

International Nuclear Information System (INIS)

Koiller, J.; Mello Neto, J.R.T. de; Soares, I.D.

1984-01-01

A class of Bianchi IX cosmological models is shown to have chaotic gravitational collapse, due to Poincare's homoclinic phenomena. Such models can be programmed so that for any given positive integer N (N=infinity included) the universe undergoes N non-periodic oscillations (each oscillation requiring a long time) before collapsing. For N=infinity the universe undergoes periodic oscillations. (Author) [pt

Non explosive collapse of white dwarfs

International Nuclear Information System (INIS)

Canal, R.; Schatzmann, E.

1976-01-01

We show that if a sufficiently cold carbon-oxygen white dwarf, close to the critical mass, accretes matter from a companion in a binary system, the time scale of collapse is long enough to allow neutronization before the onset of pycnonuclear reactions. This can possibly lead to the formation of X-ray sources by a non explosive collapse. (orig.) [de

Design of a cone target for fast ignition

Directory of Open Access Journals (Sweden)

Sunahara Atsushi

2013-11-01

Full Text Available We propose a new type of target for the fast ignition of inertial confinement fusion. Pre-formed plasma inside a cone target can significantly reduce the energy coupling efficiency from the ultra-high intense short-pulse laser to the imploded core plasma. Also, in order to protect the tip of the cone and reduce generation of pre-formed plasma, we propose pointed shaped cone target. In our estimation, the shock traveling time can be delayed 20–30 ps by lower-Z material with larger areal density compared to the conventional gold flat tip. Also, the jet flow can sweep the blow-off plasma from the tip of the cone, and the implosion performance is not drastically affected by the existence of pointed tip. In addition, the self-generated magnetic field is generated along the boundary of cone tip and surrounding CD or DT plasma. This magnetic field can confine fast electrons and focus to the implosion core plasma. Resultant heating efficiency is improved by 30% compared to that with conventional gold flat tip.

Noise masking of S-cone increments and decrements.

Science.gov (United States)

Wang, Quanhong; Richters, David P; Eskew, Rhea T

2014-11-12

S-cone increment and decrement detection thresholds were measured in the presence of bipolar, dynamic noise masks. Noise chromaticities were the L-, M-, and S-cone directions, as well as L-M, L+M, and achromatic (L+M+S) directions. Noise contrast power was varied to measure threshold Energy versus Noise (EvN) functions. S+ and S- thresholds were similarly, and weakly, raised by achromatic noise. However, S+ thresholds were much more elevated by S, L+M, L-M, L- and M-cone noises than were S- thresholds, even though the noises consisted of two symmetric chromatic polarities of equal contrast power. A linear cone combination model accounts for the overall pattern of masking of a single test polarity well. L and M cones have opposite signs in their effects upon raising S+ and S- thresholds. The results strongly indicate that the psychophysical mechanisms responsible for S+ and S- detection, presumably based on S-ON and S-OFF pathways, are distinct, unipolar mechanisms, and that they have different spatiotemporal sampling characteristics, or contrast gains, or both. © 2014 ARVO.

Identifying Dirac cones in carbon allotropes with square symmetry

Energy Technology Data Exchange (ETDEWEB)

Wang, Jinying [College of Chemistry and Molecular Engineering, Peking University, Beijing 100871 (China); Huang, Huaqing; Duan, Wenhui [Department of Physics, Tsinghua University, Beijing 100084 (China); Liu, Zhirong, E-mail: LiuZhiRong@pku.edu.cn [College of Chemistry and Molecular Engineering, Peking University, Beijing 100871 (China); State Key Laboratory for Structural Chemistry of Unstable and Stable Species and Beijing National Laboratory for Molecular Sciences (BNLMS), Peking University, Beijing 100871 (China)

2013-11-14

A theoretical study is conducted to search for Dirac cones in two-dimensional carbon allotropes with square symmetry. By enumerating the carbon atoms in a unit cell up to 12, an allotrope with octatomic rings is recognized to possess Dirac cones under a simple tight-binding approach. The obtained Dirac cones are accompanied by flat bands at the Fermi level, and the resulting massless Dirac-Weyl fermions are chiral particles with a pseudospin of S = 1, rather than the conventional S = 1/2 of graphene. The spin-1 Dirac cones are also predicted to exist in hexagonal graphene antidot lattices.

Conical Refraction: new observations and a dual cone model.

Science.gov (United States)

Sokolovskii, G S; Carnegie, D J; Kalkandjiev, T K; Rafailov, E U

2013-05-06

We propose a paraxial dual-cone model of conical refraction involving the interference of two cones of light behind the exit face of the crystal. The supporting experiment is based on beam selecting elements breaking down the conically refracted beam into two separate hollow cones which are symmetrical with one another. The shape of these cones of light is a product of a 'competition' between the divergence caused by the conical refraction and the convergence due to the focusing by the lens. The developed mathematical description of the conical refraction demonstrates an excellent agreement with experiment.

Radiation dose delivery verification in the treatment of carcinoma-cervix

International Nuclear Information System (INIS)

Shrotriya, D.; Srivastava, R. N. L.; Kumar, S.

2015-01-01

The accurate dose delivery to the clinical target volume in radiotherapy can be affected by various pelvic tissues heterogeneities. An in-house heterogeneous woman pelvic phantom was designed and used to verify the consistency and computational capability of treatment planning system of radiation dose delivery in the treatment of cancer cervix. Oncentra 3D-TPS with collapsed cone convolution (CCC) dose calculation algorithm was used to generate AP/PA and box field technique plan. the radiation dose was delivered by Primus Linac (Siemens make) employing high energy 15 MV photon beam by isocenter technique. A PTW make, 0.125cc ionization chamber was used for direct measurements at various reference points in cervix, bladder and rectum. The study revealed that maximum variation between computed and measured dose at cervix reference point was 1% in both the techniques and 3% and 4% variation in AP/PA field and 5% and 4.5% in box technique at bladder and rectum points respectively

Radiation dose delivery verification in the treatment of carcinoma-cervix

Science.gov (United States)

Shrotriya, D.; Kumar, S.; Srivastava, R. N. L.

2015-06-01

The accurate dose delivery to the clinical target volume in radiotherapy can be affected by various pelvic tissues heterogeneities. An in-house heterogeneous woman pelvic phantom was designed and used to verify the consistency and computational capability of treatment planning system of radiation dose delivery in the treatment of cancer cervix. Oncentra 3D-TPS with collapsed cone convolution (CCC) dose calculation algorithm was used to generate AP/PA and box field technique plan. the radiation dose was delivered by Primus Linac (Siemens make) employing high energy 15 MV photon beam by isocenter technique. A PTW make, 0.125cc ionization chamber was used for direct measurements at various reference points in cervix, bladder and rectum. The study revealed that maximum variation between computed and measured dose at cervix reference point was 1% in both the techniques and 3% and 4% variation in AP/PA field and 5% and 4.5% in box technique at bladder and rectum points respectively.

Radiation dose delivery verification in the treatment of carcinoma-cervix

Energy Technology Data Exchange (ETDEWEB)

Shrotriya, D., E-mail: shrotriya2007@gmail.com; Srivastava, R. N. L. [Department of Radiotherapy, J.K. Cancer Institute Kanpur-208019 (India); Kumar, S. [Department of Physics, Christ Church College, Kanpur-208001 (India)

2015-06-24

The accurate dose delivery to the clinical target volume in radiotherapy can be affected by various pelvic tissues heterogeneities. An in-house heterogeneous woman pelvic phantom was designed and used to verify the consistency and computational capability of treatment planning system of radiation dose delivery in the treatment of cancer cervix. Oncentra 3D-TPS with collapsed cone convolution (CCC) dose calculation algorithm was used to generate AP/PA and box field technique plan. the radiation dose was delivered by Primus Linac (Siemens make) employing high energy 15 MV photon beam by isocenter technique. A PTW make, 0.125cc ionization chamber was used for direct measurements at various reference points in cervix, bladder and rectum. The study revealed that maximum variation between computed and measured dose at cervix reference point was 1% in both the techniques and 3% and 4% variation in AP/PA field and 5% and 4.5% in box technique at bladder and rectum points respectively.

Conceptual Design of Deployment Structure of Morphing Nose Cone

Directory of Open Access Journals (Sweden)

Junlan Li

2013-01-01

Full Text Available For a reusable space vehicle or a missile, the shape of the nose cone has a significant effect on the drag of the vehicle. In this paper, the concept of morphing nose cone is proposed to reduce the drag when the reentry vehicle flies back into the atmosphere. The conceptual design of the structure of morphing nose cone is conducted. Mechanical design and optimization approach are developed by employing genetic algorithm to find the optimal geometric parameters of the morphing structure. An example is analyzed by using the proposed method. The results show that optimal solution supplies the minimum position error. The concept of morphing nose cone will provide a novel way for the drag reduction of reentry vehicle. The proposed method could be practically used for the design and optimization of the deployable structure of morphing nose cone.

Non-Spherical Gravitational Collapse of Strange Quark Matter

Institute of Scientific and Technical Information of China (English)

Zade S S; Patil K D; Mulkalwar P N

2008-01-01

We study the non-spherical gravitational collapse of the strange quark null fluid.The interesting feature which emerges is that the non-spherical collapse of charged strange quark matter leads to a naked singularity whereas the gravitational collapse of neutral quark matter proceeds to form a black hole.We extend the earlier work of Harko and Cheng[Phys.Lett.A 266 (2000) 249]to the non-spherical case.

Full utilization of semi-Dirac cones in photonics

Science.gov (United States)

Yasa, Utku G.; Turduev, Mirbek; Giden, Ibrahim H.; Kurt, Hamza

2018-05-01

In this study, realization and applications of anisotropic zero-refractive-index materials are proposed by exposing the unit cells of photonic crystals that exhibit Dirac-like cone dispersion to rotational symmetry reduction. Accidental degeneracy of two Bloch modes in the Brillouin zone center of two-dimensional C2-symmetric photonic crystals gives rise to the semi-Dirac cone dispersion. The proposed C2-symmetric photonic crystals behave as epsilon-and-mu-near-zero materials (ɛeff≈ 0 , μeff≈ 0 ) along one propagation direction, but behave as epsilon-near-zero material (ɛeff≈ 0 , μeff≠ 0 ) for the perpendicular direction at semi-Dirac frequency. By extracting the effective medium parameters of the proposed C4- and C2-symmetric periodic media that exhibit Dirac-like and semi-Dirac cone dispersions, intrinsic differences between isotropic and anisotropic materials are investigated. Furthermore, advantages of utilizing semi-Dirac cone materials instead of Dirac-like cone materials in photonic applications are demonstrated in both frequency and time domains. By using anisotropic transmission behavior of the semi-Dirac materials, photonic application concepts such as beam deflectors, beam splitters, and light focusing are proposed. Furthermore, to the best of our knowledge, semi-Dirac cone dispersion is also experimentally demonstrated for the first time by including negative, zero, and positive refraction states of the given material.

Cadmium Removal from Aqueous Solutions by Ground Pine Cone

Directory of Open Access Journals (Sweden)

H Izanloo, S Nasseri

2005-01-01

Full Text Available A study on the removal of cadmium ions from aqueous solutions by pine cone was conducted in batch conditions. Kinetic data and equilibrium removal isotherms were obtained. The influence of different experimental parameters such as contact time, initial concentration of cadmium, pine cone mass and particle size, and temperature on the kinetics of cadmium removal was studied. Results showed that the main parameters that played an important role in removal phenomenon were initial cadmium concentration, particle size and pine cone mass. The necessary time to reach equilibrium was between 4 and 7 hours based on the initial concentration of cadmium. The capacity of cadmium adsorption at equilibrium increased with the decrease of pine cone particle size. The capacity of cadmium adsorption at equilibrium by pine cone increased with the quantity of pine cone introduced (1–4 g/L. Temperature in the range of 20-30°C showed a restricted effect on the removal kinetics (13.56 mg/g at 20°C and a low capacity of adsorption about 11.48 mg/g at 30°C. The process followed pseudo second-order kinetics. The cadmium uptake of pine cone was quantitatively evaluated using adsorption isotherms. Results indicated that the Langmuir model gave a better fit to the experimental data in comparison with the Freundlich equation.

Two-level convolution formula for nuclear structure function

Science.gov (United States)

Ma, Boqiang

1990-05-01

A two-level convolution formula for the nuclear structure function is derived in considering the nucleus as a composite system of baryon-mesons which are also composite systems of quark-gluons again. The results show that the European Muon Colaboration effect can not be explained by the nuclear effects as nucleon Fermi motion and nuclear binding contributions.

Two-level convolution formula for nuclear structure function

International Nuclear Information System (INIS)

Ma Boqiang

1990-01-01

A two-level convolution formula for the nuclear structure function is derived in considering the nucleus as a composite system of baryon-mesons which are also composite systems of quark-gluons again. The results show that the European Muon Colaboration effect can not be explained by the nuclear effects as nucleon Fermi motion and nuclear binding contributions

General relativistic collapse of rotating stars

International Nuclear Information System (INIS)

Nakamura, T.

1984-01-01

When a rotating star begins to collapse, the gravity becomes so strong that there appears a region from which even a photon cannot escape. After the distortion of space-time is radiated as gravitational waves, a Kerr black hole is formed finally. One of the main goals for numerical relativity is to simulate the collapse of a rotating star under realistic conditions. However, to know both the dynamics of matter and the propagation of gravitational radiation seems to be very difficult. Therefore, in this paper the problem is divided into 4 stages. They are: (1) The time evolution of pure gravitational waves is calculated in a 2-D code. (2) In this stage, the author tries to understand the dynamics of a collapsing, rotating star in 2D code. (3) Combining the techniques from stages 1, 2, the author tries to know both the dynamics of matter and the propagation of gravitational waves generated by the nonspherical motion of matter. (4) The author simulates the gravitational collapse of a rotating star to a black hole in 3D. 25 references, 12 figures, 1 table

Correction of the tip convolution effects in the imaging of nanostructures studied through scanning force microscopy

International Nuclear Information System (INIS)

Canet-Ferrer, Josep; Coronado, Eugenio; Forment-Aliaga, Alicia; Pinilla-Cienfuegos, Elena

2014-01-01

AFM images are always affected by artifacts arising from tip convolution effects, resulting in a decrease in the lateral resolution of this technique. The magnitude of such effects is described by means of geometrical considerations, thereby providing better understanding of the convolution phenomenon. We demonstrate that for a constant tip radius, the convolution error is increased with the object height, mainly for the narrowest motifs. Certain influence of the object shape is observed between rectangular and elliptical objects with the same height. Such moderate differences are essentially expected among elongated objects; in contrast they are reduced as the object aspect ratio is increased. Finally, we propose an algorithm to study the influence of the size, shape and aspect ratio of different nanometric motifs on a flat substrate. Indeed, with this algorithm, convolution artifacts can be extended to any kind of motif including real surface roughness. From the simulation results we demonstrate that in most cases the real motif’s width can be estimated from AFM images without knowing its shape in detail. (paper)

JWFront: Wavefronts and Light Cones for Kerr Spacetimes

Science.gov (United States)

Frutos Alfaro, Francisco; Grave, Frank; Müller, Thomas; Adis, Daria

2015-04-01

JWFront visualizes wavefronts and light cones in general relativity. The interactive front-end allows users to enter the initial position values and choose the values for mass and angular momentum per unit mass. The wavefront animations are available in 2D and 3D; the light cones are visualized using the coordinate systems (t, x, y) or (t, z, x). JWFront can be easily modified to simulate wavefronts and light cones for other spacetime by providing the Christoffel symbols in the program.

Tracking blue cone signals in the primate brain.

Science.gov (United States)

Jayakumar, Jaikishan; Dreher, Bogdan; Vidyasagar, Trichur R

2013-05-01

In this paper, we review the path taken by signals originating from the short wavelength sensitive cones (S-cones) in Old World and New World primates. Two types of retinal ganglion cells (RGCs) carrying S-cone signals (blue-On and blue-Off cells) project to the dorsal lateral geniculate nucleus (dLGN) in the thalamus. In all primates, these S-cone signals are relayed through the 'dust-like' (konis in classical Greek) dLGN cells. In New World primates such as common marmoset, these very small cells are known to form distinct and spatially extensive, koniocellular layers. Although in Old World primates, such as macaques, koniocellular layers tend to be very thin, the adjacent parvocellular layers contain distinct koniocellular extensions. It appears that all S-cone signals are relayed through such konio cells, whether they are in the main koniocellular layers or in their colonies within the parvocellular layers of the dLGN. In the primary visual cortex, these signals begin to merge with the signals carried by the other two principal parallel channels, namely the magnocellular and parvocellular channels. This article will also review the possible routes taken by the S-cone signals to reach one of the topographically organised extrastriate visual cortical areas, the middle temporal area (area MT). This area is the major conduit for signals reaching the parietal cortex. Alternative visual inputs to area MT not relayed via the primary visual cortex area (V1) may provide the neurological basis for the phenomenon of 'blindsight' observed in human and non-human primates, who have partial or complete damage to the primary visual cortex. Short wavelength sensitive cone (S-cone) signals to area MT may also play a role in directing visual attention with possible implications for understanding the pathology in dyslexia and some of its treatment options. © 2012 The Authors. Clinical and Experimental Optometry © 2012 Optometrists Association Australia.

Cinder cones of Mount Slamet, Central Java, Indonesia

Directory of Open Access Journals (Sweden)

Igan S. SutawIdjaja

2014-06-01

Full Text Available http://dx.doi.org/10.17014/ijog.vol4no1.20096The Mount Slamet volcanic field in Central Java, Indonesia, contains thirty five cinder cones within an area of 90 sq. km in the east flank of the volcano. The cinder cones occur singly or in small groups, with diameter of the base ranges from 130 - 750 m and the height is around 250 m. Within the volcanic field, the cinder cones are spread over the volcanic area at the distance of 4 to 14 km from the eruption center of the Slamet Volcano. They are concentrated within latitudes 7°11’00” - 7°16’00” S,, and longitudes 109°15’00” - 109°18’00” E. The density of the cinder cones is about 1.5 cones/km2. Most of the cinder cones lie on the Tertiary sedimentary rocks along the NW-trending fault system and on radial fractures. The structural pattern may be related to the radial faults in this region. The cone surfaces are commonly blanketed by Slamet air-falls and lava flows. The deposits consist of poorly bedded, very coarse-grained, occasionally overlain by oxidized scoria, and large-sized of ballistic bombs and blocks. There are various kind of volcanic bombs originating from scoriae ballistic rock fragments. The other kind of volcanic bombs are breadcrust bomb, almond seed or contorted shape. All of the cinder cones have undergone degradation, which can be observed from the characters of gully density and surface morphology. By using Porter parameters, Hco is equal to 0.25 Wco, whilst Wcr is equal to 0.40 Wco. The Hco/Wco ratio is higher than Hco = 0.2 Wco reference line. A radiometric dating using K-Ar method carried out on a scoria bomb yields the age of 0.042 + 0.020 Ma.  

Cardiopulmonary Collapse during Labour

Directory of Open Access Journals (Sweden)

Vasilis Sitras

2010-01-01

Full Text Available Cardiopulmonary collapse during labour is a catastrophic event caused by various medical, surgical and obstetrical conditions. It is an emergency that threatens the life of the mother and her unborn child. We present a case of a pregnant woman who suffered from preeclampsia and underwent induction of labour. Severe lung edema occurred early in labour that caused cardiopulmonary collapse. Advanced heart-lung resuscitation was established immediately and continued until an emergency cesarean section was performed few minutes later. The outcome was favourable for both mother and child. We further discuss some aspects of the pathophysiology and appropriate treatment of cardiorespiratory arrest during labour, which involves the coordinated action of the obstetric, pediatric and surgical ward personnel.

Jordan's algebra of a facially homogeneous autopolar cone

International Nuclear Information System (INIS)

Bellissard, Jean; Iochum, Bruno

1979-01-01

It is shown that a Jordan-Banach algebra with predual may be canonically associated with a facially homogeneous autopolar cone. This construction generalizes the case where a trace vector exists in the cone [fr

The covariant entropy bound in gravitational collapse

International Nuclear Information System (INIS)

Gao, Sijie; Lemos, Jose P. S.

2004-01-01

We study the covariant entropy bound in the context of gravitational collapse. First, we discuss critically the heuristic arguments advanced by Bousso. Then we solve the problem through an exact model: a Tolman-Bondi dust shell collapsing into a Schwarzschild black hole. After the collapse, a new black hole with a larger mass is formed. The horizon, L, of the old black hole then terminates at the singularity. We show that the entropy crossing L does not exceed a quarter of the area of the old horizon. Therefore, the covariant entropy bound is satisfied in this process. (author)

Scalar field collapse in Gauss-Bonnet gravity

Science.gov (United States)

Banerjee, Narayan; Paul, Tanmoy

2018-02-01

We consider a "scalar-Einstein-Gauss-Bonnet" theory in four dimension, where the scalar field couples non-minimally with the Gauss-Bonnet (GB) term. This coupling with the scalar field ensures the non-topological character of the GB term. In this scenario, we examine the possibility for collapsing of the scalar field. Our result reveals that such a collapse is possible in the presence of Gauss-Bonnet gravity for suitable choices of parametric regions. The singularity formed as a result of the collapse is found to be a curvature singularity which is hidden from the exterior by an apparent horizon.

Self-similar Langmuir collapse at critical dimension

International Nuclear Information System (INIS)

Berge, L.; Dousseau, Ph.; Pelletier, G.; Pesme, D.

1991-01-01

Two spherically symmetric versions of a self-similar collapse are investigated within the framework of the Zakharov equations, namely, one relative to a vectorial electric field and the other corresponding to a scalar modeling of the Langmuir field. Singular solutions of both of them depend on a linear time contraction rate ξ(t) = V(t * -t), where t * and V = -ξ denote, respectively, the collapse time and the constant collapse velocity. It is shown that under certain conditions, only the scalar model admits self-similar solutions, varying regularly as a function of the control parameter V from the subsonic (V >1) regime. (author)

Core-Collapse Supernovae, Neutrinos, and Gravitational Waves

Energy Technology Data Exchange (ETDEWEB)

Ott, C.D. [TAPIR, California Institute of Technology, Pasadena, California (United States); Kavli Institute for the Physics and Mathematics of the Universe, Kashiwa, Chiba (Japan); O' Connor, E.P. [Canadian Institute for Theoretical Astrophysics, Toronto, Ontario (Canada); Gossan, S.; Abdikamalov, E.; Gamma, U.C.T. [TAPIR, California Institute of Technology, Pasadena, California (United States); Drasco, S. [Grinnell College, Grinnell, Iowa (United States); TAPIR, California Institute of Technology, Pasadena, California (United States)

2013-02-15

Core-collapse supernovae are among the most energetic cosmic cataclysms. They are prodigious emitters of neutrinos and quite likely strong galactic sources of gravitational waves. Observation of both neutrinos and gravitational waves from the next galactic or near extragalactic core-collapse supernova will yield a wealth of information on the explosion mechanism, but also on the structure and angular momentum of the progenitor star, and on aspects of fundamental physics such as the equation of state of nuclear matter at high densities and low entropies. In this contribution to the proceedings of the Neutrino 2012 conference, we summarize recent progress made in the theoretical understanding and modeling of core-collapse supernovae. In this, our emphasis is on multi-dimensional processes involved in the explosion mechanism such as neutrino-driven convection and the standing accretion shock instability. As an example of how supernova neutrinos can be used to probe fundamental physics, we discuss how the rise time of the electron antineutrino flux observed in detectors can be used to probe the neutrino mass hierarchy. Finally, we lay out aspects of the neutrino and gravitational-wave signature of core-collapse supernovae and discuss the power of combined analysis of neutrino and gravitational wave data from the next galactic core-collapse supernova.

Core-Collapse Supernovae, Neutrinos, and Gravitational Waves

International Nuclear Information System (INIS)

Ott, C.D.; O'Connor, E.P.; Gossan, S.; Abdikamalov, E.; Gamma, U.C.T.; Drasco, S.

2013-01-01

Core-collapse supernovae are among the most energetic cosmic cataclysms. They are prodigious emitters of neutrinos and quite likely strong galactic sources of gravitational waves. Observation of both neutrinos and gravitational waves from the next galactic or near extragalactic core-collapse supernova will yield a wealth of information on the explosion mechanism, but also on the structure and angular momentum of the progenitor star, and on aspects of fundamental physics such as the equation of state of nuclear matter at high densities and low entropies. In this contribution to the proceedings of the Neutrino 2012 conference, we summarize recent progress made in the theoretical understanding and modeling of core-collapse supernovae. In this, our emphasis is on multi-dimensional processes involved in the explosion mechanism such as neutrino-driven convection and the standing accretion shock instability. As an example of how supernova neutrinos can be used to probe fundamental physics, we discuss how the rise time of the electron antineutrino flux observed in detectors can be used to probe the neutrino mass hierarchy. Finally, we lay out aspects of the neutrino and gravitational-wave signature of core-collapse supernovae and discuss the power of combined analysis of neutrino and gravitational wave data from the next galactic core-collapse supernova

Infimal Convolution Regularisation Functionals of BV and Lp Spaces

KAUST Repository

Burger, Martin

2016-02-03

We study a general class of infimal convolution type regularisation functionals suitable for applications in image processing. These functionals incorporate a combination of the total variation seminorm and Lp norms. A unified well-posedness analysis is presented and a detailed study of the one-dimensional model is performed, by computing exact solutions for the corresponding denoising problem and the case p=2. Furthermore, the dependency of the regularisation properties of this infimal convolution approach to the choice of p is studied. It turns out that in the case p=2 this regulariser is equivalent to the Huber-type variant of total variation regularisation. We provide numerical examples for image decomposition as well as for image denoising. We show that our model is capable of eliminating the staircasing effect, a well-known disadvantage of total variation regularisation. Moreover as p increases we obtain almost piecewise affine reconstructions, leading also to a better preservation of hat-like structures.

Improving deep convolutional neural networks with mixed maxout units.

Directory of Open Access Journals (Sweden)

Hui-Zhen Zhao

Full Text Available Motivated by insights from the maxout-units-based deep Convolutional Neural Network (CNN that "non-maximal features are unable to deliver" and "feature mapping subspace pooling is insufficient," we present a novel mixed variant of the recently introduced maxout unit called a mixout unit. Specifically, we do so by calculating the exponential probabilities of feature mappings gained by applying different convolutional transformations over the same input and then calculating the expected values according to their exponential probabilities. Moreover, we introduce the Bernoulli distribution to balance the maximum values with the expected values of the feature mappings subspace. Finally, we design a simple model to verify the pooling ability of mixout units and a Mixout-units-based Network-in-Network (NiN model to analyze the feature learning ability of the mixout models. We argue that our proposed units improve the pooling ability and that mixout models can achieve better feature learning and classification performance.

Real-Time Video Convolutional Face Finder on Embedded Platforms

Directory of Open Access Journals (Sweden)

Mamalet Franck

2007-01-01

Full Text Available A high-level optimization methodology is applied for implementing the well-known convolutional face finder (CFF algorithm for real-time applications on mobile phones, such as teleconferencing, advanced user interfaces, image indexing, and security access control. CFF is based on a feature extraction and classification technique which consists of a pipeline of convolutions and subsampling operations. The design of embedded systems requires a good trade-off between performance and code size due to the limited amount of available resources. The followed methodology copes with the main drawbacks of the original implementation of CFF such as floating-point computation and memory allocation, in order to allow parallelism exploitation and perform algorithm optimizations. Experimental results show that our embedded face detection system can accurately locate faces with less computational load and memory cost. It runs on a 275 MHz Starcore DSP at 35 QCIF images/s with state-of-the-art detection rates and very low false alarm rates.

Real-Time Video Convolutional Face Finder on Embedded Platforms

Directory of Open Access Journals (Sweden)

Franck Mamalet

2007-03-01

Full Text Available A high-level optimization methodology is applied for implementing the well-known convolutional face finder (CFF algorithm for real-time applications on mobile phones, such as teleconferencing, advanced user interfaces, image indexing, and security access control. CFF is based on a feature extraction and classification technique which consists of a pipeline of convolutions and subsampling operations. The design of embedded systems requires a good trade-off between performance and code size due to the limited amount of available resources. The followed methodology copes with the main drawbacks of the original implementation of CFF such as floating-point computation and memory allocation, in order to allow parallelism exploitation and perform algorithm optimizations. Experimental results show that our embedded face detection system can accurately locate faces with less computational load and memory cost. It runs on a 275 MHz Starcore DSP at 35 QCIF images/s with state-of-the-art detection rates and very low false alarm rates.

sEMG-Based Gesture Recognition with Convolution Neural Networks

Directory of Open Access Journals (Sweden)

Zhen Ding

2018-06-01

Full Text Available The traditional classification methods for limb motion recognition based on sEMG have been deeply researched and shown promising results. However, information loss during feature extraction reduces the recognition accuracy. To obtain higher accuracy, the deep learning method was introduced. In this paper, we propose a parallel multiple-scale convolution architecture. Compared with the state-of-art methods, the proposed architecture fully considers the characteristics of the sEMG signal. Larger sizes of kernel filter than commonly used in other CNN-based hand recognition methods are adopted. Meanwhile, the characteristics of the sEMG signal, that is, muscle independence, is considered when designing the architecture. All the classification methods were evaluated on the NinaPro database. The results show that the proposed architecture has the highest recognition accuracy. Furthermore, the results indicate that parallel multiple-scale convolution architecture with larger size of kernel filter and considering muscle independence can significantly increase the classification accuracy.

Modified superstring in light cone gauge

International Nuclear Information System (INIS)

Kamimura, Kiyoshi; Tatewaki, Machiko.

1988-01-01

We analyze the covariant superstring theory proposed by Siegel in light cone gauge. The physical states are the direct product of those of Green-Schwarz Superstring and the additional internal space spanned by light cone spinors. At clasical level, there is no difference among observables in Siegel's modified Superstring theory (SMST) and Green-Schwarz's one (GSST). However SMST can not be quantized with additional constraints as the physical state conditions. (author)

Comparison of the WSA-ENLIL model with three CME cone types

Science.gov (United States)

Jang, Soojeong; Moon, Y.; Na, H.

2013-07-01

We have made a comparison of the CME-associated shock propagation based on the WSA-ENLIL model with three cone types using 29 halo CMEs from 2001 to 2002. These halo CMEs have cone model parameters as well as their associated interplanetary (IP) shocks. For this study we consider three different cone types (an asymmetric cone model, an ice-cream cone model and an elliptical cone model) to determine 3-D CME parameters (radial velocity, angular width and source location), which are the input values of the WSA-ENLIL model. The mean absolute error (MAE) of the arrival times for the asymmetric cone model is 10.6 hours, which is about 1 hour smaller than those of the other models. Their ensemble average of MAE is 9.5 hours. However, this value is still larger than that (8.7 hours) of the empirical model of Kim et al. (2007). We will compare their IP shock velocities and densities with those from ACE in-situ measurements and discuss them in terms of the prediction of geomagnetic storms.Abstract (2,250 Maximum Characters): We have made a comparison of the CME-associated shock propagation based on the WSA-ENLIL model with three cone types using 29 halo CMEs from 2001 to 2002. These halo CMEs have cone model parameters as well as their associated interplanetary (IP) shocks. For this study we consider three different cone types (an asymmetric cone model, an ice-cream cone model and an elliptical cone model) to determine 3-D CME parameters (radial velocity, angular width and source location), which are the input values of the WSA-ENLIL model. The mean absolute error (MAE) of the arrival times for the asymmetric cone model is 10.6 hours, which is about 1 hour smaller than those of the other models. Their ensemble average of MAE is 9.5 hours. However, this value is still larger than that (8.7 hours) of the empirical model of Kim et al. (2007). We will compare their IP shock velocities and densities with those from ACE in-situ measurements and discuss them in terms of the

The light-cone Fock state expansion and hadron physics phenomenology

International Nuclear Information System (INIS)

Brodsky, S.J.

1997-06-01

The light-cone Fock expansion is defined in the following way: one first constructs the light-cone time evolution operator and the invariant mass operator in light-cone gauge from the QCD Lagrangian. The total longitudinal momentum and transverse momenta are conserved, i.e. are independent of the interactions. The matrix elements of the invariant mass operator on the complete orthonormal basis of the free theory can then be constructed. The matrix elements connect Fock states differing by 0, 1, or 2 quark or gluon quanta, and they include the instantaneous quark and gluon contributions imposed by eliminating dependent degrees of freedom in light-cone gauge. Applications of light-cone methods to QCD phenomenology are briefly described

Rapid Recovery of Visual Function Associated with Blue Cone Ablation in Zebrafish

Science.gov (United States)

Hagerman, Gordon F.; Noel, Nicole C. L.; Cao, Sylvia Y.; DuVal, Michèle G.; Oel, A. Phillip; Allison, W. Ted

2016-01-01

Hurdles in the treatment of retinal degeneration include managing the functional rewiring of surviving photoreceptors and integration of any newly added cells into the remaining second-order retinal neurons. Zebrafish are the premier genetic model for such questions, and we present two new transgenic lines allowing us to contrast vision loss and recovery following conditional ablation of specific cone types: UV or blue cones. The ablation of each cone type proved to be thorough (killing 80% of cells in each intended cone class), specific, and cell-autonomous. We assessed the loss and recovery of vision in larvae via the optomotor behavioural response (OMR). This visually mediated behaviour decreased to about 5% or 20% of control levels following ablation of UV or blue cones, respectively (Pvision recovery following UV cone ablation was robust, as measured by both assays, returning to control levels within four days. In contrast, robust functional recovery following blue cone ablation was unexpectedly rapid, returning to normal levels within 24 hours after ablation. Ablation of cones led to increased proliferation in the retina, though the rapid recovery of vision following blue cone ablation was demonstrated to not be mediated by blue cone regeneration. Thus rapid visual recovery occurs following ablation of some, but not all, cone subtypes, suggesting an opportunity to contrast and dissect the sources and mechanisms of outer retinal recovery during cone photoreceptor death and regeneration. PMID:27893779

Collapse of the wave function models, ontology, origin, and implications

CERN Document Server

2018-01-01

This is the first single volume about the collapse theories of quantum mechanics, which is becoming a very active field of research in both physics and philosophy. In standard quantum mechanics, it is postulated that when the wave function of a quantum system is measured, it no longer follows the Schrödinger equation, but instantaneously and randomly collapses to one of the wave functions that correspond to definite measurement results. However, why and how a definite measurement result appears is unknown. A promising solution to this problem are collapse theories in which the collapse of the wave function is spontaneous and dynamical. Chapters written by distinguished physicists and philosophers of physics discuss the origin and implications of wave-function collapse, the controversies around collapse models and their ontologies, and new arguments for the reality of wave function collapse. This is an invaluable resource for students and researchers interested in the philosophy of physics and foundations of ...

A remote control neutron cone scanner and measurement of the d(T,n) α neutron cone

International Nuclear Information System (INIS)

Suwanakachorn, D.; Vilaithong, T.; Vilaithong, C.; Boonyawan, D.; Chimooy, T.; Sornphorm, P.; Hoyce, G.; Pairsuwan, W.; Singkarat, S.

1988-01-01

We have measured the neutron cone associated with alpha particles from the d(T,n)α reaction by using a remote-control cone scanner. This scanner has two principal parts. The first part is the neutron detector scanner which can move the detector in the horizontal and vertical axis using to stepping-motors. The neutron detector can be moved in 0.5 cm increments over the whole rage of 30 cm. The second part is the remote-control electronic circuit using digital ICs. The rotation of stepping-motors is controlled by pulse signals from this circuit and the position of the detector is known by counting the number of pulses. The position of the neutron detector is indicated directly on a 3 digit display at the control panel. The method of measuring the neutron cone by the Time-of-Flight technique is also described

Moduli destabilization via gravitational collapse

Energy Technology Data Exchange (ETDEWEB)

Hwang, Dong-il [Sogang Univ., Seoul (Korea, Republic of). Center for Quantum Spacetime; Pedro, Francisco G. [Deutsches Elektronen-Synchrotron DESY, Hamburg (Germany). Theory Group; Yeom, Dong-han [Sogang Univ., Seoul (Korea, Republic of). Center for Quantum Spacetime; Kyoto Univ. (Japan). Yukawa Inst. for Theoretical Physics

2013-06-15

We examine the interplay between gravitational collapse and moduli stability in the context of black hole formation. We perform numerical simulations of the collapse using the double null formalism and show that the very dense regions one expects to find in the process of black hole formation are able to destabilize the volume modulus. We establish that the effects of the destabilization will be visible to an observer at infinity, opening up a window to a region in spacetime where standard model's couplings and masses can differ significantly from their background values.

Did mud contribute to freeway collapse?

Science.gov (United States)

Hough, Susan E.; Friberg, Paul A.; Busby, Robert; Field, Edward F.; Jacob, Klaus H.; Borcherdt, Roger D.

At least 41 people were killed October 17 when the upper tier of the Nimitz Freeway in Oakland, Calif., collapsed during the Ms = 7.1 Loma Prieta earthquake. Seismologists studying aftershocks concluded that soil conditions and resulting ground motion amplification were important in the failure of the structure and should be considered in the reconstruction of the highway.Structural design weaknesses in the two-tiered freeway, known as the Cypress structure, had been identified before the tragedy. The seismologists, from Lamont Doherty Geological Observatory in Palisades, N.Y., and the U.S. Geological Survey in Menlo Park, Calif., found that the collapsed section was built on fill over Bay mud. A southern section of the Cypress structure built on alluvium of Quaternary age did not collapse (see Figure 1).

Bidirectional-Convolutional LSTM Based Spectral-Spatial Feature Learning for Hyperspectral Image Classification

Directory of Open Access Journals (Sweden)

Qingshan Liu

2017-12-01

Full Text Available This paper proposes a novel deep learning framework named bidirectional-convolutional long short term memory (Bi-CLSTM network to automatically learn the spectral-spatial features from hyperspectral images (HSIs. In the network, the issue of spectral feature extraction is considered as a sequence learning problem, and a recurrent connection operator across the spectral domain is used to address it. Meanwhile, inspired from the widely used convolutional neural network (CNN, a convolution operator across the spatial domain is incorporated into the network to extract the spatial feature. In addition, to sufficiently capture the spectral information, a bidirectional recurrent connection is proposed. In the classification phase, the learned features are concatenated into a vector and fed to a Softmax classifier via a fully-connected operator. To validate the effectiveness of the proposed Bi-CLSTM framework, we compare it with six state-of-the-art methods, including the popular 3D-CNN model, on three widely used HSIs (i.e., Indian Pines, Pavia University, and Kennedy Space Center. The obtained results show that Bi-CLSTM can improve the classification performance by almost 1.5 % as compared to 3D-CNN.

A pre-trained convolutional neural network based method for thyroid nodule diagnosis.

Science.gov (United States)

Ma, Jinlian; Wu, Fa; Zhu, Jiang; Xu, Dong; Kong, Dexing

2017-01-01

In ultrasound images, most thyroid nodules are in heterogeneous appearances with various internal components and also have vague boundaries, so it is difficult for physicians to discriminate malignant thyroid nodules from benign ones. In this study, we propose a hybrid method for thyroid nodule diagnosis, which is a fusion of two pre-trained convolutional neural networks (CNNs) with different convolutional layers and fully-connected layers. Firstly, the two networks pre-trained with ImageNet database are separately trained. Secondly, we fuse feature maps learned by trained convolutional filters, pooling and normalization operations of the two CNNs. Finally, with the fused feature maps, a softmax classifier is used to diagnose thyroid nodules. The proposed method is validated on 15,000 ultrasound images collected from two local hospitals. Experiment results show that the proposed CNN based methods can accurately and effectively diagnose thyroid nodules. In addition, the fusion of the two CNN based models lead to significant performance improvement, with an accuracy of 83.02%±0.72%. These demonstrate the potential clinical applications of this method. Copyright © 2016 Elsevier B.V. All rights reserved.

mode of collapse of square single panel reinforced concrete space

African Journals Online (AJOL)

The models were loaded directly till collapse. The estimated and actual collapse loads of the five models were compared. The estimated collapse load for the slab was 35 kN/m2. Also, the numerical estimate of the collapse load for the beam was 10.2kN/m (with an equivalent slab load of 40.8kN/m2), while the shear capacity ...

An Interactive Graphics Program for Assistance in Learning Convolution.

Science.gov (United States)

Frederick, Dean K.; Waag, Gary L.

1980-01-01

A program has been written for the interactive computer graphics facility at Rensselaer Polytechnic Institute that is designed to assist the user in learning the mathematical technique of convolving two functions. Because convolution can be represented graphically by a sequence of steps involving folding, shifting, multiplying, and integration, it…

Development of a full ice-cream cone model for halo CME structures

Science.gov (United States)

Na, Hyeonock; Moon, Yong-Jae

2015-04-01

The determination of three dimensional parameters (e.g., radial speed, angular width, source location) of Coronal Mass Ejections (CMEs) is very important for space weather forecast. To estimate these parameters, several cone models based on a flat cone or a shallow ice-cream cone with spherical front have been suggested. In this study, we investigate which cone model is proper for halo CME morphology using 33 CMEs which are identified as halo CMEs by one spacecraft (SOHO or STEREO-A or B) and as limb CMEs by the other ones. From geometrical parameters of these CMEs such as their front curvature, we find that near full ice-cream cone CMEs (28 events) are dominant over shallow ice-cream cone CMEs (5 events). So we develop a new full ice-cream cone model by assuming that a full ice-cream cone consists of many flat cones with different heights and angular widths. This model is carried out by the following steps: (1) construct a cone for given height and angular width, (2) project the cone onto the sky plane, (3) select points comprising the outer boundary, (4) minimize the difference between the estimated projection points with the observed ones. We apply this model to several halo CMEs and compare the results with those from other methods such as a Graduated Cylindrical Shell model and a geometrical triangulation method.

Quantifying Translation-Invariance in Convolutional Neural Networks

OpenAIRE

Kauderer-Abrams, Eric

2017-01-01

A fundamental problem in object recognition is the development of image representations that are invariant to common transformations such as translation, rotation, and small deformations. There are multiple hypotheses regarding the source of translation invariance in CNNs. One idea is that translation invariance is due to the increasing receptive field size of neurons in successive convolution layers. Another possibility is that invariance is due to the pooling operation. We develop a simple ...

Study of film boiling collapse behavior during vapor explosion

International Nuclear Information System (INIS)

Yagi, Masahiro; Yamano, Norihiro; Sugimoto, Jun; Abe, Yutaka; Adachi, Hiromichi; Kobayashi, Tomoyoshi.

1996-06-01

Possible large scale vapor explosions are safety concern in nuclear power plants during severe accident. In order to identify the occurrence of the vapor explosion and to estimate the magnitude of the induced pressure pulse, it is necessary to investigate the triggering condition for the vapor explosion. As a first step of this study, scooping analysis was conducted with a simulation code based on thermal detonation model. It was found that the pressure at the collapse of film boiling much affects the trigger condition of vapor explosion. Based on this analytical results, basic experiments were conducted to clarify the collapse conditions of film boiling on a high temperature solid ball surface. Film boiling condition was established by flooding water onto a high temperature stainless steel ball heated by a high frequency induction heater. After the film boiling was established, the pressure pulse generated by a shock tube was applied to collapse the steam film on the ball surface. As the experimental boundary conditions, materials and size of the balls, magnitude of pressure pulse and initial temperature of the carbon and stainless steel balls were varied. The transients of pressure and surface temperature were measured. It was found that the surface temperature on the balls sharply decreased when the pressure wave passed through the film on balls. Based on the surface temperature behavior, the film boiling collapse pattern was found to be categorized into several types. Especially, the pattern for stainless steel ball was categorized into three types; no collapse, collapse and reestablishment after collapse. It was thus clarified that the film boiling collapse behavior was identified by initial conditions and that the pressure required to collapse film boiling strongly depended on the initial surface temperature. The present results will provide a useful information for the analysis of vapor explosions based on the thermal detonation model. (J.P.N.)

Plastic collapse load of corroded steel plates

Indian Academy of Sciences (India)

Keywords. Corroded steel plate; plastic collapse; FEM; rough surface. ... The main aim of present work is to study plastic collapse load of corroded steel plates with irregular surfaces under tension. Non-linear finite element method ... Department of Ocean Engineering, AmirKabir University of Technology, 15914 Tehran, Iran ...

Applications of deep convolutional neural networks to digitized natural history collections

Directory of Open Access Journals (Sweden)

Eric Schuettpelz

2017-11-01

Full Text Available Natural history collections contain data that are critical for many scientific endeavors. Recent efforts in mass digitization are generating large datasets from these collections that can provide unprecedented insight. Here, we present examples of how deep convolutional neural networks can be applied in analyses of imaged herbarium specimens. We first demonstrate that a convolutional neural network can detect mercury-stained specimens across a collection with 90% accuracy. We then show that such a network can correctly distinguish two morphologically similar plant families 96% of the time. Discarding the most challenging specimen images increases accuracy to 94% and 99%, respectively. These results highlight the importance of mass digitization and deep learning approaches and reveal how they can together deliver powerful new investigative tools.

Applications of deep convolutional neural networks to digitized natural history collections.

Science.gov (United States)

Schuettpelz, Eric; Frandsen, Paul B; Dikow, Rebecca B; Brown, Abel; Orli, Sylvia; Peters, Melinda; Metallo, Adam; Funk, Vicki A; Dorr, Laurence J

2017-01-01

Natural history collections contain data that are critical for many scientific endeavors. Recent efforts in mass digitization are generating large datasets from these collections that can provide unprecedented insight. Here, we present examples of how deep convolutional neural networks can be applied in analyses of imaged herbarium specimens. We first demonstrate that a convolutional neural network can detect mercury-stained specimens across a collection with 90% accuracy. We then show that such a network can correctly distinguish two morphologically similar plant families 96% of the time. Discarding the most challenging specimen images increases accuracy to 94% and 99%, respectively. These results highlight the importance of mass digitization and deep learning approaches and reveal how they can together deliver powerful new investigative tools.

A mixed-scale dense convolutional neural network for image analysis

NARCIS (Netherlands)

D.M. Pelt (Daniël); J.A. Sethian (James)

2016-01-01

textabstractDeep convolutional neural networks have been successfully applied to many image-processing problems in recent works. Popular network architectures often add additional operations and connections to the standard architecture to enable training deeper networks. To achieve accurate results

Exact cone beam CT with a spiral scan

International Nuclear Information System (INIS)

Tam, K.C.; Samarasekera, S.; Sauer, F.

1998-01-01

A method is developed which makes it possible to scan and reconstruct an object with cone beam x-rays in a spiral scan path with area detectors much shorter than the length of the object. The method is mathematically exact. If only a region of interest of the object is to be imaged, a top circle scan at the top level of the region of interest and a bottom circle scan at the bottom level of the region of interest are added. The height of the detector is required to cover only the distance between adjacent turns in the spiral projected at the detector. To reconstruct the object, the Radon transform for each plane intersecting the object is computed from the totality of the cone beam data. This is achieved by suitably combining the cone beam data taken at different source positions on the scan path; the angular range of the cone beam data required at each source position can be determined easily with a mask which is the spiral scan path projected on the detector from the current source position. The spiral scan algorithm has been successfully validated with simulated cone beam data. (author)

Constraining quantum collapse inflationary models with CMB data

Energy Technology Data Exchange (ETDEWEB)

Benetti, Micol; Alcaniz, Jailson S. [Departamento de Astronomia, Observatório Nacional, 20921-400, Rio de Janeiro, RJ (Brazil); Landau, Susana J., E-mail: micolbenetti@on.br, E-mail: slandau@df.uba.ar, E-mail: alcaniz@on.br [Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires and IFIBA, CONICET, Ciudad Universitaria, PabI, Buenos Aires 1428 (Argentina)

2016-12-01

The hypothesis of the self-induced collapse of the inflaton wave function was proposed as responsible for the emergence of inhomogeneity and anisotropy at all scales. This proposal was studied within an almost de Sitter space-time approximation for the background, which led to a perfect scale-invariant power spectrum, and also for a quasi-de Sitter background, which allows to distinguish departures from the standard approach due to the inclusion of the collapse hypothesis. In this work we perform a Bayesian model comparison for two different choices of the self-induced collapse in a full quasi-de Sitter expansion scenario. In particular, we analyze the possibility of detecting the imprint of these collapse schemes at low multipoles of the anisotropy temperature power spectrum of the Cosmic Microwave Background (CMB) using the most recent data provided by the Planck Collaboration. Our results show that one of the two collapse schemes analyzed provides the same Bayesian evidence of the minimal standard cosmological model ΛCDM, while the other scenario is weakly disfavoured with respect to the standard cosmology.

Fast convolutional sparse coding using matrix inversion lemma

Czech Academy of Sciences Publication Activity Database

Šorel, Michal; Šroubek, Filip

2016-01-01

Roč. 55, č. 1 (2016), s. 44-51 ISSN 1051-2004 R&D Projects: GA ČR GA13-29225S Institutional support: RVO:67985556 Keywords : Convolutional sparse coding * Feature learning * Deconvolution networks * Shift-invariant sparse coding Subject RIV: JD - Computer Applications, Robotics Impact factor: 2.337, year: 2016 http://library.utia.cas.cz/separaty/2016/ZOI/sorel-0459332.pdf

Light-cone averaging in cosmology: formalism and applications

International Nuclear Information System (INIS)

Gasperini, M.; Marozzi, G.; Veneziano, G.; Nugier, F.

2011-01-01

We present a general gauge invariant formalism for defining cosmological averages that are relevant for observations based on light-like signals. Such averages involve either null hypersurfaces corresponding to a family of past light-cones or compact surfaces given by their intersection with timelike hypersurfaces. Generalized Buchert-Ehlers commutation rules for derivatives of these light-cone averages are given. After introducing some adapted ''geodesic light-cone'' coordinates, we give explicit expressions for averaging the redshift to luminosity-distance relation and the so-called ''redshift drift'' in a generic inhomogeneous Universe

Scalar field collapse in Gauss-Bonnet gravity

Energy Technology Data Exchange (ETDEWEB)

Banerjee, Narayan [Indian Institute of Science Education and Research Kolkata, Department of Physical Sciences, Nadia, West Bengal (India); Paul, Tanmoy [Indian Association for the Cultivation of Science, Department of Theoretical Physics, Kolkata (India)

2018-02-15

We consider a ''scalar-Einstein-Gauss-Bonnet'' theory in four dimension, where the scalar field couples non-minimally with the Gauss-Bonnet (GB) term. This coupling with the scalar field ensures the non-topological character of the GB term. In this scenario, we examine the possibility for collapsing of the scalar field. Our result reveals that such a collapse is possible in the presence of Gauss-Bonnet gravity for suitable choices of parametric regions. The singularity formed as a result of the collapse is found to be a curvature singularity which is hidden from the exterior by an apparent horizon. (orig.)

Tokay gecko photoreceptors achieve rod-like physiology with cone-like proteins.

Science.gov (United States)

Zhang, Xue; Wensel, Theodore G; Yuan, Ching

2006-01-01

The retinal photoreceptors of the nocturnal Tokay gecko (Gekko gekko) consist exclusively of rods by the criteria of morphology and key features of their light responses. Unlike cones, they display robust photoresponses and have relatively slow recovery times. Nonetheless, the major and minor visual pigments identified in gecko rods are of the cone type by sequence and spectroscopic behavior. In the ongoing search for the molecular bases for the physiological differences between cones and rods, we have characterized the molecular biology and biochemistry of the gecko rod phototransduction cascade. We have cloned cDNAs encoding all or part of major protein components of the phototransduction cascade by RT-PCR with degenerate oligonucleotides designed to amplify cone- or rod-like sequences. For all proteins examined we obtained only cone-like and never rod-like sequences. The proteins identified include transducin alpha (Galphat), phosphodiesterase (PDE6) catalytic and inhibitory subunits, cyclic nucleotide-gated channel (CNGalpha) and arrestin. We also cloned cDNA encoding gecko RGS9-1 (Regulator of G Protein Signaling 9, splice variant 1), which is expressed in both rods and cones of all species studied but is typically found at 10-fold higher concentrations in cones, and found that gecko rods contain slightly lower RGS9-1 levels than mammalian rods. Furthermore, we found that the levels of GTPase accelerating protein (GAP) activity and cyclic GMP (cGMP) phosphodiesterase activity were similar in gecko and mammalian rods. These results place substantial constraints on the critical changes needed to convert a cone into a rod in the course of evolution: The many features of phototransduction molecules conserved between those expressed in gecko rods and those expressed in cones cannot explain the physiological differences, whereas the higher levels of RGS9-1 and GAP activity in cones are likely among the essential requirements for the rapid photoresponses of cones.

Analysis of macular cone photoreceptors in a case of occult macular dystrophy

Directory of Open Access Journals (Sweden)

Tojo N

2013-05-01

Full Text Available Naoki Tojo Tomoko Nakamura Hironori Ozaki Miyako Oka Toshihiko Oiwake Atsushi HayashiDepartment of Ophthalmology, University of Toyama, Toyama, JapanPurpose: To investigate changes in cone photoreceptors with adaptive optics (AO fundus imaging and spectral domain optical coherence tomography (SD-OCT in a case of occult macular dystrophy (OMD.Patient and methods: Both eyes of a 42-year-old woman diagnosed with OMD were examined. We used an AO fundus camera to obtain images of cone photoreceptors in the macula of the OMD subject and five healthy control subjects. Correlations between the AO images and the SD-OCT images were examined. Cone photoreceptors in eight areas in the macula of OMD and healthy control subjects were analyzed and compared.Results: SD-OCT showed a loss of the cone outer-segment tips line outside of the fovea in both eyes of the subject with OMD. The left eye with decreased visual acuity showed a discontinuous photoreceptor inner-segment and outer-segment line and cone outer-segment tips line at the fovea in SD-OCT and loss of cone mosaics as a dark spot in the AO image. In panoramic AO images and cone-density maps, less cone density was observed in a ring-like region outside the fovea than in the peripheral retina. In most of the areas examined, the cone densities were lower in the OMD eyes than in the healthy control eyes.Conclusions: Cone densities in the macula of the OMD patient were greatly decreased. AO images were found to be useful to evaluate morphologic changes in cone photoreceptors in patients with OMD.Keywords: occult macular dystrophy, adaptive optics, cone photoreceptor, cone analysis, optical coherence tomography

Spatial and Time Domain Feature of ERP Speller System Extracted via Convolutional Neural Network.

Science.gov (United States)

Yoon, Jaehong; Lee, Jungnyun; Whang, Mincheol

2018-01-01

Feature of event-related potential (ERP) has not been completely understood and illiteracy problem remains unsolved. To this end, P300 peak has been used as the feature of ERP in most brain-computer interface applications, but subjects who do not show such peak are common. Recent development of convolutional neural network provides a way to analyze spatial and temporal features of ERP. Here, we train the convolutional neural network with 2 convolutional layers whose feature maps represented spatial and temporal features of event-related potential. We have found that nonilliterate subjects' ERP show high correlation between occipital lobe and parietal lobe, whereas illiterate subjects only show correlation between neural activities from frontal lobe and central lobe. The nonilliterates showed peaks in P300, P500, and P700, whereas illiterates mostly showed peaks in around P700. P700 was strong in both subjects. We found that P700 peak may be the key feature of ERP as it appears in both illiterate and nonilliterate subjects.

A unified analysis of FBP-based algorithms in helical cone-beam and circular cone- and fan-beam scans

International Nuclear Information System (INIS)

Pan Xiaochuan; Xia Dan; Zou Yu; Yu Lifeng

2004-01-01

A circular scanning trajectory is and will likely remain a popular choice of trajectory in computed tomography (CT) imaging because it is easy to implement and control. Filtered-backprojection (FBP)-based algorithms have been developed previously for approximate and exact reconstruction of the entire image or a region of interest within the image in circular cone-beam and fan-beam cases. Recently, we have developed a 3D FBP-based algorithm for image reconstruction on PI-line segments in a helical cone-beam scan. In this work, we demonstrated that the 3D FBP-based algorithm indeed provided a rather general formulation for image reconstruction from divergent projections (such as cone-beam and fan-beam projections). On the basis of this formulation we derived new approximate or exact algorithms for image reconstruction in circular cone-beam or fan-beam scans, which can be interpreted as special cases of the helical scan. Existing algorithms corresponding to the derived algorithms were identified. We also performed a preliminary numerical study to verify our theoretical results in each of the cases. The results in the work can readily be generalized to other non-circular trajectories

Static end-expiratory and dynamic forced expiratory tracheal collapse in COPD

International Nuclear Information System (INIS)

O'Donnell, C.R.; Bankier, A.A.; O'Donnell, D.H.; Loring, S.H.; Boiselle, P.M.

2014-01-01

Aim: To determine the range of tracheal collapse at end-expiration among chronic obstructive pulmonary disease (COPD) patients and to compare the extent of tracheal collapse between static end-expiratory and dynamic forced-expiratory multidetector-row computed tomography (MDCT). Materials and methods: After institutional review board approval and obtaining informed consent, 67 patients meeting the National Heart, Lung, and Blood Institute (NHLBI)/World Health Organization (WHO) Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria for COPD were sequentially imaged using a 64-detector-row CT machine at end-inspiration, during forced expiration, and at end-expiration. Standardized respiratory coaching and spirometric monitoring were employed. Mean percentage tracheal collapse at end-expiration and forced expiration were compared using correlation analysis, and the power of end-expiratory cross-sectional area to predict excessive forced-expiratory tracheal collapse was computed following construction of receiver operating characteristic (ROC) curves. Results: Mean percentage expiratory collapse among COPD patients was 17 ± 18% at end-expiration compared to 62 ± 16% during forced expiration. Over the observed range of end-expiratory tracheal collapse (approximately 10–50%), the positive predictive value of end-expiratory collapse to predict excessive (≥80%) forced expiratory tracheal collapse was <0.3. Conclusion: COPD patients demonstrate a wide range of end-expiratory tracheal collapse. The magnitude of static end-expiratory tracheal collapse does not predict excessive dynamic expiratory tracheal collapse

Simulation of weak and strong Langmuir collapse regimes

International Nuclear Information System (INIS)

Hadzievski, L.R.; Skoric, M.M.; Kono, M.; Sato, T.

1998-01-01

In order to check the validity of the self-similar solutions and the existence of weak and strong collapse regimes, direct two dimensional simulation of the time evolution of a Langmuir soliton instability is performed. Simulation is based on the Zakharov model of strong Langmuir turbulence in a weakly magnetized plasma accounting for the full ion dynamics. For parameters considered, agreement with self-similar dynamics of the weak collapse type is found with no evidence of the strong Langmuir collapse. (author)

Renormalized G-convolution of n-point functions in quantum field theory. I. The Euclidean case

International Nuclear Information System (INIS)

Bros, Jacques; Manolessou-Grammaticou, Marietta.

1977-01-01

The notion of Feynman amplitude associated with a graph G in perturbative quantum field theory admits a generalized version in which each vertex v of G is associated with a general (non-perturbative) nsub(v)-point function Hsup(nsub(v)), nsub(v) denoting the number of lines which are incident to v in G. In the case where no ultraviolet divergence occurs, this has been performed directly in complex momentum space through Bros-Lassalle's G-convolution procedure. The authors propose a generalization of G-convolution which includes the case when the functions Hsup(nsub(v)) are not integrable at infinity but belong to a suitable class of slowly increasing functions. A finite part of the G-convolution integral is then defined through an algorithm which closely follows Zimmermann's renormalization scheme. The case of Euclidean four-momentum configurations is only treated

Determination of HCME 3-D parameters using a full ice-cream cone model

Science.gov (United States)

Na, Hyeonock; Moon, Yong-Jae; Lee, Harim

2016-05-01

It is very essential to determine three dimensional parameters (e.g., radial speed, angular width, source location) of Coronal Mass Ejections (CMEs) for space weather forecast. Several cone models (e.g., an elliptical cone model, an ice-cream cone model, an asymmetric cone model) have been examined to estimate these parameters. In this study, we investigate which cone type is close to a halo CME morphology using 26 CMEs: halo CMEs by one spacecraft (SOHO or STEREO-A or B) and as limb CMEs by the other ones. From cone shape parameters of these CMEs such as their front curvature, we find that near full ice-cream cone type CMEs are much closer to observations than shallow ice-cream cone type CMEs. Thus we develop a new cone model in which a full ice-cream cone consists of many flat cones with different heights and angular widths. This model is carried out by the following steps: (1) construct a cone for given height and angular width, (2) project the cone onto the sky plane, (3) select points comprising the outer boundary, and (4) minimize the difference between the estimated projection speeds with the observed ones. By applying this model to 12 SOHO/LASCO halo CMEs, we find that 3-D parameters from our method are similar to those from other stereoscopic methods (a geometrical triangulation method and a Graduated Cylindrical Shell model) based on multi-spacecraft data. We are developing a general ice-cream cone model whose front shape is a free parameter determined by observations.

Collapse of Incoherent Light Beams in Inertial Bulk Kerr Media

DEFF Research Database (Denmark)

Bang, Ole; Edmundson, Darran; Królikowski, Wieslaw

1999-01-01

We use the coherent density function theory to show that partially coherent beams are unstable and may collapse in inertial bulk Kerr media. The threshold power for collapse, and its dependence on the degree of coherence, is found analytically and checked-numerically. The internal dynamics of the...... of the walk-off modes is illustrated for collapsing and diffracting partially coherent beams.......We use the coherent density function theory to show that partially coherent beams are unstable and may collapse in inertial bulk Kerr media. The threshold power for collapse, and its dependence on the degree of coherence, is found analytically and checked-numerically. The internal dynamics...

Gravitational collapse from smooth initial data with vanishing radial pressure

International Nuclear Information System (INIS)

Mahajan, Ashutosh; Goswami, Rituparno; Joshi, Pankaj S

2005-01-01

We study here the spherical gravitational collapse assuming initial data to be necessarily smooth, as motivated by requirements based on physical reasonableness. A tangential pressure model is constructed and analysed in order to understand the final fate of collapse explicitly in terms of the density and pressure parameters at the initial epoch from which the collapse develops. It is seen that both black holes and naked singularities are produced as collapse end states even when the initial data are smooth. We show that the outcome is decided entirely in terms of the initial data, as given by density, pressure and velocity profiles at the initial epoch, from which the collapse evolves

The uniqueness of the solution of cone-like inversion models for halo CMEs

Science.gov (United States)

Zhao, X. P.

2006-12-01

Most of elliptic halo CMEs are believed to be formed by the Thompson scattering of the photospheric light by the 3-D cone-like shell of the CME plasma. To obtain the real propagation direction and angular width of the halo CMEs, such cone-like inversion models as the circular cone, the elliptic cone and the ice-cream cone models have been suggested recently. Because the number of given parameters that are used to characterize 2-D elliptic halo CMEs observed by one spacecraft are less than the number of unknown parameters that are used to characterize the 3-D elliptic cone model, the solution of the elliptic cone model is not unique. Since it is difficult to determine whether or not an observed halo CME is formed by an circular cone or elliptic cone shell, the solution of circular cone model may often be not unique too. To fix the problem of the uniqueness of the solution of various 3-D cone-like inversion models, this work tries to develop the algorithm for using the data from multi-spacecraft, such as the STEREO A and B, and the Solar Sentinels.

Identification and behavior of collapsible soils : [technical summary].

Science.gov (United States)

2011-01-01

Collapsible soils are susceptible to large volumetric strains when they become saturated. Numerous soil types : fall in the general category of collapsible soils, including : loess, a well-known aeolian deposit, present throughout : most of Indiana. ...

Electron capture and stellar collapse

International Nuclear Information System (INIS)

Chung, K.C.

1979-01-01

In order, to investigate the function of electron capture in the phenomenon of pre-supernovae gravitacional collapse, an hydrodynamic caculation was carried out, coupling capture, decay and nuclear reaction equation system. A star simplified model (homogeneous model) was adopted using fermi ideal gas approximation for tthe sea of free electrons and neutrons. The non simplified treatment from quasi-static evolution to collapse is presented. The capture and beta decay rates, as wellas neutron delayed emission, were calculated by beta decay crude theory, while the other reaction rates were determined by usual theories. The preliminary results are presented. (M.C.K.) [pt

Case of Unilateral Peripheral Cone Dysfunction

Directory of Open Access Journals (Sweden)

Yujin Mochizuki

2012-05-01

Full Text Available Purpose: Peripheral cone dystrophy is a subgroup of cone dystrophy, and only 4 cases have been reported. We present a patient with unilateral peripheral cone dysfunction and report the functional changes determined by electrophysiological tests and ultrastructural changes determined by spectral domain optical coherence tomography (SD-OCT. Case: A 34-year-old woman complained of blurred vision in both eyes. Our examination showed that her visual acuity was 0.05 OD and 0.2 OS. A relative afferent pupillary defect was present in her right eye. The results of slit-lamp examination, ophthalmoscopy, and fluorescein angiography were normal except for pallor of the right optic disc. SD-OCT showed a diffuse thinning of the retina in the posterior pole of the right eye. A severe constriction of the visual fields was found in both eyes but more in the right eye. The photopic full-field electroretinograms (ERGs were reduced in the right eye but normal in the left eye. The multifocal ERGs were severely reduced throughout the visual field except in the central area of the right eye. The multifocal ERGs from the left eye were normal. The pattern visual evoked responses were within the normal range in both eyes. She had a 5-year history of sniffing paint thinner. Results: Although the visual dysfunction was initially suspected to be due to psychological problems from the results of subjective tests, objective tests indicated a peripheral cone dysfunction in the right eye. The pathophysiological mechanism and the relationship with thinner sniffing were not determined. Conclusions: Our findings indicate that peripheral cone dysfunction can occur unilaterally. Electrophysiology and SD-OCT are valuable tests to perform to determine the pathogenesis of unusual ocular findings objectively.

Human Blue Cone Opsin Regeneration Involves Secondary Retinal Binding with Analog Specificity.

Science.gov (United States)

Srinivasan, Sundaramoorthy; Fernández-Sampedro, Miguel A; Morillo, Margarita; Ramon, Eva; Jiménez-Rosés, Mireia; Cordomí, Arnau; Garriga, Pere

2018-03-27

Human color vision is mediated by the red, green, and blue cone visual pigments. Cone opsins are G-protein-coupled receptors consisting of an opsin apoprotein covalently linked to the 11-cis-retinal chromophore. All visual pigments share a common evolutionary origin, and red and green cone opsins exhibit a higher homology, whereas blue cone opsin shows more resemblance to the dim light receptor rhodopsin. Here we show that chromophore regeneration in photoactivated blue cone opsin exhibits intermediate transient conformations and a secondary retinoid binding event with slower binding kinetics. We also detected a fine-tuning of the conformational change in the photoactivated blue cone opsin binding site that alters the retinal isomer binding specificity. Furthermore, the molecular models of active and inactive blue cone opsins show specific molecular interactions in the retinal binding site that are not present in other opsins. These findings highlight the differential conformational versatility of human cone opsin pigments in the chromophore regeneration process, particularly compared to rhodopsin, and point to relevant functional, unexpected roles other than spectral tuning for the cone visual pigments. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Collapse, environment, and society

Science.gov (United States)

2012-01-01

Historical collapse of ancient states poses intriguing social-ecological questions, as well as potential applications to global change and contemporary strategies for sustainability. Five Old World case studies are developed to identify interactive inputs, triggers, and feedbacks in devolution. Collapse is multicausal and rarely abrupt. Political simplification undermines traditional structures of authority to favor militarization, whereas disintegration is preconditioned or triggered by acute stress (insecurity, environmental or economic crises, famine), with breakdown accompanied or followed by demographic decline. Undue attention to stressors risks underestimating the intricate interplay of environmental, political, and sociocultural resilience in limiting the damages of collapse or in facilitating reconstruction. The conceptual model emphasizes resilience, as well as the historical roles of leaders, elites, and ideology. However, a historical model cannot simply be applied to contemporary problems of sustainability without adjustment for cumulative information and increasing possibilities for popular participation. Between the 14th and 18th centuries, Western Europe responded to environmental crises by innovation and intensification; such modernization was decentralized, protracted, flexible, and broadly based. Much of the current alarmist literature that claims to draw from historical experience is poorly focused, simplistic, and unhelpful. It fails to appreciate that resilience and readaptation depend on identified options, improved understanding, cultural solidarity, enlightened leadership, and opportunities for participation and fresh ideas. PMID:22371579

Accessibility analysis in manufacturing processes using visibility cones

Institute of Scientific and Technical Information of China (English)

尹周平; 丁汉; 熊有伦

2002-01-01

Accessibility is a kind of important design feature of products,and accessibility analysis has been acknowledged as a powerful tool for solving computational manufacturing problems arising from different manufacturing processes.After exploring the relations among approachability,accessibility and visibility,a general method for accessibility analysis using visibility cones (VC) is proposed.With the definition of VC of a point,three kinds of visibility of a feature,namely complete visibility cone (CVC),partial visibility cone (PVC) and local visibility cone (LVC),are defined.A novel approach to computing VCs is formulated by identifying C-obstacles in the C-space,for which a general and efficient algorithm is proposed and implemented by making use of visibility culling.Lastly,we discuss briefly how to realize accessibility analysis in numerically controlled (NC) machining planning,coordinate measuring machines (CMMs) inspection planning and assembly sequence planning with the proposed methods.

Testing the reliability of ice-cream cone model

Science.gov (United States)

Pan, Zonghao; Shen, Chenglong; Wang, Chuanbing; Liu, Kai; Xue, Xianghui; Wang, Yuming; Wang, Shui

2015-04-01

Coronal Mass Ejections (CME)'s properties are important to not only the physical scene itself but space-weather prediction. Several models (such as cone model, GCS model, and so on) have been raised to get rid of the projection effects within the properties observed by spacecraft. According to SOHO/ LASCO observations, we obtain the 'real' 3D parameters of all the FFHCMEs (front-side full halo Coronal Mass Ejections) within the 24th solar cycle till July 2012, by the ice-cream cone model. Considering that the method to obtain 3D parameters from the CME observations by multi-satellite and multi-angle has higher accuracy, we use the GCS model to obtain the real propagation parameters of these CMEs in 3D space and compare the results with which by ice-cream cone model. Then we could discuss the reliability of the ice-cream cone model.

Prescriptionless light-cone integrals

International Nuclear Information System (INIS)

Suzuki, A.T.; Schmidt, A.G.M.

2000-01-01

Perturbative quantum gauge field theory as seen within the perspective of physical gauge choices such as the light-cone gauge entails the emergence of troublesome poles of the type (k.n) -α in the Feynman integrals. These come from the boson field propagator, where α=1,2,.. and n μ is the external arbitrary four-vector that defines the gauge properly. This becomes an additional hurdle in the computation of Feynman diagrams, since any graph containing internal boson lines will inevitably produce integrands with denominators bearing the characteristic gauge-fixing factor. How one deals with them has been the subject of research over decades, and several prescriptions have been suggested and tried in the course of time, with failures and successes. However, a more recent development at this fronteer which applies the negative dimensional technique to compute light-cone Feynman integrals shows that we can altogether dispense with prescriptions to perform the calculations. An additional bonus comes to us attached to this new technique, in that not only it renders the light-cone prescriptionless but, by the very nature of it, it can also dispense with decomposition formulas or partial fractioning tricks used in the standard approach to separate pole products of the type (k.n) -α [(k-p).n] -β (β=1,2,..). In this work we demonstrate how all this can be done. (orig.)

Deep convolutional neural networks for automatic classification of gastric carcinoma using whole slide images in digital histopathology.

Science.gov (United States)

Sharma, Harshita; Zerbe, Norman; Klempert, Iris; Hellwich, Olaf; Hufnagl, Peter

2017-11-01

Deep learning using convolutional neural networks is an actively emerging field in histological image analysis. This study explores deep learning methods for computer-aided classification in H&E stained histopathological whole slide images of gastric carcinoma. An introductory convolutional neural network architecture is proposed for two computerized applications, namely, cancer classification based on immunohistochemical response and necrosis detection based on the existence of tumor necrosis in the tissue. Classification performance of the developed deep learning approach is quantitatively compared with traditional image analysis methods in digital histopathology requiring prior computation of handcrafted features, such as statistical measures using gray level co-occurrence matrix, Gabor filter-bank responses, LBP histograms, gray histograms, HSV histograms and RGB histograms, followed by random forest machine learning. Additionally, the widely known AlexNet deep convolutional framework is comparatively analyzed for the corresponding classification problems. The proposed convolutional neural network architecture reports favorable results, with an overall classification accuracy of 0.6990 for cancer classification and 0.8144 for necrosis detection. Copyright © 2017 Elsevier Ltd. All rights reserved.

3D Medical Image Interpolation Based on Parametric Cubic Convolution

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

In the process of display, manipulation and analysis of biomedical image data, they usually need to be converted to data of isotropic discretization through the process of interpolation, while the cubic convolution interpolation is widely used due to its good tradeoff between computational cost and accuracy. In this paper, we present a whole concept for the 3D medical image interpolation based on cubic convolution, and the six methods, with the different sharp control parameter, which are formulated in details. Furthermore, we also give an objective comparison for these methods using data sets with the different slice spacing. Each slice in these data sets is estimated by each interpolation method and compared with the original slice using three measures: mean-squared difference, number of sites of disagreement, and largest difference. According to the experimental results, we present a recommendation for 3D medical images under the different situations in the end.

ID card number detection algorithm based on convolutional neural network

Science.gov (United States)

Zhu, Jian; Ma, Hanjie; Feng, Jie; Dai, Leiyan

2018-04-01

In this paper, a new detection algorithm based on Convolutional Neural Network is presented in order to realize the fast and convenient ID information extraction in multiple scenarios. The algorithm uses the mobile device equipped with Android operating system to locate and extract the ID number; Use the special color distribution of the ID card, select the appropriate channel component; Use the image threshold segmentation, noise processing and morphological processing to take the binary processing for image; At the same time, the image rotation and projection method are used for horizontal correction when image was tilting; Finally, the single character is extracted by the projection method, and recognized by using Convolutional Neural Network. Through test shows that, A single ID number image from the extraction to the identification time is about 80ms, the accuracy rate is about 99%, It can be applied to the actual production and living environment.

Gravitational wave generation by stellar core collapse

International Nuclear Information System (INIS)

Moore, T.A.

1981-01-01

Stars which have masses greater than 5 to 8 solar masses are thought to undergo a stage of catastrophic core collapse and subsequent supernova explosion at the end of their lives. If the core is not spherically symmetric, the bounce which halts its collapse at transnuclear densities will generate a pulse of gravitational waves. This thesis presents a fully relativistic model of core collapse which treats deviations from spherical symmetry as small perturbations on a spherical background. This model may be used to predict qualitative and quantitative features of the gravitational radiation emitted by stellar cores with odd-parity, axisymmetric fluid perturbations, and represents a first step in the application of perturbative methods to more general asymmetries. The first chapter reviews the present consensus on the physics of core collapse and outlines the important features, assumptions, and limitations of the model. A series of model runs are presented and discussed. Finally, several proposals for future research are presented. Subsequent chapters explore in detail the mathematical features of the present model and its realization on the computer

Newton force from wave function collapse: speculation and test

International Nuclear Information System (INIS)

Diósi, Lajos

2014-01-01

The Diosi-Penrose model of quantum-classical boundary postulates gravity-related spontaneous wave function collapse of massive degrees of freedom. The decoherence effects of the collapses are in principle detectable if not masked by the overwhelming environmental decoherence. But the DP (or any other, like GRW, CSL) spontaneous collapses are not detectable themselves, they are merely the redundant formalism of spontaneous decoherence. To let DP collapses become testable physics, recently we extended the DP model and proposed that DP collapses are responsible for the emergence of the Newton gravitational force between massive objects. We identified the collapse rate, possibly of the order of 1/ms, with the rate of emergence of the Newton force. A simple heuristic emergence (delay) time was added to the Newton law of gravity. This non-relativistic delay is in peaceful coexistence with Einstein's relativistic theory of gravitation, at least no experimental evidence has so far surfaced against it. We derive new predictions of such a 'lazy' Newton law that will enable decisive laboratory tests with available technologies. The simple equation of 'lazy' Newton law deserves theoretical and experimental studies in itself, independently of the underlying quantum foundational considerations.

Prediction of the wetting-induced collapse behaviour using the soil-water characteristic curve

Science.gov (United States)

Xie, Wan-Li; Li, Ping; Vanapalli, Sai K.; Wang, Jia-Ding

2018-01-01

Collapsible soils go through three distinct phases in response to matric suction decrease during wetting: pre-collapse phase, collapse phase and post-collapse phase. It is reasonable and conservative to consider a strain path that includes a pre-collapse phase in which constant volume is maintained and a collapse phase that extends to the final matric suction to be experienced by collapsible soils during wetting. Upon this assumption, a method is proposed for predicting the collapse behaviour due to wetting. To use the proposed method, two parameters, critical suction and collapse rate, are required. The former is the suction value below which significant collapse deformations take place in response to matric suction decease, and the later is the rate at which void ratio reduces with matric suction in the collapse phase. The value of critical suction can be estimated from the water-entry value taking account of both the microstructure characteristics and collapse mechanism of fine-grained collapsible soils; the wetting soil-water characteristic curve thus can be used as a tool. Five sets of data of wetting tests on both compacted and natural collapsible soils reported in the literature were used to validate the proposed method. The critical suction values were estimated from the water-entry value with parameter a that is suggested to vary between 0.10 and 0.25 for compacted soils and to be lower for natural collapsible soils. The results of a field permeation test in collapsible loess soils were also used to validate the proposed method. The relatively good agreement between the measured and estimated collapse deformations suggests that the proposed method can provide reasonable prediction of the collapse behaviour due to wetting.

Noncrossing timelike singularities of irrotational dust collapse

International Nuclear Information System (INIS)

Liang, E.P.T.

1979-01-01

Known naked singularities in spherical dust collapse are either due to shell-crossing or localized to the central world line. They will probably be destroyed by pressure gradients or blue-shift instabilities. To violate the cosmic censorship hypothesis in a more convincing and general context, collapse solutions with naked singularities that are at least nonshell-crossing and nonlocalized need to be constructed. Some results concerning the probable structure of a class of nonshellcrossing and nonlocalized timelike singularities are reviewed. The cylindrical dust model is considered but this model is not asymptotically flat. To make these noncrossing singularities viable counter examples to the cosmic censorship hypothesis, the occurrence of such singularities in asymptotically flat collapse needs to be demonstrated. (UK)

Steroid-associated hip joint collapse in bipedal emus.

Directory of Open Access Journals (Sweden)

Li-Zhen Zheng

Full Text Available In this study we established a bipedal animal model of steroid-associated hip joint collapse in emus for testing potential treatment protocols to be developed for prevention of steroid-associated joint collapse in preclinical settings. Five adult male emus were treated with a steroid-associated osteonecrosis (SAON induction protocol using combination of pulsed lipopolysaccharide (LPS and methylprednisolone (MPS. Additional three emus were used as normal control. Post-induction, emu gait was observed, magnetic resonance imaging (MRI was performed, and blood was collected for routine examination, including testing blood coagulation and lipid metabolism. Emus were sacrificed at week 24 post-induction, bilateral femora were collected for micro-computed tomography (micro-CT and histological analysis. Asymmetric limping gait and abnormal MRI signals were found in steroid-treated emus. SAON was found in all emus with a joint collapse incidence of 70%. The percentage of neutrophils (Neut % and parameters on lipid metabolism significantly increased after induction. Micro-CT revealed structure deterioration of subchondral trabecular bone. Histomorphometry showed larger fat cell fraction and size, thinning of subchondral plate and cartilage layer, smaller osteoblast perimeter percentage and less blood vessels distributed at collapsed region in SAON group as compared with the normal controls. Scanning electron microscope (SEM showed poor mineral matrix and more osteo-lacunae outline in the collapsed region in SAON group. The combination of pulsed LPS and MPS developed in the current study was safe and effective to induce SAON and deterioration of subchondral bone in bipedal emus with subsequent femoral head collapse, a typical clinical feature observed in patients under pulsed steroid treatment. In conclusion, bipedal emus could be used as an effective preclinical experimental model to evaluate potential treatment protocols to be developed for prevention of

Alopecia associated with unexpected leakage from electron cone

Energy Technology Data Exchange (ETDEWEB)

Wen, B.C.; Pennington, E.C.; Hussey, D.H.; Jani, S.K.

1989-06-01

Excessive irradiation due to unexpected leakage was found on a patient receiving electron beam therapy. The cause of this leakage was analyzed and the amount of leakage was measured for different electron beam energies. The highest leakage occurred with a 6 x 6 cm cone using a 12 MeV electron beam. The leakage dose measured along the side of the cone could be as great as 40%. Until the cones are modified or redesigned, it is advised that all patient setups be carefully reviewed to assure that no significant patient areas are in the side scatter region.

Convolution-based estimation of organ dose in tube current modulated CT

Science.gov (United States)

Tian, Xiaoyu; Segars, W. Paul; Dixon, Robert L.; Samei, Ehsan

2016-05-01

Estimating organ dose for clinical patients requires accurate modeling of the patient anatomy and the dose field of the CT exam. The modeling of patient anatomy can be achieved using a library of representative computational phantoms (Samei et al 2014 Pediatr. Radiol. 44 460-7). The modeling of the dose field can be challenging for CT exams performed with a tube current modulation (TCM) technique. The purpose of this work was to effectively model the dose field for TCM exams using a convolution-based method. A framework was further proposed for prospective and retrospective organ dose estimation in clinical practice. The study included 60 adult patients (age range: 18-70 years, weight range: 60-180 kg). Patient-specific computational phantoms were generated based on patient CT image datasets. A previously validated Monte Carlo simulation program was used to model a clinical CT scanner (SOMATOM Definition Flash, Siemens Healthcare, Forchheim, Germany). A practical strategy was developed to achieve real-time organ dose estimation for a given clinical patient. CTDIvol-normalized organ dose coefficients ({{h}\\text{Organ}} ) under constant tube current were estimated and modeled as a function of patient size. Each clinical patient in the library was optimally matched to another computational phantom to obtain a representation of organ location/distribution. The patient organ distribution was convolved with a dose distribution profile to generate {{≤ft(\\text{CTD}{{\\text{I}}\\text{vol}}\\right)}\\text{organ, \\text{convolution}}} values that quantified the regional dose field for each organ. The organ dose was estimated by multiplying {{≤ft(\\text{CTD}{{\\text{I}}\\text{vol}}\\right)}\\text{organ, \\text{convolution}}} with the organ dose coefficients ({{h}\\text{Organ}} ). To validate the accuracy of this dose estimation technique, the organ dose of the original clinical patient was estimated using Monte Carlo program with TCM profiles explicitly modeled. The

Collapse Scenarios of High-Rise Buildings Using Plastic Limit Analysis

Directory of Open Access Journals (Sweden)

G. Liu

2009-01-01

Full Text Available The Twin Towers of the World Trade Center (WTC in New York, USA collapsed on 11 September, 2001. The incident is regarded as the most severe disaster for high-rise buildings in history. Investigations into the collapse scenarios are still being conducted. Possible collapse scenarios assessed by local and international experts were reported. Another possible collapse scenario of the WTC based on two hypotheses was proposed in this paper, and the idea of plastic limit analysis was applied to evaluate the approximate limit load. According to the theory analysis and numerical calculations, a conclusion can be drawn that the large fires, aroused by the terrorist attack, play a significant role on the collapse of the WTC.

Development of pits and cones on ion bombarded copper

International Nuclear Information System (INIS)

Tanovic, L.A.; Carter, G.; Nobes, M.J.; Whitton, I.L.; Williams, J.S.

1980-01-01

The formation of pits and cones on Ar ion bombarded copper has been studied. Carefully polished surfaces of large grained 99.999% pure copper crystals have been bombarded at normal incidence with 40 keV argon ions. The cone formation has been investigated for annealed and non-annealed crystals at room temperature and at 30 K and in the case of monocrystal and polycrystal samples. Although in the most other studies the presence of impurities is as a necessary condition for generation of cones and pits the obtained experimental results show that under certain conditions these features are formed on clean surfaces. It is shown that the dominant parameter in the production of cones on copper is the crystal orientation [ru

Collapse arresting in an inhomogeneous two-dimensional nonlinear Schrodinger model

DEFF Research Database (Denmark)

Schjødt-Eriksen, Jens; Gaididei, Yuri Borisovich; Christiansen, Peter Leth

2001-01-01

Collapse of (2 + 1)-dimensional beams in the inhomogeneous two-dimensional cubic nonlinear Schrodinger equation is analyzed numerically and analytically. It is shown that in the vicinity of a narrow attractive inhomogeneity, the collapse of beams that in a homogeneous medium would collapse may...

On the collapse of iron stellar cores

International Nuclear Information System (INIS)

Barkat, Z.; Rakavy, G.; Reiss, Y.; Wilson, J.R.

1975-01-01

The collapse of iron stellar cores is investigated to see whether the outward shock produced by the bounce at neutron star density is sufficient to burn appreciable amounts of the envelope around the iron core. Several models were tried, and in all cases no appreciable burn took place; hence no explosion results from the collapse of these models

The Collapse of the 'Celtic Tiger' Narrative

DEFF Research Database (Denmark)

Böss, Michael

2011-01-01

An account of the factors that led to the collapse of the 'Celtic Tiger' economy in 2008 and an explanation of the political effects and implications for Irish identity.......An account of the factors that led to the collapse of the 'Celtic Tiger' economy in 2008 and an explanation of the political effects and implications for Irish identity....

Formation of shatter cones by symmetric fracture bifurcation: Phenomenological modeling and validation

Science.gov (United States)

Kenkmann, Thomas; Hergarten, Stefan; Kuhn, Thomas; Wilk, Jakob

2016-08-01

Several models of shatter cone formation require a heterogeneity at the cone apex of high impedance mismatch to the surrounding bulk rock. This heterogeneity is the source of spherically expanding waves that interact with the planar shock front or the following release wave. While these models are capable of explaining the overall conical shape of shatter cones, they are not capable of explaining the subcone structure and the diverging and branching striations that characterize the surface of shatter cones and lead to the so-called horse-tailing effect. Here, we use the hierarchical arrangement of subcone ridges of shatter cone surfaces as key for understanding their formation. Tracing a single subcone ridge from its apex downward reveals that each ridge branches after some distance into two symmetrically equivalent subcone ridges. This pattern is repeated to form new branches. We propose that subcone ridges represent convex-curved fracture surfaces and their intersection corresponds to the bifurcation axis. The characteristic diverging striations are interpreted as the intersection lineations delimiting each subcone. Multiple symmetric crack branching is the result of rapid fracture propagation that may approach the Raleigh wave speed. We present a phenomenological model that fully constructs the shatter cone geometry to any order. The overall cone geometry including apex angle of the enveloping cone and the degree of concavity (horse-tailing) is largely governed by the convexity of the subcone ridges. Straight cones of various apical angles, constant slope, and constant bifurcation angles form if the subcone convexity is low (30°). Increasing subcone convexity leads to a stronger horse-tailing effect and the bifurcation angles increase with increasing distance from the enveloping cone apex. The model predicts possible triples of enveloping cone angle, bifurcation angle, and subcone angle. Measurements of these quantities on four shatter cones from different

Electroencephalography Based Fusion Two-Dimensional (2D-Convolution Neural Networks (CNN Model for Emotion Recognition System

Directory of Open Access Journals (Sweden)

Yea-Hoon Kwon

2018-04-01

Full Text Available The purpose of this study is to improve human emotional classification accuracy using a convolution neural networks (CNN model and to suggest an overall method to classify emotion based on multimodal data. We improved classification performance by combining electroencephalogram (EEG and galvanic skin response (GSR signals. GSR signals are preprocessed using by the zero-crossing rate. Sufficient EEG feature extraction can be obtained through CNN. Therefore, we propose a suitable CNN model for feature extraction by tuning hyper parameters in convolution filters. The EEG signal is preprocessed prior to convolution by a wavelet transform while considering time and frequency simultaneously. We use a database for emotion analysis using the physiological signals open dataset to verify the proposed process, achieving 73.4% accuracy, showing significant performance improvement over the current best practice models.

Differences in absorbed doses at risk organs and target tumoral of planning(PTV) in lung treatments using two algorithms of different calculations; Diferencias en las dosis absorbidas en organos de riesgo y volumen tumoral de planificacion (PTV) en tratamientos de pulmon usando dos algoritmos de calculo diferentes: pencil beam y collpased cone

Energy Technology Data Exchange (ETDEWEB)

Uruena Llinares, A.; Santos Rubio, A.; Luis Simon, F. J.; Sanchez Carmona, G.; Herrador Cordoba, M.

2006-07-01

The objective of this paper is to compare, in thirty treatments for lung cancer,the absorbed doses at risk organs and target volumes obtained between the two used algorithms of calculation of our treatment planning system Oncentra Masterplan, that is, Pencil Beams vs Collapsed Cone. For it we use a set of measured indicators (D1 and D99 of tumor volume, V20 of lung, homogeneity index defined as (D5-D95)/D prescribed, and others). Analysing the dta, making a descriptor analysis of the results, and applying the non parametric test of the ranks with sign of Wilcoxon we find that the use of Pencil Beam algorithm underestimates the dose in the zone of the PTV including regions of low density as well as the values of maximum dose in spine cord. So, we conclude that in those treatments in which the spine dose is near the maximum permissible limit or those in which the PTV it includes a zone with pulmonary tissue must be used the Collapse Cone algorithm systematically and in any case an analysis must become to choose between time and precision in the calculation for both algorithms. (Authors)

Review of the convolution algorithm for evaluating service integrated systems

DEFF Research Database (Denmark)

Iversen, Villy Bæk

1997-01-01

In this paper we give a review of the applicability of the convolution algorithm. By this we are able to evaluate communication networks end--to--end with e.g. BPP multi-ratetraffic models insensitive to the holding time distribution. Rearrangement, minimum allocation, and maximum allocation...

Training Convolutional Neural Networks for Translational Invariance on SAR ATR

DEFF Research Database (Denmark)

Malmgren-Hansen, David; Engholm, Rasmus; Østergaard Pedersen, Morten

2016-01-01

In this paper we present a comparison of the robustness of Convolutional Neural Networks (CNN) to other classifiers in the presence of uncertainty of the objects localization in SAR image. We present a framework for simulating simple SAR images, translating the object of interest systematically...

Direct cone beam SPECT reconstruction with camera tilt

International Nuclear Information System (INIS)

Jianying Li; Jaszczak, R.J.; Greer, K.L.; Coleman, R.E.; Zongjian Cao; Tsui, B.M.W.

1993-01-01

A filtered backprojection (FBP) algorithm is derived to perform cone beam (CB) single-photon emission computed tomography (SPECT) reconstruction with camera tilt using circular orbits. This algorithm reconstructs the tilted angle CB projection data directly by incorporating the tilt angle into it. When the tilt angle becomes zero, this algorithm reduces to that of Feldkamp. Experimentally acquired phantom studies using both a two-point source and the three-dimensional Hoffman brain phantom have been performed. The transaxial tilted cone beam brain images and profiles obtained using the new algorithm are compared with those without camera tilt. For those slices which have approximately the same distance from the detector in both tilt and non-tilt set-ups, the two transaxial reconstructions have similar profiles. The two-point source images reconstructed from this new algorithm and the tilted cone beam brain images are also compared with those reconstructed from the existing tilted cone beam algorithm. (author)

Sonographic Analysis of the Collapsed Gall Bladder

International Nuclear Information System (INIS)

Han, Sang Suk; Choi, Jae Young; Choi, Seok Jin; Eun, Chung Ki; Nam, Kyung Jin; Lee, Jeong Mi

1996-01-01

This study was done to find answers for further following questions in cases of the collapsed gallbladder (GB) : What is the probability of the presence of stone when stony echo is visible in GB area? What is the probability of the presence of stone when only acoustic shadow is visible from GB area? What are the associated GB pathologies except stone or cholecystitis in previously mentioned situations and is it possible to differentiate them? What are the underlying pathologies of GB collapse without stony echo or acoustic shadow and is it possible to differentiate them sonographic ally? What are the rate and causes of re-expansion of the collapsed GB on follow-up study? Prospective study was done in 157 cases of collapsed GB with no visible or nearly no visible bile filled lumen in recent 3 years. Sonographic analysis for GB lesions was done in 61 confirmed cases. Changing pattern of GB lumen on follow-up study and their underlying pathologies were analyzed in 28 cases. Initial sonographic examination was done with 3 or 3.5 MHz transducer. No other transducer was used in cases showing stony echo or acoustic shadow in GB area, but additional examination was done with 5 or 7-4 MHz transducer in cases without stony echo or acoustic shadow. Among 31 cases, which showed stony echo, stone was found in 30 cases and milk of calcium bile in one case. Stone was present in all of the 11 cases which showed only acoustic shadow from the collapsed GB without stony echo. GB cancer was accompanied in 2 cases among upper 42 cases, and its possibility could be suspected sonographic ally. Underlying pathologies of the 19cases without stony echo or acoustic shadow were as follows : GB stone (3), cholecystitis (6), GB cancer (1), bile plug syndrome (1), hepatitis (5), and ascites (3). And sonographic differentiation of the underlying causes for the collapse was possible in only 1 case of GB cancer. Among 28 cases of the follow-up study, 20 cases showed re-expansion of the GB lumen and

Collapse Mechanisms Of Masonry Structures

International Nuclear Information System (INIS)

Zuccaro, G.; Rauci, M.

2008-01-01

The paper outlines a possible approach to typology recognition, safety check analyses and/or damage measuring taking advantage by a multimedia tool (MEDEA), tracing a guided procedure useful for seismic safety check evaluation and post event macroseismic assessment. A list of the possible collapse mechanisms observed in the post event surveys on masonry structures and a complete abacus of the damages are provided in MEDEA. In this tool a possible combination between a set of damage typologies and each collapse mechanism is supplied in order to improve the homogeneity of the damages interpretation. On the other hand recent researches of one of the author have selected a number of possible typological vulnerability factors of masonry buildings, these are listed in the paper and combined with potential collapse mechanisms to be activated under seismic excitation. The procedure takes place from simple structural behavior models, derived from the Umbria-Marche earthquake observations, and tested after the San Giuliano di Puglia event; it provides the basis either for safety check analyses of the existing buildings or for post-event structural safety assessment and economic damage evaluation. In the paper taking advantage of MEDEA mechanisms analysis, mainly developed for the post event safety check surveyors training, a simple logic path is traced in order to approach the evaluation of the masonry building safety check. The procedure starts from the identification of the typological vulnerability factors to derive the potential collapse mechanisms and their collapse multipliers and finally addresses the simplest and cheapest strengthening techniques to reduce the original vulnerability. The procedure has been introduced in the Guide Lines of the Regione Campania for the professionals in charge of the safety check analyses and the buildings strengthening in application of the national mitigation campaign introduced by the Ordinance of the Central Government n. 3362

Bright and durable field emission source derived from refractory taylor cones

Science.gov (United States)

Hirsch, Gregory

2016-12-20

A method of producing field emitters having improved brightness and durability relying on the creation of a liquid Taylor cone from electrically conductive materials having high melting points. The method calls for melting the end of a wire substrate with a focused laser beam, while imposing a high positive potential on the material. The resulting molten Taylor cone is subsequently rapidly quenched by cessation of the laser power. Rapid quenching is facilitated in large part by radiative cooling, resulting in structures having characteristics closely matching that of the original liquid Taylor cone. Frozen Taylor cones thus obtained yield desirable tip end forms for field emission sources in electron beam applications. Regeneration of the frozen Taylor cones in-situ is readily accomplished by repeating the initial formation procedures. The high temperature liquid Taylor cones can also be employed as bright ion sources with chemical elements previously considered impractical to implement.

Method for assessing the probability of accumulated doses from an intermittent source using the convolution technique

International Nuclear Information System (INIS)

Coleman, J.H.

1980-10-01

A technique is discussed for computing the probability distribution of the accumulated dose received by an arbitrary receptor resulting from several single releases from an intermittent source. The probability density of the accumulated dose is the convolution of the probability densities of doses from the intermittent releases. Emissions are not assumed to be constant over the brief release period. The fast fourier transform is used in the calculation of the convolution

Collapse above the world's largest potash mine (Ural, Russia.

Directory of Open Access Journals (Sweden)

Andrejchuk Vjacheslav

2002-01-01

Full Text Available This paper reports the results of the study of a huge collapse that occurred in June 1986 within the area of the 3rd Berezniki potash mine (the Verkhnekamsky potash deposit, Ural. Processes that took place between the first appearance of a water inflow through the mine roof and the eventual collapse are reconstructed in detail. The origin and development of a cavity that induced the collapse are revealed. Two factors played a major role in the formation of the collapse: the presence of a tectonic fold/rupture zone with in both the salt sequence and the overburden (the zone of crush and enhanced permeability, and the ductile pillars mining system.

Cone pigments in a North American marsupial, the opossum (Didelphis virginiana).

Science.gov (United States)

Jacobs, Gerald H; Williams, Gary A

2010-05-01

Only two of the four cone opsin gene families found in vertebrates are represented in contemporary eutherian and marsupial species. Recent genetic studies of two species of South American marsupial detected the presence of representatives from two of the classes of cone opsin genes and the structures of these genes predicted cone pigments with respective peaks in the ultraviolet and long-wavelength portions of the spectrum. The Virginia opossum (Didelphis virginiana), a profoundly nocturnal animal, is the only marsupial species found in North America. The prospects for cone-based vision in this species were examined through recordings of the electroretinogram (ERG), a commonly examined retinal response to photic stimulation. Recorded under flickering-light conditions that elicit signals from cone photoreceptors, the spectral sensitivity of the opossum eye is well accounted for by contributions from the presence of a single cone pigment having peak absorption at 561-562 nm. A series of additional experiments that employed various chromatic adaptation paradigms were conducted in a search for possible contributions from a second (short-wavelength sensitive) cone pigment. We found no evidence that such a mechanism contributes to the ERG in this marsupial.

Inertial collapse of bubble pairs near a solid surface

Science.gov (United States)

Alahyari Beig, Shahaboddin; Johnsen, Eric

2017-11-01

Cavitation occurs in a variety of applications ranging from naval structures to biomedical ultrasound. One important consequence is structural damage to neighboring surfaces following repeated inertial collapse of vapor bubbles. Although the mechanical loading produced by the collapse of a single bubble has been widely investigated, less is known about the detailed dynamics of the collapse of multiple bubbles. In such a problem, the bubble-bubble interactions typically affect the dynamics, e.g., by increasing the non-sphericity of the bubbles and amplifying/hindering the collapse intensity depending on the flow parameters. Here, we quantify the effects of bubble-bubble interactions on the bubble dynamics, as well as the pressures/temperatures produced by the collapse of a pair of gas bubbles near a rigid surface. We perform high-resolution simulations of this problem by solving the three-dimensional compressible Navier-Stokes equations for gas/liquid flows. The results are used to investigate the non-spherical bubble dynamics and characterize the pressure and temperature fields based on the relevant parameters entering the problem: stand-off distance, geometrical configuration (angle, relative size, distance), collapse strength. This research was supported in part by ONR Grant N00014-12-1-0751 and NSF Grant CBET 1253157.

The Collapse of Ecosystem Engineer Populations

Directory of Open Access Journals (Sweden)

José F. Fontanari

2018-01-01

Full Text Available Humans are the ultimate ecosystem engineers who have profoundly transformed the world’s landscapes in order to enhance their survival. Somewhat paradoxically, however, sometimes the unforeseen effect of this ecosystem engineering is the very collapse of the population it intended to protect. Here we use a spatial version of a standard population dynamics model of ecosystem engineers to study the colonization of unexplored virgin territories by a small settlement of engineers. We find that during the expansion phase the population density reaches values much higher than those the environment can support in the equilibrium situation. When the colonization front reaches the boundary of the available space, the population density plunges sharply and attains its equilibrium value. The collapse takes place without warning and happens just after the population reaches its peak number. We conclude that overpopulation and the consequent collapse of an expanding population of ecosystem engineers is a natural consequence of the nonlinear feedback between the population and environment variables.

Instantaneous interactions of hadrons on the light cone

International Nuclear Information System (INIS)

Hyer, T.

1994-01-01

Hadron wave functions are most naturally defined in the framework of light-cone quantization, a Hamiltonian formulation quantized at equal light-cone ''time'' τ≡t+z. One feature of the light-cone perturbation theory is the presence of instantaneous interactions, which complicate the consideration of processes involving bound states. We show that these interactions can be written in a simple and general form, parametrized by an instantaneous contribution ψ to the hadronic wave function. We use the rotational invariance of Feynman diagrams to relate this instantaneous piece of the meson wave function to the propagating part, and to obtain constraints relating wave functions and quark fragmentation amplitudes

Learning Convolutional Text Representations for Visual Question Answering

OpenAIRE

Wang, Zhengyang; Ji, Shuiwang

2017-01-01

Visual question answering is a recently proposed artificial intelligence task that requires a deep understanding of both images and texts. In deep learning, images are typically modeled through convolutional neural networks, and texts are typically modeled through recurrent neural networks. While the requirement for modeling images is similar to traditional computer vision tasks, such as object recognition and image classification, visual question answering raises a different need for textual...

Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks

Directory of Open Access Journals (Sweden)

Haiyang Yu

2017-06-01

Full Text Available Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic speeds are converted into a series of static images and input into a novel deep architecture, namely, spatiotemporal recurrent convolutional networks (SRCNs, for traffic forecasting. The proposed SRCNs inherit the advantages of deep convolutional neural networks (DCNNs and long short-term memory (LSTM neural networks. The spatial dependencies of network-wide traffic can be captured by DCNNs, and the temporal dynamics can be learned by LSTMs. An experiment on a Beijing transportation network with 278 links demonstrates that SRCNs outperform other deep learning-based algorithms in both short-term and long-term traffic prediction.

Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks.

Science.gov (United States)

Yu, Haiyang; Wu, Zhihai; Wang, Shuqin; Wang, Yunpeng; Ma, Xiaolei

2017-06-26

Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic speeds are converted into a series of static images and input into a novel deep architecture, namely, spatiotemporal recurrent convolutional networks (SRCNs), for traffic forecasting. The proposed SRCNs inherit the advantages of deep convolutional neural networks (DCNNs) and long short-term memory (LSTM) neural networks. The spatial dependencies of network-wide traffic can be captured by DCNNs, and the temporal dynamics can be learned by LSTMs. An experiment on a Beijing transportation network with 278 links demonstrates that SRCNs outperform other deep learning-based algorithms in both short-term and long-term traffic prediction.

Transforming Musical Signals through a Genre Classifying Convolutional Neural Network

Science.gov (United States)

Geng, S.; Ren, G.; Ogihara, M.

2017-05-01

Convolutional neural networks (CNNs) have been successfully applied on both discriminative and generative modeling for music-related tasks. For a particular task, the trained CNN contains information representing the decision making or the abstracting process. One can hope to manipulate existing music based on this 'informed' network and create music with new features corresponding to the knowledge obtained by the network. In this paper, we propose a method to utilize the stored information from a CNN trained on musical genre classification task. The network was composed of three convolutional layers, and was trained to classify five-second song clips into five different genres. After training, randomly selected clips were modified by maximizing the sum of outputs from the network layers. In addition to the potential of such CNNs to produce interesting audio transformation, more information about the network and the original music could be obtained from the analysis of the generated features since these features indicate how the network 'understands' the music.

State stability analysis for the fermionic projector in the continuum

Energy Technology Data Exchange (ETDEWEB)

Hoch, Stefan Ludwig

2008-07-01

The principle of the fermionic projector in the continuum gives an indication that there might be a deeper reason why elementary particles only appear with a few definite masses. In this thesis the existence of approximately state-stable configurations is shown. In order to achieve that, we make use of a variational principle for the fermionic projector in the continuum which contains certain contributions supported on the light cone. In a certain sense, these extra terms contain the structure of the underlying discrete spacetime. Lorentz invariant distributions and their convolutions are studied. Some of these are well-defined because the convolution integrals have compactly supported integrands. Other convolutions can be regularized such that the property of being ill-defined only plays a role on the light cone. These results are used to analyze the variational principle and to give criteria for state stability, which can be numerically analyzed. Some plots are presented to allow a decision about state stability and to show how possible configurations could look like. (orig.)

State stability analysis for the fermionic projector in the continuum

International Nuclear Information System (INIS)

Hoch, Stefan Ludwig

2008-01-01

The principle of the fermionic projector in the continuum gives an indication that there might be a deeper reason why elementary particles only appear with a few definite masses. In this thesis the existence of approximately state-stable configurations is shown. In order to achieve that, we make use of a variational principle for the fermionic projector in the continuum which contains certain contributions supported on the light cone. In a certain sense, these extra terms contain the structure of the underlying discrete spacetime. Lorentz invariant distributions and their convolutions are studied. Some of these are well-defined because the convolution integrals have compactly supported integrands. Other convolutions can be regularized such that the property of being ill-defined only plays a role on the light cone. These results are used to analyze the variational principle and to give criteria for state stability, which can be numerically analyzed. Some plots are presented to allow a decision about state stability and to show how possible configurations could look like. (orig.)